Search

Abstract Growth hormone secretagogue receptor 1a (GHS-R1a), also known as the ghrelin receptor, is an important nutrient sensor and metabolic regulator in both humans and rodents. Increased GHS-R1a expression is observed in the hippocampus of both Alzheimer’s disease (AD) patients and AD model mice. However, the causal relationship between GHS-R1a elevation in the hippocampus and AD memory deficits remains uncertain. Here, we find that increasing GHS-R1a expression in dCA1 pyramidal neurons impairs hippocampus-dependent memory formation, which is abolished by local administration of the endogenous antagonist LEAP2. GHS-R1a elevation in dCA1 pyramidal neurons suppresses excitability and blocks memory allocation in these neurons. Chemogenetic activation of those high GHS-R1a neurons during training rescues GHS-R1a overexpression-induced memory impairment. Moreover, we demonstrate that increasing GHS-R1a expression in dCA1 pyramidal neurons hampers these neurons’ ability to encode spatial memory and reduces engram size in the dCA1 region. Finally, we show that GHS-R1a deletion mitigates spatial memory deficits in APP/PS1 mice with increased GHS-R1a expression in the hippocampus. Our findings reveal a negative, causal relationship between hippocampal GHS-R1a expression and memory encoding, and suggest that blocking the abnormal increase in GHS-R1a activity/expression may be a promising approach to improve memory and treat cognitive decline in AD.

Abstract A magnetic ionic liquid (abridged as MIL) [C6mim]5[Dy(SCN)8] was prepared and used as the magnetic lubricant of a steel-steel sliding pair. The tribological properties of the as-prepared MIL were evaluated with a commercially obtained magnetic fluid lubricant (abridged as MF; the mixture of dioctyl sebacate and Fe3O4, denoted as DIOS-Fe3O4) as a control. The lubrication mechanisms of the two types of magnetic lubricants were discussed in relation to worn surface analyses by SEM-EDS, XPS, and profilometry, as well as measurement of the electric contact resistance of the rubbed steel surfaces. The results revealed that the MIL exhibits better friction-reducing and antiwear performances than the as-received MF under varying test temperatures and loads. This is because the MIL participates in tribochemical reactions during the sliding process, and forms a boundary lubrication film composed of Dy2O3, FeS, FeSO4, nitrogen-containing organics, and thioether on the rubbed disk surface, thereby reducing the friction and wear of the frictional pair. However, the MF is unable to form a lubricating film on the surface of the rubbed steel at 25 °C, though it can form a boundary film consisting of Fe3O4 and a small amount of organics under high temperature. Furthermore, the excessive Fe3O4 particulates that accumulate in the sliding zone may lead to enhanced abrasive wear of the sliding pair.

Abstract Background/Objectives Increased free fatty acid (FFA) promotes adiponectin secretion in healthy subjects and induces inflammation in diabetes. Given the potential pro-inflammatory role of adiponectin in “adiponectin paradox”, we performed this study in patients with type 2 diabetes mellitus (T2DM) to assess the association of FFA with adiponectin and to investigate whether adiponectin mediates FFA-related inflammation. Methods This cross-sectional study consisted of adult patients with T2DM. FFA, adiponectin, and tumor necrosis factor-α (TNF-α) were assayed from fasting venous blood after overnight fasting for at least 8 h. Multivariable linear regression analysis and restricted cubic splines (RCS) analysis were performed to identify the association between FFA and adiponectin. Mediation analysis was performed to determine the mediating effect of adiponectin on the association between FFA and TNF-α. Results This study included 495 participants, with 332 males (67.1%) and a mean age of 47.0 ± 11.2 years. FFA was positively associated with adiponectin (b = 0.126, 95%CI: 0.036–0.215, P = 0.006) and was the main contributor to the increase of adiponectin (standardized b = 0.141). The RCS analysis demonstrated that adiponectin increased with FFA when FFA was less than 0.7 mmol/L but did not further increase thereafter (P overall

