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Psychoactive drugs are compounds that alter the function of the central nervous system, resulting in changes in perception, mood, cognition, and behavior. A subclass of psychoactive drugs, psychedelics, are hallucinogenic drugs that can trigger psychedelic experiences and possible changes in mental perception. The potential use of psychedelics as a therapeutic has led to an increase in clinical research focusing on the treatment of mental disorders including anxiety and depression. There are numerous species belonging to Psychotria and Banisteriopsis which have been reported to contain psychedelic and psychoactive compounds; however, there is a lack of validated analytical methods for raw plant material, which is crucial if these plants are to be commercially cultivated for medicines. This study provides a fully validated method using ultra-high performance liquid chromatography (UHPLC) coupled to mass spectrometry (MS) for the following six compounds: tryptamine, N,N-dimethyltryptamine (DMT), 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT), tetrahydroharmine (THH), harmaline, and harmine. The validated method was used to determine the psychoactive concentrations in Psychotria viridis, Psychotria carthagenensis, Banisteriopsis caapi, and Alicia anisopetala. Validation parameters were established; linearity (R2 = 0.988–0.999), limit of detection (LOD) (0.06–0.11 ng/mL), limit of quantitation (LOQ) (0.18–0.34 ng/mL), accuracy, precision, extraction efficiency (>98%), recovery (74.1–111.6%), and matrix effect (70.6–109%) were all evaluated. All six compounds eluted within nine minutes, with a total analysis time of 20 min including column equilibration. This method establishes a high-throughput method for the robust analysis of psychedelics which may see future use in agricultural research and industry.

Purpose: To analyze the most frequently searched questions associated with shoulder labral pathology and to evaluate the source-type availability and quality. Methods: Common shoulder labral pathology-related search terms were entered into Google, and the suggested frequently asked questions were compiled and categorized. In addition, suggested sources were recorded, categorized, and scored for quality of information using JAMA (The Journal of the American Medical Association) benchmark criteria. Statistical analysis was performed to compare the types of questions and their associated sources, as well as the quality of sources. Results: In this study, 513 questions and 170 sources were identified and categorized. The most popular topics were diagnosis/evaluation (21.5%) and indications/management (21.1%.). The most common website types were academic (27.9%), commercial (25.2%), and medical practice (22.5%). Multiple statistically significant associations were found between specific question categories and their associated source types. The average JAMA quality score for all sources was 1.56, and medical websites had significantly lower quality scores than nonmedical sites (1.05 vs 2.12, P < .001). Conclusions: Patients searching the internet for information regarding shoulder labral pathology often look for facts regarding the diagnosis and management of their conditions. They use various source types to better understand their conditions, with government sources being of the highest quality, whereas medical sites showed statistically lower quality. Across the spectrum of questions, the quality of readily available resources varies substantially. Clinical Relevance: The use of online resources in health care is expanding. It is important to understand the most commonly asked questions and the quality of information available to patients.

Introduction: The COVID-19 pandemic posed serious challenges to cancer screening delivery, including cervical cancer. While the impact of the pandemic on deferred screening has been documented, less is known about how clinicians experienced barriers to screening delivery, and, in particular, the role of pre-pandemic barriers to changes reported during the pandemic. Methods: Survey of clinicians who performed ≥ 10 cervical cancer screening tests in 2019 from Mass General Brigham, Kaiser Permanente Washington, and Parkland Health, the healthcare systems participating in the Population-based Research to Optimize the Screening Process (PROSPR II) consortium (administered 10/2020–12/2020, response rate 53.7 %). Results: Prior to the pandemic, clinicians commonly noted barriers to the delivery of cervical cancer screening including lack of staff support (57.6%), interpreters (32.5%), resources to support patients with social barriers to care (61.3%), and discrimination or bias in interactions between staff and patients (31.2%). Clinicians who reported experiencing a given barrier to care before the pandemic were more likely than those who did not experience one to report worsening during the pandemic: lack of staff support (odds ratio 4.70, 95% confidence interval 2.94–7.52); lack of interpreters (8.23, 4.46–15.18); lack of resources to support patients in overcoming social barriers (7.65, 4.41–13.27); and discrimination or bias (6.73, 3.03–14.97). Conclusions: Clinicians from three health systems who deliver cervical cancer screening commonly reported barriers to care. Barriers prior to the pandemic were associated with worsening of barriers during the pandemic. Addressing barriers to cervical cancer screening may promote resilience of care delivery during the next public health emergency.

