Unimodal size scaling of phytoplankton growth and the size dependence of nutrient uptake and use

Phytoplankton size structure is key for the ecology and biogeochemistry of pelagic ecosystems, but the relationship between cell size and maximum growth rate (μ_max) is not yet well understood. We used cultures of 22 species of marine phytoplankton from five phyla, ranging from 0.1 to 10⁶ μm³ in cell volume (V_cell), to determine experimentally the size dependence of growth, metabolic rate, elemental stoichiometry and nutrient uptake. We show that both μ_max and carbon‐specific photosynthesis peak at intermediate cell sizes. Maximum nitrogen uptake rate (V_maxN) scales isometrically with V_cell, whereas nitrogen minimum quota scales as V_cell^0.84. Large cells thus possess high ability to take up nitrogen, relative to their requirements, and large storage capacity, but their growth is limited by the conversion of nutrients into biomass. Small species show similar volume‐specific V_maxN compared to their larger counterparts, but have higher nitrogen requirements. We suggest that the unimodal size scaling of phytoplankton growth arises from taxon‐independent, size‐related constraints in nutrient uptake, requirement and assimilation.     

Lipoarabinomannan mannose caps do not affect mycobacterial virulence or the induction of protective immunity in experimental animal models of infection and have minimal impact on in vitro inflammatory responses

Mannose‐capped lipoarabinomannan (ManLAM) is considered an important virulence factor of Mycobacterium tuberculosis. However, while mannose caps have been reported to be responsible for various immunosuppressive activities of ManLAMobserved in vitro, there is conflicting evidence about their contribution to mycobacterial virulence in vivo. Therefore, we used Mycobacterium bovis BCG and M. tuberculosis mutants that lack the mannose cap of LAM to assess the role of ManLAM in the interaction of mycobacteria with the host cells, to evaluate vaccine‐induced protection and to determine its importance in M. tuberculosis virulence. Deletion of the mannose cap did not affect BCG survival and replication in macrophages, although the capless mutant induced a somewhat higher production of TNF. In dendritic cells, the capless mutant was able to induce the upregulation of co‐stimulatory molecules and the only difference we detected was the secretion of slightly higher amounts of IL‐10 as compared to the wild type strain. In mice, capless BCG survived equally well and induced an immune response similar to the parental strain. Furthermore, the efficacy of vaccination against a M. tuberculosis challenge in low‐dose aerosol infection models in mice and guinea pigs was not affected by the absence of the mannose caps in the BCG. Finally, the lack of the mannose cap in M. tuberculosis did not affect its virulence in mice nor its interaction with macrophages in vitro. Thus, these results do not support a major role for the mannose caps of LAM in determining mycobacterial virulence and immunogenicity in vivo in experimental animal models of infection, possibly because of redundancy of function.     

Anti-inflammatory effects of clarithromycin in ventilator-induced lung injury

Background

Mechanical ventilation can promote lung injury by triggering a pro-inflammatory response. Macrolides may exert some immunomodulatory effects and have shown significant benefits over other antibiotics in ventilated patients. We hypothesized that macrolides could decrease ventilator-induced lung injury.

Methods

Adult mice were treated with vehicle, clarithromycin or levofloxacin, and randomized to receive mechanical ventilation with low (12 cmH₂O, PEEP 2 cmH₂O) or high (20 cmH₂O, ZEEP) inspiratory pressures for 150 minutes. Histological lung injury, neutrophil infiltration, inflammatory mediators (NFκB activation, Cxcl2, IL-10) and levels of adhesion molecules (E-selectin, ICAM) and proteases (MMP-9 and MMP-2) were analyzed.

Results

There were no differences among groups after low-pressure ventilation. Clarithromycin significantly decreased lung injury score and neutrophil count, compared to vehicle or levofloxacin, after high-pressure ventilation. Cxcl2 expression and MMP-2 and MMP-9 levels increased and IL-10 decreased after injurious ventilation, with no significant differences among treatment groups. Both clarithromycin and levofloxacin dampened the increase in NFκB activation observed in non-treated animals submitted to injurious ventilation. E-selectin levels increased after high pressure ventilation in vehicle- and levofloxacin-treated mice, but not in those receiving clarithromycin.

