Miracle-dz/UniFAR-FTUs huggingface dataset:
Cysteinyl leukotriene induces eosinophil extracellular trap formation via cysteinyl leukotriene 1 receptor in a murine model of asthma

Abstract Purpose Eosinophils are one of the main cells responsible to the inflammatory response in asthma by the release of inflammatory molecules such as cytokines, reactive oxygen species (ROS), cytotoxic granule, eosinophil extracellular trap (EET), and lipid mediators as cysteinyl leukotriene (cysLT). The interconnections between these molecules are not fully understood. Here, we attempted to investigate the cysLT participation in the mechanisms of EET formation in an asthma model of OVA challenge. Materials and methods Before intranasal challenge with OVA, BALB/cJ mice were treated with a 5-lipoxygenase-activating protein (FLAP) inhibitor (MK-886), or with a cysLT1 receptor antagonist (MK-571) and the lung and bronchoalveolar lavage fluid (BALF) were analyzed. Results We showed that OVA-challenged mice treated with MK-886 or MK-571 had a decrease in inflammatory cells, goblet cells hyperplasia, and eosinophil peroxidase (EPO) activity in the airway. However, only OVA-challenged mice treated with MK-571 had an improvement in lung function. Also, treatments with MK-886 or MK-571 decreased Th2 cytokines levels in the airway. Moreover, we observed that OVA-challenged mice treated with MK-886 or MK-571 had a decrease in EET formation in BALF. We also verified that EET release was not due to cell death because the cell viability remained the same among the groups. Conclusion We revealed that the decrease in cysLT production or cysLT1 receptor inhibition by MK-886 or/and MK-571 treatments, respectively reduced EET formation in BALF, showing that cysLT regulates the activation process of EET release in asthma.
Sparse Recovery with Shuffled Labels: Statistical Limits and Practical Estimators

This paper considers the sparse recovery with ner-muted labels, i.e., $\boldsymbol{y}={\Pi}^{\ast}\boldsymbol{X}{\beta}^{\ast}+\boldsymbol{w}$ where $\boldsymbol{y} \in \mathbb{R}^{n}, \mathbf{\Pi} \in \mathbb{R}^{n \times n}, \boldsymbol{X} \in \mathbb{R}^{n \times p}, {\beta}^{\ast} \in \mathbb{R}^{p}, \boldsymbol{w} \in \mathbb{R}^{n}$ denote the sensing result, unknown permutation matrix, design matrix, k-sparse covariates, and additive noise, respectively. The investigation is performed from both the statistical and the computational perspectives. For the statistical aspect, we first establish the statistical lower bounds on the measurement number $n$ and the signal-to-noise ratio (SNR) for the correct recovery of the permutation matrix and the support set $\text{supp}({\beta}^{\ast})$, more specifically $n \gtrsim k \log p$ and $\log (\text{SNR}) \gtrsim \log n+\frac{k \log p}{n}$. Then we confirm the tightness of these bounds by giving an exhaustive-search based estimators with matching orders. For the computational aspect, we propose a computationally-efficient estimator, namely, M-Lasso to recover both the permutation matrix and the sparse covariates. Numerical experiments are provided to verify the correctness and efficiency of the proposed estimator.
Experimental investigation on the mean drop size and drop size distribution in an L-shaped pulsed sieve-plate column

ABSTRACT Vertical pulsed extraction columns cannot be employed in applications with height limitations. On the other hand, the horizontal extraction columns have low throughput, which affects their applicability in industrial applications. Therefore, there is a need to design a new type of extractors for such circumstances. In this paper, an experimental study on drop sizes has been implemented in a novel L-shaped pulsed sieve-plate extraction column in the absence and presence of mass transfer. Moreover, new correlations are developed for prediction of the mean drop size and size distribution using the log-normal probability density function.
Effects of protease supplementation and diet type on jejunal and ileal digestibility and total tract metabolisability of nitrogen, starch, and energy in broilers

