An Evaluation of Qualities of Nuclear Medicine Technology Programs and Graduates Leading to Employability

Our rationale was to evaluate how the qualities of nuclear medicine technology (NMT) programs and graduates associate with employability. Methods: We identified all Nuclear Medicine Technology Certification Board applicants who passed the entry-level NMT examination between 2012 and 2017. Certificants were e-mailed a survey with questions on graduate qualities, program qualities, and initial employment. Each quality was quantified. Age, sex, and desired employment within or outside the United States were also documented. An employability scale was created from the initial employment questions. Subjects were separated into 4 employability groups based on their employability score: poorly employable, marginally employable, satisfactorily employable, and optimally employable. An ANOVA test was performed on each quality using the 4 employability groups; a P value of less than 0.05 was considered significant. Results: Of the 3,930 surveys distributed, 885 (22.5%) were completed and returned. Six of the 10 qualities evaluated were significantly associated with employability: overall education (P < 0.01), number of clinic hours (P < 0.01), grade-point average (P < 0.01), number of schools within a 100-mile (161-km) radius (P < 0.01), number of attempts to pass the board examination (P < 0.01), and number of clinics (P = 0.04). The qualities that were not statistically significant were age, sex, employment location sought, board score, single versus dual certification, program level of education, and number of graduates in the class. Conclusion: There are multiple graduate and program qualities that are predictive of the employability of NMT graduates

Investigating the functionality of an OCT4-short response element in human induced pluripotent stem cells.

Pluripotent stem cells offer great therapeutic promise for personalized treatment platforms for numerous injuries, disorders, and diseases. Octamer-binding transcription factor 4 (OCT4) is a key regulatory gene maintaining pluripotency and self-renewal of mammalian cells. With site-specific integration for gene correction in cellular therapeutics, use of the OCT4 promoter may have advantages when expressing a suicide gene if pluripotency remains. However, the human OCT4 promoter region is 4 kb in size, limiting the capacity of therapeutic genes and other regulatory components for viral vectors, and decreasing the efficiency of homologous recombination. The purpose of this investigation was to characterize the functionality of a novel 967bp OCT4-short response element during pluripotency and to examine the OCT4 titer-dependent response during differentiation to human derivatives not expressing OCT4. Our findings demonstrate that the OCT4-short response element is active in pluripotency and this activity is in high correlation with transgene expression in vitro, and the OCT4-short response element is inactivated when pluripotent cells differentiate. These studies demonstrate that this shortened OCT4 regulatory element is functional and may be useful as part of an optimized safety component in a site-specific gene transferring system that could be used as an efficient and clinically applicable safety platform for gene transfer in cellular therapeutics

Degradation of electroless Ni(P) under-bump metallization in Sn3.5Ag and Sn37Pb solders during high-temperature storage

The interfacial reaction between electroless Ni(P) under-bump metallization (UBM) and solders is studied. A P-rich layer forms in the UBM along the solder side after reflow and thermal aging. Crack formation inside the P-rich layer can sometimes penetrate throughout the entire UBM layer structure. The Ni(P) UBM degradation occurs earlier in the Sn3.5Ag solder than in Sn37Pb because of its higher reflow temperature. Despite the formation of a P-rich layer and cracks inside the UBM, it still keeps its original function within the high-temperature storage period in this study. Explanations for the formation of the P-rich layer and cracks in the UBM are outlined along with explanations for the Ni(P) UBM degradation process

Restoring Ureagenesis in Hepatocytes by CRISPR/Cas9-mediated Genomic Addition to Arginase-deficient Induced Pluripotent Stem Cells.

Urea cycle disorders are incurable enzymopathies that affect nitrogen metabolism and typically lead to hyperammonemia. Arginase deficiency results from a mutation in Arg1, the enzyme regulating the final step of ureagenesis and typically results in developmental disabilities, seizures, spastic diplegia, and sometimes death. Current medical treatments for urea cycle disorders are only marginally effective, and for proximal disorders, liver transplantation is effective but limited by graft availability. Advances in human induced pluripotent stem cell research has allowed for the genetic modification of stem cells for potential cellular replacement therapies. In this study, we demonstrate a universally-applicable CRISPR/Cas9-based strategy utilizing exon 1 of the hypoxanthine-guanine phosphoribosyltransferase locus to genetically modify and restore arginase activity, and thus ureagenesis, in genetically distinct patient-specific human induced pluripotent stem cells and hepatocyte-like derivatives. Successful strategies restoring gene function in patient-specific human induced pluripotent stem cells may advance applications of genetically modified cell therapy to treat urea cycle and other inborn errors of metabolism

