Defective Signaling Research Articles

Potential brain biomarkers in patients with Autism spectrum syndrome

Autism spectrum disorder (ASD) is referred as a cluster of neurodevelopmental disorders with relatively high incidence. ASD is believed to be a multifactorial condition, and genetics is one of the most important factors in its formation. Therefore, profiling gene expression in ASD patients can lead to the identification of new molecular insights. To evaluate gene expression patterns, we have utilized NCBI GEO microarray data. The dataset of ASD patients (GSE28475, GSE28521, GSE38322 and GSE113834) were defined as two meta-data, Total brain meta-data and Lobe specified meta-data. Meta-analysis and batch effect removal was conducted by the SVA package. Microarray data analysis was performed using the LIMMA package under R 4.2.1 software. Total Meta-Analysis (TMA) identified 525 significantly differentially expressed genes (DEGs) in ASD patient’s brain. The temporal and frontal lobes of ASD patients showed 96 and 23 DEGs respectively. Among the mentioned DEGs, there were 11 common DEGs between the temporal and frontal lobes that were also dysregulated in TMA except for UTP4 which was only dysregulated in the temporal and frontal lobes. However, the occipital and cerebellum lobes did not show any significant DEGs. Enrichment analysis pointed out the vital roles of identified DEGs in transmembrane transportation, ATP production, and cellular respiration. According to our findings, gene expression profile in the temporal and frontal lobes of ASD patients are significantly different than a control group. This aberrant gene expression potentially leads to crucial complications in nerve signal transmission and defects energy production in neurons. Therefore, potential therapeutic targets may be suggested based on these findings.

SM-GMVAE: an intelligent model for defect quantification evaluation based on few ultrasonic signals

The conventional defect quantification evaluation approaches based on machine learning requires massive amounts of labelled defect signals, which is expensive and time-consuming works. This paper proposed a novel Similarity Metric Gaussian Mixture Variational Auto-Encoder (SM-GMVAE) model, which enables quantify defect with few labelled defect signals. The SM-GMVAE model is designed based on few-shot learning, which includes two modules: feature extraction (FE) module and similarity metric (SM) module. The FE module is designed to extract the feature of defect signal via the Variational Auto-Encoder (VAE). The SM module is used to measure the similarity of two defect signals based on the Gaussian Mixture Model (GMM). Moreover, sparse filtering techniques are used to enhance the sparsity of the features in the SM module. To validate proposed model, some specimens with four various depth defects are designed and fabricated for ultrasonic non-destructive testing experiments. A dataset with defects of different depths is established to compare proposed model with other methods. Our method obtains state-of-the-art experimental results with few labelled defect signals. Different from many published papers, our model is trained with few labelled data, which is more close to engineering practical application than other evaluation model trained using large numbers of labelled data. In other words, the developed approach can realize more complex defect evaluation tasks (such as: size, location, shapes, etc) at very low data labelling cost.

A single center experience on PI3K/AKT/MTOR signaling defects: Towards pathogenicity assessment for four novel defects.

Phosphoinositide 3 kinases (PI3K) are lipid kinases expressed in lymphocytes/myeloid cells. PI3K/AKT/mTOR signaling defects present with recurrent infections, autoimmunity, lymphoproliferation, and agammaglobulinemia. To characterize the PI3K/AKT/mTOR pathway defects and perform pathway analyses to assess novel variant pathogenicity. We included 12 patients (heterozygous PIK3CD (n = 9) and PIK3R1 (n = 1) (activated PI3K delta syndrome (APDS) with gain-of-function mutations) and homozygous PIK3R1 variant (n = 2)), performed clinical/laboratory/genetic evaluation, and flow cytometric PI3K/AKT/mTOR pathway analyses. Median age at onset of complaints was 17.5 months (3 months to 12 years) and at diagnosis was 15.7 years (2.5-37) in APDS. Median diagnostic delay was 12.9 years (1.6-27). Recurrent respiratory tract infections (90%), lymphoproliferation (70%), autoimmune/inflammatory findings (60%), and allergy (40%) were common in APDS. Recurrent viral infections were present in 4/10 and malignancy (non-Hodgkin lymphoma and testicular yolk sac tumor) was present in 2/10 in APDS. Low CD4+ T cells(5/8) with increased CD4+ effector memory (8/8) and CD4+ TEMRA cells (6/8) were present in the given number of APDS patients. We diagnosed tubulointerstitial nephritis, Langerhans cell histiocytosis, and late-onset congenital adrenal hyperplasia in APDS. Allergic findings, lymphoproliferation/malignancy, and high IgM were present in the APDS but not in PIK3R1 deficiency. Low IgM/IgG/CD19+ B cell counts were characteristic in patients with PIK3R1 homozygous loss-of function mutations. Differential diagnosis with combined immunodeficiency and diseases of immune dysregulation make molecular genetic analysis crucial for diagnosing mTOR pathway defects. It is easy to differentiate APDS and homozygous PIK3R1 defects with specific laboratory features. Additionally, mTOR pathway functional analysis is a definitive diagnostic and pathogenicity assessment tool for novel APDS mutations.

