Mice lacking the α isoform of the catalytic subunit of calcineurin (CnAα) were first reported in 1996 and have been an important model to understand the role of calcineurin in the brain, immune system, bones, muscle, and kidney. Research using the mice has been limited, however, by failure to thrive and early lethality of most null pups. Work in our laboratory led to the rescue of CnAα−/− mice by supplemental feeding to compensate for a defect in salivary enzyme secretion. The data revealed that, without intervention, knockout mice suffer from severe caloric restriction. Since nutritional deprivation is known to significantly alter development, it is imperative that previous conclusions based on CnAα−/− mice are revisited to determine which aspects of the phenotype were attributable to caloric restriction versus a direct role for CnAα. In this study, we find that defects in renal development and function persist in adult CnAα−/− mice including a significant decrease in glomerular filtration rate and an increase in blood urea nitrogen levels. These data indicate that impaired renal development we previously reported was not due to caloric restriction but rather a specific role for CnAα in renal development and function. In contrast, we find that rather than being hypoglycemic, rescued mice are mildly hyperglycemic and insulin resistant. Examination of muscle fiber types shows that previously reported reductions in type I muscle fibers are no longer evident in rescued null mice. Rather, loss of CnAα likely alters insulin response due to a reduction in insulin receptor substrate-2 (IRS2) expression and signaling in muscle. This study illustrates the importance of re-examining the phenotypes of CnAα−/− mice and the advances that are now possible with the use of adult, rescued knockout animals. Calcineurin is a multi-subunit phosphatase that requires the association of a regulatory subunit (B), a catalytic subunit (A), and the binding protein calmodulin to be functionally active −/− mice has been noted by several groups including our own In addition to the immune system, CnAα−/− and CnAβ−/− mice differ in their growth and development. While CnAβ−/− mice have a normal body weight and are fertile, failure to thrive and early lethality of CnAα(CnAα−/−) mice were created by J. Seidman  as previously described ad libitum.Calcineurin Aα knockout mice Kidney function was assessed by measurement of serum blood urea nitrogen (BUN) levels using a Reflotron benchtop chemistry analyzer and approximating glomerular filtration rate (GFR) as previously described 2O. Perfused kidneys were embedded in paraffin, sectioned at 4 µm and then stained with H&E for routine imaging. Some sections were also stained with Silver stain to visualize matrix proteins. For quantitation of cross sectional area of kidney zones, H&E stained coronal sections through all regions including the tip of the papilla were photographed under light microscopy at x4 magnification. Using ImagePro software , cortex, outer stripe of outer medulla (OSOM), inner stripe of outer medulla (ISOM) and inner medulla (IM) were framed and cross sectional area automatically calculated. Longitudinal axis was defined as a line through the tip of the papilla and perpendicular to the cortical surface. Length of axis was measured using ImagePro software as previously mentioned. For quantitation of glomerular size, H&E stained kidney sections were photographed under light microscopy at identical magnification. The harmonic mean glomerular area was determined using ImagePro software. Area sizes of at least 50 glomeruli per mouse were measured.Kidneys were fixed by systemic perfusion with formalin through the left ventricle of the heart at a constant pressure of 100 cm/HHindlimb muscles were snap frozen, sliced at 5µM, and mounted on glass slides. Tissue was then incubated for 15 minutes at room temperature with NADH-tetrazolium solution , and 1.5 mM nitro tetrazolium). Coverslides were mounted with Vectashield and fiber types analyzed by light microscopy. 4–6 different sections of muscle were analyzed and a total of 100–115 fibers were characterized per animal. Unstained fibers were designated type IIb, moderately stained fibers IIa/x, and intensely stained fibers type I.−7 M phenylmethylsulfonyl (PMSF)). Alternatively, primary muscle cells were plated in 60 mm dishes and allowed to grow to 80–90% confluence and the medium was changed to serum-free medium (SFM) for 24 hours and the cells were treated with insulin (1 ng/ml) for 10 minutes as indicated. Cells were harvested with trypsin-EDTA, pelleted, washed with 1X PBS, and lysed using TNESV lysis. 25 µg of protein was separated by 7.5% SDS-PAGE and proteins transferred to nitrocellulose. The membrane was incubated in 5% milk-TBST  and then immunoblotted with appropriate dilutions of primary antibodies as specified by the manufacturer. Total and phospho Akt, ERK1/2, GSK-3β primary antibodies were purchased from Cell Signaling Technology  and IRS1 and IRS2 antibodies were from SantaCruz Biotechnology . Membranes were incubated with HRP-conjugated secondary antibody, and proteins were visualized by enhanced chemiluminescence .Approximately 100 mg of tissue was lysed in TNESV lysis buffer . Statistical significance was considered when p<0.05. Unless otherwise stated, all comparisons were two-way ANOVA.All experiments in this study were approved by the Atlanta Veterans Administration Medical Center Institutional Animal Care and Use Committee protocol #VA-017.Mice in this study were rescued by supplemental feeding as previously described In addition to survival and body weight, blood glucose levels were monitored to assess caloric intake. Previously, we reported that null mice were hypoglycemic Previously, we reported that kidney, heart and liver weights were significantly reduced in null mice ad libitum fed rescued null mice and in WT littermates. CnAα−/− mice have significantly elevated fasting and fed glucose levels. Mean insulin levels in null mice trend higher but do not reach significance  as previously described ificance Table 2.Data thus far indicate that despite supplemental feeding with the modified diet, CnAα−/− mice still have impaired renal function and reduced kidney mass. To further characterize the kidney phenotype of rescued mice, we obtained perfusion fixed kidneys and measured the axonal length and cross sectional area of the cortex, outer stripe of the outer medullae (OSOM), inner stripe of the inner medullae (ISOM) and the inner medullae (IM). Previously, changes in superficial cortical glomeruli were key features of the null phenotype The data thus far suggested that early caloric deprivation did not significantly alter the renal phenotype of CnAα−/− mice. However, rescue of the mice did reveal a potential new role for CnAα in regulation of glucose levels. Interestingly, mice that overexpress constitutively active CnAα in the muscle have enhanced insulin responsiveness One mechanism for altered insulin sensitivity could be changes in the relative proportions of fast versus slow twitch skeletal muscle fibers which have different levels of glucose utilization. Previously, CnAα−/− mice were reported to have significantly fewer Type I and Type IIa/x muscle fibers compared to WT littermates As an alternative to deranged fiber type distribution, we examined expression of key insulin signaling proteins including the insulin receptor substrates 1 and 2 (IRS1 and IRS2) in hindlimb skeletal muscle tissue. Calcineurin Aα null mice were first reported in 1996. Since then, the mice have been used in studies of the brain not cause pervasive defects in maturation and development. Rather, the most significant effect on development is impaired vesicle secretion in the salivary gland that leads to decreased enzyme levels during the peri-weaning period and, subsequently, starvation. Supplementation with the modified diet aids early digestion and restores normal weight gain and body mass. In rescued adult mice, we find that most organ deficits previously noted are normalized. Liver and heart weight are no longer attenuated, suggesting that these findings were due to starvation and not loss of CnAα in those tissues. Likewise, hypoglycemia is no longer evident in rescued mice which instead have mildly elevated glucose levels. In contrast, the gross kidney phenotype of null mice persists; glomeruli are abnormal, and kidney function is reduced. These data support our previous conclusion that CnAα is required for normal kidney development and function but also highlight the impact of early starvation on previous findings.The data in this study clearly demonstrate that, contrary to what we and others previously concluded, loss of CnAα does Rescued mice confirm much of our previous work showing that CnAα plays a significant role in kidney development and function. Small kidney size in the null mice appears to stem from a deficit of late nephrogenesis. While overall glomerular number is comparable and juxtamedullary nephrons appear typical, the majority of superficial cortical glomeruli are abnormal and likely non-functional. This is associated with tubular atrophy resulting in a decrease in cortical and OSOM volume and decreased kidney function. The mechanism by which CnAα affects nephrogenesis is still unclear.Despite the success in rescuing the null mice at weaning, it is still possible that early nutritional deprivation complicates the phenotype of adult CnAα null kidneys. Although this is the first report of GFR in null mice, we did examine GFR in heterozygous mice previously In addition to confirming altered kidney growth/development with loss of CnAα, new findings in this study include splenomegaly in CnAα null mice Table 2.The last new aspect of CnAα−/− phenotype that we found is mild hyperglycemia. Previously, we reported that null mice were hypoglycemic In conclusion, these studies help to differentiate between the effects of caloric deprivation and specific roles of CnAα in the kidney and also identify new aspects of CnAα action that warrant further investigation. Now that CnAα null mice can be rescued to adulthood – and are even fertile – new opportunities exist to verify previous data and to add to our knowledge of calcineurin action.


