Non-invasive detection of hyperglycaemia in type 1 diabetic patients using electrocardiographic signals

University of Technology Sydney. Faculty of Engineering and Information Technology.Hyperglycaemia is the medical term for a state caused by a high level of blood glucose, resulting from defects in insulin secretion, insulin action, or both. Hyperglycaemia is a common dangerous complication to glycaemic control in Type 1 diabetic patients. The chronic hyperglycaemia of diabetes is associated with long-term damage, dysfunction, and failure of different organs, especially the eyes, kidneys, nerves, heart, and blood vessels. Therefore, reliable detection of hyperglycaemic episodes is important in order to avoid major health conditions. Conventionally, diabetic patients need to frequently monitor blood glucose levels to determine whether they have hyperglycaemia or not. A patient has to prick their finger (finger-stick) for a drop of blood several times a day, which can therefore significantly discourage many patients from periodically checking blood glucose levels. Another choice for hyperglycaemia detection might be continuous glucose monitoring systems (CGMS), which measure the glucose level in the interstitial fluid. For patients using CGMS, finger-sticks are still required to calibrate the sensor. The main shortcoming of CGMS is that glucose levels in interstitial fluid lag temporally behind blood glucose values, normally 10-15 minutes, which absolutely limits the accuracy of the detection. There is a strong demand to have a non-invasive technique to help patients to diagnose the disease easily and painlessly. Few methods have been reported to detect hyperglycaemia non-invasively or minimally invasively such as in exhaled methyl nitrates, and early detection of ongoing β cell death. However, the purpose of these studies was on real-time glucose control rather than disease diagnosis. Electrocardiography (ECG) is a broadly used technique to obtain a quick, non-invasive clinical and research screen for diagnosing abnormal rhythms of the heart caused by diseases. In fact, observations of ECG changes have been found in hypoglycaemia and hyperglycaemia states in T1DM, such as increased heart rate and prolongation of QT interval in hypoglycaemia, whereas hyperglycaemia was related to reduced heart rate variability. By using these findings in hypoglycaemia, researchers have developed an effective and sensitive system to detect hypoglycaemia non-invasively. These excellent performances of hypoglycaemia detection using ECG is the motivation of this thesis to study the effect of hyperglycaemia on ECG signals, and based on the findings to exploit the computational intelligence on the non-invasive detection of hyperglycaemia. This research firstly explores the changes of ECG parameters associated with the hyperglycaemic state in T1DM. The ECG parameters consist of ECG intervals relating to repolarisation phase and heart rate variability (HRV) measures. A clinical study of ten T1DM patients and ECG feature extraction process are conducted to collect ECG features. Statistical analysis is then applied to every ECG feature to estimate the significant difference between hyperglycaemic and normoglycaemic states. The results show that the selected ECG parameters in hyperglycaemia differ significantly from those in normoglycaemia (p< 0.05). It implies that certain ECG parameters are correlated with high blood glucose levels and they possibly contribute to the performance of hyperglycaemia detection. Thus, the ECG parameters are used for input data of hyperglycaemia classifiers in this thesis. Furthermore, the thesis introduces novel computational intelligent methods for hyperglycaemia detection using the ECG parameters. A neural network using Levenberg-Marquardt algorithm is the first method explored for hyperglycaemia detection in this thesis, known as LM-NN. The second algorithm is the integration of principal component analysis (PCA) with a neural network utilising the Levenberg-Marquardt algorithm, which is called a PCA-LM-NN network. PCA is a useful tool for dimensionality reduction to diminish the computational requirement and overcome the problem of multicollinearity. It is employed to filter the data so that only the significant independent ECG variables responsible for the high blood glucose levels can be used as input for the network training, in order that the neural network performs well for hyperglycaemia detection. The third method is for the improvement of the second method where particle swarm optimization is included. This algorithm is a combination of PCA, PSO and neural network, which is called PSO-NN. The PSO is utilised as an effective training algorithm to optimise the weights of the neural network. The proposed methods are compared with each other and with other traditional classifiers. All the algorithms are investigated with the clinical electrocardiographic data extracted from ten T1DM patients. The results show that the performance of PCA-LM model for hyperglycaemia detection is better than that of LM-NN (70.88% vs. 67.94%, in terms of geometric mean). In addition, the PSO-NN outperforms the PCA-LM-NN (77.58% vs. 70.88%, in terms of geometric mean). In short, the PSO-NN significantly improves the performances of both the LM-NN and PCA-LM-NN, with considerable sensitivity, specificity and geometric mean of 82.35%, 73.08% and 77.58%, respectively

