COX-2/PTGS2-targeted herbal-derived oligonucleotide drug HQi-sRNA-2 was effective in spontaneous mouse lung cancer model.

In 2020, the number of deaths caused by lung cancer worldwide reached 1,796,144, making it the leading cause of cancer-related deaths. Cyclooxygenase-2/prostaglandin endoperoxide synthase 2 (COX-2/PTGS2) is overexpressed in lung cancer, which promotes tumor proliferation, invasion, angiogenesis, and resistance to apoptosis. Here, we report that the oligonucleotide drug HQi-sRNA-2 from Traditional Chinese Medicine Huangqin targeting COX-2/PTGS2 significantly inhibited proliferation, migration, and invasion and induced apoptosis in the human lung cancer cell line NCI-H460. Oral delivery of HQi-sRNA-2 bencaosomes prolonged survival, reduced tumor burden, and maintained weight in a spontaneous mouse lung cancer model. Compared with paclitaxel, HQi-sRNA-2 may be less toxic and have approximately equal efficacy in reducing tumor burden. Our previous studies reported that herbal small RNAs (sRNAs) are functional medical components. Our data suggest that sphingosine (d18:1)-HQi-sRNA-2 bencaosomes, targeting COX-2/PTGS2 and downregulating the PI3K and AKT signaling pathways, may provide novel therapeutics for lung cancer.

Identification of key genes associated with cervical cancer based on bioinformatics analysis.

BACKGROUND: Cervical cancer has extremely high morbidity and mortality, and its pathogenesis is still in the exploratory stage. This study aimed to screen and identify differentially expressed genes (DEGs) related to cervical cancer through bioinformatics analysis. METHODS: GSE63514 and GSE67522 were selected from the GEO database to screen DEGs. Then GO and KEGG analysis were performed on DEGs. PPI network of DEGs was constructed through STRING website, and the hub genes were found through 12 algorithms of Cytoscape software. Meanwhile, GSE30656 was selected from the GEO database to screen DEMs. Target genes of DEMs were screened through TagetScan, miRTarBase and miRDB. Next, the hub genes screened from DEGs were merged with the target genes screened from DEMs. Finally, ROC curve and nomogram analysis were performed to assess the predictive capabilities of the hub genes. The expression of these hub genes were verified through TCGA, GEPIA, qRT-PCR, and immunohistochemistry. RESULTS: Six hub genes, TOP2A, AURKA, CCNA2, IVL, KRT1, and IGFBP5, were mined through the protein-protein interaction network. The expression of these hub genes were verified through TCGA, GEPIA, qRT-PCR, and immunohistochemistry, and it was found that TOP2A, AURKA as well as CCNA2 were overexpressed and IGFBP5 was low expression in cervical cancer. CONCLUSIONS: This study showed that TOP2A, AURKA, CCNA2 and IGFBP5 screened through bioinformatics analysis were significantly differentially expressed in cervical cancer samples compared with normal samples, which might be biomarkers of cervical cancer.

Influence of negative mood on restrained eaters' memory suppression of food cues: An event-related potentials study.

Negative mood has been found to be a critical trigger for overeating in restrained eaters. The ability to suppress thinking of palatable food cues is crucial to control hedonic eating; nevertheless, little research has been conducted to explore inhibitory control in cognitive processes among restrained eaters. To address this gap, this study primed restrained eaters with negative (n = 23) or neutral emotions (n = 24) and applied a Think/No-think paradigm to explore their retrieval facilitation/suppression ability for food cues, while recording Electroencephalogram (EEG) data. Results indicated that the recall rate of the No-think condition (retrieval suppressing task) was higher than the Think condition (retrieval task). Negative affect did not influence the recall rate, but it did evoke smaller N2 amplitudes, larger P2 and P3 amplitudes, as well as late positive component (LPC) amplitudes. Among these components, P2 evoked by the No-think and Think conditions was larger than the perceptual control condition. Our findings suggested that in negative moods, restrained eaters need to allocate more attentional resources to suppress food cues. The findings further demonstrated that the influence of negative moods appeared at an early stage of cognitive processing and caused a resource depletion in memory suppression. This research provides a neurophysiological basis for understanding emotional influences on the process of restrained eaters' inhibition control for external food cues.

Identification of differentially expressed genes associated with lung adenocarcinoma via bioinformatics analysis.

