Screening asthmatics for atopic status using the ALergy EXplorer (ALEX2) macroarray.

BACKGROUND: Screening asthma patients for atopy facilitates management. Since 2010, the core biomarker for screening asthma subjects for atopic status has been the qualitative Phadiatop. multi-aeroallergen screen. A more quantitative macroarray, the Allergy Explorer (ALEX2), shows promise as an alternative. OBJECTIVE: The study's goal was to examine the pros and cons of the use of ALEX2 in the screening of asthma patients for atopic status. METHODS: We evaluated the atopic (IgE-sensitization) status in asthmatic Amish and Hutterite farm children using the ImmunoCAP and ALEX2 assays in Phadiatop equivocal and positive subjects. RESULTS: All 42 asthmatic children were analyzed by Phadiatop and total serum IgE. Of these, 22 had a negative Phadiatop (<0.1 kUa/L) and total IgE <100 kU/L which defined them as non-atopic and they were excluded from ALEX2 testing. Of six children with equivocal Phadiatops (0.1-0.2 kUa/L-Group 1) and three children with a negative Phadiatop but total IgE >100 kUa/L (group 3), 44% (n = 4) had detectable IgE antibody by ALEX2 to mite, tree pollen, and other allergens not detected by Phadiatop, but confirmed by allergen-specific ImmunoCAP testing. In 11 Phadiatop positive subjects (>0.2 kUa/L-group 2), all but one were positive by ALEX2. IgE antibody specific for mold and rabbit aeroallergens matched their agricultural and pet exposure history. Three children were positive for IgE antibody to allergens in the profilin, nsLTP, or PR-10 cross-reactive protein families. CONCLUSION: Judicious use of ALEX2's enhanced specificity data not provided by the Phadiatop can aid in the interpretation of sensitization patterns and planning management of atopic asthmatics, but sensitization relevance must be confirmed by the patient's clinical history.

Image Classifier for an Online Footwear Marketplace to Distinguish between Counterfeit and Real Sneakers for Resale.

The sneaker industry is continuing to expand at a fast rate and will be worth over USD 120 billion in the next few years. This is, in part due to social media and online retailers building hype around releases of limited-edition sneakers, which are usually collaborations between well-known global icons and footwear companies. These limited-edition sneakers are typically released in low quantities using an online raffle system, meaning only a few people can get their hands on them. As expected, this causes their value to skyrocket and has created an extremely lucrative resale market for sneakers. This has given rise to numerous counterfeit sneakers flooding the resale market, resulting in online platforms having to hand-verify a sneaker's authenticity, which is an important but time-consuming procedure that slows the selling and buying process. To speed up the authentication process, Support Vector Machines and a convolutional neural network were used to classify images of fake and real sneakers and then their accuracies were compared to see which performed better. The results showed that the CNNs performed much better at this task than the SVMs with some accuracies over 95%. Therefore, a CNN is well equipped to be a sneaker authenticator and will be of great benefit to the reselling industry.

Selected Technical Aspects of Molecular Allergy Diagnostics.

Diagnosis of allergic diseases is a complex, multi-stage process. It often requires the use of various diagnostic tools. The in vitro diagnostics (IVD), which includes various laboratory tests, is one of the stages of this process. Standard laboratory tests include the measurement of the serum concentration of specific immunoglobulin E (sIgE) for selected allergens, full allergen extracts and/or single allergen components (molecules). The measurement of IgE sIgE to the allergen components is called molecular allergy diagnosis. During the standard laboratory diagnostic process, various models of immunochemical tests are used, which enable the measurement of sIgE for single allergens (one-parameter tests, singleplex) or IgE specific for many different allergens (multi-parameter tests, multiplex) in one test. Currently, there are many different test kits available, validated for IVD, which differ in the method type and allergen profile. The aim of the manuscript is to present various technical aspects related to modern allergy diagnostics, especially in the area of molecular allergy diagnostics.

Would the choice of multiplex platform impact the management of the allergic patient? A first approach focusing on LTPs.

