Improving graduate education to support a branching career pipeline: recommendations based on a survey of doctoral students in the basic biomedical sciences

Today's doctoral programs continue to prepare students for a traditional academic career path despite the inadequate supply of research-focused faculty positions. We advocate for a broader doctoral curriculum that prepares trainees for a wide range of science-related career paths. In support of this argument, we describe data from our survey of doctoral students in the basic biomedical sciences at University of California, San Francisco (UCSF). Midway through graduate training, UCSF students are already considering a broad range of career options, with one-third intending to pursue a non-research career path. To better support this branching career pipeline, we recommend that national standards for training and mentoring include emphasis on career planning and professional skills development to ensure the success of PhD-level scientists as they contribute to a broadly defined global scientific enterprise.     

Novel model reference adaptive control laws for improved transient dynamics and guaranteed saturation constraints

In classical model reference adaptive control (MRAC), the adaptive rates must be tuned to meet multiple competing objectives. Large adaptive rates guarantee rapid convergence of the trajectory tracking error to zero. However, large adaptive rates may also induce saturation of the actuators and excessive overshoots of the closed-loop system’s trajectory tracking error. Conversely, low adaptive rates may produce unsatisfactory trajectory tracking performances. To overcome these limitations, in the classical MRAC framework, the adaptive rates must be tuned through an iterative process. Alternative approaches require to modify the plant’s reference model or the reference command input. This paper presents the first MRAC laws for nonlinear dynamical systems affected by matched and parametric uncertainties that constrain both the closed-loop system’s trajectory tracking error and the control input at all times within user-defined bounds, and enforce a user-defined rate of convergence on the trajectory tracking error. By applying the proposed MRAC laws, the adaptive rates can be set arbitrarily large and both the plant’s reference model and the reference command input can be chosen arbitrarily. The user-defined rate of convergence of the closed-loop plant’s trajectory is enforced by introducing a user-defined auxiliary reference model, which converges to the trajectory tracking error obtained by applying the classical MRAC laws before its transient dynamics has decayed, and steering the trajectory tracking error to the auxiliary reference model at a rate of convergence that is higher than the rate of convergence of the plant’s reference model. The ability of the proposed MRAC laws to prescribe the performance of the closed-loop system’s trajectory tracking error and control input is guaranteed by barrier Lyapunov functions. Numerical simulations illustrate both the applicability of our theoretical results and their effectiveness compared to other techniques such as prescribed performance control, which allows to constrain both the rate of convergence and the maximum overshoot on the trajectory tracking error of uncertain systems.     

Neuromuscular control and running economy is preserved in elite international triathletes after cycling

Running is the most important discipline for Olympic triathlon success. However, cycling impairs running muscle recruitment and performance in some highly trained triathletes; though it is not known if this occurs in elite international triathletes. The purpose of this study was to investigate the effect of cycling in two different protocols on running economy and neuromuscular control in elite international triathletes. Muscle recruitment and sagittal plane joint angles of the left lower extremity and running economy were compared between control (no preceding cycle) and transition (preceded by cycling) runs for two different cycle protocols (20-minute low-intensity and 50-minute high-intensity cycles) in seven elite international triathletes. Muscle recruitment and joint angles were not different between control and transition runs for either cycle protocols. Running economy was also not different between control and transition runs for the low-intensity (62.4 +/- 4.5 vs. 62.1 +/- 4.0 ml/min/kg, p > 0.05) and high-intensity (63.4 +/- 3.5 vs. 63.3 +/- 4.3 ml/min/kg, p > 0.05) cycle protocols. The results of this study demonstrate that both low- and high-intensity cycles do not adversely influence neuromuscular control and running economy in elite international triathletes.     

Visualization of the moving Pareto frontier in DSS

A new approach to decision support in a multiobjective problem arising in controlled dynamic system design is described. The approach basically extends the feasible goals method that implies specifying the goal point by visualizing the Pareto frontier that characterizes feasible objective values and objective tradeoffs to dynamic systems. The developed approach helps explore dynamic modifications of the Pareto frontier.     

Documenting the doable and doing the documented: bridging strategies at the UK Stem Cell Bank

We explore the local negotiation of regulatory practice at the UK Stem Cell Bank, the first Bank of its type in the world. Basing our empirical work on a detailed analysis of one aspect of the Bank's regulatory commitment--the completion of the Cell Line Information form--we make visible the necessary judgements and labour involved in interpreting and operationalizing externally imposed regulation. The discussion opens by detailing the problems encountered when the Bank completes the form: reconciling a bureaucratic system of accountability with craft-like laboratory skills involving multiple kinds of tacit knowledge. We follow this by explicating the emergent 'bridging strategies' pursued by the Bank to address these issues, highlighting their reliance upon the formation of trust and social networks. The closing discussion emphasizes the contingent assembly of regulatory practices that emerge in the local setting.     

A Review on Salivary Genomics and Proteomics Biomarkers in Oral Cancer

Oral cancer has emerged as an alarming public health problem with increasing incidence and mortality rates all over the world. Therefore, the implementation of newer screening and early detection approaches are of utmost importance which could reduce the morbidity and mortality associated with this disease. Sensitive and specific biomarkers for oral cancer are likely to be most effective for screening, diagnosis, staging and follow-up for this dreaded malignancy. Unlike other deep cancers, oral cancer is located in oral cavity. Hence, the direct contact between saliva and oral cancer lesion makes the measurement of tumor markers in saliva an attractive alternative to serum and tissue testing. The DNA, RNA and protein molecules derived from the living cancer cells can be conveniently obtained from saliva. Thus, salivary biomarkers, a non-invasive alternative to serum and tissue-based biomarkers may be an effective modality for early diagnosis, prognostication and monitoring post therapy status. In the current post-genomic era, various technologies provide opportunities for high-throughput approaches to genomics and proteomics; which have been used to evaluate altered expressions of gene and protein targets in saliva of oral cancer patients. The emerging field of salivary biomarkers has great potentials to prove its clinical significance to combat oral cancer. Hence, we have reviewed importance of several salivary genomics and proteomics biomarkers for oral cancer.