Accelerated Predictive Healthcare Analytics with Pumas, a High Performance Pharmaceutical Modeling and Simulation Platform

Pharmacometric modeling establishes causal quantitative relationship between administered dose, tissue exposures, desired and undesired effects and patient’s risk factors. These models are employed to de-risk drug development and guide precision medicine decisions. Recent technological advances rendered collecting real-time and detailed data easy. However, the pharmacometric tools have not been designed to handle heterogeneous, big data and complex models. The estimation methods are outdated to solve modern healthcare challenges. We set out to design a platform that facilitates domain specific modeling and its integration with modern analytics to foster innovation and readiness to data deluge in healthcare. New specialized estimation methodologies have been developed that allow dramatic performance advances in areas that have not seen major improvements in decades. New ODE solver algorithms, such as coefficient-optimized higher order integrators and new automatic stiffness detecting algorithms which are robust to frequent discontinuities, give rise to up to 4x performance improvements across a wide range of stiff and non-stiff systems seen in pharmacometric applications. These methods combine with JIT compiler techniques and further specialize the solution process on the individual systems, allowing statically-sized optimizations and discrete sensitivity analysis via forward-mode automatic differentiation, to further enhance the accuracy and performance of the solving and parameter estimation process. We demonstrate that when all of these techniques are combined with a validated clinical trial dosing mechanism and non-compartmental analysis (NCA) suite, real applications like NLME parameter estimation see run times halved while retaining the same accuracy. Meanwhile in areas with less prior optimization of software, like optimal experimental design, we see orders of magnitude performance enhancements. Together we show a fast and modern domain specific modeling framework which lays a platform for innovation via upcoming integrations with modern analytics

Living for the weekend: youth identities in northeast England

Consumption and consumerism are now accepted as key contexts for the construction of youth identities in de-industrialized Britain. This article uses empirical evidence from interviews with young people to suggest that claims of `new community' are overstated, traditional forms of friendship are receding, and increasingly atomized and instrumental youth identities are now being culturally constituted and reproduced by the pressures and anxieties created by enforced adaptation to consumer capitalism. Analysis of the data opens up the possibility of a critical rather than a celebratory exploration of the wider theoretical implications of this process

Accelerated Predictive Healthcare Analytics with Pumas, a High Performance Pharmaceutical Modeling and Simulation Platform

Pharmacometric modeling establishes causal quantitative relationship between administered dose, tissue exposures, desired and undesired effects and patient’s risk factors. These models are employed to de-risk drug development and guide precision medicine decisions. Recent technological advances rendered collecting real-time and detailed data easy. However, the pharmacometric tools have not been designed to handle heterogeneous, big data and complex models. The estimation methods are outdated to solve modern healthcare challenges. We set out to design a platform that facilitates domain specific modeling and its integration with modern analytics to foster innovation and readiness to data deluge in healthcare. New specialized estimation methodologies have been developed that allow dramatic performance advances in areas that have not seen major improvements in decades. New ODE solver algorithms, such as coefficient-optimized higher order integrators and new automatic stiffness detecting algorithms which are robust to frequent discontinuities, give rise to up to 4x performance improvements across a wide range of stiff and non-stiff systems seen in pharmacometric applications. These methods combine with JIT compiler techniques and further specialize the solution process on the individual systems, allowing statically-sized optimizations and discrete sensitivity analysis via forward-mode automatic differentiation, to further enhance the accuracy and performance of the solving and parameter estimation process. We demonstrate that when all of these techniques are combined with a validated clinical trial dosing mechanism and non-compartmental analysis (NCA) suite, real applications like NLME parameter estimation see run times halved while retaining the same accuracy. Meanwhile in areas with less prior optimization of software, like optimal experimental design, we see orders of magnitude performance enhancements. Together we show a fast and modern domain specific modeling framework which lays a platform for innovation via upcoming integrations with modern analytics

STEAP4 expression in human islets is associated with differences in body mass index, sex, HbA1c, and inflammation

