Impact of nocturnal hypoxia on glycaemic control, appetite, gut microbiota and inflammation in adults with type 2 diabetes mellitus: A single-blind cross-over trial.

High altitude residents have a lower incidence of type 2 diabetes mellitus (T2DM). Therefore, we examined the effect of repeated overnight normobaric hypoxic exposure on glycaemic control, appetite, gut microbiota and inflammation in adults with T2DM. Thirteen adults with T2DM [glycated haemoglobin (HbA1c): 61.1 ± 14.1 mmol mol-1; aged 64.2 ± 9.4 years; four female] completed a single-blind, randomised, sham-controlled, cross-over study for 10 nights, sleeping when exposed to hypoxia (fractional inspired O2 [ F I O 2 ${{F}_{{\mathrm{I}}{{{\mathrm{O}}}_{\mathrm{2}}}}}$ ] = 0.155; ∼2500 m simulated altitude) or normoxic conditions ( F I O 2 ${{F}_{{\mathrm{I}}{{{\mathrm{O}}}_{\mathrm{2}}}}}$  = 0.209) in a randomised order. Outcome measures included: fasted plasma [glucose]; [hypoxia inducible factor-1α]; [interleukin-6]; [tumour necrosis factor-α]; [interleukin-10]; [heat shock protein 70]; [butyric acid]; peak plasma [glucose] and insulin sensitivity following a 2 h oral glucose tolerance test; body composition; appetite indices ([leptin], [acyl ghrelin], [peptide YY], [glucagon-like peptide-1]); and gut microbiota diversity and abundance [16S rRNA amplicon sequencing]. During intervention periods, accelerometers measured physical activity, sleep duration and efficiency, whereas continuous glucose monitors were used to assess estimated HbA1c and glucose management indicator and time in target range. Overnight hypoxia was not associated with changes in any outcome measure (P > 0.05 with small effect sizes) except fasting insulin sensitivity and gut microbiota alpha diversity, which exhibited trends (P = 0.10; P = 0.08 respectively) for a medium beneficial effect (d = 0.49; d = 0.59 respectively). Ten nights of overnight moderate hypoxic exposure did not significantly affect glycaemic control, gut microbiome, appetite, or inflammation in adults with T2DM. However, the intervention was well tolerated and a medium effect-size for improved insulin sensitivity and reduced alpha diversity warrants further investigation. KEY POINTS: Living at altitude lowers the incidence of type 2 diabetes mellitus (T2DM). Animal studies suggest that exposure to hypoxia may lead to weight loss and suppressed appetite. In a single-blind, randomised sham-controlled, cross-over trial, we assessed the effects of 10 nights of hypoxia (fractional inspired O2 ∼0.155) on glucose homeostasis, appetite, gut microbiota, inflammatory stress ([interleukin-6]; [tumour necrosis factor-α]; [interleukin-10]) and hypoxic stress ([hypoxia inducible factor 1α]; heat shock protein 70]) in 13 adults with T2DM. Appetite and inflammatory markers were unchanged following hypoxic exposure, but an increased insulin sensitivity and reduced gut microbiota alpha diversity were associated with a medium effect-size and statistical trends, which warrant further investigation using a definitive large randomised controlled trial. Hypoxic exposure may represent a viable therapeutic intervention in people with T2DM and particularly those unable or unwilling to exercise because barriers to uptake and adherence may be lower than for other lifestyle interventions (e.g. diet and exercise).

Dynamic threat-reward neural processing under semi-naturalistic ecologically relevant scenarios.

