30921 research outputs found
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Expanding the genome editing toolbox in wheat: comparative analysis of CRISPR/MAD7 and CRISPR/Cas9 targeting carotenoid biosynthesis
No full textExpanding the genome editing toolbox in wheat is essential for improving crop traits and addressing intellectual property (IP) limitations associated with conventional CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) systems. This study presents a comparative evaluation of the novel CRISPR/MAD7 (Cas12a-family) and CRISPR/Cas9 gene editing systems in bread wheat (Triticum aestivum L., cv. Fielder), targeting the lycopene ε-cyclase (TaLCYε) gene to enhance provitamin A (β-carotene) biosynthesis. Editing efficiency with MAD7 was highly protospacer adjacent motif (PAM)-dependent, with successful mutagenesis observed only at the canonical TTTG site (26.2% efficiency), whereas CRISPR/Cas9 achieved broader target site compatibility (5.6–42.1% efficiency) across NGG PAMs. Distinct mutation profiles were observed: MAD7 induced mid-sized deletions (6–15 bp), while Cas9 generated diverse indels, including large deletions using dual-sgRNA constructs. Both systems achieved edits in all homoeologous alleles within wheat’s hexaploid genome. The disruption of TaLCYε homoeologs demonstrates the potential for redirecting metabolic flux toward β-carotene accumulation. While CRISPR/Cas9 offers superior efficiency, MAD7 provides an IP-friendly alternative with predictable outcomes and is particularly well suited for AT-rich genomic regions. These findings establish MAD7 as a viable tool for wheat biofortification and broaden the scope of genome editing in cereal crops. This work supports the development of nutritionally enhanced wheat varieties and highlights the strategic importance of platform choice in crop biotechnology.October 202
Application of palaeodermatoglyphic analytical methods to assess age and biological sex of potter(s) from a pre-contact Late Woodland period vessel
No full textThe objectives of this research is the application and critique of analytical methods that have been developed in the dactylographic and dermatoglyphic literature to determine the biological sex and age of the potter(s) involved in the production of a Late Woodland vessel from the boreal forest region in Northwestern Ontario. Age was determined from mean ridge breadth. The modified regression equation used in Fowler et al. (2019) was chosen for this analysis. The comparative data set for the aging model consisted of mean ridge breadth data from Laing (2021). Biological sex determination used mean ridge density. The Acree method, counting ridges in 25mm2 area was used, modified using Gungadin’s (2007) approach as needed; measuring in 6.25 mm2 areas and adjusting. A bespoke model based upon fingerprints from North American Indigenous groups was used to interpret ridge density measurements (Stinson 2004). Measurements were corrected to account for shrinkage of the clay material during the drying and firing process. A shrinkage test was conducted using regional clays. The corrections used were 6% and 12%. The results of this research show that most ridge skin impressions of the vessel were made by an adolescent or adult female. There were two anomalies impressed during the decoration stage of manufacture suggesting a late adolescent or adult male. Despite earlier assumptions that pre-contact Indigenous pottery was made by women (Syms 1977; Taylor-Hollings 2017, p.110; Bales 1997), this analysis show males could have been involved in production. Moreover, this study critiques these methods, identifying issues that can affect the results obtained using the models. Some issues such as shrinkage are already factored into the models. The issue of the effect of curvature on fingerprint impressions, however, is not considered in these analytical models. This research is valuable since it provides insight into past populations where there may be no other means of investigation. This research is further significant since it is the first analysis of pre-contact epidermal prints in this region. Currently, there is no data that can be used to infer the age and sex of potters in pre-contact boreal forest hunter-gatherer societies in Canada.October 202
Evaluating the efficiency of the different resilient overdenture attachments in implant-assisted cast partial dentures
No full textThis study aims to assess the wear resistance of various robust attachments in implant-assisted removable partial overdentures over abutments such as Ball Cap, LOCATOR, and Novaloc. Each of the three attachment groups—Ball Cap (Rhein83), LOCATOR (Preat), and Novaloc (Straumann)—has a sample size of 10 each. The angle at which the attachment would be loaded would be between 0 and 10 degrees. Newton-centimeters (N-cm) of retention would be assessed both before and after 5000 cycles of load application and removal. The subsequent attachment wear will be examined under scanning electron microscope. A patient’s model with missing mandibular posterior teeth were used to design Kennedy class I implant-assisted removable partial denture (IARPD). The implant replica were placed bilaterally