Miracle-dz/UniFAR-FTUs huggingface dataset:
Fueling a Hot Debate on the Application of TiO2 Nanoparticles in Sunscreen

Titanium is one of the most abundant elements in the earth’s crust and while there are many examples of its bioactive properties and use by living organisms, there are few studies that have probed its biochemical reactivity in physiological environments. In the cosmetic industry, TiO2 nanoparticles are widely used. They are often incorporated in sunscreens as inorganic physical sun blockers, taking advantage of their semiconducting property, which facilitates absorbing ultraviolet (UV) radiation. Sunscreens are formulated to protect human skin from the redox activity of the TiO2 nanoparticles (NPs) and are mass-marketed as safe for people and the environment. By closely examining the biological use of TiO2 and the influence of biomolecules on its stability and solubility, we reassess the reactivity of the material in the presence and absence of UV energy. We also consider the alarming impact that TiO2 NP seepage into bodies of water can cause to the environment and aquatic life, and the effect that it can have on human skin and health, in general, especially if it penetrates into the human body and the bloodstream.
MD-2 Homologue Recognizes the White Spot Syndrome Virus Lipid Component and Induces Antiviral Molecule Expression in Shrimp

Key Points Shrimp MD-2 homologue ML1 recognizes a lipid component of white spot syndrome virus. Shrimp ML1 activates NF-κB signaling. ML1 induces the expression of Vago, which is a functional analogue of IFN. The myeloid differentiation factor 2 (MD-2)–related lipid-recognition (ML) domain is found in multiple proteins, including MD-2, MD-1, Niemann–Pick disease type C2, and mite major allergen proteins. The significance of ML proteins in antibacterial signal transduction and in lipid metabolism has been well studied. However, their function in host–virus interaction remains poorly understood. In the current study, we found that the ML protein family is involved in resistance against white spot syndrome virus in kuruma shrimp, Marsupenaeus japonicus. One member, which showed a high similarity to mammalian MD-2/MD-1 and was designated as ML1, participated in the antiviral response by recognizing cholesta-3,5-diene (CD), a lipid component of the white spot syndrome virus envelope. After recognizing CD, ML1 induced the translocation of Rel family NF-κB transcription factor Dorsal into the nucleus, resulting in the expression of Vago, an IFN-like antiviral cytokine in arthropods. Overall, this study revealed the significance of an MD-2 homologue as an immune recognition protein for virus lipids. The identification and characterization of CD–ML1–Dorsal–Vago signaling provided new insights into invertebrate antiviral immunity.
Relevance Vector Machines-Based Time Series Prediction for Incomplete Training Dataset: Two Comparative Approaches

Considering that real-life time series mixed with missing points cannot be directly modeled by using most of the supervised machine learning methods, this paper proposes a novel time series prediction method based on relevance vector machines for incomplete training dataset. Given the regularity between the missing inputs and outputs constructed by the phase space reconstruction, this paper imputes the missing inputs during the learning process by the values of their corresponding missing outputs such that the elements in kernel matrix related to the missing inputs are capable of being updated. This paper designs two strategies to estimate the missing outputs. The first one is based on the expectation maximization formulation in which a joint posterior distribution over the missing outputs and the weights vector is derived as a multivariate Gaussian form, and the another maximizes the marginal likelihood function with respect to the missing outputs and other hyperparameters. To verify the performance of the two proposed computing strategies, two synthetic time series and a real-life dataset are employed. The results indicate that the proposed methods have robust and better performance over the other methods when dealing with incomplete time series training dataset.
A Pilot Study Evaluating a Binge-Eating Screener in Children: Development of the Children’s Brief Binge-Eating Questionnaire in a Pediatric Obesity Clinic

