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Drones offer a a unique survey platform that can operate below cloud cover and acquire very high spatial resolution datasets in near real-time. Studies have demonstrated that drones can be used for mapping over water using the Direct Georeferencing approach. However, this method is typically only feasible with high-end drones equipped with highly accurate GNSS/IMU systems. Moreover, placing targets over water to improve accuracy in post-processing can be challenging, further exacerbating this limitation. In this study, we developed an Assisted Direct Georeferencing method which combines the advantages of traditional Bundle Adjustment (BA) and Direct Georeferencing to overcome these challenges. Our approach utilizes BA over feature-rich segments of the drone trajectory, such as the shoreline, and DG in featureless areas, such as over water. To simulate a water-type environment or surface for our early tests, synthetic datasets have been created using Python for theoretical analysis. We then conducted a theoretical assessment of our approach under low and high variability attitude measurements. Our findings revealed that our methodology performs well under low variability attitude measurements, where wind conditions are close to optimal with an R-square value of 0.93. However, our model performs poorly under high variability attitude measurements, with an R-square value of only 0.028. These results suggest that Assisted Direct Georeferencing can serve as an alternative to high-end drones and Direct Georeferencing for water mapping applications in most standard. The findings from this theoretical assessment provide valuable insights into the achievable accuracy, error budgets, and limitations of the proposed model.

Drone technology has shown the potential to act as the middle ground between satellite, light aircraft, and terrestrial or in-situ methods. However, featureless terrain such as water poses a challenge when it comes to drone mapping. The main challenge is identifying matching points to combine overlapping images into a single dataset. In particular, because traditional methods such as Structure from Motion (SfM) is dependent on tie point collection, its usage over featureless terrain is almost impossible. In solving this problem, we propose that the use of Direct Georeferencing (DG) in registering images be explored as a potential method and we propose a method for correcting errors due to tilt with low-cost IMUs. This study first assesses the accuracy of direct georeferencing using low-cost Inertial Measurement Units (IMU) and Global Navigational Satellite System (GNSS) providing analysis of the error sources associated with direct georeferencing and then demonstrates new approaches to minimize them. To best simulate a water type environment or surface for the initial studies, a drone survey was conducted on flat farmland and a POSE analysis was performed. We then processed the images using direct georeferencing and then compared our error minimisation method to standard Bundle Block Adjustment with GCPs and again with no GCPs. Results showed that using the method proposed in this study helped reduce the Mean Absolute Error associated with direct georeferencing by 54%. These initial results show a clear potential for mapping over inland water using direct georeferencing.

Abstract Axions are well-motivated candidates for dark matter. Recently, much interest has focused on the detection of photons produced by the resonant conversion of axion dark matter in neutron star magnetospheres. Various groups have begun to obtain radio data to search for the signal, however, more work is needed to obtain a robust theory prediction for the corresponding radio lines. In this work we derive detailed properties for the signal, obtaining both the line shape and time-dependence. The principal physical effects are from refraction in the plasma as well as from gravitation which together lead to substantial lensing which varies over the pulse period. The time-dependence from the co-rotation of the plasma with the pulsar distorts the frequencies leading to a Doppler broadened signal whose width varies in time. For our predictions, we trace curvilinear rays to the line of sight using the full set of equations from Hamiltonian optics for a dispersive medium in curved spacetime. Thus, for the first time, we describe the detailed shape of the line signal as well as its time dependence, which is more pronounced compared to earlier results. Our prediction of the features of the signal will be essential for this kind of dark matter search.

Opioids targeting mu;μ (MOP) receptors produce analgesia in the peri-operative period and palliative care. They also produce side effects including respiratory depression, tolerance/dependence and addiction. The N/OFQ opioid receptor (NOP) also produces analgesia but is devoid of the major MOP side effects. Evidence exists for MOP-NOP interaction and mixed MOP-NOP ligands produce analgesia with reduced side effects. We have generated a HEKMOP/NOP human expression system and used bivalent MOP-NOP and fluorescent ligands to (i) probe for receptor interaction and (ii) consequences of that interaction. We used HEKMOP/NOP cells and two bivalent ligands; Dermorphin-N/OFQ (MOP agonist-NOP agonist; DeNO) and Dermorphin-UFP101 (MOP agonist-NOP antagonist; De101). We have determined receptor binding profiles, GTPγ[35S] binding, cAMP formation and ERK1/2 activation. We have also probed MOP and NOP receptor interactions in HEK cells and hippocampal neurones using the novel MOP fluorescent ligand, DermorphinATTO488 and the NOP fluorescent ligand N/OFQATTO594. In HEKMOP/NOP MOP ligands displaced NOP binding and NOP ligands displaced MOP binding. Using fluorescent probes in HEKMOP/NOP cells we demonstrated MOP-NOP probe overlap and a FRET signal indicating co-localisation. MOP-NOP were also co-localised in hippocampal tissue. In GTPγ[35S] and cAMP assays NOP stimulation shifted the response to MOP rightwards. At ERK1/2 the response to bivalent ligands generally peaked later. We provide evidence for MOP-NOP interaction in recombinant and native tissue. NOP activation reduces responsiveness of MOP activation; this was shown with conventional and bivalent ligands.

Abstract Background Antimicrobial stewardship programs (ASPs) have been shown to reduce inappropriate antimicrobial use and its consequences. However, these programs lack legislative requirements in many places and it can be difficult to determine what human resources are required for these programs and how to create a business case to present to hospital administrators for program funding. The objectives of the current paper were to review legislative requirements and outline human resource requirements for ASPs, and to create a base business case for ASPs. Methods A working group of antimicrobial stewardship experts from across Canada met to discuss the necessary components for creation of a business case for antimicrobial stewardship. A narrative review of the literature of the regulatory requirements and human resource recommendations for ASPs was conducted. Informed by the review and using a consensus decision-making process, the expert working group developed human resource recommendations based on a 1000 bed acute care health care facility in Canada. A spreadsheet based business case model for ASPs was also created. Results Legislative and /or regulatory requirements for ASPs were found in 2 countries and one state jurisdiction. The literature review and consensus development process recommended the following minimum human resources complement: 1 physician, 3 pharmacists, 0.5 program administrative and coordination support, and 0.4 data analyst support as full time equivalents (FTEs) per 1000 acute care beds. Necessary components for the business case model, including the human resource requirements, were determined to create a spreadsheet based model. Conclusions There is evidence to support the negative outcomes of inappropriate antimicrobial use as well as the benefits of ASPs. Legislative and /or regulatory requirements for ASPs are not common. The available evidence for human resource recommendations for ASPs using a narrative review process was examined and a base business case modelling scenario was created. As regulatory requirements for ASPs increase, it will be necessary to create accurate business cases for ASPs in order to obtain the necessary funding to render these programs successful.

