HARVEST

University of Saskatchewan's Repository for Research, Scholarship, and Artistic Work

Welcome to HARVEST, the repository for research, scholarship, and artistic work created by the University of Saskatchewan community. Browse our collections below or find out more and submit your work.

Communities in HARVEST

Select a community to browse its collections.

Now showing 1 - 31 of 31

Recent Submissions

Functional and mechanistic characterization of EphA2 in human and canine melanoma
(2026-07-06) Abdi, Shabnam; Hill, Janet; Viloria-Petit, Alicia; Unniappan, Suraj; Mayer, Monique; Freywald , Andrew; Vizeacoumar, Franco
Melanoma is a highly aggressive malignancy of melanocytes associated with poor clinical outcomes in both humans and dogs. Despite conventional treatments, advanced disease remains difficult to treat, highlighting the need for more effective, biologically informed therapies. Among potential molecular targets, the erythropoietin-producing hepatocellular (Eph) receptor family has gained attention due to its role in tumor progression. In particular, EphA2 has emerged as a promising target in human cancers; however, its role in melanoma, especially in canine models, remains incompletely understood. This thesis addressed this gap using a comparative oncology approach, combining the development of a normal canine melanocyte model with functional and mechanistic analyses of canine and human melanoma cells. First, normal canine melanocyte models were established for comparison with malignant cells. Primary melanocytes were successfully isolated and characterized from canine skin, oral mucosa, and uveal tissues. These cells exhibited dendritic morphology and were validated using melanocyte-specific markers and functional assays. Transmission electron microscopy confirmed melanosome maturation. This work established a normal canine melanocyte model for comparison with malignant cells. EphA2 expression and function were then evaluated in canine and human melanoma cell lines. EphA2 was elevated in melanoma cells compared with normal melanocytes in both species. Silencing of EphA2 reduced cell viability, increased apoptosis, and impaired invasion. It also decreased colony and tumorsphere formation, indicating a role in clonogenic growth and stem-like behavior. Together, these findings demonstrate that EphA2 contributes to key malignant properties of melanoma across species. Finally, EphA2-associated signaling pathways were investigated. EphA2 silencing more clearly reduced extracellular signal-regulated kinase (ERK)-associated signaling in canine melanoma cells, while effects on p38 mitogen-activated protein kinase (p38 MAPK), focal adhesion-associated proteins, nuclear factor kappa B (NF-κB), and stemness-associated factors were cell line-dependent. In contrast, mechanistic target of rapamycin (mTOR) phosphorylation showed reduction or decreasing trends depending on the cell line, despite variable protein kinase B (AKT) responses. These findings support EphA2 as a context-dependent regulator of multiple signaling pathways linked to melanoma aggressiveness. Overall, this thesis identifies EphA2 as a key regulator of melanoma progression and highlights canine melanoma as a valuable comparative model for translational research.
Beyond the Surface: Exploring How Racism, Disconnectedness and Exclusion Shape Faculty Engagement in Continued Professional Development (CPD)
(Springer Nature, 2026) Okpalauwaekwe, Udoka; Holinaty, Carla; Smith-Windsor, Tom; Barton, James; MacLean, Cathy
Introduction Continuing Professional Development (CPD) (which includes Continuing Medical Education (CME) and Faculty Development (FD)) is essential for maintaining physician competency. However, participation in university-organized CPD at the University of Saskatchewan remains low, particularly among racialized physicians. Prior research identified racism, exclusion, and disconnectedness as barriers. This study revisits those findings through the lens of Belongingness and Social Identity Theories to examine how exclusion and identity-based harms shape CPD engagement. Methods We conducted a theory-informed sub-analysis of interview and focus group transcripts (n = 34) with physician faculty across rural and urban Saskatchewan. Participants represented various specialties and backgrounds. Reflexive thematic analysis was used to explore how unmet needs for belonging and identity affirmation influenced CPD participation. Results Three key themes emerged: (1) CPD as a site of racialized othering and professional scrutiny; (2) tokenistic inclusion without recognition or meaningful support; and (3) withdrawal as a form of self-protection. Racialized physicians and International Medical Graduates (IMGs) often disengaged not from disinterest but due to psychological fatigue, identity invalidation, and exclusion. Conclusion CPD participation is shaped by more than topic relevance or logistics, it is profoundly affected by emotional safety, institutional culture, and inclusion. Programs that fail to reflect diverse identities or foster inclusive environments risk reinforcing alienation. CPD must be reimagined as a relational, psychologically safe space. To foster equitable engagement, inclusion and representation must be embedded as foundational design principles, not treated as optional enhancements.
