19683 research outputs found
Sort by
Development of Planning-Stage Crash Prediction Tools
No full textA thesis submitted in total fulfilment of the requirements for the degree of Master of Engineering to the School of Computing, Engineering and Mathematical Sciences, La Trobe University, Victoria, Australia.</p
FITT Odyssey: A Scoping Review of Exercise Programs for Managing Rotator Cuff Related Shoulder Pain
No full textOBJECTIVE: To summarize the FITT (frequency, intensity, time, type), components of exercise programs included in randomized controlled trials (RCTs) that compared 2 or more programs for managing rotator cuff–related shoulder pain (RCRSP). DESIGN: Scoping review. LITERATURE SEARCH: Electronic searches were conducted up to May 2023. STUDY SELECTION CRITERIA: RCTs comparing the effects of 2 or more types of exercise programs, differing in prescription according to the FITT principle, in people with RCRSP. DATA SYNTHESIS: We extracted data from each trial report so that we could answer items 1 to 10 and 13 to 15 from the Consensus on Exercise Reporting Template (CERT). Descriptive analysis of the exercise programs was performed by summarizing and presenting the FITT characteristics, and other relevant CERT characteristics (material, provider, delivery, tailoring). RESULTS: FITT characteristics from 46 exercise programs included in 22 trials were extracted. The exercise programs were divided into 4 categories (defined in accordance to the original authors’ description and proposed rationale): motor control (n = 8), scapula-focused (n = 7), eccentric (n = 8), and nonspecific exercise programs (n = 28). Five programs were allocated to 2 different categories. The different program types had similar parameters. Exercise programs frequency ranged from 2 to 7 times per week, dose ranged from 1 to 3 sets and 4 to 30 repetitions per sets, and exercise program duration ranged from 4 to 16 weeks. CONCLUSION: There was considerable variability in the parameters used to prescribe exercises for RCRSP. Clinicians seeking guidance on FITT parameters derived from trials should do so cautiously because there was no one-size-fits-all approach. </p
Bacterial community shifts occur primarily through rhizosphere expansion in response to subsoil amendments
No full textTo comprehensively evaluate the impact of agricultural management practices on soil productivity, it is imperative to conduct a thorough analysis of soil bacterial ecology. Deep-banding nutrient-rich amendments is a soil management practice that aims to improve plant growth and soil structure by addressing the plant-growth constraints posed by dense-clay subsoils. However, the response of bacterial communities to deep-banded amendments has not been thoroughly studied. To address this knowledge gap, we conducted a controlled-environment column experiment to examine the effects of different types of soil amendments (poultry litter, wheat straw + chemical fertiliser and chemical fertiliser alone) on bacterial taxonomic composition in simulated dense-clay subsoils. We evaluated the bacterial taxonomic and ecological group composition in soils beside and below the amendment using 16S rRNA amplicon sequencing and robust statistical methods. Our results indicate that deep-banded amendments alter bacterial communities through direct and indirect mechanisms. All amendments directly facilitated a shift in bacterial communities in the absence of growing wheat. However, a combination of amendments with growing wheat led to a more pronounced bacterial community shift which was distinct from and eclipsed the direct impact of the amendments and plants alone. This indirect mechanism was evidenced to be mediated primarily by plant growth and hypothesised to result from an enhancement in wheat root distribution, density and rhizodeposition changes. Therefore, we propose that subsoil amendments regardless of type facilitated an expansion in the rhizosphere which engineered a substantial plant-mediated bacterial community response within the simulated dense-clay subsoils. Overall, our findings highlight the importance of considering the complex and synergistic interactions between soil physicochemical properties, plant growth and bacterial communities when assessing agricultural management strategies for improving soil and plant productivity.</p
Changes in the extractability and fractionation of cadmium and copper in a contaminated soil amended with various sugarcane bagasse-based materials
No full textHeavy-metal contamination in soil has long been a persistent challenge and the utilization of agricultural waste for in-situ stabilization remediation presents a promising approach to tackle this problem. Agricultural wastes exhibit promising potential in the remediation of contaminated land and modification could improve the adsorption performance markedly. Citric acid and Fe3O4 treated sugarcane bagasse adsorbed more heavy metals than raw materials in the aqueous system, employing these materials for heavy metal remediation in soil holds significant implications for broadening the raw material source of passivators and enhancing waste utilization efficiency. In this paper, a 120-day soil incubation study was conducted to compare the effects of pristine sugarcane bagasse (SB), citric-acid modified (SSB1, SSB2 and SSB3 with increasing proportion of citric acid) and citric-acid/Fe3O4 modified (MSB1, MSB4 and MSB7 with increasing proportion of Fe3O4) sugarcane bagasse at 1 % addition rate on cadmium (Cd) and copper (Cu) passivation. The SB, SSB1 and MSB1 did not always decrease the content of CaCl2-extractable Cd while all the seven amendments decreased the CaCl2-extractable Cu during the experiment period. Among all materials, SSB3 and MSB7 exhibited the highest efficiency in reducing the concentrations of CaCl2-extractable Cd and Cu. At Day 120, SB, SSB3 and MSB7 reduced the content of CaCl2-extractable Cd by 8 %, 18 % and 24 %, and of CaCl2-extractable Cu by 25 %, 50 % and 61 %, respectively. The efficiency of Cd and Cu immobilization was associated positively with the pH, functional groups and H-bonds of the amendments. The results suggest that the efficiency of sugarcane bagasse in heavy-metal passivation can be largely enhanced through chemical modifications using high proportions of citric acid and Fe3O4.</p
Adventures in the multiverse: a collective experience of pracademia
No full textNo description supplied</p
Guardians or Villains? Decoding the Dynamic Duo of p53 and BCL-2 Proteins in HCCs
No full textA thesis submitted in total fulfilment of the requirements for the degree of Master of Science to the La Trobe Rural Health School, La Trobe University, Victoria, Australia.</p
Brain volumes in genetic syndromes associated with mTOR dysregulation: a systematic review and meta-analysis
No full textNo description supplied</p
Educator and Student Reflections on Supervising and Conducting Biochemistry Education-based Research
No full texthttps://cdn.wsm.com.au/ASBMB/ASBMB-AB-2024-Vol-55-Number-2-August-High-Res.pdf</p
Indigenous participation in the Canadian Armed Forces: Efforts towards Reconciliation?
No full textNo description supplied</p
Artificial Intelligence in Cancer Immunotherapy: Navigating Challenges and Unlocking Opportunities
No full textCancer continues to be a major cause of global mortality rates, with conventional treatments such as chemotherapy and radiotherapy exhibiting inconsistent efficacy, high costs, and considerable side effects. Over the past decade, a promising alternative has emerged: cancer immunotherapy, which leverages the body’s immune system to identify and eradicate cancer cells [1]. Significant progress has been made in several novel immunotherapies, including immune checkpoint inhibitors (ICIs), chimeric antigen receptor T-cell therapies, and personalized therapeutic cancer vaccines. However, the heterogeneity and complexity of cancer types still pose enormous challenges. The efficient use of large numbers of medical datasets is essential for overcoming these obstacles. Without artificial intelligence (AI), linking translational and clinical data to derive meaningful insights would remain an insurmountable task. Recently, single-cell RNA sequencing cell typing (scGPT), a pretrained generative model utilizing a database of more than 33 million cells, is developed to accurately extract important biological insights concerning cellular biology [2]. A personalized learning workflow is also proposed as a simple and effective pipeline to discover neoantigens for cancer immunotherapy [3].</p