Three-dimensional (3D) analysis of the face is required for the assessment of changes following surgery, to monitor the progress of pathological conditions and for the evaluation of facial growth. Sophisticated methods have been applied for the evaluation of facial morphology, the most common being dense surface correspondence. The method depends on the application of a mathematical facial mask known as the generic facial mesh for the evaluation of the characteristics of facial morphology. This study evaluated the accuracy of the conformation of generic mesh to the underlying facial morphology. The study was conducted on 10 non-patient volunteers. Thirty-four 2-mm-diameter self-adhesive, non-reflective markers were placed on each face. These were readily identifiable on the captured 3D facial image, which was captured by Di3D stereophotogrammetry. The markers helped in minimising digitisation errors during the conformation process. For each case, the face was captured six times: at rest and at the maximum movements of four facial expressions. The 3D facial image of each facial expression was analysed. Euclidean distances between the 19 corresponding landmarks on the conformed mesh and on the original 3D facial model provided a measure of the accuracy of the conformation process. For all facial expressions and all corresponding landmarks, these distances were between 0.7 and 1.7 mm. The absolute mean distances ranged from 0.73 to 1.74 mm. The mean absolute error of the conformation process was 1.13 ± 0.26 mm. The conformation of the generic facial mesh is accurate enough for clinical trial proved to be accurate enough for the analysis of the captured 3D facial images.

Abstract The Greater Fifth Ward (GFW) is a Northeast Houston, Texas, neighborhood with a legacy of industrial contamination and a confirmed cancer cluster. To understand self-rated health in the GFW, community-based participatory research (CBPR), was used to promote the inclusion of all partners. CBPR involves the community during each stage of the research process from design to research dissemination. A complete census was conducted, and 114 surveys were obtained in the environmental justice (EJ) community from July to November 2021. EJ communities shoulder an unfair burden of environmental exposures, pollution, and poor built environments. Mental and physical health were measured using the validated 12-item Short Form Health Survey (SF-12v2). We posited that the Black or African American (Black/AA) community would have lower mental composite scores (MCS) and physical composite scores (PCS) compared to the nation and their White counterparts. The MCS and PCS were calculated and compared against the national mean. Overall, participants had higher MCS and lower PCS than the national mean. Black/AA males and females had lower MCS compared to their White counterparts. White females had the lowest PCS among all respondents, significantly lower than the national average. MCS was lower among those who lived in the neighborhood longer. Burdens from pollution may impact residents’ health and perceived health. Targeted interventions or programs that improve mental or physical health would benefit this community and other inequitably burdened neighborhoods.

Abstract Stable upland habitats in arid zone biomes are often characterised by locally endemic lineages. Explanations for this pattern include habitat or substrate specialisation (ecological specialisation) or intensifying aridity driving retreat into climatically buffered habitats (climatic refugia). Here we present an analysis of these alternative models using genetic, morphological and climate data for Diplodactylus galeatus, a gecko from central Australia that occurs in a series of isolated populations associated with dissected tablelands and mountain ranges. Analyses of mtDNA and SNP data support four distinct lineages, and dating analyses suggest divergence through the Pliocene. Morphological data show slight differences across lineages. Investigation of climate niche shows that two lineages are restricted to areas more arid than the intervening uninhabited region. These data suggest that specialisation to rocky substrates, potentially with subsequent paleo-erosion of dissected tablelands after a Pliocene wet pulse, was the key driver of divergence in this clade. Based on their deep genetic divergence, and differences in morphology and pattern, we recognise two isolated populations as new species.

The use of depolarization lidar to measure atmospheric volume depolarization ratio (VDR) is a common technique to classify cloud phase (liquid or ice). Previous work using a machine learning framework, applied to peak properties derived from co-polarized attenuated backscatter data, has been demonstrated to effectively detect supercooled-liquid-water-containing clouds (SLCCs). However, the training data from Davis Station, Antarctica, include no warm liquid water clouds (WLWCs), potentially limiting the model's accuracy in regions where WLWCs are present. In this work, we apply the same framework used on the Davis data to a 9-month micro-pulse lidar dataset collected in Ōtautahi / Christchurch, Aotearoa / New Zealand, a location which includes WLWC. We then evaluate the results relative to a reference VDR cloud-phase mask. We found that the Davis model performed relatively poorly at detecting SLCC with a recall score of 0.18, often misclassifying WLWC as SLCC. The performance of our new model, trained using data from Ōtautahi / Christchurch, displays recall scores as high as 0.88 for identification of SLCC, although it generally underestimates SLCC occurrence. The overall performance of the new model highlights the effectiveness of the machine learning technique when appropriate training data relevant to the location are used.

Abstract Yield gap analysis is used to characterize the untapped production potential of cropping systems. With emerging large-n agronomic datasets and data science methods, pathways for narrowing yield gaps can be identified that provide actionable insights into where and how cropping systems can be sustainably intensified. Here we characterize the contributing factors to rice yield gaps across seven Indian states, with a case study region used to assess the power of intervention targeting. Primary yield constraints in the case study region were nitrogen and irrigation, but scenario analysis suggests modest average yield gains with universal adoption of higher nitrogen rates. When nitrogen limited fields are targeted for practice change (47% of the sample), yield gains are predicted to double. When nitrogen and irrigation co-limitations are targeted (20% of the sample), yield gains more than tripled. Results suggest that analytics-led strategies for crop intensification can generate transformative advances in productivity, profitability, and environmental outcomes.

Knowledge of the factors influencing nutrient-limited subtropical maize yield and subsequent prediction is crucial for effective nutrient management, maximizing profitability, ensuring food security, and promoting environmental sustainability. We analyzed data from nutrient omission plot trials (NOPTs) conducted in 324 farmers' fields across ten agroecological zones (AEZs) in the Eastern Indo-Gangetic Plains (EIGP) of Bangladesh to explain maize yield variability and identify variables controlling nutrient-limited yields. An additive main effect and multiplicative interaction (AMMI) model was used to explain maize yield variability with nutrient addition. Interpretable machine learning (ML) algorithms in automatic machine learning (AutoML) frameworks were subsequently used to predict attainable yield relative nutrient-limited yield (RY) and to rank variables that control RY. The stack-ensemble model was identified as the best-performing model for predicting RYs of N, P, and Zn. In contrast, deep learning outperformed all base learners for predicting RYK. The best model's square errors (RMSEs) were 0.122, 0.105, 0.123, and 0.104 for RYN, RYP, RYK, and RYZn, respectively. The permutation-based feature importance technique identified soil pH as the most critical variable controlling RYN and RYP. The RYK showed lower in the eastern longitudinal direction. Soil N and Zn were associated with RYZn. The predicted median RY of N, P, K, and Zn, representing average soil fertility, was 0.51, 0.84, 0.87, and 0.97, accounting for 44, 54, 54, and 48% upland dry season crop area of Bangladesh, respectively. Efforts are needed to update databases cataloging variability in land type inundation classes, soil characteristics, and INS and combine them with farmers' crop management information to develop more precise nutrient guidelines for maize in the EIGP.