Conclusions

Clarithromycin ameliorates ventilator-induced lung injury and decreases neutrophil recruitment into the alveolar spaces. This could explain the advantages of macrolides in patients with acute lung injury and mechanical ventilation.     

Molecular Typing of Lung Adenocarcinoma on Cytological Samples Using a Multigene Next Generation Sequencing Panel

Identification of driver mutations in lung adenocarcinoma has led to development of targeted agents that are already approved for clinical use or are in clinical trials. Therefore, the number of biomarkers that will be needed to assess is expected to rapidly increase. This calls for the implementation of methods probing the mutational status of multiple genes for inoperable cases, for which limited cytological or bioptic material is available. Cytology specimens from 38 lung adenocarcinomas were subjected to the simultaneous assessment of 504 mutational hotspots of 22 lung cancer-associated genes using 10 nanograms of DNA and Ion Torrent PGM next-generation sequencing. Thirty-six cases were successfully sequenced (95%). In 24/36 cases (67%) at least one mutated gene was observed, including EGFR, KRAS, PIK3CA, BRAF, TP53, PTEN, MET, SMAD4, FGFR3, STK11, MAP2K1. EGFR and KRAS mutations, respectively found in 6/36 (16%) and 10/36 (28%) cases, were mutually exclusive. Nine samples (25%) showed concurrent alterations in different genes. The next-generation sequencing test used is superior to current standard methodologies, as it interrogates multiple genes and requires limited amounts of DNA. Its applicability to routine cytology samples might allow a significant increase in the fraction of lung cancer patients eligible for personalized therapy.     

Right Bundle Branch Block: A Predictor of Mortality in Early Systemic Sclerosis

Objective

To evaluate the prognostic significance of baseline electrocardiogram (ECG) abnormalities in a multiethnic cohort of patients with early systemic sclerosis (SSc) and to determine the serological, clinical, and echocardiogram correlates of ECG findings.

Methods

SSc patients with disease duration of≤5 years were enrolled in the GENISOS (Genetics versus Environment in Scleroderma Outcome Study) cohort. At the first visit, a standard 12 lead ECG was obtained along with demographic information, clinical data, and autoantibodies. The results of echocardiograms were also recorded. All ECGs were interpreted by a cardiologist unaware of the patients'' clinical data.

Results

Of 265 SSc patients with average disease duration at enrollment of 2.5 years, 140 (52.8%) had abnormal ECG findings. These findings were not associated with SSc disease type or autoantibody profile but were associated with more severe heart and lung involvement. A total of 75 patients (28.3%) died over a follow up time of 9.9 years. Complete right bundle branch block (± left anterior hemiblock) on ECG, present in 7 (2.6%) patients, predicted a higher risk of mortality (HR: 5.3; 95% CI: 2.1 to 13.4; p<0.001). The predictive significance of right bundle branch block was independent of age at enrollment, gender, ethnicity and risk factors for coronary artery disease.

Conclusion

ECG abnormalities are common in patients with early SSc and are associated with the severity of lung and heart involvement. Right bundle branch block is an independent predictor of mortality, and should be considered a marker of disease severity in SSc.     

Network Bursting Dynamics in Excitatory Cortical Neuron Cultures Results from the Combination of Different Adaptive Mechanism