Using Deep Learning Model for Network Scanning Detection

In recent years, new and devastating cyber attacks amplify the need for robust cybersecurity practices. Preventing novel cyber attacks requires the invention of Intrusion Detection Systems (IDSs), which can identify previously unseen attacks. Many researchers have attempted to produce anomaly - based IDSs, however they are not yet able to detect malicious network traffic consistently enough to warrant implementation in real networks. Obviously, it remains a challenge for the security community to produce IDSs that are suitable for implementation in the real world. In this paper, we propose a new approach using a Deep Belief Network with a combination of supervised and unsupervised machine learning methods for port scanning attacks detection - the task of probing enterprise networks or Internet wide services, searching for vulnerabilities or ways to infiltrate IT assets. Our proposed approach will be tested with network security datasets and compared with previously existing methods

Recent advances in experimental testing and computational modelling for characterisation of mechanical properties of biomaterials and biological cells

Biomaterials and biological cells possess a number of different properties; amongst them, mechanical properties are extremely important in studies and applications about tissue engineering, design and development of implants, surgical tools and medical devices for treatments and diagnosis of diseases. Changes in mechanical properties such as a stiffness of cells are often the signs of changes in cell physiology or diseases in tissues; and studying these changes can lead to the development of devices for early disease detection and new drug delivery mechanisms. This paper presents advances in recent years in experimental testing and computational modelling for characterisation of mechanical properties of biomaterials and biological cells, in which the presented research projects and related studies were mainly implemented by research groups in the UK. The recent important findings as well as research directions and challenges are emphasised and discussed, to open channels for research collaborations in development of cost-effective medical diagnosis and treatment solutions

26Postoperative diagnosis and outcome in patients with revision arthroplasty for aseptic loosening

BACKGROUND: The most common cause of implant failure is aseptic loosening (AL), followed by prosthetic joint infection (PJI). This study evaluates the incidence of PJI among patients operated with suspected AL and whether the diagnosis of PJI was predictive of subsequent implant failure including re-infection, at 2 years of follow up. METHODS: Patients undergoing revision hip or knee arthroplasty due to presumed AL from February 2009 to September 2011 were prospectively evaluated. A sonication fluid of prosthesis and tissue samples for microbiology and histopathology at the time of the surgery were collected. Implant failure include recurrent or persistent infection, reoperation for any reason or need for chronic antibiotic suppression. RESULTS: Of 198 patients with pre-and intraoperative diagnosis of AL, 24 (12.1 %) had postoperative diagnosis of PJI. After a follow up of 31 months (IQR: 21 to 38 months), 9 (37.5 %) of 24 patients in the PJI group had implant failure compared to only 1 (1.1 %) in the 198 of AL group (p 20 CFU) and peri-prosthetic tissue culture were 87.5 % vs 66.7 %, respectively. Specificities were 100 % for both techniques (95 % CI, 97.9-100 %). A greater number of patients with PJI (79.1 %) had previous partial arthroplasty revisions than those patients in the AL group (56.9 %) (p = 0.04). In addition, 5 (55.5 %) patients with PJI and implant failure had more revision arthroplasties during the first year after the last implant placement than those patients with PJI without implant failure (1 patient; 6.7 %) (RR 3.8; 95 % CI 1.4-10.1; p = 0.015). On the other hand, 6 (25 %) patients finally diagnosed of PJI were initially diagnosed of AL in the first year after primary arthroplasty, whereas it was only 16 (9.2 %) patients in the group of true AL (RR 2.7; 95 % CI 1.2-6.1; p = 0.03). CONCLUSIONS: More than one tenth of patients with suspected AL are misdiagnosed PJI. Positive histology and positive peri-implant tissue and sonicate fluid cultures are highly predictive of implant failure in patients with PJI. Patients with greater number of partial hip revisions for a presumed AL had more risk of PJI. Early loosening is more often caused by hidden PJI than late loosening