Studies of affective neuroscience have typically employed highly controlled, static experimental paradigms to investigate the neural underpinnings of threat and reward processing in the brain. Yet our knowledge of affective processing in more naturalistic settings remains limited. Specifically, affective studies generally examine threat and reward features separately and under brief time periods, despite the fact that in nature organisms are often exposed to the simultaneous presence of threat and reward features for extended periods. To study the neural mechanisms of threat and reward processing under distinct temporal profiles, we created a modified version of the PACMAN game that included these environmental features. We also conducted two automated meta-analyses to compare the findings from our semi-naturalistic paradigm to those from more constrained experiments. Overall, our results revealed a distributed system of regions sensitive to threat imminence and a less distributed system related to reward imminence, both of which exhibited overlap yet neither of which involved the amygdala. Additionally, these systems broadly overlapped with corresponding meta-analyses, with the notable absence of the amygdala in our findings. Together, these findings suggest a shared system for salience processing that reveals a heightened sensitivity toward environmental threats compared to rewards when both are simultaneously present in an environment. The broad correspondence of our findings to meta-analyses, consisting of more tightly controlled paradigms, illustrates how semi-naturalistic studies can corroborate previous findings in the literature while also potentially uncovering novel mechanisms resulting from the nuances and contexts that manifest in such dynamic environments.

Serotonergic dysfunction may mediate the relationship between alcohol consumption and Alzheimer's disease.

The impact of Alzheimer's disease (AD) and its related dementias is rapidly expanding, and its mitigation remains an urgent social and technical challenge. To date there are no effective treatments or interventions for AD, but recent studies suggest that alcohol consumption is correlated with the risk of developing dementia. In this review, we synthesize data from preclinical, clinical, and epidemiological models to evaluate the combined role of alcohol consumption and serotonergic dysfunction in AD, underscoring the need for further research on this topic. We first discuss the limitations inherent to current data-collection methods, and how neuropsychiatric symptoms common among AD, alcohol use disorder, and serotonergic dysfunction may mask their co-occurrence. We additionally describe how excess alcohol consumption may accelerate the development of AD via direct effects on serotonergic function, and we explore the roles of neuroinflammation and proteostasis in mediating the relationship between serotonin, alcohol consumption, and AD. Lastly, we argue for a shift in current research to disentangle the pathogenic effects of alcohol on early-affected brainstem structures in AD.

The effect of repeated hot water immersion on insulin sensitivity, heat shock protein 70, and inflammation in individuals with type 2 diabetes mellitus.

Repeated hot water immersion (HWI) can improve glycemic control in healthy individuals but data are limited for individuals with type 2 diabetes mellitus (T2DM). The present study investigated whether repeated HWI improves insulin sensitivity and inflammatory status and reduces plasma ([extracellular heat shock protein 70]) [eHSP70] and resting metabolic rate (RMR). Fourteen individuals with T2DM participated in this pre- versus postintervention study, with outcome measures assessed in fasted (≥12 h) and postprandial (2-h post-75 g glucose ingestion) states. HWI consisted of 1 h in 40°C water (target rectal temperature 38.5°C-39°C) repeated 8-10 times within a 14-day period. Outcome measures included insulin sensitivity, plasma [glucose], [insulin], [eHSP70], inflammatory markers, RMR, and substrate utilization. The HWI intervention increased fasted insulin sensitivity (QUICKI; P = 0.03) and lowered fasted plasma [insulin] (P = 0.04), but fasting plasma [glucose] (P = 0.83), [eHSP70] (P = 0.08), [IL-6] (P = 0.55), [IL-10] (P = 0.59), postprandial insulin sensitivity (P = 0.19), plasma [glucose] (P = 0.40), and [insulin] (P = 0.47) were not different. RMR was reduced by 6.63% (P < 0.05), although carbohydrate (P = 0.43) and fat oxidation (P = 0.99) rates were unchanged. This study shows that 8-10 HWIs within a 14-day period improved fasting insulin sensitivity and plasma [insulin] in individuals with T2DM, but not when glucose tolerance is challenged. HWI also improves metabolic efficiency (i.e., reduced RMR). Together these results could be clinically important and have implications for metabolic health outcomes and well-being in individuals with T2DM.NEW & NOTEWORTHY This is the first study to investigate repeated HWI to raise deep body temperature on insulin sensitivity, inflammation, eHSP70, and substrate utilization in individuals with T2DM. The principal novel findings were improvements in fasting insulin sensitivity and fasting plasma [insulin] but no change in fasting plasma [glucose], postprandial insulin sensitivity, plasma [insulin], or [glucose]. There was also no change in eHSP70, inflammatory status, or substrate utilization but there were reductions in RMR and oxygen consumption.