Abstract Background Ross River virus (RRV) is Australia’s most common and widespread mosquito-transmitted arbovirus and is of significant public health concern. With increasing anthropogenic impacts on wildlife and mosquito populations, it is important that we understand how RRV circulates in its endemic hotspots to determine where public health efforts should be directed. Current surveillance methods are effective in locating the virus but do not provide data on the circulation of the virus and its strains within the environment. This study examined the ability to identify single nucleotide polymorphisms (SNPs) within the variable E2/E3 region by generating full-length haplotypes from a range of mosquito trap-derived samples. Methods A novel tiled primer amplification workflow for amplifying RRV was developed with analysis using Oxford Nanopore Technology’s MinION and a custom ARTIC/InterARTIC bioinformatic protocol. By creating a range of amplicons across the whole genome, fine-scale SNP analysis was enabled by specifically targeting the variable region that was amplified as a single fragment and established haplotypes that informed spatial-temporal variation of RRV in the study site in Victoria. Results A bioinformatic and laboratory pipeline was successfully designed and implemented on mosquito whole trap homogenates. Resulting data showed that genotyping could be conducted in real time and that whole trap consensus of the viruses (with major SNPs) could be determined in a timely manner. Minor variants were successfully detected from the variable E2/E3 region of RRV, which allowed haplotype determination within complex mosquito homogenate samples. Conclusions The novel bioinformatic and wet laboratory methods developed here will enable fast detection and characterisation of RRV isolates. The concepts presented in this body of work are transferable to other viruses that exist as quasispecies in samples. The ability to detect minor SNPs, and thus haplotype strains, is critically important for understanding the epidemiology of viruses their natural environment. Graphical Abstract

Cannabis is cultivated for therapeutic and recreational purposes where delta-9 tetrahydrocannabinol (THC) is a main target for its therapeutic effects. As the global cannabis industry and research into cannabinoids expands, more efficient and cost-effective analysis methods for determining cannabinoid concentrations will be beneficial to increase efficiencies and maximize productivity. The utilization of machine learning tools to develop near-infrared (NIR) spectroscopy-based prediction models, which have been validated from accurate and sensitive chemical analysis, such as gas chromatography (GC) or liquid chromatography mass spectroscopy (LCMS), is essential. Previous research on cannabinoid prediction models targeted decarboxylated cannabinoids, such as THC, rather than the naturally occurring precursor, tetrahydrocannabinolic acid (THCA), and utilize finely ground cannabis inflorescence. The current study focuses on building prediction models for THCA concentrations in whole cannabis inflorescences prior to harvest, by employing non-destructive screening techniques so cultivators may rapidly characterize high-performing cultivars for chemotype in real time, thus facilitating targeted optimization of crossbreeding efforts. Using NIR spectroscopy and LCMS to create prediction models we can differentiate between high-THCA and even ratio classes with 100% prediction accuracy. We have also developed prediction models for THCA concentration with a R2 = 0.78 with a prediction error average of 13%. This study demonstrates the viability of a portable handheld NIR device to predict THCA concentrations on whole cannabis samples before harvest, allowing the evaluation of cannabinoid profiles to be made earlier, therefore increasing high-throughput and rapid capabilities.

Abstract Outbreaks of avian influenza virus (AIV) from wild waterfowl into the poultry industry is of upmost significance and is an ongoing and constant threat to the industry. Accurate surveillance of AIV in wild waterfowl is critical in understanding viral diversity in the natural reservoir. Current surveillance methods for AIV involve collection of samples and transportation to a laboratory for molecular diagnostics. Processing of samples using this approach takes more than three days and may limit testing locations to those with practical access to laboratories. In potential outbreak situations, response times are critical, and delays have implications in terms of the spread of the virus that leads to increased economic cost. This study used nanopore sequencing technology for in-field sequencing and subtype characterisation of AIV strains collected from wild bird faeces and poultry. A custom in-field virus screening and sequencing protocol, including a targeted offline bioinformatic pipeline, was developed to accurately subtype AIV. Due to the lack of optimal diagnostic MinION packages for Australian AIV strains the bioinformatic pipeline was specifically targeted to confidently subtype local strains. The method presented eliminates the transportation of samples, dependence on internet access and delivers critical diagnostic information in a timely manner.

