Convergence of regenerative medicine and synthetic biology to develop standardized and validated models of human diseases with clinical relevance

In order to progress beyond currently available medical devices and implants, the concept of tissue engineering has moved into the centre of biomedical research worldwide. The aim of this approach is not to replace damaged tissue with an implant or device but rather to prompt the patient's own tissue to enact a regenerative response by using a tissue-engineered construct to assemble new functional and healthy tissue. More recently, it has been suggested that the combination of Synthetic Biology and translational tissue-engineering techniques could enhance the field of personalized medicine, not only from a regenerative medicine perspective, but also to provide frontier technologies for building and transforming the research landscape in the field of in vitro and in vivo disease models.

Association of NOS1AP variants and depression phenotypes in schizophrenia

Background The nitric oxide synthase 1 adaptor protein gene (NOS1AP) has previously been recognised as a schizophrenia susceptibility gene due to its role in glutamate neurotransmission. The gene is believed to inhibit nitric oxide (NO) production activated by the N-methyl-d-aspartate (NMDA) receptor and reduced NO levels have been observed in schizophrenia patients. However, association studies investigating NOS1AP and schizophrenia have produced inconsistent results, most likely because schizophrenia is a clinically heterogeneous disorder. This study aims to investigate the association between NOS1AP variants and defined depression phenotypes of schizophrenia. Methods Nine NOS1AP SNPs, rs1415259, rs1415263, rs1858232, rs386231, rs4531275, rs4656355, rs4657178, rs6683968 and rs6704393 were genotyped in 235 schizophrenia subjects screened for various phenotypes of depression. Result One NOS1AP SNP (rs1858232) was associated with the broad diagnosis of schizophrenia and eight SNPs were associated with depression related phenotypes within schizophrenia. The rs1415259 SNP showed strong association with sleep dysregulation phenotypes of depression. Conclusion Results suggest that NOS1AP variants are associated with various forms of depression in schizophrenia and are more prevalent in males. Limitation Schizophrenia is a clinically heterogeneous disease that can vary greatly between different ethnic and geographic populations so our observations should be viewed with caution until they are independently replicated, particularly in larger patient cohorts.

Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging

Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment This fraction is the result of undesirable genotype-by-environment interactions (G x E) and measured by the genetic correlation (r(g)) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of G x E over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels

Rank regression for analyzing ordinal qualitative data for treatment comparison

Ordinal qualitative data are often collected for phenotypical measurements in plant pathology and other biological sciences. Statistical methods, such as t tests or analysis of variance, are usually used to analyze ordinal data when comparing two groups or multiple groups. However, the underlying assumptions such as normality and homogeneous variances are often violated for qualitative data. To this end, we investigated an alternative methodology, rank regression, for analyzing the ordinal data. The rank-based methods are essentially based on pairwise comparisons and, therefore, can deal with qualitative data naturally. They require neither normality assumption nor data transformation. Apart from robustness against outliers and high efficiency, the rank regression can also incorporate covariate effects in the same way as the ordinary regression. By reanalyzing a data set from a wheat Fusarium crown rot study, we illustrated the use of the rank regression methodology and demonstrated that the rank regression models appear to be more appropriate and sensible for analyzing nonnormal data and data with outliers.

Australia’s first Allied Health Prescribing Program - exploring participants' perspectives on the study program's learning objectives

BACKGROUND The Queensland University of Technology in collaboration with Queensland Health pioneered development of the Allied Health Prescribing Training Program to assist allied health professionals (AHPs) to competently prescribe medicines within their scope of practice. The study program consisted of two modules: Introduction to Clinical Therapeutics for Prescribers and Prescribing and Quality Use of Medicines. METHODS Pre- and post- surveys were developed for both modules. Key themes explored were understanding and confidence in selecting therapeutic choices for patients. For module 2 the learning objectives for safe and effective prescribing were investigated. Data were collected from participants in weeks one and thirteen of the modules via online surveys. RESULTS In the pre-module survey for the first module, participants had a limited degree of understanding and confidence regarding safe and effective use of medicines and appropriate therapeutic choices for managing patients, particularly for complex patients. This improved significantly in the post-module survey. In the pre-module survey for module 2, participants had a moderate degree of understanding and confidence regarding various prescribing learning objectives (including safe and effective prescribing, professional, legal and ethical aspects, communicating medication orders, prescribing safely in their select areas of practice, prescribing safely for complex patients in their area of practice). This increased significantly in the post-module survey. DISCUSSION This training program was implemented to develop a framework of knowledge and skills for AHPs to undertake a prescribing role. The program delivered an increase in participants’ knowledge in the key prescribing areas; and increased participants’ confidence in prescribing safely for patients and for complex patients in their select practice areas. An important aspect of this program was inclusion of prescribing–related activities under supervision of a designated medical practitioner. In conclusion, this educational program for Queensland Health AHP prescribers was successfully developed and is in the final stages of delivery.

