Spreading and Capillary Imbibition of Viscous Oil Lens into an Open-Cell Porous Structure.

Oil pollution in the ocean is becoming more and more of a serious issue, which increases interest in both ways for combating its cause and methods for observing and monitoring how oil spreads. A promising approach based on an optical method with empirical relations for selected viscous oil-water systems is presented. Based on a modified melamine sponge (MMS), the microscopic spreading and oil capillary penetration phenomenon of the porous structure were investigated. The objective of this study is 2-fold: (i) to present a more thorough experimental description of the spreading of viscous oil lens on the water surface and capillary action of oil lens into MMS porous structure; and (ii) to provide a theoretical description that helps to explain some of the observed behavior. With knowledge of δ∞2=-2SρW/gρO(ρW-ρO), we can determine the spreading coefficient S. It needs to be pointed out that the oil lens floating on the water surface does satisfy Neumann's rule as the spreading coefficient of the air-oil-water system is negative (- 9.8 mN/m), indicating the ability to form a stable oil lens with thickness δO = 3.04 mm and radius RL = 38.64 mm after 60 min of spreading test. Furthermore, to better understand the capillary phenomena from a mechanical approach, an oil lens in contact with the surface of the MMS porous structure, by in-depth visualization, is properly defined as the balance of forces acting. Finally, as an illustration of this method, we utilized this approach to obtain the equilibrium height of the capillary rise and take it into account in terms of effective material thickness.

Standard-definition White-light, High-definition White-light versus Narrow-band Imaging Endoscopy for Detecting Colorectal Adenomas: A Multicenter Randomized Controlled Trial.

OBJECTIVE: This study aimed to compare the performance of standard-definition white-light endoscopy (SD-WL), high-definition white-light endoscopy (HD-WL), and high-definition narrow-band imaging (HD-NBI) in detecting colorectal lesions in the Chinese population. METHODS: This was a multicenter, single-blind, randomized, controlled trial with a non-inferiority design. Patients undergoing endoscopy for physical examination, screening, and surveillance were enrolled from July 2017 to December 2020. The primary outcome measure was the adenoma detection rate (ADR), defined as the proportion of patients with at least one adenoma detected. The associated factors for detecting adenomas were assessed using univariate and multivariate logistic regression. RESULTS: Out of 653 eligible patients enrolled, data from 596 patients were analyzed. The ADRs were 34.5% in the SD-WL group, 33.5% in the HD-WL group, and 37.5% in the HD-NBI group (P=0.72). The advanced neoplasm detection rates (ANDRs) in the three arms were 17.1%, 15.5%, and 10.4% (P=0.17). No significant differences were found between the SD group and HD group regarding ADR or ANDR (ADR: 34.5% vs. 35.6%, P=0.79; ANDR: 17.1% vs. 13.0%, P=0.16, respectively). Similar results were observed between the HD-WL group and HD-NBI group (ADR: 33.5% vs. 37.7%, P=0.45; ANDR: 15.5% vs. 10.4%, P=0.18, respectively). In the univariate and multivariate logistic regression analyses, neither HD-WL nor HD-NBI led to a significant difference in overall adenoma detection compared to SD-WL (HD-WL: OR 0.91, P=0.69; HD-NBI: OR 1.15, P=0.80). CONCLUSION: HD-NBI and HD-WL are comparable to SD-WL for overall adenoma detection among Chinese outpatients. It can be concluded that HD-NBI or HD-WL is not superior to SD-WL, but more effective instruction may be needed to guide the selection of different endoscopic methods in the future. Our study's conclusions may aid in the efficient allocation and utilization of limited colonoscopy resources, especially advanced imaging technologies.

Progress in enhancing the remediation performance of microbial fuel cells for contaminated groundwater.

