A comprehensive study on machine learning models combining with oversampling for bronchopulmonary dysplasia-associated pulmonary hypertension in very preterm infants.

BACKGROUND: Bronchopulmonary dysplasia-associated pulmonary hypertension (BPD-PH) remains a devastating clinical complication seriously affecting the therapeutic outcome of preterm infants. Hence, early prevention and timely diagnosis prior to pathological change is the key to reducing morbidity and improving prognosis. Our primary objective is to utilize machine learning techniques to build predictive models that could accurately identify BPD infants at risk of developing PH. METHODS: The data utilized in this study were collected from neonatology departments of four tertiary-level hospitals in China. To address the issue of imbalanced data, oversampling algorithms synthetic minority over-sampling technique (SMOTE) was applied to improve the model. RESULTS: Seven hundred sixty one clinical records were collected in our study. Following data pre-processing and feature selection, 5 of the 46 features were used to build models, including duration of invasive respiratory support (day), the severity of BPD, ventilator-associated pneumonia, pulmonary hemorrhage, and early-onset PH. Four machine learning models were applied to predictive learning, and after comprehensive selection a model was ultimately selected. The model achieved 93.8% sensitivity, 85.0% accuracy, and 0.933 AUC. A score of the logistic regression formula greater than 0 was identified as a warning sign of BPD-PH. CONCLUSIONS: We comprehensively compared different machine learning models and ultimately obtained a good prognosis model which was sufficient to support pediatric clinicians to make early diagnosis and formulate a better treatment plan for pediatric patients with BPD-PH.

Insight into the Mechanism Underlying the Reduction of Digestibility and IgG/IgE Binding Ability in Ovalbumin during Different High-Temperature Conduction Modes-Induced Glycation.

Effects of different high-temperature conduction modes [high-temperature air conduction (HAC), high-temperature contact conduction (HCC), high-temperature steam conduction (HSC)]-induced glycation on the digestibility and IgG/IgE-binding ability of ovalbumin (OVA) were studied and the mechanisms were investigated. The conformation in OVA-HSC showed minimal structural changes based on circular dichroism, fluorescence, and ultraviolet spectroscopy. The degree of hydrolysis analysis indicated that glycated OVA was more resistant to digestive enzymes. Liquid chromatography-Orbitrap mass spectrometry identified 11, 14, and 15 glycation sites in OVA-HAC, OVA-HCC, and OVA-HSC, respectively. The IgG/IgE-binding ability of OVA was reduced during glycation and digestion, and the interactions among glycation, allergenicity, and digestibility were further investigated. Glycation sites masked the IgG/IgE epitopes resulting in a reduction in allergenicity. Digestion enzymes destroyed the IgG/IgE epitopes thus reducing allergenicity. Meanwhile, the glycation site in proximity to the digestion site of pepsin was observed to cause a reduction in digestibility.

Comparison of ovalbumin glycation induced by high-temperature steaming and high-temperature baking: A study combining conventional spectroscopy with high-resolution mass spectrometry.

High-temperature steaming (HTS) and high-temperature baking (HTB)-induced ovalbumin (OVA)-glucose glycation (140 °C, 1-3 min) were compared, and the different mechanisms were evaluated by changes in protein conformation, glycation sites and average degree of substitution per peptide molecule (DSP) values as well as the antioxidant activity of glycated OVA. Conventional spectroscopic results suggested that in comparison with HTB, HTS promoted protein expansion, increased ß-sheet content and made OVA structure more orderly. Liquid chromatography-high resolution mass spectrometry (LC-HRMS) analysis showed that 10 glycation sites were found under HTB, while 4 new glycation sites R111, R200, R219 and K323 appeared under HTS, and 2 of them (R219 and K323) were located in internal ß-sheet chains. The antioxidant activities of glycated OVA increased with increasing treatment time, and HTS showed stronger enhancement effect than HTB. Furthermore, the DSP values were generally higher under HTS than HTB. Compared with HTB, HTS with high penetrability could enhance the change of OVA primary structure and spatial conformation, making the protein structure more unfolded and stable, leading to more protein-sugar collisions occurred in inner OVA molecular and significantly promoted glycation. In conclusion, HTS is a promising method for high-temperature short-time glycation reaction, with drastically increasing the protein antioxidant activities.

Effects of different high-temperature conduction modes on the ovalbumin-glucose model: AGEs production and regulation of glycated ovalbumin on gut microbiota.