Background: Exosomes, one of small extracellular vesicles, play a vital role in cell to cell communication and contribute to the advancement of tumors through their cargo molecules. Exosomal circRNAs have emerged as significant players in various types of tumors. Thus, this study aimed to investigate how exosomal circRNAs are involved in the diagnosis and progression of gastric cancer (GC). Methods: Serum exosomes were characterized using transmission electron microscopy, nanoparticle tracking analysis and Western blot. CCK-8, colony formation and transwell assays were conducted to study the function of hsa_circ_0050547 (named as circ50547). qRT-PCR was used to quantify the expression of circ50547 in GC tissues and serum exosomes. Fluorescence in situ hybridization was applied to detect the cellular distribution of circ50547. Stemness and drug-resistance were detected by sphere formation, WB, flow cytometry and half-maximal inhibitory concentration analyses. Bioinformatic analyses, luciferase experiments, qRT-PCR and WB were used to investigate molecular mechanisms. Results: We discovered for the first time a new type of GC-derived exosomal circRNA, circ50547. We found that circ50547 is highly expressed in both GC tissues and serum exosomes. Interestingly, we observed that the diagnostic value of exosomal circ50547 is superior to that of serum circ50547. Circ50547 overexpression enhanced the proliferation, migration, invasion, stemness and drug resistance of GC cells, while knockdown of circ50547 showed the opposite effect. Mechanistically, circ50547 acted as a sponge for miR-217 to regulate the expression of HNF1B, which promoted gastric cancer progression. Conclusion: Exosomal circ50547 may be a promising marker for the diagnosis and prognosis prediction of GC. These findings suggest that it plays an oncogenic role through miR-217/HNF1B signaling pathway in GC.

The development of messenger RNA (mRNA) vaccines and therapeutics necessitates the production of high-quality in vitro-transcribed mRNA drug substance with specific critical quality attributes (CQAs), which are closely tied to the uniformity of linear DNA template. The supercoiled plasmid DNA is the precursor to the linear DNA template, and the supercoiled DNA percentage is commonly regarded as a key in-process control (IPC) during the manufacturing of linear DNA template. In this study, we investigate the influence of supercoiled DNA percentage on key mRNA CQAs, including purity, capping efficiency, double-stranded RNA (dsRNA), and distribution of poly(A) tail. Our findings reveal a significant impact of supercoiled DNA percentage on mRNA purity and in vitro transcription yield. Notably, we observe that the impact on mRNA purity can be mitigated through oligo-dT chromatography, alleviating the tight range of DNA supercoiled percentage to some extent. Overall, this study provides valuable insights into IPC strategies for DNA template chemistry, manufacturing, and controls (CMC) and process development for mRNA drug substance.

Abstract The implementation of primary tumor resection (PTR) in the treatment of kidney cancer patients (KC) with bone metastases (BM) has been controversial. This study aims to construct the first tool that can accurately predict the likelihood of PTR benefit in KC patients with BM (KCBM) and select the optimal surgical candidates. This study acquired data on all patients diagnosed with KCBM during 2010–2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (PSM) was utilized to achieve balanced matching of PTR and non-PTR groups to eliminate selection bias and confounding factors. The median overall survival (OS) of the non-PTR group was used as the threshold to categorize the PTR group into PTR-beneficial and PTR-Nonbeneficial subgroups. Kaplan–Meier (K–M) survival analysis was used for comparison of survival differences and median OS between groups. Risk factors associated with PTR-beneficial were identified using univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC), area under the curve (AUC), calibration curves, and decision curve analysis (DCA) were used to validate the predictive performance and clinical utility of the nomogram. Ultimately, 1963 KCBM patients meeting screening criteria were recruited. Of these, 962 patients received PTR and the remaining 1061 patients did not receive PTR. After 1:1 PSM, there were 308 patients in both PTR and non-PTR groups. The K–M survival analysis results showed noteworthy survival disparities between PTR and non-PTR groups, both before and after PSM (p