This new method extracts large-scale structural graphs where nodes represent small cortical regions that are connected by edges when they show statistical similarity. Using this method, unweighted and undirected networks were extracted from T1 weighted structural magnetic resonance imaging scans of 38 AD patients  and 38 controls . Group comparisons of standard graph properties were performed after correcting for grey matter volumetric measurements and were correlated to scores of general cognitive functioning. AD networks were characterised by a more random topology as indicated by a decreased small world coefficient (p = 3.53×10−5), decreased normalized clustering coefficient (p = 7.25×10−6) and decreased normalized path length (p = 1.91×10−7). Reduced normalized path length explained significantly (p = 0.004) more variance in measurements of general cognitive decline (32%) in comparison to volumetric measurements (9%). Altered path length of the parahippocampal gyrus, hippocampus, fusiform gyrus and precuneus showed the strongest relationship with cognitive decline. The present results suggest that single-subject grey matter graphs provide a concise quantification of cortical structure that has clinical value, which might be of particular importance for disease prognosis. These findings contribute to a better understanding of structural alterations and cognitive dysfunction in AD.Coordinated patterns of cortical morphology have been described as structural graphs and previous research has demonstrated that properties of such graphs are altered in Alzheimer's disease (AD). However, it remains unknown how these alterations are related to cognitive deficits in individuals, as such graphs are restricted to group-level analysis. In the present study we investigated this question in  Alzheimer's disease (AD) is a progressive and disabling neurodegenerative disorder that accounts for approximately 50% to 80% of all dementia cases. AD is histopathologically defined by the presence of amyloid-β plaques and tau-related neurofibrillary tangles Coordinated patterns of cortical morphology in structural magnetic resonance imaging (sMRI) scans have been described as graphs e.g., . The nodFurthermore, while most functional studies have reported that graph topologies move towards more random connectivity configurations in AD single-subject grey matter graphs for the first time in AD using a recently developed method The present study addresses these questions by investigating graph properties of In total 38 patients with probable Alzheimer's disease (AD) and 38 gender and age matched controls were recruited from the Alzheimer Centre of the VU University Medical Centre. All subjects received standard dementia screening that included a medical history, physical and neurological examination, cognitive examination, extensive neuropsychological evaluation, screening laboratory tests, an electroencephalogram (EEG), and a magnetic resonance imaging (MRI) scan. Patients were diagnosed during a multidisciplinary consensus meeting with probable AD when they fulfilled the criteria proposed by the National Institute on Aging and the Alzheimer's Association (NIA-AA) workgroup 3. All scans were reviewed for brain pathology other than atrophy by an experienced radiologist. The origin of the scans was automatically set to the anterior commissure using the linear transformation matrix to MNI space that was calculated in FSL-FLIRT Neuroimaging of the subjects was carried out on a 3.0 Tesla scanner  using a standard circularly polarised head coil with foam padding to restrict head motion. The scan protocol included a whole-brain 3D fast spoiled gradient-echo sequence (FSPGR) with a repetition time of 708 ms, an echo time of 7 ms, flip angle of 12°, 180 sagittal slices, field of view of 250 mm, slice thickness of 1 mm, and a voxel size of 0.98×0.98×1 mmjm between cubes vj and vm calculates the sum over the product of the differences between the cubes' values at each voxel location i = 1, 2, … n for n voxels . The denominator of the correlation coefficient is the product of the cubes' standard deviations:Single-subject grey matter graphs were based on intracortical similarity using a completely automated and data-driven method that has been previously described in Given that the cortex is a curved object, two similar cubes could be located at an angle from each other, which could decrease their similarity value. Therefore, the maximum correlation value was computed over different rotations of the seed cube. Regions with zero variance in grey matter values were excluded , because in these cases the correlation coefficient is undefined.SD = 0.002) spurious correlations for all individuals .In order to quantitatively describe the single-subject graphs and to maximise comparability of our results with those reported by previous graph studies in AD, we assessed the following basic network properties: the size of networks, the connectivity density , the degree, the characteristic path length , the clustering coefficient www.brain-connectivity-toolbox.net, Another feature of brain graphs is the existence of nodes with a central role in a network, i.e., “hubs”. The existence of hubs in a network decreases the characteristic path length and renders graphs more resilient towards random attack of nodes and/or edges e.g., . HoweverStatistical comparisons were performed in R version 2.15.0 (30-03-2012). Lilliefors tests from the R package “nortest” indicated a significant departure from normality of the distributions for some of the network properties. Log-transformation proved unsuccessful in rendering the data normal, and therefore we used a rank transformation of network properties values so that we could use parametric analysis methods It has been demonstrated that differences in graph size and connectivity density influence other network properties p values using the False Discovery Rate . In order to reduce dimensionality and aid comparability among graphs but also with other studies, local graph properties were summarised by averaging these across the cubes within each of the 90 anatomical areas that were defined in individual subjects by means of the Automated Anatomical Labelling atlas AAL,  using thate FDR, .p = 7.65×10−15). Furthermore, global grey matter volume was significantly lower in AD  and an average connectivity density of 15% (SD = 0.74) across all subjects.The main subject characteristics are summarised in F  = 19.62, p = 3.35×10−5; F  = 4.58, p = 0.04; F  = 33.30, p = 1.91×10−7; γ: F  = 23.45, p = 7.25×10−6; the small world property: F  = 19.50, p = 3.53×10−5). The betweenness centrality did not differ between the groups  = 0.06, p = 0.81). Taken together, these results suggest that AD networks move towards a more random topology. Because these graph properties were corrected for global grey matter volume, it is unlikely these results simply reflect cortical atrophy.All single-subject grey matter graphs in both AD and control groups had higher average clustering than random reference networks  and similar average path length , indicating that all networks had a small world topology . However, this topology was altered in AD. All full ANCOVA's models were significant after correction for multiple hypotheses testing with FDR. The graphs from AD patients were characterised by a decreased characteristic path length  = 8.18, p = 0.006), complicating the interpretation of the comparison of a relative hub definition. As an alternative, we compared regional BC between the groups. F  = 6.25, p = 0.01), left parahippocampal gyrus  = 13.83, p = 0.0004), left lingual gyrus  = 5.13, p = 0.03) and bilateral thalami  = 13.12, p = 0.0005; right F  = 4.07, p = 0.05). The left parahippocampal gyrus, left lingual gyrus and bilateral thalami of the AD group also showed decreases in clustering coefficient and path length . The average characteristic path length was strongly related to MMSE scores (2adjusted R = 0.32), which was a significant improvement (p = 0.004) when compared to the model including only global grey matter and hippocampal volume (2adjusted R = 0.09). Adding the hippocampal path length to the model did not lead to further improvements (p = 0.79). To conclude, within the AD group more random graphs were associated with worse cognitive dysfunction, supporting the clinical relevance of single-subject grey matter graphs.Next, we examined whether these graph properties could explain more variance in MMSE scores than global and hippocampal grey matter volume. single-subject grey matter graphs, using a recently developed method to describe patterns of intracortical similarities from MRI data. One of the main findings was that the topology of AD graphs was more random in comparison to control subjects. In addition, decreases in nodal centrality were found in specific anatomical areas known to be involved in AD, suggesting that the contributions of cortical areas to global disruptions are heterogeneously distributed across anatomical areas. Importantly, by using single-subject grey matter graph measurements we were able to demonstrate a relationship between graph alterations and general cognitive decline at both whole brain level and in specific cortical areas. These findings could not be explained by volumetric differences. The present results support the clinical relevance of single-subject structural brain graphs.The present study demonstrated AD-related alterations in At this point the biological mechanisms underlying intracortical similarities are still unknown and we can only speculate about the causes of AD related alterations in these patterns. Intracortical similarities might be induced by functional coherence of cortical areas that has been demonstrated to cause coordinated changes of cortical structures within individuals In addition to functional coactivation, intracortical similarities might arise as a result of axonal connectivity that can influence morphological measurements of the cortex Disruptions in any of these processes are likely to contribute to changes in patterns of intracortical similarity that are related to AD.The presently investigated single-subject graphs were characterised by a more random topology in AD and this was indicated by a decreased path length, clustering coefficient and small world coefficient (including both γ and λ). Most of these results are in line with previous functional studies that also have demonstrated more random topologies in AD Furthermore, local measurements were heterogeneously affected, indicating that specific areas are targeted in the disease. The areas that showed decreased betweenness centrality in AD included the posterior cingulate, the parahippocampal and lingual gyri. These structures have previously been reported to be altered in group-based structural graphs Another important finding of the present study was that decreased characteristic path length in medial temporal areas, including the hippocampus, but also in other areas such as the right precuneus was related to worse cognitive performance and that these relationships could not be explained by differences in local volumetric measurements. These results imply that graph measurements have the potential to monitor disease progression, which is important for the development of new treatments.Interestingly, some of the areas where we found graph disruptions, such as the posterior cingulate cortex and precuneus, are known to be highly interconnected in both functional and anatomical graphs A priori differences in network size and/or connectivity density complicate subsequent graph comparisons, because these properties influence other network property values The single-subject graphs of our previous study We found strong relationships between global cognitive functioning as measured by the MMSE and altered single-subject graph properties, that were absent with volumetric measurements. However, a limitation of the MMSE is that it is mostly a clinical screening tool and should not be regarded as an elaborate neuropsychological assessment. Future research is needed to examine whether altered graph properties are related to dysfunction in specific cognitive domains. In addition, the diagnostic potential of these graphs should be further investigated using sophisticated classification algorithms such as support vector machines e.g., .The present finding of a decreased average characteristic path length in AD was unexpected because other structural studies have associated AD with increased characteristic path lengths Our results show closer resemblance to those reported by functional graph studies The current approach could be used to further investigate why the spatial pattern of plaques in AD does not show a clear correspondence with tangles and atrophy patterns: Possibly, coordinated changes in cortical structure in AD are caused by disrupted functional dynamics due to plaques and tangles. Future research will further investigate this question by combining functional and structural graphs within subjects.Finally, the control group in the present study comprised people who entered the clinic with memory complaints, but were found to have no objective cognitive disorder after testing. It cannot be ruled out that these people might experience a very early stage of the disease, as they have a higher chance to develop AD In conclusion, this study demonstrated evidence of the clinical value of single-subject grey matter graphs, which provide a concise quantitative description of disruptions in coordinated morphological patterns of entire brains. The present results contribute to a better understanding of the relationship between structural changes and cognitive dysfunction in Alzheimer's disease.File S1Supporting information.(DOC)Click here for additional data file.


