Miracle-dz/UniFAR-FTUs huggingface dataset:
Care and outcomes of Canadian children hospitalised with periorbital and orbital cellulitis: protocol for a multicentre, retrospective cohort study

Introduction Skin and soft tissue infections of the eye can be classified based on anatomic location as either anterior to the orbital septum (ie, periorbital cellulitis) or posterior to the orbital septum (ie, orbital cellulitis). These two conditions are often considered together in hospitalised children as clinical differentiation is difficult, especially in young children. Prior studies have identified variation in management of hospitalised children with orbital cellulitis; however, they have been limited either as single centre studies or by the use of administrative data which lacks clinical details important for interpreting variation in care. We aim to describe the care and outcomes of Canadian children hospitalised with periorbital and orbital cellulitis. Method and analysis This is a multisite retrospective cohort study including previously healthy children aged 2 months to 18 years admitted to hospital with periorbital or orbital cellulitis from 2009 to 2018. Clinical data from medical records from multiple Canadian hospitals will be collected, including community and academic centres. Demographic characteristics and study outcomes will be summarised using descriptive statistics, including diagnostic testing, antibiotic therapy, adjunctive therapy, surgical intervention and clinical outcomes. Variation will be described and evaluated using χ² test or Kruskal-Wallis test. Generalised linear mixed models will be used to identify predictors of surgical intervention and longer length of stay. Ethics and dissemination Approval of the study by the Research Ethics Board at each participating site has been obtained prior to data extraction. Study results will be disseminated by presentations at national and international meetings and by publications in high impact open access journals. By identifying important differences in management and outcomes by each hospital, the results will identify areas where care can be improved, practice standardised, unnecessary diagnostic imaging reduced, pharmacotherapy rationalised and where trials are needed.
Adherence to Dietary Recommendations among Long-Term Breast Cancer Survivors and Cancer Outcome Associations

Background: Adherence to dietary recommendations has been shown to be associated with reduced mortality in healthy populations. Little is known about the possible benefits of adherence to dietary recommendations among breast cancer survivors. Methods: Dietary information was collected using food frequency questionnaires at the 5-year postdiagnosis survey in 3,450 5-year breast cancer survivors from the Shanghai Breast Cancer Survival Study. Adherence scores to Chinese Food Pagoda (CHFP)-2007, CHFP-2016, modified Dietary Approaches to Stop Hypertension (DASH), and Healthy Eating Index 2015 (HEI-2015) were created. Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for total mortality and breast cancer–specific events according to adherence scores. Results: Participants in the highest quartiles of CHFP-2007, CHFP-2016, and DASH had 25% to 34% lower risk of total mortality (HR, 0.66; 95% CI, 0.48–0.89 for CHFP-2007; HR, 0.75; 95% CI, 0.55–1.01 for CHFP-2016; HR, 0.66; 95% CI, 0.49–0.91 for DASH), and 36% to 40% lower risk of breast cancer–specific events (HR, 0.64; 95% CI, 0.44–0.93 for CHFP-2007; HR, 0.67; 95% CI, 0.45–0.99 for CHFP-2016; HR, 0.60; 95% CI, 0.40–0.90 for DASH) comparing with the lowest quartiles. Associations did not vary by known prognostic factors. HEI-2015 scores were not significantly associated with breast cancer outcomes. Conclusions: Higher adherence to CHFP and DASH dietary guidelines post-cancer diagnosis was associated with reduced risk of both overall death and breast cancer–specific recurrence or death among long-term breast cancer survivors. Impact: Our study highlights the importance of overall dietary quality among long-term breast cancer survivors.
Bupropion Inhibits Serotonin Type 3AB Heteromeric Channels at Clinically Relevant Concentrations

