Acute fluid shifts influence the assessment of serum vitamin D status in critically ill patients

Introduction Recent reports have highlighted the prevalence of vitamin D deficiency and suggested an association with excess mortality in critically ill patients. Serum vitamin D concentrations in these studies were measured following resuscitation. It is unclear whether aggressive fluid resuscitation independently influences serum vitamin D. Methods Nineteen patients undergoing cardiopulmonary bypass were studied. Serum 25(OH)D3, 1α,25(OH)2D3, parathyroid hormone, C-reactive protein (CRP), and ionised calcium were measured at five defined timepoints: T1 - baseline, T2 - 5 minutes after onset of cardiopulmonary bypass (CPB) (time of maximal fluid effect), T3 - on return to the intensive care unit, T4 - 24 hrs after surgery and T5 - 5 days after surgery. Linear mixed models were used to compare measures at T2-T5 with baseline measures. Results Acute fluid loading resulted in a 35% reduction in 25(OH)D3 (59 ± 16 to 38 ± 14 nmol/L, P < 0.0001) and a 45% reduction in 1α,25(OH)2D3 (99 ± 40 to 54 ± 22 pmol/L P < 0.0001) and i(Ca) (P < 0.01), with elevation in parathyroid hormone (P < 0.0001). Serum 25(OH)D3 returned to baseline only at T5 while 1α,25(OH)2D3 demonstrated an overshoot above baseline at T5 (P < 0.0001). There was a delayed rise in CRP at T4 and T5; this was not associated with a reduction in vitamin D levels at these time points. Conclusions Hemodilution significantly lowers serum 25(OH)D3 and 1α,25(OH)2D3, which may take up to 24 hours to resolve. Moreover, delayed overshoot of 1α,25(OH)2D3 needs consideration. We urge caution in interpreting serum vitamin D in critically ill patients in the context of major resuscitation, and would advocate repeating the measurement once the effects of the resuscitation have abated.

Status on pre-surgical deformation apparatus for fracture fixation plates

Purpose: This paper reviews the apparatus used for deformation of bone fracture fixation plates during orthopaedic surgeries including surgical irons, pliers and bending press tools. This paper extends the review to various machineries in non-medical industries and adopts their suitability to clinics-related applications and also covers the evolution of orthopaedic bone plates. This review confirms that none of the studied machineries can be implemented for the deformation of bone fracture fixation plates during orthopaedic surgeries. In addition, this paper also presents the novel apparatus that are designed from scratch for this specific purpose. Several conceptual designs have been proposed and evaluated recently. It has been found that Computer Numerical Control (CNC) systems are not the golden solution to this problem and one needs to attempt to design the robotic arm system. A new design of robotic arm that can be used for facilitating orthopaedic surgeries is being completed.

Maternal perception of weight status in first-born Australian toddlers aged 12–16 months – the NOURISH and SAIDI cohorts

Background The preference amongst parents for heavier infants is in contrast to obesity prevention efforts worldwide. Parents are poor at identifying overweight in older children, but few studies have investigated maternal perception of weight status amongst toddlers and none in the Australian setting. Methods Mothers (n = 290) completed a self-administered questionnaire at child age 12–16 months, defining their child's weight status as underweight, normal weight, somewhat overweight or very overweight. Weight-for-length z-score was derived from measured weight and length, and children categorized as underweight, normal weight, at risk overweight or obese (WHO standards). Objective classification was compared with maternal perception of weight status. Mean weight-for-length z-score was compared across categories of maternal perception using one-way ANOVA. Multinomial logistic regression was used to determine child or maternal characteristics associated with inaccurate weight perception. Results Most children (83%) were perceived as normal weight. Twenty nine were described as underweight, although none were. Sixty-six children were at risk of overweight, but 57 of these perceived as normal weight. Of the 14 children who were overweight, only 4 were identified as somewhat overweight by their mother. Compared with mothers who could accurately classify their normal weight child, mothers who were older had higher odds of perceiving their normal weight child as underweight, while mothers with higher body mass index had slightly higher odds of describing their overweight/at risk child as normal weight. Conclusion The leaner but healthy weight toddler was perceived as underweight, while only the heaviest children were recognized as overweight. Mothers unable to accurately identify children at risk are unlikely to act to prevent further excess weight gain. Practitioners can lead a shift in attitudes towards weight in infants and young children, promoting routine growth monitoring and adequate but not rapid weight gain.

Blended learning in medical imaging pre-clinical skills training – does it work?

