Increased tubulointerstitial recruitment of human CD141(hi) CLEC9A(+) and CD1c(+) myeloid dendritic cell subsets in renal fibrosis and chronic kidney disease

Dendritic cells (DCs) play critical roles in immune-mediated kidney diseases. Little is known, however, about DC subsets in human chronic kidney disease, with previous studies restricted to a limited set of pathologies and to using immunohistochemical methods. In this study, we developed novel protocols for extracting renal DC subsets from diseased human kidneys and identified, enumerated, and phenotyped them by multicolor flow cytometry. We detected significantly greater numbers of total DCs as well as CD141(hi) and CD1c(+) myeloid DC (mDCs) subsets in diseased biopsies with interstitial fibrosis than diseased biopsies without fibrosis or healthy kidney tissue. In contrast, plasmacytoid DC numbers were significantly higher in the fibrotic group compared with healthy tissue only. Numbers of all DC subsets correlated with loss of kidney function, recorded as estimated glomerular filtration rate. CD141(hi) DCs expressed C-type lectin domain family 9 member A (CLEC9A), whereas the majority of CD1c(+) DCs lacked the expression of CD1a and DC-specific ICAM-3-grabbing nonintegrin (DC-SIGN), suggesting these mDC subsets may be circulating CD141(hi) and CD1c(+) blood DCs infiltrating kidney tissue. Our analysis revealed CLEC9A(+) and CD1c(+) cells were restricted to the tubulointerstitium. Notably, DC expression of the costimulatory and maturation molecule CD86 was significantly increased in both diseased cohorts compared with healthy tissue. Transforming growth factor-β levels in dissociated tissue supernatants were significantly elevated in diseased biopsies with fibrosis compared with nonfibrotic biopsies, with mDCs identified as a major source of this profibrotic cytokine. Collectively, our data indicate that activated mDC subsets, likely recruited into the tubulointerstitium, are positioned to play a role in the development of fibrosis and, thus, progression to chronic kidney disease.

Lung recruitment manoeuvres for reducing respiratory morbidity in mechanically ventilated neonates

This is the protocol for a review and there is no abstract. The objectives are as follows: To determine the evidence supporting the use of recruitment manoeuvres in mechanically ventilated neonates and identify the optimal method of lung recruitment. To determine the effects of lung recruitment manoeuvres in neonates receiving ventilatory support on neonatal mortality and development of chronic lung disease when compared to no recruitment. If data are available, subgroup analyses will include: chronological age, gestational age, lung pathophysiology and pre-existing lung disease, mode and length of ventilation, timing and frequency of recruitment techniques.

Proteomic and other analyses to determine the functional consequences of deregulated kallikrein-related peptidase (KLK) expression in prostate and ovarian cancer

Rapidly developing proteomic tools are improving detection of deregulated kallikrein-related peptidase (KLK) expression, at the protein level, in prostate and ovarian cancer, as well as facilitating the determination of functional consequences downstream. Mass spectrometry (MS)-driven proteomics uniquely allows for the detection, identification and quantification of thousands of proteins in a complex protein pool, and this has served to identify certain KLKs as biomarkers for these diseases. In this review we describe applications of this technology in KLK biomarker discovery, and elucidate MS-based techniques which have been used for unbiased, global screening of KLK substrates within complex protein pools. Although MS-based KLK degradomic studies are limited to date, they helped to discover an array of novel KLK substrates. Substrates identified by MS-based degradomics are reported with improved confidence over those determined by incubating a purified or recombinant substrate and protease of interest, in vitro. We propose that these novel proteomic approaches represent the way forward for KLK research, in order to correlate proteolysis of biological substrates with tissue-related consequences, toward clinical targeting of KLK expression and function for cancer diagnosis, prognosis and therapies.

Fetal Alcohol Spectrum Disorder diagnosis and counselling

The Foetal Alcohol Syndrome has long gone unrecognised and undiagnosed in Australia. In the last few years of the 21st Century (2010-14) health practitioners are finally seeking ways of diagnosing the effects of alcohol in pregnancy on the next generation. The author offers a power point presentation which gives guidance on making an accurate diagnosis.