Speleothems (cave deposits), used for palaeoenvironmental reconstructions, are deposited from cave drip water. Differentiating climate and karst processes within a drip-water signal is fundamental for the correct identification of palaeoenvironmental proxies and ultimately their interpretation within speleothem records. We investigate the potential use of trace element and stable oxygen-isotope (δ18O) variations in cave drip water as palaeorainfall proxies in an Australian alpine karst site. This paper presents the first extensive hydrochemical and δ18O dataset from Harrie Wood Cave, in the Snowy Mountains, south-eastern (SE) Australia. Using a 7-year long rainfall δ18O and drip-water Ca, Cl, Mg / Ca, Sr / Ca and δ18O datasets from three drip sites, we determined that the processes of mixing, dilution, flow path change, carbonate mineral dissolution and prior calcite precipitation (PCP) accounted for the observed variations in the drip-water geochemical composition. We identify that the three monitored drip sites are fed by fracture flow from a well-mixed epikarst storage reservoir, supplied by variable concentrations of dissolved ions from soil and bedrock dissolution. We constrained the influence of multiple processes and controls on drip-water composition in a region dominated by El Niño–Southern Oscillation (ENSO). During the El Niño and dry periods, enhanced PCP, a flow path change and dissolution due to increased soil CO2 production occurred in response to warmer than average temperatures in contrast to the La Niña phase, where dilution dominated and reduced PCP were observed. We present a conceptual model, illustrating the key processes impacting the drip-water chemistry. We identified a robust relationship between ENSO and drip-water trace element concentrations and propose that variations in speleothem Mg / Ca and Sr / Ca ratios may be interpreted to reflect palaeorainfall conditions. These findings inform palaeorainfall reconstruction from speleothems regionally and provide a basis for palaeoclimate studies globally, in regions where there is intermittent recharge variability.

Background: The transition from school to adult life is challenging for young people with intellectual disability. The study aimed to explore how young people with intellectual disability themselves experience the transition from school to adult life. Methods: A co-designed, qualitative study. Thematic data analysis of qualitative survey responses, semi-structured interviews, and focus groups with 27 young people with intellectual disability in three Australian states. Results: Participants found transition planning at school inconsistent or lacking and felt excluded from decision-making about their lives. Accessing meaningful services, training, and employment beyond volunteering was challenging and enduring, leaving participants in perpetual state of transition, feeling lost, and missing out of post-school adult milestones. Conclusions: Policy, system, and service gaps must be addressed with a nationally consistent and accountable approach that truly supports choice and control for young people with intellectual disability in transitioning from school into meaningful adult lives.

Abstract To achieve coordinated functions, fluidic soft robots typically rely on multiple input lines for the independent inflation and deflation of each actuator. Fluidic actuators are controlled by rigid electronic pneumatic valves, restricting the mobility and compliance of the soft robot. Recent developments in soft valve designs have shown the potential to achieve a more integrated robotic system, but are limited by high energy consumption and slow response time. In this work, we present an electropermanent magnet (EPM) valve for electronic control of pneumatic soft actuators that is activated through microsecond electronic pulses. The valve incorporates a thin channel made from thermoplastic films. The proposed valve (3 × 3 × 0.8 cm, 2.9 g) can block pressure up to 146 kPa and negative pressures up to –100 kPa with a response time of less than 1 s. Using the EPM valves, we demonstrate the ability to switch between multiple operation sequences in real time through the control of a six-DoF robot capable of grasping and hopping with a single pressure input. Our proposed onboard control strategy simplifies the operation of multi-pressure systems, enabling the development of dynamically programmable soft fluid-driven robots that are versatile in responding to different tasks.

Abstract Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021–22 and 2022–23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021–22 and 12 out of 18 models in 2022–23. Averaging across all forecast targets, the FluSight ensemble is the 2nd most accurate model measured by WIS in 2021–22 and the 5th most accurate in the 2022–23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

Abstract Human learning varies greatly among individuals and is related to the microstructure of major white matter tracts in several learning domains, yet the impact of the existing microstructure of white matter tracts on future learning outcomes remains unclear. We employed a machine-learning model selection framework to evaluate whether existing microstructure might predict individual differences in learning a sensorimotor task, and further, if the mapping between tract microstructure and learning was selective for learning outcomes. We used diffusion tractography to measure the mean fractional anisotropy (FA) of white matter tracts in 60 adult participants who then practiced drawing a set of 40 unfamiliar symbols repeatedly using a digital writing tablet. We measured drawing learning as the slope of draw duration over the practice session and measured visual recognition learning for the symbols using an old/new 2-AFC task. Results demonstrated that tract microstructure selectively predicted learning outcomes, with left hemisphere pArc and SLF3 tracts predicting drawing learning and the left hemisphere MDLFspl predicting visual recognition learning. These results were replicated using repeat, held-out data and supported with complementary analyses. Results suggest that individual differences in the microstructure of human white matter tracts may be selectively related to future learning outcomes.

Abstract Background Clinical prediction models can help identify high-risk patients and facilitate timely interventions. However, developing such models for rare diseases presents challenges due to the scarcity of affected patients for developing and calibrating models. Methods that pool information from multiple sources can help with these challenges. Methods We compared three approaches for developing clinical prediction models for population screening based on an example of discriminating a rare form of diabetes (Maturity-Onset Diabetes of the Young - MODY) in insulin-treated patients from the more common Type 1 diabetes (T1D). Two datasets were used: a case-control dataset (278 T1D, 177 MODY) and a population-representative dataset (1418 patients, 96 MODY tested with biomarker testing, 7 MODY positive). To build a population-level prediction model, we compared three methods for recalibrating models developed in case-control data. These were prevalence adjustment (“offset”), shrinkage recalibration in the population-level dataset (“recalibration”), and a refitting of the model to the population-level dataset (“re-estimation”). We then developed a Bayesian hierarchical mixture model combining shrinkage recalibration with additional informative biomarker information only available in the population-representative dataset. We developed a method for dealing with missing biomarker and outcome information using prior information from the literature and other data sources to ensure the clinical validity of predictions for certain biomarker combinations. Results The offset, re-estimation, and recalibration methods showed good calibration in the population-representative dataset. The offset and recalibration methods displayed the lowest predictive uncertainty due to borrowing information from the fitted case-control model. We demonstrate the potential of a mixture model for incorporating informative biomarkers, which significantly enhanced the model’s predictive accuracy, reduced uncertainty, and showed higher stability in all ranges of predictive outcome probabilities. Conclusion We have compared several approaches that could be used to develop prediction models for rare diseases. Our findings highlight the recalibration mixture model as the optimal strategy if a population-level dataset is available. This approach offers the flexibility to incorporate additional predictors and informed prior probabilities, contributing to enhanced prediction accuracy for rare diseases. It also allows predictions without these additional tests, providing additional information on whether a patient should undergo further biomarker testing before genetic testing.