Bupropion, a Food and Drug Administration–approved antidepressant and smoking cessation aid, blocks dopamine and norepinephrine reuptake transporters and noncompetitively inhibits nicotinic acetylcholine and serotonin (5-HT) type 3A receptors (5-HT3ARs). 5-HT3 receptors are pentameric ligand-gated ion channels that regulate synaptic activity in the central and peripheral nervous system, presynaptically and postsynaptically. In the present study, we examined and compared the effect of bupropion and its active metabolite hydroxybupropion on mouse homomeric 5-HT3A and heteromeric 5-HT3AB receptors expressed in Xenopus laevis oocytes using two-electrode voltage clamp experiments. Coapplication of bupropion or hydroxybupropion with 5-HT dose dependently inhibited 5-HT–induced currents in heteromeric 5-HT type 3AB receptors (5-HT3ABRs) (IC50 = 840 and 526 μM, respectively). The corresponding IC50s for bupropion and hydroxybupropion for homomeric 5-HT3ARs were 10- and 5-fold lower, respectively (87 and 113 μM). The inhibition of 5-HT3ARs and 5-HT3ABRs was non–use dependent and voltage independent, suggesting bupropion is not an open channel blocker. The inhibition by bupropion was reversible and time-dependent. Of note, preincubation with a low concentration of bupropion that mimics therapeutic drug conditions inhibits 5-HT–induced currents in 5-HT3A and 5-HT3AB receptors considerably. In summary, we demonstrate that bupropion inhibits heteromeric 5-HT3ABRs as well as homomeric 5-HT3ARs. This inhibition occurs at clinically relevant concentrations and may contribute to bupropion’s clinical effects. SIGNIFICANCE STATEMENT Clinical studies indicate that antagonizing serotonin (5-HT) type 3AB (5-HT3AB) receptors in brain areas involved in mood regulation is successful in treating mood and anxiety disorders. Previously, bupropion was shown to be an antagonist at homopentameric 5-HT type 3A receptors. The present work provides novel insights into the pharmacological effects that bupropion exerts on heteromeric 5-HT3AB receptors, in particular when constantly present at low, clinically attainable concentrations. The results advance the knowledge on the clinical effects of bupropion as an antidepressant.
Using machine learning to predict extreme events in complex systems

Significance Understanding and predicting extreme events as well as the related anomalous statistics is a grand challenge in complex natural systems. Deep convolutional neural networks provide a useful tool to learn the essential model dynamics directly from data. A deep learning strategy is proposed to predict the extreme events that appear in turbulent dynamical systems. A truncated KdV model displaying distinctive statistics from near-Gaussian to highly skewed distributions is used as the test model. The neural network is trained using data only from the near-Gaussian regime without the occurrence of large extreme values. The optimized network demonstrates uniformly high skill in successfully capturing the solution structures in a wide variety of statistical regimes, including the highly skewed extreme events. Extreme events and the related anomalous statistics are ubiquitously observed in many natural systems, and the development of efficient methods to understand and accurately predict such representative features remains a grand challenge. Here, we investigate the skill of deep learning strategies in the prediction of extreme events in complex turbulent dynamical systems. Deep neural networks have been successfully applied to many imaging processing problems involving big data, and have recently shown potential for the study of dynamical systems. We propose to use a densely connected mixed-scale network model to capture the extreme events appearing in a truncated Korteweg–de Vries (tKdV) statistical framework, which creates anomalous skewed distributions consistent with recent laboratory experiments for shallow water waves across an abrupt depth change, where a remarkable statistical phase transition is generated by varying the inverse temperature parameter in the corresponding Gibbs invariant measures. The neural network is trained using data without knowing the explicit model dynamics, and the training data are only drawn from the near-Gaussian regime of the tKdV model solutions without the occurrence of large extreme values. A relative entropy loss function, together with empirical partition functions, is proposed for measuring the accuracy of the network output where the dominant structures in the turbulent field are emphasized. The optimized network is shown to gain uniformly high skill in accurately predicting the solutions in a wide variety of statistical regimes, including highly skewed extreme events. The technique is promising to be further applied to other complicated high-dimensional systems.
Time-Resolved Far Infrared Light Transport Decomposition for Thermal Photometric Stereo

We present a novel time-resolved light transport decomposition method using thermal imaging. Because the speed of heat propagation is much slower than the speed of light propagation, the transient transport of far infrared light can be observed at a video frame rate. A key observation is that the thermal image looks similar to the visible light image in an appropriately controlled environment. This implies that conventional computer vision techniques can be straightforwardly applied to the thermal image. We show that the diffuse component in the thermal image can be separated, and therefore, the surface normals of objects can be estimated by the Lambertian photometric stereo. The effectiveness of our method is evaluated by conducting real-world experiments, and its applicability to black body, transparent, and translucent objects is shown.
Tcf7l2 transcription factor is required for the maintenance, but not the initial specification, of the neurotransmitter identity in the caudal thalamus

Dysfunction of GABAergic and glutamatergic neurons in the brain, which establish inhibitory and excitatory networks, respectively, may cause diverse neurological disorders. The mechanism underlying the determination of GABAergic vs. glutamatergic neurotransmitter phenotype in the caudal diencephalon remains largely unknown.
CCMod: a GATE module for Compton camera imaging simulation