Psychoactive drugs are compounds that alter the function of the central nervous system, resulting in changes in perception, mood, cognition, and behavior. A subclass of psychoactive drugs, psychedelics, are hallucinogenic drugs that can trigger psychedelic experiences and possible changes in mental perception. The potential use of psychedelics as a therapeutic has led to an increase in clinical research focusing on the treatment of mental disorders including anxiety and depression. There are numerous species belonging to Psychotria and Banisteriopsis which have been reported to contain psychedelic and psychoactive compounds; however, there is a lack of validated analytical methods for raw plant material, which is crucial if these plants are to be commercially cultivated for medicines. This study provides a fully validated method using ultra-high performance liquid chromatography (UHPLC) coupled to mass spectrometry (MS) for the following six compounds: tryptamine, N,N-dimethyltryptamine (DMT), 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT), tetrahydroharmine (THH), harmaline, and harmine. The validated method was used to determine the psychoactive concentrations in Psychotria viridis, Psychotria carthagenensis, Banisteriopsis caapi, and Alicia anisopetala. Validation parameters were established; linearity (R2 = 0.988–0.999), limit of detection (LOD) (0.06–0.11 ng/mL), limit of quantitation (LOQ) (0.18–0.34 ng/mL), accuracy, precision, extraction efficiency (>98%), recovery (74.1–111.6%), and matrix effect (70.6–109%) were all evaluated. All six compounds eluted within nine minutes, with a total analysis time of 20 min including column equilibration. This method establishes a high-throughput method for the robust analysis of psychedelics which may see future use in agricultural research and industry. [ABSTRACT FROM AUTHOR]

Abstract Background Insecticide-treated net (ITN) durability is evaluated using longitudinal bioefficacy and fabric integrity sampling post-distribution. Interceptor® G2 was developed for resistance management and contains two adulticides: alpha-cypermethrin and chlorfenapyr; it is a pro-insecticide that is metabolized into its active form by mosquito-detoxifying enzymes and may be enhanced when the mosquito is physiologically active. To elucidate the impact of bioassay modality, mosquito exposures of the alphacypermethrin ITN Interceptor® and dual adulticide Interceptor® G2 were investigated. Methods This study evaluated the performance of Interceptor® G2 compared to Interceptor® against local strains of mosquitoes in Tanzania. Unwashed and 20× times washed nets were tested. Efficacy of ITNs was measured by four bioassay types: (1) World Health Organisation (WHO) cone test (cone), (2) WHO tunnel test (tunnel), (3) Ifakara ambient chamber test (I-ACT) and (4) the WHO gold standard experimental hut test (hut). Hut tests were conducted against free-flying wild pyrethroid metabolically resistant Anopheles arabiensis and Culex quinquefasciatus. Cone, tunnel and I-ACT bioassays used laboratory-reared metabolically resistant An. arabiensis and Cx. quinquefasciatus and pyrethroid susceptible Anopheles gambiae sensu stricto and Aedes aegypti. Results Against resistant strains, superiority of Interceptor® G2 over Interceptor® was observed in all “free-flying bioassays”. In cone tests (which restrict mosquito flight), superiority of Interceptor® over Interceptor® G2 was recorded. Mortality of unwashed Interceptor® G2 among An. arabiensis was lowest in hut tests at 42.9% (95% CI: 37.3–48.5), although this increased to 66.7% (95% CI: 47.1–86.3) by blocking hut exit traps so mosquitoes presumably increased frequencies of contact with ITNs. Higher odds of mortality were consistently observed in Interceptor® G2 compared to Interceptor® in “free-flying” bioassays using An. arabiensis: tunnel (OR = 1.42 [95% CI:1.19–1.70], p