Deep Reinforcement Learning is a branch of artificial intelligence that uses artificial neural networks to model reward-based learning as it occurs in biological agents. Here we modify a Deep Reinforcement Learning approach by imposing a suppressive effect on the connections between neurons in the artificial network—simulating the effect of dendritic spine loss as observed in major depressive disorder (MDD). Surprisingly, this simulated spine loss is sufficient to induce a variety of MDD-like behaviors in the artificially intelligent agent, including anhedonia, increased temporal discounting, avoidance, and an altered exploration/exploitation balance. Furthermore, simulating alternative and longstanding reward-processing-centric conceptions of MDD (dysfunction of the dopamine system, altered reward discounting, context-dependent learning rates, increased exploration) does not produce the same range of MDD-like behaviors. These results support a conceptual model of MDD as a reduction of brain connectivity (and thus information-processing capacity) rather than an imbalance in monoamines—though the computational model suggests a possible explanation for the dysfunction of dopamine systems in MDD. Reversing the spine-loss effect in our computational MDD model can lead to rescue of rewarding behavior under some conditions. This supports the search for treatments that increase plasticity and synaptogenesis, and the model suggests some implications for their effective administration.

The fate of chemical of concern is not yet fully understood during treatment of impaired waters. The aim of this paper is to assess the impact of different organic-based fouling layers on the removal of a large range of trace organics. Both model and real water samples (mixed with trace organic contaminants at environmental concentration of 2 μg l−1) were used to simulate fouling in nanofiltration under controlled environment. The new and fouled membranes were systematically characterised for surface charge, hydrophobicity and roughness. It was observed that fouling generally reduced the membrane surface charge; however, the alterations of the membrane hydrophobicity and surface roughness were dependent on the foulants composition. The rejection of charged trace organics was observed to be improved due to the increased electrostatic repulsion by fouled membranes and the adsorption of the trace organic chemicals onto organic matters. On the other hand, the removal of nonionic compounds decreased when fouling occurred, due to the presence of cake enhanced concentration polarization. The fouling layer structure was found to play an important role in the rejection of the trace organic compounds.

Abstract Objective Huntington's disease (HD) is an inherited neurodegenerative disease involving progressive motor abnormalities, cognitive decline, and psychiatric disturbances. Depression and cognitive difficulties are among the most impactful symptoms of HD, yet the pathogenesis of these symptoms is not fully understood. HD involves low‐level chronic inflammation and dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis, which are linked to depression and cognitive impairment in non‐HD populations. However, previous research on the relationships of these pathologies with depression and cognition in HD is limited and inconsistent. Methods Fifty‐three adults with the HD gene expansion (30 premanifest and 23 manifest) completed measures of depression and cognitive functioning. Forty‐eight out of 53 participants provided hair samples for quantification of cortisol, and 34 participants provided blood samples for quantification of peripheral inflammatory cytokines. We examined the associations of four cytokines (interleukin [IL]‐6, IL‐10, IL‐1β, and tumor necrosis factor [TNF]‐α) and cortisol levels with depression and cognitive scores. Results In unadjusted models, higher levels of plasma IL‐6, IL‐10, and TNF‐α correlated with higher depression scores, and higher levels of IL‐10 and TNF‐α correlated with poorer cognitive performance. After controlling for age, sex, and body mass index, only the correlations of IL‐10 with depression and cognitive performance remained significant. No correlations were evident with hair cortisol. Interpretations Peripheral inflammation is associated with depression symptoms and cognitive impairment in HD. Our findings suggest that interactions between the immune and nervous systems are important in HD, and highlight the potential of chronic inflammation as a therapeutic target in early stages of HD.

To understand the transmissibility and spread of infectious diseases, epidemiologists turn to estimates of the instantaneous reproduction number. While many estimation approaches exist, their utility may be limited. Challenges of surveillance data collection, model assumptions that are unverifiable with data alone, and computationally inefficient frameworks are critical limitations for many existing approaches. We propose a discrete spline-based approach that solves a convex optimization problem-Poisson trend filtering-using the proximal Newton method. It produces a locally adaptive estimator for instantaneous reproduction number estimation with heterogeneous smoothness. Our methodology remains accurate even under some process misspecifications and is computationally efficient, even for large-scale data. The implementation is easily accessible in a lightweight R package rtestim.

Calcium plays a crucial role in the heart’s electrical conduction system and facilitating the contraction of cardiac muscles. Hypocalcemia can result in electrocardiogram findings such as a prolonged QTC interval and eventually torsade de pointes, which in severe cases can progress to cardiac arrest. In cases of B-cell lymphoma, hypocalcemia may arise from various factors. Tumor infiltration can disrupt calcium homeostasis by affecting the parathyroid glands or bone tissue. Acidosis in the context of B-cell lymphoma can cause significant cardiovascular adverse effects. It will reduce peripheral vascular resistance and cardiac muscle contractility, promote dysrhythmias, and disturb oxygen uptake in the lungs. These combined effects markedly compromise cardiac function, increasing the likelihood of cardiac arrest. These mechanisms necessitate comprehensive management strategies in B-cell lymphoma patients. In this case report we present a case of cardiac arrest in a 59-year-old female woman with hypocalcemia and lactic acidosis secondary to B-cell lymphoma.

We document 1394 extreme precipitation events (EPEs) over Aotearoa New Zealand’s (ANZ) Regional Councils between March 1996 and December 2021. The characteristics of EPEs are documented using a novel spatio-temporal framework that diagnoses the peak intensity, duration, and accumulation of the EPE using the ERA-5 and MERRA-2 reanalysis products. Properties of EPEs were evaluated according to region across ANZ, and clear regional differences are highlighted. In particular, it is found that the duration of an EPE has a stronger influence than the peak intensity on the total accumulated precipitation across all regions and precipitation event types (large-scale or convective). Since larger precipitation accumulations have greater potential to cause extensive flooding over larger areas, an important implication is the need for numerical weather prediction in ANZ to forecast the duration of an intense precipitation event adequately in order to improve emergency preparedness.