Undergraduate Medical Imaging (MI)students at QUT attend their first clinical placement towards the end of semester two. Students undertake two (pre)clinical skills development units – one theory and one practical. Students gain good contextual and theoretical knowledge during these units via a blended learning model with multiple learning methods employed. Students attend theory lectures, practical sessions, tutorial sessions in both a simulated and virtual environment and also attend pre-clinical scenario based tutorial sessions. The aim of this project is to evaluate the use of blended learning in the context of 1st year Medical Imaging Radiographic Technique and its effectiveness in preparing students for their first clinical experience. It is hoped that the multiple teaching methods employed within the pre-clinical training unit at QUT builds students clinical skills prior to the real situation. A quantitative approach will be taken, evaluating via pre and post clinical placement surveys. This data will be correlated with data gained in the previous year on the effectiveness of this training approach prior to clinical placement. In 2014 59 students were surveyed prior to their clinical placement demonstrated positive benefits of using a variety of learning tools to enhance their learning. 98.31%(n=58)of students agreed or strongly agreed that the theory lectures were a useful tool to enhance their learning. This was followed closely by 97% (n=57) of the students realising the value of performing role-play simulation prior to clinical placement. Tutorial engagement was considered useful for 93.22% (n=55) whilst 88.14% (n=52) reasoned that the x-raying of phantoms in the simulated radiographic laboratory was beneficial. Self-directed learning yielded 86.44% (n=51). The virtual reality simulation software was valuable for 72.41% (n=42) of the students. Of the 4 students that disagreed or strongly disagreed with the usefulness of any tool they strongly agreed to the usefulness of a minimum of one other learning tool. The impact of the blended learning model to meet diverse student needs continues to be positive with students engaging in most offerings. Students largely prefer pre -clinical scenario based practical and tutorial sessions where 'real-world’ situations are discussed.

Associations of serum perfluoroalkyl acid levels with T-helper cell-specific cytokines in children: By gender and asthma status

Perfluoroalkyl acids (PFAAs) are a group of common chemicals that ubiquitously exist in wildlife and humans. Experimental data suggest that they may alter T-lymphocyte functioning in situ by preferentially enhancing the development of T-helper 2 (TH2)- and inhibiting TH1-lymphocyte development and might increase allergic inflammation, but few human studies have been conducted. To evaluate the association between serum PFAAs concentrations and T-lymphocyte-related immunological markers of asthma in children, and further to assess whether gender modified this association, 231 asthmatic children and 225 non-asthmatic control children from Northern Taiwan were recruited into the Genetic and Biomarker study for Childhood Asthma. Serum concentrations of ten PFAAs and levels of TH1 [interferon (IFN)-γ, interleukin (IL)-2] and TH2 (IL-4 and IL-5) cytokines were measured. The results showed that asthmatics had significantly higher serum PFAAs concentrations compared with the healthy controls. When stratified by gender, a greater number of significant associations between PFAAs and asthma outcomeswere found in males than in females. Among males, adjusted odds ratios for asthma among those with the highest versus lowest quartile of PFAAs exposure ranged from 2.59 (95% CI: 1.14, 5.87) for the perfluorobutanesulfonate (PFBS) to 4.38 (95% CI: 2.02, 9.50) for perfluorooctanesulfonate (PFOS); and serum PFAAs were associated positively with TH2 cytokines and inversely with TH1 cytokines among male asthmatics. Among females, no significant associations between PFAAs and TH2 cytokines could be detected. In conclusion, increased serum PFAAs levels may promote TH cell dysregulation and alter the availability of key TH1 and TH2 cytokines, ultimately contributing to the development of asthma that may differentially impact males to a greater degree than females. These results have potential relevance in asthma prevention.

Mitochondrial and nuclear markers suggest Hanuman langur (Primates: Colobinae) polyphyly: Implications for their species status

Recent molecular studies on langurs of the Indian subcontinent suggest that the widely-distributed and morphologically variable Hanuman langurs (Semnopithecus entellus) are polyphyletic with respect to Nilgiri and urple-faced langurs. To further investigate this scenario, we have analyzed additional sequences of mitochondrial cytochrome b as well as nuclear protamine P1 genes from these species. The results confirm Hanuman langur polyphyly in the mitochondrial tree and the nuclear markers suggest that the Hanuman langurs share protamine P1 alleles with Nilgiri and purple-faced langurs. We recommend provisional splitting of the so-called Hanuman langurs into three species such that the taxonomy is consistent with their evolutionary relationships.