Children referred to pediatric obesity programs are at high risk of binge-eating disorder (BED) symptoms. Our goal was to develop and evaluate the Children’s Brief Binge-Eating Questionnaire (CBBEQ) as a rapid screen of BED symptomatology. Seventy patients between the ages of 7 and 18 years (57% females) completed the CBBEQ and underwent the Eating Disorder Assessment for DSM-5 (EDA). Reliability and validity were assessed by examining results of the CBBEQ compared with the EDA, as well as measures of sleep, depression, and anxiety. Twenty-four of seventy (34%) children met full diagnostic interview criteria for BED and 12 (17%) met subclinical criteria. The CBBEQ demonstrated 100% specificity, 93% sensitivity, and a 100% negative predictive value for BED at a cutoff total score of 9. If confirmed in larger sample, this questionnaire could be a quick and accurate clinical tool for non–mental health providers to identify children at risk for BED.
Tudor-domain containing protein 5-like promotes male sexual identity in the Drosophila germline and is repressed in females by Sex lethal

For sexually reproducing organisms, production of male or female gametes depends on specifying the correct sexual identity in the germline. In D. melanogaster, Sex lethal (Sxl) is the key gene that controls sex determination in both the soma and the germline, but how it does so in the germline is unknown, other than that it is different than in the soma. We conducted an RNA expression profiling experiment to identify direct and indirect germline targets of Sxl specifically in the undifferentiated germline. We find that, in these cells, Sxl loss does not lead to a global masculinization observed at the whole-genome level. In contrast, Sxl appears to affect a discrete set of genes required in the male germline, such as Phf7. We also identify Tudor domain containing protein 5-like (Tdrd5l) as a target for Sxl regulation that is important for male germline identity. Tdrd5l is repressed by Sxl in female germ cells, but is highly expressed in male germ cells where it promotes proper male fertility and germline differentiation. Additionally, Tdrd5l localizes to cytoplasmic granules with some characteristics of RNA Processing (P-) Bodies, suggesting that it promotes male identity in the germline by regulating post-transcriptional gene expression.
Sigma‐1 receptor modulates neuroinflammation associated with mechanical hypersensitivity and opioid tolerance in a mouse model of osteoarthritis pain

Osteoarthritic pain is a chronic disabling condition lacking effective treatment. Continuous use of opioid drugs during osteoarthritic pain induces tolerance and may result in dose escalation and abuse. Sigma‐1 (σ1) receptors, a chaperone expressed in key areas for pain control, modulates μ‐opioid receptor activity and represents a promising target to tackle these problems. The present study investigates the efficacy of the σ1 receptor antagonist E‐52862 to inhibit pain sensitization, morphine tolerance, and associated electrophysiological and molecular changes in a murine model of osteoarthritic pain.
Diagnostic Utility of Pathological Investigations in Late Gestation Stillbirth: A Cohort Study

Objective Near term unexpected stillbirth is a common, complex diagnostic challenge. We review a large cohort of near term to term gestation unexpected fetal deaths to document the common patterns of pathology and evaluate the utility of various standard autopsy procedures. Methods A total of 123 perinatal autopsies consisting of 94 intrauterine fetal deaths (IUFDs) and 29 intrapartum deaths (IPDs) were reviewed. Deaths were classified according to the laboratory investigations establishing cause of death. Results Cause of death was attributable to placental pathology without autopsy in 55.3% of IUFD and 17% of IPD. Correlative findings at autopsy increased the ability to establish cause of death in 86.2% of IUFD and 62% of IPD. Histology was largely corroborative, with the brain, lungs, and heart demonstrating significant changes in 46%, 34.5%, and 13.8%, respectively. Microbiology was corroborative but demonstrated single organism growth in 6 of 29 cases of fatal acute chorioamnionitis. Newborn metabolic screening revealed only elevated thyroid-stimulating hormone levels in 3 cases, of questionable relevance. Aneuploidy was established by screening molecular studies in 5 IUFDs, all of which had external or visceral dysmorphism. Karyotype was established in 69 cases and was not contributory in any of the IPD: 3 IUFDs had changes of unknown significance. Cause of death was not established at autopsy in 9% of IUFD and 10% of IPD. Discussion This is the largest uniformly investigated cohort of late gestation unexpected fetal deaths studied. We confirm the importance of both placental and fetal autopsy in establishing cause of death. Autopsy histology, microbiology, and cytogenetics provide important but largely corroborative data.
DNA complexes with human apurinic/apyrimidinic endonuclease 1: structural insights revealed by pulsed dipolar EPR with orthogonal spin labeling