Abstract Background The global outbreak of coronavirus disease (COVID-19) has led medical universities in China to conduct online teaching. This study aimed to assess the effectiveness of a blended learning approach that combines online teaching and virtual reality technology in dental education and to evaluate the acceptance of the blended learning approach among dental teachers and students. Methods The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist was followed in this study. A total of 157 students’ perspectives on online and virtual reality technology education and 54 teachers’ opinions on online teaching were collected via questionnaires. Additionally, 101 students in the 2015-year group received the traditional teaching method (TT group), while 97 students in the 2017-year group received blended learning combining online teaching and virtual reality technology (BL group). The graduation examination results of students in the two groups were compared. Results The questionnaire results showed that most students were satisfied with the online course and the virtual simulation platform teaching, while teachers held conservative and neutral attitudes toward online teaching. Although the theoretical score of the BL group on the final exam was greater than that of the TT group, there was no significant difference between the two groups (P = 0.805). The skill operation score of the BL group on the final exam was significantly lower than that of the TT group (P = 0.004). The overall score of the BL group was lower than that of the TT group (P = 0.018), but the difference was not statistically significant (P = 0.112). Conclusions The blended learning approach combining online teaching and virtual reality technology plays a positive role in students’ learning and is useful and effective in dental education.

Aspect-level sentiment analysis can provide a fine-grain sentiment classification for inferring the sentiment polarity of specific aspects. Graph convolutional network (GCN) becomes increasingly popular because its graph structure can characterize the words' correlation for extracting more sentiment information. However, the word distance is often ignored and cause the cross-misclassification of different aspects. To address the problem, we propose a novel dual GCN structure to take advantage of word distance, syntactic information, and sentiment knowledge in a joint way. The word distance is not only used to enhance the syntactic dependency tree, but also to construct a new graph with semantic knowledge. Then, the two kinds of word distance assisted graphs are fed into two GCNs for further classification. The comprehensive results on two self-collected Chinese datasets (MOOC comments and Douban book reviews) as well as five open-source English datasets, demonstrate that our proposed approach achieves higher classification accuracy than the state-of-the-art methods with up to 1.81x training acceleration.

In this study, the effects of adding glutamate (Glu), glutamine (Gln), aspartate (Asp), and asparagine (Asn) on the flavor formation of Huangjiu were investigated, and the effect of Gln concentration on the quality, microbial community structure, and flavor development of Huangjiu was further explored. Varied Gln concentrations influenced yeast growth, sugar utilization, microbial communities, and quality attributes. Additional Gln promoted yeast cell counts and sugar depletion. It increased the complexity of bacterial co-occurrence networks and reduced the impact of stochastic processes on assembly. Correlation analysis linked microorganisms to flavor compounds. Isolation experiments verified the role of Saccharomyces cerevisiae, Aspergillus chevalieri, Bacillus altitudinis, and Lactobacillus coryniformis in flavor production under Gln conditions. This research elucidated the microbiological mechanisms by which amino acid supplementation, especially Gln, enhances Huangjiu quality by modulating microbial metabolic functions and community dynamics during fermentation. This research is significant for guiding the production of Huangjiu and enhancing its quality.

Breast cancer seriously threatens women's physical and mental health. Mammography is one of the most effective methods for breast cancer diagnosis via artificial intelligence algorithms to identify diverse breast masses. The popular intelligent diagnosis methods require a large amount of breast images for training. However, collecting and labeling many breast images manually is extremely time consuming and inefficient. In this paper, we propose a distributed multi-latent code inversion enhanced Generative Adversarial Network (dm-GAN) for fast, accurate and automatic breast image generation. The proposed dm-GAN takes advantage of the generator and discriminator of the GAN framework to achieve automatic image generation. The new generator in dm-GAN adopts a multi-latent code inverse mapping method to simplify the data fitting process of GAN generation and improve the accuracy of image generation, while a multi-discriminator structure is used to enhance the discrimination accuracy. The experimental results show that the proposed dm-GAN can automatically generate breast images with higher accuracy, up to a higher 1.84 dB Peak Signal-to-Noise Ratio (PSNR) and lower 5.61% Fréchet Inception Distance (FID), as well as 1.38x faster generation than the state-of-the-art.

