https://repository.monashhealth.org/monashhealthjspui/handle/1/26410 Browse research outputs according to type. Fri, 14 Aug 2026 21:20:15 GMT 2026-08-14T21:20:15Z https://repository.monashhealth.org/monashhealthjspui/handle/1/60578 Title: Cross-Dataset Transcriptomic Analysis Identifies Oxidative Stress-Inflammation Gene Networks Modulated by Nutrigenomic Interventions in Parkinson's Disease. Authors: Rafiee M.; Abaj F.; Ghiasvand R. Abstract: Inflammation and oxidative stress (OS) are key to Parkinson's disease (PD). We performed a cross-dataset integrative transcriptomic analysis to identify OS- and inflammation-related hub genes consistently dysregulated in PD and to explore gene-compound relationships using nutrigenomic studies using publicly available datasets. Four GEO datasets (GSE7621, GSE20141, GSE20146, GSE49036) were analysed to identify differentially expressed genes (DEGs), which were intersected with GeneCards OS-inflammation gene sets. Functional enrichment analyses, including gene ontology (GO), pathway over-representation analysis (ORA), and protein-protein interaction (PPI) analysis, were used to identify key pathways and hub genes. Gene-food bioactive compound (FBC) association was explored by integrating PD signatures with nutrigenomic profiles from NutriGenomeDB. We identified 183 DEGs in PD, enriched in synaptic, dopaminergic, OS, and inflammatory pathways. Intersection analysis yielded 26 OS-inflammation-related genes and 10 central regulators, including TH, DDC, SNCA, LRRK2, HSPB1, and HSPA1B. Integration with nutrigenomic datasets revealed opposing-direction transcriptional patterns, with several FBC-associated signatures showing lower expression of stress-related genes and higher expression of dopaminergic markers such as TH, GCH1, and DDC. Overall, this integrative analysis highlights OS-inflammation gene networks in PD and identifies candidate diet-gene associations that warrant further experimental and clinical validation.Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. Tue, 28 Jul 2026 00:00:00 GMT https://repository.monashhealth.org/monashhealthjspui/handle/1/60578 2026-07-28T00:00:00Z https://repository.monashhealth.org/monashhealthjspui/handle/1/60577 Title: Mapping immune cellular landscapes and vaccine responses across a spectrum of health and immunodeficiency. Authors: Vespasiani D.; Quig A.; Lancaster J.; Shen C.Y.; Cooper J.; Tuong Z.K.; Jackson A.; Schulz S.; Tsang S.-Y.; Deckert K.; Lucas E.C.; Margetts M.; Horton M.; Chan S.; Bosco J.J.; Chatelier J.; Ojaimi S.; Slade C.; Jin C.; King H.W. Abstract: Immune responses to infection and vaccination exhibit diversity between individuals that can be shaped by differences in their immune cell landscapes and the signalling, transcriptional, and genetic mechanisms that coordinate immune cell function. Specific antibody deficiency (SAD) and common variable immunodeficiency (CVID) are common forms of predominantly antibody deficiencies that result in poor responses to vaccination. While molecular and cellular causes of the immune dysfunction and poor vaccination responses for individuals with CVID have been reported, immune cell or molecular defects have not yet been identified in SAD. Here, we have used single-cell multi-omics to define the cellular landscapes, transcriptional states, adaptive immune repertoires and protein expression of patients with SAD and CVID before and after polysaccharide vaccination. We discovered that while SAD and CVID exhibit overlapping immune defects, including accumulation of exhausted NK memory cells and dysregulated expression of genes that mediate lipopolysaccharide sensing and clearance by monocytes, individuals with SAD have a unique expansion of cytotoxic CD4+ T cells that correlates with reduced regulatory T cells. In response to vaccination, we observed rapid changes in gene expression associated with lipopolysaccharide responses by monocytes and NF-kB pathway activation in B cells, and an apparent expansion of a CD95+ class-switched memory B cell population that does not occur in patients with lower antigen-specific responses. Together, our findings reveal cellular and molecular factors that underpin variability in vaccine responses and define SAD in a broader spectrum of immune dysfunction.Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license. Thu, 30 Jul 2026 00:00:00 GMT https://repository.monashhealth.org/monashhealthjspui/handle/1/60577 2026-07-30T00:00:00Z https://repository.monashhealth.org/monashhealthjspui/handle/1/60574 Title: Extrinsic airway compression: an unusual presentation of thoracic vertebral osteophytes from osteoarthritis. Authors: Al Balushi A.; MacDonald M.I.; Friesen B. Abstract: Extrinsic airway compression secondary to vertebral osteophytes is a rare clinical entity. We report a case of an elderly patient presenting with pneumonia where a subsequent chest CT scan showed right main bronchus compression caused by lower thoracic vertebral osteoarthritis-related osteophytes. There were additional incidental findings of sclerotic skeletal lesions prompting a new diagnosis of metastatic prostate cancer. The pneumonia improved with antibiotic therapy. Interventional management of airway compression was not pursued in this patient given his poor functional state and advanced metastatic malignancy. The patient was later readmitted with recurrent pneumonia as expected. Clinicians should be aware of this rare entity as a potential cause of airway compression identifiable on CT chest.Copyright © BMJ Publishing Group Limited 2026. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ Group. Mon, 27 Jul 2026 00:00:00 GMT https://repository.monashhealth.org/monashhealthjspui/handle/1/60574 2026-07-27T00:00:00Z https://repository.monashhealth.org/monashhealthjspui/handle/1/60576 Title: Machine learning-enabled behavioural and psychological symptoms of dementia management intervention for dementia caregivers: protocol for a hybrid factorial SMART-MRT trial. Authors: Cheung D.S.K.; Kor P.P.K.; Chu A.M.Y.; Xie H.; Qian M.; Chu L.W.; Zarit S.; Chou K.L. Abstract: BACKGROUND: Behavioural and psychological symptoms of dementia (BPSD) affect over 90% of people living with dementia and are a major contributor to stress and adverse health outcomes among family caregivers. Caregiver-led behavioural management interventions based on the Antecedents-Behaviour-Consequences (ABC) framework are effective, yet their overall impact is modest. This may be due to the highly individualised and fluctuating nature of BPSD and insufficient adaptive support to sustain engagement. Mobile health interventions offer scalable support; however, engagement and adherence remain challenging. Recent advances in adaptive trial designs and machine-learning methods offer opportunities to optimise interventions and deliver personalised just-in-time support. METHOD(S): This hybrid experimental trial integrates a five-arm randomised controlled trial (RCT), a two-stage sequential multiple assignment randomised Trial (SMART), and three embedded micro-randomised trials (MRTs). A total of 550 family caregivers of community-dwelling people with dementia will be recruited and randomised to one of five conditions: (1) BPSD management intervention with combined human- and app-based coaching; (2) human coaching only; (3) app-based coaching only; (4) no coaching; or (5) psychoeducation control. The intervention includes telephone-based psychoeducation and BPSD management training followed by app-based support. Participants with inadequate engagement after six weeks will be re-randomised to intensified human coaching or a booster session in the next four weeks. MRTs will be conducted to evaluate the proximal effects of push-notification timing, personalised motivational messages, and symptom-specific guidance on engagement. The primary outcome measure is caregiver stress. Secondary outcome measures include caregiver burden, psychological well-being, anxiety, depression, sleep quality, health-related quality of life, caregiving self-efficacy, and severity of BPSD in care recipients. Linear mixed-effects models will be used to evaluate intervention effectiveness, coaching strategies, and adaptive sequences. MRT data will be analysed using weighted regression methods to estimate time-varying causal effects of just-in-time intervention components on next-day engagement. Supervised machine-learning models (e.g., random forests, support vector machines), reinforcement learning, including contextual multi-armed bandit approaches, will be trained to predict caregiver receptivity and optimise notification timing, frequency, and content. DISCUSSION(S): This study design will inform the development of scalable, personalised interventions for dementia caregivers that are feasible for real-world implementation. TRIAL REGISTRATION: This study is registered at the ClinicalTrial.gov Registry on 25 Feb 2026 (NCT07444866).Copyright © 2026. The Author(s). Mon, 27 Jul 2026 00:00:00 GMT https://repository.monashhealth.org/monashhealthjspui/handle/1/60576 2026-07-27T00:00:00Z