Microbial fuel cells (MFCs) have become more prevalent in groundwater remediation due to their capacity for power generation, removal of pollution, ease of assembly, and low secondary contamination. It is currently being evaluated for practical application in an effort to eliminate groundwater pollution. However, a considerable majority of research was conducted in laboratories. But the operational circumstances including anaerobic characteristics, pH, and temperature vary at different sites. In addition, the complexity of contaminants and the positioning of MFCs significantly affect remediation performance. Taking the aforementioned factors into consideration, this review summarizes a bibliography on the application of MFCs for the remediation of groundwater contamination during the last ten decades and assesses the impact of environmental conditions on the treatment performance. The design of the reactor, including configuration, dimensions, electrodes, membranes, separators, and target contaminants are discussed. This review aims to provide practical guidance for the future application of MFCs in groundwater remediation.

Combined impact of sleep and obesity on female infertility in the NHANES 2017-2020.

BACKGROUND: Sleep health and obesity may affect the risk of female infertility. However, few studies focused on the interaction of obesity and sleep health on the female infertility risk. This study aimed to evaluate the combined impact of trouble sleeping / sleep duration and overweight/obesity/ abdominal obesity on the risk of female infertility. METHODS: The data for this cross-sectional study was obtained from National Health and Nutritional Examination Survey, which provided information on trouble sleeping, sleep duration, overweight/obesity, abdominal obesity, and confounding factors. Adopted weighted univariate and multivariate logistic regression models to explore the relationship between trouble sleeping, sleep duration, overweight/obesity, abdominal obesity, and the risk of infertility, respectively, and the combined effect of trouble sleeping and overweight/obesity, trouble sleeping and abdominal obesity, sleep duration and overweight/obesity, sleep duration and abdominal obesity, on the female infertility risk. RESULTS: This study included a total of 1,577 women, and 191 were diagnosed with infertility. Women with infertility had a higher proportion of people with overweight/obesity, abdominal obesity, sleep duration ≤ 7 h and trouble sleeping than those with non-infertility. The result indicated that trouble sleeping [odds ratio (OR) = 2.25, 95% confidence intervals (CI): 1.49-3.39], sleep duration ≤ 7 h (OR = 1.59, 95% CI: 1.03-2.48), and the combined impact of abdominal obesity and trouble sleeping (OR = 2.18, 95% CI: 1.28-3.72), abdominal obesity and sleep duration ≤ 7 h (OR = 2.00, 95% CI: 1.17-3.40), overweight/obesity and trouble sleeping (OR = 2.29, 95% CI: 1.24-4.26), and overweight/obesity and sleep duration ≤ 7 h (OR = 1.88, 95% CI: 1.01-3.49) were associated with increased odds of infertility, respectively. CONCLUSION: There was combined effects of trouble sleeping/sleep duration ≤ 7 h and overweight/obesity/ abdominal obesity on increased odds of female infertility.

Association of preoperative neutrophil-to-lymphocyte ratio with the risk of postoperative delirium in elderly patients undergoing noncardiac surgery: a systematic review and meta-analysis.

To assess the correlation between preoperative neutrophil-to-lymphocyte ratio (NLR) and risk of postoperative delirium (POD) in older patients undergoing noncardiac surgery. PubMed, Web of Science, Embase, and Scopus were systematically retrieved from inception until February 2023. Two authors independently conducted the selection of literature, data extraction and statistical analysis. In this meta-analysis, Review Manager 5.4 was used for statistical analysis, and the mean difference (MD) and 95% confidence intervals (CIs) of preoperative NLR between the POD group and non-POD group were calculated. We utilised the Newcastle-Ottawa Scale (NOS) to evaluate the quality of literature. Further, our meta-analysis used a random-effects model, and publication bias was evaluated by conducting a funnel plot. The correlation between preoperative NLR and POD was the primary outcome, and the secondary outcome was the association of other prognostic factors with the risk of POD. This meta-analysis included seven studies with 2424 patients, of whom 403 were diagnosed with POD with an incidence of 16.63%. Results indicated a positive correlation between preoperative NLR and the risk of POD (MD = 1.06, 95% CI: 0.64-1.49; P < 0.001). Further, our results found that neutrophil counts, advanced age, longer surgery time, diabetes, and elevated C-reactive protein were significantly associated with POD (MD = 0.98, 95% CI: 0.40-1.56; P = 0.001; MD = 4.20, 95% CI: 2.90-5.51; P < 0.001; MD = 0.15, 95% CI: 0.05-0.25; P < 0.01; OR = 1.42, 95% CI: 1.08-1.86; P = 0.01; MD = 1.26, 95% CI: 0.36-2.16; P < 0.01). Other factors including lymphocyte counts, hypertension and male gender were not significantly associated with POD (MD = -0.11, 95% CI: -0.27 to 0.05; P > 0.05; OR = 1.20, 95% CI: 0.91-1.58, P > 0.05; OR = 1.28, 95% CI: 1.00-1.63; P = 0.05). Our meta-analysis indicated a positive correlation between preoperative NLR and the risk of POD in older noncardiac surgery patients.