BACKGROUND: In the Mediterranean area, patients with LTP syndrome who are sensitized to multiple allergens are often tested for sIgE using multiplex platforms. The results obtained from different commercial platforms are not interchangeable, so it is important to compare and validate the platform selected for use. The objective of this study is to compare and validate the performance of the ImmunoCAP ISAC E112i and the macroarray ALEX2 in our daily practice. METHODS: From August 2021 to March 2022, we tested 20 random serum samples from polysensitized patients using the ALEX2 test (MADx) and ImmunoCAP tIgE and ISAC E112i (Thermo Fisher Scientific). We compared the total IgE (tIgE) and sIgE levels for shared allergens. RESULTS: The heatmap generally showed more intense results for ISAC. The overall correlation was good, but some exceptions were noted. The main discrepancies were found for Ole e 7, which was positive for 11 patients in ISAC but negative for all patients in ALEX2, and for nut LTPs, for which ISAC showed a threefold higher detection rate for Ara h 9 and a fivefold higher detection rate for Cor a 8 and Jug r 3 compared to ALEX2. The regression model showed no interchangeability of tIgE results. CONCLUSIONS: Despite our small sample size and the complexity of comparing a quantitative and a semi-quantitative platform, our results suggest that patient diagnosis and management can be influenced by the platform used. Therefore, our findings must be taken into consideration when choosing a platform to use for some profiles of LTP-polysensitized patients, even though more data is needed.

Automated Sleep Stages Classification Using Convolutional Neural Network From Raw and Time-Frequency Electroencephalogram Signals: Systematic Evaluation Study.

BACKGROUND: Most existing automated sleep staging methods rely on multimodal data, and scoring a specific epoch requires not only the current epoch but also a sequence of consecutive epochs that precede and follow the epoch. OBJECTIVE: We proposed and tested a convolutional neural network called SleepInceptionNet, which allows sleep classification of a single epoch using a single-channel electroencephalogram (EEG). METHODS: SleepInceptionNet is based on our systematic evaluation of the effects of different EEG preprocessing methods, EEG channels, and convolutional neural networks on automatic sleep staging performance. The evaluation was performed using polysomnography data of 883 participants (937,975 thirty-second epochs). Raw data of individual EEG channels (ie, frontal, central, and occipital) and 3 specific transformations of the data, including power spectral density, continuous wavelet transform, and short-time Fourier transform, were used separately as the inputs of the convolutional neural network models. To classify sleep stages, 7 sequential deep neural networks were tested for the 1D data (ie, raw EEG and power spectral density), and 16 image classifier convolutional neural networks were tested for the 2D data (ie, continuous wavelet transform and short-time Fourier transform time-frequency images). RESULTS: The best model, SleepInceptionNet, which uses time-frequency images developed by the continuous wavelet transform method from central single-channel EEG data as input to the InceptionV3 image classifier algorithm, achieved a Cohen κ agreement of 0.705 (SD 0.077) in reference to the gold standard polysomnography. CONCLUSIONS: SleepInceptionNet may allow real-time automated sleep staging in free-living conditions using a single-channel EEG, which may be useful for on-demand intervention or treatment during specific sleep stages.

Extended IgE profile of shrimp-sensitized patients based on Multiplex Examination ALEX2 - Allergy Explorer.

Introduction: The key to the correct diagnosis of shrimp allergy is a qualification to the most efficient diagnostic method and later interpretation of the result. To achieve this, it is necessary to apply a diagnostic strategy relevant to each patient's clinical situation and approach every case individually. Aim: In this study the allergen profile of shrimp-sensitized patients was analysed using ALEX2 Allergy Explorer. Material and methods: This study includes 50 adult patients with positive prick-by-prick tests with tiger shrimp bought from the local eco-market and an elevated concentration of IgE specific to the shrimp allergen extract (ImmunoCap). A total of 35 patients with negative skin prick tests with shrimp and not detectable sIgE shrimp in ImmunoCap were included in the control group. All patients had ALEX2 Allergy Explorer microarray test. Results: In the shrimp-sensitized group, 22 patients were sensitized to at least one allergen component of Penaeus monodon, 20 patients were sensitized to crab, and 20 were sensitized to lobster. Only 15 (30%) patients were sensitized to the Northern prawn (Pandalus borealis) allergen extract in ALEX2 and only 12 (24%) to Shrimp mix (Litopenaeus setiferus, Farfantepenaeus aztecus, Farfantepenaeus dourarum). Conclusions: Sensitization to shrimp tropomyosin in the research group was present only in 34% of cases. There may be other shrimp allergen components, not available in ALEX2, which are responsible for shrimp sensitization.

