Glomerulosclerosis correlates with reduction in podocyte number that occurs through mechanisms which include apoptosis. Podocyte injury or podocyte loss in the renal glomerulus has been proposed as the crucial mechanism in the development of glomerulosclerosis. However, the mechanism by which podocytes respond to injury is poorly understood. TNF and TNF receptor superfamilies are important in the pathogenesis of podocyte injury and apoptosis. The ligand of receptor activator of NF-kappaB (RANKL) and receptor activator of NF-kappaB (RANK) are members of the TNF and receptor superfamilies. We investigated whether RANK - RANKL is a receptor - ligand complex for podocytes responding to injury.in vitro after injury induced by puromycin aminonucleoside (PA). Knockdown of RANK expression by small interference RNA (siRNA) exacerbated podocyte apoptosis induced by PA. However, RANKL inhibited significantly the apoptosis of podocytes induced by PA.In this study, RANKL and RANK were examined in human podocyte diseases and a rat model of puromycin aminonucleoside nephrosis (PAN). Compared with controls, RANK and RANKL were increased in both human podocyte diseases and the rat PAN model; double immunofluorescence staining revealed that RANK protein expression was mainly attributed to podocytes. Immunoelectron microscopy showed that RANK was localized predominantly at the top of the foot process membrane and the cytoplasm of rat podocyte. In addition, RANK was upregulated in mouse podocytes These findings suggest the increase in RANK–RANKL expression is a response to podocyte injury, and RANK–RANKL may be a novel receptor–ligand complex for the survival response during podocyte injury. Podocytes are terminally differentiated cells that line the outer aspect of the glomerular basement membrane (GBM) Podocytes are injured in immune- and non-immune-mediated disease, resulting in damage to the glomerular filtration barrier. The fate of the podocyte then depends on several factors, such as reparative mechanisms and injury factors. If these are present, and/or the initial injury is halted, there may be resolution. However, if injury persists, and/or there are inadequate repair mechanisms present, proteinuria persists, leading to reduced renal function TNF and TNF receptor superfamilies are important in the pathogenesis of podocyte injury and apoptosis in vivo, we measured the expression of RANK and RANKL in the PAN rat model. PAN induced by a single injection of PA was characterized by an increase in urine protein levels at 7 days of follow-up . We found that rats with PAN had significantly increased levels of RANK protein in the kidney compared with controls , with persistently raised levels throughout the observation period , focal segmental glomerulosclerosis , IgA nephropathy (n = 14), and membranous nephropathy , and the latter three groups are with proteinuria. Confocal microscopy showed the co-localization of RANK and synaptopodin, indicating that podocytes contribute to glomerular RANK expression in podocyte injury diseases . We founRANKL is a member of the tumor necrosis factor superfamily, which is expressed by activated T-cells. To determine whether RANK upregulation resulted from a direct action in podocytes rather than from the activation of T cells, we measured the expression of RANK in SCID mice treated with lipopolysaccharide (LPS), which are devoid of T and B cells Immortalized mouse podocytes were used and differentiated by raising the cell culture temperature from 33° to 37°C in vitro RANK knockdown system to determine whether RANK was necessary for podocyte survival in vitro, we studied podocytes apoptosis before and after stable knockdown of RANK with siRNA. The knockdown of RANK alone did not induce podocytes apoptosis, but increased mildly the apoptosis of podocytes exposed to PA. However, RANKL reduced apoptosis of podocytes transfected with RANK siRNA exposed to PA compared with control siRNA  family member RANKL and its receptor RANK are important regulators of T cells Despite the importance of podocytes in renal physiology and as a target of glomerular disease Podocytes respond to injury by enacting coordinated genetic programs. These responses can modify the cell in an adaptive manner against the noxious stimuli and to promote their recovery from an injury in vitro. However, future studies will be needed to define the RANK-RANKL complex physiological and pathophysiological functions in kidney disease with gene knockout mice model in vivo.Although the expression of RANK and RANKL is induced in podocytes with PA, the underlying molecular mechanisms and signaling pathways of RANKL-RANK complex are incompletely understood. We demonstrated that RANK-RANKL complex was important for response to podocyte injury In summary, the upregulation of RANKL and RANK, in combination with the significant protective effects of RANKL, indicates that RANK is part of an adaptive, recovery response to podocyte injury. This is the first observation that RANKL, acting through RANK, functions in an injury paradigm in the kidney. These data raise the exciting therapeutic possibility of giving exogenous RANKL to patients with glomerular disease that is characterized by a loss of podocytes, such as membranous nephropathy and focal segmental glomerulosclerosis.Male Sprague-Dawley rats that weighed 110∼130 g were fed a standard diet. Rats were divided into the control and PAN groups. PAN was induced by a single intravenous injection of PA (Alexis) at 10 mg/100 g body weight, diluted in 0.9% saline SCID mice were obtained from the Jackson Laboratory. SCID mice urinary protein was analyzed by a urine dipstick before the animals were injected intraperitoneally with either 200 µg LPS This study was carried out in strict accordance with the recommendations of the Guide for the Care and Use of Laboratory Animals of Sun Yat-Sen University. All animal procedures were approved by the Animal Experiment Committee of Sun Yat-Sen University (protocol number 10100341).Diseased kidney tissues were obtained from needle biopsies of 42 patients with proteinuria. The kidney tissues were obtained with informed consent to be used for research purposes after the diagnostic workup was completed. The study’s protocol was approved by Guangdong General Hospital Ethics Committee (protocol number YY01023). Of the 42 patients with proteinuria, the pathological diagnosis included IgA nephropathy (IgAN), membranous nephropathy (MN), and focal segmental glomerular sclerosis (FSGS). Normal kidney tissues were obtained from surgical nephrectomy necessitated by the presence of renal tumors (n = 3). Podocyte foot process effacement was seen in kidney tissues from all patients with proteinuria, as demonstrated by electron microscopy. No pathological findings were observed in normal kidney tissues.An immortalized murine podocyte cell line 2 in 25 ml flasks in a culture medium composed of RPMI-1640 medium (Life Technologies) supplemented with 10% fetal bovine serum .SJRH30 cells are human rhabdomyosarcoma cell lines, which are RANK positive controls . SJRH30 cells were cultured at 37°C and 5% CORANK small interference RNA (siRNA) knockdown was performed by using transient transfection of pooled, functionally validated Cy3–labeled RANK siRNA (Invitrogen) Human and murine renal tissues were cut into 5 µm cryosections that were fixed in acetone for 10 min at −20°C, washed with phosphate-buffered saline (PBS), then treated with 0.5% Triton X-100 for 15 min, and blocked with 5% BSA for 30 min. Podocytes on coverslips were washed with PBS, then fixed with 4°C acetone and blocked with 5% BSA. For indirect immunofluorescence staining of kidney sections, cryosections were stained with antibodies against Synaptopin  overnight at 4°C. After washing, the sections were incubated in FITC-conjugated anti-IgG secondary antibody  for 60 min. The primary antibodies that were used for immunofluorescence studies also included anti-RANK antibody  and anti-RANKL antibody . RANK (H-300) is recommended for detection of RANK of mouse, rat and human origin by Western Blotting (dilution 1∶1000), immunofluorescence (dilution 1∶50). Antigen–antibody complexes were visualized with secondary antibodies  conjugated with Rhodamine. We added second antibody dilution times (1∶200), and reduced nonspecific staining. We used positive control SJRH30 cells, which were expressed RANK on the plasma membrane. Sections were viewed and imaged with confocal microscopy (Zeiss LSM510).For transmission electron microscopy, ultrathin sections (60 to 100 nm) were cut from cortical kidney tissue samples embedded in epon resin, using an ultramicrotome (Leica), collected on copper grids, and stained with uranyl acetate and lead citrate. Ultrathin sections were stained with uranyl acetate for 10 min and subsequently in Reynolds lead citrate for 2 min. Ultrastructural analysis was performed by transmission electron microscopy 15 with Superscript reverse transcriptase (Invitrogen). The housekeeping gene GAPDH was used as an internal control. To quantify the transcript copy of target genes and GAPDH in each sample, DNA plasmid standards corresponding to target genes and GAPDH were prepared and used in the real-time quantitative PCR assay. Real-time PCR was performed using the MJ Opticon II Quantitative PCR System  with the following thermal cycling profile: 95°C for 5 min, followed by 40 cycles of amplification . The absorption values of the SYBR Green I fluorescence in each tube were detected at the end of each cycle. Quantification in each sample was done by expressing the ratio of transcript copy number of target genes (RANK and RANKL) versus that of GAPDH. PCR primers for the genes of interest used in this study are shown as follows: rat RANKL (Accession NM 057149) forward: GCT CAC CTC ACC ATC AAT GCT; reverse: GGT ACC AAG AGG ACA GAC TGA CTT TA; rat GAPDH (Accession M17701)forward: CTC CCA TTC CTC CAC CTT TG; reverse: CCA CCA CCC TGT TGC TGT AG; mouse RANK (Accession BC019185) forward: GCT GGC TAC CAC TGG AAC TC; reverse: TGT GCA CAC CGT ATC CTT GT; mouse GAPDH (Accession M32599) forward: CGT GTT CCT ACC CCC AAT GT; reverse: TGT CAT CAT ACT TGG CAG GTT TCT; human RANK (Accession M32599) forward: CCC GTT GCA GCT CAA CAA G; reverse: GCA TTT GTC CGT GGA GGA A; human RANKL (Accession NM 033012) forward: ACG CAG TGA AAA CAC AGT T; reverse: TGC CTC TGG CTG GAA ACC; human GAPDH (Accession M33197) forward: AAA TTC CAT GGC ACC GTC AA; reverse: AGG GAT CTC GCT CCT GGA A.Total RNA was extracted from human renal biopsy specimens using the Qiagen RNeasy Micro kit (Qiagen) according to the manufacturer’s protocol. Total RNA was extracted from rodent renal cortex tissues using a TRIzol kit (Invitrogen) according to the manufacturer’s instructions. First-strand cDNAs were synthesized using oligo(dT)Protein expression of RANK and RANKL were determined by Western blot analysis Results are expressed as means ± SE. The difference between groups at one time point was assessed by Student’s t-test. Comparisons were made by analysis of variance using the computer software PEMS 3.1 for Windows software . Differences were considered significant if the p value was less than 0.05.