Valorisation of proteins and lipids from flax straw using combinations of microbial fermentation and black soldier fly larvae (Hermetia illucens)
(Brill, 2026-05-26) Golshenas, Parham; Tanaka, Takuji
The recovery of nutrients from underutilised agricultural byproducts offers a sustainable strategy to enhance food and feed production without major changes to existing supply systems. This current study examined the possibilities to use abundant agricultural byproducts, flax straw, to recover nutrients in the form of insect biomass. Flax straw was treated with Aspergillus oryzae-Lactobacillus plantarum or A. niger-Trichoderma koningii with and without autoclave pretreatments. Without the heating treatments, the straw was found a poor feed for the black soldier fly larvae. Their body mass only reached to 25.6 mg per larva in 15 days. Even with A. oryzae-L. plantarum fermentation, where we expected the better growth, the average weight per larva reached only 30.5 mg. These were much smaller compared to what can be achieved using rich feed, such as corn meal-based feeds. Rich feed typically allows a larva grow to 70+ mg after 15 days culture. When the straw was autoclaved, it supported a larvae growth to 34.5 mg. Fermentation of this cooked straw with cellulose-degrading microbes (A. niger and T. koningii) allowed even better growth. BSFL fed with cooked-fermented feed had a larva growing to 47.7 mg where proteins and lipids had 41.5 and 13.2% contents, respectively. The improvement of feed quality by cooking and fermentation is notable, given the inherently low nutrient bioavailability of straw. These results demonstrate the potential of microbial pretreatment and insect bioconversion to valorise underexploited agricultural byproducts within sustainable feed and food production systems.
Detection of Fusarium Damaged Kernels in Wheat Using Deep Semi-Supervised Learning on a Novel WheatSeedBelt Dataset
(IEEE, 2023) Najafian, Kayhan; Jin, Lingling; Kutcher, Randy; Hladun, Mackenzie; Horovatin, Samuel; Oviedo-Ludena, Maria Alejandra; Pereira de Andrade, Sheila Maria; Wang, Lipu; Stavness, Ian
Fusarium head blight, caused by Fusarium spp., is a destructive disease of wheat worldwide. Fusarium damaged kernels (FDKs) significantly reduce grain yield and quality. Thus, FDK detection is a priority for wheat breeders seeking to develop high-grain quality and FDK-resistant wheat cultivars. However, traditional FDK measurement methods are time-consuming, labor-intensive, and of variable accuracy. Image-based phenotyping methods have the potential to efficiently detect FDK, but are challenging to develop due to the lack of large-scale damage-annotated wheat kernel datasets. Addressing this issue, we introduced WheatSeedBelt, a high-resolution large-scale dataset including 40, 420 close-up top- and side-view single-kernel images of 268 wheat varieties with kernel damage annotations. Utilizing this dataset, we developed an image-processing pipeline to efficiently process images and extract the representative features for machine and deep-learning purposes. We also conducted three experiments on the dataset using pretraining and semi-supervised fine-tuning phases to classify wheat kernels into healthy, unhealthy but non-FDK, and FDK affected. Our best models achieved an F1-score of 84.29% for the Healthy-Unhealthy (including FDKs) task, 56.35% for the binary FDK-nonFDK, and 68.30% for the 3-class task (Healthy, Unhealthy, and FDK). We also conducted an interrater reliability study, which indicated that human experts do not outperform our model in FDK prediction, providing evidence that visual classification of FDK from RGB images is a challenging task.
The Costs of Wetland Conservation for Agricultural Producers in the Canadian Prairies
(2026-07-02) Xuan, Oliver; Lloyd-smith, Patrick; Belcher, Kenneth W.; Weegman, Mitch; Zapata, Oscar
Wetland extent in the Prairie Pothole Region of North America has continued to decline, largely due to conversion to agricultural production. This thesis investigates the preferences and decisions of agricultural producers regarding wetlands on their fields to understand the factors influencing these decisions. Using a stated preference survey of land rental decisions in Alberta, Saskatchewan, and Manitoba, the study estimates the costs of conserving wetlands on crop land. These conservation costs increase with the number of wetlands and producers are generally averse to more centrally located wetlands on their fields. The findings also reveal substantial heterogeneity in these costs related to farm operation and respondent characteristics. These insights inform policymakers about wetland costs to improve the effectiveness of conservation efforts in Canada.
Privacy-Preserving Multimodal News Recommendation through Federated Learning
(IEEE, 2026) Khalaj, Mehdi; Najafabadi, Shahrzad Golestani; Vassileva, Julita