The present paper aimed to comprehensively analyse available data from genetic and animal studies with mice, rats, pigs, cows, and laying hens and from human studies in order to compare the regulation of genes involved in carnitine homeostasis by PPARα across different species. Overall, our comparative analysis indicates that the role of PPARα as a regulator of carnitine homeostasis is well conserved across different species. However, despite demonstrating a well-conserved role of PPARα as a key regulator of carnitine homeostasis in general, our comprehensive analysis shows that this assumption particularly applies to the regulation by PPARα of carnitine uptake which is obviously highly conserved across species, whereas regulation by PPARα of carnitine biosynthesis appears less well conserved across species.Recent studies in rodents convincingly demonstrated that PPAR Mechanistic details of gene regulation by PPARα and tissue distribution of PPARα has been extensively described in the literature, wherefore the reader is referred to the literature with regard to this [α, which is common to energy deprivation and fibrate treatment, was shown to cause an increase in the expression of genes involved in carnitine uptake and biosynthesis in liver cells [α protein strengthening the assumption that PPARα is a critical regulator of carnitine homeostasis [γ-butyrobetaine dioxygenase (BBOX1) and 4-trimethylaminobutyraldehyde dehydrogenase (ALDH9A1), are direct PPARα target genes as evidenced by the identification of functional PPRE within the regulatory region of the respective genes [Peroxisome proliferator-activated receptor eostasis , becauseogenesis . PPARα-d to this . The moler cells  serving eostasis , 10. Usive genes –13.α activators exert distinct species-specific actions [α activators leads to a marked peroxisomal enzyme induction, peroxisome proliferation, and even hepatocarcinogenesis [α activators cannot induce peroxisome proliferation and hepatocarcinogenesis and the induction of peroxisomal metabolism pathways is much less pronounced in human hepatocytes and livers from nonhuman primates [α activators is responsible for the classification of different species into proliferating  and nonproliferating ones . Several factors are considered to account for the marked difference in the response to PPARα activators between different species: expression level of PPARα, degree of conservation and functionality of the PPRE in the regulatory region of target genes, and lack or overexpression of transcriptional coregulators [α activators on peroxisome proliferation between proliferating and nonproliferating species, a comparative analysis of gene regulation by PPARα between mouse and human revealed that at least the role of PPARα as a master regulator of hepatic lipid catabolism is well conserved [β-oxidation is carnitine-dependent, is also a well conserved function of PPARα. However, despite its well conserved role as an important regulator of lipid catabolism in general, the specific genes under control of PPARα within each lipid metabolic pathway were shown to differ at least between humans and mice [α can be considered as a critical regulator of genes involved in carnitine homeostasis across different species requires thorough analysis of the effect of PPARα activation on carnitine homeostasis in each individual species and cannot be predicted for one species by simply transferring observations obtained in mice or rats. In light of the abovementioned species specificities with regard to the response to PPARα activation the present paper aims to (1) briefly describe current knowledge about the genes involved in the regulation of carnitine homeostasis and (2) to comprehensively analyse available data from genetic and animal studies with mice, rats, pigs, cows, and laying hens and from human studies in order to compare the regulation of genes involved in carnitine homeostasis by PPARα across different species. It is well established that PPAR actions –17. In rogenesis , 19. In onserved . It may and mice . Thus, wβ-oxidation. In mammals, carnitine is considered a conditionally essential nutrient because it is synthesized by the organism but most is taken up from the diet [μmol/L), because vegetarians have a more efficient renal reabsorption of carnitine  because most of the filtered carnitine is lost in the urine [μmol/L in plasma to about 4000 μmol/L in skeletal muscle) [Carnitine is a water soluble quaternary amine  which is essential for normal function of all tissues. The primary function of carnitine is to facilitate the translocation of activated long-chain fatty acids from the cytosol into the mitochondrial matrix, a process called carnitine shuttle, for subsequent fatty acid the diet . Food ofthe diet . Thus, dthe diet , whereasetarians ) and a getarians , 26. In he urine . If plashe urine . This exhe urine , 30. Thehe urine , and, li muscle) . Due to  muscle) –35. γ-butyrobetaine (BB). In the final biosynthetic step, BB is hydroxylated by BB dioxygenase (encoded by BBOX1) to form carnitine [The carnitine biosynthesis pathway consists of a cascade of four distinct enzymatic reactions through which 6-N-trimethyllysine (TML), which is the substrate for carnitine biosynthesis, is converted stepwise into carnitine. TML is the product of lysosomal and proteasomal degradation of proteins containing N-methylated lysines, such as calmodulin, myosin, actin, and histones . In the arnitine . In all arnitine , and in arnitine , 37. Otharnitine , 37, andarnitine .Tissues which are incapable of providing carnitine via endogenous biosynthesis, such as skeletal muscle and myocardium, are highly dependent on the uptake of carnitine from the circulation. This transport across the plasma membrane against a high concentration gradient  is mediated by the novel organic cation transporters (OCTNs) which belong to the solute carrier 22A family , 39. TheThe OCTN1 isoform is considered to contribute less to carnitine transport than OCTN2 due to its low carnitine transport activity. OCTN1 is localized in the mitochondrial membrane in close proximity to CPT I, the rate-limiting enzyme for carnitine-dependent fatty acid oxidation. Due to this localization, OCTN1 has been proposed to operate on the mitochondrial influx and efflux of carnitine and acylcarnitine esters indicating that OCTN1 is mainly involved in maintaining intracellular carnitine homeostasis . Anotherα, causes a marked elevation of the hepatic carnitine concentration [α activation is responsible for this phenomenon. Indeed, we demonstrated for the first time that PPARα activators strongly increase transcript levels of OCTN2 in rat liver and cultivated rat hepatocytes [α activators was accompanied by an elevation of the carnitine concentration in rat liver and cultivated rat hepatocytes [α plays a role in regulating carnitine homeostasis through stimulating OCTN2-mediated carnitine uptake from blood into the liver. In subsequent studies with rats, we found that treatment with PPARα activators increases also OCTN2 transcript levels in small intestine [α is an important regulator of carnitine uptake and that upregulation of OCTN2 in small intestine may contribute to the elevation of hepatic carnitine concentration in response to PPARα activators through increasing carnitine availability from the diet. A further study in rats revealed that energy deprivation, which is a physiologic state of PPARα activation, also results in increases of OCTN2 transcript levels and carnitine concentration in the liver [α in rats [α, we also investigated whether feeding of oxidized fats causes similar effects on carnitine homeostasis as energy deprivation and fibrate treatment [α activators.Based on earlier reports that energy deprivation or treatment with fibrates, both of which induce activation of hepatic PPARntration –7, we haatocytes . Moreoveatocytes . These fntestine , 47, andhe liver . Since a in rats –51 due treatment . Indeed,α, we performed in silico analysis of the rat OCTN2 promoter which revealed several putative PPRE upstream of the transcription start site [α target gene. However, in comparison to the marked induction of OCTN2 mRNA by fibrates and fasting [α activation.Since the results from these experiments suggested that OCTN2 might be a direct target gene of PPARart site . Using rart site  recently fasting , 46, 48  fasting  suggesteα in regulating genes involved in carnitine biosynthesis in rats. All of the abovementioned studies in rats did not show any increase in the transcript levels of ALDH9A1 and BBOX1 in the liver in response to fibrate treatment, fasting, or administration of oxidized fat. This indicates that at least the rat genes encoding ALDH9A1 and BBOX1 are not transcriptionally regulated by PPARα, despite the fact that several conserved PPRE were identified in the proximal promoter of the rat BBOX1 gene using NUBIScan software [α activation, an effect that is not mediated by increasing expression of genes encoding enzymes of the carnitine biosynthesis pathway but rather by stimulating lysosomal and proteasomal degradation of proteins which leads to the release of TML [Although previous studies in rats indicated that the clofibrate-induced increase in hepatic carnitine concentration is due to an increase in the rate of hepatic carnitine synthesis , 7, resusoftware , 48, 54.software . In factsoftware . Thus, ie of TML , 58. Thee of TML  is suppoα plays a role in the regulation of carnitine homeostasis, studies with PPARα knockout and corresponding wild-type mice have been conducted [α regulates gene expression of OCTN2 in the liver of mice as evidenced by the observation that upregulation of OCTN2 in response to fasting or WY-14,643 treatment occurs only in wild-type but not in PPARα knockout mice. Using the same mice genotypes, Koch et al. [α activators cause OCTN2 upregulation also in kidney and small intestine. Studies from both groups showed that the elevation of hepatic carnitine concentration in response to PPARα activation occurs only in wild-type mice [α is a critical player for regulating carnitine homeostasis. Noteworthy, these studies revealed also upregulation of genes encoding the carnitine biosynthetic enzymes ALDH9A1 and BBOX1 in the liver of wild-type but not PPARα knockout mice indicating that genes involved in carnitine biosynthesis are regulated by PPARα in mice, which is in