Mitochondrial DNA (mtDNA) mutations have been found in many cancers but the physiological derangements caused by such mutations have remained elusive. Prostate cancer is associated with both inherited and somatic mutations in the cytochrome c oxidase (COI) gene. We present a prostate cancer patient-derived rare heteroplasmic mutation of this gene, part of mitochondrial respiratory complex IV. Functional studies indicate that this mutation leads to the simultaneous decrease in cytochrome oxidation, increase in reactive oxygen, and increased reactive nitrogen. These data suggest that mitochondrial DNA mutations resulting in increased reactive oxygen and reactive nitrogen generation may be involved in prostate cancer biology. The mitochondrion contains the only functional DNA outside the eukaryotic cell nucleus and mutations in this genome have been linked to a vast array of human disease including pediatric neurologic disease, degenerative muscular disease, and blindness in the pediatric population and more recently to chronic diseases of adults including diabetes, Alzheimer's dementia, Parkinson's disease, cardiovascular disease, and cancer . BecauseP < 0.05) and in strong linkage disequilibrium with each other (r > 0.6) [in vitro [Prostate cancer is one example of an adult disease tightly linked to ageing for which there is evidence linking both inherited and somatic mtDNA mutations to disease . Mutatioer r > 0. [6]. MtDr > 0.6) . MtDNA cin vitro  and analin vitro . A speciin vitro . While multiple independent investigators have confirmed mtDNA mutations in prostate cancer, there is little understanding of the cell biologic and biochemical consequences of specific prostate cancer-associated mtDNA mutations. We investigated the mtDNA from a patient with prostate cancer and found a heteroplasmic missense mutation in the mitochondrial COI gene that impairs the oxidation of cytochrome c (respiratory complex IV inhibition) and increases the generation of both reactive oxygen species (ROS) and reactive nitrogen species (RNS).http://www.mitomap.org/). Full mtDNA sequencing was performed as described above using primer sets that span the full length of the mitochondrial DNA /2 [ Mice were injected subcutaneously in the neck with 3 separate 6124WT clones for a total of 29 mice and 3 separate 6124Mut clones for a total of 30 mice. 2.5 × 10dth)2]/2 . ExperimN = 61) for which the sequence has been determined. This conservation index (CI) of 95 is at the very upper end of what is observed for “adaptive mutations” (CI = 85 ± 9%) and significantly above the CI of “neutral polymorphisms” (CI = 23 ± 15%), making it highly likely to be functional in terms of mitochondrial physiology [A 60-year old patient underwent radical prostatectomy after presenting to his primary care physician with an elevated-serum-prostate-specific antigen (PSA = 5.5 ng/mL) that prompted a prostate biopsy revealing a Gleason 6 prostatic adenocarcinoma. Histopathologic examination of the radical prostatectomy specimen revealed a Gleason's score 6 (moderately differentiated-grade G2) conventional (acinar) prostatic adenocarcinoma involving ~5% of the left lobe of the prostate with negative surgical margins (pathologic stage pT2a). Follow-up of over 7 years with history, physical examinations and serum PSA determinations found the patient to be without evidence of prostate cancer recurrence. There was no family history of prostate cancer and the patient was otherwise healthy. DNA from the prostate tissue was the first specimen to be sequenced from this patient and this demonstrated a heteroplasmic point mutation at nucleotide position (np) 6124 of the mitochondrial genome. The sequencing chromatogram demonstrated approximately equal proportions of the wild type base (T) and mutant base (C) . The mutysiology , where 2In order to study the biochemical consequences of this mutation we studied reactive oxygen production and enzymatic activity of respiratory complex (RC) IV (cytochrome oxidoreductase). The COI polypeptide forms the catalytic core of this enzyme. Cytochrome oxidation was measured in mitochondria isolated from the patient's lymphoblast cell line and compared to other lymphoblast cell lines from two unrelated, individuals' lymphoblast lines, sequence proven to be wild type at the COI locus . The mutMutations in the COI polypeptide that lead to decreased RCIV activity could potentially lead to increased reactive oxygen . In orde In order to eliminate the potential confounding effects of the nuclear genome we made cytoplasmic hybrids (cybrids) that combined either pure mutant or pure wild type genomes from this patient with a stable nuclear background (143 B cells). The resultant pair of cybrids thus have the exact same nucleus (different from the patient), and the exact same mitochondrial DNA sequence except for the single base mutation at n.p. 6124. MtDNA genotypes were sequence verified in cybrids.P ≤ 0.098)  .P ≤ 0.0001) increase in DCF fluorescence (P ≤ 0.04) (P ≤ 0.00001). For comparison, NO was also measured cybrids containing 8993WT or Mut. 8993Mut cells had 1.8-fold higher NO when compared to 8993WT (P ≤ 0.0003). Finally, there were no differences in the overall levels of hydroxyl radicals and peroxynitrite anions as measured by hydroxyphenylfluorescein (HPF) (We then compared multiple wild type and mutant clones for reactive oxygen species (ROS) and reactive nitrogen species generation using flow cytometry and ROS and RNS sensitive fluorescent dyes. In order to study the cellular peroxide levels in cells that were either entirely mutant or entirely wild type at this base, cybrid cell lines were made and multiple clones assayed by DCF fluorescence. Overall, 6 individual mutant clones showed a consistent increase in peroxide levels when compared to 5 individual wildtype clones (data not shown). When averaging the relative level of fluorescence in all wildtype clones compared to mutant clones, the mutation is associated with a statistically significant (rescence . Similar ≤ 0.04) . A subst ≤ 0.04) . When trin (HPF) .In order to determine the possible source of the increased NO, we harvested RNA from the 6124WT and 6124Mut cybrids cell lines, followed by reverse transcription and PCR. There were no detectable levels of NOS1 or NOS3 observed (data not shown). However, NOS2 was demonstrated to be in both WT and Mut cell lines . The brePAPR (poly ADP ribose polymerase) cleavage was analyzed to determine if changes in cellular proliferation were in part due to changes in apoptosis. Western blot analysis of PARP cleavage demonstrates that PARP cleavage was reduced in 6124Mut cybrids compared to 6124WT .in vivo when compared to 6124WT cybrids cells (P ≤ 0.001 at day 32). The animals injected with cybrids showed no systemic symptoms in response to tumor injection or growth.  6124Mut cybrid cell lines grew faster ds cells . There wP < 0.05) and in strong linkage disequilibrium with each other (r2 > 0.6). It is therefore likely that COI gene mutations predispose individuals to the development of prostate cancer. For this reason we have sequenced the COI gene from 482 prostate cancer patients and identified missense mutations in 116 (24.1%) [The mitochondrially encoded COI gene was first implicated in cancer biology in 1998 when a somatically acquired chain termination mutation was reported in colon cancer by the Vogelstein group at Johns Hopkins . In 2005The biochemical analysis of mtDNA mutations requires that viable cells are obtained from patients with such mutations and that potentially confounding nuclear events are controlled. This is made possible by the combination of capturing clinically relevant mutations in patient lymphoblast cell lines and the subsequent formation of cybrids with a common nuclear background. The cybrid formation process has the further advantage of allowing the mutant base to be studied separately from the wild type base. This paper documents that a prostate cancer-associated COI mutation affects the normal functioning of respiratory complex (RC) IV (cytochrome oxidase) in at least two distinct ways: decreasing the rate of mitochondrial cytochrome c oxidation and increasing the rate of ROS and NO generation in intact cells. It therefore seems likely that both of these effects are a direct consequence of the mutation. As The possible tumorigenic effects of increases in ROS are well known and include (at least) an increased rate of DNA mutations and ROS-induced promitogenic signaling –22. ThesThe possible mechanism by which a decreased efficiency of oxidative phosphorylation is related to malignant transformation is less obvious. It is probably relevant to the so called “Warburg Effect” wherein tumor cells exhibit defective oxidative phosphorylation and increased glycolysis as a primary means of ATP generation . It is pThe possible tumorigenic effects of increases in RNS are also well known. Nitric oxide (NO) is generated enzymatically by synthases (NOS), which oxidize L-arginine to L-citrulline. The inducible form, iNOS, is present in a variety of cell types. Over the past 20 years iNOS expression has been associated with various human tumors including: breast, brain, lung, prostate, colorectal, and melanoma –32. NO ain vivo tumor growth. These are quintessential characteristics of the malignant phenotype. These results are concordant with other studies that demonstrate a profound effect of mtDNA mutations on tumor cell biology. In 2008 Ishikawa demonstrated that mtDNA mutations determined the metastatic potential of lung cancer cell lines independent of the characteristics of the cancer cell nucleus. Specifically, high-metastatic cell lines lost their metastatic potential when the mtDNA was replaced with mtDNA from low-metastatic cell lines and low-metastatic cell lines acquired high-metastatic capabilities when mtDNA from high metastatic lines were inserted [We have demonstrated that the T6124C (M74T) mutation was inherited in a heteroplasmic state by a patient that developed prostate cancer and that the mutation not only causes increased ROS and nitric oxide but also induces increased cellular proliferation, decreased apoptosis, and increased inserted . The metinserted .in vitro and caused increased tumor growth in vivo. These findings suggest a possible molecular substrate (mtDNA mutation) for the “Warburg effect” of anaerobic metabolism exhibited by some tumors and increased cellular reactive oxygen, a common finding in solid tumors.Mitochondrial DNA from a prostate cancer patient with an inherited-heteroplasmic-mtDNA mutation in COI, the catalytic core of mitochondrial respiratory complex IV was studied. In the laboratory, this mutation was found to simultaneously decrease the activity of the respiratory complex as measured by the rate of cytochrome c oxidation and to increase the rate of mitochondrial reactive oxygen generation. Other mutation-induced biochemical changes included increased generation of nitric oxide. Cells harboring the mutation proliferated faster


