A Fatty Acid Based Bayesian Approach for Inferring Diet in Aquatic Consumers

We modified the stable isotope mixing model MixSIR to infer primary producer contributions to consumer diets based on their fatty acid composition. To parameterize the algorithm, we generated a ‘consumer-resource library’ of FA signatures of Daphnia fed different algal diets, using 34 feeding trials representing diverse phytoplankton lineages. This library corresponds to the resource or producer file in classic Bayesian mixing models such as MixSIR or SIAR. Because this library is based on the FA profiles of zooplankton consuming known diets, and not the FA profiles of algae directly, trophic modification of consumer lipids is directly accounted for. To test the model, we simulated hypothetical Daphnia comprised of 80% diatoms, 10% green algae, and 10% cryptophytes and compared the FA signatures of these known pseudo-mixtures to outputs generated by the mixing model. The algorithm inferred these simulated consumers were comprised of 82% (63-92%) [median (2.5th to 97.5th percentile credible interval)] diatoms, 11% (4-22%) green algae, and 6% (0-25%) cryptophytes. We used the same model with published phytoplankton stable isotope (SI) data for δ¹³C and δ¹⁵N to examine how a SI based approach resolved a similar scenario. With SI, the algorithm inferred that the simulated consumer assimilated 52% (4-91%) diatoms, 23% (1-78%) green algae, and 18% (1-73%) cyanobacteria. The accuracy and precision of SI based estimates was extremely sensitive to both resource and consumer uncertainty, as well as the trophic fractionation assumption. These results indicate that when using only two tracers with substantial uncertainty for the putative resources, as is often the case in this class of analyses, the underdetermined constraint in consumer-resource SI analyses may be intractable. The FA based approach alleviated the underdetermined constraint because many more FA biomarkers were utilized (n < 20), different primary producers (e.g., diatoms, green algae, and cryptophytes) have very characteristic FA compositions, and the FA profiles of many aquatic primary consumers are strongly influenced by their diets.     

A sparse neural code for some speech sounds but not for others

The precise neural mechanisms underlying speech sound representations are still a matter of debate. Proponents of 'sparse representations' assume that on the level of speech sounds, only contrastive or otherwise not predictable information is stored in long-term memory. Here, in a passive oddball paradigm, we challenge the neural foundations of such a 'sparse' representation; we use words that differ only in their penultimate consonant ("coronal" [t] vs. "dorsal" [k] place of articulation) and for example distinguish between the German nouns Latz ([lats]; bib) and Lachs ([laks]; salmon). Changes from standard [t] to deviant [k] and vice versa elicited a discernible Mismatch Negativity (MMN) response. Crucially, however, the MMN for the deviant [lats] was stronger than the MMN for the deviant [laks]. Source localization showed this difference to be due to enhanced brain activity in right superior temporal cortex. These findings reflect a difference in phonological 'sparsity': Coronal [t] segments, but not dorsal [k] segments, are based on more sparse representations and elicit less specific neural predictions; sensory deviations from this prediction are more readily 'tolerated' and accordingly trigger weaker MMNs. The results foster the neurocomputational reality of 'representationally sparse' models of speech perception that are compatible with more general predictive mechanisms in auditory perception.     

Mechanisms of NLRP1-Mediated Autoinflammatory Disease in Humans and Mice

NLRP1 was the first NOD-like receptor described to form an inflammasome, recruiting ASC to activate caspase-1, which processes interleukin-1β and interleukin-18 to their active form. A wealth of new genetic information has now redefined our understanding of this innate immune sensor. Specifically, rare loss-of-function variants in the N-terminal pyrin domain indicate that this part of NLRP1 is autoinhibitory and normally acts to prevent a familial autoinflammatory skin disease associated with cancer. In the absence of a ligand to trigger human NLRP1, these mutations have now confirmed the requirement of NLRP1 autolytic cleavage within the FIIND domain, which had previously been implicated in NLRP1 activation. Autolytic cleavage generates a C-terminal fragment of NLRP1 containing the CARD domain which then forms an ASC-dependent inflammasome. The CARD domain as an inflammasome linker is consistent with the observation that under some conditions, particularly for mouse NLRP1, caspase-1 can be engaged directly, and although it is no longer processed, it is still capable of producing mature IL-1β. Additional rare variants in a linker region between the LRR and FIIND domains of NLRP1 also cause autoinflammatory disease in both humans and mice. This new genetic information is likely to provide for more mechanistic insight in the years to come, contributing to our understanding of how NLRP1 functions as an innate immune sensor of infection and predisposes to autoimmune or autoinflammatory diseases.     

地表自然过程排汞研究进展及展望

地表自然过程排汞包括了自然源排汞过程和先前排放的汞沉降到地表后的再排放过程.已有证据显示,地表自然过程向大气的排汞量可能远大于人为活动直接向大气的排汞量.准确确定自然过程汞的释放通量,不仅对正确评价目前减少人为活动向大气排汞对全球环境汞污染的影响程度具有重要的意义,而且可为全球大气汞的减排政策的制定提供重要科学理论依据.本综述通过对国内外地表自然排放源相关文献的调研分析发现:由于缺少可靠的观测技术、对地表与大气间汞交换过程和机理的准确认识及大气汞沉降对地表自然排汞过程影响的认识还不清楚,因此目前还难以准确估算地表自然过程向大气的排汞量.近年来,随着技术手段的进步,已具备了开展地表自然排汞及先前排汞沉降后的再释放过程、机理和通量研究的可行性.地表自然过程排汞的研究将是汞的生物地球化学循环演化研究领域的前沿之一.     

