Caffeine has a dual influence on NMDA receptor–mediated glutamatergic transmission at the hippocampus

Caffeine, a stimulant largely consumed around the world, is a non-selective adenosine receptor antagonist, and therefore caffeine actions at synapses usually, but not always, mirror those of adenosine. Importantly, different adenosine receptors with opposing regulatory actions co-exist at synapses. Through both inhibitory and excitatory high-affinity receptors (A₁R and A₂R, respectively), adenosine affects NMDA receptor (NMDAR) function at the hippocampus, but surprisingly, there is a lack of knowledge on the effects of caffeine upon this ionotropic glutamatergic receptor deeply involved in both positive (plasticity) and negative (excitotoxicity) synaptic actions. We thus aimed to elucidate the effects of caffeine upon NMDAR-mediated excitatory post-synaptic currents (NMDAR-EPSCs), and its implications upon neuronal Ca²⁺ homeostasis. We found that caffeine (30–200 μM) facilitates NMDAR-EPSCs on pyramidal CA1 neurons from Balbc/ByJ male mice, an action mimicked, as well as occluded, by 1,3-dipropyl-cyclopentylxantine (DPCPX, 50 nM), thus likely mediated by blockade of inhibitory A₁Rs. This action of caffeine cannot be attributed to a pre-synaptic facilitation of transmission because caffeine even increased paired-pulse facilitation of NMDA-EPSCs, indicative of an inhibition of neurotransmitter release. Adenosine A_2ARs are involved in this likely pre-synaptic action since the effect of caffeine was mimicked by the A_2AR antagonist, SCH58261 (50 nM). Furthermore, caffeine increased the frequency of Ca²⁺ transients in neuronal cell culture, an action mimicked by the A₁R antagonist, DPCPX, and prevented by NMDAR blockade with AP5 (50 μM). Altogether, these results show for the first time an influence of caffeine on NMDA receptor activity at the hippocampus, with impact in neuronal Ca²⁺ homeostasis.

     

The ecology of chronic wasting disease in wildlife

Prions are misfolded infectious proteins responsible for a group of fatal neurodegenerative diseases termed transmissible spongiform encephalopathy or prion diseases. Chronic Wasting Disease (CWD) is the prion disease with the highest spillover potential, affecting at least seven Cervidae (deer) species. The zoonotic potential of CWD is inconclusive and cannot be ruled out. A risk of infection for other domestic and wildlife species is also plausible. Here, we review the current status of the knowledge with respect to CWD ecology in wildlife. Our current understanding of the geographic distribution of CWD lacks spatial and temporal detail, does not consider the biogeography of infectious diseases, and is largely biased by sampling based on hunters' cooperation and funding available for each region. Limitations of the methods used for data collection suggest that the extent and prevalence of CWD in wildlife is underestimated. If the zoonotic potential of CWD is confirmed in the short term, as suggested by recent results obtained in experimental animal models, there will be limited accurate epidemiological data to inform public health. Research gaps in CWD prion ecology include the need to identify specific biological characteristics of potential CWD reservoir species that better explain susceptibility to spillover, landscape and climate configurations that are suitable for CWD transmission, and the magnitude of sampling bias in our current understanding of CWD distribution and risk. Addressing these research gaps will help anticipate novel areas and species where CWD spillover is expected, which will inform control strategies. From an ecological perspective, control strategies could include assessing restoration of natural predators of CWD reservoirs, ultrasensitive CWD detection in biotic and abiotic reservoirs, and deer density and landscape modification to reduce CWD spread and prevalence.     

Pentoxifylline with metformin treatment improves biochemical parameters in patients with nonalcoholic steatohepatitis

BackgroundThe progression of the nonalcoholic fatty liver disease to nonalcoholic steatohepatitis (NASH) is multifactorial, and there is still a lack of approved medications for its treatment. The study aimed to evaluate the impact of combined treatment with Pentoxifylline and Metformin on biochemical parameters in patients with Nash. Setting: Outpatient hepatology clinic.MethodsA prospective trial was conducted. The first cohort included patients with biopsy-proven Nash, while the second cohort consisted of patients with biopsy-confirmed NAFLD. Blood tests were checked at baseline and every three months. Pentoxifylline at a dosage of 400 mg t.i.d. and Metformin at the dosage of 500 mg t.i.d. were introduced for six months in Nash group. The impact of the treatment was assessed based on biochemical results after combined treatment with low-cost medications.ResultsAll 33 Nash patients completed 24 weeks of treatment. We observed significant improvement (p<0.05) of median values after treatment for the following parameters: serum uric acid levels decreased by 51.0 mmol/L, calcium decreased for 0.27 mmoL/L, magnesium showed an increase of 0.11 mmoL/L. Insulin resistance improved as a reduction of HOMA - IR by 1.3 was detected. A significant decrease of median in liver enzymes, alanine aminotransferase, aspartate aminotransferase and gamma-glutamyltransferase by 24.0 U/L, 9.1 U/L, 10.8 U/L respectively, was noted.ConclusionsPentoxifylline and Metformin may provide possible treatment option in Nash. Some new potential benefit of the therapy in improving liver function whilst decreasing cardiovascular risk was perceived.     

Comparing diversity levels in environmental samples: DNA sequence capture and metabarcoding approaches using 18S and COI genes

Environmental DNA studies targeting multiple taxa using metabarcoding provide remarkable insights into levels of species diversity in any habitat. The main drawbacks are the presence of primer bias and difficulty in identifying rare species. We tested a DNA sequence‐capture method in parallel with the metabarcoding approach to reveal possible advantages of one method over the other. Both approaches were performed using the same eDNA samples and the same 18S and COI regions, followed by high throughput sequencing. Metabarcoded eDNA libraries were PCR amplified with one primer pair from 18S and COI genes. DNA sequence‐capture libraries were enriched with 3,639 baits targeting the same gene regions. We tested amplicon sequence variants (ASVs) and operational taxonomic units (OTUs) in silico approaches for both markers and methods, using for this purpose the metabarcoding data set. ASVs methods uncovered more species for the COI gene, whereas the opposite occurred for the 18S gene, suggesting that clustering reads into OTUs could bias diversity richness especially using 18S with relaxed thresholds. Additionally, metabarcoding and DNA sequence‐capture recovered 80%–90% of the control sample species. DNA sequence‐capture was 8x more expensive, nonetheless it identified 1.5x more species for COI and 13x more genera for 18S than metabarcoding. Both approaches offer reliable results, sharing ca. 40% species and 72% families and retrieve more taxa when nuclear and mitochondrial markers are combined. eDNA metabarcoding is quite well established and low‐cost, whereas DNA‐sequence capture for biodiversity assessment is still in its infancy, is more time‐consuming but provides more taxonomic assignments.     

Model‐assisted identification of metabolic engineering strategies for Jatropha curcas lipid pathways

Efficient approaches to increase plant lipid production are necessary to meet current industrial demands for this important resource. While Jatropha curcas cell culture can be used for in vitro lipid production, scaling up the system for industrial applications requires an understanding of how growth conditions affect lipid metabolism and yield. Here we present a bottom‐up metabolic reconstruction of J. curcas supported with labeling experiments and biomass characterization under three growth conditions. We show that the metabolic model can accurately predict growth and distribution of fluxes in cell cultures and use these findings to pinpoint energy expenditures that affect lipid biosynthesis and metabolism. In addition, by using constraint‐based modeling approaches we identify network reactions whose joint manipulation optimizes lipid production. The proposed model and computational analyses provide a stepping stone for future rational optimization of other agronomically relevant traits in J. curcas.