contrast to the rat. According to convincing data from studies with rats that PPARonducted , 10. vanonducted  were theh et al.  but addiype mice , 10, whiα dependency of regulation of the mouse genes encoding OCTN2, ALDH9A1, and BBOX1 is provided by the observation that hepatic mRNA, and protein levels of OCTN2, ALDH9A1, and BBOX1 are decreased in obese mice compared to lean mice [α function and to impair PPARα dependent gene transcription [α, these data suggest that endurance exercise was able to restore at least in part the obesity-induced disruption of PPARα function and thereby contributed to the elevated gene expression of OCTN2, ALDH9A1, and BBOX1.Further indication for the PPARean mice , becausecription , 62. Notα, evidence has been provided that PPARα might influence the availability of requisite biosynthetic precursors—through the abovementioned stimulatory effect of PPARα activation on proteolysis—and enzymatic cofactors required for carnitine synthesis. In this context a study from Makowski et al. [α knockout mice display markedly lower levels of methionine, which serves as a methyl donor during posttranslational assembly of methylated proteins, and α-ketoglutarate, which is a cofactor of TMLHE and BBOX1, in plasma and tissues, respectively, than wild-type mice.Besides direct transcriptional regulation of genes involved in carnitine homeostasis by PPARi et al.  is worthα target genes [α knockout mice [α was evidenced by the identification of one functional PPRE each in the regulatory region of these genes. The functional PPREs were shown to be located in either the proximal promoter  or ALDH9A1; ). Taken α activators between rodents and humans [α in the liver and the response to PPARα activators  is very weak, wherefore pigs like humans and nonhuman primates belong to the nonproliferating species. A recent study from our group showed that PPARα mRNA levels in the liver are comparable between pig and human [α activation. Activation of PPARα in liver and other tissues of pigs have been already demonstrated in response to clofibrate, oxidized fat as well as fasting [α also in pigs we performed two experiments in which pigs were either treated with clofibrate or fasted for 24 h. Treatment with clofibrate caused an upregulation of OCTN2 in liver, skeletal muscle, and small intestine, and increased carnitine concentrations in liver and skeletal muscle [α, even though the extent of upregulation of OCTN2 and BBOX1 is lower in pigs than in rodents. The latter may be explained by the lower tissue expression level of PPARα in pigs than in rodents but also by species differences in the availability of transcriptional coregulators. In this context it is worth mentioning that a large number of PPAR related coregulators, such as CBP/p300, SRC-1-3, PGC-1α, PGC-1β, PRIP, PRIC285, CARM1, and PIMT, have been described to influence PPAR target gene transcription and that their relative availability in a given tissue is at least partially responsible for the tissue specific expression of target genes and the responsiveness of PPAR isotypes to specific ligands [The abovementioned observations in rodents cannot be directly applied for humans, because of marked differences in the response to PPARd humans , 18. In nd human , which s fasting –67. In ol muscle . Upregul ligands . α in rodents, only limited information is available on the regulation of PPARα activity and its role for carnitine homeostasis in cattle liver. Apart from demonstrating that PPARα is functional in cattle liver [α in bovine cells [α target genes in nonruminants in the liver being indicative of PPARα activation during early lactation [α target genes in nonruminants [α in early lactating cows. In line with our hypothesis, our study showed that the transition from late pregnancy (3 wk prepartum) to early lactation leads to an upregulation of various genes involved in carnitine synthesis  and carnitine uptake (OCTN2) in the liver of cows at 1 wk postpartum [α target genes, the positive correlations between plasma free fatty acids, which are endogenous activators of PPARα, and hepatic carnitine concentrations during lactation are supportive for a role of PPARα in the regulation of carnitine homeostasis in cattle. Besides these data from pregnant and lactating cows which provide indirect evidence for a PPARα-dependency of carnitine homeostasis in cattle, unpublished data from our own group from cell culture experiments provide stronger evidence for a role for PPARα in regulating genes involved in carnitine homeostasis in cattle. We found that treatment of bovine kidney cells with a PPARα agonist increases transcript and protein levels of OCTN2. Whether the bovine BBOX1 gene is also regulated by PPARα cannot be answered with certainty because BBOX1 is not expressed in this bovine kidney cell line (unpublished observation).In contrast to the large body of literature with regard to the regulation of carnitine homeostasis by PPARle liver  and longne cells , 72, it actation –76. Baseactation , 78, we actation . As expeactation , our stuuminants , which istpartum ; transcrstpartum . Thus, iα has been shown to be highly expressed in chicken liver and to play an important role for the homeostasis of energy and lipid metabolism during fasting [α with mouse, rat, and human PPARα [α in tissues between chicken and rodents as well as humans has been reported [α in the liver of laying hens can be strongly activated by the administration of clofibrate as evidenced from elevated transcript levels of classical PPARα target genes [α in laying hens, we have recently performed a study with laying hens which were fed diets supplemented without (control) or with clofibrate [α in the liver of clofibrate-treated hens could be demonstrated by elevated transcript levels of classical PPARα target genes. In addition, this study demonstrated that OCTN2 but not genes encoding enzymes of carnitine biosynthesis in the liver are upregulated by clofibrate in the liver of laying hens [α has an essential role in the regulation of carnitine homeostasis in hens like in mammalian species. Unlike in mice and pigs, however, PPARα in laying hens appears to play a role only for regulating OCTN2-mediated carnitine uptake but not carnitine biosynthesis. In a further study, it has been investigated whether carnitine homeostasis in laying hens can be also influenced by the administration of nutritive PPARα activators [α agonists on carnitine homeostasis, however, is not a contradiction to the abovementioned study but rather reflects the fact that activation of PPARα by both fish oil and CLA in this study was negligible, which itself is likely due to the low binding affinity of n-3 PUFA and CLA isomers when compared to the synthetic PPARα activator clofibrate.Like in mammals, PPAR fasting . In addian PPARα , 82 and reported , 82. Moret genes . In ordeofibrate . Interesing hens , which itivators . This stα in animals, only few studies with limited significance are available to evaluate whether PPARα regulates carnitine homeostasis in humans as well. One important reason for the limited significance of human studies is that, with few exceptions, most of them used plasma samples only, which is not appropriate for evaluating changes in carnitine homeostasis. To our knowledge only one study is available in the literature analyzing the change in the urinary profile of carnitine and its derivates in healthy adults in response to starvation [α activation. According to this study, 48 h starvation caused a slight decrease in the urinary excretion of free carnitine and a marked increase in that of acetyl carnitine. Albeit being speculative, the reduced urinary excretion of free carnitine in the starved subjects may be indicative of a PPARα-induced increase in the tubular reabsorption of carnitine in the kidney which is possibly mediated by an upregulation of OCTN2. In another study with human subjects, from which skeletal muscle biopsies were taken, no change in skeletal muscle carnitine levels were found in patients under starvation conditions [α is a regulator of carnitine homeostasis also in humans because the carnitine concentration in skeletal muscle, which is the main storage site for carnitine in the body, is expected to change only slightly even if OCTN2 is upregulated by PPARα activation. Supportive of this assumption is the observation that concentrations of total carnitine in skeletal muscle also did not change in rats and pigs which were starved for 24 h [α in humans may be expected to be obtained from clinical studies dealing with pharmacological PPARα agonists . However, according to our literature research no clinical studies investigating the efficacy of different fibrates  for blood lipid modifying purposes were found that also reported on either plasma or urinary carnitine levels.In contrast to extensive research on the regulation of carnitine homeostasis by PPARarvation , which inditions . This fifor 24 h . Furtherα, two other PPAR isotypes, PPARγ, which is expressed in two different full-length translated isoforms , and PPARδ, exist in mammals and birds. The distribution pattern and expression levels of the PPARs show great differences between tissues. Whereas PPARα is highly expressed in tissues with high rates of fatty acid oxidation , PPARγ1 is poorly expressed in these tissues. Both PPARα and PPARγ1 are found in cells of the immune system and the vessel wall and in epithelial cells. The adipocyte-specific PPARγ2 isoform is exclusively and highly expressed in adipose tissue. PPARδ is ubiquitously expressed and the predominant PPAR isotype in skeletal muscle. To our knowledge only one study has been published investigating the role of other PPAR isotypes than PPARα on genes involved in either carnitine uptake or carnitine biosynthesis [γ in humans and mice and thereby contributes to local and systemic carnitine homeostasis. Whether PPARγ is also a transcriptional regulator of genes encoding enzymes of the carnitine biosynthesis pathway has not been investigated in this study. In addition, the role of PPARδ in regulating genes involved in carnitine homeostasis has not been addressed so far. However, PPARδ has similar and partially overlapping functions as PPARα, in particular with regard to fatty acid catabolism [α and PPARδ. Thus, it would be not unlikely that PPARδ is also a transcriptional regulator of OCTN2 and genes of the carnitine