Unravelling Resistance Mechanisms in Philadelphia Positive Leukemias: Targeted Treatment Strategies to Overcome Resistance

The advent of Tyrosine Kinase Inhibitors (TKIs) has significantly improved the survival outcomes of Philadelphia-positive (Ph+) leukaemias, including Chronic Myeloid Leukaemia (CML) and Ph+ Acute Lymphoblastic Leukaemia (ALL). However, the development of TKI resistance remains a major challenge, particularly in cases where mutations other than in BCR::ABL1 are involved. Cancer-associated gene mutations, such as those in Protein tyrosine phosphatase non-receptor type-11 (PTPN11), are frequently found in patients with poor prognosis, but their role in mechanisms of resistance is poorly understood. In this study, I investigated the role of two PTP domain PTPN11 mutations (p.A461T and p.P491H) in cell line models of Ph+ ALL. I modelled these mutations in multiple cell lines and demonstrated that they directly lead to TKI resistance. I also showed that Ph+ ALL cell lines with PTPN11 mutations were resistant to venetoclax, a BCL-2 inhibitor. I found that genetically knocking down PTPN11 could sensitize cells to both TKIs and venetoclax. Furthermore, I demonstrated a novel mechanism of TKI resistance involving reactivation of pBCR-Y177 part of BCR::ABL1 and overexpression of pERK1/2 and antiapoptotic protein BCL-XL. This study is the first to show BCR::ABL1 dependent mechanisms of resistance driven by non-BCR::ABL1 mutations. I investigated potential therapeutic options and demonstrated that targeting the antiapoptotic proteins BCL-2 and MCL-1 could overcome resistance in Ph+ ALL cells with PTP domain PTPN11 mutations. Inhibition of MCL-1 in these cells could also be achieved by blocking BCR::ABL1 activation, which also overcame resistance when combined with venetoclax. This discovery of a new precision medicine approach could be a promising treatment option for Ph+ ALL patients carrying PTP domain PTPN11 mutations. I also investigated targeting MEK, an upstream molecule of ERK in MAPK pathway, with its inhibitor to overcome resistance, but its clinical translation may be limited due to its significant side effects. Before testing this combination treatment option for Ph+ ALL patients in clinical trials, future work should test this treatment option in mouse models. In conclusion, this study not only provides a promising treatment option for Ph+ ALL patients carrying PTPN11 mutations, but also adds knowledge in understanding the function of the poorly understood SHP-2 protein and implications when mutations are acquired in the PTP domain. The knowledge from this study could also be used in understanding the mechanisms of poor response and resistance in Ph- leukaemias such as JMML, AML and MDS where PTPN11 mutations are highly prevalent, and patients have very limited treatment options.Thesis (Ph.D.) -- University of Adelaide, Adelaide Medical School, 202

Imaging Individual Differences in the Response of the Human Suprachiasmatic Area to Light

Circadian disruption is associated with poor health outcomes, including sleep and mood disorders. The suprachiasmatic nucleus (SCN) of the anterior hypothalamus acts as the master biological clock in mammals, regulating circadian rhythms throughout the body. The clock is synchronized to the day/night cycle via retinal light exposure. The BOLD-fMRI response of the human suprachiasmatic area to light has been shown to be greater in the night than in the day, consistent with the known sensitivity of the clock to light at night. Whether the BOLD-fMRI response of the human suprachiasmatic area to light is related to a functional outcome has not been demonstrated. In a pilot study (n = 10), we investigated suprachiasmatic area activation in response to light in a 30 s block-paradigm of lights on (100 lux) and lights off (< 1 lux) using the BOLD-fMRI response, compared to each participant's melatonin suppression response to moderate indoor light (100 lux). We found a significant correlation between activation in the suprachiasmatic area in response to light in the scanner and melatonin suppression, with increased melatonin suppression being associated with increased suprachiasmatic area activation in response to the same light level. These preliminary findings are a first step toward using imaging techniques to measure individual differences in circadian light sensitivity, a measure that may have clinical relevance in understanding vulnerability in disorders that are influenced by circadian disruption