Objective STEAP4 (six-transmembrane epithelial antigen of the prostate 4) is a metalloreductase that has been shown previously to protect cells from inflammatory damage. Genetic variants in STEAP4 have been associated with numerous metabolic disorders related to obesity, including putative defects in the acute insulin response to glucose in type 2 diabetes. Purpose We examined whether obesity and/or type 2 diabetes altered STEAP4 expression in human pancreatic islets. Methods Human islets were isolated from deceased donors at two medical centers and processed for quantitative polymerase chain reaction. Organ donors were selected by status as non-diabetic or having type 2 diabetes. Site 1 (Edmonton): N = 13 type 2 diabetes donors (7M, 6F), N = 20 non-diabetic donors (7M, 13F). Site 2 (Virginia): N = 6 type 2 diabetes donors (6F), N = 6 non-diabetic donors (3M, 3F). Results STEAP4 showed reduced islet expression with increasing body mass index among all donors (P < 0.10) and non-diabetic donors (P < 0.05) from Site 1; STEAP4 showed reduced islet expression among type 2 diabetes donors with increasing hemoglobin A1c. Islet STEAP4 expression was also marginally higher in female donors (P < 0.10). Among type 2 diabetes donors from Site 2, islet insulin expression was reduced, STEAP4 expression was increased, and white blood cell counts were increased compared to non-diabetic donors. Islets from non-diabetic donors that were exposed overnight to 5 ng/ml IL-1β displayed increased STEAP4 expression, consistent with STEAP4 upregulation by inflammatory signaling. Conclusions These findings suggest that increased STEAP4 mRNA expression is associated with inflammatory stimuli, whereas lower STEAP4 expression is associated with obesity in human islets. Given its putative protective role, downregulation of STEAP4 by chronic obesity suggests a mechanism for reduced islet protection against cellular damage

The response of perennial and temporary headwater stream invertebrate communities to hydrological extremes

The headwaters of karst rivers experience considerable hydrological variability, including spates and streambed drying. Extreme summer flooding on the River Lathkill (Derbyshire, UK) provided the opportunity to examine the invertebrate community response to unseasonal spate flows, flow recession and, at temporary sites, streambed drying. Invertebrates were sampled at sites with differing flow permanence regimes during and after the spates. Following streambed drying at temporary sites, dewatered surface sediments were investigated as a refugium for aquatic invertebrates. Experimental rehydration of these dewatered sediments was conducted to promote development of desiccation-tolerant life stages. At perennial sites, spate flows reduced invertebrate abundance and diversity, whilst at temporary sites, flow reactivation facilitated rapid colonisation of the surface channel by a limited number of invertebrate taxa. Following streambed drying, 38 taxa were recorded from the dewatered and rehydrated sediments, with Oligochaeta being the most abundant taxon and Chironomidae (Diptera) the most diverse. Experimental rehydration of dewatered sediments revealed the presence of additional taxa, including Stenophylax sp. (Trichoptera: Limnephilidae) and Nemoura sp. (Plecoptera: Nemouridae). The influence of flow permanence on invertebrate community composition was apparent despite the aseasonal high-magnitude flood events

The Distribution and Origin of Smooth Plains on Mercury

Orbital images from the MESSENGER spacecraft show that ~27% of Mercury's surface is covered by smooth plains, the majority (greater than 65%) of which are interpreted to be volcanic in origin. Most smooth plains share the spectral characteristics of Mercury's northern smooth plains, suggesting they also share their magnesian alkali-basalt-like composition. A smaller fraction of smooth plains interpreted to be volcanic in nature have a lower reflectance and shallower spectral slope, suggesting more ultramafic compositions, an inference that implies high temperatures and high degrees of partial melting in magma source regions persisted through most of the duration of smooth plains formation. The knobby and hummocky plains surrounding the Caloris basin, known as Odin-type plains, occupy an additional 2% of Mercury’s surface. The morphology of these plains and their color and stratigraphic relationships suggest that they formed as Caloris ejecta, although such an origin is in conflict with a straightforward interpretation of crater size-frequency distributions. If some fraction is volcanic, this added area would substantially increase the abundance of relatively young effusive deposits inferred to have more mafic compositions. Smooth plains are widespread on Mercury, but they are more heavily concentrated in the north and in the hemisphere surrounding Caloris. No simple relationship between plains distribution and crustal thickness or radioactive element distribution is observed. A likely volcanic origin for some older terrain on Mercury suggests that the uneven distribution of smooth plains may indicate differences in the emplacement age of large-scale volcanic deposits rather than differences in crustal formational process