biosynthesis pathway. This, however, remains to be shown in future studies.Besides PPARynthesis . Accorditabolism . For instabolism  and carntabolism , were shα suggests that carnitine homeostasis, which is intrinsically linked with lipid catabolism, is well conserved across different species. This confirms recent observations from genome-wide comparative analysis of gene regulation by PPARα between mouse and human demonstrating that at least the role of PPARα as a master regulator of hepatic lipid catabolism is well conserved [α as a key regulator of carnitine homeostasis in general, our comprehensive analysis shows that this assumption particularly applies to the regulation of genes involved in carnitine uptake (OCTN2) by PPARα which is obviously highly conserved across species. The highly conserved regulation of OCTN2 by PPARα is possibly explained by the fact that the sequence of the functional PPRE identified in the mouse OCTN2 gene is completely identical (100%) between mouse, rat, pig, cattle, and even human  generally show a weaker response to PPARα activation than proliferating species . In contrast, regulation of genes involved in carnitine biosynthesis  by PPARα appears less well conserved across species, which is demonstrated by the fact that PPARα activation causes upregulation of genes involved in carnitine biosynthesis in mice, pigs and cattle but not in rats and chicken. The reasons underlying these species specificities cannot be simply explained by differences in the PPARα expression level between species because mice and rats, for instance, exhibit comparably high hepatic PPARα expression levels. In the case of BBOX1 differences in the nucleotide sequence of the functional PPRE of the BBOX1 gene between mouse and rat also cannot explain this species specificity because this PPRE shares a complete (100%) sequence identity between mouse and rat and even human and cattle (α is the different location of the translation start site of the BBOX1 gene between mouse (translation start site in the first exon) and rat (translation start site in the second exon). In addition, a species specific expression pattern of transcriptional coregulators in the liver may be causative for the different regulation of BBOX1 by PPARα between mouse and rat. By contrast, a small discrepancy in the sequence of the functional PPRE of the ALDH9A1 promoter between mouse and rat  could explain the species specificity regarding ALDH9A1 regulation by PPARα (α across different species and, therefore, further research is required to unravel the underlying reasons. Overall, our comparative analysis indicates that PPARα is not only a master transcriptional regulator of fatty acid catabolism, ketogenesis, and gluconeogenesis but also of carnitine homeostasis—a role which is well conserved across species.Comparison of data from genetic and animal studies with mice, rats, pigs, cows, and laying hens and from human studies on the regulation of genes involved in carnitine homeostasis by PPARonserved . Howeveren human . The comd cattle . One facby PPARα . Neverth


Hyponatremia is the most common electrolyte disorder in clinical practice, and evidence to date indicates that severe hyponatremia is associated with increased morbidity and mortality. The aim of our study was to perform a meta-analysis that included the published studies that compared mortality rates in subjects with or without hyponatremia of any degree.st 2012, using the following words: “hyponatremia” and “mortality”. Eighty-one studies satisfied inclusion criteria encompassing a total of 850222 patients, of whom 17.4% were hyponatremic. The identification of relevant abstracts, the selection of studies and the subsequent data extraction were performed independently by two of the authors, and conflicts resolved by a third investigator. Across all 81 studies, hyponatremia was significantly associated with an increased risk of overall mortality (RR = 2.60[2.31–2.93]). Hyponatremia was also associated with an increased risk of mortality in patients with myocardial infarction (RR = 2.83[2.23–3.58]), heart failure (RR = 2.47[2.09–2.92]), cirrhosis (RR = 3.34[1.91–5.83]), pulmonary infections (RR = 2.49[1.44–4.30]), mixed diseases (RR = 2.59[1.97–3.40]), and in hospitalized patients (RR = 2.48[2.09–2.95]). A mean difference of serum [Na+] of 4.8 mmol/L was found in subjects who died compared to survivors (130.1±5.6 vs 134.9±5.1 mmol/L). A meta-regression analysis showed that the hyponatremia-related risk of overall mortality was inversely correlated with serum [Na+]. This association was confirmed in a multiple regression model after adjusting for age, gender, and diabetes mellitus as an associated morbidity.An extensive Medline, Embase and Cochrane search was performed to retrieve the studies published up to October 1+] decrease is associated with an increased risk of mortality in commonly observed clinical conditions across large numbers of patients.This meta-analysis shows for the first time that even a moderate serum [Na In addition, a linear regression analysis model, weighing each study for the number of subjects enrolled, was performed to verify the independent effect of hyponatremia on mortality after the adjustment for age, gender and diabetes mellitus as an associated morbidity. It was not possible to include other co-morbidities because there were not enough data to be collected and analyzed from the selected literature. Finally, sensitivity analyses was performed considering only larger studies (including ≥1000 subjects) or those reporting the prevalence of diabetes mellitus. In addition, mean baseline serum [Na+] in subjects who eventually died or not at follow up were meta-analyzed using a random effect model.Heterogeneity was assessed using the IRelative risks (RRs) with 95% CIs were calculated using Comprehensive Meta-analysis Version 2, Biostat, . Logistic multivariate analysis was performed on SPSS  for Windows 20.1.Out of 718 retrieved articles, 637 articles were excluded for different reasons. The flow of the meta-analysis is summarized in +] in dead or alive individuals was specified in 3 of the aforementioned studies and in a further 8 studies enrolling patients with HF (n = 2), cirrhosis (n = 1), pulmonary infection (n = 2) or mixed disease (n = 3), respectively . The baseline mean difference of serum [Na+] was significantly lower in subjects who eventually died when compared to survivors (130.1±5.6 vs 134.9±5.1 mmol/L) at follow up . Sub-analysis for mean serum [Na+] in specific diseases was not performed due to insufficient data.When all 81 studies were considered, hyponatremia was significantly associated with an increased risk of overall mortality . Similar results were obtained when patients with specific diseases or series of hospitalized patients were analyzed separately , confirmed the association between hyponatremia and mortality .Sensitivity analyses performed considering only larger studies (including ≥1000 subjects), those reporting the prevalence of diabetes mellitus or those with severe hyponatremia ([Na+] (16%), and the risk of death appeared to increase linearly with serum [Na+] <140 mmol/L. Hyponatremia was an independent predictor of death either when the patients were considered as a whole, or when they were grouped based on the presence of a reduced (n = 1199) or a preserved (n = 419) ejection fraction. The MAGGIC meta-analysis was limited to patients with HF and considered studies published to the end of 2008.Hyponatremia has been associated with increased in-hospital mortality st 2012 that compared the mortality rate in human subjects with or without hyponatremia of any degree. Eighty-one published studies were selected according to specified inclusion criteria for a total of 850222 patients, of whom 17.4% were hyponatremic. This percentage is in general agreement with epidemiological data about the prevalence of hyponatremia among hospitalized patients Our meta-analysis included all of the English-language published studies up until October 1vs patients without hyponatremia ranged between 2.47 and 3.34, thus indicating that this electrolyte disorder strongly predicts prognosis of all hospitalized patients. Another interesting result of our meta-analysis is that a moderate serum [Na+] reduction  was associated with an increased risk of mortality, and a meta-regression analysis showed that the hyponatremia-related risk of overall mortality was inversely correlated with the serum [Na+]. Hence, the lower threshold considered, the higher the risk of mortality. This association was confirmed in a multiple regression model after adjusting for age, gender and diabetes mellitus. The linear increase of risk of death that we showed in our analysis is in agreement with the findings of the MAGGIC meta-analysis, which found a linear increase of mortality starting at serum [Na+] <140 mmol/L. Overall, our findings indicate that even a moderate reduction of serum [Na+] is associated with an increased risk of mortality in patients affected by multiple disease types across large numbers of hospitalized patients.The major finding of this meta-analysis is that across all groups of patients the relative risk of mortality in patients with hyponatremia Although the present meta-analysis both confirms and extends the strong association between hyponatremia and adverse outcomes such as inpatient mortality, it cannot prove a causal relation between these variables. In fact, only diabetes mellitus could be used as a possible confounder in the present study. Perhaps the major outstanding question regarding hyponatremia is whether hyponatremia contributes directly to poor outcomes or is simply a marker for severity of underlying co-morbidities, or possibly for other factors that might influence the progression of underling co-morbidities In conclusion, this study represents the first extensive and updated meta-analysis demonstrating that hyponatremia is significantly associated with an increased risk of overall mortality, and that it is a negative prognostic factor across multiple commonly observed clinical conditions, such as myocardial infarction, HF, cirrhosis and pulmonary infections. These findings might suggest the importance to correct this electrolyte disorder, even when mild, using the most appropriate strategies Checklist S1PRISMA Checklist.(DOC)Click here for additional data file.


