Hao Yang

Use of 1H-nuclear magnetic resonance to screen a set of biomarkers for monitoring metabolic disturbances in severe burn patients

IntroductionTo establish a plasma metabolomics fingerprint spectrum for severe burn patients and to use it to identify a set of biomarkers that could be used for clinical monitoring.MethodsTwenty-one severe burn patients and three healthy control individuals were enrolled in this study, and the plasma samples from patients and healthy individuals were collected for nuclear magnetic resonance (NMR) measurements. The NMR spectra were analyzed using principal component analysis (PCA) and partial least squares (PLS) in order to establish the metabolomics fingerprint representing the changes in metabolism and to select the major biomarkers.ResultsNMR spectra of the plasma samples showed significant differences between burn patients and healthy individuals. Using metabolomics techniques, we found an Eigen-metabolome that consists of 12 metabolites, which are regulated by 103 enzymes in a global metabolic network. Among these metabolites, α-ketoisovaleric acid, 3-methylhistidine, and β-hydroxybutyric acid were the most important biomarkers that were significantly increased during the early stage of burn injury. These results suggest that the mitochondrial damage and carbohydrate, protein and fatty acid metabolism disturbances occur after burn injury. Our analysis also show that histone deacetylases, which are protein transcription suppressors, were remarkably increased and indicate that protein transcription was inhibited and anabolism was restrained during the early stage of burn injury.ConclusionsMetabolomics techniques based on NMR can be used to monitor metabolism in severe burn patients. Our study demonstrates that integrated 1H-NMR metabolome and global metabolic network analysis is useful for visualizing complex metabolic disturbances after severe burn injury and may provide a new quantitative injury severity evaluation for future clinical use.Trial registrationChinese Clinical Trial Registry ChiCTR-OCC-12002145. Registered 25 April 2012.

Establishment of quantitative severity evaluation model for spinal cord injury by metabolomic fingerprinting

Spinal cord injury (SCI) is a devastating event with a limited hope for recovery and represents an enormous public health issue. It is crucial to understand the disturbances in the metabolic network after SCI to identify injury mechanisms and opportunities for treatment intervention. Through plasma 1H-nuclear magnetic resonance (NMR) screening, we identified 15 metabolites that made up an “Eigen-metabolome” capable of distinguishing rats with severe SCI from healthy control rats. Forty enzymes regulated these 15 metabolites in the metabolic network. We also found that 16 metabolites regulated by 130 enzymes in the metabolic network impacted neurobehavioral recovery. Using the Eigen-metabolome, we established a linear discrimination model to cluster rats with severe and mild SCI and control rats into separate groups and identify the interactive relationships between metabolic biomarkers in the global metabolic network. We identified 10 clusters in the global metabolic network and defined them as distinct metabolic disturbance domains of SCI. Metabolic paths such as retinal, glycerophospholipid, arachidonic acid metabolism; NAD–NADPH conversion process, tyrosine metabolism, and cadaverine and putrescine metabolism were included. In summary, we presented a novel interdisciplinary method that integrates metabolomics and global metabolic network analysis to visualize metabolic network disturbances after SCI. Our study demonstrated the systems biological study paradigm that integration of 1H-NMR, metabolomics, and global metabolic network analysis is useful to visualize complex metabolic disturbances after severe SCI. Furthermore, our findings may provide a new quantitative injury severity evaluation model for clinical use.

Is Omega-3 Fatty Acids Enriched Nutrition Support Safe for Critical Ill Patients? A Systematic Review and Meta-Analysis