Dysbiosis-activated IL-17-producing T cells promote skin immunopathological progression in mice deficient of the Notch ligand Jag1 in keratinocytes

BackgroundThe Notch signaling pathway is an evolutionarily conserved regulatory cascade critical in skin development and homeostasis. Mice deficient of Notch signaling molecules have impaired skin and hair follicle development associated with local tissue inflammation. However, mechanisms underlying skin inflammation and pathology resulting from defective Notch signals are not well understood. ObjectiveTo dissect molecular and cellular mechanisms underlying development of skin immunopathology in mice defective of the Notch ligand Jagged-1 (Jag1). MethodsWe assessed involvement of microbiota and immune cell subsets in skin pathogenic symptoms in Foxn1CreJag1fl/fl mice that were deficient of Jag1 in keratinocytes. We also used RNA-seq and 16S rRNA gene-seq analyses to identify molecular factors and bacterial species contributing to skin pathologic symptoms in Foxn1CreJag1fl/fl mice. ResultsCompared to Jag1-sufficient littermate control mice, Foxn1CreJag1fl/fl mice had specific expansion of IL-17a-producing T cells accompanying follicular and epidermal hyperkeratosis and cyst formation while antibody blockage of IL-17a reduced the skin pathology. RNA-sequencing and 16S rRNA gene-sequencing analyses revealed dysregulated immune responses and altered microbiota compositions in the skin of Foxn1CreJag1fl/fl mice. Antibiotic treatment completely prevented over-activation of IL-17a-producing T cells and alleviated skin pathology in Foxn1CreJag1fl/fl mice. ConclusionDysbiosis-induced over-activation of IL-17a-producing T cells is critically involved in development of skin pathology in Foxn1CreJag1fl/fl mice, establishing Foxn1CreJag1fl/fl mice as a useful model to study pathogenesis and therapeutic targets in microbiota-IL-17-mediated skin inflammatory diseases such as hidradenitis suppurativa (HS) and psoriasis.

Defect Recognition and Classification Using Ultrasonic Scattered Signals Based on Convolutional Neural Network

Abstract Carbon Fiber Reinforced Polymer (CFRP) is widely used in the aerospace, aircraft, and railway industries because of its remarkable advantages, such as its lightweight and high strength. Detecting and identifying defects in CFRP is crucial for ensuring its secure and efficient use. Ultrasonic non-destructive testing is one of the most practical and effective methods for defect detection and identification. The ultrasonic scattered signals of defects, which contain abundant defect feature information, are advantageous for defect recognition and classification. However, the anisotropy and inhomogeneity of CFRP, which lead to a low signal-to-noise ratio and poor image quality, pose challenges in flaw recognition. To address the issue, this paper proposes using Convolutional Neural Networks (CNN) methods for defect classification, which can adequately extract information from ultrasonic scattered signals directly. The scattering signals from various types of defects in CFRP, including the different sizes of holes and folds, were selected as inputs for CNN models. Different network models combining Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) with 1D-CNN were employed to classify and identify defect signals. To generate sufficient input sample signals, the data sets were further enlarged by incorporating noise into the original signals. The experimental results showed that using the 1D-LSTM-CNN and 1D-GRU-CNN network models can reduce computational resources while ensuring the accuracy of defect recognition.