Novel 3D printable PEEK-HA-Mg2SiO4 composite material for spine implants: biocompatibility and imaging compatibility assessments.

PURPOSE: To develop a novel 3D printable polyether ether ketone (PEEK)-hydroxyapatite (HA)-magnesium orthosilicate (Mg2SiO4) composite material with enhanced properties for potential use in tumour, osteoporosis and other spinal conditions. We aim to evaluate biocompatibility and imaging compatibility of the material. METHODS: Materials were prepared in three different compositions, namely composite A: 75 weight % PEEK, 20 weight % HA, 5 weight % Mg2SiO4; composite B: 70 weight% PEEK, 25 weight % HA, 5 weight % Mg2SiO4; and composite C: 65 weight % PEEK, 30 weight % HA, 5 weight % Mg2SiO4. The materials were processed to obtain 3D printable filament. Biomechanical properties were analysed as per ASTM standards and biocompatibility of the novel material was evaluated using indirect and direct cell cytotoxicity tests. Cell viability of the novel material was compared to PEEK and PEEK-HA materials. The novel material was used to 3D print a standard spine cage. Furthermore, the CT and MR imaging compatibility of the novel material cage vs PEEK and PEEK-HA cages were evaluated using a phantom setup. RESULTS: Composite A resulted in optimal material processing to obtain a 3D printable filament, while composite B and C resulted in non-optimal processing. Composite A enhanced cell viability up to ~ 20% compared to PEEK and PEEK-HA materials. Composite A cage generated minimal/no artefacts on CT and MR imaging and the images were comparable to that of PEEK and PEEK-HA cages. CONCLUSION: Composite A demonstrated superior bioactivity vs PEEK and PEEK-HA materials and comparable imaging compatibility vs PEEK and PEEK-HA. Therefore, our material displays an excellent potential to manufacture spine implants with enhanced mechanical and bioactive property.

A deep learning-based technique for the diagnosis of epidural spinal cord compression on thoracolumbar CT.

PURPOSE: To develop a deep learning (DL) model for epidural spinal cord compression (ESCC) on CT, which will aid earlier ESCC diagnosis for less experienced clinicians. METHODS: We retrospectively collected CT and MRI data from adult patients with suspected ESCC at a tertiary referral institute from 2007 till 2020. A total of 183 patients were used for training/validation of the DL model. A separate test set of 40 patients was used for DL model evaluation and comprised 60 staging CT and matched MRI scans performed with an interval of up to 2 months. DL model performance was compared to eight readers: one musculoskeletal radiologist, two body radiologists, one spine surgeon, and four trainee spine surgeons. Diagnostic performance was evaluated using inter-rater agreement, sensitivity, specificity and AUC. RESULTS: Overall, 3115 axial CT slices were assessed. The DL model showed high kappa of 0.872 for normal, low and high-grade ESCC (trichotomous), which was superior compared to a body radiologist (R4, κ = 0.667) and all four trainee spine surgeons (κ range = 0.625-0.838)(all p < 0.001). In addition, for dichotomous normal versus any grade of ESCC detection, the DL model showed high kappa (κ = 0.879), sensitivity (91.82), specificity (92.01) and AUC (0.919), with the latter AUC superior to all readers (AUC range = 0.732-0.859, all p < 0.001). CONCLUSION: A deep learning model for the objective assessment of ESCC on CT had comparable or superior performance to radiologists and spine surgeons. Earlier diagnosis of ESCC on CT could reduce treatment delays, which are associated with poor outcomes, increased costs, and reduced survival.

Customised acoustic therapy delivered through a web-based platform-An innovative approach to tinnitus treatment.