In the brain, synchronization among cells of an assembly is a common phenomenon, and thought to be functionally relevant. Here we used an in vitro experimental model of cell assemblies, cortical cultures, combined with numerical simulations of a spiking neural network (SNN) to investigate how and why spontaneous synchronization occurs. In order to deal with excitation only, we pharmacologically blocked GABA_Aergic transmission using bicuculline. Synchronous events in cortical cultures tend to involve almost every cell and to display relatively constant durations. We have thus named these “network spikes” (NS). The inter-NS-intervals (INSIs) proved to be a more interesting phenomenon. In most cortical cultures NSs typically come in series or bursts (“bursts of NSs”, BNS), with short (∼1 s) INSIs and separated by long silent intervals (tens of s), which leads to bimodal INSI distributions. This suggests that a facilitating mechanism is at work, presumably short-term synaptic facilitation, as well as two fatigue mechanisms: one with a short timescale, presumably short-term synaptic depression, and another one with a longer timescale, presumably cellular adaptation. We thus incorporated these three mechanisms into the SNN, which, indeed, produced realistic BNSs. Next, we systematically varied the recurrent excitation for various adaptation timescales. Strong excitability led to frequent, quasi-periodic BNSs (CV∼0), and weak excitability led to rare BNSs, approaching a Poisson process (CV∼1). Experimental cultures appear to operate within an intermediate weakly-synchronized regime (CV∼0.5), with an adaptation timescale in the 2–8 s range, and well described by a Poisson-with-refractory-period model. Taken together, our results demonstrate that the INSI statistics are indeed informative: they allowed us to infer the mechanisms at work, and many parameters that we cannot access experimentally.     

HSPRO acts via SnRK1-mediated signaling in the regulation of Nicotiana attenuata seedling growth promoted by Piriformospora indica

Nicotiana attenuata HSPRO (NaHSPRO) is a negative regulator of seedling growth promoted by the fungus Piriformospora indica. Homologs of NaHSPRO in Arabidopsis thaliana (i.e., AtHSPRO1 and AtHSPRO2) are known to physically interact with the AKINβγ subunit of the SnRK1 complex.² To investigate whether NaHSPRO is associated with SnRK1 function during the stimulation of seedling growth by P. indica, we studied N. attenuata plants silenced in the expression of NaGAL83 (as-gal83 plants)—a gene that encodes for the regulatory β-subunit of SnRK1—and plants silenced in the expression of both NaHSPRO and NaGAL83 (ir-hspro/as-gal83 plants). The results showed that P. indica differentially stimulated the growth of both as-gal83 and ir-hspro/as-gal83 seedlings compared with control seedlings, with a magnitude similar to that observed in ir-hspro seedlings. Thus, we showed that, similar to NaHSPRO, NaGAL83 is a negative regulator of seedling growth stimulated by P. indica. We propose that the effect of NaHSPRO on seedling growth is associated with SnRK1 signaling.     

Prediction of Complex Human Traits Using the Genomic Best Linear Unbiased Predictor

Despite important advances from Genome Wide Association Studies (GWAS), for most complex human traits and diseases, a sizable proportion of genetic variance remains unexplained and prediction accuracy (PA) is usually low. Evidence suggests that PA can be improved using Whole-Genome Regression (WGR) models where phenotypes are regressed on hundreds of thousands of variants simultaneously. The Genomic Best Linear Unbiased Prediction (G-BLUP, a ridge-regression type method) is a commonly used WGR method and has shown good predictive performance when applied to plant and animal breeding populations. However, breeding and human populations differ greatly in a number of factors that can affect the predictive performance of G-BLUP. Using theory, simulations, and real data analysis, we study the performance of G-BLUP when applied to data from related and unrelated human subjects. Under perfect linkage disequilibrium (LD) between markers and QTL, the prediction R-squared (R²) of G-BLUP reaches trait-heritability, asymptotically. However, under imperfect LD between markers and QTL, prediction R² based on G-BLUP has a much lower upper bound. We show that the minimum decrease in prediction accuracy caused by imperfect LD between markers and QTL is given by (1−b)², where b is the regression of marker-derived genomic relationships on those realized at causal loci. For pairs of related individuals, due to within-family disequilibrium, the patterns of realized genomic similarity are similar across the genome; therefore b is close to one inducing small decrease in R². However, with distantly related individuals b reaches very low values imposing a very low upper bound on prediction R². Our simulations suggest that for the analysis of data from unrelated individuals, the asymptotic upper bound on R² may be of the order of 20% of the trait heritability. We show how PA can be enhanced with use of variable selection or differential shrinkage of estimates of marker effects.