Application of machine learning technique in wind turbine fault diagnosis

In this study, a machine learning technique called anomaly detection is employed for wind turbine bearing fault detection. Basically, the anomaly detection algorithm is used to recognize the presence of unusual and potentially faulty data in a dataset, which contains two phases: a training phase and a testing phase. Two bearing datasets were used to validate the proposed technique, fault-seeded bearing from a test rig located at Case Western Reserve University to validate the accuracy of the anomaly detection method, and a test to failure data of bearings from the NSF I/UCR Center for Intelligent Maintenance Systems (IMS). The latter data set was used to compare anomaly detection with SVM, a previously well-known applied method, in rapidly finding the incipient faults.

Fault diagnosis of low speed bearing based on acoustic emission signal and multi-class relevance vector machine

This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing using multi-class relevance vector machine (RVM). A low speed test rig was developed to simulate the various defects with shaft speeds as low as 10 rpm under several loading conditions. The data was acquired using anAEsensor with the test bearing operating at a constant loading (5 kN) andwith a speed range from20 to 80 rpm. This study is aimed at finding a reliable method/tool for low speed machines fault diagnosis based on AE signal. In the present study, component analysis was performed to extract the bearing feature and to reduce the dimensionality of original data feature. The result shows that multi-class RVM offers a promising approach for fault diagnosis of low speed machines.

Comparison of high sensitivity troponin T and I assays in the diagnosis of non-ST elevation acute myocardial infarction in emergency patients with chest pain

Objectives: Concentrations of troponin measured with high sensitivity troponin assays are raised in a number of emergency department (ED) patients; however many are not diagnosed with acute myocardial infarction (AMI). Clinical comparisons between the early use (2 h after presentation) of high sensitivity cardiac troponin T (hs-cTnT) and I (hs-cTnI) assays for the diagnosis of AMI have not been reported. Design and methods: Early (0 h and 2 h) hs-cTnT and hs-cTnI assay results in 1571 ED patients with potential acute coronary syndrome (ACS) without ST elevation on electrocardiograph (ECG) were evaluated. The primary outcome was diagnosis of index MI adjudicated by cardiologists using the local cTnI assay results taken ≥6 h after presentation, ECGs and clinical information. Stored samples were later analysed with hs-cTnT and hs-cTnI assays. Results: The ROC analysis for AMI (204 patients; 13.0%) for hs-cTnT and hs-cTnI after 2 h was 0.95 (95% CI: 0.94–0.97) and 0.98 (95% CI: 0.97–0.99) respectively. The sensitivity, specificity, PLR, and NLR of hs-cTnT and hs-cTnI for AMI after 2 h were 94.1% (95% CI: 90.0–96.6) and 95.6% (95% CI: 91.8–97.7), 79.0% (95% CI: 76.8–81.1) and 92.5% (95% CI: 90.9–93.7), 4.48 (95% CI: 4.02–5.00) and 12.86 (95% CI: 10.51–15.31), and 0.07 (95% CI: 0.04–0.13) and 0.05 (95% CI:0.03–0.09) respectively. Conclusions: Exclusion of AMI 2 h after presentation in emergency patients with possible ACS can be achieved using hs-cTnT or hs-cTnI assays. Significant differences in specificity of these assays are relevant and if using the hs-cTnT assay, further clinical assessment in a larger proportion of patients would be required.

Prenatal diagnosis, genetics and reproductive decision-making

Recent developments in genetic science will potentially have a significant impact on reproductive decision-making by adding to the list of conditions which can be diagnosed through prenatal diagnosis. This article analyses the jurisdictional variations that exist in Australian abortion laws and examines the extent to which Australian abortion laws specifically provide for termination of pregnancy on the grounds of fetal disability. The article also examines the potential impact of pre-implantation genetic diagnosis on reproductive decision-making and considers the meaning of reproductive autonomy in the context of the new genetics.