Research on Phased Array Ultrasonic Imaging Method Based on Time Reversal Theory

Abstract With the wide application of additive manufacturing components and composite materials, it is of great significance to detect defects with non-destructive testing methods in the material manufacturing process and in service. Due to the strong attenuation and inhomogeneity characteristics, it is inefficient and poor imaging results to detect its internal defects by conventional ultrasonic testing methods. To improve the detection accuracy, this paper proposes an improved imaging algorithm with time reversal-total focusing method (TR-TFM) imaging technology to improve the defects detection in strongly attenuating materials. The experimental results show that the amplitude of the defect signal is increased by 8.30 dB, and compared with total focusing method (TFM), the diameter of the detected defect with TR-TFM imaging is increased from 1.20 mm to 1.60 mm, which is more adjacent to the accurate size. Meanwhile, with the sparse matrix based on FMC data, TR-TFM could obtain the same image quality with the approximate time of TFM imaging.

Research on signal denoising algorithm based on ICEEMDAN eddy current detection

This study addresses the challenges of non-stationarity and significant background noise interference in eddy current detection signals by proposing a noise reduction method based on Improved Complete Ensemble Empirical Mode Decomposition with Adapted Noise (ICEEMDAN). The process commences with the signal being decomposed using Improved Complete Ensemble Empirical Mode Decomposition with Adapted Noise into a finite number of Intrinsic Mode Functions (IMFs). Each Intrinsic Mode Function is then evaluated for the presence of high-frequency noise using a Power Spectral Density (PSD) analysis. The high-frequency noise present in the Intrinsic Mode Functions is then reduced using Normalized Least Mean Squares (NLMS) before being reconstructed with the remaining Intrinsic Mode Functions. Subsequently, the reconstructed signals are subjected to another round of decomposition using Improved Complete Ensemble Empirical Mode Decomposition with Adapted Noise. The Pearson Product Moment Correlation Coefficient (PPMCC) is utilised to calculate the correlation between the Intrinsic Mode Functions within each layer, retaining those with a strong correlation to further attenuate noise. Ultimately, the local maxima judgement method selectively amplifies defect signals by assessing changes in peak and valley degrees, thereby improving the signal-to-noise ratio of the eddy current detection signal. The experimental results demonstrate that, in comparison to the use of only the conventional Improved Complete Ensemble Empirical Mode Decomposition with Adapted Noise and Normalized Least Mean Squares denoising methods, the proposed method increases the Signal-to-Noise Ratio (SNR) by 1.08 dB and 2.31 dB, respectively, and decreases the Mean Square Error (MSE) by 106.9 and 223.9, respectively. The false alarm rate for stainless steel welded tubes with defects is 1.4%, while the false alarm rate for stainless steel welded tubes without defects is 0.4%.

Subcell‐Resolved Electroluminescence Imaging of Monolithic Perovskite/Silicon Tandem Solar Cell for High‐Throughput Characterization

In the midterm future, the photovoltaic industry is expected to be dominated by two‐terminal (2T) perovskite–silicon (pero–Si) tandem solar cells, which have high energy conversion efficiency and require characterization for large‐scale production. Electroluminescence (EL) imaging is one of the most prevalent and nondestructive techniques for defect detection, recognition, and characterization in Si‐solar cells in mass production. This work presents an EL setup that enables fast, simultaneous, and separate luminescence capture from the two subcells of pero–Si tandem devices. To demonstrate the setup, several encapsulated 2T pero–Si tandem samples are investigated. First, the effect that resistive coupling between the two subcells has on defect appearance in EL images is recorded. Therefore, EL image under different operational conditions is recorded. A strong dependence of defect signatures on current injection is observed, that is explained partly by resistive coupling but partly as well by injection‐dependent changes of the prevalent defects in the cells. An investigation of preconditioning under dark forward operation reveals significant local decrease of EL intensity going along with rapid reversible or irreversible and severe degradation close to the edges of the samples. This degradation takes place under forward bias during a period of ≈1 h.

Unraveling the unphosphorylated STAT3-unphosphorylated NF-κB pathway in loss of function STAT3 Hyper IgE syndrome.

