Effect of Seedling Stock on the Early Stand Development and Physiology of Improved Loblolly Pine (Pinus taeda L.) Seedlings

This study assessed the effects of spacing and genotype on the growth and physiology of improved loblolly pine (Pinus taeda L.) seedlings from three distinct genotypes planted in Drew County, Arkansas (USA). Genotype had a significant effect on survival and height. Clone CF Var 1 showed greater height and survival compared to other seedlings. Genotype had significant effects on uniformity in height both years and ground line diameter (GLD) first year. However, genotype had no significant effects on leaf water potential and coefficient variation of leaf water potential. These growth and physiology should be further studied to assess potential genetic differences among seedlings and to determine if they can be identified early for improved growth at later ages

Recombinant canine single chain insulin analogues: Insulin receptor binding capacity and ability to stimulate glucose uptake

Virtually all diabetic dogs require exogenous insulin therapy to control their hyperglycaemia. In the UK, the only licensed insulin product currently available is a purified porcine insulin preparation. Recombinant insulin is somewhat problematic in terms of its manufacture, since the gene product (preproinsulin) undergoes substantial post-translational modification in pancreatic β cells before it becomes biologically active. The aim of the present study was to develop recombinant canine single chain insulin (SCI) analogues that could be produced in a prokaryotic expression system and which would require minimal processing. Three recombinant SCI constructs were developed in a prokaryotic expression vector, by replacing the insulin C-peptide sequence with one encoding a synthetic peptide (GGGPGKR), or with one of two insulin-like growth factor (IGF)-2 C-peptide coding sequences (human: SRVSRRSR; canine: SRVTRRSSR). Recombinant proteins were expressed in the periplasmic fraction of Escherichia coli and assessed for their ability to bind to the insulin and IGF-1 receptors, and to stimulate glucose uptake in 3T3-L1 adipocytes. All three recombinant SCI analogues demonstrated preferential binding to the insulin receptor compared to the IGF-1 receptor, with increased binding compared to recombinant canine proinsulin. The recombinant SCI analogues stimulated glucose uptake in 3T3-L1 adipocytes compared to negligible uptake using recombinant canine proinsulin, with the canine insulin/cIGF-2 chimaeric SCI analogue demonstrating the greatest effect. Thus, biologically-active recombinant canine SCI analogues can be produced relatively easily in bacteria, which could potentially be used for treatment of diabetic dogs

Ariel - Volume 8 Number 4

Executive Editor James W. Lockard Jr. Issues Editor Neeraj K. Kanwal Business Manager Neeraj K. Kanwal University News Martin Trichtinger World News Doug Hiller Opinions Elizabeth A. McGuire Features Patrick P. Sokas Sports Desk Shahab S. Minassian Managing Editor Edward H. Jasper Managing Associate Brenda Peterson Photography Editor Robert D. Lehman, Jr. Graphics Christine M. Kuhnl

Ariel - Volume 8 Number 2

Executive Editor James W. Lockard , Jr. Issue Editor Doug Hiller Business Manager Neeraj K. Kanwal University News Richard J. Perry World News Doug Hiller Opinions Elizabeth A. McGuire Features Patrick P. Sokas Sports Desk Shahab S. Minassian Managing Editor Edward H. Jasper Managing Associate Brenda Peterson Photography Editor Robert D. Lehman, Jr. Graphics Christine M. Kuhnl

Using AI to Measure Parkinson's Disease Severity at Home

We present an artificial intelligence system to remotely assess the motor performance of individuals with Parkinson's disease (PD). Participants performed a motor task (i.e., tapping fingers) in front of a webcam, and data from 250 global participants were rated by three expert neurologists following the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). The neurologists' ratings were highly reliable, with an intra-class correlation coefficient (ICC) of 0.88. We developed computer algorithms to obtain objective measurements that align with the MDS-UPDRS guideline and are strongly correlated with the neurologists' ratings. Our machine learning model trained on these measures outperformed an MDS-UPDRS certified rater, with a mean absolute error (MAE) of 0.59 compared to the rater's MAE of 0.79. However, the model performed slightly worse than the expert neurologists (0.53 MAE). The methodology can be replicated for similar motor tasks, providing the possibility of evaluating individuals with PD and other movement disorders remotely, objectively, and in areas with limited access to neurological care

Wide-field dynamic astronomy in the near-infrared with Palomar Gattini-IR and DREAMS

There have been a dramatic increase in the number of optical and radio transient surveys due to astronomical transients such as gravitational waves and gamma ray bursts, however, there have been a limited number of wide-field infrared surveys due to narrow field-of-view and high cost of infrared cameras, we present two new wide-field near-infrared fully automated surveyors; Palomar Gattini-IR and the Dynamic REd All-sky Monitoring Survey (DREAMS). Palomar Gattini-IR, a 25 square degree J-band imager that begun science operations at Palomar Observatory, USA in October 2018; we report on survey strategy as well as telescope and observatory operations and will also providing initial science results. DREAMS is a 3.75 square degree wide-field imager that is planned for Siding Spring Observatory, Australia; we report on the current optical and mechanical design and plans to achieve on-sky results in 2020. DREAMS is on-track to be one of the first astronomical telescopes to use an Indium Galium Arsenide (InGaAs) detector and we report initial on-sky testing results for the selected detector package. DREAMS is also well placed to take advantage and provide near-infrared follow-up of the LSST

Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity:The Mobile Parkinson Disease Score