Personalized News Recommendation systems (PNR) have emerged as a solution to information overload by predicting and suggesting news items tailored to individual user interests. However, traditional PNR systems face several challenges, including an overreliance on textual content, common neglect of short-term user interests, and significant privacy concerns due to centralized data storage. This paper addresses these issues by introducing a novel multimodal federated learning-based approach for news recommendation. First, it integrates both textual and visual features of news items using a multimodal model, enabling a more comprehensive representation of content. Second, it employs a time-aware model that balances users’ longterm and short-term interests through multi-head self-attention networks, improving recommendation accuracy. Finally, to enhance privacy, a federated learning framework is implemented, enabling collaborative model training without sharing user data. The framework divides the recommendation model into a large server-maintained news model and a lightweight user model shared between the server and clients. The client requests news representations (vectors) and a user model from the central server, then computes gradients with user local data, and finally sends their locally computed gradients to the server for aggregation. The central server aggregates gradients to update the global user model and news model. The updated news model is further used to infer news representation by the server. To further safeguard user privacy, a secure aggregation algorithm based on Shamir’s secret sharing is employed. Experiments on a realworld news dataset demonstrate strong performance compared to existing systems, representing a significant advancement in privacy-preserving personalized news recommendation.
Effectiveness of washing procedures for removing Brucella abortus from in vivo- and in vitro-derived wood bison embryos
(Elsevier, 2026) Cervantes, Miriam P.; Palomino, J. Manuel; Anzar, Muhammad; Allan, Brenda J.; Mastromonaco, Gabriela; Adams, Gregg Patrick
Washing procedures for zona pellucida (ZP)–intact bovine embryos have been developed to enable international movement of pathogen-free embryos. We evaluated the effectiveness of a washing procedure to remove Brucella abortus from in vivo– and in vitro–produced bison embryos exposed to the pathogen in vitro. In Experiment 1, ZP-intact embryos from superovulated bison were incubated with B. abortus biovar 1 (1.9 × 10⁵ to 3.8 × 10⁸ CFU/mL) for 2 h at 37ºC. Embryos underwent a 10-step wash using medium (PBS + 0.4% BSA) with or without antibiotics (penicillin and streptomycin). Medium samples were cultured after washes 1, 3, 6, and 9, and embryos were individually cultured on blood agar after the final wash. B. abortus was not detected in samples after the third wash in either group. PCR detected B. abortus in 2/27 embryos washed without antibiotics, but in none of those washed with antibiotics (0/27). In Experiment 2, cumulus-oocyte complexes were collected from superstimulated bison 34 h after hCG treatment, fertilized in vitro immediately, and cultured for 7 days. ZP-intact embryos were exposed to B. abortus and washed as in Experiment 1. B. abortus was not detected in samples after wash 3, and all embryos were culture-negative (0/84). In summary, B. abortus was detected only in in vivo-derived embryos washed without antibiotics (2/27), whereas no positives were observed in embryos washed with antibiotics or in vitro-derived embryos. Washing effectively removed B. abortus from in vivo- and in vitro-derived wood bison embryos, but disease-free calf production remains unconfirmed.
The effects of loading direction on the dynamic impact response of additively manufactured M350 maraging steel-Al0.5CoCrFeNi1.5 hybrid plates
(Elsevier, 2025) ODIAKA, TIMOTHY; Asala, G.; Ola, O. T.; Ojo, O. A.; Oguocha, I. N. A.; Odeshi, A. G.
Despite the impressive impact strength of maraging steels, which informs their application in the defence industry, they are highly susceptible to cracking resulting from adiabatic shear band (ASB) nucleation when subjected to dynamic loading. Hence, a potential solution to mitigate this problem is needed. In this study, a hybrid plate containing layers of M350 maraging steel and Al0.5CoCrFeNi1.5 high entropy alloy was fabricated using laser-based directed energy deposition (L-DED) additive manufacturing with the aim of combining the high impact strength of M350 maraging steel with the ductility and ASB-resistant properties of Al0.5CoCrFeNi1.5. To determine the effect of loading direction on the impact strength and absorbed energy of the hybrid specimens, cylindrical specimens, with the layers oriented longitudinally and transversely to the cylinder's axis, were cut out of the hybrid plate. High-strain rate testing was performed using an instrumented split-Hopkinson pressure bar (SHPB) to determine the dynamic mechanical response of the specimens. Statistical analyses of the results using generalised additive models (GAM) showed that layer orientation with respect to the direction of impact significantly affects the hybrid specimens' impact strength and absorbed energy. The longitudinally oriented specimens demonstrated superior impact strength across all tested impact momenta. However, the transversely oriented specimens showed higher absorbed energy up to an impact momentum of 32.8 kg ms−1. The Al0.5CoCrFeNi1.5 layer contributed significantly to energy absorption, strain hardening, and the inhibition of ASB propagation in the hybrid specimens.