The effects of psychosocial factors on the emotional well-being of women during pregnancy: A cross-cultural study of Britain and Greece

The effects of life events, social support and the emotional well-being of partner on the emotional well-being of the mother during pregnancy was examined within the cultural contexts of Britain and Greece. It was proposed that social support, impact of life events and relationship of the mother with her partner would be affected by the different social structures of each culture and would influence emotional well-being. A sample of 200 Greek and 156 British mothers and their partners completed questionnaires which included a life event inventory, measure of social support and measure of emotional well-being (Crown-Crisp Experiential Index). Greek mothers were found to score significantly higher on measures of depression, anxiety and somaticism, experience more stressful life events (most relating to family issues) and report feeling less supported than British mothers. Life events, particularly those relating to family stresses were found to predict poor emotional well-being among Greek mothers. For British mothers, social support was the strongest predictor of emotional well-being. Findings were discussed in the light of differences in social structure and it was suggested that future research might focus on the disruption of established social support structures rather than the differences in availability of social support per se when considering maternal emotional well-being.

Quality of life after early enteral feeding versus standard care for proven or suspected advanced epithelial ovarian cancer: Results from a randomised trial

Background Malnutrition is common in patients with advanced epithelial ovarian cancer (EOC), and is associated with impaired quality of life (QoL), longer hospital stay and higher risk of treatment-related adverse events. This phase III multi-centre randomised clinical trial tested early enteral feeding versus standard care on postoperative QoL. Methods From 2009 to 2013, 109 patients requiring surgery for suspected advanced EOC, moderately to severely malnourished were enrolled at five sites across Queensland and randomised to intervention (n = 53) or control (n = 56) groups. Intervention involved intraoperative nasojejunal tube placement and enteral feeding until adequate oral intake could be maintained. Despite being randomised to intervention, 20 patients did not receive feeds (13 did not receive the feeding tube; 7 had it removed early). Control involved postoperative diet as tolerated. QoL was measured at baseline, 6 weeks postoperatively and 30 days after the third cycle of chemotherapy. The primary outcome measure was the difference in QoL between the intervention and the control group. Secondary endpoints included treatment-related adverse event occurrence, length of stay, postoperative services use, and nutritional status. Results Baseline characteristics were comparable between treatment groups. No significant difference in QoL was found between the groups at any time point. There was a trend towards better nutritional status in patients who received the intervention but the differences did not reach statistical significance except for the intention-to-treat analysis at 7 days postoperatively (11.8 intervention vs. 13.8 control, p 0.04). Conclusion Early enteral feeding did not significantly improve patients' QoL compared to standard of care but may improve nutritional status.

Switching period randomisation for multilevel converter modulation

The spectral energy associated with the carrier and sidebands of naturally sampled carrier based PWM can be spread by randomising the carrier (switch) half-period Tc = 1/2fc. So long as the switch duty cycle each period still correctly reflects the value of the modulating fundamental waveform as sampled during that switch period, then the fundamental component will remain undistorted. Natural sampling will ensure this occurs. Carrier based PWM can be extended to (m+1) level multilevel converter waveform generation by creating m triangular carriers, each with an equal 2*pi/m phase displacement. Alternatively the carrier disposition strategy calls for m amplitude displaced triangular carriers, each of amplitude 1/m and frequency mfc. Randomising these carrier sub-periods T0> = 1/2mfc is shown to generate (m+ 1) level PWM waveforms where the first (m-1) carrier groups are cancelled, while the remaining carrier and sidebands at multiples of mfc are spectrally spread. Numerous five level simulation and experimentally gathered randomised PWM waveforms are presented, showing the effects of the variation of the degree of randomisation, modulation depth and pulse number.