Abstract A DNA molecule is under continuous influence of endogenous and exogenous damaging factors, which produce a variety of DNA lesions. Apurinic/apyrimidinic sites (abasic or AP sites) are among the most common DNA lesions. In this work, we applied pulse dipolar electron paramagnetic resonance (EPR) spectroscopy in combination with molecular dynamics (MD) simulations to investigate in-depth conformational changes in DNA containing an AP site and in a complex of this DNA with AP endonuclease 1 (APE1). For this purpose, triarylmethyl (TAM)-based spin labels were attached to the 5′ ends of an oligonucleotide duplex, and nitroxide spin labels were introduced into APE1. In this way, we created a system that enabled monitoring the conformational changes of the main APE1 substrate by EPR. In addition, we were able to trace substrate-to-product transformation in this system. The use of different (orthogonal) spin labels in the enzyme and in the DNA substrate has a crucial advantage allowing for detailed investigation of local damage and conformational changes in AP-DNA alone and in its complex with APE1.
The Pol IV largest subunit CTD quantitatively affects siRNA levels guiding RNA-directed DNA methylation

Abstract In plants, nuclear multisubunit RNA polymerases IV and V are RNA Polymerase II-related enzymes that synthesize non-coding RNAs for RNA-directed DNA methylation (RdDM) and transcriptional gene silencing. Here, we tested the importance of the C-terminal domain (CTD) of Pol IV’s largest subunit given that the Pol II CTD mediates multiple aspects of Pol II transcription. We show that the CTD is dispensable for Pol IV catalytic activity and Pol IV termination-dependent activation of RNA-DEPENDENT RNA POLYMERASE 2, which partners with Pol IV to generate dsRNA precursors of the 24 nt siRNAs that guide RdDM. However, 24 nt siRNA levels decrease ∼80% when the CTD is deleted. RNA-dependent cytosine methylation is also reduced, but only ∼20%, suggesting that siRNA levels typically exceed the levels needed for methylation of most loci. Pol IV-dependent loci affected by loss of the CTD are primarily located in chromosome arms, similar to loci dependent CLSY1/2 or SHH1, which are proteins implicated in Pol IV recruitment. However, deletion of the CTD does not phenocopy clsy or shh1 mutants, consistent with the CTD affecting post-recruitment aspects of Pol IV activity at target loci.
Thorax-Net: An Attention Regularized Deep Neural Network for Classification of Thoracic Diseases on Chest Radiography

Deep learning techniques have been increasingly used to provide more accurate and more accessible diagnosis of thorax diseases on chest radiographs. However, due to the lack of dense annotation of large-scale chest radiograph data, this computer-aided diagnosis task is intrinsically a weakly supervised learning problem and remains challenging. In this paper, we propose a novel deep convolutional neural network called Thorax-Net to diagnose 14 thorax diseases using chest radiography. Thorax-Net consists of a classification branch and an attention branch. The classification branch serves as a uniform feature extraction–classification network to free users from the troublesome hand-crafted feature extraction and classifier construction. The attention branch exploits the correlation between class labels and the locations of pathological abnormalities via analyzing the feature maps learned by the classification branch. Feeding a chest radiograph to the trained Thorax-Net, a diagnosis is obtained by averaging and binarizing the outputs of two branches. The proposed Thorax-Net model has been evaluated against three state-of-the-art deep learning models using the patientwise official split of the ChestX-ray14 dataset and against other five deep learning models using the imagewise random data split. Our results show that Thorax-Net achieves an average per-class area under the receiver operating characteristic curve (AUC) of 0.7876 and 0.896 in both experiments, respectively, which are higher than the AUC values obtained by other deep models when they were all trained with no external data.
Predictive Value of First Posttreatment Imaging Using Standardized Reporting in Head and Neck Cancer