Food high-temperature processing frequently induces the production of advanced glycation end products (AGEs) in the food industry. In this study, the effects of three high-temperature conduction modes on the AGEs production derived from ovalbumin (OVA)-glucose model and the regulation of glycated OVA on gut microbiota were investigated. The peak time of OVA shifted maximally from 13.72 to 13.57 due to the rise in molecular weight, confirming successful coupling between OVA and glucose. The inhibition of superheated steam (SS) on AGEs was observed, with the sample treated by SS showing the lowest content among glycated OVA groups. The analysis revealed an increase in AGEs during digestion and a decrease in fermentation, suggesting the release during digestion and the availability by intestinal flora. Furthermore, an expansion of Bifidobacterium and Lactobacillus, and the inhibition of Desulfovibrio and Escherichia-Shigella were observed, indicating the prebiotic activity of glycated OVA and its potential to improve intestinal health. These results provide valuable information for controlling high-temperature processing to inhibit AGEs formation and highlight the positive effects of glycated proteins on intestinal health.

[Clinical characteristics and pathogens of infancy lower respiratory tract infections in infants with bronchopulmonary dysplasia]. / æ”¯æ°”ç®¡è‚ºå‘è‚²ä¸è‰¯æ‚£å„¿å©´å„¿æœŸä¸‹å‘¼å¸é“æ„ŸæŸ“çš„ä¸´åºŠç‰¹å¾åŠç— åŽŸå­¦åˆ†æž.

OBJECTIVES: To study the clinical characteristics and pathogen features of infants with bronchopulmonary dysplasia (BPD) who were readmitted during infancy due to lower respiratory tract infections. METHODS: A retrospective analysis was conducted on 128 preterm infants with BPD who were admitted for lower respiratory tract infections in Qingdao Women and Children's Hospital from January 2020 to December 2022. An equal number of non-BPD preterm infants admitted during the same period were selected as controls. General information, clinical characteristics, lung function parameters, and respiratory pathogen results were compared between the two groups. RESULTS: Compared with the non-BPD group, the BPD group had a lower gestational age and birth weight, were more likely to experience shortness of breath, wheezing, and cyanosis, and had a longer duration of wheezing relief (P<0.05). Compared with the non-BPD group, the BPD group had lower lung function parameters, including tidal volume per kilogram of body weight, ratio of time to peak tidal expiratory flow to total expiratory time, ratio of volume at peak tidal expiratory flow to expiratory tidal volume, tidal expiratory flow at 25%, 50%, and 75% of tidal volume, and increased respiratory rate (P<0.05). The detection rates of gram-negative bacteria, such as Klebsiella pneumoniae and Acinetobacter baumannii, were higher in the BPD group than in the non-BPD group (P<0.05). CONCLUSIONS: Infants with BPD who develop infancy lower respiratory tract infections require closer attention to the clinical characteristics such as shortness of breath, wheezing, and cyanosis. Lung function is characterized by obstructive changes and small airway dysfunction. Gram-negative bacteria, including Klebsiella pneumoniae and Acinetobacter baumannii, are more likely to be detected as respiratory pathogens.

Microbial signatures of neonatal bacterial meningitis from multiple body sites.

As a common central nervous system infection in newborns, neonatal bacterial meningitis (NBM) can seriously affect their health and growth. However, although metagenomic approaches are being applied in clinical diagnostic practice, there are some limitations for whole metagenome sequencing and amplicon sequencing in handling low microbial biomass samples. Through a newly developed ultra-sensitive metagenomic sequencing method named 2bRAD-M, we investigated the microbial signatures of central nervous system infections in neonates admitted to the neonatal intensive care unit. Particularly, we recruited a total of 23 neonates suspected of having NBM and collected their blood, cerebrospinal fluid, and skin samples for 2bRAD-M sequencing. Then we developed a novel decontamination method (Reads Level Decontamination, RLD) for 2bRAD-M by which we efficiently denoised the sequencing data and found some potential biomarkers that have significantly different relative abundance between 12 patients that were diagnosed as NBM and 11 Non-NBM based on their cerebrospinal fluid (CSF) examination results. Specifically, we discovered 11 and 8 potential biomarkers for NBM in blood and CSF separately and further identified 16 and 35 microbial species that highly correlated with the physiological indicators in blood and CSF. Our study not only provide microbiological evidence to aid in the diagnosis of NBM but also demonstrated the application of an ultra-sensitive metagenomic sequencing method in pathogenesis study.

Insight into the effect of traditional frying techniques on glycosylated hazardous products, quality attributes and flavor characteristics of grass carp fillets.

