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As molecular and cellular therapies advance in the clinic, the role of genetic regulation is becoming increasingly important for controlling therapeutic potency and safety. The emerging field of mammalian synthetic biology provides promising tools for the construction of regulatory platforms that can intervene with endogenous pathways and control cell behavior. Recent work has highlighted the development of synthetic biological systems that integrate sensing of molecular signals to regulated therapeutic function in various disease settings. However, the toxicity and limited dosing of currently available molecular inducers have largely inhibited translation to clinical settings. In this work, we developed synthetic microRNA-based genetic systems that are controlled by the pharmaceutical drug leucovorin, which is readily available and safe for prolonged administration in clinical settings. We designed microRNA switches to target endogenous cytokine receptor subunits (IL-2Rβ and γc) that mediate various signaling pathways in T cells. We demonstrate the function of these control systems by effectively regulating T cell proliferation with the drug input. Each control system produced unique functional responses, and combinatorial targeting of multiple receptor subunits exhibited greater repression of cell growth. This work highlights the potential use of drug-responsive genetic control systems to improve the management and safety of cellular therapeutics.

Background: The effects of two lipidlowering drugs, simvastatin and fenofibrate on osteoporosis in the femurs of healthy and ovariectomized female rats were investigated quantitatively by histological images and 1H NMR relaxometry. Methodology: The intertrabecular cavities percentage was estimated from numerically cleaned histological images which initially present both the trabecular bone architecture and bone marrow filling the intertrabecular pores. The eight weeks evolution of intertrabecular cavities percentage measured from histological images of randomly selected sections in ovariectomized rats femoral diaphysis is similar with the evolution of transverse relaxation time centre of gravity T2,CG, a selected parameter to quantify the changes in intertrabecular cavities dimensions from onedimensional (1D) transverse relaxation time T2 distributions. Results: The analysis of histological images recorded for non-ovariectomized rats show that the treatment with simvastatin and fenofibrate has a negative effect on the dimension of the femoral diaphysis trabecular bone. The analysis of 1D T2 distributions show that the simvastatin and fenofibrate lipid-lowering drugs produce different effects on different particular sections of studied rat bones, i.e. proximal part of femoris, diaphysis or distal epiphysis. Conclusions: Finally, it is shown that the effects of the treatments are strongly dependent on the duration of treatment.

The 1H 1D NMR T2 distribution method was implemented for the measurement of the proximal part of the femoris of a series of ovariectomized and non-ovariectomized Wistar albino rats. The rats were sacrificed at 2, 4, 6 and 8 weeks after ovariectomy and the proximal part of femoris was harvested. The CPMG echoes train decays measured for the dried bone were analysed by Laplace inversion and an average of T2 distributions was considered for all rats' groups. The 1D normalized T2 distributions present four peaks which were associated with protons in four major environments. The first one corresponds to the protons from bound water to collagenous matrix. The second one was correlated with fluids in osteocyte lacunae and canaliculi channels, while the third one was correlated with fluids in secondary pores like Haversian and transverse Volkmann canals. Finally the last one corresponds to soft matter like bone marrow and to the fluids in primary pores like trabecular bone cavities. The femoral bone of ovariectomized and non-ovariectomized rats was treated as a quasi-porous media and from the T2 distributions the pores-size distributions were estimated function of observation time or evolution after ovariectomy. The results show that mainly the large cavities of proximal part of femoris, with the diameter in the range from 0.05 mm to 2 mm, are affected by osteoporosis for the ovariectomized rats. [ABSTRACT FROM AUTHOR]

Apurinic/apyrimidinic (AP) sites are ubiquitous DNA lesions that are highly mutagenic and cytotoxic if not repaired. In addition, clusters of two or more abasic lesions within one to two turns of DNA, a hallmark of ionizing radiation, are repaired much less efficiently and thus present greater mutagenic potential. Abasic sites are chemically labile, but naked DNA containing them undergoes strand scission slowly with a half-life on the order of weeks. We find that independently generated AP sites within nucleosome core particles are highly destabilized, with strand scission occurring ~60-fold more rapidly than in naked DNA. The majority of core particles containing single AP lesions accumulate DNA-protein cross-links, which persist following strand scission. The N-terminal region of histone protein H4 contributes significantly to DNA-protein cross-links and strand scission when AP sites are produced approximately 1.5 helical turns from the nucleosome dyad, which is a known hot spot for nucleosomal DNA damage. Reaction rates for AP sites at two positions within this region differ by ∼4-fold. However, the strand scission of the slowest reacting AP site is accelerated when it is part of a repair resistant bistranded lesion composed of two AP sites, resulting in rapid formation of double strand breaks in high yields. Multiple lysine residues within a single H4 protein catalyze double strand cleavage through a mechanism believed to involve a templating effect. These results show that AP sites within the nucleosome produce significant amounts of DNA-protein cross-links and generate double strand breaks, the most deleterious form of DNA damage. [ABSTRACT FROM AUTHOR]