Functional Imagery Training to reduce snacking: Testing a novel motivational intervention based on Elaborated Intrusion theory

Functional Imagery Training (FIT) is a new theory-based, manualized intervention that trains positive goal imagery. Multisensory episodic imagery of proximal personal goals is elicited and practised, to sustain motivation and compete with less functional cravings. This study tested the impact of a single session of FIT plus a booster phone call on snacking. In a stepped-wedge design, 45 participants who wanted to lose weight or reduce snacking were randomly assigned to receive a session of FIT immediately or after a 2-week delay. High-sugar and high-fat snacks were recorded using timeline follow back for the previous 3 days, at baseline, 2 and 4 weeks. At 2 weeks, snacking was lower in the immediate group than in the delayed group, and the reduction after FIT was replicated in the delayed group between 2 and 4 weeks. Frequencies of motivational thoughts about snack reduction rose following FIT for both groups, and this change correlated with reductions in snacking and weight loss. By showing that FIT can support change in eating behaviours, these findings show its potential as a motivational intervention for weight management.

Application of artificial intelligence for the assessment of the status of power transformers

The Dissolved Gas Analysis (DGA) a non destructive test procedure, has been in vogue for a long time now, for assessing the status of power and related transformers in service. An early indication of likely internal faults that may exist in Transformers has been seen to be revealed, to a reasonable degree of accuracy by the DGA. The data acquisition and subsequent analysis needs an expert in the concerned area to accurately assess the condition of the equipment. Since the presence of the expert is not always guaranteed, it is incumbent on the part of the power utilities to requisition a well planned and reliable artificial expert system to replace, at least in part, an expert. This paper presents the application of Ordered Ant Mner (OAM) classifier for the prediction of involved fault. Secondly, the paper also attempts to estimate the remaining life of the power transformer as an extension to the elapsed life estimation method suggested in the literature.

Bone health and vitamin D status in children with motor disability and adults with intellectual disability

Osteoporosis is not only a disease of the elderly, but is increasingly diagnosed in chronically ill children. Children with severe motor disabilities, such as cerebral palsy (CP), have many risk factors for osteoporosis. Adults with intellectual disability (ID) are also prone to low bone mineral density (BMD) and increased fractures. This study was carried out to identify risk factors for low BMD and osteoporosis in children with severe motor disability and in adults with ID. In this study 59 children with severe motor disability, ranging in age from 5 to 16 years were evaluated. Lumbar spine BMD was measured with dual-energy x-ray absorptiometry. BMD values were corrected for bone size by calculating bone mineral apparent density (BMAD), and for bone age. The values were transformed into Z-scores by comparison with normative data. Spinal radiographs were assessed for vertebral morphology. Blood samples were obtained for biochemical parameters. Parents were requested to keep a food diary for three days. The median daily energy and nutrient intakes were calculated. Fractures were common; 17% of the children had sustained peripheral fractures and 25% had compression fractures. BMD was low in children; the median spinal BMAD Z-score was -1.0 (range -5.0 – +2.0) and the BMAD Z-score <-2.0 in 20% of the children. Low BMAD Z-score and hypercalciuria were significant risk factors for fractures. In children with motor disability, calcium intakes were sufficient, while total energy and vitamin D intakes were not. In the vitamin D intervention studies, 44 children and adolescents with severe motor disability and 138 adults with ID were studied. After baseline blood samples, the children were divided into two groups; those in the treatment group received 1000 IU peroral vitamin D3 five days a week for 10 weeks, and subjects in the control group continued with their normal diet. Adults with ID were allocated to receive either 800 IU peroral vitamin D3 daily for six months or a single intramuscular injection of 150 000 IU D3. Blood samples were obtained at baseline and after treatment. Serum concentrations of 25-OH-vitamin D (S-25-OHD) were low in all subgroups before vitamin D intervention: in almost 60% of children and in 77% of adults the S-25-OHD concentration was below 50 nmol/L, indicating vitamin D insufficiency. After vitamin D intervention, 19% of children and 42% adults who received vitamin D perorally and 12% of adults who received vitamin D intramuscularly had optimal S-25-OHD (>80 nmol/L). This study demonstrated that low BMD and peripheral and spinal fractures are common in children with severe motor disabilities. Vitamin D status was suboptimal in the majority of children with motor disability and adults with ID. Vitamin D insufficiency can be corrected with vitamin D supplements; the peroral dose should be at least 800 IU per day.

Cluster based training for scaling non-linear support vector machines

Support Vector Machines(SVMs) are hyperplane classifiers defined in a kernel induced feature space. The data size dependent training time complexity of SVMs usually prohibits its use in applications involving more than a few thousands of data points. In this paper we propose a novel kernel based incremental data clustering approach and its use for scaling Non-linear Support Vector Machines to handle large data sets. The clustering method introduced can find cluster abstractions of the training data in a kernel induced feature space. These cluster abstractions are then used for selective sampling based training of Support Vector Machines to reduce the training time without compromising the generalization performance. Experiments done with real world datasets show that this approach gives good generalization performance at reasonable computational expense.