ABSTRACT 1. A study was conducted to assess the effects of supplemental protease (0 or 15,000 units/kg) and diet type (maize- or wheat-based) on apparent jejunal and ileal digestibility and apparent total tract metabolisability of nutrients in Cobb 500 mixed-sex broilers from 6 to 31 d of age. 2. Birds were randomly distributed into 56 metabolism cages (6 birds/cage; 14 replicates/treatment). At 22 d of age, jejunal and ileal digesta contents were collected and pooled from 4 birds/cage to determine apparent digestibility coefficients (DC) and digestible energy (DE). Feed intake was measured, and total excreta were collected from 8 to 11 and 18 to 21 d of age to determine apparent metabolisable energy (AME) and total tract nitrogen and starch metabolisability coefficients. 3. Broilers offered the maize-based diet with protease had greater (P < 0.05) jejunal nitrogen DC, starch DC, and DE (8.2, 6.5, and 14.9%, respectively) and ileal nitrogen DC and DE (5.1 and 6.8%, respectively) than those offered the maize-based diet without protease. Ileal starch DC was increased (P < 0.05) by 1.1% with protease supplementation. 4. Broilers offered maize-based diets had greater (P < 0.05) nitrogen (7.3%) and starch (0.6%) metabolisability coefficients and AME (4.7%) from 8 to 11 d of age, and nitrogen (4.3%) metabolisability coefficients and AME (2.0%) from 18 to 21 d of age compared with those offered wheat-based diets. 5. Thus, protease supplementation and diet type can affect digestive dynamics and nutrient utilisation in broilers.
The link between atopic dermatitis and mental health outcomes across childhood: A longitudinal cohort study

Importance Research has highlighted associations between atopic dermatitis (AD) and mental health conditions in adults. However, literature on the development of mental health comorbidities in children is limited despite the large burden of pediatric AD worldwide. Objective To examine the relationship between AD and internalizing behaviors and symptoms of depression at multiple time points across childhood and adolescence, and to explore potential mediating factors including asthma/rhinitis, sleep, and inflammation. Design Longitudinal cohort study Setting Population-based birth cohort in the United Kingdom Participants Children followed from birth for a mean duration of 10.0 years (SD 2.9 years) from The Avon Longitudinal Study of Parents and Children Exposure AD annual period prevalence and disease severity assessed at 11 time points between ages 6 months and 18 years, measured by standardized questions about flexural dermatitis Main outcomes and measures Symptoms of depression, measured using child-reported responses to the Short Moods and Feelings Questionnaire at five time points between ages 10 and 18 years; and Internalizing behaviors, measured by maternal report of the Emotional Symptoms subscore of the Strength and Difficulties Questionnaire collected at seven time points between ages 4 and 16 years. Results Among 11,181 children, the annual period prevalence of internalizing behaviors and symptoms of depression ranged from 10.3% to 16.0% and 6.0% to 22.1%, respectively. Although mild/moderate AD was not associated with symptoms of depression, it was associated with internalizing behaviors as early as age 4 (average of 29-84% increased odds across childhood in adjusted models). Severe AD was associated with symptoms of depression (aOR 2.38, 95% CI 1.21-4.72) and internalizing symptoms (aOR 1.90, 95% CI 1.14-3.16). Sleep quality mediated some of this association, but it was not explained by differences in sleep duration, asthma/rhinitis, nor inflammatory markers (IL-6 and CRP). Conclusion and relevance Within a population-based birth cohort in the United Kingdom, severe AD was associated with symptoms of depression and internalizing behaviors throughout childhood and adolescence. Risk of internalizing symptoms was increased even for children with mild AD beginning early in childhood, highlighting the importance of behavioral/mental health awareness in providers treating this population.
Anomaly Detection in Medical Imaging With Deep Perceptual Autoencoders

Anomaly detection is the problem of recognizing abnormal inputs based on the seen examples of normal data. Despite recent advances of deep learning in recognizing image anomalies, these methods still prove incapable of handling complex images, such as those encountered in the medical domain. Barely visible abnormalities in chest X-rays or metastases in lymph nodes on the scans of the pathology slides resemble normal images and are very difficult to detect. To address this problem, we introduce a new powerful method of image anomaly detection. It relies on the classical autoencoder approach with a re-designed training pipeline to handle high-resolution, complex images, and a robust way of computing an image abnormality score. We revisit the very problem statement of fully unsupervised anomaly detection, where no abnormal examples are provided during the model setup. We propose to relax this unrealistic assumption by using a very small number of anomalies of confined variability merely to initiate the search of hyperparameters of the model. We evaluate our solution on two medical datasets containing radiology and digital pathology images, where the state-of-the-art anomaly detection models, originally devised for natural image benchmarks, fail to perform sufficiently well. The proposed approach suggests a new baseline for anomaly detection in medical image analysis tasks.
Morbidity and predictors of delayed recognition of iatrogenic ureteric injuries.