Objective The Neck Imaging Reporting and Data System (NI-RADS) is a standardized numerical reporting template for surveillance of head and neck squamous cell carcinoma (HNSCC). Our aim was to analyze the accuracy of NI-RADS on the first posttreatment fluorodeoxyglucose positron emission tomography/contrast-enhanced computed tomography (PET/CECT). Study Design Retrospective cohort study. Setting Academic tertiary hospital. Subject and Methods Patients with HNSCC with a 12-week posttreatment PET/CECT interpreted using the NI-RADS template and 9 months of clinical and radiologic follow-up starting from treatment completion between June 2014 and July 2016 were included. Treatment failure was defined as positive tumor confirmed by biopsy or Response Evaluation Criteria in Solid Tumors criteria. Cox proportional hazards models were performed. Results This study comprised 199 patients followed for a median of 15.5 months after treatment completion (25% quartile, 11.8 months; 75% quartile, 20.2 months). The rates of treatment failure increased with each incremental increase in NI-RADS category from 1 to 3 (4.3%, 9.1%, and 42.1%, respectively). A Cox proportional hazards model demonstrated a strong association between NI-RADS categories and treatment failure at both primary and neck sites (hazard ratio [HR], 2.60 and 5.22, respectively; P < .001). In the smaller treatment subgroup analysis, increasing NI-RADS category at the primary site in surgically treated patients and treatment failure did not achieve statistically significant association (HR, 0.88; P = .82). Conclusion Increasing NI-RADS category at the baseline posttreatment PET/CECT is strongly associated with increased risk of treatment failure in patients with HNSCC.
Tuning ZnO Sensors Reactivity toward Volatile Organic Compounds via Ag Doping and Nanoparticle Functionalization

Nanomaterials for highly selective and sensitive sensors toward specific gas molecules of volatile organic compounds (VOCs) are most important in developing new-generation of detector devices, for example, for biomarkers of diseases as well as for continuous air quality monitoring. Here, we present an innovative preparation approach for engineering sensors, which allow for full control of the dopant concentrations and the nanoparticles functionalization of columnar material surfaces. The main outcome of this powerful design concept lies in fine-tuning the reactivity of the sensor surfaces toward the VOCs of interest. First, nanocolumnar and well-distributed Ag-doped zinc oxide (ZnO:Ag) thin films are synthesized from chemical solution, and, at a second stage, noble nanoparticles of the required size are deposited using a gas aggregation source, ensuring that no percolating paths are formed between them. Typical samples that were investigated are Ag-doped and Ag nanoparticle-functionalized ZnO:Ag nanocolumnar films. The highest responses to VOCs, in particular to (CH3)2CHOH, were obtained at a low operating temperature (250 °C) for the samples synergistically enhanced with dopants and nanoparticles simultaneously. In addition, the response times, particularly the recovery times, are greatly reduced for the fully modified nanocolumnar thin films for a wide range of operating temperatures. The adsorption of propanol, acetone, methane, and hydrogen at various surface sites of the Ag-doped Ag8/ZnO(0001) surface has been examined with the density functional theory (DFT) calculations to understand the preference for organic compounds and to confirm experimental results. The response of the synergistically enhanced sensors to gas molecules containing certain functional groups is in excellent agreement with density functional theory calculations performed in this work too. This new fabrication strategy can underpin the next generation of advanced materials for gas sensing applications and prevent VOC levels that are hazardous to human health and can cause environmental damages.
Surgical Repair of Small Bowel Fistulas: Risk Factors of Complications or Fistula Recurrence