Abstract Background For millennia, drug-type cannabis strains were extensively used for various medicinal, ritual, and inebriant applications. However, cannabis prohibition during the last century led to cultivation and breeding activities being conducted under clandestine conditions, while scientific development of the crop ceased. Recently, the potential of medicinal cannabis has been reacknowledged and the now expanding industry requires optimal and scientifically characterized varieties. However, scientific knowledge that can propel this advancement is sorely lacking. To address this issue, the current study aims to provide a better understanding of key physiological and phenological traits that can facilitate the breeding of advanced cultivars. Results A diverse population of 121 genotypes of high-THC or balanced THC-CBD ratio was cultivated under a controlled environment facility and 13 plant parameters were measured. No physiological association across genotypes attributed to the same vernacular classification was observed. Floral bud dry weight was found to be positively associated with plant height and stem diameter but not with days to maturation. Furthermore, the heritability of both plant height and days to maturation was relatively high, but for plant height it decreased during the vegetative growth phase. To advance breeding efficacy, a prediction equation for forecasting floral bud dry weight was generated, driven by parameters that can be detected during the vegetative growth phase solely. Conclusions Our findings suggest that selection for taller and fast-growing genotypes is likely to lead to an increase in floral bud productivity. It was also found that the final plant height and stem diameter are determined by 5 independent factors that can be used to maximize productivity through cultivation adjustments. The proposed prediction equation can facilitate the selection of prolific genotypes without the completion of a full cultivation cycle. Future studies that will associate genome-wide variation with plants morphological traits and cannabinoid profile will enable precise and accelerated breeding through genomic selection approaches.

Background: When coronavirus disease 2019 (COVID-19) first spread to the United States, our institution was at the outbreak's epicenter. Despite limited understanding of COVID-19's long-term effects, we continued performing surgical fixation of geriatric hip fractures under strict guidelines. This study examined the outcomes of these patients during the pandemic compared with those of patients treated pre-pandemic. Materials and Methods: We conducted a retrospective cohort study of patients with hip fractures between December 2019 and June 2020, the peak of the pandemic in our region. Outcomes of patients treated with surgical fixation (2020 cohort) were compared with those of a historical control group (2019 cohort). The primary outcome was 90-day mortality, with secondary outcomes including pneumonia, thromboembolic events, emergency department visits, readmission, and cardiac events. Results: The 2020 cohort (n=64) and 2019 cohort (n=78) had similar baseline characteristics. The 2020 cohort had a 4.27 times higher risk (95% CI, 1.30–13.98) of developing pneumonia compared with the pre-pandemic cohort but had no other differences in 90-day complications. Patients with COVID-19 in the 2020 cohort had a 5.09 times higher risk (95% CI, 1.35–19.20) of developing pneumonia and a 5.38 times higher risk (95% CI, 1.13–25.64) of postoperative mortality. There was no increased risk for thromboembolism between the 2020 and 2019 cohorts, even among COVID-19 cases, as all patients received anticoagulation with heparin. Conclusion: Our study demonstrates that hip fracture surgery remained safe during the peak of the US COVID-19 pandemic, with an expected increase in pneumonia and mortality risk for patients with hip fracture with COVID-19. [Orthopedics. 2024;47(6):359–364.] [ABSTRACT FROM AUTHOR]

In recent decades with the reacknowledgment of the medicinal properties of Cannabis sativa L. (cannabis) plants, there is an increased demand for high performing cultivars that can deliver quality products for various applications. However, scientific knowledge that can facilitate the generation of advanced cannabis cultivars is scarce. In order to improve cannabis breeding and optimize cultivation techniques, the current study aimed to examine the morphological attributes of cannabis inflorescences using novel image analysis practices. The investigated plant population comprises 478 plants ascribed to 119 genotypes of high−THC or blended THC−CBD ratio that was cultivated under a controlled environment facility. Following harvest, all plants were manually processed and an image of the trimmed and refined inflorescences extracted from each plant was captured. Image analysis was then performed using in-house custom-made software which extracted 8 morphological features (such as size, shape and perimeter) for each of the 127,000 extracted inflorescences. Our findings suggest that environmental factors play an important role in the determination of inflorescences’ morphology. Therefore, further studies that focus on genotype X environment interactions are required in order to generate inflorescences with desired characteristics. An examination of the intra-plant inflorescences weight distribution revealed that processing 75% of the plant’s largest inflorescences will gain 90% of its overall yield weight. Therefore, for the optimization of post-harvest tasks, it is suggested to evaluate if the benefits from extracting and processing the plant’s smaller inflorescences outweigh its operational costs. To advance selection efficacy for breeding purposes, a prediction equation for forecasting the plant’s production biomass through width measurements of specific inflorescences, formed under the current experimental methodology, was generated. Thus, it is anticipated that findings from the current study will contribute to the field of medicinal cannabis by improving targeted breeding programs, advancing crop productivity and enhancing the efficacy of post-harvest procedures.

