Clinical Insight-Augmented Multi-View Learning for Alzheimer’s Detection in Retinal OCTA Images

Alzheimer’s disease (AD) poses a significant globalchallenge, with a notable absence of accessible and cost-effectivediagnostic tools for widespread AD detection. The retina, mirroringthe brain in anatomy and physiology, has emerged asa potential avenue for rapid AD identification through retinalimaging. The current retinal image-based AD detection methodsusually focus primarily on the macular area, but ignore thepotential value that the optic disc region may have for thedetection task. In this study, we leverage both macular- anddisc-centered OCTA images and propose a multi-region fusionframework for AD detection. Based on clinical evidence, weintegrate handcrafted features into the framework to improvemodel performance and interpretability. Specifically, vascularmorphological parameters extracted from the macular and discregions are used as input to a revalued KNN model to improvepredictive capabilities. Furthermore, recognizing the significanceof extracting and utilizing complementary information from themacular and optic disc regions, we propose an uncertaintyguidedstrategy based on Dempster-Shefer Theory (DST) tofuse knowledge from different regions. This approach considerseach region’s forecast quality and significantly improves theeffectiveness and robustness of the model. Through comparativeanalysis with existing methods, we have demonstrated that ourmethod outperforms the state-of-the-art ones and provides morevaluable pathological evidence for the association between retinalvascular changes and AD

MicroRNA-575 targets BLID to promote growth and invasion of non-small cell lung cancer cells

AbstractThis study was designed to detect miR-575 expression and function in non-small cell lung cancer (NSCLC). A higher expression of miR-575 in NSCLC tissues was observed compared with adjacent non-neoplastic tissues. Furthermore, re-introduction of miR-575 significantly promoted cell proliferation, migration, and invasion in the NSCLC line. Moreover, we showed that BLID is negatively regulated by miR-575 at the posttranscriptional level, via a specific target site within the 3′UTR. Overexpression of BLID counteracted miR-575-induced proliferation and invasion in NSCLC cells. The expression of BLID is frequently downregulated in NSCLC tumors and cell lines and inversely correlates with miR-575 expression. The findings of this study contribute to the current understanding of the functions of miR-575 in NSCLC

Impact of CRAMP-34 on Pseudomonas aeruginosa biofilms and extracellular metabolites

Biofilm is a structured community of bacteria encased within a self-produced extracellular matrix. When bacteria form biofilms, they undergo a phenotypic shift that enhances their resistance to antimicrobial agents. Consequently, inducing the transition of biofilm bacteria to the planktonic state may offer a viable approach for addressing infections associated with biofilms. Our previous study has shown that the mouse antimicrobial peptide CRAMP-34 can disperse Pseudomonas aeruginosa (P. aeruginosa) biofilm, and the potential mechanism of CRAMP-34 eradicate P. aeruginosa biofilms was also investigated by combined omics. However, changes in bacterial extracellular metabolism have not been identified. To further explore the mechanism by which CRAMP-34 disperses biofilm, this study analyzed its effects on the extracellular metabolites of biofilm cells via metabolomics. The results demonstrated that a total of 258 significantly different metabolites were detected in the untargeted metabolomics, of which 73 were downregulated and 185 were upregulated. Pathway enrichment analysis of differential metabolites revealed that metabolic pathways are mainly related to the biosynthesis and metabolism of amino acids, and it also suggested that CRAMP-34 may alter the sensitivity of biofilm bacteria to antibiotics. Subsequently, it was confirmed that the combination of CRAMP-34 with vancomycin and colistin had a synergistic effect on dispersed cells. These results, along with our previous findings, suggest that CRAMP-34 may promote the transition of PAO1 bacteria from the biofilm state to the planktonic state by upregulating the extracellular glutamate and succinate metabolism and eventually leading to the dispersal of biofilm. In addition, increased extracellular metabolites of myoinositol, palmitic acid and oleic acid may enhance the susceptibility of the dispersed bacteria to the antibiotics colistin and vancomycin. CRAMP-34 also delayed the development of bacterial resistance to colistin and ciprofloxacin. These results suggest the promising development of CRAMP-34 in combination with antibiotics as a potential candidate to provide a novel therapeutic approach for the prevention and treatment of biofilm-associated infections

Improved method for aging assessment of winding hot-spot insulation of transformer based on the 2-FAL concentration in oil

2-furfuraldehyde (2-FAL) is widely accepted as a chemical marker to indicate the degradation of cellulose insulation in oil-impregnated transformers. However, the application of 2-FAL in the aging diagnosis of transformers in operation is ineffective. The excessive dispersion of 2-FAL concentration measured in transformers is caused by many influence factors. In addition, the 2-FAL concentration in oil cannot indicate the aging of the most serious point given the temperature distribution along the winding height, that is, the insulation at the hot spot of a winding. To optimize the assessment, an improved method for the hot-spot insulation assessment based on the 2-FAL concentration in oil is proposed in this work. The 2-FAL generation in cellulose chain scission is firstly analyzed theoretically, and a new linear relationship between (1/DP -1/DP ) and 2-FAL total generation is obtained. Moreover, the 2-FAL partitioning between an insulation paper and mineral oil influenced by temperature, moisture, and aging status in total is considered. Second, by considering the linear relationship and the 2-FAL partitioning, an equation between the insulation at hot-spot temperature and the 2-FAL concentration in oil is established for the thermal aging under unequal temperature distribution condition. Finally, to verify the proposed method, a testing platform is introduced to conduct the thermal aging experiment with temperature gradients. The proposed method demonstrates better assessment results than the conventional thermal aging test at constant temperature

Oleanolic Acid Promotes the Formation of Probiotic <i>Escherichia coli</i> Nissle 1917 (EcN) Biofilm by Inhibiting Bacterial Motility