This study aimed to evaluate the evolution of quality attributes, oxidation index, glycosylated hazardous products, aroma characteristics of grass carp fillets and their relationship under air-frying, roast-frying and pan-frying. With frying progressed, the level of carbonyl protein and lipid oxidation products increased significantly (following air-frying > pan-frying > roast-frying), and the latter decreased subsequently after 6 min. Fillets possessed by frying increased significantly Nε-carboxymethyl-lysines (CML) and 5-hydroxymethylfurfural (5-HMF) levels, whose increment was pan-frying > air-frying > roast-frying. Compared to raw, eighty-seven volatiles were identified and the total concentrations of those increased gradually in air-frying, but then decreased up to 6 min in roast-frying and pan-frying. Furthermore, significant correlations between CML, TBARS and 5-HMF, quality attributes, oxidation index; volatiles (VIP and/or OAV > 1) and lipid oxidation index were obtained. Conclusively, fillets possessed by air-/roast-frying showed more lipid oxidation and alcohols/aldehydes, while pan-fried enriched CML and pyrazines.

Intelligent monitoring method of tridimensional storage system based on deep learning.

Growing international trade requires more flexible warehouse management to match it. In order to achieve more effective warehouse management efficiency, a shelf status-detection method based on deep learning is proposed. Firstly, the image acquisition of a multi-level shelf containing multiple bays is performed under different time and lighting conditions. Due to the difference in image characteristics between the bottom shelf on the ground and the upper shelf on the non-ground level, the collected images were divided into two groups: floor images and shelf images; and the warehouse status recognition was performed on the two groups separately. The two sets of images are cropped and center projection transformed separately to obtain the region of interest. On this basis, the improved residual network model is used to construct different depot detection models for the two sets of images, respectively, and the above algorithm is verified by actual measurements. In this paper, 102,614 images of 3246 depots with different states of non-ground layer, and 27,903 images of ground layer are collected. They are divided into training set and test set according to the ratio of 4:1, and the accuracy of training set is 99.6%, and the accuracy of test set is 99.3%. The experimental outcomes provide a theoretical method and technical support for the intelligent warehouse system management.

Flufenamic acid alleviates sepsis-induced lung injury by up-regulating CBR1.

Investigate the effect of flufenamic acid (FFA) on lung injury of sepsis rats. Rat sepsis model was established using cecal ligation and puncture (CLP). The pathomorphology of lung tissue was detected by Hematoxylin-eosin (H&E) staining. The expression levels of tumor necrosis factor alpha (TNF-α), interleukin-6 (IL-6), and high mobility group box-1 (HMGB-1) in serum and TNF-α, IL-6, malondialdehyde (MDA), glutathione (GSH), and superoxide dismutase (SOD) in lung tissues. The viability of RLE-6TN cells was detected by CCK-8 assay. The expression of carbonyl reductase 1 (CBR1) in RLE-6TN cells was analyzed by Western blot analysis and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis. The inflammatory response was obviously enhanced in CLP-constructed sepsis rats and alleviated by FFA treatment. Sepsis induced the increase of W/D ratio, promoted the levels of TNF-α, IL-6, HMGBR1, and MDA and inhibited the levels of SOD and GSH. FFA could effectively alleviate the sepsis-induced lung injury. The viability of RLE-6TN cells induced by LPS was improved with the treatment of FFA. CBR1 expression in LPS-induced RLE-6TN cells was decreased and FFA could up-regulate the CBR1 expression. In addition, LPS-induced lung injury promoted the inflammatory response in lung tissues, increased the W/D ratio and levels of TNF-α, IL-6, HMGBR1, and MDA while inhibited the levels of SOD and GSH. FFA could effectively improve the LPS-induced lung injury while the effect of FFA on LPS-induced lung injury was alleviated by CBR1 interference. FFA may alleviate sepsis-induced lung injury by up-regulating CBR1.

Human motion segmentation and recognition using machine vision for mechanical assembly operation.

The observation, decomposition and record of motion are usually accomplished through artificial means during the process of motion analysis. This method not only has a heavy workload, its efficiency is also very low. To solve this problem, this paper proposes a novel method to segment and recognize continuous human motion automatically based on machine vision for mechanical assembly operation. First, the content-based dynamic key frame extraction technology was utilized to extract key frames from video stream, and then automatic segmentation of action was implemented. Further, the SIFT feature points of the region of interest (ROIs) were extracted, on the basis of which the characteristic vector of the key frame was derived. The feature vector can be used not only to represent the characteristic of motion, but also to describe the connection between motion and environment. Finally, the classifier is constructed based on support vector machine (SVM) to classify feature vectors, and the type of therblig is identified according to the classification results. Our approach enables robust therblig recognition in challenging situations (such as changing of light intensity, dynamic backgrounds) and allows automatic segmentation of motion sequences. Experimental results demonstrate that our approach achieves recognition rates of 96.00 % on sample video which captured on the assembly line.