OBJECTIVES: Customised acoustic therapy aims to moderate the neural pathways implicated in the pathophysiology of tinnitus. This study aimed to assess the efficacy of customised acoustic therapy administered via a web-based treatment platform. DESIGN: Clinical trial with prospective recruitment. Fifty-eight participants underwent 6 weeks of customised acoustic therapy. SETTING: Treatment was delivered for 2 h each day using a smartphone, tablet or computer. Treatment was integrated into usual daily activities. PARTICIPANTS: Participants with subjective tinnitus were recruited through public and private otolaryngology clinics and electronic and print media. MAIN OUTCOMES MEASURED: FiveQ, a novel 5 question tinnitus questionnaire, was measured at baseline and each week of treatment. Statistical analyses, including Wilcoxon, Mann-Whitney and mixed linear regression, were used to assess treatment efficacy and identify factors associated with treatment response. RESULTS: 39/58 participants (67.2%) had an improvement in symptom severity scores, 4 had no change (6.9%) and 15 had a decline from baseline (25.9%). Mean FiveQ scores improved by 22.9% from 40.8 (SD = 21.4) at baseline to 31.5 (SD = 21.3) following 6 weeks of treatment (p < 0.001). With the exception of the slight tinnitus group, all other groups (from mild to catastrophic) demonstrated a treatment response. Participants with low frequency tinnitus (<2000 Hz) had a significantly greater treatment response (p < 0.001). CONCLUSION: Customised acoustic therapy administered via a web-based platform demonstrated encouraging efficacy. At least mild symptoms at baseline and low frequency tinnitus were associated with a greater treatment response. Customised acoustic therapy offers accessible and efficacious tinnitus treatment, however longer term clinical studies are required to confirm the observed initial benefit is maintained.

Improved Productivity Using Deep Learning-assisted Reporting for Lumbar Spine MRI.

Background Lumbar spine MRI studies are widely used for back pain assessment. Interpretation involves grading lumbar spinal stenosis, which is repetitive and time consuming. Deep learning (DL) could provide faster and more consistent interpretation. Purpose To assess the speed and interobserver agreement of radiologists for reporting lumbar spinal stenosis with and without DL assistance. Materials and Methods In this retrospective study, a DL model designed to assist radiologists in the interpretation of spinal canal, lateral recess, and neural foraminal stenoses on lumbar spine MRI scans was used. Randomly selected lumbar spine MRI studies obtained in patients with back pain who were 18 years and older over a 3-year period, from September 2015 to September 2018, were included in an internal test data set. Studies with instrumentation and scoliosis were excluded. Eight radiologists, each with 2-13 years of experience in spine MRI interpretation, reviewed studies with and without DL model assistance with a 1-month washout period. Time to diagnosis (in seconds) and interobserver agreement (using Gwet κ) were assessed for stenosis grading for each radiologist with and without the DL model and compared with test data set labels provided by an external musculoskeletal radiologist (with 32 years of experience) as the reference standard. Results Overall, 444 images in 25 patients (mean age, 51 years ± 20 [SD]; 14 women) were evaluated in a test data set. DL-assisted radiologists had a reduced interpretation time per spine MRI study, from a mean of 124-274 seconds (SD, 25-88 seconds) to 47-71 seconds (SD, 24-29 seconds) (P < .001). DL-assisted radiologists had either superior or equivalent interobserver agreement for all stenosis gradings compared with unassisted radiologists. DL-assisted general and in-training radiologists improved their interobserver agreement for four-class neural foraminal stenosis, with κ values of 0.71 and 0.70 (with DL) versus 0.39 and 0.39 (without DL), respectively (both P < .001). Conclusion Radiologists who were assisted by deep learning for interpretation of lumbar spinal stenosis on MRI scans showed a marked reduction in reporting time and superior or equivalent interobserver agreement for all stenosis gradings compared with radiologists who were unassisted by deep learning. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Hayashi in this issue.

Histone Deacetylase 9 Activates IKK to Regulate Atherosclerotic Plaque Vulnerability.

