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Circular RNAs (circRNAs) are an endogenous mircoRNA sponge that could act as potential biomarkers for the diagnosis and treatment of diseases. However, the role of circRNAs in asthma is far from clear.

The aim of this study is to assess the diagnostic and therapeutic value of hsa_circ_0002594 for T helper (Th) 2-mediated allergic asthma.

The expression profiles of hsa_circ_0002594 in CD4+ T cells were revealed by circRNA microarray. Hsa_circ_0002594 expression was confirmed via quantitative real-time PCR (qRT-PCR) in asthmatic patients and healthy subjects. Hsa_circ_0002594 levels were compared between subgroups. The clinical diagnostic abilities and therapeutic response of hsa_circ_0002594 were evaluated. The analyses utilized included a student's t test, nonparametric tests, Spearman's rank-order correlation, Fisher's exact test, and the generation of receiver operating characteristic (ROC) curves.

Hsa_circ_0002594 was upregulated and positively correlated with fraction of exhaled nitric oxide while negatively correlated with methacholine dose producing a decrease of 20% from baseline in forced expiratory volume in the first second (PD20) in CD4+ T cells of asthma. Furthermore, hsa_circ_0002594 expression was higher in subgroups with a family history, skin pricking test (SPT)-positive, or Th2-high. The hsa_circ_0002594-high subgroup was more frequently associated with Th2-high biomarker profiles and positive SPT. Hsa_circ_0002594 was decreased after inhaled corticosteroids (ICS) treatment. ROC curve analyses of hsa_circ_0002594 showed high area under the curve values in the presence of ICS or not.

Our data suggested that hsa_circ_0002594 was upregulated in CD4+ T cells and might have potential value in the diagnosis and treatment of Th2-mediated allergic asthma.

Our data suggested that hsa_circ_0002594 was upregulated in CD4+ T cells and might have potential value in the diagnosis and treatment of Th2-mediated allergic asthma.

Hidradenitis suppurativa (HS) and plaque psoriasis (Pso) are supposed to have a coprevalence. However, data showing a more detailed description of patients with both diseases are rare. In this study, we characterized patients with both skin diseases in terms of onset, disease course, severity, concomitant diseases and therapeutical management.

Data from 28 patients with a confirmed codiagnosis of HS and Pso from 2 university hospitals presented between 2015 and 2019 were evaluated retrospectively. For further characterization, patients were divided into different cohorts depending on whether HS or Pso was diagnosed as the first disease.

The average age of patients with a coprevalence of both diseases was 44.4 years with a female/male ratio of 11.15. Fifteen patients were diagnosed first with HS at an average age of 22.8 years, 13 patients first showed symptoms of Pso at a mean age of 21.7 years. The average time to the onset of the corresponding second disease was 14.3 years. Patients with HS as first dith an increased risk of development of obesity and psychiatric comorbidity in both cohorts.

From cell phones to aerospace, artificial intelligence (AI) has wide-reaching influence in the modern age. In this review, we discuss the application of AI solutions to an equally ubiquitous problem in cytopathology - thyroid fine needle aspiration biopsy (FNAB). Thyroid nodules are common in the general population, and FNAB is the sampling modality of choice. The resulting prevalence in the practicing pathologist's daily workload makes thyroid FNAB an appealing target for the application of AI solutions.

This review summarizes all available literature on the application of AI to thyroid cytopathology. We follow the evolution from morphometric analysis to convolutional neural networks. We explore the application of AI technology to different questions in thyroid cytopathology, including distinguishing papillary carcinoma from benign, distinguishing follicular adenoma from carcinoma and identifying non-invasive follicular thyroid neoplasm with papillary-like nuclear features by key words and phrases. Key Messages The current literature shows promise towards the application of AI technology to thyroid fine needle aspiration biopsy. Much work is needed to define how this powerful technology will be of best use to the future of cytopathology practice.

This review summarizes all available literature on the application of AI to thyroid cytopathology. We follow the evolution from morphometric analysis to convolutional neural networks. We explore the application of AI technology to different questions in thyroid cytopathology, including distinguishing papillary carcinoma from benign, distinguishing follicular adenoma from carcinoma and identifying non-invasive follicular thyroid neoplasm with papillary-like nuclear features by key words and phrases. Key Messages The current literature shows promise towards the application of AI technology to thyroid fine needle aspiration biopsy. Much work is needed to define how this powerful technology will be of best use to the future of cytopathology practice.

Hemochromatosis gene (HFE)-associated hereditary hemochromatosis (HH) is characterized by downregulation of hepcidin synthesis, leading to increased intestinal iron absorption.

The objectives were to characterize and elucidate a possible association between gene expression profile, hepcidin levels, disease severity, and markers of inflammation in HFE-associated HH patients.

Thirty-nine HFE-associated HH patients were recruited and assigned to 2 groups according to genetic profile C282Y homozygotes in 1 group and patients with H63D, as homozygote or in combination with C282Y, in the other group. Eleven healthy first-time blood donors were recruited as controls. Gene expression was characterized from peripheral blood cells, and inflammatory cytokines and hepcidin-25 isoform were quantified in serum. Biochemical disease characteristics were recorded.

