Biochemical studies on plant glycerol-3- phosphate acyltransferase

sn-Glycerol-3-phosphate acyltransferase [G3PAT, PlsB (E.coli), EC 2.3.1.15] is an enzyme involved in glycerolipid biosynthesis, catalysing the acylation of glycerol-3-phosphate (G3P) to produce lysophosphatidic acid (LPA). Chilling tolerance in plants is linked to the acyl-group composition of membranes, which is linked to acyltransferases with a higher selectivity for unsaturated acyl-substrates. Plant soluble G3PAT is located in the chloroplast and uses acyl-acyl carrier protein (acyl-ACP) as substrate. Soluble G3PAT exhibits strong substrate selectivity for acyl-ACP, the plastidial substrate in vivo, over acyl-CoA. cDNAs encoding soluble G3PATs have previously been cloned from several plant species and both oleate-selective and non-selective forms identified. The purpose of this thesis is to study the mechanism of plastidial G3PAT and attempt to identify factors important in determining substrate selectivity. An in vitro assay has been optimised to distinguish selective and non-selective enzyme forms under physiologically relevant conditions. The assay has been adapted to determine enzyme activity with a range of acyl-ACP and acyl-CoA substrates and to measure the kinetic constants Km and Vmax. Kinetic measurements have been made on a G3PAT protein from the chilling sensitive plant squash (Cucurbita moschata) and the L261F mutant protein containing a single amino acid substitution that significantly alters substrate selectivity. The mutation was found to increase selectivity by raising Km for unsaturated acyl-substrate. Mutant squash G3PAT proteins have been investigated to determine the importance of particular regions or amino acid residues. The mutations E142A, K193S, R235S and R237S resulted in enzymes that were completely inactive. The mutations H194S and L261F altered catalytic or substrate binding characteristics without enzyme inactivation. The catalytic mechanism and order of substrate binding for squash G3PAT have been determined, the reaction was found to proceed via a compulsory-ordered ternary complex with acyl-ACP binding before glycerol-3-phosphate

The Bard Sequence Program: An Equitable Approach to Virtual Learning

Earning as few as twelve college credits from a genuine college program in high school is a consistent predictor of student success and graduation from college. Unfortunately, many students either do not have access to dual enrollment or the access they do have is limited to canned lectures, asynchronous busy work, and predatory degree mill programs. This is disproportionately so for students from historically marginalized communities. The Bard Sequence is expanding virtually to fill this major nationwide gap in dual enrollment opportunities. The equity-based Writing and Thinking pedagogy at the heart of the Bard Sequence ensures that more students than ever before have access to life-changing educational opportunities in high school

Optical Theory for the Advancement of Polarization Lidar

Determining the polarization scattering properties of sub micron size particles through interactions with transmitted visible wavelengths requires the capability to detect polarization effects on the order of a few percent. Such small changes in polarization can easily be overwhelmed by the intrinsic polarization properties of the instrument. When applied to lidar remote sensing techniques, additional environmental factors such as background noise, volume content of scatterers, range to the scatterer, and temporal variations in the scattering medium result in degradation of the instrument's SNR. Furthermore, present approaches in polarization lidar are often confined to measurement of a single parameter which provides no distinction between different scattering and instrumentation polarization effects, limiting the possible interpretations of the measurement. These issues confronting polarization lidar present an opportunity for a novel approach in lidar polarization studies through expansion of system measurement capabilities and instrument performance optimization. In this work, I discuss how these issues may be addressed for the purpose of characterizing particle properties through polarization. Instrument retarding effects are reduced by measuring the optical system Mueller matrix and implementing a hardware polarization compensator which also increases system SNR by improving rejection of the polarized sky noise component. We have developed a calibration algorithm which then removes residual phase shifts, depolarization, and misalignment of transmitter and receiver polarization planes. These techniques are proven through polarization data from atmospheric aerosols measured by the ARCLITE lidar in Kangerlussuaq, Greenland. By recognizing that a scattering phase matrix is a Mueller matrix, the polarization effects of scatterers can be decomposed and described as a combination of depolarizers, retarders, and diattenuators. Furthermore, the polarization attributes of scatterers can be directly related to their physical properties. While it is well established that depolarizing effects can distinguish between thermodynamic phase of tropospheric clouds, diattenuation can be used as an indicator for the presence of horizontally oriented ice crystals which are known to impact Earth's radiative budget. We have developed techniques for making this new and novel polarization measurement in the atmosphere. A NOAA lidar has been designed to detect diattenuation in the troposphere and has begun a campaign to detect oriented scatterers over Summit Camp, Greenland. The lidar was tilted by 11 degrees off zenith in late April 2011 and initial results of this campaign are shown. These results appear promising in demonstrating the lidar's ability to perform this novel measurement for detection of horizontally oriented ice crystals