Abstract Background More than 650 million people are obese (BMI > 30) worldwide, which increases their risk for several metabolic diseases and cancer. While cachexia and obesity are at opposite ends of the weight spectrum, leading many to suggest a protective effect of obesity against cachexia, mechanistic support for obesity's benefit is lacking. Given that obesity and cachexia are both accompanied by metabolic dysregulation, we sought to investigate the impact of obesity on skeletal muscle mass loss and mitochondrial dysfunction in murine cancer cachexia. Methods Male C57BL/6 mice were given a purified high fat or standard diet for 16 weeks before being implanted with 106 Lewis lung carcinoma (LLC) cells. Mice were monitored for 25 days, and hindlimb muscles were collected for cachexia indices and mitochondrial assessment via western blotting, high‐resolution respirometry and transmission electron microscopy (TEM). Results Obese LLC mice experienced significant tumour‐free body weight loss similar to lean (−12.8% vs. −11.8%, P = 0.0001) but had reduced survival (33.3% vs. 6.67%, χ2 = 10.04, P = 0.0182). Obese LLC mice had reduced muscle weights (−24%, P

Traumatic brain injuries (TBIs) and concussions are prevalent in collision sports, and there is evidence that levels of exposure to such sports may increase the risk of neurological abnormalities. Elevated levels of fluid-based biomarkers have been observed after concussions or among athletes with a history of participating in collision sports, and certain biomarkers exhibit sensitivity toward neurodegeneration. This study investigated a cohort of 28 male amateur athletes competing in ?Masters? competitions for persons >35 years of age. The primary objective of this study was to compare the levels of blood and saliva biomarkers associated with brain injury, inflammation, aging, and neurodegeneration between athletes with an extensive history of collision sport participation (i.e., median?=?27 years; interquartile range?=?18?44, minimum?=?8) and those with no history. Plasma proteins associated with neural damage and neurodegeneration were measured using Simoa? assays, and saliva was analyzed for markers associated with inflammation and telomere length using quantitative real-time polymerase chain reaction. There were no significant differences between collision and non-collision sport athletes for plasma levels of glial fibrillary acidic protein, neurofilament light, ubiquitin C-terminal hydrolase L1, tau, tau phosphorylated at threonine 181, and brain-derived neurotrophic factor. Moreover, salivary levels of genes associated with inflammation and telomere length were similar between groups. There were no significant differences between groups in symptom frequency or severity on the Sport Concussion Assessment Tool?5th Edition. Overall, these findings provide preliminary evidence that biomarkers associated with neural tissue damage, neurodegeneration, and inflammation may not exhibit significant alterations in asymptomatic amateur athletes with an extensive history of amateur collision sport participation.

Abstract Traumatic brain injury (TBI) is a key contributor to global morbidity that lacks effective treatments. Microbial infections are common in TBI patients, and their presence could modify the physiological response to TBI. It is estimated that one-third of the human population is incurably infected with the feline-borne parasite, Toxoplasma gondii, which can invade the central nervous system and result in chronic low-grade neuroinflammation, oxidative stress, and excitotoxicity—all of which are also important pathophysiological processes in TBI. Considering the large number of TBI patients that have a pre-existing T. gondii infection prior to injury, and the potential mechanistic synergies between the conditions, this study investigated how a pre-existing T. gondii infection modified TBI outcomes across acute, sub-acute and chronic recovery in male and female mice. Gene expression analysis of brain tissue found that neuroinflammation and immune cell markers were amplified in the combined T. gondii + TBI setting in both males and females as early as 2-h post-injury. Glutamatergic, neurotoxic, and oxidative stress markers were altered in a sex-specific manner in T. gondii + TBI mice. Structural MRI found that male, but not female, T. gondii + TBI mice had a significantly larger lesion size compared to their uninfected counterparts at 18-weeks post-injury. Similarly, diffusion MRI revealed that T. gondii + TBI mice had exacerbated white matter tract abnormalities, particularly in male mice. These novel findings indicate that a pre-existing T. gondii infection affects the pathophysiological aftermath of TBI in a sex-dependent manner, and may be an important modifier to consider in the care and prognostication of TBI patients.

The biogeochemical formation of dimethyl sulfide (DMS) from the Southern Ocean is complex, dynamic, and driven by physical, chemical, and biological processes. Such processes, produced by marine biogenic activity, are the dominant source of sulfate aerosol over the Southern Ocean. Using an atmosphere-only configuration of the United Kingdom Earth System Model (UKESM1-AMIP), we performed eight 10-year simulations for the recent past (2009–2018) during austral summer. We tested the sensitivity of atmospheric DMS to four oceanic DMS datasets and three DMS transfer velocity parameterizations. One oceanic DMS dataset was developed here from satellite chlorophyll a. We find that the choice of oceanic DMS dataset has a larger influence on atmospheric DMS than the choice of DMS transfer velocity. Simulations with linear transfer velocity parameterizations show a more accurate representation of atmospheric DMS concentration than those using quadratic relationships. This work highlights that the oceanic DMS and DMS transfer velocity parameterizations currently used in climate models are poorly constrained for the Southern Ocean region. Simulations using oceanic DMS derived from satellite chlorophyll a data, and when combined with a recently developed linear transfer velocity parameterization for DMS, show better spatial variability than the UKESM1 configuration. We also demonstrate that capturing large-scale spatial variability can be more important than large-scale interannual variability. We recommend that models use a DMS transfer velocity parameterization that was developed specifically for DMS and improvements to oceanic DMS spatial variability. Such improvements may provide a more accurate process-based representation of oceanic and atmospheric DMS, and therefore sulfate aerosol, in the Southern Ocean region.

Abstract The incretin hormones glucagon‐like peptide‐1 (GLP‐1) and glucose‐dependent insulinotropic polypeptide (GIP), are thought to be the main drivers of insulin secretion in individuals with sulfonylurea (SU)‐treated KCNJ11 permanent neonatal diabetes. The aim of this study was to assess for the first time the incretin hormone response to carbohydrate and protein/fat in adults with sulfonylurea‐treated KCNJ11 permanent neonatal diabetes compared with that of controls without diabetes. Participants were given a breakfast high in carbohydrate and an isocaloric breakfast high in protein/fat on two different mornings. Incremental area under the curve and total area under the curve (0‐240 minutes) for total GLP‐1 and GIP were compared between groups, using non‐parametric statistical methods. Post‐meal GLP‐1 and GIP secretion were similar in cases and controls, suggesting this process is adenosine triphosphate‐sensitive potassium channel‐independent. Future research will investigate whether treatments targeting the incretin pathway are effective in individuals with KCNJ11 permanent neonatal diabetes who do not have good glycemic control on sulfonylurea alone.