The height limit of a siphon

The maximum height of a siphon is generally assumed to be dependent on barometric pressure—about 10 m at sea level. This limit arises because the pressure in a siphon above the upper reservoir level is below the ambient pressure, and when the height of a siphon approaches 10 m, the pressure at the crown of the siphon falls below the vapour pressure of water causing water to boil breaking the column. After breaking, the columns on either side are supported by differential pressure between ambient and the low-pressure region at the top of the siphon. Here we report an experiment of a siphon operating at sea level at a height of 15 m, well above 10 m. Prior degassing of the water prevented cavitation. This experiment provides conclusive evidence that siphons operate through gravity and molecular cohesion.

Automated feature engineering for HTTP tunnel detection

Generating discriminative input features is a key requirement for achieving highly accurate classifiers. The process of generating features from raw data is known as feature engineering and it can take significant manual effort. In this paper we propose automated feature engineering to derive a suite of additional features from a given set of basic features with the aim of both improving classifier accuracy through discriminative features, and to assist data scientists through automation. Our implementation is specific to HTTP computer network traffic. To measure the effectiveness of our proposal, we compare the performance of a supervised machine learning classifier built with automated feature engineering versus one using human-guided features. The classifier addresses a problem in computer network security, namely the detection of HTTP tunnels. We use Bro to process network traffic into base features and then apply automated feature engineering to calculate a larger set of derived features. The derived features are calculated without favour to any base feature and include entropy, length and N-grams for all string features, and counts and averages over time for all numeric features. Feature selection is then used to find the most relevant subset of these features. Testing showed that both classifiers achieved a detection rate above 99.93% at a false positive rate below 0.01%. For our datasets, we conclude that automated feature engineering can provide the advantages of increasing classifier development speed and reducing development technical difficulties through the removal of manual feature engineering. These are achieved while also maintaining classification accuracy.

A shallow water AUV for benthic and water column observations

Autonomous underwater vehicles (AUVs) are becoming commonplace in the study of inshore coastal marine habitats. Combined with shipboard systems, scientists are able to make in-situ measurements of water column and benthic properties. In CSIRO, autonomous gliders are used to collect water column data, while surface vessels are used to collect bathymetry information through the use of swath mapping, bottom grabs, and towed video systems. Although these methods have provided good data coverage for coastal and deep waters beyond 50m, there has been an increasing need for autonomous in-situ sampling in waters less than 50m deep. In addition, the collection of benthic and water column data has been conducted separately, requiring extensive post-processing to combine data streams. As such, a new AUV was developed for in-situ observations of both benthic habitat and water column properties in shallow waters. This paper provides an overview of the Starbug X AUV system, its operational characteristics including vision-based navigation and oceanographic sensor integration.

Changes in cannabis use among psychotic clients without specialised substance use treatment

The need to address substance use among people with psychosis has been well established. However, treatment studies targeting substance use in this population have reported mixed results. Substance users with psychosis in no or minimal treatment control groups achieve similar reductions in substance use compared to those in more active substance use treatment, suggesting a role for natural recovery from substance use. This meta-analysis aims to quantify the amount of natural recovery from substance use within control groups of treatment studies containing samples of psychotic substance users, with a particular focus on changes in cannabis use. A systematic search was conducted to identify substance use treatment studies. Meta-analyses were performed to quantify reductions in the frequency of substance use in the past 30 days. Significant but modest reductions (mean reduction of 0.3–0.4 SD across the time points) in the frequency of substance use were found at 6 to 24 months follow up. The current study is the first to quantify changes in substance use in samples enrolled in no treatment or minimal treatment control conditions. These findings highlight the potential role of natural recovery from substance use among individuals with psychosis, although they do not rule out effects of regression to the mean. Additionally, the results provide a baseline from which to estimate likely changes or needed effects sizes in intervention studies. Future research is required to identify the processes underpinning these changes, in order to identify strategies that may better support self-management of substance use in people with psychosis.