Mimicking non-ideal instrument behavior for hologram processing using neural style translation

Holographic cloud probes provide unprecedented information on cloud particle density, size and position. Each laser shot captures particles within a large volume, where images can be computationally refocused to determine particle size and shape. However, processing these holograms, either with standard methods or with machine learning (ML) models, requires considerable computational resources, time and occasional human intervention. ML models are trained on simulated holograms obtained from the physical model of the probe since real holograms have no absolute truth labels. Using another processing method to produce labels would be subject to errors that the ML model would subsequently inherit. Models perform well on real holograms only when image corruption is performed on the simulated images during training, thereby mimicking non-ideal conditions in the actual probe (Schreck et. al, 2022). Optimizing image corruption requires a cumbersome manual labeling effort. Here we demonstrate the application of the neural style translation approach (Gatys et. al, 2016) to the simulated holograms. With a pre-trained convolutional neural network (VGG-19), the simulated holograms are ``stylized'' to resemble the real ones obtained from the probe, while at the same time preserving the simulated image ``content'' (e.g. the particle locations and sizes). Two image similarity metrics concur that the stylized images are more like real holograms than the synthetic ones. With an ML model trained to predict particle locations and shapes on the stylized data sets, we observed comparable performance on both simulated and real holograms, obviating the need to perform manual labeling. The described approach is not specific to hologram images and could be applied in other domains for capturing noise and imperfections in observational instruments to make simulated data more like real world observations.Comment: 23 pages, 9 figure

Global Estimation of Range Resolved Thermodynamic Profiles from MicroPulse Differential Absorption Lidar

We demonstrate thermodynamic profile estimation with data obtained using the MicroPulse DIAL such that the retrieval is entirely self contained. The only external input is surface meteorological variables obtained from a weather station installed on the instrument. The estimator provides products of temperature, absolute humidity and backscatter ratio such that cross dependencies between the lidar data products and raw observations are accounted for and the final products are self consistent. The method described here is applied to a combined oxygen DIAL, potassium HSRL, water vapor DIAL system operating at two pairs of wavelengths (nominally centered at 770 and 828 nm). We perform regularized maximum likelihood estimation through the Poisson Total Variation technique to suppress noise and improve the range of the observations. A comparison to 119 radiosondes indicates that this new processing method produces improved temperature retrievals, reducing total errors to less than 2 K below 3 km altitude and extending the maximum altitude of temperature retrievals to 5 km with less than 3 K error. The results of this work definitively demonstrates the potential for measuring temperature through the oxygen DIAL technique and furthermore that this can be accomplished with low-power semiconductor-based lidar sensors

2D Signal Estimation for Sparse Distributed Target Photon Counting Data

In this study, we explore the utilization of maximum likelihood estimation for the analysis of sparse photon counting data obtained from distributed target lidar systems. Specifically, we adapt the Poisson Total Variation processing technique to cater to this application. By assuming a Poisson noise model for the photon count observations, our approach yields denoised estimates of backscatter photon flux and related parameters. This facilitates the processing of raw photon counting signals with exceptionally high temporal and range resolutions (demonstrated here to 50 Hz and 75 cm resolutions), including data acquired through time-correlated single photon counting, without significant sacrifice of resolution. Through examination involving both simulated and real-world 2D atmospheric data, our method consistently demonstrates superior accuracy in signal recovery compared to the conventional histogram-based approach commonly employed in distributed target lidar applications