HTT gene. Importantly, the CAG repeat undergoes tissue-specific somatic instability, prevalent in brain regions that are disease targets, suggesting a potential role for somatic CAG repeat instability in modifying HD pathogenesis. Thus, understanding underlying mechanisms of somatic CAG repeat instability may lead to discoveries of novel therapeutics for HD. Investigation of the dynamics of the CAG repeat size changes over time may provide insights into the mechanisms underlying CAG repeat instability.Age at onset of Huntington's disease (HD) is largely determined by the CAG trinucleotide repeat length in the HTT CAG repeat length changes over time, we quantified somatic instability of the CAG repeat in Huntington's disease CAG knock-in mice from 2–16 months of age in liver, striatum, spleen and tail. The HTT CAG repeat in spleen and tail was very stable, but that in liver and striatum expanded over time at an average rate of one CAG per month. Interestingly, the patterns of repeat instability were different between liver and striatum. Unstable CAG repeats in liver repeatedly gained similar sizes of additional CAG repeats (approximately two CAGs per month), maintaining a distinct population of unstable repeats. In contrast, unstable CAG repeats in striatum gained additional repeats with different sizes resulting in broadly distributed unstable CAG repeats. Expanded CAG repeats in the liver were highly enriched in polyploid hepatocytes, suggesting that the pattern of liver instability may reflect the restriction of the unstable repeats to a unique cell type.To understand how the Our results are consistent with repeat expansion occurring as a consequence of recurrent small repeat insertions that differ in different tissues. Investigation of the specific mechanisms that underlie liver and striatal instability will contribute to our understanding of the relationship between instability and disease and the means to intervene in this process. HTT gene over 35 repeats causes HD Hdh CAG knock-in mice), striatum and liver show the greatest levels of repeat expansion Huntington's disease (HD) is a dominantly inherited neurodegenerative disease, presenting symptoms such as involuntary movements, cognitive decline and psychiatric disturbances HTT CAG repeat instability is its accumulation over time HTT CAG repeat instability over an extensive period of time have not previously been quantified. We recently developed a method for quantifying instability from GeneMapper traces that can be used in various research applications Hdh CAG knock-in mice at various time points to determine how the HTT CAG repeat length changes over time.Another important characteristic of somatic Q111Hdh CAG knock-in mice  at various time points  to quantify HTT CAG repeat instability. Similar to HD patients, these mice exhibit expansion-biased, time-dependent and tissue-specific HTT CAG repeat instability Q111Hdh CAG repeats in spleen and tail were very stable, maintaining the patterns observed at 2 months at later time points. In contrast, the Q111Hdh CAG repeats in liver and striatum showed repeat instability at 5 months with levels of instability increasing over time. Interestingly, the pattern of repeat instability in liver differed from that of striatum. In liver, the population of unstable repeats remained distinct until 16 months, broadening slightly over time. In contrast, the shape of the initial distinctive population of unstable repeats in striatum broadened to a much greater degree over time, becoming diffuse at 16 months.We extracted genomic DNA from two unstable tissues (liver and striatum) and two stable tissues (spleen and tail) from Hdh CAG knock-in mice with 48 CAG repeats Next, we quantified the levels of repeat instability using a recently developed method −6). This suggested that once CAG repeats in liver expand the same population of repeats gains approximately 2 CAG units per month repeatedly. In striatum, the bimodal distribution of repeats was much less obvious with the population of unstable repeats being more widely distributed. To capture this characteristic pattern of repeat instability in striatum, we measured the distance between the constitutive repeat mode and the longest repeat after background correction −16) and liver . However, striatum showed a significantly increased rate of change in distance compared to that of liver , implying that units of additional CAG repeats obtained by striatum are more broadly distributed and more dynamic than those in liver.It is also interesting to note that liver and striatum showed similar instability indices and that the rates of instability index increase were not significantly different from each other  even though the patterns of repeat instability in these tissues were quite different . As the HTT CAG repeat is unstable in both neurons and glia with neurons showing more instability than glia HTT CAG instability in liver has not previously been investigated, and therefore we examined whether the defined population of unstable repeats in liver might be enriched in a specific cell-type. To test this we isolated hepatocytes from an Q111Hdh/+ mouse and measured HTT CAG repeat lengths in comparison to whole liver. Interestingly, the unstable repeats were considerably enriched relative to the stable repeats in the isolated hepatocyte preparation  or 8N octaploid (mononucleated or binucleated) ectively , and morpulation . Interespulation . Due to pulation , obtainipulation . These rpulation . In addipulation ; 25∶75 rpulation . Thus, wHTT CAG repeat instability in tissues at multiple time points, we show that repeat instability in liver and striatum of Q111Hdh mice increases over time, supporting published qualitative data indicating that repeat expansion is a recurring process Q111Hdh CAG repeats in liver and striatum expand continuously, with similar overall levels of repeat expansions in these tissues; on average 1 CAG unit increase per month. However, the distributions of unstable repeats in these tissues are different. The unstable repeats in liver gain similar sizes of additional repeats over time (approximately 2 CAG units per month), maintaining a well-defined population of unstable repeats. In contrast, the unstable repeat population in striatum gains broadly distributed sizes of additional repeats, and the longest repeat lengthens at a rate of approximately 3.5 CAG units per month per cell resulting in a less defined population of expanded repeats. While this is the simplest interpretation of the data, given the nature of our cross-sectional study in which instability is examined at 3–4 month intervals, it is also plausible that CAG increases of greater magnitude could occur less frequently. A denser cross-sectional time-course, or ideally a longitudinal analysis that may be feasible in liver, would allow greater resolution of the repeat length changes that occur over time.By quantifying In contrast to the continuous expansions of unstable repeats, we did not observe any significant shift or migration of the constitutive repeat over time in liver or striatum (data not shown). While analysis of GeneMapper traces does not readily permit quantification of the relative levels of constitutive versus somatically expanded repeat lengths, these data are consistent with the presence of stable and unstable populations of repeats in both liver and striatum at 16 months of age.HTT CAG repeat instability Notably, consistent with a number of studies in HD mice Hdh CAG knock-in mice bearing repeat lengths from 48 to 109 repeats The increases in instability index in liver and striatum that we observed appeared to be linear over the relatively narrow range of constitutive repeat lengths of 96–109 CAGs, suggesting that within this repeat length range the gain of additional CAG repeats does not dramatically accelerate the rate of repeat instability within a relatively short period of time. However, it may be still possible to see accelerated rates of repeat expansion if instability were measured at later time points in these mice. In HD patients, where the repeat can expand over decades from ∼40 CAGs to hundreds of CAGs solely with the polylpoid hepatocytes, however our data indicate that 2N hepatocytes do contain stable repeats, suggesting that the polyploid cells reflect a state that is permissive to repeat expansion. These data support previous findings in a mouse model of Myotonic Dystrophy Type 1 (DM1) in which expanded DM1 CTG alleles were associated with polyploid hepatocytes The phenomenon of similar overall repeat instabilities with different patterns of unstable repeats in liver and striatum is quite intriguing. Migration of the unstable repeats to the right in the liver, whilst maintaining a similar distribution about the mode, supports the notion that similar sizes of repeats are successively added in liver. In contrast, striatum showed a distinct population of unstable repeats initially, but the shape of the unstable repeat population became broader as the mice aged, generating a distribution of unstable repeats that resembled a uniform distribution at 16 months. We determined that the unstable repeats are highly enriched in polyploid hepatocytes, suggesting that the relatively tight distribution of unstable repeats in the liver may be due to their occurrence in a unique cell population. We were not able to determine unequivocally whether the unstable alleles were associated cis sequences or CAG repeat length may account for the difference, as discussed above. Notably, we have observed a bimodal distribution of repeat lengths in Q111Hdh/+ mice in five genetic backgrounds - CD1, C57BL/6J, C57BL/6N, FVB/N, 129S2/SvPasCrlf  Q111Hdh/+ mice on FVB/N Q111Hdh/+ mice on C57BL/6J, C57BL/6N and 129S2/SvPasCrlf backgrounds Q111Hdh C57BL/6N congenic line HTT CAG repeat-specific primers as previously described Each step of the experimental procedure  was performed at a same time for a given time point. Genomic DNA (300 ng), isolated from mouse tissues , was used for PCR amplification using et al.2 and 0.025% (w/v) collagenase IV (Gibco). Following dissection of the liver, cells were gently filtered through a 70 µm nylon cell strainer . Hepatocyte enrichment was performed by three sequential washes with DMEM complete media  in combination with low speed centrifugation at 500 rpm for five minutes. The cells were subsequently fixed in 70% ethanol overnight at −20°C. Following a wash with PBS, the cells were stained in PBS containing 20 µg/ml propidium iodide and 1 mg/ml RNase, for 15 minutes at room temperature. Finally, hepatocytes were FACS sorted into 2N, 4N and 8N populations using a BD 5 laser SORP FACS Vantage SE Diva system (MGH Flow Cytometry Core facility). Cytological analysis of FACS sorted cells (approximately 100 cells) was performed by standard hematoxylin and eosin (H&E) staining.Hepatocytes were isolated from liver as previously described by van den Broek To test whether age, constitutive CAG repeat length, or their interaction contributed to the instability index, multiple regression models were fitted to data for each tissue. All variables were centered around the corresponding mean value. All statistical analysis was done using R .Figure S1FACS analysis of mouse hepatocytes based on DNA content. Hepatocytes isolated from a 9 month old Q111/+Hdh mouse  were fixed, stained with propidium iodide and FACS sorted based on DNA content into 2N, 4N and 8N hepatocyte pools. (A) FACS light scatter plot representing the population of cells selected based on size and granularity, as indicated by purple box. (B) Selected cells were further gated by propidium iodide signal. The purple box represents the final population of cells that was FACS sorted according to nuclear content, which contained 100% hepatocytes judged by morphology of cells (H&E staining).(PDF)Click here for additional data file.Figure S2Assessment of the extent to which the unstable repeats detected in the 2N hepatocytes pool is due to contamination from 4N cells. (A) In order to calculate the levels of polyploidy contamination in 2N hepatocytes pool, we hypothesized that binucleated cells in the 2N pool are contamination from binucleated 4N cells. All calculations were based on 100 cells. FACS sorted cells were examined by H&E staining for cell morphology and nuclearity  To assess whether the signal from the expanded repeats in 2N pool (top panel) might arise from unstable alleles present in contaminating polyploid hepatocytes we conducted a mixing experiment whereby we mixed DNA from tail (containing only stable repeats) with DNA from 8N cells  in various proportions (bottom panels). Based on the traces obtained with proportions of 50∶50 & 25∶75 stable∶unstable repeats, and our calculation of 60% contaminating DNA, it appears that the majority of the unstable repeats in the 2N pool GeneMapper trace is likely to arise from unstable repeats that originate in contaminating polyploid hepatocytes.clearity , and all(PDF)Click here for additional data file.Figure S3Graphical illustration of age-dependent instability in liver and striatum. To illustrate age-dependent repeat instability in liver and striatum, outlines of representative GeneMapper traces were drawn. (A) We propose that unstable repeats in liver recurrently gain similar sizes of additional repeats, resulting in migration of the unstable repeat population to the right as the mice age. (B) In contrast, we propose that unstable repeats in striatum gain different sizes of additional repeats, leading to broadening of the initial distinctive unstable repeat population. Arrow represents the constitutive repeat.(PDF)Click here for additional data file.Figure S4Q111/+Hdh mice on different genetic backgrounds show qualitatively similar bimodal distributions of repeats in liver. GeneMapper traces of PCR-amplified HTT CAG repeat from liver DNA of Q111Hdh/+ mice with different genetic backgrounds . Mice are congenic on these backgrounds as determined by SNP typing. Constitutive CAG repeat numbers and ages of the mice are shown on top of each panel.(PDF)Click here for additional data file.Table S1Mice used in this study.(DOC)Click here for additional data file.