Probiotic biofilms have been beneficial in the fight against infections, restoring the equilibrium of the host’s gut microbiota, and enhancing host health. They are considered a novel strategy for probiotic gut colonization. In this case, we evaluated the effects of various active substances from traditional Chinese medicine on Escherichia coli Nissle 1917 (EcN) to determine if they promote biofilm formation. It was shown that 8–64 μg/mL of oleanolic acid increased the development of EcN biofilm. Additionally, we observed that oleanolic acid can effectively suppress biofilm formation in pathogenic bacteria such as Salmonella and Staphylococcus aureus. Next, we assessed the amount of EcN extracellular polysaccharides, the number of live bacteria, their metabolic activity, the hydrophobicity of their surface, and the shape of their biofilms using laser confocal microscopy. Through transcriptome analysis, a total of 349 differentially expressed genes were identified, comprising 134 upregulated and 215 downregulated genes. GO functional enrichment analysis and KEGG pathway enrichment analysis revealed that oleanolic acid functions are through the regulation of bacterial motility, the iron absorption system, the two-component system, and adhesion pathways. These findings suggest that the main effects of oleanolic acid are to prevent bacterial motility, increase initial adhesion, and encourage the development of EcN biofilms. In addition, oleanolic acid interacts with iron absorption to cooperatively control the production of EcN biofilms within an optimal concentration range. Taking these results together, this study suggests that oleanolic acid may enhance probiotic biofilm formation in the intestines, presenting new avenues for probiotic product development

Association between preoperative serum sodium and postoperative 30-day mortality in adult patients with tumor craniotomy

Abstract Background Limited data exist regarding preoperative serum sodium (Na) and 30-day mortality in adult patients with tumor craniotomy. Therefore, this study investigates their relationship. Methods A secondary retrospective analysis was performed using data from the ACS NSQIP database (2012–2015). The principal exposure was preoperative Na. The outcome measure was 30-day postoperative mortality. Binary logistic regression modeling was conducted to explore the link between them, and a generalized additive model and smooth curve fitting were applied to evaluate the potential association and its explicit curve shape. We also conducted sensitivity analyses and subgroup analyses. Results A total of 17,844 patients (47.59% male) were included in our analysis. The mean preoperative Na was 138.63 ± 3.23 mmol/L. The 30-day mortality was 2.54% (455/17,844). After adjusting for covariates, we found that preoperative Na was negative associated with 30-day mortality. (OR = 0.967, 95% CI:0.941, 0.994). For patients with Na ≤ 140, each increase Na was related to a 7.1% decreased 30-day mortality (OR = 0.929, 95% CI:0.898, 0.961); for cases with Na > 140, each increased Na unit was related to a 8.8% increase 30-day mortality (OR = 1.088, 95% CI:1.019, 1.162). The sensitivity analysis and subgroup analysis indicated that the results were robust. Conclusions This study shows a positive and nonlinear association between preoperative Na and postoperative 30-day mortality in adult patients with tumor craniotomy. Appropriate preoperative Na management and maintenance of serum Na near the inflection point (140) may reduce 30-day mortality

Recognition of Rare Microfossils Using Transfer Learning and Deep Residual Networks

Various microfossils from the early Cambrian provide crucial clues for understanding the Cambrian explosion and the origin of animal phyla. However, specimens with important anatomical structures are extremely rare and the efficiency of retrieving such fossils by traditional manual selection under a microscope is quite low. Such a contradiction has hindered breakthroughs in micropaleontology for a long time. Here, we propose a solution for identifying specific taxa of Cambrian microfossils using only a few available specimens by transferring a model pre-trained on natural image datasets to the field of paleontological artificial intelligence. The method employs a 34-layer deep residual neural network as the underlying framework, migrates the ImageNet pre-trained model, freezes the low-layer network parameters and retrains the high-layer parameters to build a microfossil image recognition model. We built training sets with randomly selected images of varied number for each taxon. Our experiments show that the average recognition accuracy for specific taxa of Cambrian microfossils (50 images for each taxon) is higher than 0.97 and it can reach 0.85 with only three training samples per taxon. Comparative analyses indicate that our results are much better than those of various prevalent methods, such as the transpose convolutional neural network (TCNN). This demonstrates the feasibility of using natural images (ImageNet) for the training of microfossil recognition models and provides a promising tool for the discovery of rare fossils

IHGA: An interactive web server for large-scale and comprehensive discovery of genes of interest in hepatocellular carcinoma

Mining gene expression data is valuable for discovering novel biomarkers and therapeutic targets in hepatocellular carcinoma (HCC). Although emerging data mining tools are available for pan-cancer–related gene data analysis, few tools are dedicated to HCC. Moreover, tools specifically designed for HCC have restrictions such as small data scale and limited functionality. Therefore, we developed IHGA, a new interactive web server for discovering genes of interest in HCC on a large-scale and comprehensive basis. Integrative HCC Gene Analysis (IHGA) contains over 100 independent HCC patient-derived datasets (with over 10,000 tissue samples) and more than 90 cell models. IHGA allows users to conduct a series of large-scale and comprehensive analyses and data visualizations based on gene mRNA levels, including expression comparison, correlation analysis, clinical characteristics analysis, survival analysis, immune system interaction analysis, and drug sensitivity analysis. This method notably enhanced the richness of clinical data in IHGA. Additionally, IHGA integrates artificial intelligence (AI)–assisted gene screening based on natural language models. IHGA is free, user-friendly, and can effectively reduce time spent during data collection, organization, and analysis. In conclusion, IHGA is competitive in terms of data scale, data diversity, and functionality. It effectively alleviates the obstacles caused by HCC heterogeneity to data mining work and helps advance research on the molecular mechanisms of HCC