INTRODUCTION Although intraoperative iatrogenic ureteric injuries (IUI) are rare, significant consequences can occur if they are unrecognized at the time. The focus of our study is to characterize the associated morbidity and identify predictors of delayed recognition of IUI. METHODS Sunnybrook Health Sciences Centre Research Ethics Board approved the study. Patients with a diagnosis of IUI between 2002 and 2020 were identified through an institutional electronic medical record system. Data pertaining to the demographic characteristics, diagnosis, and management of IUI and overall outcomes were collected retrospectively. RESULTS Of the 103 patients identified, 83% were female, 52% had previous abdominal surgery, and 18% had previous radiation. The median age was 67 (21-88) years. Twenty percent were not recognized at the time of surgery. Although delayed recognition was not a significant predictor for poor outcome after subsequent repair (i.e., hydronephrosis, ureteric stricture/obstruction), it was associated with substantial morbidity to the patient (i.e., additional procedures) and increased cost to the healthcare system (i.e., longer hospital stay, readmission to hospital). Patients who underwent laparoscopic surgery had an 11 times more likely chance of having an unrecognized IUI as compared to those who underwent open surgery (odds ratio 11.515, p=0.0001). CONCLUSIONS Delayed recognition of IUI may be associated with considerable adverse effects. In this retrospective case series, we identified laparoscopic surgery as a significant predictor for delayed recognition of IUI. This information underscores the need for future studies to facilitate intraoperative identification of ureteric injuries, particularly during laparoscopic procedures.
Coding for Transverse-Reads in Domain Wall Memories

Transverse-read is a novel technique to detect the number of ‘1's stored in domain wall memory, also known as racetrack memory, without shifting any domains. Motivated by this technique, we propose a novel scheme to combine transverse-read and shift-operations such that the number of shift-operations can be reduced while still achieving high capacity. We also show that this scheme is helpful to correct errors in domain wall memory. A set of valid words in this transverse-read channel is called a transverse-read code. We first present several properties of transverse-read codes and show that they are equivalent to constrained codes. Then, we compute the maximal asymptotic rate of transverse-read codes for several parameters. Next, we construct achieving capacity codes with efficient encoding/decoding algorithms. Finally, we discuss transverse-read codes which correct shift-errors in domain wall memory.
The Continuous Matching Task (CMT) – real-time procedural stimulus generation for adaptive testing of attention

Abstract The Continuous Matching Task (CMT) is a novel paradigm designed to measure sustained attention and alertness. It is a special type of Continuous Performance Task (CPT) that utilizes truly continuous stimulus material. Stimuli are generated in real-time by a procedural algorithm which also enables adaptive testing. The task is highly flexible and can be used in either single or dual-task configurations that also allow for task mixing. The functionality of the algorithm and applications are presented. The viability of the CMT is tested and results are compared with similar tasks, i.e. Stroop-Task and Conner’s CPT (CCPT), as well as self-reports of ADHD in adults in a Multi-Trait-Multi-Method approach in a sample of N = 122 participants. Self-reports and measurements of heart rate variability during testing are analyzed to infer and compare mental workload during tasks. Overall, variants of the CMT induce a higher mental workload than the other tasks, and employing the dual-task CMT with adaptive difficulty resulted in the highest reliability and validity. Results indicate that the CMT is primarily a measure of alertness and processing speed and benefits from adaptive testing.
Seasonal and Age-Related Variation in Daily Travel Distances of California Condors

Abstract. Despite a dramatic recovery from the brink of extinction, California Condors (Gymnogyps californianus) still face significant anthropogenic threats. Although condor movement patterns across large temporal scales are understood, less is known about their movements on a fine temporal scale. We used a trajectory-based analysis of GPS telemetry data gathered from condors during 2013 to 2018 to investigate the relationship between the distances condors travel in a day, demographic characteristics (e.g., age and sex), and time of year. Most (>71.4%) daily travel distances by condors were <100 km, and, on average, condors traveled 70.1 ± 60.9 km/d (x̄ ± SD). On two occasions one condor traveled >400 km in a single day (477 km one day and 415 km the following day). The tendency for condors to travel long distances increased with age, and condors traveled longer distances during the summer and when nesting. Traveling such long distances likely exposes birds to threats across a greater variety of landscapes than would be expected for birds that moved shorter distances. Given anticipated condor range expansion and population increase, this work highlights the importance of coordinating condor conservation across the broad spatial scales at which they move.
Using a smartwatch electrocardiogram to detect abnormalities associated with sudden cardiac arrest in young adults.