Determine whether white matter signal fluctuation on T2* weighted BOLD contrast images are associated with aging and cerebral small vessel disease (SVD).physio) and cardiac pulsatility (i.e. fluctuations at the cardiac frequency) were calculated voxel wise and group differences were tested by ANOVA. It was also possible to calculate σphysio in 2s TR cardiac aliased whole-brain BOLD (wb-BOLD) data (N = 84) obtained from the International Consortium for Brain Mapping.Resting state BOLD data were collected with a 250 ms repetition time (TR) to achieve unaliased, ungated cardiac sampled BOLD (cs-BOLD) images on 11 young adult controls, 10 healthy older adult controls and 7 adults with extensive white matter hyperintensities (WMH) from SVD. Tissue classes (WM and GM) were segmented on T1 images. WMH were identified on FLAIR images in the SVD group. Raw physiological noise (σphysio (p = 0.184). As a verification of the cs-BOLD findings, the wb-BOLD also showed a linear aging effect of σphysio in WM. In the SVD adults, cardiac pulsatility and σphysio were lower in WMH regions compared to normal appearing white matter (NAWM) regions . Cardiac pulsatility was better able to distinguish WMH regions from NAWM than σphysio as measured by effect size .CS-BOLD metrics showed an aging and SVD effects (p<0.0005). Covariates such as thermal noise, WM volume and partial volume did not influence the significant aging effect seen on the cardiac pulsatility metric (p<0.017) but did influence the σNAWM was found to have graded increases in cardiac pulsations due to age and SVD, independently. Within SVD participants, WMH lesions had reduced physiological noise compared to NAWM. Cardiac pulsatility in resting BOLD data may provide a complementary dynamic measure of WM integrity to add to static FLAIR anatomical images. Two candidate physiological noise metrics are introduced: 1) physiological noise across the entire temporal frequency spectrum and 2) the amplitude of physiological noise specifically at the principal cardiac frequency. The former metric can be used on high or low temporal resolution BOLD data while the latter requires cardiac unaliased sampling and is expected to be more specific to cardiac effects in the time series. It is hypothesized that both physiological noise metrics within the normal appearing white matter (NAWM) will be: 1) larger in healthy elderly controls compared to healthy young controls and 2) larger in SVD patients compared to age matched elderly controls. Within the SVD cohort, a direct comparison between WMH and NAWM regions was also performed. As a post-hoc analysis, publically available resting-state BOLD data were accessed and an aging effect in WM voxels was performed to verify our first hypothesis.Two independent MRI datasets were included in this study. The primary dataset of twenty-eight participants was acquired in a cross-sectional study at Sunnybrook Health Sciences Centre and comprised three cohorts, referred to as the cardiac sampled BOLD data (cs-BOLD) . Writtenhttp://www.nitrc.org/projects/fcon_1000/A second resting-state BOLD dataset, consisting of 84 participants from the International Consortium for Brain Mapping (ICBM) study was included in the current investigation. These data are referred to as the whole-brain BOLD or wb-BOLD cohort  and downloaded from CS-BOLD data acquisition was performed using a GE 750 3 T scanner . Resting-state images of each participant were acquired axially using an EPI sequence with the following parameters: flip angle = 34°, TR/TE = 250/30 ms, imaging matrix = 64×64, FOV = 192×192 mm. The resulting voxel resolution was 3×3×5 mm, and 4 slices were acquired for a total of 510 volumes over 2∶08 min. The imaging volume was positioned axially at the superior portion of the lateral ventricles  A, B becwww.nitrc.org.The EPI resting-state scans from this dataset were acquired on a 3 T scanner with a TR = 2 seconds, TE = 50 ms, 128 volumes, 23 axial slices, and a 4×4 mm in-plane resolution. Of the 84 total scans, 40 were acquired with a slice thickness of 5.5 mm and 44 with a slice thickness of 4 mm. Information concerning this dataset and project can be found at Both the wb-BOLD and cs-BOLD datasets were preprocessed using similar steps. The skull was removed from T1 images using the brain extraction tool  Inverse matrices were used to transform tissue class masks from T1 space to EPI space and enable analysis in native subject space. WMH masks were coregistered to EPI space from FLAIR by concatenating the transformation matrices from T1 to EPI and from FLAIR to T1. After the transformation from T1 to EPI space, tissue class masks were eroded using a 3 mm full width at half maximum Gaussian kernel to reduce partial volume effects.physio, was calculated on a voxel-wise basis. The method described previously by Yacoub et al. 2EPI = σ2physio+σ2therm, was employed to subtract the variance in signal attributed to thermal noise from the total variance. σ2EPI is the total temporal variance at a particular voxel , σ2physio is the temporal variance at that voxel due to physiological processes , and σtherm2 is the temporal variance due to thermal noise. Temporal variances were calculated over the entire 500 point time course.A physiological noise metric, σphysio was normalized to each voxel’s mean signal intensity and expressed as a percentage; the average value was reported for each participant. Physiological noise was calculated by tissue type: GM, WM and WMH. In the case of wb-BOLD data, WM and WMH tissue types were merged since this dataset did not include FLAIR images.Thermal noise was measured as the average variance in a region of interest (ROI) placed outside the brain in a corner of each resting-state image; this placement was chosen to minimize contribution from the EPI ghosting artifact. The σTo determine the relative BOLD signal change at the cardiac frequency, a voxelwise “cardiac pulsatility” metric was calculated. A fast Fourier transform was applied to each voxel’s time course to transform signal fluctuations to the frequency domain. Given a TR of 0.25 seconds, the Nyquist theorem states that signal fluctuations at up to 2 Hz could be detected without aliasing. The cardiac frequency was identified using pulse oximetry data and the spectral amplitude within 0.02 Hz of the cardiac frequency was integrated and divided by the frequency domain (0.04 Hz) to obtain average amplitude. This average amplitude was then normalized to each voxel’s mean intensity. A frequency range of ±0.02 Hz was chosen based on manual evaluation of the average width of the cardiac peak. The resulting metric was a voxel wise percentage signal change at the cardiac frequency and the average value was reported for each participant and tissue type. Cardiac pulsatility was not calculated for the wb-BOLD dataset because the sampling frequency of 0.5 Hz was not sufficient to isolate BOLD fluctuations at the heart rate. A mean tissue class frequency spectrum is shown in Head motion accumulated over the cs-BOLD scan was calculated to determine whether gross motion was 1) different between groups (unpaired t-test) or 2) correlated with physiological noise metrics (Pearson’s correlation). FLIRT’s root mean squared head displacement relative to previous TR was summed over the 500 cs-BOLD volumes.physio metric, 2) WM cs-BOLD group differences on the cardiac pulsatility metric, 3) a intra-subject comparison of physiological noise between NAWM and GM, 4) ANCOVA tests were the same as in 1 and 2 but with thermal noise, white matter volume and white matter partial volume estimate as covariates of non-interest, 5) a within-SVD cohort paired t-test for the differences between NAWM and WMH, with reported Cohen’s D effect sizes for the two metrics, 6) a group comparison of head motion during cs-BOLD. Test 4 was performed evaluate the potential effect of temporal  and spatial nuisance (white matter characteristics) factors that may influence the physiological noise metrics. Finally, a linear regression model was used on the ICBM data to support test 1 above and characterize an aging effect on the σphysio metric.To address our main hypotheses, Analysis of Variance (ANOVA) tests were performed using SPSS Statistics 19 . In all cases two tail p value statistics are reported and considered significant, unless stated otherwise, at p = 0.05. The following tests were performed: 1) WM cs-BOLD group differences on the σThere was a statistically significant difference between σphysio in the YC, EC and SVD groups as determined by one-way ANOVA  = 13.5, p<0.0005). Results of post-hoc unpaired t-tests are provided in Physiological noise had homogeneous variance across the YC, EC, and SVD cohorts for all tissue classes . Normality was evaluated for all tissue classes using the Shapiro-Wilk test .An illustration of the cardiac pulsatility images for three representative participants is shown in physio and cardiac pulsatility remained significant when accounting thermal noise as a covariate  = 4.8, p<0.02 and F = 8.8, p<0.001, respectively). After including WM volume and WM partial volume estimate as two additional covariates in the cs-BOLD data, the F statistic for σphysio was not significant  = 1.8, p = 0.18), however cardiac pulsatility remained significant  = 4.6, p<0.02). This may be attributed to the fact that physiological noise was calculated over the entire power spectrum and therefore may be less specific to cardiac pulsation effects than cardiac pulsatility.The cs-BOLD group differences in σphysio were reduced in WMH regions compared to NAWM regions . NAWM volume was not correlated with either metric (p = 0.19 and p = 0.57).Within the SVD cohort, cardiac pulsatility and σCumulative head motion over 500 volumes was not significantly different between EC and SVD cohorts . Cumulative head motion was also not significantly correlated to physiological noise in either the EC or SVD cohort . Head motion was not correlated to age in any of the cs-BOLD cohorts .physio increased with age in WM for the wb-BOLD (TR = 2s). A linear regression showed a significant age effect  and remained significant when slice thickness was included in the model (p<0.007). Residuals were assessed using a plot of residuals versus predicted values and a quantile-quantile (QQ) plot. The residuals were randomly distributed. Two wb-BOLD sub-groups were chosen to match the cs-BOLD data . We found a significant age-related WM σphysio difference  = 5.8, p<0.02), which remained significant with thermal noise as a covariate  = 5.7, p<0.021). A tissue type contrast between GM and WM was performed and all 84/84 participants had