A comprehensive comparison between ISAC and ALEX2 multiplex test systems.

OBJECTIVES: Diagnosis of type I hypersensitivity is based on anamnesis, provocation as well as blood- and skin testing. Multiplex specific IgE (sIgE) testing enables determination of sIgE antibodies against multiple recombinant or purified natural allergen components. The aim of this study was to evaluate the performance of the novel ALEX2® (Allergy Explorer, ALEX2 test introduced on the market November 2019) multiplex platform and to compare it with the ImmunoCAP ISAC® test system. METHODS: Serum samples of 49 patients, routinely determined with ISAC, were selected based on positive results covering in total most of the 112 ISAC components. Cohen's kappa, negative percent agreement (NPA), and positive percent agreement (PPA) of ALEX2 data compared to ISAC data (as a non-reference standard) were computed for those allergen components present on both platforms (n=103). Furthermore, in some samples sIgE results against allergen extracts and/or -components tested with either ImmunoCAP® (ThermoFisher) or IMMULITE® (Siemens) were available and compared to ALEX2 results. RESULTS: The overall agreement between ISAC and ALEX2 common allergen components was 94%. NPA and PPA were respectively 95 and 90%. Kappa values differed for specific allergen groups and varied between 0.60 and 0.92 showing moderate to almost perfect agreement. Of the qualitative discrepancies between ALEX2 and ISAC, 59% were related to weak positive results i.e. results under 1 kUA/L or 1 ISU, respectively. CONCLUSIONS: The method comparison between ISAC and ALEX2 multiplex tests showed a high concordance for those allergen components present on both platforms.

ALEX versus ISAC multiplex array in analyzing food allergy in atopic children.

ALEX multiplex array is a relatively new multiplex allergy test which analyses more than 120 allergen extracts and 170 molecular components. ISAC is the most used and studied multiplex array to date, offering 112 molecular components. In ten atopic children with multiple food allergies good agreement was observed between ALEX and ISAC sIgE results for nearly all shared food components. Presence of larger number of allergens in ALEX could help clinicians to improve personalized dietary advice. However more positive sensitizations with unknown clinical relevance were found by ALEX, potentially increasing clinical complexity. Pediatric allergists should be aware of this, especially in young atopic children with (severe) eczema who have not introduced all sorts of food yet.

Face Spoofing, Age, Gender and Facial Expression Recognition Using Advance Neural Network Architecture-Based Biometric System.

Nowadays, the demand for soft-biometric-based devices is increasing rapidly because of the huge use of electronics items such as mobiles, laptops and electronic gadgets in daily life. Recently, the healthcare department also emerged with soft-biometric technology, i.e., face biometrics, because the entire data, i.e., (gender, age, face expression and spoofing) of patients, doctors and other staff in hospitals is managed and forwarded through digital systems to reduce paperwork. This concept makes the relation friendlier between the patient and doctors and makes access to medical reports and treatments easier, anywhere and at any moment of life. In this paper, we proposed a new soft-biometric-based methodology for a secure biometric system because medical information plays an essential role in our life. In the proposed model, 5-layer U-Net-based architecture is used for face detection and Alex-Net-based architecture is used for classification of facial information i.e., age, gender, facial expression and face spoofing, etc. The proposed model outperforms the other state of art methodologies. The proposed methodology is evaluated and verified on six benchmark datasets i.e., NUAA Photograph Imposter Database, CASIA, Adience, The Images of Groups Dataset (IOG), The Extended Cohn-Kanade Dataset CK+ and The Japanese Female Facial Expression (JAFFE) Dataset. The proposed model achieved an accuracy of 94.17% for spoofing, 83.26% for age, 95.31% for gender and 96.9% for facial expression. Overall, the modification made in the proposed model has given better results and it will go a long way in the future to support soft-biometric based applications.

Analysis of Results of Specific IgE in 100 Atopic Dermatitis Patients with the Use of Multiplex Examination ALEX2-Allergy Explorer.