Patients with loss of function signal transducer and activator of transcription 3-related Hyper IgE Syndrome (LOF STAT3 HIES) present with recurrent staphylococcal skin and pulmonary infections along with the elevated serum IgE levels, eczematous rashes, and skeletal and facial abnormalities. Defective STAT3 signaling results in reduced Th17 cells and an impaired IL-17/IL-22 response primarily due to a compromised canonical Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway that involves STAT3 phosphorylation, dimerization, nuclear translocation, and gene transcription. The non-canonical pathway involving unphosphorylated STAT3 and its role in disease pathogenesis, however, is unexplored in HIES. This study aims to elucidate the role of unphosphorylated STAT3-unphosphorylated NF-κB (uSTAT3-uNF-κB) activation pathway in LOF STAT3 HIES patients. The mRNA expression of downstream molecules of unphosphorylated STAT3-unphosphorylated NF-κB pathway was studied in five LOF STAT3 HIES patients and transfected STAT3 mutants post-IL-6 stimulation. Immunoprecipitation assays were performed to assess the binding of STAT3 and NF-κB to RANTES promoter. A reduced expression of the downstream signaling molecules of the uSTAT3-uNF-κB complex pathway, viz., RANTES, STAT3, IL-6, IL-8, ICAM1, IL-8, ZFP36L2, CSF1, MRAS, and SOCS3, in LOF STAT3 HIES patients as well as the different STAT3 mutant plasmids was observed. Immunoprecipitation studies showed a reduced interaction of STAT3 and NF-κB to RANTES in HIES patients. The reduced expression of downstream signaling molecules, specially RANTES and STAT3, confirmed the impaired uSTAT3-uNF-κB pathway in STAT3 LOF HIES. Decreased levels of RANTES and STAT3 could be a significant component in the disease pathogenesis of Hyper IgE Syndrome.

Medulloblastomas Initiated by Homologous Recombination Defects in Mice

Germline mutations of homologous-recombination (HR) genes are among the top contributors to medulloblastomas. A significant portion of human medulloblastomas exhibited genomic signatures of HR defects. We asked whether ablation of Brca2, Palb2, and their related Brca1 and Bccip genes, in the mouse brain can differentially initiate medulloblastomas. We established conditional knockout mouse models of these HR-genes, and a conditional knockdown of Bccip (shBccip-KD). Deletion of any of these genes led to microcephaly and neurological defects, with Brca1- and Bccip- producing the worst. Trp53 co-deletion significantly rescued the microcephaly with Brca1, Palb2, and Brca2 deficiency, but it exhibited limited impact on Bccip- mice. For the first time, inactivation of either Brca1 or Palb2 with Trp53 was found to induce medulloblastomas. Bccip/Trp53 deletions failed, despite that shBccip-CKD was highly penetrative, to induce medulloblastomas. The tumors displayed diverse immunohistochemical features and chromosome copy number variation. While there were widespread upregulations of cell proliferative pathways, most of the tumors expressed biomarkers of the Sonic Hedgehog subgroup. The MBs developed from Brca1-, Palb2-, and Brca2- mice were highly sensitive to a PARP inhibitor, but not the ones from shBccip-CKD mice. Our models recapitulate the spontaneous medulloblastoma development with high penetrance and narrow time-window, providing ideal platforms to test therapeutic agents with the ability to differentiate HR defective and proficient tumors.

Study on Denoising Method of Weld Defect Signal Based on SSA-VMD-WPD

Defects in welds can affect the structural safety and reliability of workpieces. Currently, the method of using phased array ultrasonic inspection technology for non-destructive testing of weld structures with high detection efficiency, good sensitivity, and good visualization of the results is widely used. However, the defective A-scan data collected by the ultrasonic phased array detector inevitably contain noise data, including the test piece material structure noise, equipment noise, and environmental noise, which undoubtedly affects the analysis of the A-scan signal. In addition, when defects are interpreted, the presence of noise also interferes with the process, which affects the accuracy of the interpretation. Therefore, to enhance the accuracy of defect identification based on phased array ultrasonic inspection technology, we must prevent the series of consequences caused by misjudgments. In this study, ultrasonic phased array inspection experiments were carried out, and the specific process flow of ultrasonic phased array inspection of flat plate butt welds was summarized. Utilizing pre-fabricated flat plate butt specimen blocks containing five types of typical defects, defect A-sweep signals based on ultrasonic phased array inspection were obtained. Combining the sparrow optimization algorithm (SSA), variational mode decomposition (VMD), and wavelet packet decomposition (WPD), a defect signal noise reduction method based on parameter optimization was studied. A noise reduction study was carried out using the noise-added simulated signal, and the results indicated that the noise reduction method proposed in this paper had a better noise reduction effect and the proposed method could effectively retain the detailed features of the ultrasonic phased array defective A-scan signal and realize the noise reduction processing of the defective A-scan signal.