in the 1st molar region using manufactures recommendation. The scan bodies were digitally scanned using Prime Scan (Dentsply Sirona) intraoral scanner after hand tightened. Three models were printed, one for each attachment type, and the cast IARPDs were designed on the models. The IARPDs were constructed in the laboratory. The attachments were placed in the IARPDs. The custom-made replica of the testing device was designed using Exocad software. The attachment specimen was observed under scanning electron microscope. The degree of attachment wear was recorded and compared within the group and against the controls for evaluation. There are statistically significant differences in the diameter of the ball cap, Locator and Novaloc attachments. The nylon Ball cap attachment shows significantly more wear after 5000 cycles compared to the nylon Locator and polyetheretherketone (PEEK) Novaloc attachment. Resilient attachments wear differently depending on the type and material after cyclic load is applied on an IARPD.American Academy of Implant DentistryMay 202
Evaluation of soil health indicators in the Red River Valley of Manitoba
No full textThe Comprehensive Assessment of Soil Health (CASH) uses multiple biological, chemical, and physical soil indicators to assess soil health. These indicators were originally selected because they were responsive to management in the northeastern United States. The objective of this research was to determine if the indicators found in the CASH would be responsive to agronomic management on humic vertisols in the Red River Valley of Manitoba. To test this, 14 soil health indicators were used to assess the effect of three different treatments from the National Centre for Livestock and the Environment long-term nutrient management study. In this experiment, the crop history treatment contained an annual crop history or a perennial crop history treatment. The perennial crops had been terminated the growing season prior to soil sample collection. The second treatment was fertility history containing an unfertilized control, a synthetic fertilizer, liquid pig manure applied at the nitrogen rate, and solid dairy manure applied at the nitrogen rate. The fertility treatment had ceased five years prior to sampling. The third treatment was soil management, including soil building management or conventional management. The soil management treatment started the year of sampling for this study. Seven of the 14 soil health indicators tested were responsive to a fertility history treatment. These indicators were total organic carbon, active carbon, autoclave citrate extractable soil protein, potentially mineralizable nitrogen, soil test potassium, Olsen phosphorus, and soil test zinc. Within the soil fertility treatment, the soil with a history of solid dairy manure was the best at increasing soil health indicator values. Four of the soil health indicators were responsive to the cropping system history treatment. These indicators were potentially mineralizable nitrogen, soil respiration, wet aggregate stability, and soil test potassium. Soil with a history of perennial crops increased three of the responsive indicators compared with soil with a history of annual crops. While soil with a history of perennial crops decreased soil test potassium relative to soil with a history of annual crops. None of the soil health indicators were responsive to the land management treatment. However, this was likely due to there only being one year of treatment effect. Future research will need to focus on developing scoring functions that help interpret soil health indicator values.October 202
Genomic characterization of antimicrobial resistance and mobile genetic elements in swine gut bacteria isolated from a Canadian research farm
No full textAbstract Introduction The widespread use of antimicrobials in the livestock industry has raised global concerns regarding the emergence and spread of antimicrobial resistance genes (ARGs). Comprehensive databases of ARGs specific to different farm animal species can greatly improve the surveillance of ARGs within the agri-food sector and beyond. In particular, defining the association of ARGs with mobile genetic elements (MGEs)—the primary agents responsible for the spread and acquisition of resistant phenotypes among bacterial populations—could help assess the transmissibility potential of clinically relevant ARGs. Recognizing the gut microbiota as a vast reservoir of ARGs, we aimed to generate a representative isolate collection and genome database of the swine gut microbiome, enabling high-resolution characterization of ARGs in relation to bacterial host range and their association with MGEs. Results We generated a biobank of bacteria from different sections of the gastrointestinal tracts of four clinically healthy pigs housed at a research farm in Ontario, Canada. The culturing was performed under anaerobic conditions using both selective and general enrichment media to ensure the capture of a diverse range of bacterial families within the swine gut microbiota. We sequenced the genomes of 129 unique isolates encompassing 44 genera and 25 distinct families of the swine gut microbiome. Approximately 