Critical Limb Ischemia

Critical limb ischemia (CLI), defined as chronic ischemic rest pain, ulcers, or gangrene attributable to objectively proven arterial occlusive disease, is the most advanced form of peripheral arterial disease. Traditionally, open surgical bypass was the only effective treatment strategy for limb revascularization in this patient population. However, during the past decade, the introduction and evolution of endovascular procedures have significantly increased treatment options. In a certain subset of patients for whom either surgical or endovascular revascularization may not be appropriate, primary amputation remains a third treatment option. Definitive high-level evidence on which to base treatment decisions, with an emphasis on clinical and cost effectiveness, is still lacking. Treatment decisions in CLI are individualized, based on life expectancy, functional status, anatomy of the arterial occlusive disease, and surgical risk. For patients with aortoiliac disease, endovascular therapy has become first-line therapy for all but the most severe patterns of occlusion, and aortofemoral bypass surgery is a highly effective and durable treatment for the latter group. For infrainguinal disease, the available data suggest that surgical bypass with vein is the preferred therapy for CLI patients likely to survive 2 years or more, and for those with long segment occlusions or severe infrapopliteal disease who have an acceptable surgical risk. Endovascular therapy may be preferred in patients with reduced life expectancy, those who lack usable vein for bypass or who are at elevated risk for operation, and those with less severe arterial occlusions. Patients with unreconstructable disease, extensive necrosis involving weight-bearing areas, nonambulatory status, or other severe comorbidities may be considered for primary amputation or palliative measures

Safety and Efficacy of Adalimumab in Patients with Noninfectious Uveitis in an Ongoing Open-Label Study: VISUAL III

PURPOSE: To evaluate safety and efficacy of adalimumab in patients with noninfectious intermediate, posterior, or panuveitis. DESIGN: Phase 3, open-label, multicenter clinical trial extension (VISUAL III). PARTICIPANTS: Adults meeting treatment failure (TF) criteria or who completed VISUAL I or II (phase 3, randomized, double-masked, placebo-controlled) without TF. METHODS: Patients received adalimumab 40 mg every other week. Interim follow-up data were described from VISUAL III weeks 0 through 78. MAIN OUTCOME MEASURES: Disease quiescence, steroid-free quiescence, active inflammatory chorioretinal/retinal vascular lesions, anterior chamber cell grade, vitreous haze grade, best-corrected visual acuity (BCVA), and corticosteroid dose. Binary data were reported using nonresponder imputation (NRI), continuous data using last observation carried forward and as-observed analysis, and corticosteroid dose using observed-case analysis. Adverse events (AEs) were reported from first adalimumab dose in VISUAL III through interim cutoff. RESULTS: Of 424 patients enrolled, 371 were included in intent-to-treat analysis. At study entry, 242 of 371 (65%) patients had active uveitis; 60% (145/242, NRI) achieved quiescence at week 78, and 66% (95/143, as-observed) of those were corticosteroid free. At study entry, 129 of 371 (35%) patients had inactive uveitis; 74% (96/129, NRI) achieved quiescence at week 78, and 93% (89/96, as-observed) of those were corticosteroid free. Inflammatory lesions, anterior chamber grade, and vitreous haze grade showed initial improvement followed by decline in patients with active uveitis and remained stable in patients with inactive uveitis. BCVA improved in patients with active uveitis from weeks 0 to 78 (0.27 to 0.14 logMAR; left and right eyes; as-observed) and remained stable in patients with inactive uveitis. Mean corticosteroid dose decreased from 13.6 mg/day (week 0) to 2.6 mg/day (week 78) in patients with active uveitis and remained stable in those with inactive uveitis (1.5-1.2 mg/day). AEs (424 events/100 patient-years) and serious AEs (16.5 events/100 patient-years) were comparable with previous VISUAL trials. CONCLUSIONS: Patients with active uveitis at study entry who received adalimumab therapy were likely to achieve quiescence, improve visual acuity, and reduce their daily uveitis-related systemic corticosteroid use. Most patients with inactive uveitis at study entry sustained quiescence without a systemic corticosteroid dose increase. No new safety signals were identified