Effects of uneven wall thickness of steel pipes on magnetic permeability perturbation testing for internal defects

ABSTRACT Magnetic Permeability Perturbation testing (MPPT) has the advantage of high sensitivity for deeply buried defects in steel pipes. However, in complex working conditions, variations in the partial wall thickness of the pipe can affect the defect detection results. The paper discusses the influence mechanism of uneven wall thickness on the MPPT of internal defects on steel pipes and analyzes the magnetic field distribution caused by uneven wall thickness which influences on the magnetic permeability perturbation (MPP) of internal defects. The MPP is enhanced at the thinning wall and weakened at the thickening wall. The effect of uneven wall thickness on MPPT signals is confirmed through simulation and experiment. The signal of defects in thinning wall is enhanced, while the signal of defects in thickening wall is weakened. The greater the wall thickness variation, the degree of signal distortion is more significant. Experimental results show that uneven wall thickness has an effect on the detection of the defects with different depths. Finally, a method using deep saturation magnetisation is proposed to mitigate the inconsistent signals caused by uneven wall thickness. The findings will contribute to quantitative evaluation of defects in MPPT.

Heart failure with preserved ejection fraction.

Heart failure with preserved ejection fraction (HFpEF) accounts for nearly half of all heart failure cases and has a prevalence that is expected to rise with the growing ageing population. HFpEF is associated with significant morbidity and mortality. Specific HFpEF risk factors include age, diabetes, hypertension, obesity and atrial fibrillation. Haemodynamic contributions to HFpEF include changes in left ventricular structure, diastolic and systolic dysfunction, left atrial myopathy, pulmonary hypertension, right ventricular dysfunction, chronotropic incompetence, and vascular dysfunction. Inflammation, fibrosis, impaired nitric oxide signalling, sarcomere dysfunction, and mitochondrial and metabolic defects contribute to the cellular and molecular changes observed in HFpEF. HFpEF impacts multiple organ systems beyond the heart, including the skeletal muscle, peripheral vasculature, lungs, kidneys and brain. The diagnosis of HFpEF can bemade in individuals with signs and symptoms of heart failure with abnormality in natriuretic peptide levels or evidence of cardiopulmonary congestion, facilitated by the use of HFpEF risk scores and additional imaging and testing with the exclusion of HFpEF mimics. Management includes initiation of guideline-directed medical therapy and management of comorbidities. Given the significant impact of HFpEF on quality of life, future research efforts should include a particular focus on how patients can live better with this disease.

Bottom Crack Detection with Real-Time Signal Amplitude Correction Using EMAT-PEC Composite Sensor.

During electromagnetic ultrasonic testing, it is difficult to recognize small-size bottom cracks by time of flight (ToF), and the lift-off fluctuation of the probe affects the accuracy and consistency of the inspection results. In order to overcome the difficulty, a novel composite sensor of an electromagnetic acoustic transducer (EMAT) and pulse eddy current (PEC) is designed. We use the amplitude of a bottom echo recorded by EMAT to identify the tiny bottom crack as well as the amplitude of PEC signals picked up by the integrated symmetric coils to measure the average lift-off of the probe in real time. Firstly, the effects of lift-off and bottom cracks on the amplitude of bottom echo are distinguished by combining the theoretical analysis and finite element method (FEM). And then an amplitude correction method based on the fusion of EMAT and PEC signals is proposed to reduce the impact of lift-off on the defect signal. The experimental results demonstrate that the designed composite sensor can effectively detect a bottom crack as small as 0.1 mm × 0.3 mm. The signal fusion method can accurately correct the amplitude of defect signals and the relative error is less than ±8%.

