The rules of engagement: how to defend against combinations of predators

Studies of inducible defenses have traditionally examined prey responses to one predator at a time. However, prey in nature encounter combinations of predators that should force them to produce phenotypic compromises. We examined how snails (Helisoma trivolvis) alter their phenotype in the presence of three different predator species that were presented alone and in pairwise combinations. When snails were exposed to each predator alone, they formed predator-specific defenses that reflected the differences in each predator’s foraging mode. When snails were exposed to pairwise combinations of predators, their phenotype was dependent on their ability to detect each predator, the risk posed by each predator, and the effectiveness of a given defense against each predator. Consequently, responses to combined predators were typically biased towards one of the predators in the pair. This suggests that prey facing combined predators do not form simple intermediate defenses and, as a result, may experience enhanced mortality risk when they encounter natural predator regimes.     

The role of antibodies in multiple sclerosis

B cells, plasma cells, and antibodies are commonly found in active central nervous system (CNS) lesions in patients with multiple sclerosis (MS). B cells isolated from CNS lesions as well as from the cerebrospinal fluid (CSF) show signs of clonal expansion and hypermutation, suggesting their local activation. Plasma blasts and plasma cells maturating from these B cells were recently identified to contribute to the development of oligoclonal antibodies produced within the CSF, which remain a diagnostic hallmark finding in MS. Within the CNS, antibody deposition is associated with complement activation and demyelination, indicating antigen recognition-associated effector function. While some studies indeed implied a disease-intrinsic and possibly pathogenic role of antibodies directed against components of the myelin sheath, no unequivocal results on a decisive target antigen within the CNS persisted to date. The notion of a pathogenic role for antibodies in MS is nevertheless empirically supported by the clinical benefit of plasma exchange in patients with histologic signs of antibody deposition within the CNS. Further, such evidence derives from the animal model of MS, experimental autoimmune encephalomyelitis (EAE). In transgenic mice endogenously producing myelin-specific antibodies, EAE severity was substantially increased accompanied by enhanced CNS demyelination. Further, genetic engineering in mice adding T cells that recognize the same myelin antigen resulted in spontaneous EAE development, indicating that the coexistence of myelin-specific B cells, T cells, and antibodies was sufficient to trigger CNS autoimmune disease. In conclusion, various pathological, clinical, immunological, and experimental findings collectively indicate a pathogenic role of antibodies in MS, whereas several conceptual challenges, above all uncovering potential target antigens of the antibody response within the CNS, remain to be overcome.     

Thoughts on the origin and nature of life and intelligence on earth

Believing, for good reasons, that our Universe engenders the occurrence of Life, it is probable that Life appeared more than once on young planet Earth. The universality of our genetic code indicates though, that only one line produced a population that was cellular, autopoietic, responsive intelligently (i.e., to its advantage) to its environment, and capable of reproduction. Its evolution took time during which other intermediate or incipient forms of life disappeared. Trying to retrace ab initio the preceding chemical evolution on our young planet, we may not repeat the chemistry which led to our line. One can argue that it may be profitable to attempt to construct artificial life forms using the kind of building blocks that we learned to know through studying the chemistry of our life. Independently, computers are being built, or are planned, which possess memory that can be used appropriately (intelligently), and which to some extent can repair and reproduce themselves. Such Life does not depend on our biochemistry. However, these machines do perform as yet only partly along the lines of our human intelligence which is guided by self-awareness and a sense of individual integrity, and are thereby not equipped to search for Understanding and Self-expression.     

多发性硬化与病毒感染研究进展

多发性硬化发病机制复杂,病毒感染在其发病中可能起着举足轻重的作用,目前多项研究支持他们之间的关联性;分子模拟、免疫调节网络的失调、表位扩展、旁路激活、超抗原激活和直接细胞损伤等是病毒感染导致多发性硬化发病的主要机理。本文就相关研究进行综述。     

Model misspecification confounds the estimation of rates and exaggerates their time dependency