BACKGROUND AND AIM: Progress in laboratory diagnostics of IgE-mediated allergy is the use of component-resolved diagnosis. Our study analyses the results of specific IgE to 295 allergen reagents (117 allergenic extracts and 178 molecular components) in patients suffering from atopic dermatitis (AD) with the use of ALEX2 Allergy Explorer. METHOD: The complete dermatological and allergological examination, including the examination of the sensitization to molecular components with ALEX2 Allergy Explorer testing, was performed. The statistical analysis of results was performed with these methods: TURF (total unduplicated reach and frequency), best reach and frequency by group size, two-sided tests, Fisher's exact test, and chi-square test (at an expected minimum frequency of at least 5). RESULTS: Altogether, 100 atopic dermatitis patients were examined: 48 men, 52 women, the average age 40.9 years, min. age 14 years, max. age 67 years. The high and very high level of specific IgE was reached in 75.0% of patients to 18 molecular components: from PR-10 proteins (Aln g 1, Bet v 1, Cor a1.0103, Cor a1.0401, Fag s 1), lipocalin (Can f 1), NPC2 family (Der f 2, Der p 2), uteroglobin (Fel d 1), from Alternaria alternata (Alt a 1), Beta expansin (Lol p 1, Phl p 1), molecular components from Timothy, cultivated rye (Secc pollen) and peritrophin-like protein domain Der p 23. The high and very high level of specific IgE to other lipocalins (Fel d 7, Can f 4), to arginine kinase (Bla g 9, German cockroach), and to allergen extracts Art v (mugwort), and Cyn d (Bermuda grass) reached 52.0% of patients. The severity of AD is in significant relation to the sensitization to molecular components of storage mites (Gly d 2, Lep d 2-NPC2 family), lipocalins (Can f 1, Can f 2, Can f 4, and Can f 6), arginine kinase (Asp f 6, Bla g 9, Der p 20, Pen m 2), uteroglobin (Fel d 1, Ory c 3), Mn superoxide dismutase (Mala s 11), PR-10 proteins (Fag s 1, Mal d 1, Cor a 1.0401, Cor a 1.0103), molecular components of the peritrophin-like domain (Der p 21, Der p 23), and to Secc pollen. In the subgroup of patients suffering from bronchial asthma, the significant role play molecular components from house dust mites and storage mites (Lep d 2, Der p 2, Der f 2-NPC2 family), cysteine protease (Der p 1), peritrophin-like protein domain (Der p 21, Der p 23), enolase from Alternaria alternata (Alt a 6), and Beta expansin Phl p 1. CONCLUSION: The results of our study demonstrate the detailed profile of sensitization to allergens reagents (allergen extract and molecular components) in patients with atopic dermatitis. We show the significance of disturbed epidermal barrier, resulting in increased penetration of allergens. We confirmed the significant relationship between the severity of AD, the occurrence of bronchial asthma and allergic rhinitis, and high levels of specific IgE to allergen reagents. Our results may be important for regime measures and immunotherapy; Der p 23 shall be considered as an essential component for the diagnosis and specific immunotherapy of house dust mite allergy.

Transcriptional landscape of pathogen-responsive lncRNAs in rice unveils the role of ALEX1 in jasmonate pathway and disease resistance.

Plant defence is multilayered and is essential for surviving in a changing environment. The discovery of long noncoding RNAs (lncRNAs) has dramatically extended our understanding of post-transcriptional gene regulation in diverse biological processes. However, the expression profile and function of lncRNAs in disease resistance are still largely unknown, especially in monocots. Here, we performed strand-specific RNA sequencing of rice leaves infected by Xanthomonas oryzae pv. Oryzae (Xoo) in different time courses and systematically identified 567 disease-responsive rice lncRNAs. Target analyses of these lncRNAs showed that jasmonate (JA) pathway was significantly enriched. To reveal the interaction between lncRNAs and JA-related genes, we studied the coexpression of them and found 39 JA-related protein-coding genes to be interplayed with 73 lncRNAs, highlighting the potential modulation of lncRNAs in JA pathway. We subsequently identified an lncRNA, ALEX1, whose expression is highly induced by Xoo infection. A T-DNA insertion line constructed using enhancer trap system showed a higher expression of ALEX1 and exerted a significant resistance to rice bacterial blight. Functional study revealed that JA signalling is activated and the endogenous content of JA and JA-Ile is increased. Overexpressing ALEX1 in rice further confirmed the activation of JA pathway and resistance to bacterial blight. Our findings reveal the expression of pathogen-responsive lncRNAs in rice and provide novel insights into the connection between lncRNAs and JA pathway in the regulation of plant disease resistance.

miR-106b Promotes Metastasis of Early Gastric Cancer by Targeting ALEX1 in Vitro and in Vivo.