RATIONALE: Arterial inflammation manifested as atherosclerosis is the leading cause of mortality worldwide. Genome-wide association studies have identified a prominent role of HDAC (histone deacetylase)-9 in atherosclerosis and its clinical complications including stroke and myocardial infarction. OBJECTIVE: To determine the mechanisms linking HDAC9 to these vascular pathologies and explore its therapeutic potential for atheroprotection. METHODS AND RESULTS: We studied the effects of Hdac9 on features of plaque vulnerability using bone marrow reconstitution experiments and pharmacological targeting with a small molecule inhibitor in hyperlipidemic mice. We further used 2-photon and intravital microscopy to study endothelial activation and leukocyte-endothelial interactions. We show that hematopoietic Hdac9 deficiency reduces lesional macrophage content while increasing fibrous cap thickness thus conferring plaque stability. We demonstrate that HDAC9 binds to IKK (inhibitory kappa B kinase)-α and ß, resulting in their deacetylation and subsequent activation, which drives inflammatory responses in both macrophages and endothelial cells. Pharmacological inhibition of HDAC9 with the class IIa HDAC inhibitor TMP195 attenuates lesion formation by reducing endothelial activation and leukocyte recruitment along with limiting proinflammatory responses in macrophages. Transcriptional profiling using RNA sequencing revealed that TMP195 downregulates key inflammatory pathways consistent with inhibitory effects on IKKß. TMP195 mitigates the progression of established lesions and inhibits the infiltration of inflammatory cells. Moreover, TMP195 diminishes features of plaque vulnerability and thereby enhances plaque stability in advanced lesions. Ex vivo treatment of monocytes from patients with established atherosclerosis reduced the production of inflammatory cytokines including IL (interleukin)-1ß and IL-6. CONCLUSIONS: Our findings identify HDAC9 as a regulator of atherosclerotic plaque stability and IKK activation thus providing a mechanistic explanation for the prominence of HDAC9 as a vascular risk locus in genome-wide association studies. Its therapeutic inhibition may provide a potent lever to alleviate vascular inflammation. Graphical Abstract: A graphical abstract is available for this article.

The wash-in effect and its significance for mass casualty decontamination.

Decontamination of skin by washing may increase dermal absorption, a phenomenon known as the wash-in effect. The wash-in effect is frequently discussed in studies investigating casualty decontamination where potentially life-saving interventions may enhance the dermal penetration of toxic chemicals, leading to an increase in incidence of morbidity and rates of mortality. However, the wash-in effect is seldom investigated within the context of mass casualty decontamination and real-life consequences are therefore poorly understood. This paper reviews the existing literature on the wash-in effect to highlight the proposed mechanisms for enhanced absorption and evaluate the wash-in effect within the context of mass casualty chemical decontamination.

Effect of Training Data Volume on Performance of Convolutional Neural Network Pneumothorax Classifiers.

Large datasets with high-quality labels required to train deep neural networks are challenging to obtain in the radiology domain. This work investigates the effect of training dataset size on the performance of deep learning classifiers, focusing on chest radiograph pneumothorax detection as a proxy visual task in the radiology domain. Two open-source datasets (ChestX-ray14 and CheXpert) comprising 291,454 images were merged and convolutional neural networks trained with stepwise increase in training dataset sizes. Model iterations at each dataset volume were evaluated on an external test set of 525 emergency department chest radiographs. Learning curve analysis was performed to fit the observed AUCs for all models generated. For all three network architectures tested, model AUCs and accuracy increased rapidly from 2 × 103 to 20 × 103 training samples, with more gradual increase until the maximum training dataset size of 291 × 103 images. AUCs for models trained with the maximum tested dataset size of 291 × 103 images were significantly higher than models trained with 20 × 103 images: ResNet-50: AUC20k = 0.86, AUC291k = 0.95, p < 0.001; DenseNet-121 AUC20k = 0.85, AUC291k = 0.93, p < 0.001; EfficientNet AUC20k = 0.92, AUC 291 k = 0.98, p < 0.001. Our study established learning curves describing the relationship between dataset training size and model performance of deep learning convolutional neural networks applied to a typical radiology binary classification task. These curves suggest a point of diminishing performance returns for increasing training data volumes, which algorithm developers should consider given the high costs of obtaining and labelling radiology data.