Compton cameras are gamma-ray imaging systems which have been proposed for a wide variety of applications such as medical imaging, nuclear decommissioning or homeland security. In the design and optimization of such a system Monte Carlo simulations play an essential role. In this work, we propose a generic module to perform Monte Carlo simulations and analyses of Compton Camera imaging which is included in the open-source GATE/Geant4 platform. Several digitization stages have been implemented within the module to mimic the performance of the most commonly employed detectors (e.g. monolithic blocks, pixelated scintillator crystals, strip detectors.). Time coincidence sorter and sequence coincidence reconstruction are also available in order to aim at providing modules to facilitate the comparison and reproduction of the data taken with different prototypes. All processing steps may be performed during the simulation (on–the–fly mode) or as a post–process of the output files (offline mode). The predictions of the module have been compared with experimental data in terms of energy spectra, angular resolution, efficiency and back-projection image reconstruction. Consistent results within a 3-sigma interval were obtained for the energy spectra except for low energies where small differences arise. The angular resolution measure for incident photons of 1275 keV was also in good agreement between both data sets with a value close to 13°. Moreover, with the aim of demonstrating the versatility of such a tool the performance of two different Compton camera designs was evaluated and compared.
Implicit and explicit processing of bodily emotions in schizophrenia

ABSTRACT Introduction Disturbed emotion processing is well documented in schizophrenia, but the majority of studies evaluate processing of emotion only from facial expressions. Social cues are also communicated via body posture, and they are similarly relevant for successful social interactions. The aim of the current study was to thoroughly examine body perception abilities in individuals with schizophrenia. Methods Fifty-nine patients with schizophrenia and 37 healthy controls completed two tasks of body processing. The first, which was based on the Affect Misattribution Procedure, evaluated implicit processing of bodily emotions, and the second utilised a traditional emotion identification paradigm to assess explicit emotion recognition. Results Results revealed aberrant implicit processing, but more normative explicit processing, in individuals with schizophrenia. Moderate associations were found between processing of bodies and symptoms of paranoia. Performance on the tasks was not related to cognitive functioning but was associated with clinician-rated social functioning. Conclusions Collectively, these results provide information about disturbed processing of bodily emotions in schizophrenia and suggest that these disturbances are associated with the severity of positive symptoms and predict difficulties in everyday social activities and interpersonal relationships.
Validation of the Chinese Version of Obsessive-Compulsive Inventory-Revised.

BACKGROUND The Obsessive-Compulsive Inventory-Revised (OCI-R) is a psychometrically sound and valid self-report measure for evaluating the severity of six dimensions of obsessive-compulsive symptoms: washing, obsessing, hoarding, ordering, checking, and neutralising. We aimed to validate the Chinese version of the OCI-R (C-OCI-R) in patients with obsessive-compulsive disorder (OCD) in Hong Kong. METHODS The C-OCI-R was forward and backward translated and reviewed by an expert panel and a focus group. The internal consistency and test-retest reliability (2-week interval) were examined. Confirmatory factor analysis was used to examine the construct validity of the C-OCI-R. Concurrent validity was examined by the correlation between the C-OCI-R and the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), whereas divergent validity was examined by the correlation of the C-OCI-R with the Beck Depression Inventory-Second Edition and the Hamilton Depression Rating Scale. RESULTS 130 OCD patients were recruited. The C-OCI-R showed excellent internal consistency (Cronbach's alpha = 0.92) and test-retest reliability (Spearman's rho correlation coefficient = 0.96). The original six-factor model was supported by confirmatory factor analysis. Concurrent validity and divergent validity were established. However, the neutralising subscale may need further development, and the divergent validity of the obsessing subscale was unsatisfactory. The structure of OCD symptoms was similar in Chinese and western patients. CONCLUSION The C-OCI-R is a valid and reliable measure for assessing the severity of obsessive-compulsive symptoms in local Chinese patients with OCD.
Subcellular drug targeting illuminates local kinase action

Deciphering how signaling enzymes operate within discrete microenvironments is fundamental to understanding biological processes. A-kinase anchoring proteins (AKAPs) restrict the range of action of protein kinases within intracellular compartments. We exploited the AKAP targeting concept to create genetically encoded platforms that restrain kinase inhibitor drugs at distinct subcellular locations. Local Kinase Inhibition (LoKI) allows us to ascribe organelle-specific functions to broad specificity kinases. Using chemical genetics, super resolution microscopy, and live-cell imaging we discover that centrosomal delivery of Polo-like kinase 1 (Plk1) and Aurora A (AurA) inhibitors attenuates kinase activity, produces spindle defects, and prolongs mitosis. Targeted inhibition of Plk1 in zebrafish embryos illustrates how centrosomal Plk1 underlies mitotic spindle assembly. Inhibition of kinetochore-associated pools of AurA blocks phosphorylation of microtubule-kinetochore components. This versatile precision pharmacology tool enhances investigation of local kinase biology.
Improved Gradient-echo 3D Magnetic Resonance Imaging Using Compressed Sensing and Toeplitz Encoding with Phase-Scrambled RF Excitation.

