Protein Arrays: Issues to Be Addressed

Protein arrays are fast becoming established as a means to monitor protein expression levels and investigate protein interactions and function. They present particular technical demands that will need to be solved in order to achieve the maximum capability of efficient and sensitive protein analysis in the high throughput setting of functional genomics. The following resumé of some major issues around this new technology was made as the chairperson’s introduction to the workshop session on peptide and protein chips

Cellular preservation of musculoskeletal specializations in the Cretaceous bird Confuciusornis

The hindlimb of theropod dinosaurs changed appreciably in the lineage leading to extant birds, becoming more ‘crouched’ in association with changes to body shape and gait dynamics. This postural evolution included anatomical changes of the foot and ankle, altering the moment arms and control of the muscles that manipulated the tarsometatarsus and digits, but the timing of these changes is unknown. Here, we report cellular-level preservation of tendon- and cartilage-like tissues from the lower hindlimb of Early Cretaceous Confuciusornis. The digital flexor tendons passed through cartilages, cartilaginous cristae and ridges on the plantar side of the distal tibiotarsus and proximal tarsometatarsus, as in extant birds. In particular, fibrocartilaginous and cartilaginous structures on the plantar surface of the ankle joint of Confuciusornis may indicate a more crouched hindlimb posture. Recognition of these specialized soft tissues in Confuciusornis is enabled by our combination of imaging and chemical analyses applied to an exceptionally preserved fossil

Reinforcement learning or active inference?

This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain

Particle swarm control

International audienceControlling several and possibly independent moving agents in order to reach global goals is a tedious task that has applications in many engineering fields such as robotics or computer animation. Together, the different agents form a whole called swarm, which may display interesting collective behaviors. When the agents are driven by their own dynamics, controlling this swarm is known as the particle swarm control problem. In that context, several strategies, based on the control of individuals using simple rules, exist. This paper defends a new and original method based on a centralized approach. More precisely, we propose a framework to control several particles with constraints either expressed on a per-particle basis, or expressed as a function of their environment. We refer to these two categories as respectively Lagrangian or Eulerian constraints. The contributions of the paper are the following: (i) we show how to use optimal control recipes to express an optimization process over a large state space including the dynamic information of the particles; and (ii) the relation between the Lagrangian state space and Eulerian values is conveniently expressed with graph operators that make it possible to conduct all the mathematical operations required by the control process. We show the effectiveness of our approach on classical and more original particle swarm control problems

MR imaging of osteochondral grafts and autologous chondrocyte implantation

Surgical articular cartilage repair therapies for cartilage defects such as osteochondral autograft transfer, autologous chondrocyte implantation (ACI) or matrix associated autologous chondrocyte transplantation (MACT) are becoming more common. MRI has become the method of choice for non-invasive follow-up of patients after cartilage repair surgery. It should be performed with cartilage sensitive sequences, including fat-suppressed proton density-weighted T2 fast spin-echo (PD/T2-FSE) and three-dimensional gradient-echo (3D GRE) sequences, which provide good signal-to-noise and contrast-to-noise ratios. A thorough magnetic resonance (MR)-based assessment of cartilage repair tissue includes evaluations of defect filling, the surface and structure of repair tissue, the signal intensity of repair tissue and the subchondral bone status. Furthermore, in osteochondral autografts surface congruity, osseous incorporation and the donor site should be assessed. High spatial resolution is mandatory and can be achieved either by using a surface coil with a 1.5-T scanner or with a knee coil at 3 T; it is particularly important for assessing graft morphology and integration. Moreover, MR imaging facilitates assessment of complications including periosteal hypertrophy, delamination, adhesions, surface incongruence and reactive changes such as effusions and synovitis. Ongoing developments include isotropic 3D sequences, for improved morphological analysis, and in vivo biochemical imaging such as dGEMRIC, T2 mapping and diffusion-weighted imaging, which make functional analysis of cartilage possible

Profile of down syndrome–associated malignancies: Epidemiology, clinical features and therapeutic aspects