[Research progress on curcumin improving chronic low-grade inflammation and related diseases].

Chronic low-grade inflammation(CLGI), a relatively new concept without a clear definition, refers to a nonspecific, chronic, continuous, and low-grade inflammation state, and it is closely associated with various chronic diseases, including obesity, inflammatory bowel disease, neurodegenerative diseases, and tumors. Improvement of CLGI can slow down disease progression. Anti-inflammatory treatment is an important strategy for prevention and treatment of CLGI. However, there is currently no definitive drug treatment method. Curcumin is a polyphenolic compound extracted from the rhizome of zingiberaceae, with significant anti-inflammatory activity. Research has shown that curcumin can play an anti-inflammatory role by regulating NF-κB, JAK/STAT, PI3K/Akt, MAPK, NLRP3 inflammasome, Nrf2/ARE, and other inflammation-related pathways. This paper summarized the anti-inflammatory mechanisms, pharmacological effect, and clinical application of curcumin in improving CLGI and other diseases, so as to provide a reference for in-depth research and clinical application of curcumin in improving CLGI.

Identifying allergic-rhinitis-associated genes with random-walk-based method in PPI network.

Allergic rhinitis is a common allergic disease with a complex pathogenesis and many unresolved issues. Studies have shown that the incidence of allergic rhinitis is closely related to genetic factors, and research on the related genes could help further understand its pathogenesis and develop new treatment methods. In this study, 446 allergic rhinitis-related genes were obtained on the basis of the DisGeNET database. The protein-protein interaction network was searched using the random-walk-with-restart algorithm with these 446 genes as seed nodes to assess the linkages between other genes and allergic rhinitis. Then, this result was further examined by three screening tests, including permutation, interaction, and enrichment tests, which aimed to pick up genes that have strong and special associations with allergic rhinitis. 52 novel genes were finally obtained. The functional enrichment test confirmed their relationships to the biological processes and pathways related to allergic rhinitis. Furthermore, some genes were extensively analyzed to uncover their special or latent associations to allergic rhinitis, including IRAK2 and MAPK, which are involved in the pathogenesis of allergic rhinitis and the inhibition of allergic inflammation via the p38-MAPK pathway, respectively. The new found genes may help the following investigations for understanding the underlying molecular mechanisms of allergic rhinitis and developing effective treatments.

ELRL-MD: a deep learning approach for myocarditis diagnosis using cardiac magnetic resonance images with ensemble and reinforcement learning integration.

Objective.Myocarditis poses a significant health risk, often precipitated by viral infections like coronavirus disease, and can lead to fatal cardiac complications. As a less invasive alternative to the standard diagnostic practice of endomyocardial biopsy, which is highly invasive and thus limited to severe cases, cardiac magnetic resonance (CMR) imaging offers a promising solution for detecting myocardial abnormalities.Approach.This study introduces a deep model called ELRL-MD that combines ensemble learning and reinforcement learning (RL) for effective myocarditis diagnosis from CMR images. The model begins with pre-training via the artificial bee colony (ABC) algorithm to enhance the starting point for learning. An array of convolutional neural networks (CNNs) then works in concert to extract and integrate features from CMR images for accurate diagnosis. Leveraging the Z-Alizadeh Sani myocarditis CMR dataset, the model employs RL to navigate the dataset's imbalance by conceptualizing diagnosis as a decision-making process.Main results.ELRL-DM demonstrates remarkable efficacy, surpassing other deep learning, conventional machine learning, and transfer learning models, achieving an F-measure of 88.2% and a geometric mean of 90.6%. Extensive experimentation helped pinpoint the optimal reward function settings and the perfect count of CNNs.Significance.The study addresses the primary technical challenge of inherent data imbalance in CMR imaging datasets and the risk of models converging on local optima due to suboptimal initial weight settings. Further analysis, leaving out ABC and RL components, confirmed their contributions to the model's overall performance, underscoring the effectiveness of addressing these critical technical challenges.

