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Golf swing technician Jim Christine: Bridging the gap between the science of the golf swing and the art of golf coaching: A Commentary

The stimulus article, “Golf swing technician Jim Christine: Bridging the gap between the science of the golf swing and the art of golf coaching”, and the accompanying commentaries present some key issues in golf coaching, especially coach development, technology, coaching methods, and critical thinking. The first two commentaries provide insight about Jim Christine’s development as a coach. International golf coach Peter Green discusses the legendary John Jacobs, who Jim accepted an invitation from to shadow him at one of his golf schools; and John Stirling, who Jim had coaching from on his own golf game. PGA Master Professional Luther Blacklock discusses Alex Hay, who also coached Jim. Both Stirling and Hay were pioneers in the training programme of the Professional Golfers’ Association (PGA) of Great Britain and Ireland in which Jim became highly influential as an author of training resources and as a tutor. There are commentaries from three distinguished members of the PGA of America, the world’s largest working sports organisation: David Wright, John Callahan and Eric Alpenfels. John Callahan shares how he took up opportunities to shadow leading golf coaches such as TJ Tomasi, Craig Shankland and Paul Runyan during his PGA apprenticeship under Frank Cardi. Callahan advocates the use of launch monitors as a technological aid, more staunchly so than Jim Christine who is aware of the limitations in the algorithms involved in providing the output from a radar device like TrackMan for measuring impact factors. Chris Bertram refers to his own empirical research on the use of another technological aid, video feedback, to indicate that “just because technical information is readily available, it does not mean that more information is necessarily serving the interests of the student” (p. 37). Drawing on his doctoral research on operant conditioning, David Wright discusses backward chaining, which is one of the coaching methods used by Jim Christine. Eric Alpenfels discusses Jim’s use of coaching methods in terms of “focus of attention – internal/external swing cues” (p. 33). Researchers Thomas Hawkins et al., suggest that “[the clock analogy], one of Christine’s favoured coaching tools may result in performance and learning benefits [through external focus of attention] because it allows the body to organise movement better than it would if conscious control was either requested or triggered by an internally focused coaching instruction” (p. 35). In a similar vein, Nicky Lumb, a PGA coach “who specialises in golf practice management, skill development and peak performance” (p. 40), indicates that several of Jim’s coaching tools give the golfer an external focus of attention. There is overlap in what Nicky does with Edward Coughlan, a sports scientist whose “main job for players involves asking questions about how they practice, what they practice and inevitably, whether their practice transfers to the competition arena” (p. 42). While two PGA of Great Britain and Ireland professionals, Will Shaw and Gordon Morrison discuss some of Jim’s coaching methods from an Information-Processing perspective, a third one – Noel Rousseau – advocates an Ecological Dynamics/Constraints-led Approach. Rousseau presents the case that “Jim’s coaching methods are staunchly embedded in the Information Processing camp yet he simultaneously highlights some of the shortcoming of coaching this way” (p. 50), especially on the matter of sloping lies (p. 51). Jim describes himself as a “swing technician” (p. 17). Researchers Liam Thomas et al. discuss the notion of a ‘model golf swing’ or ‘technical blue print’ and highlight the challenge of distinguishing between ‘technical faults’ and “the inherent variability both within and between individuals in response to changes in constraints” (p. 54). Tour pro coach, Hugh Marr argues, “Every coach has a picture in their head of what a great swing looks like. It’s not the model that makes coaches great, it’s the understanding of what George Gankas calls ‘match-ups’ – if a player displays one particular swing characteristic, they need to match it with another swing characteristic that complements it” (p. 57). The final two commentaries, by research professor David Grecic and performance coach Jon Roy, both emphasize the development of critical thinking in coaches, with the latter arguing that “Jim’s critical faculties comprise dialectics, scepticism, and innovation” (p. 63)

Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve

Repeat doses of antibody to serum amyloid P component clear amyloid deposits in patients with systemic amyloidosis