Sensors and Systems for Monitoring Mental Fatigue: A systematic review

Mental fatigue is a leading cause of motor vehicle accidents, medical errors, loss of workplace productivity, and student disengagements in e-learning environment. Development of sensors and systems that can reliably track mental fatigue can prevent accidents, reduce errors, and help increase workplace productivity. This review provides a critical summary of theoretical models of mental fatigue, a description of key enabling sensor technologies, and a systematic review of recent studies using biosensor-based systems for tracking mental fatigue in humans. We conducted a systematic search and review of recent literature which focused on detection and tracking of mental fatigue in humans. The search yielded 57 studies (N=1082), majority of which used electroencephalography (EEG) based sensors for tracking mental fatigue. We found that EEG-based sensors can provide a moderate to good sensitivity for fatigue detection. Notably, we found no incremental benefit of using high-density EEG sensors for application in mental fatigue detection. Given the findings, we provide a critical discussion on the integration of wearable EEG and ambient sensors in the context of achieving real-world monitoring. Future work required to advance and adapt the technologies toward widespread deployment of wearable sensors and systems for fatigue monitoring in semi-autonomous and autonomous industries is examined.Comment: 19 Pages, 3 Figure

Analysis of KatG Ser315Thr Mutation in Multidrug Resistant Mycobacterium tuberculosis and SLC11A1 Polymorphism in Multidrug Resistance Tuberculosis in Central Development Region of Nepal Using PCR-RFLP Technique: A Pilot Study

Ser315Thr mutations in genes encoding the mycobacteria catalase-peroxidase (KatG) has been associated with the major resistance to isoniazid (INH) in Mycobacterium tuberculosis (MTB). Also G/C polymorphisms in INT4 region of the solute carrier family 11 member 1 gene (SLC11A1) and susceptibility towards tuberculosis (TB) has been demonstrated worldwide. 24 drug resistant MTB culture positive samples and 24 whole?blood samples were collected from different TB patients of Central Development Region of Nepal in 2009. A Polymerase Chain Reaction (PCR) - Restriction Fragment Length Polymorphism (RFLP) assay was carried out in order to investigate Ser315Thr KatG mutation and G/C polymorphism in INT4 region. 4 (16.67%) samples out of 24 MTB culture samples demonstrated the Ser315Thr KatG mutation whereas none of the 24 whole blood samples were found to contain G/C polymorphism in INT4. Though no significant correlation could be found between INT4 polymorphism and TB susceptibility, overall scenario of Nepal cannot be drawn from this data. Molecular diagnostic technique such as PCR-RFLP can be used in a robust scale to carry out base line studies in the TB population of Nepal. Key words: Multi?drug resistance; Tuberculosis; PCR; RFLP Nepal Journal of Biotechnology. Jan. 2011, Vol. 1, No. 1 : 14-2

"Schöne Welt, du gingst in Fransen!" : Auf der Suche nach dem authentischen deutschen Tango

Voluntary motor deficits are a common feature in Huntington's disease (HD), characterised by movement slowing and performance inaccuracies. This deficit may be exacerbated when visual cues are restricted.To characterize the upper limb motor profile in HD with various levels of difficulty, with and without visual targets.Nine premanifest HD (pre-HD), nine early symptomatic HD (symp-HD) and nine matched controls completed a motor task incorporating Fitts' law, a model of human movement enabling the quantification of movement timing, via the manipulation of task difficulty (i.e., target size, and distance between targets). The task required participants to make reciprocal movements under cued and blind conditions. Dwell times (time stationary between movements), speed, accuracy and variability of movements were compared between groups.Symp-HD showed significantly prolonged and less consistent movement times, compared with controls and pre-HD. Furthermore, movement planning and online control were significantly impaired in symp-HD, compared with controls and pre-HD, evidenced by prolonged dwell times and deceleration times. Speed and accuracy were comparable across groups, suggesting that group differences observed in movement time, variability, dwell time and deceleration time were evident over and above simple performance measures. The presence of cues resulted in greater movement time variability in symp-HD, compared with pre-HD and controls, suggesting that the deficit in movement consistency manifested only in response to targeted movements.Collectively, these findings provide evidence of a deficiency in both motor planning, particularly in relation to movement timing and online control, which became exacerbated as a function of task difficulty during symp-HD stages. These variables may provide a more sensitive measure of motor dysfunction than speed and/or accuracy alone in symp-HD

