The corrosion behavior of carbon steel under coexistence of carbon dioxide and SRB.

The corrosion behavior of carbon steel under the coexistence of carbon dioxide and SRB was studied by means of corrosion weight loss, SEM, EDS, in situ pH test, and other methods. The results showed that Chloride ions, temperature, pH, and oxygen coexist with iron bacteria will affect the corrosion under the coexistence of CO2 and SRB, and SRB tends to grow in a favorable environment for itself, and the corrosion rate of X52N at 42 days is slightly higher than that at 21 days. However, the pitting depth increased sharply from 21.20 µm in 21 days to 39.79 µm in 42 days. So that the corrosion can be divided into two stages. First, SRB catalyze the dissolution of FeCO3, leading to local uniform corrosion. Second, SRB directly obtain electrons from the metal surface, resulting in local pitting. In addition, the environment under the stable mineralized biofilm was found to be slightly alkaline.

Advancing presurgical non-invasive molecular subgroup prediction in medulloblastoma using artificial intelligence and MRI signatures.

Global investigation of medulloblastoma has been hindered by the widespread inaccessibility of molecular subgroup testing and paucity of data. To bridge this gap, we established an international molecularly characterized database encompassing 934 medulloblastoma patients from thirteen centers across China and the United States. We demonstrate how image-based machine learning strategies have the potential to create an alternative pathway for non-invasive, presurgical, and low-cost molecular subgroup prediction in the clinical management of medulloblastoma. Our robust validation strategies-including cross-validation, external validation, and consecutive validation-demonstrate the model's efficacy as a generalizable molecular diagnosis classifier. The detailed analysis of MRI characteristics replenishes the understanding of medulloblastoma through a nuanced radiographic lens. Additionally, comparisons between East Asia and North America subsets highlight critical management implications. We made this comprehensive dataset, which includes MRI signatures, clinicopathological features, treatment variables, and survival data, publicly available to advance global medulloblastoma research.

Screening and diagnosis of cardiovascular disease using artificial intelligence-enabled cardiac magnetic resonance imaging.

Cardiac magnetic resonance imaging (CMR) is the gold standard for cardiac function assessment and plays a crucial role in diagnosing cardiovascular disease (CVD). However, its widespread application has been limited by the heavy resource burden of CMR interpretation. Here, to address this challenge, we developed and validated computerized CMR interpretation for screening and diagnosis of 11 types of CVD in 9,719 patients. We propose a two-stage paradigm consisting of noninvasive cine-based CVD screening followed by cine and late gadolinium enhancement-based diagnosis. The screening and diagnostic models achieved high performance (area under the curve of 0.988 ± 0.3% and 0.991 ± 0.0%, respectively) in both internal and external datasets. Furthermore, the diagnostic model outperformed cardiologists in diagnosing pulmonary arterial hypertension, demonstrating the ability of artificial intelligence-enabled CMR to detect previously unidentified CMR features. This proof-of-concept study holds the potential to substantially advance the efficiency and scalability of CMR interpretation, thereby improving CVD screening and diagnosis.

A Novel Strategy for the Synthesis of High Stability of Luminescent Zero Dimensional-Two Dimensional CsPbBr3 Quantum Dot/1,4-bis(4-methylstyryl)benzene Nanoplate Heterostructures at an Atmospheric Condition.

Perovskite quantum dots (QDs), emerging with excellent bright-green photoluminescence (PL) and a large absorption coefficient, are of great potential for the fabrication of light sources in underwater optical wireless communication systems. However, the instability caused by low formation energy and abundant surface traps is still a major concern for perovskite-based light sources in underwater conditions. Herein, we propose ultra-stable zero dimensional-two dimensional (0D-2D) CsPbBr3 QD/1,4-bis(4-methylstyryl)benzene (p-MSB) nanoplate (NP) heterostructures synthesized via a facile approach at room temperature in air. CsPbBr3 QDs can naturally nucleate on the p-MSB NP toluene solution, and the radiative combination is drastically intensified owing to the electron transfer within the typical type-II heterostructures, leading to a sharply increased PLQY of the heterostructure thin films up to 200% compared with the pristine sample. The passivation of defects within CsPbBr3 QDs can be effectively realized with the existence of p-MSB NPs, and thus the obviously improved PL is steadily witnessed in an ambient atmosphere and thermal environment. Meanwhile, the enhanced humidity stability and a peak EQE of 9.67% suggests a synergetic strategy for concurrently addressing the knotty problems on unsatisfied luminous efficiency and stability of perovskites for high-performance green-emitting optoelectronic devices in underwater applications.