A systematic review of community-based interventions for emerging zoonotic diseases in Southeast Asia

Background Southeast Asia has been at the epicentre of recent epidemics of emerging and re-emerging zoonotic diseases. Community-based surveillance and control interventions have been heavily promoted but the most effective interventions have not been identified. Objectives This review evaluated evidence for the effectiveness of community-based surveillance interventions at monitoring and identifying emerging infectious disease; the effectiveness of community-based control interventions at reducing rates of emerging infectious disease; and contextual factors that influence intervention effectiveness. Inclusion criteria Participants Communities in Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand and Viet Nam. Types of intervention(s) Non-pharmaceutical, non-vaccine, and community-based surveillance or prevention and control interventions targeting rabies, Nipah virus , dengue, SARS or avian influenza. Types of outcomes Primary outcomes: measures: of infection or disease; secondary outcomes: measures of intervention function. Types of studies Original quantitative studies published in English. Search strategy Databases searched (1980 to 2011): PubMed, CINAHL, ProQuest, EBSCOhost, Web of Science, Science Direct, Cochrane database of systematic reviews, WHOLIS, British Development Library, LILACS, World Bank (East Asia), Asian Development Bank. Methodological quality Two independent reviewers critically appraised studies using standard Joanna Briggs Institute instruments. Disagreements were resolved through discussion. Data extraction A customised tool was used to extract quantitative data on intervention(s), populations, study methods, and primary and secondary outcomes; and qualitative contextual information or narrative evidence about interventions. Data synthesis Data was synthesised in a narrative summary with the aid of tables. Meta-analysis was used to statistically pool quantitative results. Results Fifty-seven studies were included. Vector control interventions using copepods, environmental cleanup and education are effective and sustainable at reducing dengue in rural and urban communities, whilst insecticide spraying is effective in urban outbreak situations. Community-based surveillance interventions can effectively identify avian influenza in backyard flocks, but have not been broadly applied. Outbreak control interventions for Nipah virus and SARS are effective but may not be suitable for ongoing control. Canine vaccination and education is more acceptable than culling, but still fails to reach coverage levels required to effectively control rabies. Contextual factors were identified that influence community engagement with, and ultimately effectiveness of, interventions. Conclusion Despite investment in community-based disease control and surveillance in Southeast Asia, published evidence evaluating interventions is limited in quantity and quality. Nonetheless this review identified a number of effective interventions, and several contextual factors influencing effectiveness. Identification of the best programs will require comparative evidence of effectiveness acceptability, cost-effectiveness and sustainability.

Recursive actuator fault detection and diagnosis for emergency landing of UASs

This paper presents a practical recursive fault detection and diagnosis (FDD) scheme for online identification of actuator faults for unmanned aerial systems (UASs) based on the unscented Kalman filtering (UKF) method. The proposed FDD algorithm aims to monitor health status of actuators and provide indication of actuator faults with reliability, offering necessary information for the design of fault-tolerant flight control systems to compensate for side-effects and improve fail-safe capability when actuator faults occur. The fault detection is conducted by designing separate UKFs to detect aileron and elevator faults using a nonlinear six degree-of-freedom (DOF) UAS model. The fault diagnosis is achieved by isolating true faults by using the Bayesian Classifier (BC) method together with a decision criterion to avoid false alarms. High-fidelity simulations with and without measurement noise are conducted with practical constraints considered for typical actuator fault scenarios, and the proposed FDD exhibits consistent effectiveness in identifying occurrence of actuator faults, verifying its suitability for integration into the design of fault-tolerant flight control systems for emergency landing of UASs.

What does it mean to 'securitize' infectious diseases?

This paper seeks to explain how the selective securitization of infectious disease arose, and to analyze the policy successes from this move. It is argued that despite some success, such as the revised International Health Regulations (IHR) in 2005, there remain serious deficiencies in the political outputs from the securitization of infectious disease.

