Synoptic relationships between surface Chlorophyll-<i>a</i> and diagnostic pigments specific to phytoplankton functional types

Error-quantified, synoptic-scale relationships between chlorophyll-<i>a</i> (Chl-<i>a</i>) and phytoplankton pigment groups at the sea surface are presented. A total of ten pigment groups were considered to represent three Phytoplankton Size Classes (PSCs, micro-, nano- and picoplankton) and seven Phytoplankton Functional Types (PFTs, i.e. diatoms, dinoflagellates, green algae, prymnesiophytes (haptophytes), pico-eukaryotes, prokaryotes and <i>Prochlorococcus</i> sp.). The observed relationships between Chl-<i>a</i> and PSCs/PFTs were well-defined at the global scale to show that a community shift of phytoplankton at the basin and global scales is reflected by a change in Chl-<i>a</i> of the total community. Thus, Chl-<i>a</i> of the total community can be used as an index of not only phytoplankton biomass but also of their community structure. Within these relationships, we also found non-monotonic variations with Chl-<i>a</i> for certain pico-sized phytoplankton (pico-eukaryotes, Prokaryotes and <i>Prochlorococcus</i> sp.) and nano-sized phytoplankton (Green algae, prymnesiophytes). The relationships were quantified with a least-square fitting approach in order to enable an estimation of the PFTs from Chl-<i>a</i> where PFTs are expressed as a percentage of the total Chl-<i>a</i>. The estimated uncertainty of the relationships depends on both PFT and Chl-<i>a</i> concentration. Maximum uncertainty of 31.8% was found for diatoms at Chl-<i>a</i> = 0.49 mg m⁻³. However, the mean uncertainty of the relationships over all PFTs was 5.9% over the entire Chl-<i>a</i> range observed in situ (0.02 &lt; Chl-<i>a</i> &lt; 4.26 mg m^&minus;3). The relationships were applied to SeaWiFS satellite Chl-<i>a</i> data from 1998 to 2009 to show the global climatological fields of the surface distribution of PFTs. Results show that microplankton are present in the mid and high latitudes, constituting only ~10.9% of the entire phytoplankton community in the mean field for 1998–2009, in which diatoms explain ~7.5%. Nanoplankton are ubiquitous throughout the global surface oceans, except the subtropical gyres, constituting ~45.5%, of which prymnesiophytes (haptophytes) are the major group explaining ~31.7% while green algae contribute ~13.9%. Picoplankton are dominant in the subtropical gyres, but constitute ~43.6% globally, of which prokaryotes are the major group explaining ~26.5% (<i>Prochlorococcus</i> sp. explaining 22.8%), while pico-eukaryotes explain ~17.2% and are relatively abundant in the South Pacific. These results may be of use to evaluate global marine ecosystem models

Artemisinin Attenuates Lipopolysaccharide-Stimulated Proinflammatory Responses by Inhibiting NF-κB Pathway in Microglia Cells

Microglial activation plays an important role in neuroinflammation, which contributes to neuronal damage, and inhibition of microglial activation may have therapeutic benefits that could alleviate the progression of neurodegeneration. Recent studies have indicated that the antimalarial agent artemisinin has the ability to inhibit NF-κB activation. In this study, the inhibitory effects of artemisinin on the production of proinflammatory mediators were investigated in lipopolysaccharide (LPS)-stimulated primary microglia. Our results show that artemisinin significantly inhibited LPS-induced production of tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), monocyte chemotactic protein-1 (MCP-1) and nitric oxide (NO). Artemisinin significantly decreased both the mRNA and the protein levels of these pro-inflammatory cytokines and inducible nitric oxide synthase (iNOS) and increased the protein levels of IκB-α, which forms a cytoplasmic inactive complex with the p65-p50 heterodimeric complex. Artemisinin treatment significantly inhibited basal and LPS-induced migration of BV-2 microglia. Electrophoretic mobility shift assays revealed increased NF-κB binding activity in LPS-stimulated primary microglia, and this increase could be prevented by artemisinin. The inhibitory effects of artemisinin on LPS-stimulated microglia were blocked after IκB-α was silenced with IκB-α siRNA. Our results suggest that artemisinin is able to inhibit neuroinflammation by interfering with NF-κB signaling. The data provide direct evidence of the potential application of artemisinin for the treatment of neuroinflammatory diseases

Potential immunological consequences of pharmacological suppression of gastric acid production in patients with multiple sclerosis

Corticosteroids are standard treatment for patients with multiple sclerosis experiencing acute relapse. Because dyspeptic pain is a common side effect of this intervention, patients can be given a histamine receptor-2 antagonist, proton pump inhibitor or antacid to prevent or ameliorate this disturbance. Additionally, patients with multiple sclerosis may be taking these medications independent of corticosteroid treatment. Interventions for gastric disturbances can influence the activation state of the immune system, a principal mediator of pathology in multiple sclerosis. Although histamine release promotes inflammation, activation of the histamine receptor-2 can suppress a proinflammatory immune response, and blocking histamine receptor-2 with an antagonist could shift the balance more towards immune stimulation. Studies utilizing an animal model of multiple sclerosis indicate that histamine receptor-2 antagonists potentially augment disease activity in patients with multiple sclerosis. In contrast, proton pump inhibitors appear to favor immune suppression, but have not been studied in models of multiple sclerosis. Antacids, histamine receptor-2 antagonists and proton pump inhibitors also could alter the intestinal microflora, which may indirectly lead to immune stimulation. Additionally, elevated gastric pH can promote the vitamin B12 deficiency that patients with multiple sclerosis are at risk of developing. Here, we review possible roles of gastric acid inhibitors on immunopathogenic mechanisms associated with multiple sclerosis