Though there is a strong consensus that word length and frequency are the most important single-word features determining visual-orthographic access to the mental lexicon, there is less agreement as how to best capture syntactic and semantic factors. The traditional approach in cognitive reading research assumes that word predictability from sentence context is best captured by cloze completion probability (CCP) derived from human performance data. We review recent research suggesting that probabilistic language models provide deeper explanations for syntactic and semantic effects than CCP. Then we compare CCP with three probabilistic language models for predicting word viewing times in an English and a German eye tracking sample: (1) Symbolic n-gram models consolidate syntactic and semantic short-range relations by computing the probability of a word to occur, given two preceding words. (2) Topic models rely on subsymbolic representations to capture long-range semantic similarity by word co-occurrence counts in documents. (3) In recurrent neural networks (RNNs), the subsymbolic units are trained to predict the next word, given all preceding words in the sentences. To examine lexical retrieval, these models were used to predict single fixation durations and gaze durations to capture rapidly successful and standard lexical access, and total viewing time to capture late semantic integration. The linear item-level analyses showed greater correlations of all language models with all eye-movement measures than CCP. Then we examined non-linear relations between the different types of predictability and the reading times using generalized additive models. N-gram and RNN probabilities of the present word more consistently predicted reading performance compared with topic models or CCP. For the effects of last-word probability on current-word viewing times, we obtained the best results with n-gram models. Such count-based models seem to best capture short-range access that is still underway when the eyes move on to the subsequent word. The prediction-trained RNN models, in contrast, better predicted early preprocessing of the next word. In sum, our results demonstrate that the different language models account for differential cognitive processes during reading. We discuss these algorithmically concrete blueprints of lexical consolidation as theoretically deep explanations for human reading., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Hofmann, Remus, Biemann, Radach and Kuchinke.)

Big data using data science methods (data analytics) has the potential to effectively inform strategies to address complex healthcare challenges. However, this potential can only be realized if healthcare professionals have the requisite depth and breadth of knowledge (i.e., informatics competencies). With the emergence of electronic health records (EHRs - commonly known as clinical information systems [CISs]) in healthcare organizations, data analytics that can "interrogate" CIS big data are now possible. In its digitized form, CIS healthcare data meant to support real-time, evidence-based practice decisions and guide new health policy directions remain more of a conceptual promise than a practice reality. Further, the "data rich information poor" phenomenon existing with today's CISs is often the reality for nurses who document more patient information compared to other healthcare professionals and get negligible results in return. However, data science methods when applied to CIS big data are "uncovering" new evidence currently unavailable through traditional data analytic approaches. Big data science is predicted to provide immense opportunities for nurse leaders by offering robust, electronic tools, which support informed decision-making at corporate tables and "arm" all point-of-care/service clinicians with real-time evidence. In this article, we provide a perspective on how the field of data science can enable informatics-savvy nurse executives to lead clinical transformation in the development of the next generation of evidence-based practice, "practice-based evidence.", (Copyright © 2019 Longwoods Publishing.)

Limited informatics competency uptake is a recognized nursing leadership challenge impacting digital practice settings. The health system's inability to reap the promised benefits of EHRs is a manifestation of inadequate development of informatics competencies by chief nurse executives (CNEs) and other clinicians. Through the application of Transformational Leadership Theory (TL), this discussion paper explains how informatics competencies enable CNEs to become transformational nursing leaders in digital health allowing them to meet their accountabilities to lead integrated, high-quality care delivery through evidence based practices (EBPs). It is proposed that successful CNE eHealth sponsors will be those armed with informatics competencies who can drive health organizations' investment in technology and innovation. Finally, some considerations are suggested in how nurse informaticists globally play a critical role in preparing our existing and future CNEs to fulfill their transformational leader roles in the digital age.

Informatics competency adoption is a recognized issue across nursing roles in digital health practice settings. Further, it has been suggested that the health system's inability to reap the promised benefits of electronic health/patient records is, in part, a manifestation of inadequate development of informatics competency by chief nurse executives (CNEs) and other clinicians (Amendola 2008; Simpson 2013). This paper will focus on CNE informatics competency and nursing knowledge development as it pertains to the Big Data revolution. With the paper's aim of showing how CNEs armed with informatics competency can harness the full potential of Big Data offering new opportunities for nursing knowledge development in their clinical transformation roles as eHealth project sponsors. It is proposed that informatics-savvy CNEs are the new transformational leaders of the digital age who will have the advantage to successfully advocate for nurses in leading 21st-century health systems. Also, transformational CNEs armed with informatics competency will position nurses and the nursing profession to achieve its future vision, where nurses are perceived by patients and professionals alike as knowledge workers, providing the leadership essential for safe, quality care and demonstrating nursing's unique contributions to fiscal health through clinically relevant, evidence-based practices (McBride 2005b)., (Copyright © 2016 Longwoods Publishing.)

In a recent brief to the Canadian Nurses Association's National Expert Commission on the Health of Our Nation, the Academy of Canadian Executive Nurses (ACEN) discussed leadership needs in the Canadian healthcare system, and promoted the pivotal role of nursing executives in transforming Canada's healthcare system into an integrated patient-centric system. Included among several recommendations was the need to develop innovative leadership competencies that enable nurse leaders to lead and advance transformative health system change. This paper focuses on an emerging "avant-garde executive leadership competency" recommended for today's health leaders to guide health system transformation. Specifically, this competency is articulated as "state of the art communication and technology savvy," and it implies linkages between nursing informatics competencies and transformational leadership roles for nurse executive. The authors of this paper propose that distinct nursing informatics competencies are required to augment traditional executive skills to support transformational outcomes of safe, integrated, high-quality care delivery through knowledge-driven care. International trends involving nursing informatics competencies and the evolution of new corporate informatics roles, such as chief nursing informatics officers (CNIOs), are demonstrating value and advanced transformational leadership as nursing executive roles that are informed by clinical data., (Copyright © 2013 Longwoods Publishing.)

Patients experiencing mechanical ventilation are unable to speak while being dependent on others for their physical needs. The purpose of this work is to describe the communication needs of individuals who are mechanically ventilated. This article reports the findings of a pilot study to assess communication needs of ventilated patients and to compare patients' perceptions of their needs with their nurses' perceptions of their needs. Twenty-seven nurse-patient comparisons were generated. The only statistically significant correlation was observed for the needs concerning social stimulation. Nurses and patients did not agree on the patients' communication needs in areas of information-seeking, information-sharing or request for assistance. Further research is needed to verify these findings.