Evaluation of an emergency safe supply drugs and managed alcohol program in COVID-19 isolation hotel shelters for people experiencing homelessness

BACKGROUND: During a COVID-19 outbreak in the congregate shelter system in Halifax, Nova Scotia, Canada, a multidisciplinary health care team provided an emergency “safe supply” of pharmaceutical-grade medications and beverage-grade alcohol to facilitate isolation in COVID-19 hotel shelters for residents who are dependent on these substances. We aimed to evaluate (a) substances and dosages provided, and (b) effectiveness and safety of the program. METHODS: We retrospectively reviewed medical records of all COVID-19 isolation hotel shelter residents during May 2021. We extracted data on medication and alcohol dosages provided each day. The primary outcome was residents prematurely leaving isolation against public health orders. Adverse events included (a) overdose; (b) intoxication; and (c) diversion, selling, or sharing of medications or alcohol. RESULTS: Over 25 days, 77 isolation hotel residents were assessed (mean age 42 ± 14 years; 24% women). Sixty-two (81%) residents were provided medications, alcohol, or cigarettes. Seventeen residents (22%) received opioid agonist treatment medications (methadone, buprenorphine, or slow-release oral morphine) and 27 (35%) received hydromorphone tablets. Thirty-one (40%) residents received stimulant tablets with methylphenidate (27; 35%), dextroamphetamine (8; 10%), or lisdexamfetamine (2; 3%). Six residents (8%) received benzodiazepines. Forty-two (55%) residents received alcohol, including 41 (53%) with strong beer, three (3%) with wine, and one (1%) with hard liquor. Over 14 days in isolation, mean daily dosages increased of hydromorphone (45 ± 32 to 57 ± 42mg), methylphenidate (51 ± 28 to 77 ± 37mg), dextroamphetamine (33 ± 16 to 46 ± 13mg), and alcohol (12.3 ± 7.6 to 13.0 ± 6.9 standard drinks). Six residents (8%) left isolation prematurely, but four of those residents returned. Over 1,059 person-days in isolation, there were zero overdoses. Documented concerns regarding intoxication occurred six times (0.005 events/person-day) and medication diversion or sharing three times (0.003 events/person-day). CONCLUSIONS: An emergency safe supply and managed alcohol program, paired with housing, was associated with low rates of adverse events and high rates of successful completion of the 14-day isolation period in COVID-19 isolation hotel shelters. This supports the effectiveness and safety of emergency safe supply prescribing and managed alcohol in this setting

Prediction of Radiation Esophagitis in Non-Small Cell Lung Cancer Using Clinical Factors, Dosimetric Parameters, and Pretreatment Cytokine Levels

Radiation esophagitis (RE) is a common adverse event associated with radiotherapy for non-small cell lung cancer (NSCLC). While plasma cytokine levels have been correlated with other forms of radiation-induced toxicity, their association with RE has been less well studied. We analyzed data from 126 patients treated on 4 prospective clinical trials. Logistic regression models based on combinations of dosimetric factors [maximum dose to 2 cubic cm (D2cc) and generalized equivalent uniform dose (gEUD)], clinical variables, and pretreatment plasma levels of 30 cytokines were developed. Cross-validated estimates of area under the receiver operating characteristic curve (AUC) and log likelihood were used to assess prediction accuracy. Dose-only models predicted grade 3 RE with AUC values of 0.750 (D2cc) and 0.727 (gEUD). Combining clinical factors with D2cc increased the AUC to 0.779. Incorporating pretreatment cytokine measurements, modeled as direct associations with RE and as potential interactions with the dose-esophagitis association, produced AUC values of 0.758 and 0.773, respectively. D2cc and gEUD correlated with grade 3 RE with odds ratios (ORs) of 1.094/Gy and 1.096/Gy, respectively. Female gender was associated with a higher risk of RE, with ORs of 1.09 and 1.112 in the D2cc and gEUD models, respectively. Older age was associated with decreased risk of RE, with ORs of 0.992/year and 0.991/year in the D2cc and gEUD models, respectively. Combining clinical with dosimetric factors but not pretreatment cytokine levels yielded improved prediction of grade 3 RE compared to prediction by dose alone. Such multifactorial modeling may prove useful in directing radiation treatment planning