Experimental evidence suggests that random, spontaneous (stochastic) fluctuations in gene expression have important biological consequences, including determination of cell fate and phenotypic variation within isogenic populations. We propose that fluctuations in gene expression represent a valuable tool to explore therapeutic strategies for patients who have suffered traumatic brain injury (TBI), for which there is no effective drug therapy. We have studied the effects of TBI on the hippocampus because TBI survivors commonly suffer cognitive problems that are associated with hippocampal damage. In our previous studies we separated dying and surviving hippocampal neurons by laser capture microdissection and observed unexplainable variations in post-TBI gene expression, even though dying and surviving neurons were adjacent and morphologically identical. We hypothesized that, in hippocampal neurons that subsequently are subjected to TBI, randomly increased pre-TBI expression of genes that are associated with neuroprotection predisposes neurons to survival; conversely, randomly decreased expression of these genes predisposes neurons to death. Thus, to identify genes that are associated with endogenous neuroprotection, we performed a comparative, high-resolution transcriptome analysis of dying and surviving hippocampal neurons in rats subjected to TBI. We found that surviving hippocampal neurons express a distinct molecular signature — increased expression of networks of genes that are associated with regeneration, cellular reprogramming, development, and synaptic plasticity. In dying neurons we found decreased expression of genes in those networks. Based on these data, we propose a hypothetical model in which hippocampal neuronal survival is determined by a rheostat that adds injury-induced genomic signals to expression of pro-survival genes, which pre-TBI varies randomly and spontaneously from neuron to neuron. We suggest that pharmacotherapeutic strategies that co-activate multiple survival signals and enhance self-repair mechanisms have the potential to shift the cell survival rheostat to favor survival and therefore improve functional outcome after TBI. After traumatic brain injury (TBI), long-term cognitive disability is associated with injury-induced neurodegeneration in the hippocampus, a region in the medial temporal lobe that is critical to learning, memory and executive function Based on our observation that hippocampal neurons that survive after TBI express significantly higher levels of neuroprotective genes than adjacent dying neurons In vitro reprogramming to induce pluripotent cells is a stochastic process that can be enhanced to increase the chances of reprogramming We speculated that differential neuronal vulnerability in morphologically identical neurons could result from stochasticity in gene and protein expression – unexplained fluctuations in transcription and translation of genes in individual neurons. Depending on the cellular context, stochastic fluctuations in gene expression can be beneficial or harmful and are postulated to be the underlying mechanism of phenotypic variation in genetically identical organisms Therefore, we reasoned that we could identify endogenous survival signals by studying the transcriptome of neurons that are able to mount a protective response sufficient to survive an injury that leads to the death of adjacent neurons. We identified dying neurons by Fluoro-Jade staining. Although Fluoro-Jade does not distinguish between apoptotic and necrotic cell death, all types of degenerating neurons can be detected by this stain In this study we tested the hypothesis that random fluctuation in expression of protective genes, essential for survival, would determine the fate of individual neurons when exposed to TBI. Thus, we predicted that high levels of genes involved in the brain's intrinsic survival and repair functions, would be associated with surviving neurons. We further hypothesized that differential vulnerability to TBI in a homogeneous population of hippocampal neurons reflects a cell-survival rheostat that integrates injury-induced gene expression with stochastically elevated pre-injury expression of survival-associated genes. To test this hypothesis, we directly compared the transcriptomes of dying and surviving hippocampal neurons 24 h after experimental TBI to identify differences between these two groups of neurons that could explain their differential survival.in vivo brain injury studies, one solution is to perform gene expression analysis of pure populations of identified neurons obtained by laser capture microdissection (LCM). Previously, in our clinically relevant rat model of moderate fluid percussion TBI Interpretation of gene expression studies of brain injury in animal models is confounded by the brain's complexity-the mammalian brain contains 2500–5000 different cell types We first analyzed gene expression in a small pool (10 cells) of dying and surviving hippocampal neurons 24 hours after TBI. We had previously determined empirically that quantities of total RNA isolated from smaller pools  were so variable that in many cases we could not reliably detect expression of even moderate to highly expressed genes by real-time PCR but the majority of genes that are known to be expressed in low (less than 10 copies/cell) or higher copy numbers are detectable in 10 cell samples. Based on results from our previous studies In all, two observations emerge from these results. First, the variability and lack of significant differences between dying and surviving neurons suggests that random noise in gene expression in a small (10 cells) pool of neurons may obscure the global effects of TBI which have been documented using larger pools of neurons. Second, the significant increases in both variability and magnitude of gene expression changes in surviving neurons versus naïve neurons suggest that surviving cells, despite being “uninjured”, nonetheless responded at a genomic level to TBI as reflected in the expression of injury-induced genes. Because in the small sampling size of 10 neurons, as reported here, the weight of the single cell on the group is higher than when assessing a larger group of cells, these observations strongly suggest that gene expression is a stochastic process at the single cell level and support our hypothesis that stochastic fluctuations in pre-injury gene expression play an important role in determining cell death or survival after TBI.Based on these data we speculate that a cell that has high expression of genes associated with cell survival would survive after TBI, while a cell that has low expression of the same genes will die because it is more vulnerable to the effects of deleterious injury-induced genes. Moreover, we would predict that by increasing the sampling size, the probability of finding cells that have high expression of genes associated with survival is higher in surviving neurons versus dying neurons.To gain support for our hypothesis, we compared the whole-genome transcriptional profile of approximately 600 dying and 600 surviving hippocampal neurons after TBI. Since our objective is to understand the brain's own protective responses to injury, we decided to focus only on comparison of the two groups, dying and surviving neurons from injured rats with particular emphasis on survival and regenerative signals found in surviving neurons.For whole-genome profiling, we laser microdissected individual pyramidal neurons from the hippocampal CA3 subfield of frozen brain sections stained with Fluoro-Jade. All Fluoro-Jade-positive neurons were presumed to be injured and dying; adjacent Fluoro-Jade-negative neurons were presumed to be uninjured and surviving. RNA samples from separate pools of Fluoro-Jade-positive and Fluoro-Jade-negative CA3 pyramidal neurons were screened for integrity and quantity. The quality of total RNA from pooled hippocampal RNA samples was assessed using the ultrasensitive Agilent Bioanalyzer Pico Chip assay . The quaHierarchical clustering analysis confirmed that gene expression in biological replicate samples of dying neurons was concordant as was gene expression in replicates of surviving neurons; however, gene expression profiles of dying and surviving neurons were strikingly distinct . The 2,1We observed a strong and expected correlation between the histopathology (dying or surviving neurons) and the transcriptional profiles , S7, S8,Ingenuity pathway analysis distinguished seven prominently defined groups of interacting genes with common features that included similar biological functions , S7, S8.We were not surprised to find high expression of cell cycle regulatory genes  in dying neurons. Increased expression of cell cycle genes in post-mitotic neurons is associated with apoptosis We also found that cell death-associated genes that were highly upregulated in dying neurons have pleiotropic pro-survival functions associated with development, neuronal remodeling and memory. For instance, the cell division cycle 42 (CDC42) gene is implicated in apoptosis but also regulates cytoskeletal dynamics and neuronal remodeling Consistent with previous reports, surviving hippocampal neurons expressed high levels of numerous genes associated with neural plasticity and regenerative processes such as BDNF, NTF5 and CREB. Increases in neurotrophin levels after TBI have long been associated with neuronal survival Clearly, one way that the brain deals with the pathological consequences of brain trauma is to reset gene expression to an earlier, embryological state at a time when developing cells were more plastic. This is a common theme that is found in other regenerating tissues; for example, mechanisms of bone repair in adults closely resemble bone formation during embryogenesis Also consistent with our results, a recent study of recovery after stroke found that increased plasticity in surviving neurons allows previously hard-wired neurons to adopt wider functional roles to compensate for loss of stroke-damaged neurons A review of the evolution of regeneration in the CNS found that regeneration in diverse organisms recapitulates the paths taken during early embryonic CNS development, suggesting that successful regeneration and repair is facilitated by a regeneration-competent environment Importantly, evidence of increased expression both of genes that promote neuronal survival and those that contribute to embryological development, suggest additional therapeutic