Feel good,do good? Disentangling reciprocity from unconditional prosociality

Direct and generalised reciprocity can establish evolutionarily stable levels of cooperation among unrelated individuals, with animals reciprocating help based on whether they have been helped by a social partner before. It has been argued that the actual cooperative act by a social partner may be of minor importance for seemingly reciprocal cooperation and that a mere positive experience might suffice to enhance helpful behaviour towards a conspecific (‘feel good, do good’). However, this effect could easily be exploited by defectors free‐riding on an individual's enhanced propensity to cooperate after an unspecific positive experience, without investing in reciprocity themselves. Here, we use female Norway rats (Rattus norvegicus) to test if a positive experience that was not provided by a helping partner increases the propensity to subsequently help a social partner. We manipulated the experience of test subjects by providing them with treats, either in the presence or absence of a conspecific. Thereafter, we assessed whether they produce treats and if so, how many, for an unfamiliar social partner compared to a situation in which they had not received treats before. As the treats the test subject received had not been provided by a social partner even if the partner was present, we predicted that the rats should not be more cooperative after they had received treats than if they had not. Indeed, the helping behaviour of rats was apparently not influenced by prior experience made either in a social or non‐social context. Rats have been shown previously to perform both direct and generalised reciprocity in the same variant of the iterated prisoner's dilemma game. Our results suggest that this behaviour cannot be explained by an unspecific positive experience. The decision to help a social partner seems to be contingent on previously receiving help from a social partner (reciprocity), not on any positive experience (unconditional prosociality).     

What constitutes good prescribing?

Drugs are the mainstay of medical treatment, yet there are few reports on what constitutes "good prescribing." What is more the existing guidance tends to imply that right answers exist, rather than recognising the complex trade offs that have to be made between conflicting aims. This paper proposes four aims that a prescriber should try to achieve, both on first prescribing a drug and on subsequently monitoring it. They are: to maximise effectiveness, minimise risks, minimise costs, and respect the patient''s choices. This model of good prescribing brings together the traditional balancing of risks and benefits with the need to reduce costs and the right of the patient to make choices in treatment. The four aims are shown as a diagram plotting their commonest conflicts, which may be used as an aid to discussion and decision making.     

When are good genes good? Variable outcomes of female choice in wax moths

Female lesser wax moths (Achroia grisella) choose males based on characters of their ultrasonic advertisement signals. Because a female''s opportunity to obtain increased somatic benefits by mating with a particular male is limited, we investigated whether females obtain genetic benefits for their offspring via mate choice. Controlled breeding experiments conducted under favourable food and temperature conditions showed that developmental characters are heritable, that sire attractiveness and offspring survivorship are unrelated, but that females mating with attractive signallers produce offspring who mature faster than the offspring of females mating with non-attractive signallers. However, under some unfavourable food or temperature conditions, it is the offspring of females mating with non-attractive males who mature faster; these offspring are heavier as well. Thus, the relationship between male attractiveness and offspring development is not environmentally robust, and support for a good genes model of mate choice in A. grisella is dependent on conditions. These findings suggest genotype–environment interactions and emphasize the necessity of testing sexual selection models under a range of natural environments.     

Do frogs make good canaries?

Coal miners used to take canaries with them into coal mines; more sensitive than humans to poisonous gases, they provided a living early-warning system. Are recent population declines among the world's frogs warning us of an environmental catastrophe to come?     

How good is our genome?

Our genome has evolved to perpetuate itself through the maintenance of the species via an uninterrupted chain of reproductive somas. Accordingly, evolution is not concerned with diseases occurring after the soma's reproductive stage. Following Richard Dawkins, we would like to reassert that we indeed live as disposable somas, slaves of our germline genome, but could soon start rebelling against such slavery. Cancer and its relation to the TP53 gene may offer a paradigmatic example. The observation that the latency period in cancer can be prolonged in mice by increasing the number of TP53 genes in their genome, suggests that sooner or later we will have to address the question of heritable disease avoidance via the manipulation of the human germline.     

Optimal isn’t good enough

The notion that biological systems come to embody optimal solutions seems consistent with the competitive drive of evolution. It has been used to interpret many examples of sensorimotor behavior. It is attractive from the viewpoint of control engineers because it solves the redundancy problem by identifying the one optimal motor strategy out of many similarly acceptable possibilities. This perspective examines whether there is sufficient basis to apply the formal engineering tools of optimal control to a reductionist understanding of biological systems. For an experimental biologist, this translates into whether the theory of optimal control generates nontrivial and testable hypotheses that accurately predict novel phenomena, ideally at deeper levels of structure than the observable behavior. The methodology of optimal control is applicable when there is (i) a single, known cost function to be optimized, (ii) an invertible model of the plant, and (iii) simple noise interfering with optimal performance. None of these is likely to be true for biological organisms. Furthermore, their motivation is usually good-enough rather than globally optimal behavior. Even then, the performance of a biological organism is often much farther from optimal than the physical limits of its hardware because the brain is continuously testing the acceptable limits of performance as well as just performing the task. This perspective considers an alternative strategy called ??good-enough?? control, in which the organism uses trial-and-error learning to acquire a repertoire of sensorimotor behaviors that are known to be useful, but not necessarily optimal. This leads to a diversity of solutions that tends to confer robustness on the individual organism and its evolution. It is also more consistent with the capabilities of higher sensorimotor structures, such as cerebral cortex, which seems to be designed to classify and recall complex sets of information, thereby allowing the organism to learn from experience, rather than to compute new strategies online. Optimal control has been a useful metaphor for understanding some superficial aspects of motor psychophysics. Reductionists who want to understand the underlying neural mechanisms need to move on.     

What is mzXML good for?

mzXML (extensible markup language) is one of the pioneering data formats for mass spectrometry-based proteomics data collection. It is an open data format that has benefited and evolved as a result of the input of many groups, and it continues to evolve. Due to its dynamic history, its structure, purpose and applicability have all changed with time, meaning that groups that have looked at the standard at different points during its evolution have differing impressions of the usefulness of mzXML. In discussing mzXML, it is important to understand what mzXML is not. First, mzXML does not capture the raw data. Second, mzXML is not sufficient for regulatory submission. Third, mzXML is not optimized for computation and, finally, mzXML does not capture the experiment design. In general, it is the authors' opinion that XML is not a panacea for bioinformatics or a substitute for good data representation, and groups that want to use mzXML (or other XML-based representations) directly for data storage or computation will encounter performance and scalability problems. With these limitations in mind, the authors conclude that mzXML is, nonetheless, an indispensable data exchange format for proteomics.     

What are oligomerization domains good for?

Collagen triple helices, coiled coils and other oligomerization domains mediate the subunit assembly of a large number of proteins. Oligomerization leads to functional advantages of multivalency and high binding strength, increased structure stabilization and combined functions of different domains. These features seen in naturally occurring proteins can be engineered by protein design by combining oligomerization domains with functional domains.     

How good are deep phylogenetic trees?

Great interest is given to species emerging early in phylogenetic reconstruction because they are often assumed to represent an ancestor. Recent studies indicate, however, that species branching deep in molecular trees are often fast-evolving ones, misplaced because of the long-branch artefact. The detection of genuinely deep-branching organisms remains an elusive task.