DIAPH1-Deficiency is Associated with Major T, NK and ILC Defects in Humans

Loss of function mutations in Diaphanous related formin 1 (DIAPH1) are associated with seizures, cortical blindness, and microcephaly syndrome (SCBMS) and are recently linked to combined immunodeficiency. However, the extent of defects in T and innate lymphoid cells (ILCs) remain unexplored. Herein, we characterized the primary T, natural killer (NK) and helper ILCs of six patients carrying two novel loss of function mutation in DIAPH1 and Jurkat cells after DIAPH1 knockdown. Mutations were identified by whole exome sequencing. T-cell immunophenotyping, proliferation, migration, cytokine signaling, survival, and NK cell cytotoxicity were studied via flow cytometry-based assays, confocal microscopy, and real-time qPCR. CD4+ T cell proteome was analyzed by mass spectrometry. p.R351* and p.R322*variants led to a significant reduction in the DIAPH1 mRNA and protein levels. DIAPH1-deficient T cells showed proliferation, activation, as well as TCR-mediated signaling defects. DIAPH1-deficient PBMCs also displayed impaired transwell migration, defective STAT5 phosphorylation in response to IL-2, IL-7 and IL-15. In vitro generation/expansion of Treg cells from naïve T cells was significantly reduced. shRNA-mediated silencing of DIAPH1 in Jurkat cells reduced DIAPH1 protein level and inhibited T cell proliferation and IL-2/STAT5 axis. Additionally, NK cells from patients had diminished cytotoxic activity, function and IL-2/STAT5 axis. Lastly, DIAPH1-deficient patients’ peripheral blood contained dramatically reduced numbers of all helper ILC subsets. DIAPH1 deficiency results in major functional defects in T, NK cells and helper ILCs underlining the critical role of formin DIAPH1 in the biology of those cell subsets.Graphical The summary of findings are presented as a graphical abstract. DIAPH1 deficiency results in multiple defects in CD4+ T, Treg, NK cells and ILCs.

Integrase inhibitor drugs during pregnancy and congenital anomalies: A case/non-case study from the global pharmacovigilance database VigiBase®.

In 2018, a significant neural tube defects (NTD) signal was reported after pre-conceptional exposure to dolutegravir, but was not confirmed in further analysis. Since 2019, dolutegravir-based regimen, an integrase inhibitor (INI), is recommended by WHO as the most-effective first-line therapy in all patients living with HIV. To explore the potential INI-related teratogenic effect, we searched disproportionate signals between exposure to INI-class drugs and congenital anomalies, compared to non-INI drugs, using the international pharmacovigilance database, VigiBase®. We selected all the reports registered in VigiBase® between 01/01/2007 and 30/03/2021 on any antiretroviral drug-related fetal or neonatal adverse drug reactions, declared either in children (<2 years) exposed in utero or in pregnant women (12-50 years). A case/non-case study was conducted to detected signals between congenital anomalies and prenatal exposure to any INI-class drug, compared to non-INI drugs, by estimating adjusted reporting odds ratios (aROR) with 95% confidence intervals (95%CI). We identified 2521 unique reports, among which 664 (26.3%) were related to INI-class use. Overall, 520 congenital anomalies were cited from 327 unique reports, of whom 31.0% were INI-related. Compared to non-INI drugs, no significant disproportionate reporting signal between prenatal exposure to INI-class drugs and congenital anomalies was found (aROR 1.13; 95% CI:0.85-1.51). However, specific significant signals were reported for raltegravir/elvitegravir/dolutegravir drug exposure and urinary malformations (aROR 2.43; 95%CI:1.08-5.43), digestive malformations (aROR 3.09; 95%CI:1.22-7.84), and NTDs (aROR 3.02; 95%CI:1.09-8.37). Although specific congenital anomalies signals associated with raltegravir/elvitegravir/dolutegravir exposure were notified, causal relationship needs to be further investigated in prospective studies.

Design of subsurface defect detection system based on two channels.

With the continuous improvement of quality requirements for optical components, the detection of subsurface defects in optical components has become a key technology. However, there is a problem with existing detection techniques, which is that they cannot simultaneously and independently detect subsurface defects at the micrometer and nanometer levels. This article analyzes the scattering field model of subsurface scratches and conducts simulation experiments on the relationship between scattering light intensity and system aperture. Based on the simulation results, a dual channel experimental system with adjustable spot size was designed to achieve automated measurement of subsurface defects. The narrow channel was used to detect micrometer-level subsurface defects and the wide channel was used to detect nanometer-level subsurface defects. The experimental results verified the correctness of the simulation experiment. In order to improve the sensitivity of the system, we designed an aperture based on the scattering field distribution of surface and subsurface defects, which is used to block the interference signal on the sample surface and improve the signal-to-noise ratio of the subsurface defect signal. The experimental results show that this aperture plays an important role, and the detection sensitivity of the system reaches 100 nm. We used four algorithms for data processing and found that the IQR algorithm is most suitable for this system. Finally, the detection results were compared under different spot sizes, and it was found that small spot sizes have better detection effects on nanoscale subsurface defects. In practice, the spot size can be dynamically adjusted according to the detection needs to achieve the optimal configuration of detection speed and sensitivity.

