Predictors of Chikungunya rheumatism: a prognostic survey ancillary to the TELECHIK cohort study

Introduction

Long-lasting relapsing or lingering rheumatic musculoskeletal pain (RMSP) is the hallmark of Chikungunya virus (CHIKV) rheumatism (CHIK-R). Little is known on their prognostic factors. The aim of this prognostic study was to search the determinants of lingering or relapsing RMSP indicative of CHIK-R.

Methods

Three hundred and forty-six infected adults (age ≥ 15 years) having declared RMSP at disease onset were extracted from the TELECHIK cohort study, Reunion island, and analyzed using a multinomial logistic regression model. We also searched for the predictors of CHIKV-specific IgG titres, assessed at the time of a serosurvey, using multiple linear regression analysis.

Results

Of these, 111 (32.1%) reported relapsing RMSP, 150 (43.3%) lingering RMSP, and 85 (24.6%) had fully recovered (reference group) on average two years after acute infection. In the final model controlling for gender, the determinants of relapsing RMSP were the age 45-59 years (adjusted OR: 2.9, 95% CI: 1.0, 8.6) or greater or equal than 60 years (adjusted OR: 10.4, 95% CI: 3.5, 31.1), severe rheumatic involvement (fever, at least six joints plus four other symptoms) at presentation (adjusted OR: 3.6, 95% CI: 1.5, 8.2), and CHIKV-specific IgG titres (adjusted OR: 3.2, 95% CI: 1.8, 5.5, per one unit increase). Prognostic factors for lingering RMSP were age 45-59 years (adjusted OR: 6.4, 95% CI: 1.8, 22.1) or greater or equal than 60 years (adjusted OR: 22.3, 95% CI: 6.3, 78.1), severe initial rheumatic involvement (adjusted OR: 5.5, 95% CI: 2.2, 13.8) and CHIKV-specific IgG titres (adjusted OR: 6.2, 95% CI: 2.8, 13.2, per one unit increase). CHIKV specific IgG titres were positively correlated with age, female gender and the severity of initial rheumatic symptoms.

Conclusions

Our data support the roles of age, severity at presentation and CHIKV specific IgG titres for predicting CHIK-R. By identifying the prognostic value of the humoral immune response of the host, this work also suggest a significant contribution of the adaptive immune response to the physiopathology of CHIK-R and should help to reconsider the paradigm of this chronic infection primarily shifted towards the involvement of the innate immune response.     

The oxidative burst reaction in mammalian cells depends on gravity

Gravity has been a constant force throughout the Earth’s evolutionary history. Thus, one of the fundamental biological questions is if and how complex cellular and molecular functions of life on Earth require gravity. In this study, we investigated the influence of gravity on the oxidative burst reaction in macrophages, one of the key elements in innate immune response and cellular signaling. An important step is the production of superoxide by the NADPH oxidase, which is rapidly converted to H₂O₂ by spontaneous and enzymatic dismutation. The phagozytosis-mediated oxidative burst under altered gravity conditions was studied in NR8383 rat alveolar macrophages by means of a luminol assay. Ground-based experiments in “functional weightlessness” were performed using a 2 D clinostat combined with a photomultiplier (PMT clinostat). The same technical set-up was used during the 13th DLR and 51st ESA parabolic flight campaign. Furthermore, hypergravity conditions were provided by using the Multi-Sample Incubation Centrifuge (MuSIC) and the Short Arm Human Centrifuge (SAHC). The results demonstrate that release of reactive oxygen species (ROS) during the oxidative burst reaction depends greatly on gravity conditions. ROS release is 1.) reduced in microgravity, 2.) enhanced in hypergravity and 3.) responds rapidly and reversible to altered gravity within seconds. We substantiated the effect of altered gravity on oxidative burst reaction in two independent experimental systems, parabolic flights and 2D clinostat / centrifuge experiments. Furthermore, the results obtained in simulated microgravity (2D clinorotation experiments) were proven by experiments in real microgravity as in both cases a pronounced reduction in ROS was observed. Our experiments indicate that gravity-sensitive steps are located both in the initial activation pathways and in the final oxidative burst reaction itself, which could be explained by the role of cytoskeletal dynamics in the assembly and function of the NADPH oxidase complex.     