a significantly greater σphysio in GM than in WM .physio WM of 0.99 and 0.94 for males and females respectively, p = 0.1 and t = 1.65). In the smaller cs-BOLD dataset, the effect of sex on physiological noise was not significant in any of the cohorts. The mean σphysio WM for males and females respectively were 0.60 and 0.63 in the YC cohort ; 1.1 and 0.9 in the EC cohort ; and 1.3 and 0.97 in the SVD cohort .The effect of sex on physiological noise was not significant in the larger wb-BOLD dataset (mean σThis study found that whole brain cardiac sampled BOLD (TR = 0.25 s) could be used to identify aging and small vessel disease pathology effects within white matter. Physiological noise in cs-BOLD data increased with age in the NAWM of healthy adults, an effect that could not be explained by thermal noise and was corroborated by a parallel analysis performed on publically available whole brain BOLD data (TR = 2 s). Significant cs-BOLD findings were also observed when considering the older participants. First, physiological noise was increased in NAWM in adults with SVD compared to age-matched controls. Second, within the SVD cohort itself, physiological noise was decreased in the regions defined by the white matter hyperintensities (WMH) when compared to NAWM.A FLAIR MR image provides excellent contrast to visualize WMH as manifestations of SVD. In this study we provide evidence that global WM metrics of dynamic and/or pulsatile information can also be used to differentiate WM tissue types and groups. These approaches may help to advance our understanding SVD given that others argue that static MR imaging approaches may be inadequate Regions where WMH were present showed the opposite trend compared to the NAWM aging observation, in the sense that physiological noise and cardiac pulsatility were decreased in WMH compared to NAWM. Reduced cardiac pulsatility in the WMH lesion itself may be explained in part by the following. First, Brown et al. found a decreased concentration of afferent vessels within WMH regions compared to NAWM on histological analysis physio findings from the cs-BOLD data but the two datasets had some discrepant imaging parameters. In addition to the TR difference, 2 s for whole brain versus 0.25 s for unaliased cardiac sampling, TE, slice thickness and voxel dimensions were different, which could influence σphysio. Second, the cs-BOLD data had a relatively small SVD cohort that consisted of adults with extensive SVD, of which two were individuals with a CADASIL diagnosis. In addition the SVD and EC groups were not well matched in age and sex. Another issue was the lack of FLAIR images from the wb-BOLD dataset that would be used to characterize the WM as NAWM or WMH, as was performed in the cs-BOLD data. Finally, atrophy in WM is a consequence of aging physio as non-significant, however, the cardiac pulsatility aging effect did remain significant (p<0.021) and provides some support for the use of the cardiac pulsatility as a sensitive physiological metric.This study has limitations that are addressed by the following. First, the wb-BOLD data served as a means to validate the σThe cs-BOLD sequence used a short TR (0.25 s) to sample unaliased cardiac signals at the expense of brain coverage in the z-direction (20 mm). We established the proof of principle that global WM indices of physiological noise can be used, however, future work could involve voxel-wise analyses to identify specific locations of heightened cardiac pulsatility effects. Other potentially useful areas of future work could include characterization of inflow effects The current study made use of a stock BOLD fMRI pulse sequence with reduced TR (0.25 s) and a short scan duration (2∶08 m) to demonstrate increased physiological noise and cardiac pulsatility in NAWM in aging and additionally the presence of SVD. The WMH lesion volume itself had reduced physiological noise compared to NAWM, while the physiological noise in NAWM of adults with SVD was higher compared to NAWM in elderly controls. White matter cardiac frequency physiological signal in resting state BOLD data may reflect the increased cerebral blood volume fluctuations that are due to pulsatile energy that is transmitted down the vascular tree to the small vessels. This relatively straightforward technique could prove useful in the clinical characterization of SVD abnormalities that are not readily identified with conventional static MR imaging.


A) ion channels are important drug targets for treatment of neurological and psychiatric disorders. Finding GABAA channel subtype selective allosteric modulators could lead to new improved treatments. However, the progress in this area has been obstructed by the challenging task of developing functional assays to support screening efforts and the generation of cells expressing functional GABAA ion channels with the desired subtype composition. To address these challenges, we developed a yellow fluorescent protein (YFP)-based assay to be able to study allosteric modulation of the GABAA ion channel using cryopreserved, transiently transfected, assay-ready cells. We show for the first time how the MaxCyte STX electroporation instrument can be used to generate CHO-K1 cells expressing functional GABAA α2β3γ2 along with a halide sensing YFP-H148Q/I152L (YFP-GABAA2 cells). As a basis for a cell-based assay capable of detecting allosteric modulators, experiments with antagonist, ion channel blocker and modulators were used to verify GABAA subunit composition and functionality. We found that the I− concentration used in the YFP assay affected both basal quench of YFP and potency of GABA. For the first time the assay was used to study modulation of GABA with 7 known modulators where statistical analysis showed that the assay can distinguish modulatory pEC50 differences of 0.15. In conclusion, the YFP assay proved to be a robust, reproducible and inexpensive assay. These data provide evidence that the assay is suitable for high throughput screening (HTS) and could be used to discover novel modulators acting on GABAA ion channels.The γ-aminobutyric acid A (GABA A ion channels mediate inhibitory neurotransmission in the central nervous system. They are members of the pentameric, ligand-gated ion channel family composed of around 18 different subunits which can give rise to a high variability in subunit composition, function and pharmacology A ion channels are important drug targets for neurological and psychiatric disorders such as sedation, anaesthesia, epilepsy, anxiolysis and muscle relaxation. Nevertheless, there is scope for development of new and improved drugs with subtype selectivity to overcome unwanted side effects of current treatments A ion channel modulation and identify compounds that could address this unmet medical need.GABA− channels such as GABAA. For a functional assay to be suitable for HTS of large compound libraries it should preferably be sensitive, fast, inexpensive and adaptable to high-density format. Patch-clamp electrophysiology is considered the “gold standard” for studying ion channels due to its sensitivity, however, it is costly and often limited in throughput. Binding assays are simple and fast but do not necessarily correlate with functional activity. Membrane potential assays using fast responding fluorescent dyes show medium to high sensitivity, give a robust signal under HTS conditions, have a good dynamic range and are high throughput A ion channel, A modulators we established a YFP assay to study GABAA activity and modulation. The method was developed by Galietta and colleagues −, NO3−, Br− and Cl− enter the cell, bind to YFP and quench its fluorescence. Agonist-dependent quench of YFP fluorescence can then be measured with a fluorescent reader and used to determine channel activation, inhibition and modulation. The YFP assay has the benefit of being a noninvasive technique with the ability to measure fast responses. In addition, ions flux in the natural direction of the GABAA ion channel in comparison to a membrane potential assay where the electrochemical gradient is artificially polarized and a chloride efflux is measured. Furthermore, with no external addition of fluorescent dye the cost is reduced and the risk of GABA modulatory effects from the dye is avoided. A significant advantage of the YFP assay is that it does not require stable cell lines to obtain full dynamic range as only transfected cells produce a signal and simultaneous transfection of YFP-H148Q/I152L and ion channel subunits show high degree of co-expression There are several techniques for monitoring activity of Cl7–3.5×108 cells for optimization work and large scale flow electroporation of up to 1010 cells with high transfection efficiency and reproducibility.Difficulties in establishing stable cell lines along with the large investment in time and resources have made large scale transient transfection an attractive way of generating cells for assays. Among transfection technologies electroporation is an efficient way of introducing DNA into cells without the need for chemical transfection reagents. The mechanism for DNA uptake into the cell involves electrophoretic association of DNA with the cell membrane followed by DNA insertion in the membrane and entry into the cell AA α2β3γ2 expressed transiently in Chinese Hamster Ovary (CHO-K1) cells, to confirm the applicability of cryopreserved transiently transfected cells, and to test the assay's suitability for screening of modulators. We found that cryopreserved transiently transfected assay-ready cells showed robust performance in the YFP assay and enabled easy handling and scale-up. Our results show that the YFP assay can be established to study agonist activation and modulation of the GABAA channel.The YFP assay has previously been developed for CFTR Diazepam, Alpidem, Lorazepam, Clobazam, Desmethyl-clobazam, TPA-023, L-838417 and Bicuculline were synthesized at AstraZeneca. Ham's F-12 medium, Picrotoxin, GABA and all other chemicals were purchased from Sigma.A subunits α2, β3 and γ2  were inserted into pGen-IRES-neo2 vectors The cDNA of YFP (Genbank accession number AY818378) with H148Q and I152L mutations was inserted into the pcDNA3.1 vector using 5′ BamHI and 3′ NotI sites. Human GABA2. Transient transfection was performed using MaxCyte STX electroporation instrument  with CHO cell line specific electroporation protocol. The cells were split one day prior to electroporation to ensure that cells were in the log phase growth at time of transfection. Cells were harvested with Accutase (PAA Laboratories), pelleted at 250 g for 10 minutes, rinsed with MaxCyte Electroporation Buffer , pelleted again and resuspended in MaxCyte Electroporation Buffer at a density of 1×108 cells/ml. CHO-K1 cells were electroporated simultaneously with four plasmids using a total amount of 300 µg DNA per 1×108 cells; YFP-H148Q/I152L (150 µg) and GABAA  plasmids. Following electroporation, cells were incubated at 37°C and 5% CO2 for 20 minutes to recover. Cells were then diluted in culture medium and centrifuged 250 g for 10 minutes. Pelleted cells were resuspended to 5–10×106 cells/ml in Ham's F12 with 20% fetal bovine serum and 10% DMSO, and cryopreserved using controlled-rate cryo containers . Cryopreserved assay-ready cells were used for all experiments.CHO-K1 cell line  was cultured in Ham's F-12 medium supplemented with 10% fetal bovine serum and incubated at 37°C and 5% CO2, cells were washed three times on an ELx405 Select Deep Well Microplate Washer (BioTEK), exchanging 50 µl culture medium with 30 µl HBSS buffer supplemented with 20 mM Hepes. Plates were incubated with buffer for 1 h at 37°C and 5% CO2. Cell plates were assayed on a FLIPR Tetra (Molecular Devices) using excitation filter of 470–495 nm and emission filter of 515–575 nm. Starting with 30 µl buffer in each well, cells were pre-incubated with 10 µl compound for 15 minutes. 