Symptoms and Conditions in Children and Adults up to 90 Days after SARS-CoV-2 Infection: A Retrospective Observational Study Utilizing the Common Data Model.

Background/Objectives: There have been widespread reports of persistent symptoms in both children and adults after SARS-CoV-2 infection, giving rise to debates on whether it should be regarded as a separate clinical entity from other postviral syndromes. This study aimed to characterize the clinical presentation of post-acute symptoms and conditions in the Korean pediatric and adult populations. Methods: A retrospective analysis was performed using a national, population-based database, which was encoded using the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). We compared individuals diagnosed with SARS-CoV-2 to those diagnosed with influenza, focusing on the risk of developing prespecified symptoms and conditions commonly associated with the post-acute sequelae of COVID-19. Results: Propensity score matching yielded 1,656 adult and 343 pediatric SARS-CoV-2 and influenza pairs. Ninety days after diagnosis, no symptoms were found to have elevated risk in either adults or children when compared with influenza controls. Conversely, at 1 day after diagnosis, adults with SARS-CoV-2 exhibited a significantly higher risk of developing abnormal liver function tests, cardiorespiratory symptoms, constipation, cough, thrombophlebitis/thromboembolism, and pneumonia. In contrast, children diagnosed with SARS-CoV-2 did not show an increased risk for any symptoms during either acute or post-acute phases. Conclusions: In the acute phase after infection, SARS-CoV-2 is associated with an elevated risk of certain symptoms in adults. The risk of developing post-acute COVID-19 sequelae is not significantly different from that of having postviral symptoms in children in both the acute and post-acute phases, and in adults in the post-acute phase. These observations warrant further validation through studies, including the severity of initial illness, vaccination status, and variant types.

Mechanistic exploration of the Shenlian formula in the suppression of atherosclerosis progression via network pharmacology and in vivo experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: The Shenlian formula (SL) is a Chinese medicine formula used to curb the development of atherosclerosis (AS) and cardiovascular disease in clinical practice. However, owing to the complexity of compounds and their related multiple targets in traditional Chinese medicine (TCM), it remains difficult and urgent to elucidate the underlying mechanisms at a holistic level. AIM: To investigate the intrinsic mechanisms by which SL suppresses AS progression and to gain new insight into its clinical use. METHODS: We proposed a network pharmacology-based workflow to evaluate the mechanism by which SL affects AS via data analysis, target prediction, PPI network construction, GO and KEGG analyses, and a "drug-core ingredient-potential target-key pathway" network. Then, non-targeted lipidomic analysis was performed to explore the differential lipid metabolites in AS rats, revealing the possible mechanism by which SL affects atherosclerotic progression. Moreover, an AS rabbit model was constructed and gavaged for SL intervention. Serum lipid profiles and inflammatory cytokine indices were tested as an indication of the mitigating effect of SL on AS. RESULTS: A total of 89 bioactive compounds and 298 targets related to SL and AS, which play essential roles in this process, were identified, and a component-target-disease network was constructed. GO and KEGG analyses revealed that SL regulated metabolic pathway, lipids and atherosclerosis, the PI3K-Akt pathway, the MAPK pathway and so on.In vivo experimental validation revealed that a total of 43 different lipid metabolites regulated by SL were identified by non-targeted lipidomics, and glycerophospholipid metabolism was found to be an important mechanism for SL to interfere with AS. SL reduced the plaque area and decreased the levels of inflammatory cytokines (TNF-α and IL-4) and blood lipids (TC, TG, LDL-C, and ApoB) in HFD-induced AS models. In addition, HDL and ApoA1 levels are increased. PLA2 and Lipin1 are highly expressed in AS model, indicating their role in destabilizing glycerophosphatidylcholine metabolism and contributing to the onset and progression of ankylosing spondylitis. Moreover, SL intervention significantly reduced the level of pro-inflammatory cytokines; significantly down-regulated NF-kB/p65 expression, exhibiting anti-inflammatory activity. CONCLUSION: The Shenlian formula (SL) plays a pivotal role in the suppression of AS progression by targeting multiple pathways and mechanisms. This study provides novel insights into the essential genes and pathways associated with the prognosis and pathogenesis of AS.