High quality medical images play an important role in intelligent medical analyses. However, the difficulty of acquiring medical images with professional annotation makes the required medical image datasets, very expensive and time-consuming. In this paper, we propose a semi-supervised method, $ {\mathrm{C}\mathrm{A}\mathrm{U}}^{+} $, which is a consensus model of augmented unlabeled data for cardiac image segmentation. First, the whole is divided into two parts: the segmentation network and the discriminator network. The segmentation network is based on the teacher student model. A labeled image is sent to the student model, while an unlabeled image is processed by CTAugment. The strongly augmented samples are sent to the student model and the weakly augmented samples are sent to the teacher model. Second, $ {\mathrm{C}\mathrm{A}\mathrm{U}}^{+} $ adopts a hybrid loss function, which mixes the supervised loss for labeled data with the unsupervised loss for unlabeled data. Third, an adversarial learning is introduced to facilitate the semi-supervised learning of unlabeled images by using the confidence map generated by the discriminator as a supervised signal. After evaluating on an automated cardiac diagnosis challenge (ACDC), our proposed method $ {\mathrm{C}\mathrm{A}\mathrm{U}}^{+} $ has good effectiveness and generality and $ {\mathrm{C}\mathrm{A}\mathrm{U}}^{+} $ is confirmed to have a improves dice coefficient (DSC) by up to 18.01, Jaccard coefficient (JC) by up to 16.72, relative absolute volume difference (RAVD) by up to 0.8, average surface distance (ASD) and 95% Hausdorff distance ($ {HD}_{95} $) reduced by over 50% than the latest semi-supervised learning methods.

Abstract Exosomal circRNA serves a novel genetic information molecule, facilitating communication between tumor cells and microenvironmental cells, such as immune cells, fibroblasts, and other components, thereby regulating critical aspects of cancer progression including immune escape, tumor angiogenesis, metabolism, drug resistance, proliferation and metastasis. Interestingly, microenvironment cells have new findings in influencing tumor progression and immune escape mediated by the release of exosomal circRNA. Given the intrinsic stability, abundance, and broad distribution of exosomal circRNAs, they represent excellent diagnostic and prognostic biomarkers for liquid biopsy. Moreover, artificially synthesized circRNAs may open up new possibilities for cancer therapy, potentially bolstered by nanoparticles or plant exosome delivery strategies. In this review, we summarize the functions and underlying mechanisms of tumor cell and non-tumor cell-derived exosomal circRNAs in cancer progression, with a special focus on their roles in tumor immunity and metabolism. Finally, we examine the potential application of exosomal circRNAs as diagnostic biomarkers and therapeutic targets, highlighting their promise for clinical use.

Aim: To evaluate the costs and consequences of two front-line atrial fibrillation (AF) treatments from Chinese healthcare system perspective: radiofrequency catheter ablation (RFCA) using ThermoCool SmartTouch Catheter guided by Ablation Index (STAI), in comparison to antiarrhythmic drugs (AADs). Patients & methods: We simulated clinical and economic consequences for AF patients initially receiving STAI or AADs using a short-term decision tree model leading to a 10-year long-term Markov model. The model projected both clinical consequences and costs associated with, among others, AF, heart failure (HF), strokes, and deaths due to AF or AF related complications. Data informing the models included combination of a local real-world study and published clinical studies. Results: STAI was advantageous versus AADs on all 4 main clinical outcomes evaluated; AF: 25.83% lower (12.84% vs 38.67%), HF: 2.22% lower (1.33% vs 3.55%), stroke or post stroke: 1.82% lower (10.00% vs 11.82%) and deaths due to AF or AF related complications: 0.64% lower (4.11% vs 4.75%). The average total cost per patient in STAI group was ¥16,682 lower (¥123,124 vs ¥139,806). The one-way sensitivity analysis indicated that the difference in total cost was most sensitive to annual AF recurrence probability in AADs-treated patients. Probabilistic sensitivity analysis indicated a 98.5% probability that RFCA treatment would result in cost savings by the end of the 10th year. Conclusion: Radiofrequency catheter ablation using SmartTouch catheter guided by Ablation Index was superior to AADs as the first-line AF treatment in Chinese setting with better clinical outcomes and at lower costs over a 10-year time horizon.