AIMS Smartwatch electrocardiograms (ECGs) could facilitate the detection of sudden cardiac arrest (SCA)-associated abnormalities. We evaluated the feasibility of using smartwatch-derived ECGs for detecting SCA-associated abnormalities in young adults and its agreement with 12-lead ECGs. METHODS AND RESULTS Twelve-lead and Apple Watch ECGs were registered in 155 healthy volunteers and 67 patients aged 18-45 years with diagnosis and ECG signs of long-QT syndrome (n = 10), Brugada syndrome (n = 12), ventricular pre-excitation (n = 19), hypertrophic cardiomyopathy (HCM, n = 13), and arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC/D, n = 13). Cardiologists separately analysed 12-lead ECGs and the smartwatch ECGs taken from the left wrist (AW-I) and then from chest positions V1, V3, and V6 (AW-4). Compared with AW-I, AW-4 improved the classification of ECGs as 'abnormal', increasing the sensitivity from 64% to 89% (P < 0.01). Pre-excitation was detected in most cases using AW-I (sensitivity 89%) and in all cases using AW-4 (sensitivity 100%, P = 0.48 compared with AW-I, specificity 100% for both). Brugada was missed using AW-I but was detected in 11/12 patients using AW-4 (sensitivity 92%, specificity 100%, P = 0.003). Long QT was detected in 8/10 cases using AW-I (sensitivity 80%, specificity 100%) and in 9 patients using AW-4 (sensitivity 90%, specificity 100%, P > 0.99). Hypertrophic cardiomyopathy was correctly suspected using AW-I and AW-4 (sensitivity 92% and 85%, specificity 85%, and 100%, P > 0.99). AW-I was mostly (62%) considered normal in ARVC/D whereas AW-4 was useful in suspecting ARVC/D (100% sensitivity, 99% specificity, P = 0.004). CONCLUSIONS Detection of SCA-associated ECG abnormalities (pre-excitation, Brugada patterns, long QT, and signs suggestive of HCM and ARVC/D) is possible with an ECG smartwatch.
Immune response to intravenous immunoglobulin in patients with Kawasaki disease and MIS-C.

BACKGROUND Multisystem inflammatory syndrome in children (MIS-C) is a rare but potentially severe illness that follows exposure to severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2). Kawasaki Disease (KD) shares several clinical features with MIS-C, which prompted the use of intravenous immunoglobulin (IVIG), a mainstay therapy for KD. Both diseases share a robust activation of the innate immune system, including the IL-1 signaling pathway, and IL-1 blockade has been used for the treatment of both MIS-C and KD. The mechanism of action of IVIG in these two diseases and the cellular source of IL-1b have not been defined. METHODS The effects of IVIG on peripheral blood leukocyte populations from patients with MIS-C and KD were examined using flow cytometry, mass cytometry (CyTOF), and live cell imaging. RESULTS Circulating neutrophils were highly activated in patients with KD and MIS-C, and were a major source of IL-1β. Following IVIG treatment, activated IL-1β+ neutrophils were reduced in the circulation. In vitro, IVIG was a potent activator of neutrophil cell death via PI3-K and NADPH oxidase but independently of caspase activation. CONCLUSIONS Activated neutrophils expressing IL-1β can be targeted by IVIG, supporting its use in both KD and MIS-C to ameliorate inflammation.
The Sur7 cytoplasmic C terminus regulates morphogenesis and stress responses in Candida albicans