Host proteins interact with viral elements and affect the life cycle of highly pathogenic avian influenza A virus H7N9.

Host-virus interactions can significantly impact the viral life cycle and pathogenesis; however, our understanding of the specific host factors involved in highly pathogenic avian influenza A virus H7N9 (HPAI H7N9) infection is currently restricted. Herein, we designed and synthesized 65 small interfering RNAs targeting host genes potentially associated with various aspects of RNA virus life cycles. Afterward, HPAI H7N9 viruses were isolated and RNA interference was used to screen for host factors likely to be involved in the life cycle of HPAI H7N9. Moreover, the research entailed assessing the associations between host proteins and HPAI H7N9 proteins. Twelve key host proteins were identified: Annexin A (ANXA)2, ANXA5, adaptor related protein complex 2 subunit sigma 1 (AP2S1), adaptor related protein complex 3 subunit sigma 1 (AP3S1), ATP synthase F1 subunit alpha (ATP5A1), COPI coat complex subunit alpha (COP)A, COPG1, heat shock protein family A (Hsp70) member 1A (HSPA)1A, HSPA8, heat shock protein 90 alpha family class A member 1 (HSP90AA1), RAB11B, and RAB18. Co-immunoprecipitation revealed intricate interactions between viral proteins (hemagglutinin, matrix 1 protein, neuraminidase, nucleoprotein, polymerase basic 1, and polymerase basic 2) and these host proteins, presumably playing a crucial role in modulating the life cycle of HPAI H7N9. Notably, ANXA5, AP2S1, AP3S1, ATP5A1, HSP90A1, and RAB18, were identified as novel interactors with HPAI H7N9 proteins rather than other influenza A viruses (IAVs). These findings underscore the significance of host-viral protein interactions in shaping the dynamics of HPAI H7N9 infection, while highlighting subtle variations compared with other IAVs. Deeper understanding of these interactions holds promise to advance disease treatment and prevention strategies.

TransC-ac4C: Identification of N4-acetylcytidine (ac4C) sites in mRNA using deep learning.

N4-acetylcytidine (ac4C) is a post-transcriptional modification in mRNA that is critical in mRNA translation in terms of stability and regulation. In the past few years, numerous approaches employing convolutional neural networks (CNN) and Transformer have been proposed for the identification of ac4C sites, with each variety of approaches processing distinct characteristics. CNN-based methods excels at extracting local features and positional information, whereas Transformer-based ones stands out in establishing long-range dependencies and generating global representations. Given the importance of both local and global features in mRNA ac4C sites identification, we propose a novel method termed TransC-ac4C which combines CNN and Transformer together for enhancing the feature extraction capability and improving the identification accuracy. Five different feature encoding strategies (One-hot, NCP, ND, EIIP, and K-mer) are employed to generate the mRNA sequence representations, in which way the sequence attributes and physical and chemical properties of the sequences can be embedded. To strengthen the relevance of features, we construct a novel feature fusion method. Firstly, the CNN is employed to process five single features, stitch them together and feed them to the Transformer layer. Then, our approach employs CNN to extract local features and Transformer subsequently to establish global long-range dependencies among extracted features. We use 5-fold cross-validation to evaluate the model, and the evaluation indicators are significantly improved. The prediction accuracy of the two datasets is as high as 81.42.

Review of predicting protein stability changes upon variations.