Objective: To systematically review the effects of omega-3 poly unsaturated fatty acids (FA) enriched nutrition support on the mortality of critically illness patients. Methods: Databases of Medline, ISI, Cochrane Library, and Chinese Biomedicine Database were searched and randomized controlled trials (RCTs) were identified. We enrolled RCTs that compared fish oil enriched nutrition support and standard nutrition support. Major outcome is mortality. Methodological quality assessment was conducted based on Modified Jadad’s score scale. For control heterogeneity, we developed a method that integrated I2 test, nutritional support route subgroup analysis and clinical condition of severity. RevMan 5.0 software (The Nordic Cochrane Centre, Copenhagen, Denmark) was used for meta-analysis. Results: Twelve trials involving 1208 patients that met all the inclusion criteria. Heterogeneity existed between the trials. A random model was used, there was no significant effect on mortality RR, 0.82, 95% confidence interval (CI) (0.62, 1.09), p = 0.18. Knowing that the route of fish oil administration may affect heterogeneity, we categorized the trials into two sub-groups: parenteral administration (PN) of omega-3 and enteral administration (EN) of omega-3. Six trials administered omega-3 FA through PN. Pooled results indicated that omega-3 FA had no significant effect on mortality, RR 0.76, 95% CI (0.52, 1.10), p = 0.15. Six trials used omega-3 fatty acids enriched EN. After excluded one trial that was identified as source of heterogeneity, pooled data indicated omega-3 FA enriched EN significant reduce mortality, RR=0.69, 95% CI [0.53, 0.91] (p = 0.007). Conclusion: Omega-3 FA enriched nutrition support is safe. Due to the limited sample size of the included trials, further large-scale RCTs are needed.

The origin of novel avian influenza A (H7N9) and mutation dynamics for its human-to-human transmissible capacity.

In February 2013, H7N9 (A/H7N9/2013_China), a novel avian influenza virus, broke out in eastern China and caused human death. It is a global priority to discover its origin and the point in time at which it will become transmittable between humans. We present here an interdisciplinary method to track the origin of H7N9 virus in China and to establish an evolutionary dynamics model for its human-to-human transmission via mutations. After comparing influenza viruses from China since 1983, we established an A/H7N9/2013_China virus evolutionary phylogenetic tree and found that the human instances of virus infection were of avian origin and clustered into an independent line. Comparing hemagglutinin (HA) and neuraminidase (NA) gene sequences of A/H7N9/2013_China viruses with all human-to-human, avian, and swine influenza viruses in China in the past 30 years, we found that A/H7N9/2013_China viruses originated from Baer’s Pochard H7N1 virus of Hu Nan Province 2010 (HA gene, EPI: 370846, similarity with H7N9 is 95.5%) and duck influenza viruses of Nanchang city 2000 (NA gene, EPI: 387555, similarity with H7N9 is 97%) through genetic re-assortment. HA and NA gene sequence comparison indicated that A/H7N9/2013_China virus was not similar to human-to-human transmittable influenza viruses. To simulate the evolution dynamics required for human-to-human transmission mutations of H7N9 virus, we employed the Markov model. The result of this calculation indicated that the virus would acquire properties for human-to-human transmission in 11.3 years (95% confidence interval (CI): 11.2–11.3, HA gene).

The dilemma of heterogeneity tests in meta-analysis: a challenge from a simulation study.

Introduction After several decades’ development, meta-analysis has become the pillar of evidence-based medicine. However, heterogeneity is still the threat to the validity and quality of such studies. Currently, Q and its descendant I2 (I square) tests are widely used as the tools for heterogeneity evaluation. The core mission of this kind of test is to identify data sets from similar populations and exclude those are from different populations. Although Q and I2 are used as the default tool for heterogeneity testing, the work we present here demonstrates that the robustness of these two tools is questionable. Methods and Findings We simulated a strictly normalized population S. The simulation successfully represents randomized control trial data sets, which fits perfectly with the theoretical distribution (experimental group: p = 0.37, control group: p = 0.88). And we randomly generate research samples Si that fits the population with tiny distributions. In short, these data sets are perfect and can be seen as completely homogeneous data from the exactly same population. If Q and I2 are truly robust tools, the Q and I2 testing results on our simulated data sets should not be positive. We then synthesized these trials by using fixed model. Pooled results indicated that the mean difference (MD) corresponds highly with the true values, and the 95% confidence interval (CI) is narrow. But, when the number of trials and sample size of trials enrolled in the meta-analysis are substantially increased; the Q and I2 values also increase steadily. This result indicates that I2 and Q are only suitable for testing heterogeneity amongst small sample size trials, and are not adoptable when the sample sizes and the number of trials increase substantially. Conclusions Every day, meta-analysis studies which contain flawed data analysis are emerging and passed on to clinical practitioners as “updated evidence”. Using this kind of evidence that contain heterogeneous data sets leads to wrong conclusion, makes chaos in clinical practice and weakens the foundation of evidence-based medicine. We suggest more strict applications of meta-analysis: it should only be applied to those synthesized trials with small sample sizes. We call upon that the tools of evidence-based medicine should keep up-to-dated with the cutting-edge technologies in data science. Clinical research data should be made available publicly when there is any relevant article published so the research community could conduct in-depth data mining, which is a better alternative for meta-analysis in many instances.