Lung adenocarcinoma (LUAD) with extremely high morbidity as well as mortality is still in the exploration stage of pathogenesis and treatment. This study aimed to screen and identify differentially expressed genes (DEGs) associated with LUAD via bioinformatics analysis. Three LUAD microarray datasets, GSE116959, GSE68571 and GSE40791, were selected from the Gene Expression Omnibus (GEO) database to analyze the DEGs. 128 DEGs were identified in all, incorporating 36 upregulated and 92 downregulated. Function and pathway enrichment analyses showed that metabolic pathways were their main signaling pathways. After that, seven hub genes including VWF, SPP1, PECAM1, TOP2A, CDK1, UBE2C and KIF23 were mined by the protein-protein interaction (PPI) network. Gene expression analysis, TNM and survival analysis of these hub genes were performed via Gene Expression Profiling Interactive Analysis (GEPIA) online database. Further analysis indicated that TOP2A, CDK1, UBE2C and KIF23 were related to the stage of LUAD patients and overall survival. Then, we verified the relative expression levels of TOP2A, CDK1, UBE2C and KIF23 in LUAD cell lines by qRT-PCR. In conclusion, this study indicated that the four hub genes screened out by bioinformatics analysis were differentially expressed in LUAD compared to normal sample and might be prognostic markers of LUAD.

Wanting to eat matters: Negative affect and emotional eating were associated with impaired memory suppression of food cues.

OBJECTIVE: Previous studies have linked emotional eating with negative affect and decreased inhibitory control. However, studies on inhibitory control have generally focused on motor inhibition. How to stop higher-level cognitive processes, such as food-related memory retrieval or voluntary thoughts, received few direct investigation in field of food intake or food-related decision making. The current study, adopting Anderson and Green's Think/No-Think paradigm, aimed to investigate the relationship between emotional eating, negative affect and food-related memory suppression. METHOD: Sixty-one young females participated in the current study, during which they finished food specific Think/No-Think task. Their positive and negative affect and eating style were measured using Positive Affect and Negative Affect Schedule and Dutch Eating Behavior Question. The reward value of the food item used in the Think/No-Think task was measured using liking and wanting ratings. RESULTS: As hypothesized, negative affect and emotional eating were associated with decreased memory suppression of palatable food cues. Further analysis showed that higher emotional eating was associated with greater wanting only among the food items which were previously suppressed however remembered later. DISCUSSION: The current study presents the first evidence that negative affect and emotional eating were associated with impaired memory suppression of palatable food cues, and it provided insight into the interaction between reward valuation for the food cues and hippocampal memory mechanisms during retrieval suppression.

Measurement of Gas-Oil Two-Phase Flow Patterns by Using CNN Algorithm Based on Dual ECT Sensors with Venturi Tube.

In modern society, the oil industry has become the foundation of the world economy, and how to efficiently extract oil is a pressing problem. Among them, the accurate measurement of oil-gas two-phase parameters is one of the bottlenecks in oil extraction technology. It is found that through the experiment the flow patterns of the oil-gas two-phase flow will change after passing through the venturi tube with the same flow rates. Under the different oil-gas flow rate, the change will be diverse. Being motivated by the above experiments, we use the dual ECT sensors to collect the capacitance values before and after the venturi tube, respectively. Additionally, we use the linear projection algorithm (LBP) algorithm to reconstruct the image of flow patterns. This paper discusses the relationship between the change of flow patterns and the flow rates. Furthermore, a convolutional neural network (CNN) algorithm is proposed to predict the oil flow rate, gas flow rate, and GVF (gas void fraction, especially referring to sectional gas fraction) of the two-phase flow. We use ElasticNet regression as the loss function to effectively avoid possible overfitting problems. In actual experiments, we compare the Typical-ECT-imaging-based-GVF algorithm and SVM (Support Vector Machine) algorithm with CNN algorithm based on three different ECT datasets. Three different sets of ECT data are used to predict the gas flow rate, oil flow rate, and GVF, and they are respectively using the venturi front-based ECT data only, while using the venturi behind-based ECT data and using both these data.

Combined analysis of metabolomics and 16S rRNA sequencing for ankylosing spondylitis patients before and after secukinumab therapy.

OBJECTIVE: Alterations in gut microbiota have been implicated in the pathogenesis of ankylosing spondylitis (AS), but the underlying mechanisms remain elusive. This study aims to investigate changes in gut microbiota and metabolites in individuals with AS before and after treatment with secukinumab, to identify the biological characteristics specific to AS patients and investigate the potential biomarkers, for optimizing therapeutic strategies more effectively. METHODS: Fecal microbiome data were collected from 30 AS patients before and after secukinumab therapy and compared with data from 40 healthy controls (HC). Additionally, we analyzed the metabolic profile of both groups from plasma. RESULTS: Findings indicated that the treatment-induced changes in the composition of several crucial bacterial groups, including Megamonas, Prevotella_9, Faecalibacterium, Roseburia, Bacteroides, and Agathobacter. Post-treatment, these groups exhibited a distribution more akin to that of the healthy populations compared with their pretreatment status. We identified three gut microbial taxa, namely Prevotellaceae_bacterium_Marseille_P2831, Prevotella_buccae, and Elusimicrobiota, as potential biomarkers for diagnosing individuals at a higher risk of developing AS and assessing disease outcomes. Plasma metabolomics analysis revealed 479 distinct metabolites and highlighted three disrupted metabolic pathways. Integration of microbiome and metabolomics datasets demonstrated a significant degree of correlation, underscoring the impact of the microbiome on metabolic activity. CONCLUSION: Secukinumab can restore the balance of the gut microbiome and metabolites in AS patients, rendering them more similar to those found in the healthy population. The analysis of microbiome and metabolomics data have unveiled some candidate biomarkers capable of evaluating treatment efficacy.