Background Definitive surgical repair of persistent fistulas of the small intestine remains a surgical challenge with a high rate of re-fistulation and mortality. The aim of this study was to evaluate the type and incidence of complications after definitive surgical repair, and to identify factors predictive of severe postoperative complications or fistula recurrence. Material/Methods This was a retrospective study of 42 patients who underwent elective surgical repair of a persistent fistula of the small intestine. The analysis included preoperative and intraoperative parameters. Results The healing rate after definitive surgery was 71.4%. Postoperative complications developed in 88.1% of patients. The mortality rate was 7.2%. Fistula recurrence was recognized in 21.4% of cases. Overall, 93 complications occurred in 37 patients. The most common complications were septic (48.0%). Hemorrhagic and digestive tract-related complications accounted for 19.0% and 15.0% of all complications, respectively. Severe complications (Clavien-Dindo grade III–V) made up 28.0% of all complications. In univariate analysis, multiple fistulas (p=0.03), higher C-reactive protein level (p=0.01), and longer time interval from admission to definitive surgery (p=0.01) were associated with an increased risk of severe complications or fistula recurrence. In multivariate analysis, only multiple fistulas were an independent risk factor for severe complications or fistula recurrence (OR=8.2, p=0.04). Conclusions Fistula complexity determines the risk of severe postoperative complications or fistula recurrence after definitive surgical repair of the persistent small intestine fistulas. Inflammatory parameters should be normalized before definitive surgery.
Fetal phenotypes emerge as genetic technologies become robust

Prenatal genomic evaluation of the fetus is available at decreasing cost and with a faster turnaround time. However, fetal genotype‐phenotype correlations are in their infancy. By comparison, pediatric and adult genotype‐phenotype databases are well established and publicly accessible. A similar system for fetal genomics is lacking. When a fetal anomaly is identified by ultrasound imaging, a genetic diagnosis provides important information. However, fetal prognostic counseling is problematic if the only available information is based on outcomes following postnatal diagnoses. The same conditions identified prenatally may have more benign or more deleterious outcomes. Also, the condition may evolve over the pregnancy itself. As genomic testing increasingly examines fetal DNA at a single nucleotide level, the concomitant in utero phenotype deserves equal attention. Often, the reports of fetal phenotype are limited. Among sonologists, an increased awareness of attaining and communicating detailed fetal phenotypes is needed. The interpretation of expanded prenatal sequencing is reliant on deeper fetal phenotyping. The information gained significantly impacts clinical care and understanding of fetal development. This case series highlights: the broad spectrum of fetal phenotypes for known genetic conditions, phenotype progression during pregnancy, and the need to supplement systematic imaging with descriptive details when assessing fetuses with malformations.
Human Activity Recognition Using Inertial Sensors in a Smartphone: An Overview

The ubiquity of smartphones and the growth of computing resources, such as connectivity, processing, portability, and power of sensing, have greatly changed people’s lives. Today, many smartphones contain a variety of powerful sensors, including motion, location, network, and direction sensors. Motion or inertial sensors (e.g., accelerometer), specifically, have been widely used to recognize users’ physical activities. This has opened doors for many different and interesting applications in several areas, such as health and transportation. In this perspective, this work provides a comprehensive, state of the art review of the current situation of human activity recognition (HAR) solutions in the context of inertial sensors in smartphones. This article begins by discussing the concepts of human activities along with the complete historical events, focused on smartphones, which shows the evolution of the area in the last two decades. Next, we present a detailed description of the HAR methodology, focusing on the presentation of the steps of HAR solutions in the context of inertial sensors. For each step, we cite the main references that use the best implementation practices suggested by the scientific community. Finally, we present the main results about HAR solutions from the perspective of the inertial sensors embedded in smartphones.
Safety verification of state/time-driven hybrid systems using barrier certificates

This paper addresses formal safety verification issue of hybrid systems which resort either state-driven or time-driven strategies. Modeling hybrid systems as linear hybrid automata, we provide a formal method for safety verification by constructing barrier certificates whose existence guarantees the soundness of safety specifications. Barrier certificates for safety of state-driven hybrid systems are presented. Particularly, we propose a formal method for constructing time-dependent barrier certificates and show its sufficiency for safety of time-driven hybrid systems. Through formulating the search of time-dependent barrier certificates as a bilinear sum-of-squares programming problem, a computationally tractable method is proposed to derive a certification on safety in polynomial time. A numerical example illustrates the efficiency of the proposed approach.