Deciphering the Functional Long Non-Coding RNAs Derived from MicroRNA Loci.

Albeit the majority of eukaryotic genomes can be pervasively transcribed to a diverse population of lncRNAs and various subtypes of lncRNA are discovered. However, the genome-wide study of miRNA-derived lncRNAs is still lacking. Here, it is reported that over 800 miRNA gene-originated lncRNAs (molncRNAs) are generated from miRNA loci. One of them, molnc-301b from miR-301b and miR-130b, functions as an "RNA decoy" to facilitate dissociation of the chromatin remodeling protein SMARCA5 from chromatin and thereby sequester transcription and mRNA translation. Specifically, molnc-301b attenuates erythropoiesis by mitigating the transcription of erythropoietic and translation-associated genes, such as GATA1 and FOS. In addition, a useful and powerful CRISPR screen platform to characterize the biological functions of molncRNAs at large-scale and single-cell levels is established and 29 functional molncRNAs in hematopoietic cells are identified. Collectively, the focus is on miRNA-derived lncRNAs, deciphering their landscape during normal hematopoiesis, and comprehensively evaluating their potential roles.

AI Transformers for Radiation Dose Reduction in Serial Whole-Body PET Scans.

Purpose: To develop a deep learning approach that enables ultra-low-dose, 1% of the standard clinical dosage (3 MBq/kg), ultrafast whole-body PET reconstruction in cancer imaging. Materials and Methods: In this Health Insurance Portability and Accountability Act-compliant study, serial fluorine 18-labeled fluorodeoxyglucose PET/MRI scans of pediatric patients with lymphoma were retrospectively collected from two cross-continental medical centers between July 2015 and March 2020. Global similarity between baseline and follow-up scans was used to develop Masked-LMCTrans, a longitudinal multimodality coattentional convolutional neural network (CNN) transformer that provides interaction and joint reasoning between serial PET/MRI scans from the same patient. Image quality of the reconstructed ultra-low-dose PET was evaluated in comparison with a simulated standard 1% PET image. The performance of Masked-LMCTrans was compared with that of CNNs with pure convolution operations (classic U-Net family), and the effect of different CNN encoders on feature representation was assessed. Statistical differences in the structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), and visual information fidelity (VIF) were assessed by two-sample testing with the Wilcoxon signed rank t test. Results: The study included 21 patients (mean age, 15 years ± 7 [SD]; 12 female) in the primary cohort and 10 patients (mean age, 13 years ± 4; six female) in the external test cohort. Masked-LMCTrans-reconstructed follow-up PET images demonstrated significantly less noise and more detailed structure compared with simulated 1% extremely ultra-low-dose PET images. SSIM, PSNR, and VIF were significantly higher for Masked-LMCTrans-reconstructed PET (P < .001), with improvements of 15.8%, 23.4%, and 186%, respectively. Conclusion: Masked-LMCTrans achieved high image quality reconstruction of 1% low-dose whole-body PET images.Keywords: Pediatrics, PET, Convolutional Neural Network (CNN), Dose Reduction Supplemental material is available for this article. © RSNA, 2023.

Moderate vs. mild cases of overseas-imported COVID-19 in Beijing: a retrospective cohort study.

This study compared the differences in the clinical manifestations, treatment courses and clinical turnover between mild and moderate coronavirus disease 2019 (COVID-19). Clinical data of the patients with imported COVID-19 admitted to Beijing Xiaotangshan Designated Hospital between March 15 and April 30, 2020, were retrospectively analysed. A total of 53 COVID-19 patients were included, with 21 mild and 32 moderate cases. Compared with the mild group, the moderate group showed significant differences in breathing frequency, lymphocyte count, neutrophil percentage, neutrophil/lymphocyte ratio, procalcitonin, C-reactive protein, and dynamic erythrocyte sedimentation rate. In the moderate group, 87.5% exhibited ground-glass opacities, 14% exhibited consolidative opacities, 53.1% exhibited local lesions and 68.8% exhibited unilateral lesions. The proportion of patients who received antiviral or antibiotic treatment in the moderate group was higher than that in the mild group, and the number of cases that progressed to severe disease in the moderate group was also significantly higher (18.7% vs. 0%, p = 0.035). Compared with patients with mild COVID-19, those with moderate COVID-19 exhibited more noticeable inflammatory reactions, more severe pulmonary imaging manifestations and earlier expression of protective antibodies. The overall turnover of the moderate cases was poorer than that of the mild cases.

Artificial intelligence enables whole-body positron emission tomography scans with minimal radiation exposure.