Elevated levels of interleukin 8 were observed in a significant higher proportion of patients than controls. In addition, compared to controls, gene expression of ζ-globin was significantly increased among C282Y homozygote patients, while gene expression of matrix metalloproteinase 8, and other neutrophil-secreted proteins, was significantly upregulated in patients with H63D.

Different disease signatures may characterize HH patients according to their HFE genetic profile. Studies on larger populations, including analyses at protein level, are necessary to confirm these findings.

Different disease signatures may characterize HH patients according to their HFE genetic profile. Studies on larger populations, including analyses at protein level, are necessary to confirm these findings.Assessing the position of the Bragg peak (BP) in hadron radiotherapy utilizing prompt-gamma imaging (PGI) presents many challenges in terms of detector physics. Gamma detectors with the capability of extracting the best energy, timing, and spatial information from each gamma interaction, as well as with high detection efficiency and count rate performance, are needed for this application. In this work we present the characterization of a pixel Čerenkov charge induction (CCI) thallium bromide (TlBr) detector in terms of energy and and electron drift time for its potential use in PGI. The CCI TlBr detector had dimensions of 4 × 4 × 5 mm3 and one of its electrodes was segmented in pixels with 1.7 mm pitch. A silicon photomultiplier (SiPM) was optically coupled to one of the faces of the TlBr slab to read out the Čerenkov light promptly emitted after the interaction of a gamma ray. The detector was operated stand-alone and the 1.275 prompt gammas from a 22Na radioactive source were used for the study. The electro excellent energy, timing, and spatial resolution performance and are a very promising option for PGI in hadron therapy.

Sleep spindles in the electroencephalogram (EEG) are significant in sleep analysis related to cognitive functions and neurological diseases, and thus are of great clinical interests. An automatic sleep spindle detection algorithm could help decrease the workload of visual inspection by sleep clinicians.

We propose a robust two-stage approach for sleep spindle detection using single-channel EEG. In the pre-detection stage, a stable number of sleep spindle candidates are discovered using the Teager energy operator with adaptive parameters, where the number of true sleep spindles are ensured as many as possible to maximize the detection sensitivity. In the refinement stage, representative features are designed and a bagging classifier is exploited to further recognize the true spindles from all candidates, in order to remove the false detection in the first stage.

Using the union of all experts' annotations as the ground truth, its performance outperforms state-of-the-art works in terms of F1-score on two public databases (F1-score 0.814 for MASS dataset and 0.690 for DREAMS dataset). The annotation consistency between the proposed method and certain selected expert as the trainer could exceed the consistency between two human experts.

The proposed sleep spindle detection method is based on single-channel EEG thus introduces as less interference to the subjects as possible. It is robust to subject variations between databases and is capable of learning certain annotation rules, which is expected to help facilitate the manual labelling of certain experts. In addition, this method is fast enough for real-time applications.

The proposed sleep spindle detection method is based on single-channel EEG thus introduces as less interference to the subjects as possible. It is robust to subject variations between databases and is capable of learning certain annotation rules, which is expected to help facilitate the manual labelling of certain experts. In addition, this method is fast enough for real-time applications.As different low-dimensional materials are sought to be incorporated into microelectronic devices, graphene integration is dependent on the development of band gap opening strategies. Amidst the different methods currently investigated, application of strain and use of electronic quantum confinement have shown promising results. In the present work, epitaxial graphene nanoribbons (GNR), formed by surface graphitization of SiC (0001) on crystalline step edges, were submitted to photochemical chlorination. The incorporation of Cl into the buffer layer underlying graphene increased the compressive uniaxial strain in the ribbons. Such method is a promising tool for tuning the band gap of GNRs.The figure 1 from our paper (Nanotechnology, 2015. 26(33) 335201) was wrongly replaced during the process of revising the manuscript. And the corrected figure 1 is as follows.Si δ-doped AlGaAs/InGaAs/AlGaAs quantum well (QW) structure is commonly adopted as one of the core elements in modern electric and optoelectronic devices. Here, the time dependent photoconductivity spectra along the active InGaAs QW channel in a dual and symmetric Si δ-doped AlGaAs/InGaAs/AlGaAs QW structure are systematically studied under various temperatures (T = 80-300 K) and various incident photon energies (E in = 1.10-1.88 eV) and intensities. In addition to positive photoconductivity, negative photoconductivity (NPC) was observed and attributed to two origins. For T = 180-240 K with E in = 1.51-1.61 eV, the trapping of the photo-excited electrons by the interface states located inside the conduction band of InGaAs QW layer is one of the origins for NPC curves. Selleck NXY-059 For T = 80-120 K with E in = 1.10-1.63 eV, the photoexcitation of the excess 'supersaturated' electrons within the active InGaAs QW caused by the short cooling process is another origin.

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