In a major Victorian hospital, dietitians observed that requests tomedical staff to prescribe nutritional supplements via themedication chart were inefficient. This led to delays in the deliveryof nutritional recommendations, thus compromising patients’nutritional status. Lean Methodology was applied to simplify theordering of patients’ nutritional supplements as medication(NSAM) by dietitians. A literature review was conducted. Directobservation and value stream mapping were used to identifyprocess time and wasted time related to NSAM prescription. Adetailed root cause analysis of identified issues was undertaken,followed by the development of an implementation plan. Thefollowing problems were identified: ordering process wascomplicated and not linear, delay in patient receiving NSAM (2.8days, range 0–23 days), and 60% repeat requests by the dietitian forNSAM. An implementation plan was developed which included:submission to the Medical Executive Committee to seekprescribing privileges for dietitians; dietetic competency trainingand credentialing, communication strategy, development ofprescribing and administering procedures; and ward education.Dietetic prescribing privileges were granted, implemented, andevaluation of this change in dietetic practice undertaken. Inconclusion, application of Lean Methodology enabled dietitians toclearly examine, in a systematic manner, delays, risks andinefficiencies with our current process of ordering NSAM. It led toa plan of action to improve quality of care to our patients, includingrenal patients, and reduce waste in our health care setting by timelyand appropriate commencement of NSAM.

Not available.

Study design We conducted a retrospective cross-sectional study including patients admitted to the adult critical care unit and started on the stress ulcer prophylaxis with a proton pump inhibitor (PPI) or histamine receptor 2 blocker (H2 blocker) with an aim to determine the prevalence of inappropriate continuation at discharge and associated factors.Result 3200 people were initiated on stress ulcer prophylaxis, and the medication was continued in 1666 patients upon discharge. Indication for long-term use was not found in 744 of 1666, with a 44% prevalence of inappropriate continuation. A statistically significant association was found with the following risk factors: discharge disposition (home vs other medical facilities, p=0.002), overall length of stay (more than 10 days vs less than or equal to 10 days, p

Background:. Studies comparing carpal tunnel release with ultrasound guidance (CTR-US) to mini-open CTR (mOCTR) are limited. This randomized trial compared the efficacy and safety of these techniques. Methods:. In this multicenter randomized trial, patients were randomized (2:1) to unilateral CTR-US or mOCTR. Outcomes included Boston Carpal Tunnel Questionnaire Symptom Severity Scale (BCTQ-SSS) and Functional Status Scale (BCTQ-FSS), numeric pain scale (0–10), EuroQoL-5 Dimension 5-Level (EQ-5D-5L), scar outcomes, and complications over 1 year. Results:. Patients received CTR-US (n = 94) via wrist incision (mean 6 mm) or mOCTR (n = 28) via palmar incision (mean 22 mm). Comparing CTR-US with mOCTR, the mean changes in BCTQ-SSS (−1.8 versus -1.8; P = 0.96), BCTQ-FSS (−1.0 versus −1.0; P = 0.75), numeric pain scale (−3.9 versus −3.8; P = 0.74), and EQ-5D-5L (0.13 versus 0.12; P = 0.79) over 1 year were comparable between groups. Freedom from scar sensitivity or pain favored CTR-US (95% versus 74%; P = 0.005). Complications occurred in 2.1% versus 3.6% of patients (P = 0.55), all within 3 weeks postprocedure. There was one revision surgery in the CTR-US group, and no revisions for persistent or recurrent symptoms in either group. Conclusions:. CTR-US and mOCTR demonstrated similar improvement in carpal tunnel syndrome symptoms and quality of life with comparable low complication rates over 1 year of follow-up. CTR-US was performed with a smaller incision and associated with less scar discomfort.

It is a fundamental duty of neuroscientists to discuss the results of research and related ethical implications. Engagement with neuroscience is especially critical for families with children affected by disorders such as drug resistant epilepsy (DRE) as they navigate complex decisions about innovations in treatment that increasingly include invasive neurotechnologies. Through an evidence-based, iterative, and value-guided approach, we created the short-form documentary film, Seizing Hope: High Tech Journeys in Pediatric Epilepsy, to delve into the relationship between experts with first-hand, lived experience – youth with DRE and caregivers – and physician experts as they weigh medical and ethical trade-offs on this landscape. We describe the co-creation and evolution of this film, screenings, and feedback. Survey responses from 385 viewers highlight new developments in technologies for the treatment of DRE, how families navigate choices for treatment with brain technology, and a sense of hope for the future for children with epilepsy as key attributes of this science communication piece.

Abstract Education, occupation, and an active lifestyle, comprising enhanced social, physical, and mental components are associated with improved cognitive functions in aged people and may delay the progression of various neurodegenerative diseases including Alzheimer’s disease. To investigate this protective effect, 3-month-old APPNL-G-F/NL-G-F mice were exposed to repeated single- or multi-domain cognitive training. Cognitive training was given at the age of 3, 6, & 9 months. Single-domain cognitive training was limited to a spatial navigation task. Multi-domain cognitive training consisted of a spatial navigation task, object recognition, and fear conditioning. At the age of 12 months, behavioral tests were completed for all groups. Then, mice were sacrificed, and their brains were assessed for pathology. APPNL-G-F/NL-G-F mice given multi-domain cognitive training compared to APPNL-G-F/NL-G-F control group showed an improvement in cognitive functions, reductions in amyloid load and microgliosis, and a preservation of cholinergic function. Additionally, multi-domain cognitive training improved anxiety in APPNL-G-F/NL-G-F mice as evidenced by measuring thigmotaxis behavior in the Morris water maze. There were mild reductions in microgliosis in the brain of APPNL-G-F/NL-G-F mice with single-domain cognitive training. These findings provide causal evidence for the potential of certain forms of cognitive training to mitigate the cognitive deficits in Alzheimer disease.

When General Chemistry at West Point switched from interactive lectures to guided inquiry, it provided an opportunity to examine what was expected of students in classrooms and on assessments. Learning objectives and questions on mid-term exams for four semesters of General Chemistry I (two traditional semesters and two guided inquiry semesters) were analyzed by the Cognitive Process and Knowledge dimensions of Bloom’s revised taxonomy. The results of this comparison showed the learning objectives for the guided inquiry semesters had a higher proportion of Conceptual and Understand with a corresponding decrease of Factual, Procedural, Remember and Apply learning objectives. On mid-term exams, the proportion of Remember, Understand, Analyze/Evaluate, Factual, and Conceptual questions increased. We found that guided inquiry learning objectives and mid-term exam questions are more conceptual than traditional courses and may help explain how active learning improves equity in introductory chemistry.