The continuous increase in the number of transactions is exerting significant pressure on the storage capacity of blockchains. By storing data on multiple blockchains and interacting with each other with cross-chain technology, the storage pressure can be relieved to a large degree. Nevertheless, the feature of immutability may impede the further development of blockchains, e.g., some expired identity information cannot be updated due to immutability. The decentralized chameleon hash function can resolve the issue while ensuring the feature of decentralization. Unfortunately, how to ensure the consistency of dynamic data updating in cross-chain interaction is still a question worth considering. In this paper, we propose a dynamic cross-chain decentralized data consistency verification (DCCV) model, in which we adopt an audit chain and design a dynamic Merkle hash tree to guarantee the consistency of dynamic data updating between the source chain and the target chain. In addition, in order to enhance the relevance of calculations across different smart contracts and improve audit efficiency, we propose a way to develop cross-chain smart contracts collaboratively. Moreover, Cosi protocol and multi-signcryption are utilized to ensure the security and privacy of cross-chain data transmission. Finally, theoretical and experimental analysis demonstrates that DCCV can achieve dynamic data consistency verification in the process of cross-chain interaction.

Cordycepin is considered a major bioactive component in Cordyceps militaris extract. This study was performed to evaluate the ameliorative effect of Cordyceps militaris extract (CME) and cordycepin (CPN) supplementation on intestinal damage in LPS-challenged piglets. The results showed that CPN or CME supplementation significantly increased the villus height (p < 0.01) and villus height/crypt depth ratio (p < 0.05) in the jejunum and ileum of piglets with LPS-induced intestinal inflammation. Meanwhile, CPN or CME supplementation alleviated oxidative stress and inflammatory responses by reducing the levels of MDA (p < 0.05) and pro-inflammatory cytokines in the serum. Additionally, supplementation with CPN or CME modulated the structure of the intestinal microbiota by enriching short-chain fatty acid-producing bacteria, and increased the level of butyrate (p < 0.05). The RNA-seq results demonstrated that CME or CPN altered the complement and coagulation-cascade-related genes (p < 0.05), including upregulating gene KLKB1 while downregulating the genes CFD, F2RL2, CFB, C4BPA, F7, C4BPB, CFH, C3 and PROS1, which regulate the complement activation involved in inflammatory and immune responses. Correlation analysis further demonstrated the potential relation between the gut microbiota and intestinal inflammation, oxidative stress, and butyrate in piglets. In conclusion, CPN or CME supplementation might inhibit LPS-induced inflammation and oxidative stress by modulating the intestinal microbiota and its metabolite butyrate in piglets.

Abstract Medical image is an essential tool used in quantitative and qualitative evaluation of different diseases. Medical imaging methods such as fluorescein angiography (FA), optical coherence tomography angiography (OCTA), computed tomography (CT), optical coherence tomography (OCT), and X-ray are used for diagnosis. These imaging modalities suffer from low contrast, which leads to deterioration in the image quality. Consequently, this causes limitation in the usage of medical images in clinical routine and hindered its potential by depriving clinicians from assessing useful information that are needed in disease monitoring, treatment, progression, and decision-making. To overcome this limitation, we propose a novel local transfer function for medical image enhancement algorithm using the pixel neighborhood constraint. The proposed algorithm uses block-wise intensity distribution to generate the regional similarity index. The regional similarity index transformed each centered pixel in the block, to generate a new similarity image. An intuitive optimization algorithm is utilized to optimize the proposed algorithm parameters. Experimentation results show that the proposed LTF-NSI performs better than the state-of-the-art methods and improves the interpretability and perception of the medical images, which can provide clinicians and computer vision program with good quantitative and qualitative information.