Deep Learning Model for Automated Detection and Classification of Central Canal, Lateral Recess, and Neural Foraminal Stenosis at Lumbar Spine MRI.

Background Assessment of lumbar spinal stenosis at MRI is repetitive and time consuming. Deep learning (DL) could improve -productivity and the consistency of reporting. Purpose To develop a DL model for automated detection and classification of lumbar central canal, lateral recess, and neural -foraminal stenosis. Materials and Methods In this retrospective study, lumbar spine MRI scans obtained from September 2015 to September 2018 were included. Studies of patients with spinal instrumentation or studies with suboptimal image quality, as well as postgadolinium studies and studies of patients with scoliosis, were excluded. Axial T2-weighted and sagittal T1-weighted images were used. Studies were split into an internal training set (80%), validation set (9%), and test set (11%). Training data were labeled by four radiologists using predefined gradings (normal, mild, moderate, and severe). A two-component DL model was developed. First, a convolutional neural network (CNN) was trained to detect the region of interest (ROI), with a second CNN for classification. An internal test set was labeled by a musculoskeletal radiologist with 31 years of experience (reference standard) and two subspecialist radiologists (radiologist 1: A.M., 5 years of experience; radiologist 2: J.T.P.D.H., 9 years of experience). DL model performance on an external test set was evaluated. Detection recall (in percentage), interrater agreement (Gwet κ), sensitivity, and specificity were calculated. Results Overall, 446 MRI lumbar spine studies were analyzed (446 patients; mean age ± standard deviation, 52 years ± 19; 240 women), with 396 patients in the training (80%) and validation (9%) sets and 50 (11%) in the internal test set. For internal testing, DL model and radiologist central canal recall were greater than 99%, with reduced neural foramina recall for the DL model (84.5%) and radiologist 1 (83.9%) compared with radiologist 2 (97.1%) (P < .001). For internal testing, dichotomous classification (normal or mild vs moderate or severe) showed almost-perfect agreement for both radiologists and the DL model, with respective κ values of 0.98, 0.98, and 0.96 for the central canal; 0.92, 0.95, and 0.92 for lateral recesses; and 0.94, 0.95, and 0.89 for neural foramina (P < .001). External testing with 100 MRI scans of lumbar spines showed almost perfect agreement for the DL model for dichotomous classification of all ROIs (κ, 0.95-0.96; P < .001). Conclusion A deep learning model showed comparable agreement with subspecialist radiologists for detection and classification of central canal and lateral recess stenosis, with slightly lower agreement for neural foraminal stenosis at lumbar spine MRI. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Hayashi in this issue.

Drosophila CaV2 channels harboring human migraine mutations cause synapse hyperexcitability that can be suppressed by inhibition of a Ca2+ store release pathway.