20 µl GABA in NaI buffer pH 7.3  was added to activate the ion channel and induce an agonist-dependent quench of YFP fluorescence. Data was acquired for 120 s with fluorescence recording at 1 s intervals where GABA/NaI solution was added after 10 s of baseline reading. Compounds were initially solubilized to a concentration of 10 mM in DMSO and then diluted in HBSS buffer with 20 mM Hepes. Final DMSO concentration in the assay was 0.02% for modulators and at 1% for Picrotoxin and Bicuculline. DMSO only controls were included in every experiment and there was no detectable effect of DMSO on GABA channel activation. GABA solutions were prepared fresh for every experiment and 3-fold serial dilutions were performed on a 384-well microplate in NaI buffer using a Biomek FX (Beckman Coulter) liquid handling device.Cryopreserved transiently transfected cells were thawed and plated in 384-well poly-D-lysine-coated plates at a density of 15000 cells/well using a Multidrop Combi Reagent Dispenser (Thermo Scientific). After 24 h incubation at 37°C and 5% COinit – Ffinal)/Finit*100 where Finit and Ffinal are the initial and final values of fluorescence respectively. GABA concentration-response curves were fitted with the Hill equation, F  =  Finit/(1+(EC50/[GABA])nH), where F is the fluorescence corresponding to a GABA concentration [GABA], Finit is the initial fluorescence value, EC50 is the concentration that elicits half-maximal response and nH is the Hill coefficient. Curve fits were performed using least-squares fitting routine .Data at 1–10 s was adjusted to a baseline of 100% and results were then extracted as % quench at 120 s. % quench is defined as  between two EC50 values.To calculate the pECA ion channel for the YFP assay, four different plasmids  were electroporated simultaneously using MaxCyte STX. DNA ratio for subunits of GABAA α2β3γ2 has previously been optimized by Liu et al. A  to YFP-H148Q/I152L plasmid. Results showed that 300 µg of total DNA containing 50% YFP-H148Q/I152L plasmid was optimal for functionality of GABAA in CHO-K1 cells and generated the largest assay window in a GABA concentration-response experiment (data not shown). Cells were cryopreserved directly after electroporation and no change in assay performance was identified after at least 6 months storage in −150°C.To generate cells expressing the GABA− concentrations  by exposing cells to NaI buffer in the absence and presence of GABA . To further verify that I− was transported through the GABAA ion channel 100 µM Picrotoxin, a non-competitive GABAA antagonist, was added to YFP-GABAA2 cells 15 minutes prior to stimulation with buffer containing different I− concentrations. Picrotoxin reduced basal quench to background levels  when comparing 5 mM and 10 mM I− and p<0.05 (*) when comparing 10 mM and 20 mM I−  to 0.20 µM±0.02 µM (n = 3) which equals a 1.7 fold EC50 shift. To further investigate the YFP assay's ability to distinguish GABA modulation, concentration-responses of GABA in the presence of 7 known modulators were determined. A pooled estimate of variability was used to calculate the standard error of the difference between two compounds' pEC50 values (average of 3 occasions). The data show that known modulators yielding a ≥1.40 times shift in GABA EC50, or a difference in pEC50 ≥0.15, compared to GABA, could be considered to have a statistically significant effect on GABA potency with 95% confidence, when averaging across 3 occasions ; Fisher rat thyroid; 3T3 and CHO-K1 cells − concentration in the YFP assay is dependent on the cell background and on the characteristics of the ion channel used. Furthermore, the influence of I− concentration on basal quench, as well as our data showing decrease in GABA potency with increasing I− concentration, demonstrates the importance of careful optimization to identify the most suitable assay concentration. Robertson describes an increase in negative current at negative potentials when performing single-electrode voltage clamp of GABA stimulated dorsal root ganglion neurons in the presence of I− compared to Cl−− prolongs the opening time of the ion channel possibly by interacting and modulating the kinetics, thereby increasing the time that GABA binds to the ion channel. Based on this, it is possible that the modulating effect of I− is concentration dependent and as a consequence affects GABA potency, as observed in our assay. Furthermore, control experiments using Picrotoxin, a non-competitive GABAA antagonist, supported the theory that I− influx occurs selectively through the GABAA ion channel.Genetically modified YFP-H148Q/I152L has the capacity to bind small anions resulting in quench of its fluorescence. The relative affinity of anions to YFP-H148Q/I152L are IA ion channel subunit composition, assay and cell type used. There are only few reports in the literature stating GABA EC50 values using a α2β3γ2 subunit composition. It has been shown that GABA sensitivity is increased for αβ composition compared to αβγ A2 cells in the YFP assay we obtained a GABA EC50 of 0.34 µM±0.08 µM. Lui et al. obtained a GABA EC50 of 2.2 µM with HEK 293 cells expressing the α2β3γ2 ion channel subtype in a membrane potential assay 50 may be accounted for by the different cell backgrounds used, HEK293 and CHO-K1. In addition, the membrane potential assay measures outward current of ions whereas the YFP assay measures influx, which is the physiological current of ions upon GABA stimulation. To conclude, the aim with the YFP assay is not to obtain absolute potency measurements, but to measure the modulation of GABA activation of the channel in order to compare different modulators.Differences in GABA potency have been reported depending on GABAA α2β3γ2 optimized to yield a composition of two α2, two β3 and one γ2 subunit stoichiometry. Functionality of the GABAA ion channel was confirmed by agonist activation using GABA as well as inhibition using Bicuculline and Picrotoxin. The benzodiazepine site is located at the interface of the α and γ subunits and a correct subunit composition of the channel is required to yield agonist modulatory effect with a benzodiazepine-class compound. We report modulation of GABA activation using different positive allosteric modulators. The strong positive modulator Diazepam shifted GABA EC50 1.7 fold, which corresponds to a pEC50 difference of 0.23, compared to GABA alone. This may be considered a small shift and can be compared to a pEC50 difference of 0.41 generated with VSD assay by Liu and coworkers 50 differences as small as 0.15 when averaging across 3 occasions. A direct comparison of EC50 values of these 7 different modulators compared to literature values is however not relevant, given the difference in modulator effect observed using different subunit compositions of the GABA channel and the variation in EC50 values reported from different cell backgrounds and assays. The ability to modulate GABA potency upon modulator addition confirms that our YFP-GABAA2 cells express functional GABAA α2β3γ2 ion channels with correct subunit composition containing a benzodiazepine binding site. It further implies that the assay can be used to screen for modulators and rank order modulators with small pEC50 differences. However, using the current assay protocol, we were not able to detect a statistically significant effect of known weak positive allosteric modulators. In mouse fibroblast L(tk−) cells expressing GABA α2β3γ2, relative in vitro efficacy of TPA-023 or L-838417 was reported to be 11% and 34% respectively, measured as the potentiation of GABA EC20 compared to a 100% response from a classical benzodiazepine full agonist, chlordiazepoxide − concentration. Using different I− concentrations we observed a trend of increased positive modulator efficacy with decreased I− concentrations, (data not shown). However, a consequence of decreased I− concentration is a decreased assay window and an increased variability of the assay. Taken together, increasing the sensitivity of the YFP assay by decreasing the I− concentration results in reduced assay reproducibility and robustness. Even though there is an obvious challenge of using the YFP assay for screening of positive GABAA modulators in an HTS format, our initial results indicate that the assay produces robust data for moderate to strong modulators.DNA ratio used for transfection does not necessarily correlate with protein subunit expression. Functional and pharmacological experiments are therefore needed to ensure correct subunit assembly and ion channel function A. To find subtype selective modulators of GABAA, cells with different subunit compositions would need to be generated and used in screening. Our work demonstrates how to successfully generate YFP-GABAA2 cells. To generate transiently transfected cells expressing GABAA with a different set of subunits, DNA ratio optimization could be evaluated with functional characterization similar to what has been described here. In conclusion, using the YFP assay with transiently transfected CHO-K1 cells provides a flexible means for discovering novel GABAA modulators.Although it is beyond the scope of the current study, screening a larger set of compounds would confirm the YFP assay's robustness and provide an answer about the utility of the assay in HTS to identify positive allosteric modulators of GABA