Learning from the voiceless

This article is concerned with understanding what is at stake in the everyday lives of family members facing Huntington's Disease (HD). The methodological and analytical point of departure is German critical psychology, particularly the category of conduct of everyday life (Holzkamp, 1995; Dreier, 1999). Specifically, I address questions of accessing and understanding the conduct of everyday life of persons facing HD who are not visibly visibly active with respect to this circumstance. The question of access is not merely about getting in touch with persons who are not known to the research, professional and HD communities, but also about the consequences of establishing contact with persons who have not made an entry onto any of these public areanas themselves. The question of understanding is about developing an analysis from a first-person perspective on the personal conduct of everyday life that is not visibly active. The development of such an understanding has broader implications, not just for further research and health care practices, but importantly also for the prevailing moral and ethical demands made on persons living at risk of hereditary diseases.     

Vulnerability and strength--giving voice to the voiceless

This article examines the requisites of working with people who are interpersonally, institutionally, and politically oppressed and therefore vulnerable. To work successfully with them requires that we understand their vulnerability, appreciate their strengths and resources, and recognize the remarkable heroism of their daily lives. This insight is especially useful for professionals in the fields of health, mental health, public welfare, and family services.     

向传统学习

向传统学习,就是要学习在当地民族在石漠化地区如何靠植物去覆盖裸露的岩石,在农牧经营中如何绕开生态的脆弱环节,以求生存的文化精髓。     

Learning lessons in sepsis from the children

Sepsis research has had relatively limited therapeutic success so far. In their recent study, Kobzik and colleagues (Joachim et al, 2018 ) identify novel drug‐sensitive pathways in sepsis, derived exclusively from patient data. Their strategy is based on the analysis of a naturally sepsis‐resistant population (pre‐puberty children) and on the implementation of a novel‐rich Pathway Drug Network, constructed from human gene expression data enriched in drug–pathway–gene clusters.     

Learning from the past: palaeohydrology and palaeoecology

Attempts to increase European biodiversity by restoring rivers and floodplains are based on inadequate data on natural systems. This is particularly the case for NW European rivers because all catchments have been impacted by agriculture and river engineering. If river restoration is to have an ecological, as opposed to `cosmetic' design basis then baseline models are required. However, this poses three questions; (a) what is the natural river‐floodplain state, (b) how can it be defined and modelled and (c) can this state be recreated today? The first two questions can only be addressed by using palaeohydrological and palaeoecological data. A second and equally vital consideration is the stability/instability of any restored system to change in external forcing factors (e.g. climate) and in this context it may not be realistic to expect baseline models to provide equilibrium solutions but instead to define process‐form domains. Over the last two decades evidence has accumulated that the natural state of lowland rivers in much of NW Europe was multi rather than single thread‐braided, anastomosing or anabranching. Until recently our knowledge of floodplain palaeoecology was generally derived from pollen diagrams, which have source‐area of problems and lack of taxonomic specificity. The precision and breadth of palaeoecological reconstruction (including richness and structure) has been greatly increased by the use of multiple palaeo‐indicators including macrofossils, diatoms and beetles. The dynamics of small to medium sized, low‐energy, predeforestation floodplains were dominated by disturbance (windthrow, beavers, etc.) and large woody debris. In order to compare the hydrogeomorphological basis of floodplain ecology, both temporally and spatially, a simple index of fluvial complexity is presented. Palaeoecological and geomorphological investigations have the potential to provide in‐depth models of the natural range of channel conditions and sensitivity to external change that can be used to provide a scientific basis for floodplain restoration. There is also the possibility that floodplain‐channel restoration may be a valuable tool in the mitigation of future geomorphological change forced by climatic instability.     

Learning Natural Selection from the Site Frequency Spectrum

Genetic adaptation to external stimuli occurs through the combined action of mutation and selection. A central problem in genetics is to identify loci responsive to specific selective constraints. Many tests have been proposed to identify the genomic signatures of natural selection by quantifying the skew in the site frequency spectrum (SFS) under selection relative to neutrality. We build upon recent work that connects many of these tests under a common framework, by describing how selective sweeps affect the scaled SFS. We show that the specific skew depends on many attributes of the sweep, including the selection coefficient and the time under selection. Using supervised learning on extensive simulated data, we characterize the features of the scaled SFS that best separate different types of selective sweeps from neutrality. We develop a test, SFselect, that consistently outperforms many existing tests over a wide range of selective sweeps. We apply SFselect to polymorphism data from a laboratory evolution experiment of Drosophila melanogaster adapted to hypoxia and identify loci that strengthen the role of the Notch pathway in hypoxia tolerance, but were missed by previous approaches. We further apply our test to human data and identify regions that are in agreement with earlier studies, as well as many novel regions.     

Learning continuous potentials from smFRET

Potential energy landscapes are useful models in describing events such as protein folding and binding. While single-molecule fluorescence resonance energy transfer (smFRET) experiments encode information on continuous potentials for the system probed, including rarely visited barriers between putative potential minima, this information is rarely decoded from the data. This is because existing analysis methods often model smFRET output assuming, from the onset, that the system probed evolves in a discretized state space to be analyzed within a hidden Markov model (HMM) paradigm. By contrast, here, we infer continuous potentials from smFRET data without discretely approximating the state space. We do so by operating within a Bayesian nonparametric paradigm by placing priors on the family of all possible potential curves. As our inference accounts for a number of required experimental features raising computational cost (such as incorporating discrete photon shot noise), the framework leverages a structured-kernel-interpolation Gaussian process prior to help curtail computational cost. We show that our structured-kernel-interpolation priors for potential energy reconstruction from smFRET analysis accurately infers the potential energy landscape from a smFRET binding experiment. We then illustrate advantages of structured-kernel-interpolation priors for potential energy reconstruction from smFRET over standard HMM approaches by providing information, such as barrier heights and friction coefficients, that is otherwise inaccessible to HMMs.     

Learning from Our Treatment Failures

Barton and Blanchard's report that multicomponent behavioral treatment fails to modify chronic daily headaches is discussed with reference to the effectiveness of behavioral and drug treatments for chronic tension-type headache, the distinction between chronic tension-type headache and chronic migraine, and the psychophysiology of episodic vs. persistent pain (K. A. Barton & E. B. Blanchard, 2001). It is suggested that the treatment of chronic daily headache can be improved through research on the benefits of combined behavioral and drug therapy, the psychophysiology of persistent pain, and methods of preventing episodic headaches from evolving to daily headaches.