Systemic amyloidosis is a fatal disorder caused by pathological extracellular deposits of amyloid fibrils that are always coated with the normal plasma protein, serum amyloid P component (SAP). The small-molecule drug, miridesap, [(R)-1-[6-[(R)-2-carboxy-pyrrolidin-1-yl]-6-oxo-hexanoyl]pyrrolidine-2-carboxylic acid (CPHPC)] depletes circulating SAP but leaves some SAP in amyloid deposits. This residual SAP is a specific target for dezamizumab, a fully humanized monoclonal IgG1 anti-SAP antibody that triggers immunotherapeutic clearance of amyloid. We report the safety, pharmacokinetics, and dose-response effects of up to three cycles of miridesap followed by dezamizumab in 23 adult subjects with systemic amyloidosis (ClinicalTrials.gov identifier: NCT01777243). Amyloid load was measured scintigraphically by amyloid-specific radioligand binding of 123I-labeled SAP or of 99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid. Organ extracellular volume was measured by equilibrium magnetic resonance imaging and liver stiffness by transient elastography. The treatment was well tolerated with the main adverse event being self-limiting early onset rashes after higher antibody doses related to whole body amyloid load. Progressive dose-related clearance of hepatic amyloid was associated with improved liver function tests. 123I-SAP scintigraphy confirmed amyloid removal from the spleen and kidneys. No adverse cardiac events attributable to the intervention occurred in the six subjects with cardiac amyloidosis. Amyloid load reduction by miridesap treatment followed by dezamizumab has the potential to improve management and outcome in systemic amyloidosis

Metabolic flexibility as a major predictor of spatial distribution in microbial communities

A better understand the ecology of microbes and their role in the global ecosystem could be achieved if traditional ecological theories can be applied to microbes. In ecology organisms are defined as specialists or generalists according to the breadth of their niche. Spatial distribution is often used as a proxy measure of niche breadth; generalists have broad niches and a wide spatial distribution and specialists a narrow niche and spatial distribution. Previous studies suggest that microbial distribution patterns are contrary to this idea; a microbial generalist genus (Desulfobulbus) has a limited spatial distribution while a specialist genus (Methanosaeta) has a cosmopolitan distribution. Therefore, we hypothesise that this counter-intuitive distribution within generalist and specialist microbial genera is a common microbial characteristic. Using molecular fingerprinting the distribution of four microbial genera, two generalists, Desulfobulbus and the methanogenic archaea Methanosarcina, and two specialists, Methanosaeta and the sulfate-reducing bacteria Desulfobacter were analysed in sediment samples from along a UK estuary. Detected genotypes of both generalist genera showed a distinct spatial distribution, significantly correlated with geographic distance between sites. Genotypes of both specialist genera showed no significant differential spatial distribution. These data support the hypothesis that the spatial distribution of specialist and generalist microbes does not match that seen with specialist and generalist large organisms. It may be that generalist microbes, while having a wider potential niche, are constrained, possibly by intrageneric competition, to exploit only a small part of that potential niche while specialists, with far fewer constraints to their niche, are more capable of filling their potential niche more effectively, perhaps by avoiding intrageneric competition. We suggest that these counter-intuitive distribution patterns may be a common feature of microbes in general and represent a distinct microbial principle in ecology, which is a real challenge if we are to develop a truly inclusive ecology

Antagonism between Gdf6a and retinoic acid pathways controls timing of retinal neurogenesis and growth of the eye in zebrafish.

