An Effective Approach for Endocrine Dynamic Function Tests Workflow and Reporting Using Cerner Millennium®

Introduction/Objective Endocrine dynamic function testing (DFT), also known as hormone stimulation tests, are indispensable tools in the endocrine practice. Common pitfalls of ineffective testing and misdiagnosis are due to incorrect sample recordings, delay in sample collections and disorganized or confusing result presentation. Clinical and laboratory data deserves careful attention and discrepancies must be reviewed by a clinical biochemist before releasing results for proper patient diagnosis. The main objective of this Cerner DFT project is to design and implement Cerner Millennium applications for effective management and organized result reporting of hospital-wide DFT protocols. Methods/Case Report The DFT Cerner workflow is uniquely designed in-house and known as a pioneer build for Cerner Millenium. The design involves the use of Cerner Discern Analytics 2.0 and clinical modules to complete such a complex build. Five DFT panels are defined as care-sets with specific hormone discrete task assays (DTA). For each care-set, an ‘order sentence’ is created to produce the order priority rules. The DFT panels can only be requested as future orders in PowerChart and activated by the medical staff upon collection of the baseline sample. On Cerner PathNet, results are pre-verified by the medical technologists then auto-filtered in the clinical Review Queue (RQ) module for final verification and addition of comments by the biochemistry consultant. A word processing template is used to collate the results and present the summary of the DFT report where standardized canned comments are added using pre-defined codes. Results (if a Case Study enter NA) See Conclusion Section Conclusion The Cerner DFT project mproves the diagnosis and treatment of patients with hormone disorders. Before, there was a danger of misdiagnosis when samples are individually requested producing separate reports with no organized presentation. Report comments from the clinical biochemist consultant also served as good diagnostic guidance. This quality initiative has definitely improved the previous and long term issues of endocrine dynamic function tests.

Muscle as a tunable material: implications for achieving muscle-like function in robotic prosthetic devices

ABSTRACT An ideal prosthesis should perform as well as or better than the missing limb it was designed to replace. Although this ideal is currently unattainable, recent advances in design have significantly improved the function of prosthetic devices. For the lower extremity, both passive prostheses (which provide no added power) and active prostheses (which add propulsive power) aim to emulate the dynamic function of the ankle joint, whose adaptive, time-varying resistance to applied forces is essential for walking and running. Passive prostheses fail to normalize energetics because they lack variable ankle impedance that is actively controlled within each gait cycle. By contrast, robotic prostheses can normalize energetics for some users under some conditions. However, the problem of adaptive and versatile control remains a significant issue. Current prosthesis-control algorithms fail to adapt to changes in gait required for walking on level ground at different speeds or on ramps and stairs. A new paradigm of ‘muscle as a tunable material’ versus ‘muscle as a motor’ offers insights into the adaptability and versatility of biological muscles, which may provide inspiration for prosthesis design and control. In this new paradigm, neural activation tunes muscle stiffness and damping, adapting the response to applied forces rather than instructing the timing and amplitude of muscle force. A mechanistic understanding of muscle function is incomplete and would benefit from collaboration between biologists and engineers. An improved understanding of the adaptability of muscle may yield better models as well as inspiration for developing prostheses that equal or surpass the functional capabilities of biological limbs across a wide range of conditions.

New Structural Economic Analysis of Anti-COVID-19 Pandemic Model of BEST Region

The successful anti-COVID-19 pandemic model of BEST region (Beijing-Seoul-Tokyo) includes China, Japan and South Korea, which benefit from its well-functioning organizational ecosystem and specific anti-COVID-19 pandemic strategies. Under the premise of an efficient market, the capable organizations of China, Japan and South Korea will play the dynamic function of coordination and organic connection. They will also help improve the governance efficiency of facilitating state in different stages of fighting against the pandemic. This article follows the analytical logic of the new structural economics, taking the factor endowment and its structure as the starting point for the analysis, through the comparative advantage operation mode determined by the market, and based on the collaborative anti-COVID-19 pandemic perspective of the government, the market and various social organizations, to build a framework for the facilitating state-efficient market-capable organization. The key to the success of the anti-COVID-19 pandemic method in China, Japan and South Korea is organically coordinated between government, market and organizations. Based on the effective promotion of micro-organizations, governments organize resource integration and implement macro-control of the market. A dynamic balance between economic governance and pandemic prevention and control has been achieved by optimizing the endowment structure of resources, improving infrastructure and reducing system costs.

Dynamic prospect theory - two core economic decision theories coexist in the gambling behavior of monkeys

Research in behavioral economics and reinforcement learning has given rise to two influential theories describing human economic choice under uncertainty. The first, prospect theory, assumes that decision-makers use static mathematical functions, utility and probability weighting, to calculate the values of alternatives. The second, reinforcement learning theory, posits that dynamic mathematical functions update the values of alternatives based on experience through reward prediction error (RPE). To date, these theories have been examined in isolation without reference to one another. Therefore, it remains unclear whether RPE affects a decision-maker's utility and/or probability weighting functions, or whether these functions are indeed static as in prospect theory. Here, we propose a dynamic prospect theory model that combines prospect theory and RPE, and test this combined model using choice data on gambling behavior of captive macaques. We found that under standard prospect theory, monkeys, like humans, had a concave utility function. Unlike humans, monkeys exhibited a concave, rather than inverse-S shaped, probability weighting function. Our dynamic prospect theory model revealed that probability distortions, not the utility of rewards, solely and systematically varied with RPE: after a positive RPE, the estimated probability weighting functions became more concave, suggesting more optimistic belief about receiving rewards and over-weighted subjective probabilities at all probability levels. Thus, the probability perceptions in laboratory monkeys are not static even after extensive training, and are governed by a dynamic function well captured by the algorithmic feature of reinforcement learning. This novel evidence supports combining these two major theories to capture choice behavior under uncertainty.

RNA-Binding Proteins and the Complex Pathophysiology of ALS

Genetic analyses of patients with amyotrophic lateral sclerosis (ALS) have identified disease-causing mutations and accelerated the unveiling of complex molecular pathogenic mechanisms, which may be important for understanding the disease and developing therapeutic strategies. Many disease-related genes encode RNA-binding proteins, and most of the disease-causing RNA or proteins encoded by these genes form aggregates and disrupt cellular function related to RNA metabolism. Disease-related RNA or proteins interact or sequester other RNA-binding proteins. Eventually, many disease-causing mutations lead to the dysregulation of nucleocytoplasmic shuttling, the dysfunction of stress granules, and the altered dynamic function of the nucleolus as well as other membrane-less organelles. As RNA-binding proteins are usually components of several RNA-binding protein complexes that have other roles, the dysregulation of RNA-binding proteins tends to cause diverse forms of cellular dysfunction. Therefore, understanding the role of RNA-binding proteins will help elucidate the complex pathophysiology of ALS. Here, we summarize the current knowledge regarding the function of disease-associated RNA-binding proteins and their role in the dysfunction of membrane-less organelles.