Note: A Convenient Method for the Preparation of N2, N2-Dimethylguanosine

Abstract

The preparation of N², N²-dimethylguanosine is described. The use of the 2-(p-nitrophenyl)ethyl group instead of the benzyl protecting group for the O⁶ position of the guanine ring resulted in better yields and shorter protocols.     

Neutron-encoded Signatures Enable Product Ion Annotation From Tandem Mass Spectra

We report the use of neutron-encoded (NeuCode) stable isotope labeling of amino acids in cell culture for the purpose of C-terminal product ion annotation. Two NeuCode labeling isotopologues of lysine, ¹³C₆¹⁵N₂ and ²H₈, which differ by 36 mDa, were metabolically embedded in a sample proteome, and the resultant labeled proteins were combined, digested, and analyzed via liquid chromatography and mass spectrometry. With MS/MS scan resolving powers of ∼50,000 or higher, product ions containing the C terminus (i.e. lysine) appear as a doublet spaced by exactly 36 mDa, whereas N-terminal fragments exist as a single m/z peak. Through theory and experiment, we demonstrate that over 90% of all y-type product ions have detectable doublets. We report on an algorithm that can extract these neutron signatures with high sensitivity and specificity. In other words, of 15,503 y-type product ion peaks, the y-type ion identification algorithm correctly identified 14,552 (93.2%) based on detection of the NeuCode doublet; 6.8% were misclassified (i.e. other ion types that were assigned as y-type products). Searching NeuCode labeled yeast with PepNovo⁺ resulted in a 34% increase in correct de novo identifications relative to searching through MS/MS only. We use this tool to simplify spectra prior to database searching, to sort unmatched tandem mass spectra for spectral richness, for correlation of co-fragmented ions to their parent precursor, and for de novo sequence identification.The ability to make de novo sequence identifications directly from tandem mass spectra has long been a holy grail of the proteomic community. Such a capability would wean the field from its reliance upon sequenced genome databases. Even for organisms with fully annotated genomes, events such as single nucleotide polymorphisms, alternative splicing, gene fusion, and a host of other genomic transformations can result in altered proteomes. These alterations can vary from cell to cell and individual to individual. Thus, one could argue that the most valuable proteomic information, the individual and cellular proteome variation from the genome, remains elusive (1). This problem has received considerable attention; that said, it is not easy to de novo correlate spectrum to sequence in a large-scale, automated fashion (2–6). Improvements in mass accuracy have helped, but routine, reliable de novo sequencing without database assistance is not standard (7–10).A primary means to facilitate de novo spectral interpretation is the simple annotation of m/z peaks in tandem mass spectra as either N- or C-terminal. We and others have investigated this seemingly simple first step. Real-world spectra, however, are complex. Difficulties often arise in determining the charge state of the fragment or in differentiating between fragment ions and peaks arising from neutral loss, internal fragmentation, or spectral noise, both electronic and chemical. Several strategies have focused on product ion annotation. These approaches have included manipulation of the N-terminus basicity combined with electron transfer dissociation (ETD)¹ (11–13). This approach can yield mostly N-terminal fragments for peptides having only two charges. However, it requires both ETD and the protease LysN. Other methods have used differential labeling of N- and C-terminal peptides to shift either one or the other product ion series, by either metabolic or chemical means (14–18). Metabolic incorporation of amino acids is an efficient method of introducing distinctive labels that eliminates in vitro labeling, but this method requires that the sample be amenable to cell culture (19, 