Associations of neighbourhood environmental attributes and socio-economic status with health-related quality of life in urban mid-aged and older adults : Mediation by physical activity and sedentary behaviour

This study examined the associations of objectively assessed physical features of the neighbourhood environment with physical and mental aspects of health-related quality of life (HRQoL) as measured by the SF-36, and the roles of physical activity and sedentary behaviour in these associations. We used data from a national sample of Australian mid-aged and older adults living in urban areas (N = 4141). Environmental attributes were computed for 1-km-radius areas surrounding participants' residential addresses. Neighbourhood socio-economic status (SES) and average annual concentrations of PM2.5 were the only attributes related to HRQoL in the expected direction in the total- and direct-effect regression models. All other environmental attributes were related to HRQoL via physical activity behaviours and leisure-time sitting. The associations of most environmental features with HRQoL mediated by physical activity and sedentary behaviours were inconsistent, positive through some pathways and negative through others. This study suggests that neighbourhood SES may in part benefit HRQoL by helping promote an active lifestyle. Neighbourhood attributes defining walkability may benefit HRQoL by providing opportunities for walking and resistance training and, through these, by helping reduce leisure-time sitting. However, the same attributes also may limit opportunities for household activities and gardening and negatively impact on HRQoL through these pathways

Machine Learning for Prediction of Cognitive Health in Adults Using Sociodemographic, Neighbourhood Environmental, and Lifestyle Factors

The environment we live in, and our lifestyle within this environment, can shape our cognitive health. We investigated whether sociodemographic, neighbourhood environment, and lifestyle variables can be used to predict cognitive health status in adults. Cross-sectional data from the AusDiab3 study, an Australian cohort study of adults (34–97 years) (n = 4141) was used. Cognitive function was measured using processing speed and memory tests, which were categorized into distinct classes using latent profile analysis. Sociodemographic variables, measures of the built and natural environment estimated using geographic information system data, and physical activity and sedentary behaviours were used as predictors. Machine learning was performed using gradient boosting machine, support vector machine, artificial neural network, and linear models. Sociodemographic variables predicted processing speed (r2 = 0.43) and memory (r2 = 0.20) with good accuracy. Lifestyle factors also accurately predicted processing speed (r2 = 0.29) but weakly predicted memory (r2 = 0.10). Neighbourhood and built environment factors were weak predictors of cognitive function. Sociodemographic (AUC = 0.84) and lifestyle (AUC = 0.78) factors also accurately classified cognitive classes. Sociodemographic and lifestyle variables can predict cognitive function in adults. Machine learning tools are useful for population-level assessment of cognitive health status via readily available and easy-to-collect data