Down syndrome (DS) is a congenital chromosomal abnormality caused by the presence of all or part of a third copy of chromosome 21 (+21). DS is frequently complicated by congenital heart or digestive tract diseases at birth. DS patients are prone to infections and have mental retardation, with dementia such as Alzheimer's disease showing in later life. Furthermore, malignancies with specific characteristics are also highly reported in DS patients compared with non-DS patients. Therefore, DS is believed to be a cancer predisposition syndrome due to the chromosomal instability. Acute myeloid leukemia (AML) and especially acute megakaryoblastic leukemia (AMKL) by French-American-British (FAB) classification are the most frequent hematological malignancies in DS patients, occurring at a rate that is 500 times higher than that in non-DS patients. Interestingly, transient abnormal myelopoiesis (TAM) is observed in approximately 10% of DS neonates with GATA1 mutations, and most TAM patients are asymptomatic and show spontaneous regression; however, about 10%–20% of TAM cases are fatal because of complications such as fetal effusion, liver fibrosis, and other complications.Acute lymphoblastic leukemia (ALL) is also associated with DS, occurring at a rate that is 20 times higher than that in non-DS patients. Furthermore, the prognosis of DS-ALL patients is poorer than that of non-DS-ALL patients. A recent genetic analysis revealed that more than half of DS-ALL cases have a mutation in the CRLF2–JAK pathway, indicating that JAK inhibitors might have a limited effect for DS-ALL patients.Notably, solid tumors such as neuroblastoma, Wilms tumor, and brain tumor, which are frequently observed in non-DS children, are rarely reported in DS children. The reason remains unknown, but it may be because of the triplication of the Down syndrome critical region 1 (DSCR1) gene on chromosome 21. In adult patients with DS, the expected age-adjusted incidence rates of solid tumors are low compared with age-matched euploid cohorts for most cancers except for testicular cancer. Although the average life expectancy of patients with DS will increase with advances in healthcare, the detailed health problems including cancer rates in older DS patients remain unknown. Therefore, these issues will be needed to be addressed in future studies

Pattern Classification of Working Memory Networks Reveals Differential Effects of Methylphenidate, Atomoxetine, and Placebo in Healthy Volunteers

Stimulant and non-stimulant drugs can reduce symptoms of attention deficit/hyperactivity disorder (ADHD). The stimulant drug methylphenidate (MPH) and the non-stimulant drug atomoxetine (ATX) are both widely used for ADHD treatment, but their differential effects on human brain function remain unclear. We combined event-related fMRI with multivariate pattern recognition to characterize the effects of MPH and ATX in healthy volunteers performing a rewarded working memory (WM) task. The effects of MPH and ATX on WM were strongly dependent on their behavioral context. During non-rewarded trials, only MPH could be discriminated from placebo (PLC), with MPH producing a similar activation pattern to reward. During rewarded trials both drugs produced the opposite effect to reward, that is, attenuating WM networks and enhancing task-related deactivations (TRDs) in regions consistent with the default mode network (DMN). The drugs could be directly discriminated during the delay component of rewarded trials: MPH produced greater activity in WM networks and ATX produced greater activity in the DMN. Our data provide evidence that: (1) MPH and ATX have prominent effects during rewarded WM in task-activated and -deactivated networks; (2) during the delay component of rewarded trials, MPH and ATX have opposing effects on activated and deactivated networks: MPH enhances TRDs more than ATX, whereas ATX attenuates WM networks more than MPH; and (3) MPH mimics reward during encoding. Thus, interactions between drug effects and motivational state are crucial in defining the effects of MPH and ATX

Behavioral Implications of Demand Perception in Inventory Management

The newsvendor problem is one of the rudimentary problems of inventory management with significant practical consequences, thus receiving considerable attention in the behavioral operational research literature. In this chapter, we focus on how decision makers perceive demand uncertainty in the newsvendor setting and discuss how such perception patterns influence commonly observed phenomena in order decisions, such as the pull-to-center effect. Drawing from behavioral biases such as over precision, we propose that decision makers tend to perceive demand to be smaller than it actually is in high margin contexts, and this effect becomes more pronounced with increases in demand size. The opposite pattern is observed in low margin settings; decision makers perceive demand to be larger than the true demand, and this tendency is stronger at lower mean demand levels. Concurrently, decision makers tend to perceive demand to be less variable than it actually is, and this tendency propagates as the variability of demand increases in low margin contexts and decreases in high margin contexts. These perceptions, in turn, lead to more skewed decisions at both ends of the demand spectrum. We discuss how decision makers can be made aware of these biases and how decision processes can be re-designed to convert these unconscious competencies into capabilities to improve decision making