20). Additionally, it may be difficult to achieve complete labeling in complex systems. Several other approaches used to introduce heavy isotopes onto one terminus have been investigated, including trypsin digestion in ¹⁸O water (21–23), differential isotopic esterification (24, 25), derivatization of the C-terminal carboxylate by p-bromophenethylamine (8, 26), N-terminal derivatization with sulfonic acid groups (27, 28), and formaldehyde labeling via reductive amination (29–31). These chemical modifications are introduced after cell lysis, often immediately prior to analysis. Although chemical labeling strategies can be used with a variety of samples, difficulties can arise from differences in labeling efficiency between samples, and often a clean-up step is required following labeling, which may lead to sample loss. No matter the labeling method, in this regime, the two precursors must be separately isolated, fragmented, and analyzed either together or separately. The recognition and selection of the broadly spaced doublet in real time also are necessary. These requirements have limited the utility of these approaches. Our own laboratory discovered that the c- and ^●z-type product ions generated from either electron capture dissociation or ETD have distinct chemical formulae and therefore can always be distinguished based on accurate mass alone (32). The problem with this approach is that extremely high mass accuracy (<500 ppb) is required in order to distinguish these product ion types above ∼600 Da in mass. Thus, the majority of the product ions within a spectrum cannot be readily mapped to either terminus with high confidence.Despite these difficulties, we assert that robust de novo sequencing methodology would benefit greatly from a simple method that could be used to distinguish N- and C-terminal product ions with high accuracy and precision. Ideally, the approach would work regardless of the choice of proteolytic enzyme or dissociation method. Recently, we described a new technology for protein quantification called neutron encoding (NeuCode) (33). NeuCode embeds millidalton mass differences into peptides and proteins by exploiting the mass defect induced by differences in the nuclear binding energies of the various stable isotopes of common elements such as C, N, H, and O. For example, consider the amino acid lysine, which has eight additional neutrons (+8 Da). One way to synthesize this amino acid is to add six ¹³C atoms and two ¹⁵N atoms (+8.0142 Da). Another isotopologue could be constructed by adding eight ²H atoms (+8.0502). These two isotopologues differ by only 36 mDa; peptide precursors containing both of these amino acids would appear as a single, unresolved precursor m/z peak at a mass resolving power of less than ∼100,000. However, under high resolving powers (i.e. greater than ∼100,000 at m/z 400), this doublet is resolved. We first developed this NeuCode concept in the context of metabolic labeling, akin to stable isotope labeling with amino acids in cell culture (SILAC), except that instead of the precursor partners being separated by 4 to 8 Da, they are separated by only 6 to 40 mDa. For quantitative purposes, NeuCode promises to deliver ultraplexed SILAC (>12) without increasing spectral complexity.We reasoned that the isotopologues of Lys that permit NeuCode SILAC would generate a distinct fingerprint on C-terminal product ions. Specifically, peptides that have been labeled with NeuCode SILAC and digested with LysC uniformly contain Lys at the C terminus. Upon MS/MS, all C-terminal product ions should present as doublets (with duplex NeuCode), whereas N-terminal products will be detected as a single m/z peak. The very close m/z spacing of the NeuCode SILAC partners will ensure that each partner is always co-isolated and that the signatures are visible only upon high-resolving-power mass analysis. Here we investigate the combination of NeuCode SILAC and high-resolving-power MS/MS analysis to allow the straightforward identification of C-terminal product ions.