BACKGROUND/AIMS: Aberrant expression of miR-106b is a specific symptom of many solid carcinomas. Overexpression of miR-106b has been observed in gastric cancer. The effect of miR-106b on gastric cancer has been investigated in different cell culture models. However, the effect of miR-106b on metastasis of early gastric cancer (EGC) remains unknown. METHODS: In the study, qRT-PCR, FISH, western blot, luciferase reporter assay, migration and invasion assays, flow cytometry and TUNEL staining were used to investigate the effect of miR-106b on metastasis of EGC. RESULTS: To explore the function of miR-106b in EGC, we investigated the downstream signaling of miR-106b and found that ALEX1 was a direct target of miR-106 in gastric cancer cells. Up-regulation of ALEX1 effectively rescued the cell apoptosis induced by miR-106b inhibitor and promoted the expression levels of phosphorylation of JAK1 and STAT3. Moreover, overexpression of JAK1 reduced the cell apoptosis induced by miR-106b inhibitor and decreased the expression levels of the apoptotic proteins in gastric cancer cells. Furthermore, down-regulation of miR-106b promoted apoptosis of gastric cancer cells via inhibiting JAK1/STAT3 signaling pathway in vitro and in vivo. In addition, GLPG0643, a JAK1 inhibitor, enhanced the inhibitory effect of miR-106b inhibitor on gastric cancer growth in vivo. CONCLUSION: These findings provided a potential therapeutic manner for the treatment of metastasis of EGC in clinic.

Atrial fibrillation classification based on convolutional neural networks.

BACKGROUND: The global age-adjusted mortality rate related to atrial fibrillation (AF) registered a rapid growth in the last four decades, i.e., from 0.8 to 1.6 and 0.9 to 1.7 per 100,000 for men and women during 1990-2010, respectively. In this context, this study uses convolutional neural networks for classifying (diagnosing) AF, employing electrocardiogram data in a general hospital. METHODS: Data came from Anam Hospital in Seoul, Korea, with 20,000 unique patients (10,000 normal sinus rhythm and 10,000 AF). 30 convolutional neural networks were applied and compared for the diagnosis of the normal sinus rhythm vs. AF condition: 6 Alex networks with 5 convolutional layers, 3 fully connected layers and the number of kernels changing from 3 to 256; and 24 residual networks with the number of residuals blocks (or kernels) varying from 8 to 2 (or 64 to 2). RESULTS: In terms of the accuracy, the best Alex network was one with 24 initial kernels (i.e., kernels in the first layer), 5,268,818 parameters and the training time of 89 s (0.997), while the best residual network was one with 6 residual blocks, 32 initial kernels, 248,418 parameters and the training time of 253 s (0.999). In general, the performance of the residual network improved as the number of its residual blocks (its depth) increased. CONCLUSION: For AF diagnosis, the residual network might be a good model with higher accuracy and fewer parameters than its Alex-network counterparts.

A New Approach for Brain Tumor Segmentation and Classification Based on Score Level Fusion Using Transfer Learning.

Brain tumor is one of the most death defying diseases nowadays. The tumor contains a cluster of abnormal cells grouped around the inner portion of human brain. It affects the brain by squeezing/ damaging healthy tissues. It also amplifies intra cranial pressure and as a result tumor cells growth increases rapidly which may lead to death. It is, therefore desirable to diagnose/ detect brain tumor at an early stage that may increase the patient survival rate. The major objective of this research work is to present a new technique for the detection of tumor. The proposed architecture accurately segments and classifies the benign and malignant tumor cases. Different spatial domain methods are applied to enhance and accurately segment the input images. Moreover Alex and Google networks are utilized for classification in which two score vectors are obtained after the softmax layer. Further, both score vectors are fused and supplied to multiple classifiers along with softmax layer. Evaluation of proposed model is done on top medical image computing and computer-assisted intervention (MICCAI) challenge datasets i.e., multimodal brain tumor segmentation (BRATS) 2013, 2014, 2015, 2016 and ischemic stroke lesion segmentation (ISLES) 2018 respectively.

Alex3 suppresses non-small cell lung cancer invasion via AKT/Slug/E-cadherin pathway.