85.3% (110 isolates) contained one or more ARGs, with a total of 246 ARGs identified across 38 resistance gene families. Tetracycline and macrolide resistance genes were the most prevalent across different lineages of the swine gut microbiota. Additionally, we observed a wide range of MGEs, including integrative conjugative elements, plasmids, and phages, frequently associated with ARGs, indicating that the swine gut ecosystem is conducive to the horizontal transfer of ARGs. High-throughput alignment of the identified ARG-MGE complexes to large-scale metagenomics datasets of the swine gut microbiome suggests the presence of highly prevalent and conserved resistome sequences across diverse pig populations. Conclusion Our findings reveal a highly diverse and relatively conserved reservoir of ARGs and MGEs within the gut microbiome of pigs. A deeper understanding of the microbial host range and potential transmissibility of prevalent ARGs in the swine microbiome can inform development of targeted antimicrobial resistance surveillance and disease control programs
Prevalence, distribution, and diagnostic testing for Legionella, and growth curves and immune responses of clinical isolates of Legionella: a scoping review and an in-vitro study
No full textBackground: Legionella spp. is an underrecognized etiology of pneumonia, capable of causing severe
disease and occurring more frequently in people living with HIV and over the age of 45. Studies suggest
that non-pneumophila serogroup 1 Legionella is underdiagnosed. Research and diagnostics for species
and serogroups other than Legionella pneumophila serogroup 1 are limited due to reliance on urinary
antigen for diagnostics.
Methods: A scoping review was conducted to evaluate the prevalence and incidence of Legionella
stratified by species and serogroups, and the methods used to detect Legionella. Articles were extracted
from several databases and independently screened by 2 researchers. U937 cells were infected with L.
pneumophila Philadelphia-1 and clinical strains of L. bozemanae, L. dumoffii, L. micdadei, and L.
pneumophila from a tertiary care hospital in Winnipeg, Manitoba. Intracellular growth of Legionella was
evaluated by a colony-forming unit assay (CFU). Cell culture supernatants were evaluated for Eotaxin, FGF-
2, fractalkine, GM-CSF, IFN-α2, IFN-γ, IL-1β, IL-6, IL-8, IL-9, IL-10, IL-12p40, IL-12p70, IL-13, IP-10, MCP-1,
MCP-2, RANTES, TGF-β, and TNF-α.
Results: 31 of 3449 articles met the inclusion criteria for the review. The most common species found
were L. pneumophila, L. longbeachae, and unidentified Legionella species in 1.4%, 0.9%, and 0.6% of total
pneumonia cases. Nearly 50% of Legionnaires’ disease cases are caused by species not detected by first-
line diagnostics. NAT-based techniques were more likely to detect Legionella than non-NAT-based
techniques. U937 cells increased expression of TGF-β when infected with Legionella bozemanae;
decreased GM-CSF when infected with Legionella dumoffii; increased expression of MCP-2 when infected
with Legionella micdadei; decreased expression of FGF-2, GM-CSF, and IL-8 when infected with Legionella
pneumophila; and increased FGF-2 when infected with Legionella pneumophila Phildadelphia-1.
Conclusions: Legionella detection is hampered by a lack of application of broader or pan-Legionella
diagnostics. Our findings provide new insights into differential cytokine responses elicited by Legionella
species, highlighting the need for further research into specific mechanisms involved in the responses.October 202
Development and validation of a self-report scale measuring mental health self-reliance
No full textAbstract
Background and Objectives: Self-reliance is commonly understood as a rigid belief that individuals will manage challenges independently, without seeking or relying on external support and is a leading reason that people do not seek mental health help. Despite its importance, efforts to mitigate the negative impact of self-reliance on mental health service utilization have been limited, partly due to the poor conceptualization of the construct and the absence of a reliable and valid measurement scale. This dissertation addresses these gaps by proposing a multifaceted conceptualization of self-reliance, which was used to create a validated measure: the mental health self-reliance scale (MHSRS).
Methods: Scale development followed a four-step process. The first conceptualization step involved the development of a conceptual model of self-reliance as consisting of three unique expressions, and the second stop focused on developing an initial item pool based on this conceptual model. The third step involved item selection and revision using an exploratory factor analysis (EFA) with a large online community sample (n = 521). Finally, in the fourth psychometric evaluation step, confirmatory factor analysis (CFA) with a new online community sample (n = 242) validated the factor structure and assessed concurrent validity by examining convergent and discriminant relationships with ancillary measures. Also, in the fourth step the temporal stability of the scale over a three-week period was established with a unique sample (n = 62).