Lung recruitment and endotracheal suction in ventilated preterm infants measured with electrical impedance tomography

Aims Although suctioning is a standard airway maintenance procedure, there are significant associated risks, such as loss of lung volume due to high negative suction pressures. This study aims to assess the extent and duration of change in end-expiratory level (EEL) resulting from endotracheal tube (ETT) suction and to examine the relationship between EEL and regional lung ventilation in ventilated preterm infants with respiratory distress syndrome. Methods A prospective observational clinical study of the effect of ETT suction on 20 non-muscle-relaxed preterm infants with respiratory distress syndrome (RDS) on conventional mechanical ventilation was conducted in a neonatal intensive care unit. Ventilation distribution was measured with regional impedance amplitudes and EEL using electrical impedance tomography. Results ETT suction resulted in a significant increase in EEL post-suction (P < 0.01). Regionally, anterior EEL decreased and posterior EEL increased post-suction, suggesting heterogeneity. Tidal volume was significantly lower in volume-guarantee ventilation compared with pressure-controlled ventilation (P = 0.04). Conclusions ETT suction in non-muscle-relaxed and ventilated preterm infants with RDS results in significant lung volume increase that is maintained for at least 90 min. Regional differences in distribution of ventilation with ETT suction suggest that the behaviour of the lung is heterogeneous in nature.

Condition monitoring and fault diagnosis of diesel engines using instantaneous angular speed analysis

Continuous monitoring of diesel engine performance is critical for early detection of fault developments in an engine before they materialize into a functional failure. Instantaneous crank angular speed (IAS) analysis is one of a few nonintrusive condition monitoring techniques that can be utilized for such a task. Furthermore, the technique is more suitable for mass industry deployments than other non-intrusive methods such as vibration and acoustic emission techniques due to the low instrumentation cost, smaller data size and robust signal clarity since IAS is not affected by the engine operation noise and noise from the surrounding environment. A combination of IAS and order analysis was employed in this experimental study and the major order component of the IAS spectrum was used for engine loading estimation and fault diagnosis of a four-stroke four-cylinder diesel engine. It was shown that IAS analysis can provide useful information about engine speed variation caused by changing piston momentum and crankshaft acceleration during the engine combustion process. It was also found that the major order component of the IAS spectra directly associated with the engine firing frequency (at twice the mean shaft rotating speed) can be utilized to estimate engine loading condition regardless of whether the engine is operating at healthy condition or with faults. The amplitude of this order component follows a distinctive exponential curve as the loading condition changes. A mathematical relationship was then established in the paper to estimate the engine power output based on the amplitude of this order component of the IAS spectrum. It was further illustrated that IAS technique can be employed for the detection of a simulated exhaust valve fault in this study.

Advanced mass spectrometry-based multi-omics technologies for exploring the pathogenesis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the primary hepatic malignancies and is the third most common cause of cancer related death worldwide. Although a wealth of knowledge has been gained concerning the initiation and progression of HCC over the last half century, efforts to improve our understanding of its pathogenesis at a molecular level are still greatly needed, to enable clinicians to enhance the standards of the current diagnosis and treatment of HCC. In the post-genome era, advanced mass spectrometry driven multi-omics technologies (e.g., profiling of DNA damage adducts, RNA modification profiling, proteomics, and metabolomics) stand at the interface between chemistry and biology, and have yielded valuable outcomes from the study of a diversity of complicated diseases. Particularly, these technologies are being broadly used to dissect various biological aspects of HCC with the purpose of biomarker discovery, interrogating pathogenesis as well as for therapeutic discovery. This proof of knowledge-based critical review aims at exploring the selected applications of those defined omics technologies in the HCC niche with an emphasis on translational applications driven by advanced mass spectrometry, toward the specific clinical use for HCC patients. This approach will enable the biomedical community, through both basic research and the clinical sciences, to enhance the applicability of mass spectrometry-based omics technologies in dissecting the pathogenesis of HCC and could lead to novel therapeutic discoveries for HCC.