The spotted wing drosophila (Drosophila suzukii, Matsumara) is a rapidly spreading global pest of soft and stone fruit production. Due to the similarity of many of its life stages to other cosmopolitan drosophilids, surveillance for this pest is currently bottlenecked by the laborious sorting and morphological identification of large mixed trap catches. DNA metabarcoding presents an alternative high-throughput sequencing (HTS) approach for multi-species identification, which may lend itself ideally to rapid and scalable diagnostics of D. suzukii within unsorted trap samples. In this study, we compared the qualitative (identification accuracy) and quantitative (bias toward each species) performance of four metabarcoding primer pairs on D. suzukii and its close relatives. We then determined the sensitivity of a non-destructive metabarcoding assay (i.e., which retains intact specimens) by spiking whole specimens of target species into mock communities of increasing specimen number, as well as 29 field-sampled communities from a cherry and a stone fruit orchard. Metabarcoding successfully detected D. suzukii and its close relatives Drosophila subpulchrella and Drosophila biarmipes in the spiked communities with an accuracy of 96, 100, and 100% respectively, and identified a further 57 non-target arthropods collected as bycatch by D. suzukii surveillance methods in a field scenario. While the non-destructive DNA extraction retained intact voucher specimens, dropouts of single species and entire technical replicates suggests that these protocols behave more similarly to environmental DNA than homogenized tissue metabarcoding and may require increased technical replication to reliably detect low-abundance taxa. Adoption of high-throughput metabarcoding assays for screening bulk trap samples could enable a substantial increase in the geographic scale and intensity of D. suzukii surveillance, and thus likelihood of detecting a new introduction. Trap designs and surveillance protocols will, however, need to be optimized to adequately preserve specimen DNA for molecular identification.

Category: Lesser Toes; Trauma Introduction/Purpose: To evaluate the importance of a radiographic lateral view in diagnosing lesser toes traumatic conditions. Methods: Between January 2018 and March 2018, 378 radiographs of 126 patients evaluated in an emergency care hospital for trauma in the lesser toe were retrospectively evaluated for presence of lesser toes traumatic conditions. Patients were selected if a complete series of radiographs were performed, anteroposterior (AP), lateral (LA) and Oblique (OB). Radiographs of the same patient were duplicated and divided in two groups: standard group (AP and OB) and complete group (AP + LA + OB). Images were examined by four independent examiners with different degrees of experience. Each examiner randomly evaluated the same patient twice (one for each group). Kappa index was used to evaluate intra and inter-examiner concordance, and the two- proportion equality test was used to calculate statistical significance. Results: Mean age of patients was 37.2 years (4-85yr), 144 injuries were diagnosed in standard group (28.6%) and 266 injuries (52.8%) in complete group (p

Heterosis is defined as increased performance of the F1 hybrid relative to its parents. In the current study, a cohort of populations and parents were created to evaluate and understand heterosis across generations (i.e., F1 to F3) in lentil, a self-pollinated annual diploid (2n = 2× = 14) crop species. Lentil plants were evaluated for heterotic traits in terms of plant height, biomass fresh weight, seed number, yield per plant and 100 grain weight. A total of 47 selected lentil genotypes were cross hybridized to generate 72 F1 hybrids. The F1 hybrids from the top five crosses exhibited between 31%-62% heterosis for seed number with reference to the better parent. The five best performing heterotic crosses were selected with a negative control for evaluation at the subsequent F2 generation and only the tails of the distribution taken forward to be assessed in the F3 generation as a sub selection. Overall, heterosis decreases across the subsequent generations for all traits studied. However, some individual genotypes were identified at the F2 and sub-selected F3 generations with higher levels of heterosis than the best F1 mean value (hybrid mimics). The phenotypic data for the selected F2 and sub selected F3 hybrids were analysed, and the study suggested that 100 grain weight was the biggest driver of yield followed by seed number. A genetic diversity analysis of all the F1 parents failed to correlate genetic distance and divergence among parents with heterotic F1's. Therefore, genetic distance was not a key factor to determine heterosis in lentil. The study highlights the challenges associated with different breeding systems for heterosis (i.e., F1 hybrid-based breeding systems and/or via hybrid mimics) but demonstrates the potential significant gains that could be achieved in lentil productivity.