IMPORTANCE: Current Parkinson disease (PD) measures are subjective, rater-dependent, and assessed in clinic. Smartphones can measure PD features, yet no smartphone-derived rating score exists to assess motor symptom severity in real-world settings. OBJECTIVES: To develop an objective measure of PD severity and test construct validity by evaluating the ability of the measure to capture intraday symptom fluctuations, correlate with current standard PD outcome measures, and respond to dopaminergic therapy. DESIGN, SETTING, AND PARTICIPANTS: This observational study assessed individuals with PD who remotely completed 5 tasks (voice, finger tapping, gait, balance, and reaction time) on the smartphone application. We used a novel machine-learning-based approach to generate a mobile Parkinson disease score (mPDS) that objectively weighs features derived from each smartphone activity (eg, stride length from the gait activity) and is scaled from 0 to 100 (where higher scores indicate greater severity). Individuals with and without PD additionally completed standard in-person assessments of PD with smartphone assessments during a period of 6 months. MAIN OUTCOMES AND MEASURES: Ability of the mPDS to detect intraday symptom fluctuations, the correlation between the mPDS and standard measures, and the ability of the mPDS to respond to dopaminergic medication. RESULTS: The mPDS was derived from 6148 smartphone activity assessments from 129 individuals (mean [SD] age, 58.7 [8.6] years; 56 [43.4%] women). Gait features contributed most to the total mPDS (33.4%). In addition, 23 individuals with PD (mean [SD] age, 64.6 [11.5] years; 11 [48%] women) and 17 without PD (mean [SD] age 54.2 [16.5] years; 12 [71%] women) completed in-clinic assessments. The mPDS detected symptom fluctuations with a mean (SD) intraday change of 13.9 (10.3) points on a scale of 0 to 100. The measure correlated well with the Movement Disorder Society Unified Parkinson Disease's Rating Scale total (r = 0.81; P < .001) and part III only (r = 0.88; P < .001), the Timed Up and Go assessment (r = 0.72; P = .002), and the Hoehn and Yahr stage (r = 0.91; P < .001). The mPDS improved by a mean (SD) of 16.3 (5.6) points in response to dopaminergic therapy. CONCLUSIONS AND RELEVANCE: Using a novel machine-learning approach, we created and demonstrated construct validity of an objective PD severity score derived from smartphone assessments. This score complements standard PD measures by providing frequent, objective, real-world assessments that could enhance clinical care and evaluation of novel therapeutics

Metadata Framework to Support Deployment of Digital Health Technologies in Clinical Trials in Parkinson’s Disease

Sensor data from digital health technologies (DHTs) used in clinical trials provides a valuable source of information, because of the possibility to combine datasets from different studies, to combine it with other data types, and to reuse it multiple times for various purposes. To date, there exist no standards for capturing or storing DHT biosensor data applicable across modalities and disease areas, and which can also capture the clinical trial and environment-specific aspects, so-called metadata. In this perspectives paper, we propose a metadata framework that divides the DHT metadata into metadata that is independent of the therapeutic area or clinical trial design (concept of interest and context of use), and metadata that is dependent on these factors. We demonstrate how this framework can be applied to data collected with different types of DHTs deployed in the WATCH-PD clinical study of Parkinson’s disease. This framework provides a means to pre-specify and therefore standardize aspects of the use of DHTs, promoting comparability of DHTs across future studies

Cross-site comparison of ribosomal depletion kits for Illumina RNAseq library construction

Background Ribosomal RNA (rRNA) comprises at least 90% of total RNA extracted from mammalian tissue or cell line samples. Informative transcriptional profiling using massively parallel sequencing technologies requires either enrichment of mature poly-adenylated transcripts or targeted depletion of the rRNA fraction. The latter method is of particular interest because it is compatible with degraded samples such as those extracted from FFPE and also captures transcripts that are not poly-adenylated such as some non-coding RNAs. Here we provide a cross-site study that evaluates the performance of ribosomal RNA removal kits from Illumina, Takara/Clontech, Kapa Biosystems, Lexogen, New England Biolabs and Qiagen on intact and degraded RNA samples. Results We find that all of the kits are capable of performing significant ribosomal depletion, though there are differences in their ease of use. All kits were able to remove ribosomal RNA to below 20% with intact RNA and identify ~ 14,000 protein coding genes from the Universal Human Reference RNA sample at >1FPKM. Analysis of differentially detected genes between kits suggests that transcript length may be a key factor in library production efficiency. Conclusions These results provide a roadmap for labs on the strengths of each of these methods and how best to utilize them. Keywords: RNAseqr; RNA depletion; Illumina; NGS; ABRF; TranscriptomicsNational Cancer Institute (U.S.) (Grant P30-CA14051)National Institute of Environmental Health Sciences (Grant P30-ES002109

Wide-field dynamic astronomy in the near-infrared with Palomar Gattini-IR and DREAMS

There have been a dramatic increase in the number of optical and radio transient surveys due to astronomical transients such as gravitational waves and gamma ray bursts, however, there have been a limited number of wide-field infrared surveys due to narrow field-of-view and high cost of infrared cameras, we present two new wide-field near-infrared fully automated surveyors; Palomar Gattini-IR and the Dynamic REd All-sky Monitoring Survey (DREAMS). Palomar Gattini-IR, a 25 square degree J-band imager that begun science operations at Palomar Observatory, USA in October 2018; we report on survey strategy as well as telescope and observatory operations and will also providing initial science results. DREAMS is a 3.75 square degree wide-field imager that is planned for Siding Spring Observatory, Australia; we report on the current optical and mechanical design and plans to achieve on-sky results in 2020. DREAMS is on-track to be one of the first astronomical telescopes to use an Indium Galium Arsenide (InGaAs) detector and we report initial on-sky testing results for the selected detector package. DREAMS is also well placed to take advantage and provide near-infrared follow-up of the LSST