Sample Preparation

Saccharomyces cerevisiae strain BY4741 Lys1Δ was grown in defined synthetic complete (SC, Sunrise Science, San Diego, CA) drop-out media with either heavy 6C¹³/2N¹⁵ lysine (+8.0142 Da, Cambridge Isotopes, Tewksbury, MA), or heavy 8D (+8.0502 Da, Cambridge Isotopes). Cells were propagated to a minimum of 10 doublings. At mid-log phase, cells were harvested via centrifugation at 3,000 × g for 3 min and then washed three times with chilled double distilled H₂O. Cell pellets were resuspended in 5 ml lysis buffer (50 mm Tris pH 8, 8 m urea, 75 mm sodium chloride, 100 mm sodium butyrate, 1 mm sodium orthovanadate, protease and phosphatase inhibitor tablet), and protein was extracted via glass bead milling (Retsch, Haan, Germany). Protein concentration was measured via BCA (Pierce). Cysteines in the yeast lysate were reduced with 5 m dithiothreitol at ambient temperature for 30 min, alkylated with 15 mm iodoacetamide in the dark at ambient temperature for 30 min, and then quenched with 5 mm dithiothreitol. 50 mm tris (pH 8.0) was used to dilute the urea concentration to 4 m. Proteins were digested with LysC (1:50 enzyme:protein ratio) at ambient temperature for 16 h. The digestion was quenched with TFA and desalted with a tC18 Sep-Pak (Waters, Etten-Leur, The Netherlands). Samples were prepared by mixing 6C¹³/2N¹⁵ (+8.0412 Da) and 8D (+8.0502 Da) labeled peptides in 1:1 ratios by mass. For strong cation exchange fractionation, peptides were dissolved in 400 μl of strong cation exchange buffer A (5 mm KH₂PO₄ and 30% acetonitrile; pH 2.65) and injected onto a polysulfoethylaspartamide column (9.4 mm × 200 mm; PolyLC) attached to a Surveyor LC quarternary pump (Thermo Electron, West Chester, PA) operating at 3 ml/min. Peptides were detected by photodiode array detector (Thermo Electron, West Chester, PA). Fractions were collected every 2 min starting at 10 min into the following gradient: 0–2 min at 100% buffer A, 2–5 min at 0%–15% buffer B (5 mm KH₂PO₄, 30% acetonitrile, and 350 mm KCl (pH 2.65)), and 5–35 min at 15%–100% buffer B. Buffer B was held at 100% for 10 min. Finally, the column was washed with buffer C (50 mm KH₂PO₄ and 500 mm KCl (pH 7.5)) and water before recalibration. Fractions were collected by hand every 2 to 3 min starting at 10 min into the gradient and were lyophilized and desalted with a tC18 Sep-Pak (Waters).

LC-MS/MS

Samples were loaded onto a 15-cm-long, 75-μm capillary column packed with 5 μm Magic C18 (Michrom, Auburn, CA) particles in mobile phase A (0.2% formic acid in water). Peptides were eluted with mobile phase B (0.2% formic acid in acetonitrile) over a 120-min gradient at a flow rate of 300 nl/min. Eluted peptides were analyzed by an Orbitrap Elite mass spectrometer. For the nonfractionated samples, mass spectrometer instrument methods comprised one MS¹ scan followed by data-dependent MS² scans of the five most intense precursors. A survey MS¹ scan was performed by the Orbitrap at 30,000 resolving power to identify precursors to sample for tandem mass spectrometry, and this was followed by an additional MS¹ scan at 480,000 resolving power (at m/z 400; actual mass resolving power of 470,700). Data-dependent tandem mass spectrometry was performed via beam-type collisional activated dissociation (HCD) in the Orbitrap at a resolving power of 15,000, 60,000, 120,000, or 240,000 and a collision energy of 30. Preview mode was enabled, and precursors of unknown charge or with a charge of +1 were excluded from MS² sampling. For experiments comparing the duty cycle and resolving power required in order to distinguish y-ion doublets, MS¹ and MS² target ion accumulation values were set to 5 × 10⁵ and 5 × 10⁴, respectively. For all other experiments, MS¹ target accumulation values were set to 1 × 10⁶ and MS² accumulation values were set to 4 × 10⁵. Dynamic exclusion was set to 30 s for −0.55 m/z and +2.55 m/z of selected precursors. For ETD analysis, data-dependent top-five mass spectrometry was performed at a resolving power of 240,000 (m/z 400; actual MS² mass resolving power of 271,000) (34). ETD accumulation values were set to 1 × 10⁶ for MS¹ target accumulation and 4 × 10⁵ for MS² target accumulation. The fluoranthene reaction time was set to 100 ms. For the high-pH strong cation exchange fractions, data-dependent tandem mass spectrometry was performed via HCD at a resolving power of either 60,000 or 120,000 and a collision energy of 30. Preview mode was enabled, and precursors of unknown charge or with a charge of +1 were excluded from MS² sampling. MS¹ targets were set to 1 × 10⁶, and MS² accumulation values were set to 4 × 10⁵. Dynamic exclusion was set to 45 s for −0.55 m/z and +2.55 m/z of selected precursors. Analysis by use of a wide isolation window was performed on an Orbitrap Fusion. MS¹ analysis was performed at 450,000 resolving power (m/z 200), and MS² analysis was performed at 120,000 resolving power (m/z 400). Data-dependent top-N mass spectrometry was performed, with precursors selected from sequential 25-Da windows. HCD was performed twice on the same precursor, first by use of a quadrupole isolation width of 0.7 m/z for peptide identification, and then using 25 m/z quadrupole isolation. Fragment ions were analyzed in the Orbitrap at a mass resolving power of 120,000 (m/z 400). MS¹ and MS² target accumulation values were set to 2 × 10⁵ and 5 × 10⁴, respectively.