High-Throughput Screening of Multispecies Biofilm Formation and Quantitative PCR-Based Assessment of Individual Species Proportions,Useful for Exploring Interspecific Bacterial Interactions

Multispecies biofilms are predominant in almost all natural environments, where myriads of resident microorganisms interact with each other in both synergistic and antagonistic manners. The interspecies interactions among different bacteria are, despite the ubiquity of these communities, still poorly understood. Here, we report a rapid, reproducible and sensitive approach for quantitative screening of biofilm formation by bacteria when cultivated as mono- and multispecies biofilms, based on the Nunc-TSP lid system and crystal violet staining. The relative proportion of the individual species in a four-species biofilm was assessed using quantitative PCR based on SYBR Green I fluorescence with specific primers. The results indicated strong synergistic interactions in a four-species biofilm model community with a more than 3-fold increase in biofilm formation and demonstrated the strong dominance of two strains, Xanthomonas retroflexus and Paenibacillus amylolyticus. The developed approach can be used as a standard procedure for evaluating interspecies interactions in defined microbial communities. This will be of significant value in the quantitative study of the microbial composition of multispecies biofilms both in natural environments and infectious diseases to increase our understanding of the mechanisms that underlie cooperation, competition and fitness of individual species in mixed-species biofilms.     

Metabolism of ethanol in vitro produces a compound which induces sister-chromatid exchanges in human peripheral lymphocytes in vitro: acetaldehyde not ethanol is mutagenic

Ethanol (EtOH) in the presence of the EtOH-metabolizing enzyme, alcohol dehydrogenase (ADH) leads to the induction of sister-chromatid exchanges (SCEs) in human peripheral lymphocytes in vitro. Acetaldehyde (AA) induces SCEs, whose frequencies are lowered in the presence of the AA-metabolizing enzyme, aldehyde dehydrogenase (ALDH). EtOH in the presence of ADH produces more SCEs than EtOH in the presence of ADH and ALDH. These data are interpreted to show that not ethanol itself, but its first metabolite acetaldehyde is mutagenic.     

Nitric oxide from neuronal nitric oxide synthase sensitises neurons to hypoxia-induced death via competitive inhibition of cytochrome oxidase

Hypoxia/ischaemia is known to trigger neuronal death, but the role of neuronal nitric oxide synthase (nNOS) in this process is controversial. Nitric oxide (NO) inhibits cytochrome oxidase in competition with oxygen. We tested whether NO derived from nNOS synergises with hypoxia to induce neuronal death by inhibiting mitochondrial cytochrome oxidase. Sixteen hours of hypoxia (2% oxygen) plus deoxyglucose (an inhibitor of glycolysis) caused extensive, excitotoxic death of neurons in rat cerebellar granule cell cultures. Three different nNOS inhibitors (including the selective inhibitor N-4S-4-amino-5-2-aminoethyl-aminopentyl-N'-nitroguanidine) decreased this neuronal death by half, indicating a contribution of nNOS to hypoxic death. The selective nNOS inhibitor did not, however, block neuronal death induced either by added glutamate or by added azide (an uncompetitive inhibitor of cytochrome oxidase), indicating that nNOS does not act downstream of glutamate or cytochrome oxidase. Hypoxia plus deoxyglucose-induced glutamate release and neuronal depolarisation, and the nNOS inhibitor decreased this. Hypoxia inhibited cytochrome oxidase activity in the cultures, but a selective nNOS inhibitor prevented this inhibition, indicating NO from nNOS was inhibiting cytochrome oxidase in competition with oxygen. These data indicate that hypoxia synergises with NO from nNOS to induce neuronal death via cytochrome oxidase inhibition causing neuronal depolarisation. This mechanism might contribute to ischaemia/stroke-induced neuronal death in vivo.     

Where are Europe’s last primary forests?

Aim

Primary forests have high conservation value but are rare in Europe due to historic land use. Yet many primary forest patches remain unmapped, and it is unclear to what extent they are effectively protected. Our aim was to (1) compile the most comprehensive European‐scale map of currently known primary forests, (2) analyse the spatial determinants characterizing their location and (3) locate areas where so far unmapped primary forests likely occur.

Location

Europe.

Methods

We aggregated data from a literature review, online questionnaires and 32 datasets of primary forests. We used boosted regression trees to explore which biophysical, socio‐economic and forest‐related variables explain the current distribution of primary forests. Finally, we predicted and mapped the relative likelihood of primary forest occurrence at a 1‐km resolution across Europe.

Results

Data on primary forests were frequently incomplete or inconsistent among countries. Known primary forests covered 1.4 Mha in 32 countries (0.7% of Europe’s forest area). Most of these forests were protected (89%), but only 46% of them strictly. Primary forests mostly occurred in mountain and boreal areas and were unevenly distributed across countries, biogeographical regions and forest types. Unmapped primary forests likely occur in the least accessible and populated areas, where forests cover a greater share of land, but wood demand historically has been low.

Main conclusions

Despite their outstanding conservation value, primary forests are rare and their current distribution is the result of centuries of land use and forest management. The conservation outlook for primary forests is uncertain as many are not strictly protected and most are small and fragmented, making them prone to extinction debt and human disturbance. Predicting where unmapped primary forests likely occur could guide conservation efforts, especially in Eastern Europe where large areas of primary forest still exist but are being lost at an alarming pace.