Gain-of-function mutations in the human CaV2.1 gene CACNA1A cause familial hemiplegic migraine type 1 (FHM1). To characterize cellular problems potentially triggered by CaV2.1 gains of function, we engineered mutations encoding FHM1 amino-acid substitutions S218L (SL) and R192Q (RQ) into transgenes of Drosophila melanogaster CaV2/cacophony. We expressed the transgenes pan-neuronally. Phenotypes were mild for RQ-expressing animals. By contrast, single mutant SL- and complex allele RQ,SL-expressing animals showed overt phenotypes, including sharply decreased viability. By electrophysiology, SL- and RQ,SL-expressing neuromuscular junctions (NMJs) exhibited enhanced evoked discharges, supernumerary discharges, and an increase in the amplitudes and frequencies of spontaneous events. Some spontaneous events were gigantic (10-40 mV), multi-quantal events. Gigantic spontaneous events were eliminated by application of TTX-or by lowered or chelated Ca2+-suggesting that gigantic events were elicited by spontaneous nerve firing. A follow-up genetic approach revealed that some neuronal hyperexcitability phenotypes were reversed after knockdown or mutation of Drosophila homologs of phospholipase Cß (PLCß), IP3 receptor, or ryanodine receptor (RyR)-all factors known to mediate Ca2+ release from intracellular stores. Pharmacological inhibitors of intracellular Ca2+ store release produced similar effects. Interestingly, however, the decreased viability phenotype was not reversed by genetic impairment of intracellular Ca2+ release factors. On a cellular level, our data suggest inhibition of signaling that triggers intracellular Ca2+ release could counteract hyperexcitability induced by gains of CaV2.1 function.

Homeostatic control of Drosophila neuromuscular junction function.

The ability to adapt to changing internal and external conditions is a key feature of biological systems. Homeostasis refers to a regulatory process that stabilizes dynamic systems to counteract perturbations. In the nervous system, homeostatic mechanisms control neuronal excitability, neurotransmitter release, neurotransmitter receptors, and neural circuit function. The neuromuscular junction (NMJ) of Drosophila melanogaster has provided a wealth of molecular information about how synapses implement homeostatic forms of synaptic plasticity, with a focus on the transsynaptic, homeostatic modulation of neurotransmitter release. This review examines some of the recent findings from the Drosophila NMJ and highlights questions the field will ponder in coming years.

Cross-modal tactile-visual neural representations in bumble bees.

The centuries-old philosophical question posed by William Molyneux and referred to by John Locke (1689) concerns the transfer of object information from touch to vision. Solvi, Al-Khudhairy, and Chittka (2020) tested this question comparatively in bumble bees and found evidence of crossmodal object recognition between touch and vision.

Redefining community based on place attachment in a connected world.

The concept of community is often used in environmental policy to foster environmental stewardship and public participation, crucial prerequisites of effective management. However, prevailing conceptualizations of community based on residential location or resource use are limited with respect to their utility as surrogates for communities of shared environment-related interests, and because of the localist perspective they entail. Thus, addressing contemporary sustainability challenges, which tend to involve transnational social and environmental interactions, urgently requires additional approaches to conceptualizing community that are compatible with current globalization. We propose a framing for redefining community based on place attachment (i.e., the bonds people form with places) in the context of Australia's Great Barrier Reef, a World Heritage Area threatened by drivers requiring management and political action at scales beyond the local. Using data on place attachment from 5,403 respondents residing locally, nationally, and internationally, we identified four communities that each shared a type of attachment to the reef and that spanned conventional location and use communities. We suggest that as human-environment interactions change with increasing mobility (both corporeal and that mediated by communication and information technology), new types of people-place relations that transcend geographic and social boundaries and do not require ongoing direct experience to form are emerging. We propose that adopting a place attachment framing to community provides a means to capture the neglected nonmaterial bonds people form with the environment, and could be leveraged to foster transnational environmental stewardship, critical to advancing global sustainability in our increasingly connected world.

Microwave Intensified Synthesis: Batch and Flow Chemistry.

Many studies have been conducted on organic and inorganic synthesis by microwave heating owing to its special heating mechanism, leading to improved reaction rate, higher purity and yields. We specifically demonstrated microwave heating in the fabrication of nanoparticles and polyester. By fine-tuning the microwave and experimental parameters, the materials prepared have shown excellent physical and bio-properties, e. g. narrow particle size distribution, controlled morphology, varied molecular structure and so forth. We further highlight the recent procedure of using fluidic reactors on preparing both metals and metal oxides nanoparticles. The experimental design strategies and fundamentals of the microwave interaction with chemicals are presented. Furthermore, the key factors and issues facing in this area are also discussed.

The impact of varying cluster size in cross-sectional stepped-wedge cluster randomised trials.