PURPOSE: To generate diagnostic 18F-FDG PET images of pediatric cancer patients from ultra-low-dose 18F-FDG PET input images, using a novel artificial intelligence (AI) algorithm. METHODS: We used whole-body 18F-FDG-PET/MRI scans of 33 children and young adults with lymphoma (3-30 years) to develop a convolutional neural network (CNN), which combines inputs from simulated 6.25% ultra-low-dose 18F-FDG PET scans and simultaneously acquired MRI scans to produce a standard-dose 18F-FDG PET scan. The image quality of ultra-low-dose PET scans, AI-augmented PET scans, and clinical standard PET scans was evaluated by traditional metrics in computer vision and by expert radiologists and nuclear medicine physicians, using Wilcoxon signed-rank tests and weighted kappa statistics. RESULTS: The peak signal-to-noise ratio and structural similarity index were significantly higher, and the normalized root-mean-square error was significantly lower on the AI-reconstructed PET images compared to simulated 6.25% dose images (p < 0.001). Compared to the ground-truth standard-dose PET, SUVmax values of tumors and reference tissues were significantly higher on the simulated 6.25% ultra-low-dose PET scans as a result of image noise. After the CNN augmentation, the SUVmax values were recovered to values similar to the standard-dose PET. Quantitative measures of the readers' diagnostic confidence demonstrated significantly higher agreement between standard clinical scans and AI-reconstructed PET scans (kappa = 0.942) than 6.25% dose scans (kappa = 0.650). CONCLUSIONS: Our CNN model could generate simulated clinical standard 18F-FDG PET images from ultra-low-dose inputs, while maintaining clinically relevant information in terms of diagnostic accuracy and quantitative SUV measurements.

Electrospun Polyurethane-Gelatin Composite: A New Tissue-Engineered Scaffold for Application in Skin Regeneration and Repair of Complex Wounds.

Wound healing is vital for patients with complex wounds including burns. While the gold standard of skin transplantation ensures a surgical treatment to heal wounds, it has its limitations, for example, insufficient donor sites for patients with large burn wounds and creation of wounds and pain when harvesting the donor skin. Therefore, tissue-engineered skin is of paramount importance. The aim of this study is to investigate and characterize an elastomeric acellular scaffold that would demonstrate the ability to promote skin regeneration. A hybrid gelatin-based electrospun scaffold is fabricated via the use of biodegradable polycarbonate polyurethane (PU). It is hypothesized that the addition of PU would enable a tailored degradation rate and an enhanced mechanical strength of electrospun gelatin. Introducing 20% PU to gelatin scaffolds (Gel80-PU20) results in a significant increase in the degradation resistance, yield strength, and elongation of these scaffolds without altering the cell viability. In vivo studies using a mouse excisional wound biopsy grafted with the scaffolds reveals that the Gel80-PU20 scaffold enables greater cell infiltration than clinically established matrices, for example, Integra (dermal regeneration matrix, DRM), a benchmark scaffold. Immunostaining shows fewer macrophages and myofibroblastic cells on the Gel80-PU20 scaffold when compared with the DRM. The findings show that electrospun Gel80-PU20 scaffolds hold potential for generating tissue substitutes and overcoming some limitations of conventional wound care matrices.

Identifying Crohn's disease signal from variome analysis.

BACKGROUND: After years of concentrated research efforts, the exact cause of Crohn's disease (CD) remains unknown. Its accurate diagnosis, however, helps in management and preventing the onset of disease. Genome-wide association studies have identified 241 CD loci, but these carry small log odds ratios and are thus diagnostically uninformative. METHODS: Here, we describe a machine learning method-AVA,Dx (Analysis of Variation for Association with Disease)-that uses exonic variants from whole exome or genome sequencing data to extract CD signal and predict CD status. Using the person-specific coding variation in genes from a panel of only 111 individuals, we built disease-prediction models informative of previously undiscovered disease genes. By additionally accounting for batch effects, we were able to accurately predict CD status for thousands of previously unseen individuals from other panels. RESULTS: AVA,Dx highlighted known CD genes including NOD2 and new potential CD genes. AVA,Dx identified 16% (at strict cutoff) of CD patients at 99% precision and 58% of the patients (at default cutoff) with 82% precision in over 3000 individuals from separately sequenced panels. CONCLUSIONS: Larger training panels and additional features, including other types of genetic variants and environmental factors, e.g., human-associated microbiota, may improve model performance. However, the results presented here already position AVA,Dx as both an effective method for revealing pathogenesis pathways and as a CD risk analysis tool, which can improve clinical diagnostic time and accuracy. Links to the AVA,Dx Docker image and the BitBucket source code are at https://bromberglab.org/project/avadx/ .