Cannabis sativa L. produces unique phytocannabinoids, which are used for their pharmaceutical benefits. To date, there are no reports of in vivo engineering targeting the cannabinoid biosynthesis genes to greater elucidate the role each of these genes play in synthesis of these medically important compounds. Reported here is the first modulation of cannabinoid biosynthesis genes using RNAi via agroinfiltration. Vacuum infiltrated leaf segments of the Cannbio-2 C. sativa strain, transfected with different RNAi constructs corresponding to THCAS, CBDAS, and CBCAS gene sequences, showed significant downregulation of all cannabinoid biosynthesis genes using real-time quantitative PCR. Using RNAi, significant off-targeting occurs resulting in the downregulation of highly homologous transcripts. Significant (p

Maintaining specific and reproducible cannabinoid compositions (type and quantity) is essential for the production of cannabis-based remedies that are therapeutically effective. The current study investigates factors that determine the plant’s cannabinoid profile and examines interrelationships between plant features (growth rate, phenology and biomass), inflorescence morphology (size, shape and distribution) and cannabinoid content. An examination of differences in cannabinoid profile within genotypes revealed that across the cultivation facility, cannabinoids’ qualitative traits (ratios between cannabinoid quantities) remain fairly stable, while quantitative traits (the absolute amount of Δ9-tetrahydrocannabinol (THC), cannabidiol (CBD), cannabichromene (CBC), cannabigerol (CBG), Δ9-tetrahydrocannabivarin (THCV) and cannabidivarin (CBDV)) can significantly vary. The calculated broad-sense heritability values imply that cannabinoid composition will have a strong response to selection in comparison to the morphological and phenological traits of the plant and its inflorescences. Moreover, it is proposed that selection in favour of a vigorous growth rate, high-stature plants and wide inflorescences is expected to increase overall cannabinoid production. Finally, a range of physiological and phenological features was utilised for generating a successful model for the prediction of cannabinoid production. The holistic approach presented in the current study provides a better understanding of the interaction between the key features of the cannabis plant and facilitates the production of advanced plant-based medicinal substances.

Cannabis is cultivated for therapeutic and recreational purposes where delta-9 tetrahydrocannabinol (THC) is a main target for its therapeutic effects. As the global cannabis industry and research into cannabinoids expands, more efficient and cost-effective analysis methods for determining cannabinoid concentrations will be beneficial to increase efficiencies and maximize productivity. The utilization of machine learning tools to develop near-infrared (NIR) spectroscopy-based prediction models, which have been validated from accurate and sensitive chemical analysis, such as gas chromatography (GC) or liquid chromatography mass spectroscopy (LCMS), is essential. Previous research on cannabinoid prediction models targeted decarboxylated cannabinoids, such as THC, rather than the naturally occurring precursor, tetrahydrocannabinolic acid (THCA), and utilize finely ground cannabis inflorescence. The current study focuses on building prediction models for THCA concentrations in whole cannabis inflorescences prior to harvest, by employing non-destructive screening techniques so cultivators may rapidly characterize high-performing cultivars for chemotype in real time, thus facilitating targeted optimization of crossbreeding efforts. Using NIR spectroscopy and LCMS to create prediction models we can differentiate between high-THCA and even ratio classes with 100% prediction accuracy. We have also developed prediction models for THCA concentration with a R2 = 0.78 with a prediction error average of 13%. This study demonstrates the viability of a portable handheld NIR device to predict THCA concentrations on whole cannabis samples before harvest, allowing the evaluation of cannabinoid profiles to be made earlier, therefore increasing high-throughput and rapid capabilities. [ABSTRACT FROM AUTHOR]