Alex3, is a newly identified mitochondrial protein, regulates mitochondrial dynamics and is involved in neural development. However, its expression pattern and clinicopathological relevance in human tumors are still unclear. In this study, Immunohistochemistry assay was performed in 109 cases of lung cancer samples and found that Alex 3 expression in lung cancer tissues was significantly lower than adjacent normal lung tissues (28.4% vs 52.6%, p < 0.001). Sequent statistical analysis indicated that negative Alex3 expression was significantly associated with advanced tumor-node-metastasis stages (p = 0.001), positive lymph node metastasis (p = 0.005), and poor prognosis (p = 0.008). After overexpression of Alex3, levels of p-AKT and Slug were downregulated, while level of E-cadherin was upregulated, which results in the inhibition of invasion and migration ability of lung cancer cells. In conclusion, reduction of Alex3 correlates with the development of non-small cell lung cancer and predicts adverse clinical outcome of non-small cell lung cancer patients. The effect of Alex3 on inhibiting invasion and migration may attribute to upregulation of E-cadherin expression through AKT-Slug pathway inactivation.

Increased regulatory T-cell numbers are associated with farm milk exposure and lower atopic sensitization and asthma in childhood.

BACKGROUND: European cross-sectional studies have suggested that prenatal and postnatal farm exposure decreases the risk of allergic diseases in childhood. Underlying immunologic mechanisms are still not understood but might be modulated by immune-regulatory cells early in life, such as regulatory T (Treg) cells. OBJECTIVE: We sought to assess whether Treg cells from 4.5-year-old children from the Protection against Allergy: Study in Rural Environments birth cohort study are critical in the atopy and asthma-protective effect of farm exposure and which specific exposures might be relevant. METHODS: From 1133 children, 298 children were included in this study (149 farm and 149 reference children). Detailed questionnaires until 4 years of age assessed farming exposures over time. Treg cells were characterized as upper 20% CD4(+)CD25(+) forkhead box protein 3 (FOXP3)(+) (intracellular) in PBMCs before and after stimulation (with phorbol 12-myristate 13-acetate/ionomycin or LPS), and FOXP3 demethylation was assessed. Atopic sensitization was defined by specific IgE measurements; asthma was defined by a doctor's diagnosis. RESULTS: Treg cells were significantly increased in farm-exposed children after phorbol 12-myristate 13-acetate/ionomycin and LPS stimulation. Exposure to farm milk was defined as a relevant independent farm-related exposure supported by higher FOXP3 demethylation. Treg cell (upper 20% CD4(+)CD25(+), FOXP3(+) T cells) numbers were significantly negatively associated with doctor-diagnosed asthma (LPS stimulated: adjusted odds ratio, 0.26; 95% CI, 0.08-0.88) and perennial IgE (unstimulated: adjusted odds ratio, 0.21; 95% CI, 0.08-0.59). Protection against asthma by farm milk exposure was partially mediated by Treg cells. CONCLUSIONS: Farm milk exposure was associated with increased Treg cell numbers on stimulation in 4.5-year-old children and might induce a regulatory phenotype early in life, potentially contributing to a protective effect for the development of childhood allergic diseases.

Multiplex Assays in Allergy Diagnosis: Allergy Explorer 2 versus ImmunoCAP ISAC E112i.

ImmunoCAP ISAC E112i (ISAC) and Allergy Explorer 2 (ALEX2) detect specific immunoglobulin E (IgE) reactivity. Both multiplex assays contain molecular allergens and ALEX2 additionally includes allergen extracts and inhibitors that block the binding of IgE to cross-reacting carbohydrate determinants (CCDs). This study aimed to compare the performance of ISAC and ALEX2 by determining the IgE reactivity against allergen extracts and/or allergen components and by using qualitative, semiquantitative, and quantitative analyses of all comparable allergen components in sera from 216 participants recruited in South Tyrol/Italy. For extract sensitization in ALEX2, the analysis revealed negative corresponding allergen components in 18.4% and at least one positive corresponding allergen component in 81.6% of all cases. For ISAC, the corresponding results were 23.5% and 76.5% of cases, respectively. The ALEX2 CCD inhibitor eliminated CCD-positive signals detected by ISAC in 88.5% of cases. Based on sensitization values of 0.3-14.9 ISU or kUA/L, there was good agreement between ALEX2 and ISAC, although ALEX2 showed higher values than ISAC. The addition of allergen-extract tests in ALEX2 resulted in the detection of more sensitizations than with corresponding allergen components alone. In the range of <15 ISU or kUA/L, ALEX2 may be more effective in detecting sensitizations.