Avian diversification patterns across the K-Pg boundary: Influence of calibrations, datasets, and model misspecification

Birds represent the most diverse extant tetrapod clade, with ca. 10,000 extant species, and the timing of the crown avian radiation remains hotly debated. The fossil record supports a primarily Cenozoic radiation of crown birds, whereas molecular divergence dating analyses generally imply that this radiation was well underway during the Cretaceous. Furthermore, substantial differences have been noted between published divergence estimates. These have been variously attributed to clock model, calibration regime, and gene type. One underappreciated phenomenon is that disparity between fossil ages and molecular dates tends to be proportionally greater for shallower nodes in the avian Tree of Life. Here, we explore potential drivers of disparity in avian divergence dates through a set of analyses applying various calibration strategies and coding methods to a mitochondrial genome dataset and an 18-gene nuclear dataset, both sampled across 72 taxa. Our analyses support the occurrence of two deep divergences (i.e., the Palaeognathae/Neognathae split and the Galloanserae/Neoaves split) well within the Cretaceous, followed by a rapid radiation of Neoaves near the K-Pg boundary. However, 95% highest posterior density intervals for most basal divergences in Neoaves cross the boundary, and we emphasize that, barring unreasonably strict prior distributions, distinguishing between a rapid Early Paleocene radiation and a Late Cretaceous radiation may be beyond the resolving power of currently favored divergence dating methods. In contrast to recent observations for placental mammals, constraining all divergences within Neoaves to occur in the Cenozoic does not result in unreasonably high inferred substitution rates. Comparisons of nuclear DNA (nDNA) versus mitochondrial DNA (mtDNA) datasets and NT- versus RY-coded mitochondrial data reveal patterns of disparity that are consistent with substitution model misspecifications that result in tree compression/tree extension artifacts, which may explain some discordance between previous divergence estimates based on different sequence types. Comparisons of fully calibrated and nominally calibrated trees support a correlation between body mass and apparent dating error. Overall, our results are consistent with (but do not require) a Paleogene radiation for most major clades of crown birds.

Metabolomic and proteomic analysis of breast cancer patient samples suggests that glutamate and 12-HETE in combination with CA15-3 may be useful biomarkers reflecting tumour burden

Evaluation of protein and metabolite expression patterns in blood using mass spectrometry and high-throughput antibody-based screening platforms has potential for the discovery of new biomarkers for managing breast cancer patient treatment. Previously identified blood-based breast cancer biomarkers, including cancer antigen 15.3 (CA15-3) are useful in combination with imaging (computed tomography scans, magnetic resonance imaging, X-rays) and physical examination for monitoring tumour burden in advanced breast cancer patients. However, these biomarkers suffer from insufficient levels of accuracy and with new therapies available for the treatment of breast cancer, there is an urgent need for reliable, non-invasive biomarkers that measure tumour burden with high sensitivity and specificity so as to provide early warning of the need to switch to an alternative treatment. The aim of this study was to identify a biomarker signature of tumour burden using cancer and non-cancer (healthy controls/non-malignant breast disease) patient samples. Results demonstrate that combinations of three candidate biomarkers from Glutamate, 12-Hydroxyeicosatetraenoic acid, Beta-hydroxybutyrate, Factor V and Matrix metalloproteinase-1 with CA15-3, an established biomarker for breast cancer, were found to mirror tumour burden, with AUC values ranging from 0.71 to 0.98 when comparing non-malignant breast disease to the different stages of breast cancer. Further validation of these biomarker panels could potentially facilitate the management of breast cancer patients, especially to assess changes in tumour burden in combination with imaging and physical examination.

Abnormal levels of heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) in tumour tissue and blood samples from patients diagnosed with lung cancer

Lung cancer is the second most common type of cancer in the world and is the most common cause of cancer-related death in both men and women. Research into causes, prevention and treatment of lung cancer is ongoing and much progress has been made recently in these areas, however survival rates have not significantly improved. Therefore, it is essential to develop biomarkers for early diagnosis of lung cancer, prediction of metastasis and evaluation of treatment efficiency, as well as using these molecules to provide some understanding about tumour biology and translate highly promising findings in basic science research to clinical application. In this investigation, two-dimensional difference gel electrophoresis and mass spectrometry were initially used to analyse conditioned media from a panel of lung cancer and normal bronchial epithelial cell lines. Significant proteins were identified with heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1), pyruvate kinase M2 isoform (PKM2), Hsc-70 interacting protein and lactate dehydrogenase A (LDHA) selected for analysis in serum from healthy individuals and lung cancer patients. hnRNPA2B1, PKM2 and LDHA were found to be statistically significant in all comparisons. Tissue analysis and knockdown of hnRNPA2B1 using siRNA subsequently demonstrated both the overexpression and potential role for this molecule in lung tumorigenesis. The data presented highlights a number of in vitro derived candidate biomarkers subsequently verified in patient samples and also provides some insight into their roles in the complex intracellular mechanisms associated with tumour progression.