Dynamic impact response of additively manufactured monolithic and hybrid armour materials
(Elsevier, 2026) ODIAKA, TIMOTHY; Asala, G.; Ola, O. T.; Ojo, O. A.; Oguocha, I. N. A.; Odeshi, A. G.
Although M350 maraging steel is widely used for defence, automotive, medical and aerospace applications due to its exceptional strength and toughness, it is susceptible to cracking in high strain rate conditions. To address this limitation, a novel hybrid plate was fabricated using laser-based directed energy deposition (DED) additive manufacturing by combining layers of M350 maraging steel and Al0.5CoCrFeNi1.5 high-entropy alloy (HEA). Then, its dynamic impact response was compared with those of the constituting monolithic alloys. Samples of the monolithic and hybrid materials were heat-treated. M350 maraging steel and the hybrid specimens were austenitized at 850 °C for 0.5 h, water-quenched, and artificially aged at 535 °C for 0.5 h, while the monolithic Al0.5CoCrFeNi1.5 HEA was normalized at 700 °C for 1.5 h and air cooled to room temperature. Both heat-treated and as-built materials were subjected to dynamic impact tests at impact momenta that varied from 24.3 to 47.6 kg.ms⁻¹ using an instrumented split Hopkinson pressure bar (SHPB). The heat-treated hybrid specimens demonstrated impressive energy absorption capability, outperforming their monolithic M350 maraging steel counterparts by 46.6 % and 59.4 % at impact momenta of 32.8 kg.ms−1 and 38.8 kg.ms−1 respectively. These heat-treated hybrid specimens survived testing up to 43.8 kg.ms−1, while their monolithic M350 maraging steel counterparts began to fracture at 38.8 kg.ms−1. Microstructural analyses revealed that transformed adiabatic shear bands formed more readily in monolithic M350 maraging steel than in the hybrid specimens leading to early catastrophic failure. These findings demonstrate a new strategy for mitigating the cracking propensity of maraging steel in defense applications through additive manufacturing of hybrid maraging steel-HEA structures.
Sensitivity of Large-Scale Hydrological Predictions to Precipitation Phase Partitioning Methods Under a Changing Climate
(Wiley, 2026) Yassin, Dr. Fuad; Pomeroy, John W.; Pietroniro, Alain; Davison, Bruce; Elshamy, Mohamed; Tesemma, Zelalem
Accurate partitioning of precipitation into rain and snow remains a major source of uncertainty in hydrological projections for cold regions. This study quantifies how four precipitation phase-partitioning formulations influence simulated precipitation phase, snow storage and streamflow response in the Saskatchewan River Basin under historical (1981–2010) and late-century (2071–2100) climate conditions. Simulations were conducted under naturalised conditions, with all reservoir regulation, irrigation and water-management abstractions deactivated to isolate the effect of phase-partitioning choice, using the MESH land-surface hydroloical model forced with CanRCM4 climate projections spanning 1950 to 2100. Three empirical temperature-based methods (single-threshold, linear-transition and polynomial) and one physically based psychrometric formulation were evaluated using diagnostic variables including total precipitation, snow and rain fractions, annual maximum snow water equivalent (SWE), runoff, peak discharge and streamflow timing metrics. Late-century projections showed increases in total precipitation of 19%–30% and declines in snowfall fraction of 25%–34% across landforms. Reductions in annual maximum SWE ranged from approximately 5%–13% in the cordillera and foothills to 13%–19% in the plains. Inter-method spreads in projected SWE were small in colder landforms (< 4 percentage points) but reached 6–9 percentage points in the plains and lowlands, comparable in magnitude to the projected climate-change signal. Streamflow timing advanced consistently: spring pulse onset date advanced by a median of 27 days, centre-of-mass timing by 22 days and time to peak flow by 26 days. Peak discharge increased by a median of 12.6% and annual streamflow volume by 23.9%. Inter-method differences were smallest for spring onset and centre-of-mass timing (1–3 days) and largest for time to peak flow and peak discharge, with mean absolute deviations exceeding 10 days and 14 percentage points respectively under some empirical methods. Snowfall-fraction biases between empirical and physical methods were spatially structured, with time of emergence occurring as early as 1952 for the single-threshold and linear-transition methods and several decades later for the polynomial method. The physically based psychrometric formulation remained consistent across historical and future climates, whereas empirical temperature-threshold schemes exhibited systematic biases and increasing divergence under stronger warming. These findings highlight the importance of explicitly accounting for precipitation phase-partitioning uncertainty in climate-impact assessments for snow-dominated and mixed-regime river basins.