Structural-Functional Connectivity Bandwidth of the Human Brain

Background: The human brain is a complex network that seamlessly manifests behaviour and cognition. This network comprises neurons that directly, or indirectly mediate communication between brain regions. Here, we show how multilayer/multiplex network analysis provides a suitable framework to uncover the throughput of structural connectivity (SC) to mediate information transfer-giving rise to functional connectivity (FC). Method: We implemented a novel method to reconcile SC and FC using diffusion and resting-state functional MRI connectivity data from 484 subjects (272 females, 212 males; age = 29.15 ± 3.47) from the Human Connectome Project. First, we counted the number of direct and indirect structural paths that mediate FC. FC nodes with indirect SC paths were then weighted according to their least restrictive SC path. We refer to this as SC-FC Bandwidth. We then mapped paths with the highest SC-FC Bandwidth across 7 canonical resting-state networks. Findings: We found that most pairs of FC nodes were connected by SC paths of length two and three (SC paths of length >5 were virtually non-existent). Direct SC-FC connections accounted for only 10% of all SC-FC connections. The majority of FC nodes without a direct SC path were mediated by a proportion of two (44%) or three SC path lengths (39%). Only a small proportion of FC nodes were mediated by SC path lengths of four (5%). We found high-bandwidth direct SC-FC connections show dense intra- and sparse inter-network connectivity, with a bilateral, anteroposterior distribution. High bandwidth SC-FC triangles have a right superomedial distribution within the somatomotor network. High-bandwidth SC-FC quads have a superoposterior distribution within the default mode network. Conclusion: Our method allows the measurement of indirect SC-FC using undirected, weighted graphs derived from multimodal MRI data in order to map the location and throughput of SC to mediate FC. An extension of this work may be to explore how SC-FC Bandwidth changes over time, relates to cognition/behavior, and if this measure reflects a marker of neurological injury or psychiatric disorders

Rate of torque development and striatal shape in individuals with prodromal Huntington\u27s disease

The aim of the present study was to quantify explosive joint torque or the ability to develop joint torque rapidly, typically measured as the rate of torque development, in individuals with prodromal Huntington’s disease and healthy controls and its associations with measures of disease burden and striatal pathology. Twenty prodromal Huntington’s disease and 19 healthy control individuals volunteered for this study. Plantar flexor isometric rate of torque development values were evaluated using isokinetic dynamometry. Pathological changes in striatal shape were evaluated using magnetic resonance imaging. Disease burden was evaluated using the disease burden score and cytosine-adenine-guanine age product score. No statistical differences in the rate of torque development were observed between individuals with prodromal Huntington’s disease and healthy controls. However, significant associations were observed between the rate of torque development values and measures of disease burden (r = −0.42 to −0.69) and striatal pathology (r = 0.71–0.60) in individuals with prodromal Huntington’s disease. We found significant associations between lower rate of torque development values and greater striatal shape deflation and disease burden and striatal pathology in individuals with prodromal Huntington’s disease. While no significant differences in the rate of torque development were found between prodromal Huntington’s disease and healthy controls, the noted associations suggest that differences may emerge as the disease advances, which should be investigated longitudinally in future studies

Network diffusion modeling predicts neurodegeneration in traumatic brain injury

Objective Traumatic brain injury (TBI) is a heterogeneous disease with multiple neurological deficits that evolve over time. It is also associated with an increased incidence of neurodegenerative diseases. Accordingly, clinicians need better tools to predict a patient’s long‐term prognosis. Methods Diffusion‐weighted and anatomical MRI data were collected from 17 adolescents (mean age = 15y8mo) with moderate‐to‐severe TBI and 19 healthy controls. Using a network diffusion model (NDM), we examined the effect of progressive deafferentation and gray matter thinning in young TBI patients. Moreover, using a novel automated inference method, we identified several injury epicenters in order to determine the neural degenerative patterns in each TBI patient. Results We were able to identify the subject‐specific patterns of degeneration in each patient. In particular, the hippocampus, temporal cortices, and striatum were frequently found to be the epicenters of degeneration across the TBI patients. Orthogonal transformation of the predicted degeneration, using principal component analysis, identified distinct spatial components in the temporal–hippocampal network and the cortico‐striatal network, confirming the vulnerability of these networks to injury. The NDM model, best predictive of the degeneration, was significantly correlated with time since injury, indicating that NDM can potentially capture the pathological progression in the chronic phase of TBI. Interpretation These findings suggest that network spread may help explain patterns of distant gray matter thinning, which would be consistent with Wallerian degeneration of the white matter connections (i.e., “diaschisis”) from diffuse axonal injuries and multifocal contusive injuries, and the neurodegenerative patterns of abnormal protein aggregation and transmission, which are hallmarks of brain changes in TBI. NDM approaches could provide highly subject‐specific biomarkers relevant for disease monitoring and personalized therapies in TBI