MCC/eisosome subdomains of the plasma membrane promote proper cell wall morphogenesis that is critical for the fungal pathogen Candida albicans to grow invasively and resist stressful environments in the host. Sur7 localizes to MCC/eisosomes and is needed for their function, so in this work, the role of this tetraspan membrane protein was studied by mutagenesis. Deletion mutant analysis showed that the N‐terminal region containing the four transmembrane domains mediates Sur7 localization to MCC/eisosomes. Mutation of 32 conserved residues in the N‐terminal region indicated that extracellular loop 1 is important, although these mutants generally displayed weak phenotypes. Surprisingly, two Cys residues in a conserved motif in extracellular loop 1 were not important. However, deletion of the entire 15 amino acid motif revealed that it was needed for proper membrane trafficking of Sur7. Deletion and substitution mutagenesis showed that the C terminus is important for resisting cell wall stress. This is significant as it indicates Sur7 carries out an important role in the cytoplasm. Altogether, these results indicate that the N‐terminal region localizes Sur7 to MCC/eisosomes and that the C‐terminal domain promotes responses in the cytoplasm needed for cell wall morphogenesis and stress resistance.
Unsigned Matrix Completion

Inspired by real phase retrieval and low-rank matrix recovery, we introduce the problem of unsigned matrix retrieval, where the aim is to recover a matrix of bounded-rank from a sign-ambiguous version of it. Allowing for missing entries in addition to sign ambiguities leads to the problem of unsigned matrix completion. Under an algebraic geometry framework, we provide fundamental results regarding unique recovery up to a class of rank-preserving sign patterns and finite completability.
Production of aromatic three‐line hybrid rice using novel alleles of BADH2

Abstract Aroma is a key grain quality trait that directly influences the market price of rice globally. Loss of function of betaine aldehyde dehydrogenase 2 (OsBADH2) affects the biosynthesis of 2‐acetyl‐1‐pyrroline (2‐AP), which is responsible for aroma in fragrant rice. The current study was aimed at creating new alleles of BADH2 using CRISPR/Cas9 gene editing technology under the genetic background of the japonica Ningjing 1 (NJ1) and indica Huang Huazhan (HHZ) varieties. Sensory evaluation and analysis using headspace solid‐phase microextraction gas chromatography–mass spectrometry (HS‐SPME‐GC‐MS) showed that the grains of the four homozygous T1 lines with new alleles of BADH2 (nj1‐cr BADH2‐1, nj1‐cr BADH2‐2, hhz‐cr BADH2‐1 and hhz‐cr BADH2‐2) produced moderate fragrance and had significantly increased 2‐AP content compared with wild‐types. Moreover, there were no significant differences in the amylose content and gelatinization temperature among the four lines with new alleles of BADH2 to the wild‐types. Thereafter, we crossed the HHZ background new alleles of BADH2 with CMS line Taonong 1A (TN1A) to produce a three‐line hybrid variety B‐Tao‐You‐Xiangzhan (BTYXZ) with increased grain aroma. The 2‐AP content in grains of the improved BTYXZ‐1 and BTYXZ‐2 reached at 26.16 and 18.74 μg/kg, and the gel consistency of BTYXZ‐1 and BTYXZ‐2 increased significantly by 9.1% and 6.5%, respectively, compared with the wild‐type Tao‐You‐Xiangzhan (TYXZ). However, the γ‐aminobutyric acid (GABA) content in the improved three‐line hybrid rice BTYXZ‐1 (5.6 mg/100 g) and BTYXZ‐2 (10.7 mg/100 g) was significantly lower than that of the TYXZ. These results demonstrated that CRISPR/Cas9 gene editing technology could be successfully utilized in improving aroma in non‐fragrant japonica and indica varieties. In addition, the newly developed BADH2 alleles provided important genetic resources for grain aroma improvement in three‐line hybrid rice.
Fast-Rate Loss Bounds via Conditional Information Measures with Applications to Neural Networks

We present a framework to derive bounds on the test loss of randomized learning algorithms for the case of bounded loss functions. Drawing from Steinke & Zakynthinou (2020), this framework leads to bounds that depend on the conditional information density between the output hypothesis and the choice of the training set, given a larger set of data samples from which the training set is formed. Furthermore, the bounds pertain to the average test loss as well as to its tail probability, both for the PAC-Bayesian and the single-draw settings. If the conditional information density is bounded uniformly in the size $n$ of the training set, our bounds decay as 1/n, This is in contrast with the tail bounds involving conditional information measures available in the literature, which have a less benign 1/√n dependence. We demonstrate the usefulness of our tail bounds by showing that they lead to nonvacuous estimates of the test loss achievable with some neural network architectures trained on MNIST and Fashion-MNIST.