Abstract Background Patients with type 2 diabetes mellitus (T2DM) usually have higher blood viscosity attributed to high blood glucose that can decrease blood supply to the pancreas. A mild increase in blood pressure (BP) has been reported as a potential compensatory response that can maintain blood perfusion in the islet. However, how BP influences beta-cell function in T2DM subjects remains inconsistent. This study aimed to examine the relationship between BP and beta-cell function in patients with T2DM under different HbA1c levels. Methods This is a cross-sectional study of 615 T2DM patients, whose clinical data were extracted from hospital medical records. Beta-cell function was assessed by insulin secretion-sensitivity index-2 (ISSI2). Multivariable linear regression analysis and restricted cubic splines (RCS) analysis were performed to identify the association between systolic BP (SBP) and ISSI2. Mediation analysis was performed to determine whether higher SBP could reduce blood glucose by enhancing beta-cell function. Results After adjustment of potential confounders, in participants with HbA1c ≥ 10%, the SBP between 140 to150 mmHg had the highest log ISSI2 (b = 0.227, 95% CI 0.053–0.402), an association specific to participants with

Abstract Aims To explore facilitators and barriers to self-management engagement of Chinese people with poorly controlled type 2 diabetes. Methods Purposive sampling method was used for recruitment. Semi-structured interview and thematic analysis was used for data collection and analysis. Results Twenty-six semi-structured interviews were conducted. Poor blood glucose control introduced awareness of susceptibility to complications, while mental disorders could be concomitant. General knowledge about healthy lifestyle and unhealthy habits impeded lifestyle management. Temporary remission of hyperglycemia and no perceived symptoms interfered engagement of medication therapy and regular blood glucose monitoring. Family and work environments could impact self-management engagement. Accessibility to reliable diabetes-related information influenced self-management engagement. Conclusions Awareness of susceptibility to complications motivated self-management engagement, while the awareness could cause mental disorders that need to be addressed. Customized lifestyle plans and behavior change technologies were crucial for lifestyle management. The progression of diabetes, importance of continuity of medication therapy, and the value of blood glucose monitoring should be clarified in diabetes education. Building diabetes-friendly social environments and providing reliable diabetes-related information were essential.

BackgroundThe evidence from observational studies on the association between the use of aspirin and the risk of hayfever or allergic rhinitis is conflicting, with a dearth of high-quality randomized controlled trials.ObjectiveThis study aims to investigate the causal relationship between aspirin use and the risk of hayfever or allergic rhinitis.MethodsWe conducted a two-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median, and MR-Egger regression methods. We utilized publicly available summary statistics datasets from genome-wide association studies (GWAS) meta-analyses on aspirin use in individuals of European descent (n = 337,159) as the exposure variable, and a GWAS on doctor-diagnosed hayfever or allergic rhinitis in individuals from the UK Biobank (n = 83,529) as the outcome variable.ResultsWe identified 7 single nucleotide polymorphisms (SNPs) at genome-wide significance from the GWASs associated with aspirin use as instrumental variables (P