Forecasting alterations in protein stability caused by variations holds immense importance. Improving the thermal stability of proteins is important for biomedical and industrial applications. This review discusses the latest methods for predicting the effects of mutations on protein stability, databases containing protein mutations and thermodynamic parameters, and experimental techniques for efficiently assessing protein stability in high-throughput settings. Various publicly available databases for protein stability prediction are introduced. Furthermore, state-of-the-art computational approaches for anticipating protein stability changes due to variants are reviewed. Each method's types of features, base algorithm, and prediction results are also detailed. Additionally, some experimental approaches for verifying the prediction results of computational methods are introduced. Finally, the review summarizes the progress and challenges of protein stability prediction and discusses potential models for future research directions.

Comparison of prognosis and postoperative morbidities between standard pancreaticoduodenectomy and the TRIANGLE technique for resectable pancreatic ductal adenocarcinoma.

BACKGROUND: Radical surgery combined with systemic chemotherapy offers the possibility of long-term survival or even cure for patients with pancreatic ductal adenocarcinoma (PDAC), although tumor recurrence, especially locally, still inhibits the treatment efficacy. The TRIANGLE technique was introduced as an extended dissection procedure to improve the R0 resection rate of borderline resectable or locally advanced PDAC. However, there was a lack of studies concerning postoperative complications and long-term outcomes of this procedure on patients with resectable PDAC. AIM: To compare the prognosis and postoperative morbidities between standard pancreaticoduodenectomy (PD) and the TRIANGLE technique for resectable PDAC. METHODS: Patients with resectable PDAC eligible for PD from our hospital between June 2018 and December 2021 were enrolled in this retrospective cohort study. All the patients were divided into PDstandard and PDTRIANGLE groups according to the surgical procedure. Baseline characteristics, surgical data, and postoperative morbidities were recorded. All of the patients were followed up, and the date and location of tumor recurrence, and death were recorded. The Kaplan-Meier method and log-rank test were used for the survival analysis. RESULTS: There were 93 patients included in the study and 37 underwent the TRIANGLE technique. Duration of operation was longer in the PDTRIANGLE group compared with the PDstandard group [440 (410-480) min vs 320 (265-427) min] (P = 0.001). Intraoperative blood loss [700 (500-1200) mL vs 500 (300-800) mL] (P = 0.009) and blood transfusion [975 (0-1250) mL vs 400 (0-800) mL] (P = 0.009) were higher in the PDTRIANGLE group. There was a higher incidence of surgical site infection (43.2% vs 12.5%) (P = 0.001) and postoperative diarrhea (54.1% vs 12.5%) (P = 0.001) in the PDTRIANGLE group. The rates of R0 resection and local recurrence, overall survival, and disease-free survival did not differ significantly between the two groups. CONCLUSION: The TRIANGLE technique is safe, with acceptable postoperative morbidities compared with standardized PD, but it does not improve prognosis for patients with resectable PDAC.

Evaluation of drug interactions of Saposhnikoviae Radix and its major components with astragaloside IV and paeoniflorin using in vitro and in vivo experiments.

Saposhnikoviae Radix (SR) may enhance the pharmacodynamics of Huangqi Chifeng Tang (HQCFT) in the treatment of cerebral infarction according to our previous research, but the underlying mechanism is unknown. Herein, an in vivo pharmacokinetic assay in rats and in vitro MDCK-MDR1 cell assays were used to investigate the possible mechanism of SR, its main components, and its interactions with Astragali Radix (AR) and Paeoniae Radix (PR). An ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC‒MS/MS)-based analytical method for quantifying astragaloside IV (ASIV) and paeoniflorin (PAE) in microdialysis and transport samples was developed. The pharmacokinetic parameters of SR were determined using noncompartmental analyses CCK-8 assays were used to detect the cytotoxicity of ASIV, PAE, cimifugin (CIM), prim-o-glucosylcimifugin (POG) and their combinations. Moreover, drug transport was studied using MDCK-MDR1 cells. Western blotting was performed to measure the protein expression levels of P-GP and MRP1. Claudin-5, ZO-1, and F-actin expression was determined via immunohistochemical staining of MDCK-MDR1 cells. harmacokinetic studies revealed that, compared with those of Huangqi Chifeng Tang-Saposhnikoviae Radix (HQCFT-SR), the Tmax of ASIV increased by 11.11 %, and the MRT0-t and Tmax of PAE increased by 11.19 % and 20 %, respectively, in the HQCFT group. Transport studies revealed that when ASIV was coincubated with 28 µM CIM or POG, the apparent permeability coefficient (Papp) increased by 71.52 % and 50.33 %, respectively. Coincubation of PAE with 120 µM CIM or POG increased the Papp by 87.62 % and 60.95 %, respectively. Moreover, CIM and POG significantly downregulated P-gp and MRP1 (P < 0.05), inhibited the expression of Claudin-5, ZO-1, and F-actin (P < 0.05), and affected intercellular tight junctions (TJs). In conclusion, our study successfully established a selective, sensitive and reproducible UPLC‒MS/MS analytical method to detect drug‒drug interactions between SR, AR and PR in vivo and in vitro, which is beneficial for enhancing the therapeutic efficacies of AR and PR. Moreover, this study provides a theoretical basis for further research on the use of SR as a drug carrier.

Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach.

Background: In the central nervous system, glioma is the most common malignant tumor, and patients have a poor prognosis. Identification of novel marker genes and establishment of prognostic models are important for early diagnosis and prognosis determination. Methods: Download glioma data from the CGGA and TCG databases. Application of bioinformatics to analyze the impact of CYBB on the clinicopathological characteristics, immunological features and prognosis of gliomas. Using single-cell sequencing data from 7 glioblastoma patients in the CGGA database, the role of CYBB in the tumor microenvironment was analyzed. In addition, a prognostic model was constructed based on CYBB high and low differentially expressed genes and mitochondrial genes. Results: The expression of CYBB is closely related to various clinical features, immune cell infiltration level, immune checkpoint and survival time of patients. A 10-gene prediction model was constructed based on the differentially expressed genes of low and high CYBB and mitochondria-related genes. Glioma patients with higher risk scores had significantly lower survival probabilities. Receiver operating characteristic curves and nomograms were plotted over time to show the predictive accuracy and predictive value of the 10-gene prognostic model. Conclusions: Our study shows that CYBB is strongly correlated with clinical characteristics features and prognosis of glioma patients, and can be used as a potential therapeutic target. Prognostic models based on CYBB and mitochondrial genes have good performance in predicting prognosis of glioma patients.

Deep learning-accelerated T2WI: image quality, efficiency, and staging performance against BLADE T2WI for gastric cancer.

PURPOSE: The purpose of our study is to investigate image quality, efficiency, and diagnostic performance of a deep learning-accelerated single-shot breath-hold (DLSB) against BLADE for T2-weighted MR imaging (T2WI) for gastric cancer (GC). METHODS: 112 patients with GCs undergoing gastric MRI were prospectively enrolled between Aug 2022 and Dec 2022. Axial DLSB-T2WI and BLADE-T2WI of stomach were scanned with same spatial resolution. Three radiologists independently evaluated the image qualities using a 5-scale Likert scales (IQS) in terms of lesion delineation, gastric wall boundary conspicuity, and overall image quality. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated in measurable lesions. T staging was conducted based on the results of both sequences for GC patients with gastrectomy. Pairwise comparisons between DLSB-T2WI and BLADE-T2WI were performed using the Wilcoxon signed-rank test, paired t-test, and chi-squared test. Kendall's W, Fleiss' Kappa, and intraclass correlation coefficient values were used to determine inter-reader reliability. RESULTS: Against BLADE, DLSB reduced total acquisition time of T2WI from 495 min (mean 4:42 per patient) to 33.6 min (18 s per patient), with better overall image quality that produced 9.43-fold, 8.00-fold, and 18.31-fold IQS upgrading against BALDE, respectively, in three readers. In 69 measurable lesions, DLSB-T2WI had higher mean SNR and higher CNR than BLADE-T2WI. Among 71 patients with gastrectomy, DLSB-T2WI resulted in comparable accuracy to BLADE-T2WI in staging GCs (P > 0.05). CONCLUSIONS: DLSB-T2WI demonstrated shorter acquisition time, better image quality, and comparable staging accuracy, which could be an alternative to BLADE-T2WI for gastric cancer imaging.