Optimization of brain metabolism using metabolic-targeted therapeutic hypothermia can reduce mortality from traumatic brain injury

BACKGROUND Therapeutic hypothermia is widely used to treat traumatic brain injuries (TBIs). However, determining the best hypothermia therapy strategy remains a challenge. We hypothesized that reducing the metabolic rate, rather than reaching a fixed body temperature, would be an appropriate target because optimizing metabolic conditions especially the brain metabolic environment may enhance neurologic protection. A pilot single-blind randomized controlled trial was designed to test this hypothesis, and a nested metabolomics study was conducted to explore the mechanics thereof. METHODS Severe TBI patients (Glasgow Coma Scale score, 3–8) were randomly divided into the metabolic-targeted hypothermia treatment (MTHT) group, 50% to 60% rest metabolic ratio as the hypothermia therapy target, and the body temperature-targeted hypothermia treatment (BTHT) control group, hypothermia therapy target of 32°C to 35°C body temperature. Brain and circulatory metabolic pool blood samples were collected at baseline and on days 1, 3, and 7 during the hypothermia treatment, which were selected randomly from a subgroup of MTHT and BTHT groups. The primary outcome was mortality. Using 1H nuclear magnetic resonance technology, we tracked and located the disturbances of metabolic networks. RESULTS Eighty-eight severe TBI patients were recruited and analyzed from December 2013 to December 2014, 44 each were assigned in the MTHT and BTHT groups (median age, 42 years; 69.32% men; mean Glasgow Coma Scale score, 6.17 ± 1.02). The mortality was significantly lower in the MTHT than the BTHT group (15.91% vs. 34.09%; p = 0.049). From these, eight cases of MTHT and six cases from BTHT group were enrolled for metabolomics analysis, which showed a significant difference between the brain and circulatory metabolic patterns in MTHT group on day 7 based on the model parameters and scores plots. Finally, metabolites representing potential neuroprotective monitoring parameters for hypothermia treatment were identified through 1H nuclear magnetic resonance metabolomics. CONCLUSION MTHT can significantly reduce the mortality of severe TBI patients. Metabolomics research showed that this strategy could effectively improve brain metabolism, suggesting that reducing the metabolic rate to 50% to 60% should be set as the hypothermia therapy target. LEVEL OF EVIDENCE Therapeutic study, Level I.

Effects of DS-modified agarose gels on neurite extension in 3D scaffold through mechanisms other than changing the pore radius of the gels.

Dermatan sulfate is widely distributed as glycosaminoglycan side chains of proteoglycans, which are the main components of glial scar and inhibit neurite regeneration after nerve injury. However its role in the inhibiting process is not clear. Understanding neurite extension in three-dimensional scaffolds is critical for neural tissue engineering. This study used agarose gels modified with dermatan sulfate as the three-dimensional culture scaffold. We explored structure-function relationship between the three-dimensional scaffold and neurite extension and examined the role of dermatan sulfate on neurite extension in the three-dimensional scaffold. A range of agarose concentrations was used to generate varied gel physical structures and the corresponding neurite extension of embryonic day (E9) chick dorsal root ganglia was examined. We measured gel stiffness and gel pore size to determine whether dermatan sulfate changed the gels conformation. As gel concentration increased, neurite length and gel pore size decreased, and gel stiffness increased. At 1.00 and 1.25% (wt/vol) concentrations, dermatan sulfates both immobilized with agarose gels and dissolved in culture medium inhibit neurite extension. While at 1.50 and 1.75% (wt/vol) concentrations, only immobilized dermatan sulfate worked. Immobilized dermatan sulfate could modify molecular shape of agarose gels, decrease gel pore size statistically, but did not influence gel stiffness. We have proved that the decrease of gel pore size is insufficient to inhibit neurite extension. These results indicate that dermatan sulfate inhibits neurite extension not through forming a mechanical barrier. Maybe its interaction with neuron membrane is the key factor in neurite extension.