The predictive role of serum and bronchoalveolar lavage cytokines and adhesion molecules for acute respiratory distress syndrome development and outcome

BACKGROUND: The predictive role of many cytokines and adhesion molecules has not been studied systematically in acute respiratory distress syndrome (ARDS). METHODS: We measured prospectively tumour necrosis factor alpha (TNF-α), interleukin (IL)-1, soluble vascular adhesion molecule-1 (VCAM-1) and soluble intercellular adhesion molecule-1 (ICAM-1) in serum and bronchoalveolar lavage fluid (BALF) within 2 hours following admission, in 65 patients. The patients were divided into: those fulfilling the criteria for ARDS (n = 23, group A), those who were pre-ARDS and who developed ARDS within 24 hours (n = 14, group B), and those on pre-ARDS but who never developed ARDS (n = 28, group C). RESULTS: All the measured molecules were only found at higher levels in the serum of patients that died either with or without ARDS (P < 0.05 – P < 0.0001). Patients at risk exhibited a good negative predictive value (NPV) of the measured molecules for ARDS development both in their serum (89 to 95%) and BALF (86 to 92%) levels. In contrast to BALF, serum levels of IL-1 and adhesion molecules exhibited a good NPV (68 to 96%), sensitivity (60 to 88%) and survival specificity (74 to 96%) in all groups. All molecules in serum and BALF IL-1 were correlated with the APACHE II (P < 0.05 – P < 0.0001). Serum and BALF IL-1 as well as BALF TNF-α were negatively correlated to PaO(2)/FiO(2) (all P < 0.05). CONCLUSIONS: The studied molecules have good NPV for ARDS development both in serum and BALF. Serum rather than BALF levels seem to be related to outcome

Biological Stoichiometry in Human Cancer

A growing tumor in the body can be considered a complex ecological and evolutionary system. A new eco-evolutionary hypothesis (the "Growth Rate Hypothesis", GRH) proposes that tumors have elevated phosphorus (P) demands due to increased allocation to P-rich nucleic acids, especially ribosomal RNA, to meet the protein synthesis demands of accelerated proliferation.We determined the elemental (C, N, P) and nucleic acid contents of paired malignant and normal tissues from colon, lung, liver, or kidney for 121 patients. Consistent with the GRH, lung and colon tumors were significantly higher (by approximately two-fold) in P content (fraction of dry weight) and RNA content and lower in nitrogen (N):P ratio than paired normal tissue, and P in RNA contributed a significantly larger fraction of total biomass P in malignant relative to normal tissues. Furthermore, patient-specific differences for %P between malignant and normal tissues were positively correlated with such differences for %RNA, both for the overall data and within three of the four organ sites. However, significant differences in %P and %RNA between malignant and normal tissues were not seen in liver and kidney and, overall, RNA contributed only approximately 11% of total tissue P content.Data for lung and colon tumors provide support for the GRH in human cancer. The two-fold amplification of P content in colon and lung tumors may set the stage for potential P-limitation of their proliferation, as such differences often do for rapidly growing biota in ecosystems. However, data for kidney and liver do not support the GRH. To account for these conflicting observations, we suggest that local environments in some organs select for neoplastic cells bearing mutations increasing cell division rate ("r-selected," as in colon and lung) while conditions elsewhere may select for reduced mortality rate ("K-selected," as in liver and kidney)

Avoiding Dangerous Missense: Thermophiles Display Especially Low Mutation Rates

Rates of spontaneous mutation have been estimated under optimal growth conditions for a variety of DNA-based microbes, including viruses, bacteria, and eukaryotes. When expressed as genomic mutation rates, most of the values were in the vicinity of 0.003–0.004 with a range of less than two-fold. Because the genome sizes varied by roughly 104-fold, the mutation rates per average base pair varied inversely by a similar factor. Even though the commonality of the observed genomic rates remains unexplained, it implies that mutation rates in unstressed microbes reach values that can be finely tuned by evolution. An insight originating in the 1920s and maturing in the 1960s proposed that the genomic mutation rate would reflect a balance between the deleterious effect of the average mutation and the cost of further reducing the mutation rate. If this view is correct, then increasing the deleterious impact of the average mutation should be countered by reducing the genomic mutation rate. It is a common observation that many neutral or nearly neutral mutations become strongly deleterious at higher temperatures, in which case they are called temperature-sensitive mutations. Recently, the kinds and rates of spontaneous mutations were described for two microbial thermophiles, a bacterium and an archaeon. Using an updated method to extrapolate from mutation-reporter genes to whole genomes reveals that the rate of base substitutions is substantially lower in these two thermophiles than in mesophiles. This result provides the first experimental support for the concept of an evolved balance between the total genomic impact of mutations and the cost of further reducing the basal mutation rate