While welcoming the comment of Ho et al. ( 2015 ), we find little that undermines the strength of our criticism, and it would appear they have misunderstood our central argument. Here we respond with the purpose of reiterating that we are (i) generally critical of much of the evidence presented in support of the time‐dependent molecular rate (TDMR) hypothesis and (ii) specifically critical of estimates of μ derived from tip‐dated sequences that exaggerate the importance of purifying selection as an explanation for TDMR over extended timescales. In response to assertions put forward by Ho et al. ( 2015 ), we use panmictic coalescent simulations of temporal data to explore a fundamental assumption for tip‐dated tree shape and associated mutation rate estimates, and the appropriateness and utility of the date randomization test. The results reveal problems for the joint estimation of tree topology, effective population size and μ with tip‐dated sequences using beast . Given the simulations, beast consistently obtains incorrect topological tree structures that are consistent with the substantial overestimation of μ and underestimation of effective population size. Data generated from lower effective population sizes were less likely to fail the date randomization test yet still resulted in substantially upwardly biased estimates of rates, bringing previous estimates of μ from temporally sampled DNA sequences into question. We find that our general criticisms of both the hypothesis of time‐dependent molecular evolution and Bayesian methods to estimate μ from temporally sampled DNA sequences are further reinforced.     

Recombination, balancing selection and adaptive evolution in the aflatoxin gene cluster of Aspergillus parasiticus

Aflatoxins are toxic and carcinogenic polyketides produced by several Aspergillus species that are known to contaminate agricultural commodities, posing a serious threat to animal and human health. Aflatoxin (AF) biosynthesis is almost fully characterized and involves the coordinated expression of approximately 25 genes clustered in a 70-kb DNA region. Aspergillus parasiticus is an economically important and common agent of AF contamination. Naturally occurring nonaflatoxigenic strains of A. parasiticus are rarely found and generally produce O-methylsterigmatocystin (OMST), the immediate precursor of AF. To elucidate the evolutionary forces acting to retain AF and OMST pathway extrolites (chemotypes), we sequenced 21 intergenic regions spanning the entire cluster in 24 A. parasiticus isolates chosen to represent the genetic diversity within a single Georgia field population. Linkage disequilibrium analyses revealed five distinct recombination blocks in the A. parasiticus cluster. Phylogenetic network analyses showed a history of recombination between chemotype-specific haplotypes, as well as evidence of contemporary recombination. We performed coalescent simulations of variation in recombination blocks and found an approximately twofold deeper coalescence for cluster genealogies compared to noncluster genealogies, our internal standard of neutral evolution. Significantly deeper cluster genealogies are indicative of balancing selection in the AF cluster of A. parasiticus and are further corroborated by the existence of trans-species polymorphisms and common haplotypes in the cluster for several closely related species. Estimates of Ka/Ks for representative cluster genes provide evidence of selection for OMST and AF chemotypes, and indicate a possible role of chemotypes in ecological adaptation and speciation.     

Metabolomic analysis identifies altered metabolic pathways in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic, demyelinating disease that affects the central nervous system and is characterized by a complex pathogenesis and difficult management. The identification of new biomarkers would be clinically useful for more accurate diagnoses and disease monitoring. Metabolomics, the identification of small endogenous molecules, offers an instantaneous molecular snapshot of the MS phenotype. Here the metabolomic profiles (utilizing plasma from patients with MS) were characterized with a Gas cromatography-mass spectrometry-based platform followed by a multivariate statistical analysis and comparison with a healthy control (HC) population. The obtained partial least square discriminant analysis (PLS-DA) model identified and validated significant metabolic differences between individuals with MS and HC (R2X = 0.223, R2Y = 0.82, Q2 = 0.562; p < 0.001). Among discriminant metabolites phosphate, fructose, myo-inositol, pyroglutamate, threonate, l-leucine, l-asparagine, l-ornithine, l-glutamine, and l-glutamate were correctly identified, and some resulted as unknown. A receiver operating characteristic (ROC) curve with AUC 0.84 (p = 0.01; CI: 0.75–1) generated with the concentrations of the discriminant metabolites, supported the strength of the model. Pathway analysis indicated asparagine and citrulline biosynthesis as the main canonical pathways involved in MS. Changes in the citrulline biosynthesis pathway suggests the involvement of oxidative stress during neuronal damage. The results confirmed metabolomics as a useful approach to better understand the pathogenesis of MS and to provide new biomarkers for the disease to be used together with clinical data.     