PURPOSE To develop a novel 3D hybrid-encoding framework using compressed sensing (CS) and Toeplitz encoding with variable phase-scrambled radio-frequency (RF) excitation, which has the following advantages: low power deposition of RF pulses, reduction of the signal dynamic range, no additional hardware requirement, and signal-to-noise ratio (SNR) improvement. METHODS In light of the actual imaging framework of MRI scanners, we applied specially tailored RF pulses with phase-scrambled RF excitation to implement a 3D hybrid Fourier-Toeplitz encoding method based on 3D gradient-recalled echo pulse (GRASS) sequence. This method exploits Toeplitz encoding along the phase encoding direction, while keeping Fourier encoding along the readout and slice encoding directions. Phantom experiments were conducted to optimize the amplitude of specially tailored RF pulses in the 3D GRASS sequence. In vivo experiments were conducted to validate the feasibility of the proposed method, and simulations were conducted to compare the 3D hybrid encoding method with Fourier encoding and other non-Fourier encoding methods. RESULTS An optimized low RF amplitude was obtained in the phantom experiments. Using the optimized specially tailored RF pulses, both the watermelon and knee experiments demonstrated that the proposed method was able to preserves more image details than the conventional 3D Fourier-encoded methods at acceleration factors of 3.1 and 2.0. Additionally, SNR was improved because of no additional gradients and 3D volume encoding, when compared with single-slice scanning without 3D encoding. Simulation results demonstrated that the proposed scheme was superior to the conventional Fourier encoding method, and obtained comparative performance with other non-Fourier encoding methods in preserving details. CONCLUSION We developed a practical hybrid encoding method for 3D MRI with specially tailored RF pulses of phase-scrambled RF excitation. The proposed method improves image SNR and detail preservation compared with the conventional Fourier encoding methods. Furthermore, our proposed method exhibits superior performance in terms of detail preservation, compared with the conventional Fourier encoding method.
Examining the optimal timing for closed-loop auditory stimulation of slow-wave sleep in young and older adults

Abstract Study Objectives Closed-loop auditory stimulation (CLAS) is a method for enhancing slow oscillations (SOs) through the presentation of auditory clicks during sleep. CLAS boosts SOs amplitude and sleep spindle power, but the optimal timing for click delivery remains unclear. Here, we determine the optimal time to present auditory clicks to maximize the enhancement of SO amplitude and spindle likelihood. Methods We examined the main factors predicting SO amplitude and sleep spindles in a dataset of 21 young and 17 older subjects. The participants received CLAS during slow-wave-sleep in two experimental conditions: sham and auditory stimulation. Post-stimulus SOs and spindles were evaluated according to the click phase on the SOs and compared between and within conditions. Results We revealed that auditory clicks applied anywhere on the positive portion of the SO increased SO amplitudes and spindle likelihood, although the interval of opportunity was shorter in the older group. For both groups, analyses showed that the optimal timing for click delivery is close to the SO peak phase. Click phase on the SO wave was the main factor determining the impact of auditory stimulation on spindle likelihood for young subjects, whereas for older participants, the temporal lag since the last spindle was a better predictor of spindle likelihood. Conclusions Our data suggest that CLAS can more effectively boost SOs during specific phase windows, and these differ between young and older participants. It is possible that this is due to the fluctuation of sensory inputs modulated by the thalamocortical networks during the SO.
Alzheimer’s-like pathology in aging rhesus macaques: Unique opportunity to study the etiology and treatment of Alzheimer’s disease

Although mouse models of Alzheimer’s disease (AD) have provided tremendous breakthroughs, the etiology of later onset AD remains unknown. In particular, tau pathology in the association cortex is poorly replicated in mouse models. Aging rhesus monkeys naturally develop cognitive deficits, amyloid plaques, and the same qualitative pattern and sequence of tau pathology as humans, with tangles in the oldest animals. Thus, aging rhesus monkeys can play a key role in AD research. For example, aging monkeys can help reveal how synapses in the prefrontal association cortex are uniquely regulated compared to the primary sensory cortex in ways that render them vulnerable to calcium dysregulation and tau phosphorylation, resulting in the selective localization of tau pathology observed in AD. The ability to assay early tau phosphorylation states and perform high-quality immunoelectron microscopy in monkeys is a great advantage, as one can capture early-stage degeneration as it naturally occurs in situ. Our immunoelectron microscopy studies show that phosphorylated tau can induce an “endosomal traffic jam” that drives amyloid precursor protein cleavage to amyloid-β in endosomes. As amyloid-β increases tau phosphorylation, this creates a vicious cycle where varied precipitating factors all lead to a similar phenotype. These data may help explain why circuits with aggressive tau pathology (e.g., entorhinal cortex) may degenerate prior to producing significant amyloid pathology. Aging monkeys therefore can play an important role in identifying and testing potential therapeutics to protect the association cortex, including preventive therapies that are challenging to test in humans.