Racial Differences in Treatments and Toxicity in Non-Small Cell Lung Cancer Patients Treated with Thoracic Radiation Therapy

Background: Racial disparities are of particular concern for lung cancer patients given historical differences in surgery rates for African-American lung cancer patients that resulted in lower overall survival and higher recurrence rates compared with rates in White patients. Objectives: The overall objective of this study was to examine racial differences in thoracic radiation therapy (RT) treatments and toxicities in a large cohort of patients from a multi-institutional consortium database of non-small cell lung cancer (NSCLC) patients. Methods: A large multi-institutional statewide prospectively collected patient-level database of locally advanced (stage II or III) NSCLC patients who received thoracic RT from March 2012 to November 2019 was analyzed to assess the associations between race and treatment and toxicity variables. Race (White or African-American) was defined by patient self-report or if not available then by the electronic medical record system classification. Race categories other than White or African-American comprised a small minority of patients and were excluded from this analysis. Patient-reported toxicity was determined by validated tools including the Functional Assessment of Cancer Therapy-Lung (FACT-L) quality of life instrument. Provider-reported toxicity was determined by the Common Terminology Criteria for Adverse Events (CTCAE) version 4.0. Uni-variable and multi-variable regression models were then fitted to assess relationships between primary outcomes by race and indicators of high-quality treatment and secondary analysis of symptoms. Spearman rank correlation coefficients were calculated between provider reported toxicity and similar patient reported outcomes for each race category. Results: A total of 1441 patients from 24 institutions with mean age of 68 years (range 38-94) were evaluated; 226 patients were African-American, of whom 61% were treated at three facilities. Race was not significantly associated with RT treatment approach, use of concurrent chemotherapy, or the dose to the planning target volume (PTV) or organs at risk including the heart and lungs. However, there was increased patient-reported general pain in African-American patients (compared with White patients) at several time points including pre-RT (22% (vs 15%), P=0.02) and at the end of RT (30% (vs 17%), P=0.001). African-American patients were significantly less likely to have provider-reported grade 2+ radiation pneumonitis (odds ratio (OR) 0.36, P=0.03), despite similar levels of patient-reported respiratory toxicities such as cough and shortness of breath and even after controlling for known patient and treatment-related factors. Correlation coefficients between provider- and patient-reported toxicities were generally similar across race categories. Conclusions: In this large multi-institutional observational study, we reassuringly found no evidence of differences in radiation treatment or chemotherapy approaches by race, in contrast to historical differences by race in surgical care that led to worse survival and outcomes in minority race patients. However, we did unexpectedly find that African-American race was associated with lower odds of provider-reported grade 2+ radiation pneumonitis despite similar patient-reported toxicities of shortness of breath and cough. There are several possibilities for this finding including that pneumonitis is a multifactorial diagnosis that relies on clinical as well as radiologic information and clinical information alone may be insufficient. The Spearman correlation analysis also revealed stronger correlations between patient- and provider-reported toxicities in White patients compared with African-American patients, particularly for trouble swallowing/esophagitis. These findings together for pneumonitis and esophagitis discouragingly suggest possible under-recognition of symptoms in black patients. Further investigation is now warranted to better understand how these findings impact the care of racially diverse lung cancer patients