Immune gene regulation is associated with age and environmental adversity in a nonhuman primate

This is the final version. Available on open access from Wiley via the DOI in this recordData availability statement: RNA sequencing reads are available in the National Center for Biotechnology Information Short Read Archive (SRA project number 715739) (ID 715739—BioProject—NCBI, n.d.). DNA reads will be uploaded to SRA and made available upon publication under BioProject ID PRJNA610241(ID 610241—BioProject—NCBI, n.d.). Macaque chromatin accessibility data are available in the NCBI Sequence Read Archive, https://www.ncbi.nlm.nih.gov/bioproject (BioProject ID PRJNA476378) (ID 476378—BioProject—NCBI, n.d.; Snyder-Mackler et al., 2019).Phenotypic aging is ubiquitous across mammalian species, suggesting shared underlying mechanisms of aging. Aging is linked to molecular changes to DNA methylation and gene expression, and environmental factors, such as severe external challenges or adversities, can moderate these age-related changes. Yet, it remains unclear whether environmental adversities affect gene regulation via the same molecular pathways as chronological, or ‘primary’, aging. Investigating molecular aging in naturalistic animal populations can fill this gap by providing insight into shared molecular mechanisms of aging and the effects of a greater diversity of environmental adversities – particularly those that can be challenging to study in humans or laboratory organisms. Here, we characterised molecular aging – specifically, CpG methylation – in a sample of free-ranging rhesus macaques living off the coast of Puerto Rico (n samples = 571, n individuals = 499), which endured a major hurricane during our study. Age was associated with methylation at 78,661 sites (31% of all sites tested). Age-associated hypermethylation occurred more frequently in areas of active gene regulation, while hypomethylation was enriched in regions that show less activity in immune cells, suggesting these regions may become de-repressed in older individuals. Age-associated hypomethylation also co-occurred with increased chromatin accessibility while hypermethylation showed the opposite trend, hinting at a coordinated, multi-level loss of epigenetic stability during aging. We detected 32,048 CpG sites significantly associated with exposure to a hurricane, and these sites overlapped age-associated sites, most strongly in regulatory regions and most weakly in quiescent regions. Together, our results suggest that environmental adversity may contribute to aging-related molecular phenotypes in regions of active gene transcription, but that primary aging has specific signatures in non-regulatory regions.University of Washington Department of BiologyRoyal SocietyNational Institutes of Health (NIH

Latent physiological factors of complex human diseases revealed by independent component analysis of clinarrays

<p>Abstract</p> <p>Background</p> <p>Diagnosis and treatment of patients in the clinical setting is often driven by known symptomatic factors that distinguish one particular condition from another. Treatment based on noticeable symptoms, however, is limited to the types of clinical biomarkers collected, and is prone to overlooking dysfunctions in physiological factors not easily evident to medical practitioners. We used a vector-based representation of patient clinical biomarkers, or clinarrays, to search for latent physiological factors that underlie human diseases directly from clinical laboratory data. Knowledge of these factors could be used to improve assessment of disease severity and help to refine strategies for diagnosis and monitoring disease progression.</p> <p>Results</p> <p>Applying Independent Component Analysis on clinarrays built from patient laboratory measurements revealed both known and novel concomitant physiological factors for asthma, types 1 and 2 diabetes, cystic fibrosis, and Duchenne muscular dystrophy. Serum sodium was found to be the most significant factor for both type 1 and type 2 diabetes, and was also significant in asthma. TSH3, a measure of thyroid function, and blood urea nitrogen, indicative of kidney function, were factors unique to type 1 diabetes respective to type 2 diabetes. Platelet count was significant across all the diseases analyzed.</p> <p>Conclusions</p> <p>The results demonstrate that large-scale analyses of clinical biomarkers using unsupervised methods can offer novel insights into the pathophysiological basis of human disease, and suggest novel clinical utility of established laboratory measurements.</p

The evolution of cyclodextrin glucanotransferase product specificity

Cyclodextrin glucanotransferases (CGTases) have attracted major interest from industry due to their unique capacity of forming large quantities of cyclic α-(1,4)-linked oligosaccharides (cyclodextrins) from starch. CGTases produce a mixture of cyclodextrins from starch consisting of 6 (α), 7 (β) and 8 (γ) glucose units. In an effort to identify the structural factors contributing to the evolutionary diversification of product specificity amongst this group of enzymes, we selected nine CGTases from both mesophilic, thermophilic and hyperthermophilic organisms for comparative product analysis. These enzymes displayed considerable variation regarding thermostability, initial rates, percentage of substrate conversion and ratio of α-, β- and γ-cyclodextrins formed from starch. Sequence comparison of these CGTases revealed that specific incorporation and/or substitution of amino acids at the substrate binding sites, during the evolutionary progression of these enzymes, resulted in diversification of cyclodextrin product specificity