Medical images are usually degraded by numerous noises during acquisition or transmission, which often causes low contrast leading to deterioration of image quality. As such, medical image denoising and enhancement has become a paramount routine task. To overcome this problem, we propose a cutting-edge joint statistical and morphological model for the denoising and enhancement operation. Firstly, we propose a statistical model in formulating the marginal distribution of the wavelet coefficients. This model is integrated into a Bayesian inference framework to develop a maximum a posterior (MAP) estimator of the noise-free coefficient. Based on the statistical model, we eliminate the need for noise level estimation, and allows the model to automatically adapts to the observed image data. Secondly, we propose an adjustable morphological reconstruction model to eliminate known and unknown noises associated with medical images, while preserving the image details. After these operations, the image is decomposed into several wavelet subbands to extract the illumination and detail components. The image is then reconstructed based on the inverse wavelet to generate the enhanced noise-free image.Experimental results show that the proposed framework obtained high EME values of 41.04, 48.81, 47.81, and 45.75 for OCTA, FFA, CT, and X-ray imaging modalities, and performs better than the state-of-the-art methods. The proposed algorithm can effectively and efficiently enhance medical images, which will assist the clinicians in disease diagnosis, monitoring, and treatment.

Abstract Background Our previous study has identified a novel circRNA (circDIDO1) that is down-regulated in gastric cancer (GC) and significantly inhibits GC progression. The purpose of this study is to identify the molecular mechanism for circDIDO1 and to evaluate the therapeutic effect of circDIDO1 in GC. Methods By combining bioinformatic analysis with RNA sequencing data, we predicted the potential target of circDIDO1 and further validated the regulatory mechanisms for its tumor suppressor function in GC. RIP assay, luciferase reporter assay and in vitro cell function assays were performed to analyze circDIDO1-regulated downstream target genes. For the therapeutic study, circDIDO1-loaded, RGD-modified exosomes (RGD-Exo-circDIDO1) were constructed and its anti-tumor efficacy and biological safety were evaluated in vitro and in vivo. Results CircDIDO1 inhibited GC progression by regulating the expression of the signal transducer inhibitor SOSC2 through sponging miR-1307-3p. Overexpression of circDIDO1 or SOSC2 antagonized the oncogenic role of miR-1307-3p. RGD-Exo-circDIDO1 could efficiently deliver circDIDO1 to increase SOCS2 expression in GC cells. Compared with PBS and RGD-Exo-vector treatment, RGD-Exo-circDIDO1 treatment significantly inhibited the proliferation, migration and invasion of GC cells while promoted cell apoptosis. The therapeutic efficacy of RGD-Exo-circDIDO1 was further confirmed in a mouse xenograft tumor model. In addition, major tissues including the heart, liver, spleen, lungs and kidneys showed no obvious histopathological abnormalities or lesions in the RGD-Exo-circDIDO1 treated group. Conclusion Our findings revealed that circDIDO1 suppressed the progression of GC via modulating the miR-1307-3p/SOSC2 axis. Systemic administration of RGD modified, circDIDO1 loaded exosomes repressed the tumorigenicity and aggressiveness of GC both in vitro and in vivo, suggesting that RGD-Exo-circDIDO1 could be used as a feasible nanomedicine for GC therapy.

Abstract Background Increasing studies suggest that circular RNAs (circRNAs) are critical regulators of cancer development and progression. However, the biological roles and mechanisms of circRNAs in gastric cancer (GC) remain largely unknown. Methods We identified the differentially expressed circRNAs in GC by analyzing Gene Expression Omnibus (GEO) datasets. We explored the biological roles of circRNAs in GC by in vitro functional assays and in vivo animal studies. We performed tagged RNA affinity purification (TRAP), RNA immunoprecipitation (RIP), mass spectrometry (MS), RNA sequencing, luciferase reporter assays, and rescue experiments to investigate the mechanism of circRNAs in GC. Results Downregulated expression of circular RNA EIF4G3 (circEIF4G3; hsa_circ_0007991) was found in GC and was associated with poor clinical outcomes. Overexpression of circEIF4G3 suppressed GC growth and metastasis through the inhibition of β-catenin signaling, whereas knockdown of circEIF4G3 showed the opposite effects. Mechanistic studies revealed that circEIF4G3 bound to δ-catenin protein to promote its TRIM25-mediated ubiquitin degradation and interacted with miR-4449 to upregulate SIK1 expression. Conclusion Our findings uncovered a tumor suppressor function of circEIF4G3 in GC through the regulation of δ-catenin protein stability and miR-4449/SIK1 axis. CircEIF4G3 may act as a promising prognostic biomarker and therapeutic target for GC.