Enhanced Platelet Activation Mediates the Accelerated Angiogenic Switch in Mice Lacking Histidine-Rich Glycoprotein

BACKGROUND: The heparin-binding plasma protein histidine-rich glycoprotein (HRG; alternatively, HRGP/HPRG) can suppress tumor angiogenesis and growth in vitro and in vivo. Mice lacking the HRG gene are viable and fertile, but have an enhanced coagulation resulting in decreased bleeding times. In addition, the angiogenic switch is significantly enhanced in HRG-deficient mice. METHODOLOGY/PRINCIPAL FINDINGS: To address whether HRG deficiency affects tumor development, we have crossed HRG knockout mice with the RIP1-Tag2 mouse, a well established orthotopic model of multistage carcinogenesis. RIP1-Tag2 HRG(-/-) mice display significantly larger tumor volume compared to their RIP1-Tag2 HRG(+/+) littermates, supporting a role for HRG as an endogenous regulator of tumor growth. In the present study we also demonstrate that platelet activation is increased in mice lacking HRG. To address whether this elevated platelet activation contributes to the increased pathological angiogenesis in HRG-deficient mice, they were rendered thrombocytopenic before the onset of the angiogenic switch by injection of the anti-platelet antibody GP1bα. Interestingly, this treatment suppressed the increase in angiogenic neoplasias seen in HRG knockout mice. However, if GP1bα treatment was initiated at a later stage, after the onset of the angiogenic switch, no suppression of tumor growth was detected in HRG-deficient mice. CONCLUSIONS: Our data show that increased platelet activation mediates the accelerated angiogenic switch in HRG-deficient mice. Moreover, we conclude that platelets play a crucial role in the early stages of tumor development but are of less significance for tumor growth once angiogenesis has been initiated

Measurement of the branching ratio of pi^0 -> e^+e^- using K_L -> 3 pi^0 decays in flight

The branching ratio of the rare decay pi^0 -> e^+e^- has been measured in E799-II, a rare kaon decay experiment using the KTeV detector at Fermilab. The pi^0's were produced in fully-reconstructed K_L -> 3 pi^0 decays in flight. We observed 275 candidate pi^0 -> e^+e^- events, with an expected background of 21.4 +- 6.2 events which includes the contribution from Dalitz decays. We measured BR(pi^0 -> e^+e^-, x>0.95) = (6.09 +- 0.40 +- 0.24) times 10^{-8}, where the first error is statistical and the second systematic. This result is the first significant observation of the excess rate for this decay above the unitarity lower bound.Comment: New version shortened to PRL length limit. 5 pages, 4 figures. Published in Phys. Rev. Let

Salvage Cryotherapy for Radiation-Recurrent Prostate Cancer: Outcomes and Complications

Potentially curative salvage options for radio-recurrent prostate cancer include prostatectomy, brachytherapy, high-intensity focused ultrasound, and cryotherapy. Salvage cryoablation technology, surgical technique, oncologic outcomes, and complication rates have improved dramatically over the past few decades, shifting this treatment modality from investigational status to an established therapeutic option. In this review, we focus on the most up-to-date oncologic and functional outcomes, as well as complications of salvage cryotherapy for radiation-recurrent prostate cancer