Data Analysis

Thermo.raw files were converted to searchable DTA text files using the Coon OMSSA Proteomic Analysis Software Suite (COMPASS) (35). DTA files containing exclusively y-ions were generated using an in-house algorithm. DTA files were searched against the UniProt yeast database (version 132) with Lys-C specificity using the Open Mass Spectrometry Search Algorithm (OMSSA), version 2.1.9 (36). Methionine oxidation was searched as a variable modification. Cysteine carbamidomethylation and the mass shift imparted by the lysine isotopolgues were searched as fixed modifications. For MS² scans performed at a resolving power of 60,000, 120,000, or 240,000, a shift of +8.0142, representing the mass shift of the ¹³C₆¹⁵N₂ isotopologue, was searched. For MS² scans performed at 15,000 resolving power, the average shift of the ¹³C₆¹⁵N₂ and ⁸H₂ isotopologues (+8.0322) was searched. For all analyses, the precursor mass was obtained from the 480,000 MS scan. The precursor mass tolerance was defined as 50 ppm, and the fragment ion mass tolerance was set to 0.01 Da. A histogram of precursor mass error at different search tolerances is presented in supplemental Fig. S1. Using the COMPASS software suite, obtained search results were filtered to 1% FDR based on E-values. y-ion doublets were extracted from raw files using an in-house algorithm explained in the supplemental information. Briefly, an ensemble of three different machine learning models was used to score each MS/MS spectral peak for C-terminal product ion prediction. To train our ensemble learner to correctly distinguish C-terminal product ion peaks from N-terminal product ion peaks and noise peaks within our experimental MS/MS spectra, we generated a representative training set of spectral data. Instances used for training and test sets were peaks acquired only from MS/MS spectra associated with a peptide identification. Peaks with a signal-to-noise value of less than 5 were not used. Feature information for each training/testing instance was extracted from raw spectral data. Seven MS/MS spectral features were selected to generate training and test set data: (1) “has doublet” (evaluated as “true” only if a spectral peak could be found at the predicted m/z of the peak''s “heavy” partner), (2) “signal-to-noise” (discretized using a scale of 1–5 based on the peak''s signal-to-noise value), (3) “is isotope,” (4) “is neutral loss,” (5) “number of isotopes,” (6) “number of doublet isotopes,” and (7) “has neutral loss.”To evaluate NeuCode SILAC labeling for automated de novo sequencing, PepNovo⁺ (8) was benchmarked on y-ion predicted spectra. First, a set of identified spectra from 13,832 unique peptides (>7,400 per precursor charge 2–3) was produced to train PepNovo⁺ so it could learn features such as the relative peak height ranks of b/y-ions and the probability of noise at each mass interval. These training spectra were acquired under the 11 NeuCode yeast strong cation exchange fractions prepared as described above. Thermo raw files were converted into mzXML format using ProteoWizard v2.2.2828 (with peak-picking turned on) and identified by MS-GF⁺ v9358 (37) at a 1% spectrum-level FDR against the UniProt yeast database (plus isoforms), v20110729. A fixed modification of K⁺8.0142 was imposed along with variable modifications of oxidized Met and deamidated Asn/Gln. All MS/MS scans were searched with a 50-ppm precursor mass tolerance, the high-accuracy LTQ instrument setting, the HCD fragmentation setting, and one allowed missed Lys-C cleavage.Thermo.raw files were also converted into DTA spectra as before, except the in-house algorithm for selecting y-ion doublets was slightly altered to boost the peak height of predicted y-ions above that of other peaks (the cumulative peak height was equal to the sum of the monoisotopic doublet peaks, all isotopic doublet peaks, and two times the peak height of the base peak) and to convert their m/z to charge one. Remaining peaks not predicted to be y-ions were converted to charge one by a previously described MS/MS deconvolution tool (38). Deconvoluted DTA spectra that originated from identified MS/MS scans were then paired with the MSGF⁺ peptide IDs and passed to PepNovo⁺ for training. The resulting PepNovo⁺ scoring model lacked the rank-boosting component (39), which requires identified spectra from >100,000 unique peptides per precursor charge state and extensive modification of the PepNovo⁺ source code to train. Still, the model was sufficient to perform de novo peptide sequencing on the y-ion predicted spectra. PepNovo⁺ was also run on the raw MS/MS scans (mzXML spectra converted to MGF with all MS/MS peaks converted to charge one) by use of a previously trained HCD scoring model that also lacks the rank-boosting component (40). The following PepNovo⁺ parameters were set at all stages of training and benchmarking: fixed modification of K⁺8.0142; variable modifications of oxidized Met and deamidated Asn; 0.01-Da fragment mass tolerance; use of spectrum precursor charge; and use of spectrum precursor m/z.     