Producer Nutritional Quality Controls Ecosystem Trophic Structure

Trophic structure, or the distribution of biomass among producers and consumers, determines key ecosystem values, such as the abundance of infectious, harvestable or conservation target species, and the storage and cycling of carbon and nutrients. There has been much debate on what controls ecosystem trophic structure, yet the answer is still elusive. Here we show that the nutritional quality of primary producers controls the trophic structure of ecosystems. By increasing the efficiency of trophic transfer, higher producer nutritional quality results in steeper ecosystem trophic structure, and those changes are more pronounced in terrestrial than in aquatic ecosystems probably due to the more stringent nutritional limitation of terrestrial herbivores. These results explain why ecosystems composed of highly nutritional primary producers feature high consumer productivity, fast energy recycling, and reduced carbon accumulation. Anthropogenic changes in producer nutritional quality, via changes in trophic structure, may alter the values and functions of ecosystems, and those alterations may be more important in terrestrial ecosystems

Analysis of Rabies in China: Transmission Dynamics and Control

Human rabies is one of the major public-health problems in China. The number of human rabies cases has increased dramatically in the last 15 years, partially due to the poor understanding of the transmission dynamics of rabies and the lack of effective control measures of the disease. In this article, in order to explore effective control and prevention measures we propose a deterministic model to study the transmission dynamics of rabies in China. The model consists of susceptible, exposed, infectious, and recovered subpopulations of both dogs and humans and describes the spread of rabies among dogs and from infectious dogs to humans. The model simulations agree with the human rabies data reported by the Chinese Ministry of Health. We estimate that the basic reproduction number for the rabies transmission in China and predict that the number of the human rabies is decreasing but may reach another peak around 2030. We also perform some sensitivity analysis of in terms of the model parameters and compare the effects of culling and immunization of dogs. Our study demonstrates that (i) reducing dog birth rate and increasing dog immunization coverage rate are the most effective methods for controlling rabies in China; and (ii) large scale culling of susceptible dogs can be replaced by immunization of them

Enhanced biological carbon consumption in a high CO2 ocean

The oceans have absorbed nearly half of the fossil-fuel carbon dioxide (CO2) emitted into the atmosphere since pre-industrial times1, causing a measurable reduction in seawater pH and carbonate saturation2. If CO2 emissions continue to rise at current rates, upper-ocean pH will decrease to levels lower than have existed for tens of millions of years and, critically, at a rate of change 100 times greater than at any time over this period3. Recent studies have shown effects of ocean acidification on a variety of marine life forms, in particular calcifying organisms4, 5, 6. Consequences at the community to ecosystem level, in contrast, are largely unknown. Here we show that dissolved inorganic carbon consumption of a natural plankton community maintained in mesocosm enclosures at initial CO2 partial pressures of 350, 700 and 1,050 μatm increases with rising CO2. The community consumed up to 39% more dissolved inorganic carbon at increased CO2 partial pressures compared to present levels, whereas nutrient uptake remained the same. The stoichiometry of carbon to nitrogen drawdown increased from 6.0 at low CO2 to 8.0 at high CO2, thus exceeding the Redfield carbon:nitrogen ratio of 6.6 in today’s ocean7. This excess carbon consumption was associated with higher loss of organic carbon from the upper layer of the stratified mesocosms. If applicable to the natural environment, the observed responses have implications for a variety of marine biological and biogeochemical processes, and underscore the importance of biologically driven feedbacks in the ocean to global change

L1pred: A Sequence-Based Prediction Tool for Catalytic Residues in Enzymes with the L1-logreg Classifier

To understand enzyme functions, identifying the catalytic residues is a usual first step. Moreover, knowledge about catalytic residues is also useful for protein engineering and drug-design. However, to experimentally identify catalytic residues remains challenging for reasons of time and cost. Therefore, computational methods have been explored to predict catalytic residues. Here, we developed a new algorithm, L1pred, for catalytic residue prediction, by using the L1-logreg classifier to integrate eight sequence-based scoring functions. We tested L1pred and compared it against several existing sequence-based methods on carefully designed datasets Data604 and Data63. With ten-fold cross-validation, L1pred showed the area under precision-recall curve (AUPR) and the area under ROC curve (AUC) of 0.2198 and 0.9494 on the training dataset, Data604, respectively. In addition, on the independent test dataset, Data63, it showed the AUPR and AUC values of 0.2636 and 0.9375, respectively. Compared with other sequence-based methods, L1pred showed the best performance on both datasets. We also analyzed the importance of each attribute in the algorithm, and found that all the scores contributed more or less equally to the L1pred performance