targets to improve recovery after injury. For example, Andrews et al. recently showed that functional recovery of the adult CNS was improved after nerve injury by re-expression of α9 integrin, a gene that induces neurite outgrowth during embryogenesis and is subsequently developmentally downregulated Surviving neurons expressed high levels of genes that coordinate cellular pathways critical to maintenance of cell homeostasis , anti-inflammatory responses and mitochondrial function . Increased expression of genes associated with regulation of cellular and neuroanatomical plasticity in surviving neurons is a clear indication that the activation of these homeostatic processes is crucial to the brain's self repair mechanisms. Examination of the gene networks associated with these regulatory genes suggest that they regulate a coordinated response to injury , maintain ionic and membrane homeostasis and key metabolic functions, all of which influence cell survival.in silico verification that correlated gene expression data with cell fate gave us confidence in the biological relevance of our array data , probably relating both to baseline, pre-injury gene expression and gene expression induced by TBI. This molecular signature is associated with cellular reprogramming processes that lead to regeneration, cell growth and plasticity.In other complex human disorders such as common neuropsychiatric phenotypes Korsmeyer et al. A cellular rheostat appears to be an essential element of ischemic preconditioning (IP), which stimulates fundamental genomic reprogramming that promotes cytoprotection and survival Molecular rheostats are ubiquitous and central to transcriptional regulation Interestingly, treatments that coordinately upregulate or downregulate key cell signals appear to modulate the cell-survival rheostat. For example, the anti-aging intervention, caloric restriction (CR), appears to shift metabolic rheostats that increase antioxidant defenses If cell survival is an emergent property of complex cell signaling networks, then polygenic therapeutic strategies may be necessary to effectively shift the neuronal death rheostat, rather than strategies targeting individual genes. In neurons that survive TBI, increased expression of genes associated with neuronal development suggests that therapeutic strategies could target networks of genes associated with development and cellular reprogramming. Indeed, our study reflects the recent observation that clinical management could be linked to molecular biology by identifying core subnetworks associated with diseases. Therapeutic strategies could be designed to influence the net output of these molecular rheostats In terms of prompt application of these concepts to therapy of TBI patients, several drugs that are used clinically for other purposes have the potential to alter the cell survival rheostat, perhaps by influencing the expression of gatekeeper genes that act on other genes involved in cell survival. Several therapies are currently used to treat the common sequelae of TBI, such as depression, anxiety and cognitive dysfunction. Some of the drugs used to modify these disorders activate pro-survival genes. Indeed, the beneficial effects of these drugs could be interpreted as a positive effect on the cell survival rheostat. Donepezil (Aricept) appears to improve cognition in TBI and Alzheimer's Disease patients, in part, by influencing CREB expression and CREB-mediated enhancement of neurogenesis Several drugs used for non-neurologic disorders also exert pleiotropic effects. Rapamycin, which inhibits microglial activation, was neuroprotective in TBI models Increasingly, it is accepted that understanding the function and regulation of molecular networks and how they are perturbed or affected by disease is critical to understanding the complex etiology of human disorders. Our study provides only a brief snapshot of the effects of TBI on some cell signaling networks that are involved in cell survival or cell death but our data supports our conclusion that cell fate after TBI is not only an emergent property of multiple interacting cell-survival signals but that stochastic variations in cell survival signals that exist pre-injury may influence cell fate. Although this idea is not novel, our hypothesis that cell fate is determined by the integration of injury-induced gene expression with pre-injury stochastic expression of cell death and cell survival genes in neurons subjected to brain trauma has not hitherto been considered in studies of TBI. Thus, we suggest that therapeutic interventions that mobilize multiple, endogenous regenerative cell signaling networks have the potential to significantly improve treatment and functional recovery in TBI patients. Moreover, if stochastic fluctuations in pre-injury expression of pro-survival genes can affect cell fate, there is an important implication from this hypothesis. Not unlike a preconditioning effect, some studies have shown that consumption of omega-3 fatty acids – the components in fish oil that have proven anti-inflammatory and antioxidative properties – may improve outcome after brain injury and neurodegenerative disorders suggesting that dietary interventions could influence recovery from clinical brain injury The Institutional Animal Care and Use Committee of the University of Texas Medical Branch approved all animal procedures . Fluid percussion TBI was performed on 400–500 g male Sprague-Dawley rats as previously described 24 h post-injury, rat brains were removed, immediately frozen in dry ice and stored at −80°C until they were prepared for cryostat sectioning and laser capture. Once the hippocampal region was reached (Bregma –3.15 mm to Bregma −4.15 mm), 10 µm coronal serial sections were collected and mounted on uncoated, precleaned superfrost glass slides . The slides were kept at −20°C until sectioning was complete. Immediately after sectioning, the frozen sections were thawed at room temperature for 30 sec and fixed for 1 min with 75% ethanol, briefly rinsed in RNase-free water (1 min), stained with 1% cresyl violet (10–15 sec), rinsed in RNase-free water (30 sec×2), stained with 0.001% Fluoro-Jade (4 min), rinsed in RNase-free water (1 min×3), then dehydrated in 95% ethanol (30 sec), 100% ethanol (30 sec) and xylene (3 min×2), air-dried for 10 to 15 min in a hood, and stored desiccated for no more than 1 hr at room temperature before LCM. All solutions were prepared with RNase-free water; and the cresyl violet and the Fluoro-Jade solutions were sterile filtered just before use. Fluoro-Jade staining clearly distinguishes dying, degenerating neurons from surviving neurons in the rat brain LCM was performed using a PixCell IIe laser capture microscope with an infrared diode laser . To minimize contamination from adjacent surviving Fluoro-Jade negative hippocampal CA3 pyramidal neurons, dying, Fluoro-Jade-positive CA3 neurons from the ipsilateral (directly under the injury site) rat hippocampus were captured using the smallest laser spot size (7.5 micron) with a power setting of 75–100 mW and pulse duration of 0.45–0.85 ms, but these last two settings were adjusted, as necessary, for optimum capture of the cells. Surviving, Fluoro-Jade-negative neurons were only selected when found adjacent to dying neurons. Pools of dying and surviving neurons were captured on the thermoplastic films of separate CapSure Macro LCM Caps . The caps with captured cells were placed in 0.5 ml tubes with 100 µl lysis solution from the RNAquous-Micro RNA isolation kit  and vortexed for 15 sec immediately after capture, stored at −20°C and then vortexed for 30 sec before the RNA isolation procedure. Unless specified, individual neurons were pooled from 3–6 rat brains for microarray studies and pooled dying and surviving neurons from 6 or 7 separate rats were used for PCR confirmation studies.Dying and surviving neurons (approximately 600 neurons each) from at least three rats were pooled for each biological replicate sample during the RNA isolation procedure by running the RNA/lysis solution mixtures of multiple LCM caps sequentially through the same spin columns and total RNA was isolated using the RNAqueous-Micro kit according to the manufacturer's protocols. Following spin column purification, post-elution DNase1 treatment was performed according to protocols in the RNAqueous Micro kit to remove trace amounts of genomic DNA. The concentration and quality of total RNA was assessed using an Agilent Bioanalyzer with the RNA6000 Pico Lab Chip (Agilent Technologies). Only pooled RNA samples of high quality and sufficient quantity (>25 pg/µl) were used for Agilent array analysis. RNA preparation for real-time PCR analysis of array data and stochastic gene expression analysis was identical to that for microarray analysis except for the numbers of dying and surviving neurons used in these procedures (see below).Labeled cRNA was prepared from total RNA samples. Briefly, the Poly(A)+ RNA population within total RNA was amplified using MessageAMP II . After a second round of reverse transcription, second-strand cDNA synthesis, and purification of double-stranded cDNA, in vitro transcription was performed using T7 RNA polymerase in the presence of Biotin-11-UTP. The quantity and quality of the cRNA was assayed by spectrophotometry and on the Agilent Bioanalyzer.Biological replicate samples of dying and surviving hippocampal neuron total RNA were labeled and hybridized in duplicate to Agilent whole-genome rat arrays . 