The objective of this study was to determine the daily dietary nicotinamide riboside (NR) dose required to maximize the delay of subjective muscle fatigue onset. Barrows (N = 100) were assigned to one of five treatments: a conventional swine finishing diet containing 0 (CON), 15 (15NR), 30 (30NR), 45 (45NR) mg·kg body weight−1·d−1 NR, or CON supplemented with 45 mg·kg body weight−1·d−1 NR by drench or cookie dough (DRE). All treatments were administered for the final 11 days of feeding. On supplementation d 10, barrows individually experienced a performance test at 1.09 m/s until they were subjectively exhausted. Wireless electromyography (EMG) sensors were affixed to the biceps femoris (BF), tensor fascia latae (TFL), and semitendinosus (ST) to measure real-time muscle activity. There were no treatment effects for barrow speed (p = 0.57), a tendency for a treatment effect (p = 0.07) for distance, and a treatment effect (p = 0.04) on time to exhaustion. Barrows of the 15NR and DRE treatments had greater (p = 0.05) distances to exhaustion than CON barrows but did not differ from other NR barrows (p > 0.11). Barrows in the 45NR treatment did not differ (p = 0.11) in distance from 30NR barrows but tended to have a greater (p = 0.07) distance compared to CON barrows. All other treatment comparisons did not differ (p > 0.27). Barrows in the DRE treatment moved for longer (p < 0.01) than CON barrows, but all other treatments did not differ from each other (p > 0.15). There was no treatment × period interaction for all muscles’ root mean square (RMS) values (p > 0.16), but there were Period effects for all muscles (p < 0.01) and a Treatment effect (p = 0.04) in the TFL. For all muscles, period 4 had greater RMS values than all other periods (p < 0.01), who did not differ from each other (p > 0.29). In the TFL, CON barrows had greater RMS values during the performance test compared to all NR treatments (p < 0.02), who did not differ from each other (p > 0.18). Overall, NR demonstrates potential in being a useful tool in fatigue prevention, but efficient administration of the compound needs further investigation.

Purpose In North West-Indo Gangetic Plains (NW-IGP) of India in situ burning of crop residues is practiced by majority of farmersâ which deteriorates soil and environmental quality. Fungi have the potential for lignocellulose degradation and can be used for the in situ decomposition of crop residues. Lignocellulose degrading fungal spp. were isolated and evaluated for the activity of lignocellulolytic enzymes. Method The lignocellulose degrading fungi were isolated by appearance of zone on carboxy methyl cellulose (CMC) agar media and tannic acid (TA) media. Carboxy methyl cellulase, filter paperase, cellobiase, xylanase and laccase activity were estimated in submerged, as well as solid state fermentation using a mixture of rice and wheat straw in the ratio of 4:1. riceâwheat straw as substrate. The residue left after solid state fermentation was evaluated for carbon/nitrogen ratio, dry mass loss, and loss of cellulose, hemicellulose and lignin. Selected potential isolates were further tested in pot experiment for their effect on wheat plants. The interaction among isolates was also studied. Result After primary screening, 19 out of a total of 72 fungal isolates were selected based on their enzymatic activity profile and potential to degrade lignocellulosic residues in submerged fermentation. Out of these 19 isolates, 11 were further selected based on their enzymatic secretions in solid state fermentation. All the 11 strains were identified morphologically. Four fungal isolates (RPW 1/3, RPW 1/6, RPWM 2/2 and RZWM 3/2) showed higher enzymatic activities and more loss of dry mass and cell wall constituents over the other isolates. These isolates were identified by ITS region sequencing as Aspergillus flavus, Aspergillus terreus, Penicillium pinophilum and Alternaria alternata. Conclusion This study revealed that fungal isolates may be used for managing crop residues in conservation agriculture based riceâwheat system of NW-IGP to eliminate ill effects of residue burning.

PurposeTo study the effects of benign prostatic hyperplasia treatments, namely: alpha-adrenergic receptor blockers, 5-alpha-reductase inhibitors and phosphodiesterase-5 inhibitors on the risk of Parkinson's disease, Alzheimer's disease and mortality.Materials and methodsAll male Medicare enrollees aged 65 or above who were diagnosed with benign prostatic hyperplasia and received one of the study drugs between 2007-2020 were followed-up for the three outcomes. We used Cox regression analysis to assess the relative risk of each of the outcomes for each study drug compared to the most prescribed drug, tamsulosin, while controlling for demographic, socioeconomic and comorbidity factors.Results and conclusionsThe study analyzed 1.1 million patients for a mean follow-up period of 3.1 years from being prescribed one of the study drugs. For all outcomes, patients on tamsulosin were used as the reference for comparison. For mortality, alfuzosin was associated with 27% risk reduction (HR 0.73, 95%CI 0.68-0.78), and doxazosin with 6% risk reduction (HR 0.94, 95%CI 0.91-0.97). For Parkinson's disease, terazosin was associated with 26% risk reduction (HR 0.74, 95%CI 0.66-0.83), and doxazosin with 21% risk reduction (HR 0.79, 95%CI 0.72-0.88). For Alzheimer's disease, terazosin was associated with 27% risk reduction (HR 0.73, 95%CI 0.65-0.82), and doxazosin with 16% risk reduction (HR 0.84, 95%CI 0.76-0.92). Tadalafil was associated with risk reduction (27-40%) in all 3 outcomes. More research is needed to elucidate the underlying mechanisms of these observations. Given the availability of safer alternatives for treating benign prostatic hyperplasia, caution should be exercised when using tamsulosin in elderly patients, especially those with an increased risk of developing neurodegenerative diseases.

Fluorouracil/5-flourouracil (5FU) is a first-line chemotherapy drug for many cancer types; however, its associated toxicities contribute to poor quality of life and reduced dose intensities negatively impacting patient prognosis. While obesity remains a critical risk factor for most cancers, our understanding regarding how obesity may impact chemotherapy’s toxicities is extremely limited. C56BL/6 mice were given high fat (Obese) or standard diets (Lean) for 4 months and then subjected to three cycles of 5FU (5d-40 mg/kg Lean Mass, 9d rest) or PBS vehicle control. Shockingly, only 60% of Obese survived 3 cycles compared to 100% of Lean, and Obese lost significantly more body weight. Dihydropyrimidine dehydrogenase (DPD), the enzyme responsible for 5FU catabolism, was reduced in obese livers. Total white blood cells, neutrophils, and lymphocytes were reduced in Obese 5FU compared to Lean 5FU and PBS controls. While adipocyte size was not affected by 5FU in Obese, skeletal muscle mass and myofibrillar cross section area were decreased following 5FU in Lean and Obese. Although adipose tissue inflammatory gene expression was not impacted by 5FU, distinct perturbations to skeletal muscle inflammatory gene expression and immune cell populations (CD45+ Immune cells, CD45+CD11b+CD68+ macrophages and CD45+CD11b+Ly6clo/int macrophage/monocytes) were observed in Obese only. Our evidence suggests that obesity induced liver pathologies and reduced DPD exacerbated 5FU toxicities. While obesity has been suggested to protect against cancer/chemotherapy-induced cachexia and other toxicities, our results demonstrate that obese mice are not protected, but rather show evidence of increased susceptibility to 5FU-induced cytotoxicity even when dosed for relative lean mass.