Fractional whale driving training-based optimization enabled transfer learning for detecting autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a neurological illness that degrades communication and interaction among others. Autism can be detected at any stage. Early detection of ASD is important in preventing the communication, interaction and behavioral outcomes of individuals. Hence, this research introduced the Fractional Whale-driving Driving Training-based Based Optimization with Convolutional Neural Network-based Transfer learning (FWDTBO-CNN_TL) for identifying ASD. Here, the FWDTBO is modelled by the incorporation of Fractional calculus (FC), Whale optimization algorithm (WOA) and Driving Training-based Optimization (DTBO) that trains the hyperparameters of CNN-TL. Moreover, the Convolutional Neural Networks (CNN) utilize the hyperparameters from trained models, like Alex Net and Shuffle Net in such a way that the CNN-TL is designed. To improve the detection efficiency, the nub region was extracted and carried out with the functional connectivity-based Whale Driving Training Optimization (WDTBO) algorithm. Moreover, the TL is tuned by the FWDTBO algorithm. The result reveals that the ASD detection technique, FWDTBO-CNN-TL acquired 90.7 % accuracy, 95.4 % sensitivity, 93.7 % specificity and 93 % f-measure with the ABIDE-II dataset.

Percutaneous Coronary Interventions with Sirolimus-Eluting Alex Plus Stents in Patients with or without Diabetes: 4-Year Results.

We characterized the performance, as well as the safety, of a second-generation thin-strut sirolimus-eluting stent with a biodegradable polymer, Alex Plus (Balton, Poland), implanted in patients with type 2 diabetes (DM) with a 4-year follow-up. We defined the primary endpoint as the 48-month rate of major cardiovascular adverse events (MACE), including cardiac death, myocardial infarction (MI), or target lesion revascularization (TLR). The secondary endpoints were all-cause death, cardiac death, MI, and TLR rates at 12, 24, 36, and 48 months. We enrolled 232 patients in whom 282 stents were implanted, including 97 DM and 135 non-DM patients. The mean age of the DM patients was 69.5 ± 10.1 years and females accounted for 30% of the patients. DM patients had higher rates of arterial hypertension (97% vs. 88%, p = 0.016), dyslipidemia (86% vs. 70%, p = 0.005), prior MI (61% vs. 40%, p = 0.002), prior PCI (65% vs. 50%, p = 0.020), and prior CABG (14% vs. 5.9%, p = 0.029). We recorded statistically significant differences for MACE (HR 1.85, 95% CI 1.01-3.41, p = 0.046), cardiac death (HR 4.46, 95% CI 1.44-13.8, p = 0.010), and MI (HR 3.17, 95% CI 1.10-9.12, p = 0.033), but not for TLR, between DM and non-DM patients in terms of the analyzed endpoints at 4 years. Our study showed that Alex Plus was efficient and safe in a contemporary cohort of real-world DM patients undergoing percutaneous revascularization.

Two Closed Conformations of CRAF Require the 14-3-3 Binding Motifs and Cysteine-Rich Domain to be Intact in Live Cells.

The protein rapidly accelerated fibrosarcoma (RAF) is a kinase downstream of the membrane protein RAS in the cellular signal transduction system. In the structure of RAF, the N- and C-terminus domains are connected with a flexible linker. The open/close dynamics and dimerization of RAF are thought to regulate its activity, although the details of these conformations are unknown, especially in live cells. In this work, we used alternating laser excitation to measure cytosolic CRAF in live HeLa cells and obtained single-molecule Förster resonance energy transfer (smFRET) distributions of the structural states. We compared the results for wild-type (WT)-CRAF before and after epidermal growth factor (EGF) stimulation, with mutations of the 14-3-3 binding sites and cysteine-rich domain, and an N-terminus truncation. The smFRET distributions of full-length CRAFs were analyzed by global fitting with three beta distributions. Our results suggested that a 14-3-3 dimer bound to two sites on a single CRAF molecule and induced the formation of the autoinhibitory closed conformation. There were two closed conformations, which the majority of WT-CRAF adopted. These two conformations showed different responsiveness to EGF stimulation.