1 µg of purified cRNA was fragmented to uniform size and applied to the microarrays in hybridization buffer. Agilent Whole-Genome rat microarrays are comprised of approximately 41,000 60-mer probes designed to conserved exons across the transcripts of targeted genes. These probes represent well annotated, full length, and partial rat gene sequences from major public databases. Arrays were hybridized at 65°C for 17 hrs in a rotating incubator and washed at 37°C for 1 min. After staining with Streptavidin-Alexa555, rinsed and dried arrays were scanned with an Agilent G2565 Microarray Scanner  at 5 µm resolution. Agilent Feature Extraction software was used to process the scanned images from arrays (gridding and feature intensity extraction) and the data generated for each probe on the array was analyzed with GeneSpring GX v7.3.1 software .To compare individual gene expression values across arrays, raw data from Agilent arrays was imported into GeneSpring GX 7.3.1  and then expression of individual genes normalized to the median value of each array  as well as the median of each gene across all samples. Genes were removed for further analysis if at least one replicate sample was not above background intensity. Further filtering was performed to only include genes whose values were within 50% for biological replicate samples. The filtered gene list was queried for genes that have ratios greater than 2.0 and less than 0.5 (2-fold changes) in surviving or dying neurons relative to sham treatment. The filtered genes were uploaded into Ingenuity Pathway Analysis (IPA) software  and mapped to the functional networks available in the Ingenuity Pathway Knowledge Base. Genes displaying 5-fold or greater changes  in pathways and networks with highly significant enrichments based on P values were further analyzed.Biological function analysis showed that genes associated with behavior were significantly overrepresented. Then, the behavior gene list was used as a base and expanded using the “expand” and “explore” functions from Ingenuity, to generate a complete network of genes with 5-fold difference in expression between dying and surviving neurons. The network was then clustered into seven pathways based on proximity in the network and direction of the changes in expression.GSE16735.Microarray data is MIAME compliant and raw data has been deposited in the Gene Expression Omnibus under the accession number Quantitative real-time PCR was performed on a MX3000 multiplex Quantitative PCR System from Strategene  with Taqman reagents from Applied Biosystems . Reverse transcriptase (RT) reactions were performed with reagents from the Taqman Reverse Transcriptase Reagents kit; and the AmpliTaq Gold polymerase with Gene Amp kit was used for qPCR sequences of the probe , forwardEach PCR reaction was performed in triplicate and standard curves were performed in triplicate for each primer and probe set and every multiplexing set using 1 µl of a 1∶10 serial dilution of a 1 µg RT reaction. Standard curve points were tested with 5 points from 20 ng to 2 pg of RT per PCR reaction. Every multiplexing set has a standard curve containing at least four of the five points (detects down to 20 pg) with an efficiency of 90%–110% and an RSq value above 0.98. Every experiment contained a no-template-negative control and a no-RT-negative control. Valid controls are those in which Ct values are always at least 5 Ct values below the lowest experimental value for that specific gene. We used GAPDH as our normalizing gene for all of our PCRs. All data from the PCR was collected and analyzed using MXPro software (Stratagene).Significant differences in levels of mRNA for 27 different genes in dying and surviving neurons, as determined by quantitative real-time PCR, were assessed using the two-sample t test. Data analysis was conducted using statistical software, SAS®, Release 9.1 .Tissue was frozen in OCT mounting medium from six naïve and severe TBI brains, 10 µm sections were cut on a cryostat and mounted on superfrost clean slides. Sections from the TBI brain were stained with 0.001% Fluoro-Jade (Histo-chem) and counterstained with 1% cresyl violet and prepared for laser capture as described above. The naïve sections were stained only with 1% cresyl violet. LCM was performed as described above. 10 Fluoro-Jade-positive neurons (dying) and the adjacent 10 Fluoro-Jade-negative neurons (surviving) in the CA3 region of the hippocampus were collected from the same section in each TBI brain on separate CapSure Macro LCM Caps . Ten neurons were also collected from the same section of each naïve brain on separate Macro caps. The caps were vortexed with a 100 ul of lysis buffer and stored at −80C until RNA isolation. RNA was isolated using the RNA Aqueous kit (Ambion) and then DNase treated at 37°C to remove any traces of genomic DNA. Total RNA was reverse transcribed using the Taqman Reverse Transcriptase Reagents kit (Applied Biosystems cat# N808-0234). Real-Time PCR was performed using a MX3000P Quantitative PCR system (Stratagene) as described previously.Due to complexity in the statistical design of this experiment, expression data were analyzed in 2 folds for each gene. Dying and surviving cells of TBI brains were from adjacent areas in the same brain. Therefore, brain  was playing a roll of “block” and death/survival was fixed effect. Those data were analyzed using analysis of variance for the randomized block design. Effects of TBI on gene expression were assessed using the mean differences of surviving cells in TBI animals and normal cells from naïve animals with the two-sample t-test. Effect of TBI on variability of gene expression among animals was assessed using the variance ratio of surviving cells to naïve cells with the F test. All tests were assessed at the 0.05 level of significance. Statistical computations were carried out using statistical software, the SAS® system, release 9.1 24 h after fluid percussion injury, rats were anesthetized, transcardially perfused, and fixed with freshly prepared, ice-cold, 4% paraformaldehyde in PBS (pH 7.4). Brains were removed, postfixed in 4% paraformaldehyde 1 hr at room temperature and embedded in 20% sucrose solution in PBS overnight at 4°C. Brains were frozen in O.C.T. embedding medium , 16 µm thick frozen serial sections were cut on a cryostat , placed on precleaned superfrost plus slides , and stored at −80°C until needed. Frozen sections were allowed to equilibrate to room temperature and then incubated in NAOH+80% Ethanol for 5 min. Sections were then rinsed in 70% ethanol for 2 min, rinsed in de-ionized water for 2 min, incubated in 0.06% potassium permanganate for 3 min and rinsed in de-ionized water for 2 min. Sections were then blocked and permeabilized in 3% BSA with 0.3% Trition X-100 in PBS at room temperature for 30 min and then incubated in primary antibody diluted in PBS overnight at 4°C. Sections were rinsed for 5 min in PBS, and then incubated in ALEXA-conjugated secondary antibody diluted in PBS for 1 hr at room temperature . The sections were then rinsed once in PBS for 5 min and incubated in 0.0001% Fluoro-Jade C+0.1% acetic acid for 10 min . Sections were rinsed 3 times 1 min in water, dehydrated in xylene for 1 min and coverslipped with Permount . Staining controls were produced by omitting the primary antibodies.24 h after fluid percussion TBI, rats were anesthetized and sacrificed. Brains were removed, frozen on dry ice for 10 min and then stored at −80°C until sectioned. Frozen 10 µm thick serial sections were cut on a cryostat, placed on pre-cleaned superfrost plus slides, and stored at −80°C until needed. Prior to immunolabeling, frozen sections were allowed to equilibrate to room temperature, fixed for 15 min in ice-cold, 4% paraformaldehyde and rinsed 3 times 5 min in PBS. They were then blocked in 5% normal serum in PBS for 30 min at room temperature and incubated in primary antibody diluted in PBS overnight at 4°C. The sections were rinsed 3 times 10 min in PBS, then incubated in ALEXA-conjugated secondary antibody diluted 1∶400 in PBS for 1 hr at room temperature . The sections were rinsed twice in PBS for 10 min, rinsed in tap water for 5 min, incubated in 0.06% potassium permanganate in tap water for 1 min and rinsed in tap water for 2 min. They were incubated in 0.0001% Fluoro-Jade C+0.1% acetic acid for 10 min , rinsed 3 times, 1 min in tap water and finally mounted with acidic mounting media (0.1% acetic acid-80% glycerol). Staining controls were produced by omitting the primary antibodies.Sections were washed in dH2O three times 5 min. Sections were then fixed in either acetone or methanol for 10 min. Sections were then washed in PBS for 5 min and incubated in 0.3% hydrogen peroxide in methanol for 20 min, rinsed in water twice for 5 min and then washed in PBS for 5 min. Sections were then incubated with a blocking solution (kit from Vector Biolabs) for 1 hr and then incubated in primary antibody that was diluted in blocking solution overnight at 4°C. Sections were rinsed in PBS three times 5 min, incubated for 30 min with diluted biotinylated secondary antibody (Vector Biolabs) at room temperature, rinsed in PBS three times 5 min and then incubated with Vectastain ABC reagent at room temperature for 45 min. Sections were rinsed in PBS three times 5 min and then incubated with DAB substrate for 2–10 min. Sections were immersed in dH20 for 5 min and then counterstained with hematoxylin and dehydrated in 95% ETOH 2×10 sec, then 100% ETOH 2×10 sec, followed by xylene 2×10 sec. Sections were air dried and then mounted with Permount.Following immunohistochemistry, the sections were visualized using an Olympus BX51 microscope.Figure S1Microarray analysis.(TIF)Click here for additional data file.Figure S2Group 1.(TIF)Click here for additional data file.Figure S3Group 2.(TIF)Click here for additional data file.Figure S4Group 3.(TIF)Click here for additional data file.Figure S5Group 4.(TIF)Click here for additional data file.Figure S6Group 5.(TIF)Click here for additional data file.Figure S7Group 6.(TIF)Click here for additional data file.Figure S8Group 7.(TIF)Click here for additional data file.Table S1Gene ontology annotations of genes differentially expressed 2-fold or greater between dying and surviving neurons.(DOC)Click here for additional data file.Table S2Group 1: SNCA Homeostasis genes differentially expressed in dying and surviving neurons.(DOC)Click here for additional data file.Table S3Group 2: CD47 homeostasis differentially expressed in dying and surviving neurons.(DOC)Click here for additional data file.Table S4Group 3: BDNF, DRD4, PDCD6IP, cell death control genes differentially expressed in dying and surviving neurons.(DOC)Click here for additional data file.Table S5Group 4: BDNF and CREB genes differentially expressed in dying and surviving neurons.(DOC)Click here for additional data file.Table S6Group 5: IL1β, CASP3 immune response genes differentially expressed in dying and surviving neurons.(DOC)Click here for additional data file.Table S7Group 6: SOCS Acute Phase genes differentially expressed in dying and surviving neurons.(DOC)Click here for additional data file.Table S8Group 7: YY1 Oxidative Stress Response genes differentially expressed in dying and surviving neurons.(DOC)Click here for additional data file.Table S9Probe and primer sequences for qPCR.(DOC)Click here for additional data file.References S1Supplementary References.(DOC)Click here for additional data file.