Maintaining neurogenesis in growing tissues requires a tight balance between progenitor cell proliferation and differentiation. In the zebrafish retina, neuronal differentiation proceeds in two stages with embryonic retinal progenitor cells (RPCs) of the central retina accounting for the first rounds of differentiation, and stem cells from the ciliary marginal zone (CMZ) being responsible for late neurogenesis and growth of the eye. In this study, we analyse two mutants with small eyes that display defects during both early and late phases of retinal neurogenesis. These mutants carry lesions in gdf6a, a gene encoding a BMP family member previously implicated in dorsoventral patterning of the eye. We show that gdf6a mutant eyes exhibit expanded retinoic acid (RA) signalling and demonstrate that exogenous activation of this pathway in wild-type eyes inhibits retinal growth, generating small eyes with a reduced CMZ and fewer proliferating progenitors, similar to gdf6a mutants. We provide evidence that RA regulates the timing of RPC differentiation by promoting cell cycle exit. Furthermore, reducing RA signalling in gdf6a mutants re-establishes appropriate timing of embryonic retinal neurogenesis and restores putative stem and progenitor cell populations in the CMZ. Together, our results support a model in which dorsally expressed gdf6a limits RA pathway activity to control the transition from proliferation to differentiation in the growing eye

Edible crabs “Go West”: migrations and incubation cycle of Cancer pagurus revealed by electronic tags

Crustaceans are key components of marine ecosystems which, like other exploited marine taxa, show seasonable patterns of distribution and activity, with consequences for their availability to capture by targeted fisheries. Despite concerns over the sustainability of crab fisheries worldwide, difficulties in observing crabs’ behaviour over their annual cycles, and the timings and durations of reproduction, remain poorly understood. From the release of 128 mature female edible crabs tagged with electronic data storage tags (DSTs), we demonstrate predominantly westward migration in the English Channel. Eastern Channel crabs migrated further than western Channel crabs, while crabs released outside the Channel showed little or no migration. Individual migrations were punctuated by a 7-month hiatus, when crabs remained stationary, coincident with the main period of crab spawning and egg incubation. Incubation commenced earlier in the west, from late October onwards, and brooding locations, determined using tidal geolocation, occurred throughout the species range. With an overall return rate of 34%, our results demonstrate that previous reluctance to tag crabs with relatively high-cost DSTs for fear of loss following moulting is unfounded, and that DSTs can generate precise information with regards life-history metrics that would be unachievable using other conventional means

Reporting and evaluating genetic association studies

Genetic association studies have become an important part of our scientific landscape. This commentary discusses some basic scientific issues which should be considered when reporting and evaluating such studies including SNP Discovery, Genotyping and Haplotype Analysis; Population Size, Matching of Cases and Controls, and Population Stratification; Phenotype Definition and Multiple Related Phenotypes; Multiple Testing; Replication; Genome-wide Association Studies (GWAS); and the Role of Functional Studies. All of these elements are important in evaluating such studies and should be carefully considered when these studies are conceived and carried out

Applying refinement to the use of mice and rats in rheumatoid arthritis research

Rheumatoid arthritis (RA) is a painful, chronic disorder and there is currently an unmet need for effective therapies that will benefit a wide range of patients. The research and development process for therapies and treatments currently involves in vivo studies, which have the potential to cause discomfort, pain or distress. This Working Group report focuses on identifying causes of suffering within commonly used mouse and rat ‘models’ of RA, describing practical refinements to help reduce suffering and improve welfare without compromising the scientific objectives. The report also discusses other, relevant topics including identifying and minimising sources of variation within in vivo RA studies, the potential to provide pain relief including analgesia, welfare assessment, humane endpoints, reporting standards and the potential to replace animals in RA research

Evaluation of machine-learning methods for ligand-based virtual screening

Machine-learning methods can be used for virtual screening by analysing the structural characteristics of molecules of known (in)activity, and we here discuss the use of kernel discrimination and naive Bayesian classifier (NBC) methods for this purpose. We report a kernel method that allows the processing of molecules represented by binary, integer and real-valued descriptors, and show that it is little different in screening performance from a previously described kernel that had been developed specifically for the analysis of binary fingerprint representations of molecular structure. We then evaluate the performance of an NBC when the training-set contains only a very few active molecules. In such cases, a simpler approach based on group fusion would appear to provide superior screening performance, especially when structurally heterogeneous datasets are to be processed