Export of cyst wall material and Golgi organelle neogenesis in Giardia lamblia depend on endoplasmic reticulum exit sites

Giardia lamblia parasitism accounts for the majority of cases of parasitic diarrheal disease, making this flagellated eukaryote the most successful intestinal parasite worldwide. This organism has undergone secondary reduction/elimination of entire organelle systems such as mitochondria and Golgi. However, trophozoite to cyst differentiation (encystation) requires neogenesis of Golgi‐like secretory organelles named encystation‐specific vesicles (ESVs), which traffic, modify and partition cyst wall proteins produced exclusively during encystation. In this work we ask whether neogenesis of Golgi‐related ESVs during G. lamblia differentiation, similarly to Golgi biogenesis in more complex eukaryotes, requires the maintenance of distinct COPII‐associated endoplasmic reticulum (ER) subdomains in the form of ER exit sites (ERES) and whether ERES are also present in non‐differentiating trophozoites. To address this question, we identified conserved COPII components in G. lamblia cells and determined their localization, quantity and dynamics at distinct ERES domains in vegetative and differentiating trophozoites. Analogous to ERES and Golgi biogenesis, these domains were closely associated to early stages ofnewly generated ESV. Ectopic expression of non‐functional Sar1 GTPase variants caused ERES collapse and, consequently, ESV ablation, leading to impaired parasite differentiation. Thus, our data show how ERES domains remain conserved in G. lamblia despite elimination of steady‐state Golgi. Furthermore, the fundamental eukaryotic principle of ERES to Golgi/Golgi‐like compartment correspondence holds true in differentiating Giardia presenting streamlined machinery for secretory organelle biogenesis and protein trafficking. However, in the Golgi‐less trophozoites ERES exist as stable ER subdomains, likely as the sole sorting centres for secretory traffic.     