Indirect nontarget effects of host-specific biological control agents: Implications for biological control

Classical biological control of weeds currently operates under the assumption that biological control agents are safe (i.e., low risk) if they do not directly attack nontarget species. However, recent studies indicate that even highly host-specific biological control agents can impact nontarget species through indirect effects. This finding has profound implications for biological control. To better understand the causes of these interactions and their implications, we evaluate recent case studies of indirect nontarget effects of biological control agents in the context of theoretical work in community ecology. We find that although particular indirect nontarget effects are extremely difficult to predict, all indirect nontarget effects of host specific biological control agents derive from the nature and strength of the interaction between the biological control agent and the pest. Additionally, recent theoretical work suggests that the degree of impact of a biological control agent on nontarget species is proportional to the agent’s abundance, which will be highest for moderately successful control agents. Therefore, the key to safeguarding against indirect nontarget effects of host-specific biological control agents is to ensure the biological control agents are not only host specific, but also efficacious. Biological control agents that greatly reduce their target species while remaining host-specific will reduce their own populations through density-dependent feedbacks that minimize risks to nontarget species.     

Gyroscopic corrections improve wearable sensor data prior to measuring dynamic sway in the gait of people with Multiple Sclerosis

Accelerometers are incorporated into many consumer devices providing new ways to monitor gait, mobility, and fall risk. However, many health benefits have not been realised because of issues with data quality that results from gravitational ‘cross-talk’ when the wearable device is tilted. Here we present an adaptive filter designed to improve the quality of accelerometer data prior to measuring dynamic pelvic sway patterns during a six minute walk test in people with and without Multiple Sclerosis (MS). Optical motion capture was used as the gold standard. Improved wearable device accuracy (≤4.4% NRMSE) was achieved using gyroscopic corrections and scaling filter thresholds by step frequency. The people with MS presented significantly greater pelvis sway range to compensate for their lower limb weaknesses and joint contractures. The visualisation of asymmetric pelvic sway in people with MS illustrates the potential to better understand their mobility impairments for reducing fall risk.     

A structured decision making analysis to increase a Red-cockaded Woodpecker population and balance stakeholder objectives for a National Forest

Longleaf pine (Pinus palustris) savanna is a biodiverse ecosystem native to the southeastern United States. Due to fire suppression and timber harvest, longleaf pine has declined to 3% of its original range. The extant forest provides habitat for many threatened and endangered species, including the endangered Red-cockaded Woodpecker (Picoides borealis; RCW), a cavity-nesting bird that co-evolved with fire-maintained forest, resulting in savanna-like old-growth forest as the bird’s preferred habitat. Our study site, the Oakmulgee Ranger District of the Talladega National Forest, harbors the largest RCW population in Alabama and is managed with an emphasis on RCW conservation. The United States Forest Service (USFS) also manages the Oakmulgee for uses such as wildlife conservation, recreation, and timber harvest. Despite efforts to restore RCW habitat and install artificial cavities in the Oakmulgee, the number of RCW groups has not exceeded 123, although the Recovery Plan objective is 394 groups. Our project was motivated by the USFS expressing interest in determining why the RCW population has not exceeded 123 groups. We proposed using structured decision making (SDM) with the USFS and other stakeholders to address this problem. Our goals were to explicitly define management objectives, build a Bayesian belief network with a model of how decision alternatives are believed to affect management objectives, and use a sensitivity analysis to determine the part of the model to which RCW population growth was most sensitive. Therefore, results from the analysis were expected to give insights into 1) ecological factors limiting RCW population growth, 2) how management can overcome these limits, plus 3) the relative expected ability of different decision alternatives to satisfy multiple objectives in addition to increasing RCW group number. We held four SDM workshops with representatives from the USFS, the Animal and Plant Health Inspection Service, the Longleaf Alliance, the Birmingham Audubon Society, and local residents. Stakeholder objectives consisted of maximizing the following: RCW group number, forest health, recreational enjoyment, community economic health, and aesthetics. Cavity insert installation had the greatest probability of increasing the number of RCW groups. The number of RCW groups was most affected by cavity availability, adult survival, reproductive output, food availability, and herbaceous understory. Prescribed burning was most likely to meet the combination of stakeholder objectives, followed by midstory removal. Our findings suggest that cavity installation efforts may need to be increased in the Oakmulgee to increase RCW group number. Also it could be beneficial to investigate how RCWs select cavity tree locations with the goal of increasing the chance that RCWs use artificial cavities to form new groups. The Bayesian belief network provided insights into factors limiting RCW population growth and how management can overcome these limits. The Bayesian belief network also can be used to prioritize management methods in the Oakmulgee given stakeholder objectives and time constraints.