Molecular characterization of genetically modified plants can provide crucial information for the development of detection and identification methods, to comply with traceability, and labeling requirements prior to commercialization. Detailed description of the genetic modification was previously a challenging step in the safety assessment, since it required the use of laborious and time-consuming techniques. In this study an accurate, simple, and fast method was developed for molecular characterization of genetically modified (GM) plants, following a user-friendly workflow for researchers with limited bioinformatic capabilities. Three GM events from a diverse array of crop species—perennial ryegrass, white clover, and canola—were used to test the approach that exploits long-read sequencing by the MinION device, from Oxford Nanopore Technologies. The method delivered a higher degree of resolution of the transgenic events within the host genome than has previously been possible with the standard Illumina short-range sequencing strategies. The flanking sequences, copy number, and presence of backbone sequences, and overall transgene insertion structure were determined for each of the plant genomes, with the additional identification of moderate-sized secondary insertions that would have previously been missed. The proposed workflow takes only about 1 week from DNA extraction to analyzed result, and the method will complement the existing approaches for molecular characterization of GM plants, since it makes the process faster, simpler, and more cost-effective.

Cannabis is a diploid species (2n = 20), the estimated haploid genome sizes of the female and male plants using flow cytometry are 818 and 843 Mb respectively. Although the genome of Cannabis has been sequenced (from hemp, wild and high-THC strains), all assemblies have significant gaps. In addition, there are inconsistencies in the chromosome numbering which limits their use. A new comprehensive draft genome sequence assembly (∼900 Mb) has been generated from the medicinal cannabis strain Cannbio-2, that produces a balanced ratio of cannabidiol and delta-9-tetrahydrocannabinol using long-read sequencing. The assembly was subsequently analysed for completeness by ordering the contigs into chromosome-scale pseudomolecules using a reference genome assembly approach, annotated and compared to other existing reference genome assemblies. The Cannbio-2 genome sequence assembly was found to be the most complete genome sequence available based on nucleotides assembled and BUSCO evaluation in Cannabis sativa with a comprehensive genome annotation. The new draft genome sequence is an advancement in Cannabis genomics permitting pan-genome analysis, genomic selection as well as genome editing.

Intensive breeding of cultivated lentil has resulted in a relatively narrow genetic base, which limits the options to increase crop productivity through selection. Assessment of genetic diversity in the wild gene pool of lentil, as well as characterization of useful and novel alleles/genes that can be introgressed into elite germplasm, presents new opportunities and pathways for germplasm enhancement, followed by successful crop improvement. In the current study, a lentil collection consisting of 467 wild and cultivated accessions that originated from 10 diverse geographical regions was assessed, to understand genetic relationships among different lentil species/subspecies. A total of 422,101 high-confidence SNP markers were identified against the reference lentil genome (cv. CDC Redberry). Phylogenetic analysis clustered the germplasm collection into four groups, namely, Lens culinaris/Lens orientalis, Lens lamottei/Lens odemensis, Lens ervoides, and Lens nigricans. A weak correlation was observed between geographical origin and genetic relationship, except for some accessions of L. culinaris and L. ervoides. Genetic distance matrices revealed a comparable level of variation within the gene pools of L. culinaris (Nei’s coefficient 0.01468–0.71163), L. ervoides (Nei’s coefficient 0.01807–0.71877), and L. nigricans (Nei’s coefficient 0.02188–1.2219). In order to understand any genic differences at species/subspecies level, allele frequencies were calculated from a subset of 263 lentil accessions. Among all cultivated and wild lentil species, L. nigricans exhibited the greatest allelic differentiation across the genome compared to all other species/subspecies. Major differences were observed on six genomic regions with the largest being on Chromosome 1 (c. 1 Mbp). These results indicate that L. nigricans is the most distantly related to L. culinaris and additional structural variations are likely to be identified from genome sequencing studies. This would provide further insights into evolutionary relationships between cultivated and wild lentil germplasm, for germplasm improvement and introgression.