Projected increases in food demand driven by population growth coupled with heightened agricultural vulnerability to climate change jointly pose severe threats to global food security in the coming decades, especially for developing nations. By providing real-time and low-cost observations, satellite remote sensing has been widely employed to estimate crop yield across various scales. Most such efforts are based on statistical approaches that require large amounts of ground measurements for model training/calibration, which may be challenging to obtain on a large scale in developing countries that are most food-insecure and climate-vulnerable. In this paper, we develop a generalizable framework that is mechanism-guided and practically parsimonious for crop yield estimation. We then apply this framework to estimate crop yield for two crops (corn and wheat) in two contrasting regions, the US Corn Belt US-CB, and India’s Indo–Gangetic plain Wheat Belt IGP-WB, respectively. This framework is based on the mechanistic light reactions (MLR) model utilizing remotely sensed solar-induced chlorophyll fluorescence (SIF) as a major input. We compared the performance of MLR to two commonly used machine learning (ML) algorithms: artificial neural network and random forest. We found that MLR-SIF has comparable performance to ML algorithms in US-CB, where abundant and high-quality ground measurements of crop yield are routinely available (for model calibration). In IGP-WB, MLR-SIF significantly outperforms ML algorithms. These results demonstrate the potential advantage of MLR-SIF for yield estimation in developing countries where ground truth data is limited in quantity and quality. In addition, high-resolution and crop-specific satellite SIF is crucial for accurate yield estimation. Therefore, harnessing the mechanism-guided MLR-SIF and rapidly growing satellite SIF measurements (with high resolution and crop-specificity) hold promise to enhance food security in developing countries towards more effective responses to food crises, agricultural policies, and more efficient commodity pricing.

The Great Barrier Reef (GBR) is predicted to undergo its sixth mass coral bleaching event during the Southern Hemisphere summer of 2021-2022. Coral bleaching-level heat stress over the GBR is forecast to start earlier than any previous year in the satellite record (1985-present). The National Oceanic and Atmospheric Administration (NOAA) Coral Reef Watch (CRW) near real-time satellite-based heat stress products were used to investigate early-summer sea surface temperature (SST) and heat stress conditions on the GBR during late 2021. As of 14 December 2021, values of instantaneous heat stress (Coral Bleaching HotSpots) and accumulated heat stress over a 12-week running window (Degree Heating Weeks) on the GBR were unprecedented in the satellite record. Further, 89% of GBR satellite reef pixels for this date in 2021 had a positive seven-day SST trend of greater than 0.2 degrees Celsius/week. Background temperatures (the minimum temperature over the previous 29 days) were alarmingly high, with 87% of GBR reef pixels on 14 December 2021 being greater than the maximum SST over that same 29-day period for any year from 1985-2020. The GBR is starting the 2021-2022 summer season with more accumulated heat than ever before, which could have disastrous consequences for the health, recovery, and future of this critical reef system.

The Great Barrier Reef (GBR) is predicted to undergo its sixth mass coral bleaching event during the Southern Hemisphere summer of 2021-2022. Coral bleaching-level heat stress over the GBR is forecast to start earlier than any previous year in the satellite record (1985-present). The National Oceanic and Atmospheric Administration (NOAA) Coral Reef Watch (CRW) near real-time satellite-based heat stress products were used to investigate early-summer sea surface temperature (SST) and heat stress conditions on the GBR during late 2021. As of 14 December 2021, values of instantaneous heat stress (Coral Bleaching HotSpots) and accumulated heat stress over a 12-week running window (Degree Heating Weeks) on the GBR were unprecedented in the satellite record. Further, 89% of GBR satellite reef pixels for this date in 2021 had a positive seven-day SST trend of greater than 0.2 degrees Celsius/week. Background temperatures (the minimum temperature over the previous 29 days) were alarmingly high, with 87% of GBR reef pixels on 14 December 2021 being greater than the maximum SST over that same 29-day period for any year from 1985-2020. The GBR is starting the 2021-2022 summer season with more accumulated heat than ever before, which could have disastrous consequences for the health, recovery, and future of this critical reef system.

Neurodegeneration after traumatic brain injury (TBI) is increasingly recognized as a key factor contributing to poor chronic outcomes. Activation (i.e., phosphorylation) of the protein kinase R-like endoplasmic reticulum kinase (PERK) pathway has been implicated in neurodegenerative conditions with pathological similarities to TBI and may be a potential target to improve TBI outcomes. Here, we aimed to determine whether a moderate TBI would induce activation of the PERK pathway and whether treatment with the PERK inhibitor, GSK2606414, would improve TBI recovery. Male mice were administered a lateral fluid percussion injury (FPI) or sham injury and were euthanized at either 2?h, 24?h, or 1 week post-injury (n?=?5 per injury group and time point) to assess changes in the PERK pathway. In the injured cortex, there was increased phosphorylated-PERK at 2?h post-FPI and increased phosphorylation of eukaryotic translation initiation factor ? at 24?h post-FPI. We next examined the effect of acute treatment with GSK2606414 on pathological and behavioral outcomes at 4 weeks post-injury. Thus, there were a total of four groups: sham + VEH (n?=?9); sham + GSK4606414 (n?=?10); FPI + VEH (n?=?9); and FPI + GSK2606414 (n?=?9). GSK2606414 (50?mg/kg) or vehicle treatment was delivered by oral gavage beginning at 30?min post-injury, followed by two further treatments at 12-h increments. There were no significant effects of GSK2606414 on any of the outcomes assessed, which could be attributable to several reasons. For example, activation of PERK may not be a significant contributor to the neurological consequences 4 weeks post-FPI in mice. Further research is required to elucidate the role of the PERK pathway in TBI and whether interventions that target this pathway are beneficial.

The Great Barrier Reef (GBR) is predicted to undergo its sixth mass coral bleaching event during the Southern Hemisphere summer of 2021-2022. Coral bleaching-level heat stress over the GBR is forecast to start earlier than any previous year in the satellite record (1985-present). The National Oceanic and Atmospheric Administration (NOAA) Coral Reef Watch (CRW) near real-time satellite-based heat stress products were used to investigate early-summer sea surface temperature (SST) and heat stress conditions on the GBR during late 2021. As of 14 December 2021, values of instantaneous heat stress (Coral Bleaching HotSpots) and accumulated heat stress over a 12-week running window (Degree Heating Weeks) on the GBR were unprecedented in the satellite record. Further, 89% of GBR satellite reef pixels for this date in 2021 had a positive seven-day SST trend of greater than 0.2 degrees Celsius/week. Background temperatures (the minimum temperature over the previous 29 days) were alarmingly high, with 87% of GBR reef pixels on 14 December 2021 being greater than the maximum SST over that same 29-day period for any year from 1985-2020. The GBR is starting the 2021-2022 summer season with more accumulated heat than ever before, which could have disastrous consequences for the health, recovery, and future of this critical reef system.