Consistent resting brain activity patterns have been repeatedly demonstrated using measures derived from resting BOLD fMRI data. While those metrics are presumed to reflect underlying spontaneous brain activity (SBA), it is challenging to prove that association because resting BOLD fMRI metrics are purely model-free and scale-free variables. Cerebral blood flow (CBF) is typically closely coupled to brain metabolism and is used as a surrogate marker for quantifying regional brain function, including resting function. Assessing the correlations between resting BOLD fMRI measures and CBF correlation should provide a means of linking of those measures to the underlying SBA, and a means to quantify those scale-free measures. The purpose of this paper was to examine the CBF correlations of 3 widely used neuroimaging-based SBA measures, including seed-region based functional connectivity (FC), regional homogeneity (ReHo), and amplitude of low frequency fluctuation (ALFF). Test-retest data were acquired to check the stability of potential correlations across time. Reproducible posterior cingulate cortex (PCC) FC vs regional CBF correlations were found in much of the default mode network and visual cortex. Dorsal anterior cingulate cortex (ACC) FC vs CBF correlations were consistently found in bilateral prefrontal cortex. Both ReHo and ALFF were found to be reliably correlated with CBF in most of brain cortex. None of the assessed SBA measures was correlated with whole brain mean CBF. These findings suggest that resting BOLD fMRI-derived measures are coupled with regional CBF and are therefore linked to regional SBA. The human brain consumes about 20% of the body's energy Cerebral blood flow (CBF) is closely coupled with brain metabolism Using ASL MRI, our group have demonstrated that brain regions within the default mode network have higher resting CBF than other places In this study, we acquired repeat resting ASL data and resting BOLD data from the same cohort of normal subjects to assess the potential SBA-CBF correlations and their test-retest stability. Part of this work has been presented in a conference The resting BOLD fMRI data have been used in a recent publication 2, matrix = 64×64×12, slice thickness = 7 mm, inter-slice space = 2.35 mm, labeling time = 2 s, post label delay time = 1 sec, bandwidth = 3 kHz/pixel, flip angle = 90°. 50 label/control image pairs were acquired for each subject. Gradient-echo echo-planar imaging sequence was used for BOLD fMRI data acquisition with parameters of: TR = 3 s, TE = 30 ms, FOV = 220×220 mm2, matrix = 64×64, 40 interleaved slices with thickness = 3 mm, 220 images. Participants were asked to lie still in the scanner at rest, keep their eyes open, and think about nothing.MR imaging was conducted in a 3-T whole-body scanner . Each session contained an anatomical scan, a resting ASL scan, and a resting BOLD fMRI scan. High-resolution structural images were acquired for spatial brain normalization using a 3D MPRAGE sequence (TR/TE/TI = 1620/3/950 ms). ASL imaging utilized an amplitude modulated continuous ASL (CASL) perfusion imaging sequence optimized for 3.0 T The following data processing was used for both sessions of BOLD data and ASL data.http://www.fil.ion.ucl.ac.uk/spm) based batch scripts All BOLD resting data preprocessing was performed using SPM8  were defined in the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) using the Pickatlas utility The Kendall's coefficient concordance  Each voxel's BOLD time series was transformed into the frequency domain using MATLAB  and the mean amplitude of the spectrum over the frequency range of 0.01–0.08 Hz was calculated as the ALFF Across-subjects average CBF, ReHo and ALFF maps were calculated to illustrate the spatial distribution patterns of each measure. Each subject's CBF, ReHo and ALFF images were divided by the whole brain mean of each type of maps to generate relative maps of each metric. For each of the 3 relative maps , a one sample t-test was performed at each voxel to assess whether the across subject mean is significantly different from 1 or not. The positive t-map and negative t-map were used to identify brain regions with significantly higher (or lower) than average CBF/ReHo/ALFF values, respectively, for each type of the 3 measures. The same analyses were performed for each scan session (day 1 and day 2) separately.Pearson's correlation coefficient (CC) calculated in MATLAB was used to assess correlations between 1) global SBA vs global CBF, 2) regional SBA at each voxel vs global CBF, and 3) regional SBA vs regional CBF. In analysis 1, CC was directly calculated from the global SBA values and the global CBF values of all subjects. Global SBA was calculated from the corresponding SBA maps using the same brain mask used for calculating whole brain mean CBF. In analysis 2, CC at each voxel was calculated between the global CBF values and SBA values of that voxel from all subjects. CC's of all voxels were grouped into a CC map. In analysis 3, CC at each voxel was calculated between that voxel's CBF values and SBA values from the same subjects. CC's of all voxels were grouped into a CC map. The same association analyses were performed for both of 2 scan sessions. ReHo vs CBF ratio and ALFF vs CBF ratio at each voxel was calculated to directly demonstrate the spatial homogeneity of the ReHo-CBF and ALFF-CBF correlations.The CBF/FC/ReHo/ALFF distribution analysis results were thresholded at p<0.001 and the voxel-wise SBA vs CBF correlation results were thresholded at p<0.005 . The results were also thresholded with cluster extent >30 voxels. The overlap percentage of the two scan sessions' suprathreshold SBA vs CBF CC maps was calculated to evaluate the test-retest reliability for each of the assessed SBA-CBF associations.www.fmrib.ox.ac.uk/fsl). Two resting state networks were identified as examples to test the hypothesis: the default mode network (DMN) and executive control network (ECN) An additional analysis was performed to test whether various brain networks can be ranked or quantified using their CBF values. Brain networks were identified using group independent component analysis (ICA) network analysis Significant PCC-FC correlations were found in PCC, ACC, mOFC, prefrontal cortex (PFC), mTC, bilateral PC, and precuneus in both sessions . SignifiNo significant correlations were found between global CBF and any of the 4 SBA metrics either globally  or regionally . Both global ReHo and global ALFF showed a trend of correlation to global CBF. The CC of global ReHo vs global CBF was 0.19 and 0.28 for session 1 and session 2, respectively; CC of global ALFF vs global CBF was 0.41 and 0.43 for session 1 and session 2, respectively.Significant voxel-wise correlation between regional absolute CBF and PCC-FC in mOFC, VC, PCC/precuneus, bilateral PC, and left dorsal lateral PFC (DLPFC) were demonstrated in both sessions . Most ofPositive voxel-wise correlations between regional CBF and dACC-FC were consistently demonstrated in bilateral PFC in both sessions , which oRegional CBF obtained with ASL MRI provides a means to assess the links between resting BOLD imaging-derived SBA measures and underlying brain metabolism. This study provides the first evidence that the resting BOLD imaging-based SBA measures are related to regional CBF.Group level CBF, FC, ReHo, and ALFF patterns were first assessed for each of the 2 scan sessions to check the similarity of the distribution patterns of CBF and each of the 3 SBA measures . Consistent with the findings reported in the literature Repeatable regional PCC-FC vs regional CBF correlations were observed in bilateral PC, precuneus, VC, DLPFC, and mOFC, indicating a direct CBF modulation to the resting PCC-FC within the DMN , visual system, and the executive cognitive network (DLPFC and OFC). Similar to what was reported in Stable correlations between regional CBF and SBA coherence (ReHo) or the low frequency fluctuation magnitudes (ALFF) were demonstrated in most of the brain cortex. The ReHo/CBF ratio and ALFF/CBF ratio-based analyses also suggest that a spatially uniform and stable linear relation between regional CBF and the two local SBA measures exists in GM, except for VC and precuneus. Global CBF showed no significant correlations to both regional ReHo, suggesting that regional SBA is not linearly modulated by the overall brain energy supply. A trend of correlation was found between the global CBF and global ReHo or global ALFF, which can be understood from the massive regional CBF vs ReHo or ALFF correlation as the correlation of global CBF vs global ReHo or ALFF can be approximated to certain extent by a summation of the regional CBF vs regional ReHo or ALFF. As compared to the regional FC vs regional CBF correlation, regional ReHo and ALFF showed spatially more distributed correlations to regional CBF. FC is derived from the correlation of any brain voxel's time series to that of the seed region, and might be modulated by CBF of the current voxel as well as that of the seed. Consequently, regional CBF might contribute only certain part of the FC variations across subject, which explains why regional FC vs regional CBF showed correlations in fewer brain regions than regional ReHo and ALFF vs regional CBF.The value of these SBA vs CBF associations is twofold. First, it helps to link the apparent fMRI-derived parameters to a physiological meaningful measure. Though resting BOLD fMRI is assumed to be able to capture resting brain activity It is worth to note that the significant FC vs CBF correlation clusters appeared to be small, which raises a concern of noise interference. To reduce noise confounds, we used several preprocessing strategies including filtering, WM/CSF and global signal regression. More importantly, we used test-retest data from the same cohort of subjects with careful screening for any possible factors that may affect blood flow or even resting brain activity. As FC measures the correlations between two spatially distinct regions, it might be modulated by CBF from both regions.Two limitations exist in this CBF-SBA association study. First, the data sample size is moderate and an uncorrected significance level was used for thresholding the results. Second, the retest data were acquired 2 months later. The small sample size might explain why we did not find any significant (even an uncorrected threshold was used) correlation between vACC FC and regional CBF and why we did not find any correlation between SBA and the global CBF if there were. The multiple comparison issue applies to the FC vs CBF correlation analysis but not to the ReHo vs CBF or ALFF vs CBF analyses since the suprathreshold clusters of the correlation of ReHo and ALFF to regional CBF survived the false detection rate (FDR)-based multiple comparison correction (q<0.05) The test-retest data used in this paper were acquired in a project designed to test the stability of SBA measures and resting CBF with a long time interval (results were reported in a separate paper). Although a 2 month gap could conceivably introduce physiological or psychological variations to the data, we still found repeated SBA-CBF associations. One reason could be that these associations are stable over this duration in healthy subjects. Another explanation could be that the physiological and psychological variations affect SBA and CBF in the same way so their effects on the SBA-CBF correlation are canceled. Although we have screened for caffeine use and neurological disorders, several other factors, including breathing pattern, consumption of alcohol or caffeine, blood pressure, and activities of the autonomic nerve systems could alter blood flow. Since resting BOLD signals are modulated by CBF Various additional network-related measures In summary, we investigated the correlations between different SBA measures with CBF and their test-retest reproducibility. In our analysis, reliable correlations were demonstrated between CBF and PCC FC as well as dACC FC in many of the significant FC regions, respectively. Reliable correlations to regional CBF were found in ReHo and ALFF in most of gray matter area. No correlations were found between global CBF and these SBA measures. These results demonstrate that dynamic SBA measures based on BOLD fMRI are related to the static baseline CBF, which confirms a link between these apparent BOLD fMRI-based metrics and underlying SBA.File S1The abstract presented in the 18th Annual Meeting of the Organization for Human Brain Mapping, June, 2012 in Beijing, China.(DOC)Click here for additional data file.