The spatial scaling of beta diversity

Beta diversity is an important concept used to describe turnover in species composition across a wide range of spatial and temporal scales, and it underpins much of conservation theory and practice. Although substantial progress has been made in the mathematical and terminological treatment of different measures of beta diversity, there has been little conceptual synthesis of potential scale dependence of beta diversity with increasing spatial grain and geographic extent of sampling. Here, we evaluate different conceptual approaches to the spatial scaling of beta diversity, interpreted from ‘fixed’ and ‘varying’ perspectives of spatial grain and extent. We argue that a ‘sliding window’ perspective, in which spatial grain and extent covary, is an informative way to conceptualize community differentiation across scales. This concept more realistically reflects the varying empirical approaches that researchers adopt in field sampling and the varying scales of landscape perception by different organisms. Scale dependence in beta diversity has broad implications for emerging fields in ecology and biogeography, such as the integration of fine‐resolution ecogenomic data with large‐scale macroecological studies, as well as for guiding appropriate management responses to threats to biodiversity operating at different spatial scales.     

Riociguat Reduces Infarct Size and Post-Infarct Heart Failure in Mouse Hearts: Insights from MRI/PET Imaging

Aim

Stimulation of the nitric oxide (NO) – soluble guanylate (sGC) - protein kinase G (PKG) pathway confers protection against acute ischaemia/reperfusion injury, but more chronic effects in reducing post-myocardial infarction (MI) heart failure are less defined. The aim of this study was to not only determine whether the sGC stimulator riociguat reduces infarct size but also whether it protects against the development of post-MI heart failure.

Methods and Results

Mice were subjected to 30 min ischaemia via ligation of the left main coronary artery to induce MI and either placebo or riociguat (1.2 µmol/l) were given as a bolus 5 min before and 5 min after onset of reperfusion. After 24 hours, both, late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) and ¹⁸F-FDG-positron emission tomography (PET) were performed to determine infarct size. In the riociguat-treated mice, the resulting infarct size was smaller (8.5±2.5% of total LV mass vs. 21.8%±1.7%. in controls, p = 0.005) and LV systolic function analysed by MRI was better preserved (60.1%±3.4% of preischaemic vs. 44.2%±3.1% in controls, p = 0.005). After 28 days, LV systolic function by echocardiography treated group was still better preserved (63.5%±3.2% vs. 48.2%±2.2% in control, p = 0.004).

Conclusion

Taken together, mice treated acutely at the onset of reperfusion with the sGC stimulator riociguat have smaller infarct size and better long-term preservation of LV systolic function. These findings suggest that sGC stimulation during reperfusion therapy may be a powerful therapeutic treatment strategy for preventing post-MI heart failure.     

Defective Mitochondrial Function In Vivo in Skeletal Muscle in Adults with Down’s Syndrome: A 31P-MRS Study

Down’s syndrome (DS) is a developmental disorder associated with intellectual disability (ID). We have previously shown that people with DS engage in very low levels of exercise compared to people with ID not due to DS. Many aspects of the DS phenotype, such as dementia, low activity levels and poor muscle tone, are shared with disorders of mitochondrial origin, and mitochondrial dysfunction has been demonstrated in cultured DS tissue. We undertook a phosphorus magnetic resonance spectroscopy (³¹P-MRS) study in the quadriceps muscle of 14 people with DS and 11 non-DS ID controls to investigate the post-exercise resynthesis kinetics of phosphocreatine (PCr), which relies on mitochondrial respiratory function and yields a measure of muscle mitochondrial function in vivo. We found that the PCr recovery rate constant was significantly decreased in adults with DS compared to non-DS ID controls (1.7±0.1 min⁻¹ vs 2.1±0.1 min⁻¹ respectively) who were matched for physical activity levels, indicating that muscle mitochondrial function in vivo is impaired in DS. This is the first study to investigate mitochondrial function in vivo in DS using ³¹P-MRS. Our study is consistent with previous in vitro studies, supporting a theory of a global mitochondrial defect in DS.