Plant seeds have long been promoted as a production platform for novel fatty acids such as the ω3 long-chain (≥ C20) polyunsaturated fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) commonly found in fish oil. In this article we describe the creation of a canola (Brassica napus) variety producing fish oil-like levels of DHA in the seed. This was achieved by the introduction of a microalgal/yeast transgenic pathway of seven consecutive enzymatic steps which converted the native substrate oleic acid to α-linolenic acid and, subsequently, to EPA, docosapentaenoic acid (DPA) and DHA. This paper describes construct design and evaluation, plant transformation, event selection, field testing in a wide range of environments, and oil profile stability of the transgenic seed. The stable, high-performing event NS-B50027-4 produced fish oil-like levels of DHA (9–11%) in open field trials of T3 to T7 generation plants in several locations in Australia and Canada. This study also describes the highest seed DHA levels reported thus far and is one of the first examples of a deregulated genetically modified crop with clear health benefits to the consumer.

Abstract Background The growing numbers of cancer survivors challenge delivery of high-quality survivorship care by healthcare systems. Innovative ways to improve care coordination for patients with cancer and multiple chronic conditions (“complex cancer survivors”) are needed to achieve better care outcomes, improve patient experience of care, and lower cost. Our study, Project CONNECT, will adapt and implement three evidence-based care coordination strategies, shown to be effective for primary care conditions, among complex cancer survivors. Specifically, the purpose of this study is to: 1) Implement a system-level EHR-driven intervention for 500 complex cancer survivors at Parkland; 2) Test effectiveness of the strategies on system- and patient-level outcomes measured before and after implementation; and 3) Elucidate system and patient factors that facilitate or hinder implementation and result in differences in experiences of care coordination between complex patients with and without cancer. Methods Project CONNECT is a quasi-experimental implementation study among 500 breast and colorectal cancer survivors with at least one of the following chronic conditions: diabetes, hypertension, chronic lung disease, chronic kidney disease, or heart disease. We will implement three evidence-based care coordination strategies in a large, county integrated safety-net health system: 1) an EHR-driven registry to facilitate patient transitions between primary and oncology care; 2) co-locating a nurse practitioner trained in care coordination within a complex care team; 3) and enhancing teamwork through coaching. Segmented regression analysis will evaluate change in system-level (i.e. composite care quality score) and patient-level outcomes (i.e. self-reported care coordination). To evaluate implementation, we will merge quantitative findings with structured observations and physician and patient interviews. Discussion This study will result in an evaluation toolkit identifying key model elements, barriers, and facilitators that can be used to guide care coordination interventions in other safety-net settings. Because Parkland is a vanguard of safety-net healthcare nationally, findings will be widely applicable as other safety-nets move toward increased integration, enhanced EHR capability, and experience with growing patient diversity. Our proposal recognizes the complexity of interventions and scaffolds evidence-based strategies together to meet the needs of complex patients, systems of care, and service integration. Trial registration ClinicalTrials.gov, NCT02943265. Registered 24 October 2016.

Advancements in high-throughput genotyping and sequencing technologies are enabling the development of a vast range of genomic tools and resources for a new revolution in plant breeding. Several genotyping-by-sequencing (GBS) methods including capture-based, genome complexity reduction and sequencing of cDNA (GBS-t) are available for application in trait dissection, association mapping, and genomic selection (GS) in crop plants. The aims of this study were to identify genomic regions conferring resistance to Ascochyta blight (AB) introgressed from the wild Cicer echinospernum into the domesticated C. arietinum, through a conventional recombinant inbred population genotyped using a variety of GBS methods. Evaluation of GBS methods revealed that capture-based approaches are robust and reproducible while GBS-t is rapid and flexible. A genetic linkage map consisting of 5886 polymorphic loci spanning 717.26 cM was generated. Using field phenotyping data from two years, a single genomic region on LG4 was identified with quantitative trait loci (QTL) mapping. Both GBS methods reported in this study are well suited for applications in genomics assisted plant breeding. Linked markers for AB resistance, identified in the current study, provide an important resource for the deployment into chickpea breeding programs for marker-assisted selection (MAS).

This special section contains extended versions of papers presented at the IEEE International Conference on Multimedia & Expo (ICME) in London, July 2020. The invitations to contribute to the special section were based on the quality of the conference paper and its relevance to the aims and scope of the journal. Each submitted manuscript was reviewed by at least three anonymous reviewers. After a rigorous review process, three papers were accepted. Two of them present new developments in immersive media, while the third deals with the problem of efficiently encoding a deep neural network.