Despite substantial evidence that T-type Ca2+ channels mediate pathological tremors, their roles in physiological motor coordination and behavior remain unknown. Here, we review recent progress in understanding the roles that T-type Ca2+ channels play under pathological conditions, and discuss the potential relevance of these channels in mediating physiological motor coordination.Specific behavioral patterns are expressed by complex combinations of muscle coordination. Tremors are simple behavioral patterns and are the focus of studies investigating motor coordination mechanisms in the brain. T-type Ca Unraveling the mechanisms that underlie specific motor patterns is a challenging issue in neuroscience. Motor coordination is a complex process that determines the timing and sequence of both activation and relaxation of a huge number of muscles  modulate both physiological and pathological rhythms in the brain . Pharmacological and genetic studies show that T-type Ca2+ channels are also involved in the generation of pathological tremors  neurons are also implicated in the generation of harmaline tremor. IO lesions reduce harmaline tremors in rats    do not display behavioral tremors, 4–10 Hz tremor-related oscillation in the olivocerebellar pathway, or STOs in IO neurons  is known to form a complex with CaV3 channels and be activated in response to CaV3—mediated calcium influx  are a genetic model of essential tremor. These mutant mice display ~25 Hz ET-like tremors  ameliorate both a1−/− mouse tremors and harmaline tremor  exhibit exacerbated tremor behavior  likely result from different mechanisms, such as the involvement of distinct T-type Ca2+ channel isoforms . The heterogeneity of essential tremor is well-described by clinical studies  patients. PD is caused by a dopamine deficiency in the brain. Rhythmic stimulation of the motor cortex via subcortical pathway is thought to underlie resting tremor of PD patients   underlie the resting tremor in PD patients  thalamus is another candidate for PD resting tremor. Dopamine deficiency in PD would result in the activation of globus pallidus interna (Gpi) and substantia nigra reticulata (SNr) neurons that provides GABAergic input to the VL thalamus Vitek, . Subsequs Figure . Thus, tright) .While the frequencies of STOs are ~10 Hz, the average firing rate of IO neuron is about 1 Hz, suggesting that individual IO neurons are insufficient to generate signal for 10 Hz physiological tremor  by hypothalamic input.Physiological tremors in both humans and animals are amplified in response to various alerting stimuli such as anger, novelty, or stress .Increased excitatory input to the IO may enhance synchrony between IO neurons, since infusion of a glutamate receptor antagonist into the IO decreases complex spike synchrony in the mediolateral direction Lang, . Otherwi2+ channels expressed in DCN neurons , T-type Ca2+ channels may also play a role in movement initiation. 10 Hz rhythmic signals in DCN neurons may reduce the action potential threshold in VL neurons. It will be necessary to selectively inhibit DCN-VL circuits in future studies.During resting states, there is increased inhibition of VL neurons by the basal ganglia, which in turn raises the threshold for the onset of movement initiation signals in the thalamocortical pathway. VL neurons also receive excitatory signals from DCN through monosynaptic connections between them . This enhanced tremor may help overcome inertial resistances and synchronize muscles when emergent motor responses are required   and subsequently raise motor performances. The role of CaV3.1 in the IO in generating physiological tremor would be critical in this process.Common sense suggests that proprioceptive feedback signals resulted from physiological tremors act as “noise” that might interfere with sensation. However, the stochastic resonance theory . Because CaV3.1 channel majorly generate LTS in DCN neurons, knockout of CaV3.1, or the application of T-type Ca2+ channel blockers in the DCN may ameliorate emotion-dependent motor symptoms.The hypothalamus is activated by either fear or stress Porter,  and conn2+ channels are expressed in neurons that comprise motor circuits, but the roles of these channels in physiological motor functions remain unknown. Because T-type Ca2+ channels are involved in generating pathological tremors, we propose that these channels may also play important roles in various physiological motor functions by enhancing physiological tremors or muscle tone. Optogenetic techniques (Boyden et al., 2+ channels (Park et al., 2+ channels using advanced technologies will improve our understanding of the neural mechanisms underlying higher motor coordination.T-type CaThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The Oxphen response to exercise was determined by the measurement of gene expression levels of Oxphen markers in pre and 4h-post exercise quadriceps biopsies. Because exercise-induced hypoxia and oxidative stress may interfere with Oxphen response, oxygen saturation and oxidative stress markers were assessed as well. Regardless of oxygen desaturation and absolute exercise intensities, the Oxphen regulatory response to exercise was comparable between COPD patients and controls with no evidence of increased oxidative stress. In conclusion, the muscle Oxphen regulatory response to acute exercise is not blunted in less advanced COPD, regardless of exercise-induced hypoxia. Hence, this study provides further rationale for incorporation of exercise training as integrated part of disease management to prevent or slow down loss of muscle Oxphen and related functional impairment in COPD.Already in an early disease stage, patients with chronic obstructive pulmonary disease (COPD) are confronted with impaired skeletal muscle function and physical performance due to a loss of oxidative type I muscle fibers and oxidative capacity . Physical activity is a well-known stimulus of muscle Oxphen and crucial for its maintenance. We hypothesized that a blunted response of Oxphen genes to an acute bout of exercise could contribute to decreased Oxphen in COPD. For this, 28 patients with less advanced COPD (age 65±7 yrs, FEV Loss of skeletal muscle oxidative phenotype (Oxphen) is prevalent in chronic obstructive pulmonary disease (COPD) Exercise is an important stimulus for maintenance of muscle Oxphen. Because patients with COPD are physically less active in vitro permeabilized muscle fibers of patients with severe COPD produce significantly more reactive oxygen species than those of healthy controls 2O2 than those within oxidative fibers Hypoxia is known to increase muscle glycolytic capacity relative to oxidative capacity www.trialregister.nl as NTR1402.Written informed consent was obtained from all subjects and the ethical review board of the Maastricht University Medical Center+ approved the study (08-2-059). The study was registered at 1 59±16% predicted; Pa,O2 9.3±1.0 kPa) and 15 healthy controls. Recruitment of patients and controls and exclusion criteria were previously described The study population included 28 clinically stable mild to moderate COPD patients  system to examine oxygen saturation locally at the muscular level. Arterial punctures were performed before exercise and at maximal exertion for gas and lactate analyses.V′o2peak) and peak work load were determined as previously described V′o2peak were available from n = 19 COPD patients and n = 11 healthy subjects. Arterial blood gas and lactate concentrations were analyzed on a Chiron blood gas analyzer 865 .All subjects performed an incremental load cycle ergometry test. The rationale for this protocol was to invoke a rapid exercise response in terms of Oxphen regulation particularly in the quadriceps muscle (see below). Peak oxygen uptake  and those who did not  according to ATS criteria vastus lateralis of the non-biopsied leg approximately 10 cm proximally from the knee joint, and covered with a black cloth to eliminate environmental light. Measurements started 3 minutes before exercise while the subject was still at rest and continued for 2–5 minutes after the exercise test until the signal had stabilized. Baseline values were established during 3 minutes of unloaded cycling before the incremental exercise test. Tissue oxygenation was measured continuously. Traces were analyzed with OxySoft Software . The tissue saturation index (TSI) was calculated using spatial resolved spectroscopy using the equation below, with [O2Hb] and [HHb] representing concentrations of oxygenated and deoxygenated hemoglobin/myoglobin.Arterial oxygen saturation was continuously monitored using a finger pulse oximeter. By ND, 4 COPDD patients, and 4 healthy controls) were excluded from further NIRS analyses mainly because their skin fold at the site of the NIRS measurement was greater than 3 cm , or because the signal was poor or did not show a clear drop in TSI.Values were reported as change from baseline (Δ). Using mono-exponential curve fitting, the time constant of muscle reoxygenation  was determined from the slope of the TSI curve during the reoxygenation phase. Twelve subjects  of the dominant leg from two separate incisions approximately 2 cm apart using the needle biopsy technique Biopsies were obtained at rest and 4 h after the exercise test from quadriceps muscle , Welch's ANOVA (post hoc Games-Howell) or Kruskal-Wallis non-parametric ANOVA (post hoc Mann-Whitney U with Bonferroni correction) as appropriate. Discontinuous variables were tested using Fisher's Exact test. These same tests were subsequently employed to analyze differences in exercise-induced response of skeletal muscle metabolic genes and oxidative stress markers between the groups (expressed as fold inductions), whereas paired Student's t test or Wilcoxon signed-rank test were performed to analyze such changes within each study group. Correlations were tested using Pearson's correlation coefficient, or Spearman's ρ in case of non-normally distributed data. Analyses were performed using IBM SPSS Statistics 20.0 . A p-value<0.05 was considered statistically significant.The assumptions of normality and homogeneity of variances were checked for all experimental groups with the Shapiro-Wilk test and Levene's test. Three different sets of statistical comparisons were made. First, baseline comparisons between the COPD patients and controls were tested using independent Student's 1 59±16). Compared to healthy controls, the COPD patients had a lower resting arterial oxygen saturation  vs 98 %) and daily physical activity level  vs 328  counts/min). COPDD patients did not differ from COPDND patients in terms of pulmonary function indices, but had a lower BMI.Characteristics of the study subjects are summarized in vs −1.09 %/repetition in healthy controls), but it was not different between COPDD and COPDND patients  in COPDDvs −1.61 %/repetition in COPDND).At baseline, as reported previously vs 156  Watt). No differences were found between COPDD and COPDND patients.Data from the cycle ergometry test are listed in D patients compared to COPDND patients.The acute exercise clearly evoked an upregulation of genes known to be exercise-responsive, including PGC-1α-related co-activator PRC, glycolysis-involved hexokinase II and the master regulator of the hypoxic response, HIF-1α . The COPD and COPDND patients (data not shown). After exercise, gene expression levels of heme oxygenase-1 (HO-1) and manganese superoxide dismutase (MnSOD) were increased in both COPD patients and healthy controls , which specifies that the drop in saturation during exercise should be ≥4% In contrast to what we expected, exercise-induced desaturation did not blunt the Oxphen response in COPD patients. This could indicate that acute local hypoxia does not hamper the Oxphen response. Another explanation for the comparable exercise responses between the COPDet al. recently described increased exercise-induced oxidative stress in mild to moderate COPD patients, who, similar to those in our study, had a slight loss of muscle Oxphen maxvs incremental exercise until exhaustion) and the timing of the muscle biopsy after the exercise test (1 h vs 4 h) hamper comparison between our study and theirs.Previous research in advanced COPD demonstrated an increased resting and exercise-induced oxidative stress response. We also investigated relevant oxidative stress markers in this study to see if a similar enhancement is seen in less advanced COPD, in particular in desaturating patients. No striking differences were observed between COPD patients, subgroups and healthy controls. In contrast Puente-Maestu Although we did not find increased oxidative stress-derived products after exercise, gene expression levels of the antioxidants MnSOD and HO-1 were increased, which is a normal response to exercise A limitation of this study is that only one biopsy was taken after the exercise bout. The timing of the single post biopsy was chosen after careful review of the literature focusing on Oxphen gene expression after exercise, but no inferences can be made regarding differences in the temporal pattern of gene expression changes between COPD patients and controls.An important constraint of the near-infrared spectroscopy (NIRS) technique is the limited optical penetration depth. As such, subcutaneous fat disturbs or even obstructs the quadriceps NIRS measurement. Therefore, subjects with a large skin fold at the site of the NIRS probe were excluded from the NIRS measurement in our study. We explicitly report this methodological issue as it often seems to be overlooked in the existing literature.Taken together, the data in this study suggest that patients with less advanced COPD do not have a blunted muscle oxidative regulatory response to acute exercise, regardless of exercise-induced systemic desaturation. This observation, together with a normal oxidative stress response, further supports that incorporation of exercise training as integrated part of COPD management already in early disease could have a pivotal role to prevent or slow down loss of muscle Oxphen and related functional impairment. Further research is needed to investigate if the muscle oxidative regulatory response is blunted in more severe disease stages (i.e. chronic respiratory failure) and disentangle potential contributing factors that may require additional modulation to optimize exercise training in these stages.File S1Table S1. qRT-PCR primer details for genes of interest.Table S2. qRT-PCR primer details for reference genes.(DOCX)Click here for additional data file.