Assessing the performance of in silico methods for predicting the pathogenicity of variants in the gene CHEK2, among Hispanic females with breast cancer.

The availability of disease-specific genomic data is critical for developing new computational methods that predict the pathogenicity of human variants and advance the field of precision medicine. However, the lack of gold standards to properly train and benchmark such methods is one of the greatest challenges in the field. In response to this challenge, the scientific community is invited to participate in the Critical Assessment for Genome Interpretation (CAGI), where unpublished disease variants are available for classification by in silico methods. As part of the CAGI-5 challenge, we evaluated the performance of 18 submissions and three additional methods in predicting the pathogenicity of single nucleotide variants (SNVs) in checkpoint kinase 2 (CHEK2) for cases of breast cancer in Hispanic females. As part of the assessment, the efficacy of the analysis method and the setup of the challenge were also considered. The results indicated that though the challenge could benefit from additional participant data, the combined generalized linear model analysis and odds of pathogenicity analysis provided a framework to evaluate the methods submitted for SNV pathogenicity identification and for comparison to other available methods. The outcome of this challenge and the approaches used can help guide further advancements in identifying SNV-disease relationships.

The Coupling Effect of O2 and H2S on the Corrosion of G20 Steel in a Simulating Environment of Flue Gas Injection in the Xinjiang Oil Field.

Flue gas injection for heavy oil recovery has received a great deal of attention, because it is more cost effective than lots of other injection methods. However, the corrosion could occur easily, because the flue gas usually contains corrosive gases such as CO2, H2S, and O2. In this work, the corrosion behaviors of G20 steel in flue gas injection environment simulating Xinjiang oil field (China) were investigated using weight loss measurement and surface characterization techniques. The effect of environments including the O2-containing environment, the H2S-containing environment, and the O2-H2S-coexisting environment on the corrosion of G20 steel in gas phase and liquid phase was discussed. The results show that the corrosion rate of G20 steel in the O2-H2S-coexisting environment is much higher than the sum of corrosion rates of the O2-containing environment and the H2S-containing environment, regardless of the gas phase and the liquid phase. This indicates that there is a coupling effect between O2 and H2S, which can further accelerate the corrosion of steel in O2-H2S-coexisting environment. The results of surface characterization demonstrate that in a typical flue gas injection environment, the corrosion products are composed of FeCO3, FeS, FeO(OH), and elemental sulfur. Elemental sulfur could obviously accelerate the corrosion of steel. Therefore, it can be considered that the coupling effect of O2 and H2S on corrosion of G20 steel in flue gas injection environment is caused by the formation of elemental sulfur in corrosion products.

Smokeless tobacco extract inhibits proliferation and promotes apoptosis in oral mucous fibroblasts.

The consumption of smokeless tobacco extract (STE) is growing rapidly, and it has been implicated in several human diseases including diabetes, inflammation and a number of types of cancer. The toxicity of STE requires evaluation, as it is known to induce numerous public health issues. To investigate whether STE serves a role in cultured human oral mucosa fibroblasts (hOMFs), the present study examined HOMF morphology with inverted microscopy and immunofluorescence staining. The cell viability was measured with MTT assays, which detected the cell apoptosis rate via flow cytometry. The activities of reactive oxygen species (ROS), malondialdehyde (MDA), superoxide dismutase (SOD), and catalase (CAT) were measured via flow cytometry and commercial kits, subsequent to exposing the cells to various concentrations of STE. Reverse transcription quantitative polymerase chain reaction and western blot analyses were used to demonstrate that the mRNA and the protein expression levels of cell cycle-associated genes (cyclin-dependent kinase inhibitor 1 and cyclin D1), apoptosis-associated genes [B cell lymphoma 2 (Bcl-2) and Bcl-2-associatied X protein], tumor protein (p53), nuclear factor kappa light chain enhancer of activated B cells (NF-κB)-transcription factor (p65) signaling pathways, NF-E2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1) and NAD(P)H: quinoneoxidoreductase1 (NQO1). The results indicated that the hOMF cells were positive for cytokeratin staining. STE induced G1-S cell cycle progression and cell apoptosis by regulating the cell cycle or apoptosis-associated proteins. STE treatment increased the concentrations of ROS and MDA, and decreased the concentrations of SOD and CAT. STE unregulated phosphorylated-p53, NF-κB p65, Nrf2, HO-1, and NQO1 expression levels in the hOMF cells. The present study demonstrated that STE appears to promote oral disease.

Screening active components of modified Xiaoyao powder as NRF2 agonists.