BACKGROUND: Cluster randomised trials with unequal sized clusters often have lower precision than with clusters of equal size. To allow for this, sample sizes are inflated by a modified version of the design effect for clustering. These inflation factors are valid under the assumption that randomisation is stratified by cluster size. We investigate the impact of unequal cluster size when that constraint is relaxed, with particular focus on the stepped-wedge cluster randomised trial, where this is more difficult to achieve. METHODS: Assuming a multi-level mixed effect model with exchangeable correlation structure for a cross-sectional design, we use simulation methods to compare the precision for a trial with clusters of unequal size to a trial with clusters of equal size (relative efficiency). For a range of scenarios we illustrate the impact of various design features (the cluster-mean correlation - a function of the intracluster correlation and the cluster size, the number of clusters, number of randomisation sequences) on the average and distribution of the relative efficiency. RESULTS: Simulations confirm that the average reduction in precision, due to varying cluster sizes, is smaller in a stepped-wedge trial compared to the parallel trial. However, the variance of the distribution of the relative efficiency is large; and is larger under the stepped-wedge design compared to the parallel design. This can result in large variations in actual power, depending on the allocation of clusters to sequences. Designs with larger variations in cluster sizes, smaller number of clusters and studies with smaller cluster-mean correlations (smaller cluster sizes or smaller intra-cluster correlation) are particularly at risk. CONCLUSION: The actual realised power in a stepped-wedge trial might be substantially higher or lower than that estimated. This is particularly important when there are a small number of clusters or the variability in cluster sizes is large. Constraining the randomisation on cluster size, where feasible, might mitigate this effect.

Low food availability during gestation enhances offspring post-natal growth, but reduces survival, in a viviparous lizard.

The environment experienced by a mother can have profound effects on the fitness of her offspring (i.e., maternal effects). Maternal effects can be adaptive when the developmental environments experienced by offspring promote phenotypes that provide fitness benefits either via matching offspring phenotype to the post-developmental environment (also known as anticipatory maternal effects) or through direct effects on offspring growth and survival. We tested these hypotheses in a viviparous lizard using a factorial experimental design in which mothers received either high or low amounts of food during gestation, and resultant offspring were raised on either high or low amounts of food post-birth. We found no effect of food availability during gestation on reproductive traits of mothers or offspring traits at birth. However, offspring from mothers who received low food during gestation exhibited a greater increase in condition in the post-birth period, suggesting some form of priming of offspring by mothers to cope with an anticipated poor environment after birth. Offspring that received low food during gestation were also more likely to die, suggesting a trade-off for this accelerated growth. There were also significant effects of post-birth food availability on offspring snout-vent length and body condition growth, with offspring with high food availability post birth doing better. However, the effects of the pre- and post-natal resource evnironment on offspring growth were independent on one another, therefore, providing no support for the presence of anticipatory maternal effects in the traditional sense.

Sequelae of bilateral luxatio erecta in the acute post-reduction period demonstrated by MRI: a case report and literature review.

Luxatio erecta humeri (LEH), also known as inferior shoulder dislocation, is uncommon, comprising about 0.5% of all cases of shoulder dislocation. Synchronous bilateral LEH is exceedingly rare and, to our knowledge, there are no descriptions of axillary nerve injury on magnetic resonance imaging (MRI) following LEH. We present a case of traumatic bilateral LEH in a 59-year-old woman who fell from a fast-moving mobility scooter and sustained direct axial loading forces on the fully abducted shoulders. Both shoulders were successfully reduced using the traction-countertraction technique in the emergency department. In this article, we describe the characteristic features of LEH on plain radiography and the pattern of acute soft-tissue injuries on MRI. We emphasize the importance of reviewing the axillary neurovascular bundle, which by virtue of its location beneath the shoulder joint, is prone to injury in inferior shoulder dislocation and thus has a substantial impact on functional recovery. This important complication is unfortunately not routinely examined by radiologists, partly because of the paucity of literature highlighting its clinical significance.