Glucocorticoid receptor controls atopic dermatitis inflammation via functional interactions with P63 and autocrine signaling in epidermal keratinocytes

Atopic dermatitis (AD), a prevalent chronic inflammatory disease with multifactorial etiology, features epidermal barrier defects and immune overactivation. Synthetic glucocorticoids (GCs) are widely prescribed for treating AD due to their anti-inflammatory actions; however, mechanisms are incompletely understood. Defective local GC signaling due to decreased production of endogenous ligand and/or GC receptor (GR) levels was reported in prevalent inflammatory skin disorders; whether this is a consequence or contributing factor to AD pathology is unclear. To identify the chromatin-bound cell-type-specific GR protein interactome in keratinocytes, we used rapid immunoprecipitation of endogenous proteins and mass spectrometry identifying 145 interactors that increased upon dexamethasone treatment. GR-interacting proteins were enriched in p53/p63 signaling, including epidermal transcription factors with critical roles in AD pathology. Previous analyses indicating mirrored AD-like phenotypes between P63 overexpression and GR loss in epidermis, and our data show an intricate relationship between these transcription factors in human keratinocytes, identifying TP63 as a direct GR target. Dexamethasone treatment counteracted transcriptional up-regulation of inflammatory markers by IL4/IL13, known to mimic AD, causing opposite shifts in GR and P63 genomic binding. Indeed, IL4/IL13 decreased GR and increased P63 levels in cultured keratinocytes and human epidermal equivalents (HEE), consistent with GR down-regulation and increased P63 expression in AD lesions vs normal skin. Moreover, GR knockdown (GRKD) resulted in constitutive increases in P63, phospho-P38 and S100A9, IL6, and IL33. Also, GRKD culture supernatants showed increased autocrine production of TH2-/TH1-/TH17-TH22-associated factors including IL4, CXCL10, CXCL11, and CXCL8. GRKD HEEs showed AD-like features including hyperplasia and abnormal differentiation, resembling phenotypes observed with GR antagonist or IL4/IL13 treatment. The simultaneous GR/P63 knockdown partially reversed constitutive up-regulation of inflammatory genes in GRKD. In summary, our data support a causative role for GR loss in AD pathogenesis via functional interactions with P63 and autocrine signaling in epidermal keratinocytes.

Numerical simulation and experimental studies of rotational eddy current detection of cracks around rivet holes

Multi-layered aeronautical structures, such as fuselage panels and wings, are composed of several layers of materials such as metal and composites. These structures are prone to damage such as corrosion, cracks and delamination between layers, which can compromise their structural integrity. Eddy current sensors are an essential tool for the inspection and preventive maintenance of multi-layered aeronautical structures, contributing to the safety and reliability of these crucial components. Differential-mode eddy current sensors are particularly well-suited for the inspection of multi-layer aerospace structures around dished-head rivets. The differential measurement improves the detection and characterization of defects in these complex geometries, which are prone to fatigue, corrosion, and other types of damage. The advantages of differential mode are improved sensitivity to small defects, elimination of lift-off variations (distance between the sensor and the surface), reduced electromagnetic interference and detection of defects around rivets, which are critical and difficult to access areas. This work deals with a study of the rotational differential sensor signal according to geometrical parameters of fastener holes defect. It is carried out by an eddy current nondestructive testing system implemented under COMSOL Multiphysics. Indeed, despite its rapidity, the results have shown that the sensor is sensitive to the hole defects when the distances Sensor/Rivet and Lift-off are reduced. As predicted, the experimental results have shown the presence of unsuitable signals caused by the additional Lift-off and the distance Sensor/Rivet. As a solution, these tow parameters should be reduced and kept constant in order to get a better defect signal.

Theoretical infrared signature of OH defects in Fe3+, Cr3+ and Al3+-doped enstatite

Theoretical infrared signature of OH defects in Fe3+, Cr3+ and Al3+-doped enstatite