Nuclear factor (erythroid-derived 2)-like 2 (NRF2) regulates antioxidant enzymes and phase II detoxifying enzymes, such as NAD(P)H: quinone oxidoreductase 1 (NQO1). Modified Xiaoyao powder (MXP) is most frequently used in the prevention and treatment of breast cancer in China. This study aimed to screen active components of MXP for antioxidant stress and chemoprevention, which depend on NRF2-NQO1 signalling pathway. A total of 25 monomeric compounds contained in MXP were screened using an antioxidant response element-luciferase reporter. The most potent antioxidant response element-luciferase inducers were chosen to further examine their effects on NRF2 and NQO1 in MCF-7 cells. These results were then confirmed by determining the oxidative stress levels and chemopreventive effect on inhibiting carcinogenesis transformation in NRF2 knockdown (NRF2KD ) and NRF2 wild-type MCF-10A cells. We found that quercetin, kaempferol, and atractylenolide II in MXP were potent NRF2 inducers, which could up-regulate the expression of NRF2 and its downstream enzymes NQO1. In addition, these components could decrease reduced oxidative stress and inhibit carcinogenesis transformation, which depended on NRF2-NQO1 pathway. In conclusion, NRF2-NQO1 pathway plays an essential role in mediating the activity of MXP and its active components, at least in part; some beneficial effects of MXP may be applicable to breast cancer chemoprevention. Our study firstly found MXP active components including quercetin, kaempferol, and atractylenolide II. Our results firstly demonstrate that NRF2-NQO1 pathway plays an essential role in mediating the activity of MXP and its active components in breast cancer chemoprevention. Our study firstly found that atractylenolide II is a novel NRF2 inducer.

Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges.

Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype-phenotype relationships.

Quantification of Paclitaxel and Polyaspartate Paclitaxel Conjugate in Beagle Plasma: Application to a Pharmacokinetic Study.

An LC-MS/MS method for the determination of polyaspartate paclitaxel conjugate (PASP-PTX) and paclitaxel (PTX) in dog plasma with cephalomannine (Internal Standard for PASP-PTX, IS-I) and clopidogrel bisulfate (Internal Standard for PTX, IS-II) as the internal standards was developed and validated. Plasma samples of PASP-PTX were extracted by ethyl acetate following the hydrolysis reaction, while protein precipitation was used for the extraction of PTX using acetonitrile. Analytes were separated by a CAPCELL PAK C18 MG II column using a gradient elution with the mobile phase (A) 5 mM ammonium containing 0.1% formic acid, and (B) acetonitrile. Quantification was performed by monitoring the m/z transitions of 286.2/105.0 for PASP-PTX, 264.2/83.0 for IS-I, 854.4/286.0 for PTX, and 322.1/184.1 for IS-II in the ESI positive mode. This method was validated in terms of specificity, linearity, precision, accuracy, and stability. The lower limit of quantification was 0.15 µg/mL for PASP-PTX and 0.01 µg/mL for PTX, and the calibration curves were linear over 0.15-300 µg/mL for PASP-PTX and over 0.01-10 µg/mL for PTX. The samples were stable under all the tested conditions. The method was successfully applied to study the pharmacokinetic profiles of PASP-PTX and PTX in beagles following intravenous administration of PASP-PTX.

A core-shell albumin copolymer nanotransporter for high capacity loading and two-step release of doxorubicin with enhanced anti-leukemia activity.

The native transportation protein serum albumin represents an attractive nano-sized transporter for drug delivery applications due to its beneficial safety profile. Existing albumin-based drug delivery systems are often limited by their low drug loading capacity as well as noticeable drug leakage into the blood circulation. Therefore, a unique albumin-derived core-shell doxorubicin (DOX) delivery system based on the protein denaturing-backfolding strategy was developed. 28 DOX molecules were covalently conjugated to the albumin polypeptide backbone via an acid sensitive hydrazone linker. Polycationic and pegylated human serum albumin formed two non-toxic and enzymatically degradable protection shells around the encapsulated DOX molecules. This core-shell delivery system possesses notable advantages, including a high drug loading capacity critical for low administration doses, a two-step drug release mechanism based on pH and the presence of proteases, an attractive biocompatibility and narrow size distribution inherited from the albumin backbone, as well as fast cellular uptake and masking of epitopes due to a high degree of pegylation. The IC50 of these nanoscopic onion-type micelles was found in the low nanomolar range for Hela cells as well as leukemia cell lines. In vivo data indicate its attractive potential as anti-leukemia treatment suggesting its promising profile as nanomedicine drug delivery system.