Windows of sensitivity for risk of adverse birth outcomes related to gestational PM2.5 exposure: Evidence from a natural experiment.

While numerous studies have associated maternal exposure to PM2.5 with adverse birth outcomes, findings remain inconsistent and difficult to generalize. We aimed to investigate the causal relationship and window of sensitivity between gestational exposure to PM2.5 and birth outcomes. We leveraged high-resolution satellite data to quantify gestational PM2.5 exposure at the individual level, along with a combined model to determine daily relative risks (RRs) of birth outcomes in COVID-19 prelockdown and lockdown groups. RRs between the two groups were further compared using a longitudinal pre-post non-experimental design to identify sensitivity windows of adverse birth outcomes. A total of 73,781 pregnant women from the COVID-19 prelockdown group and 6267 pregnant women from the lockdown group were included for analysis. The daily mean PM2.5 concentrations in the lockdown group decreased by 21.7% compared to the prelockdown group. During the first trimester, every 10 µg/m3 increase in PM2.5 significantly increased the risk of congenital abnormalities of major organs such as the cardiovascular system, gastrointestinal tract, nervous system, urinary system, and respiratory system. Moreover, gestational exposure to PM2.5 during the first trimester was associated with higher risks of premature delivery and term low birth weight. While PM2.5 exposure during the second trimester was positively correlated with macrosomia. Gestational exposure to PM2.5 is associated with increased risks of various adverse birth outcomes with specific sensitive windows. We demonstrated that gestational exposure to PM2.5 increased risks of various adverse birth outcomes with specific window of sensitivity through the natural experiment design. Our findings underscore the urgent need for policies and initiatives targeting PM2.5 reduction, especially during critical periods of pregnancy.

Advancing Understanding of Childhood Asthma: Lessons Learned from Birth Cohort Studies.

Asthma and allergies are some of the most common chronic disorders affecting children, the prevalence of which has been increasing in countries and regions undergoing rapid development like China. To curb the rising tide of allergies and safeguard the health of future generations, it is of critical importance to understand how asthma inception is influenced by factors acting at different life stages. Birth cohorts represent a powerful tool to investigate the temporal sequence of exposures along the natural course of asthma. We examined recent evidence on birth cohort studies of asthma and allergic diseases and evaluated their strengths and weaknesses. Essential elements for a successful birth cohort are proposed to further elucidate asthma etiology and pathogenies. Initiating new cohorts in understudied populations with the application of advanced analytical approaches will be needed. Moreover, fostering collaborative networks using standardized methodologies should be prioritized to enable integration of findings across diverse cohorts. There remains an urgent and unmet need to further translate the seminal findings from asthma birth cohort studies into targeted primary prevention strategies to eradicate the disease.

Chinese Food Image Database for Eating and Appetite Studies.

Modern people live in an environment with ubiquitous food cues, including food advertisements, videos, and smells. Do these food cues change people's eating behavior? Since diet plays a crucial role in maintaining health, it has been researched for decades. As convenient alternatives for real food, food images are widely used in diet research. To date, researchers from Germany, Spain, and other countries have established food photo databases; however, these food pictures are not completely suitable for Chinese studies because of the ingredients and characteristics of Chinese food. The main goal of this research is to create a library of Chinese food images and to provide as complete a data reference as possible for future studies that use food images as experimental material. After standardized processing, we selected 508 common Chinese food pictures with high familiarity and recognizability and attached detailed classifications concerning taste, macronutrients, calories, and participants' emotional responses to the pictures. Additionally, with food pictures as material, we conducted research on how people make dietary decisions in order to identify the variables that may affect a person's food choices. The effects of individual perceived healthiness and palatability, gender, BMI, family income, and levels of emotional and restricted eating were examined using eating decisions based on healthiness and palatability as dependent variables. The results showed that people with low household incomes are more likely to be influenced by food taste in their dietary decision-making process, while individuals with high household incomes are more likely to consider the healthy aspects of food. Moreover, parental BMI affects what children consume, with children who have parents with higher BMIs being more prone to overlook the healthiness value of food.