Results: The scale development process resulted in a 12-item scale with three factors corresponding to the hypothesized dimensions of headstrong, adaptive, and other-reliance. Results from the exploratory and confirmatory factor analyses demonstrated excellent model fit and strong evidence of internal consistency, temporal reliability, and validity.
Conclusions: The MHSRS provides a psychometrically sound tool highlighting the nuanced nature of self-reliance, distinguishing between adaptive (e.g., flexible autonomy) and maladaptive (e.g., inflexible patterns of overdependence or excessive self-sufficiency) expressions. The scale offers a new approach to understanding how self-reliance impacts mental health management and help-seeking behaviours. The MHSRS can be used by clinicians, researchers, and policymakers to address barriers to mental health service utilization and support uptake and effective participation in mental health treatment.October 202
Accuracy of Bolton anterior and overall ratios on ClinCheck® Software in the crowded dentition
No full textIntroduction:
The purpose of this study is to investigate the reliability of ClinCheck® Software on predicted mesiodistal tooth widths, assess the accuracy of Bolton ratios at 2 time points and whether crowding has any influence on Bolton ratios.
Methods:
Overall and anterior Bolton ratios were calculated for 29 patients with 5 to 8mm of crowding and undergone Invisalign treatment at a private orthodontic clinic in Canada. To evaluate the Bolton ratios, the mesiodistal widths were manually measured using an electronic caliper on 3D printed casts pre-treatment (T1) and at the last refinement scan (T2) as well as via ClinCheck® Software.
Results:
There are statistically significant differences in Bolton ratios between manual measurements and ClinCheck® Software for T1 overall ratio(p<.001), T2 anterior ratio (p<.001) and T2 overall ratio (p=.016, 1% of difference). Manual measurements indicate that crowding does not affect Bolton anterior (p=.172) and overall ratios (p=.938), however ClinCheck® measurements indicate that there are statistically significant differences in the anterior (p=.05) and overall (p<.001) Bolton ratios when crowding is involved (±1%). Tooth width measurements assessed by ClinCheck® Software tends to provide larger tooth widths compared with manual measurements.
Although the overall reliability of tooth width measurements delivered by the ClinCheck® Software was excellent (ICC 0.994) the reliability of the Bolton ratios is uncertain with wide confidence intervals (0.267 – 0.949).
Conclusions:
Tooth width measurements assessed by the ClinCheck® Software are accurate and clinically acceptable when measuring individual teeth, except for first molars in both arches. ClinCheck® Software shows questionable reliability when Bolton ratios are estimated. Crowding does not influence Bolton ratios when calipers are used whereas ClinCheck® indicates there are statistically significant but in all probability not clinically relevant differences in ratios when crowding is present.October 202
Something new under the sun
No full textCharge-transfer emission of any type is extremely rare for coordination complexes of iron. Now, an Fe(III) complex has been devised that shows two-colour luminescence arising from dual metal-to-ligand and ligand-to-metal charge-transfer emission
AI in chemistry: accelerating early-stage drug discovery through the iterative use of machine learning and improved data quality
No full textCurrently, it takes around 2 billion dollars and 15 years to bring a drug to market. The excessive cost and time can be partly attributed to issues within the drug discovery pipeline. This research focuses on speeding up the time it takes to bring a drug to market as well as the associated cost. This is done by applying machine learning methods to early-stage drug discovery to improve hit rates, improve the quality of data, and investigate the size of the dataset needed for training ML models. More specifically, this study investigates the predictive power of ML models in the classification of growth inhibitory activity, colloidal aggregation, and enzyme inhibition. Furthermore, in the case of colloidal aggregation and enzyme inhibition, a subset of ML known as xAI (explainable AI) is utilized to gain insights into how the model makes predictions by having said model explain itself. While it is not yet clear whether this work has directly accelerated the drug discovery pipeline, it has contributed meaningfully to the process. Notable outcomes include: the development of a ML model used in identifying a lead compound, a predictive xAI model for small molecules for identifying and modifying aggregation, and a foundation for an xAI model that predicts enzyme inhibition of small molecules. Additionally, this work has improved data quality and provided insights into the optimal size and balance of training datasets for ML models.October 202