BackgroundElderly people are at high risk of metastatic kidney cancer (KC), and, the bone is one of the most common metastatic sites for metastatic KC. However, studies on diagnostic and prognostic prediction models for bone metastases (BM) in elderly KC patients are still vacant. Therefore, it is necessary to establish new diagnostic and prognostic nomograms.MethodsWe downloaded the data of all KC patients aged more than 65 years during 2010–2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regression analyses were used to study independent risk factors of BM in elderly KC patients. Univariate and multivariate Cox regression analysis for the study of independent prognostic factors in elderly KCBM patients. Survival differences were studied using Kaplan–Meier (K–M) survival analysis. The predictive efficacy and clinical utility of nomograms were assessed by receiver operating characteristic (ROC) curve, the area under curve (AUC), calibration curve, and decision curve analysis (DCA).ResultsA final total of 17,404 elderly KC patients (training set: n = 12,184, validation set: n = 5,220) were included to study the risk of BM. 394 elderly KCBM patients (training set: n = 278, validation set: n = 116) were included to study the overall survival (OS). Age, histological type, tumor size, grade, T/N stage and brain/liver/lung metastasis were identified as independent risk factors for developing BM in elderly KC patients. Surgery, lung/liver metastasis and T stage were identified as independent prognostic factors in elderly KCBM patients. The diagnostic nomogram had AUCs of 0.859 and 0.850 in the training and validation sets, respectively. The AUCs of the prognostic nomogram in predicting OS at 12, 24 and 36 months were: training set (0.742, 0.775, 0.787), and validation set (0.721, 0.827, 0.799), respectively. The calibration curve and DCA also showed excellent clinical utility of the two nomograms.ConclusionTwo new nomograms were constructed and validated to predict the risk of developing BM in elderly KC patients and 12-, 24-, and 36-months OS in elderly KCBM patients. These models can help surgeons provide more comprehensive and personalized clinical management programs for this population.

Adipose tissue plays an important role in systemic energy metabolism, and its dysfunction can lead to severe metabolic disorders. Various cells in adipose tissue communicate with each other to maintain metabolic homeostasis. Extracellular vesicles (EVs) are recognized as novel medium for remote intercellular communication by transferring various bioactive molecules from parental cells to distant target cells. Increasing evidence suggests that the endocrine functions of adipose tissue and even the metabolic homeostasis are largely affected by different cell-derived EVs, such as insulin signaling, lipolysis, and metabolically triggered inflammation regulations. Here, we provide an overview focused on the role of EVs released by different cell types of adipose tissue in metabolic diseases and their possible molecular mechanisms and highlight the potential applications of EVs as biomarkers and therapeutic targets. Moreover, the current EVs-based therapeutic strategies have also been discussed. This trial is registered with NCT05475418.

Despite the high prevalence of gastrointestinal tumors, early diagnosis and treatment of these tumors is limited by the lack of effective and specific biomarkers and therapeutic targets. Exosomes carry active molecules to mediate cell-to-cell communication, especially in the tumor microenvironment, and are promising biomarkers and therapeutic targets for cancer. Circular RNAs (circRNAs) are stably enriched in exosomes and show a unique circular structure, high stability, conservation, and tissue specificity. Exosomal circRNAs play important roles in regulating cell proliferation, metastasis, angiogenesis, metabolism, and the immune microenvironment of gastrointestinal tumors and exhibit great potential as tumor biomarkers and anti-tumor targets or tools. This review briefly introduces the characteristics and functions of circRNAs and exosomes, and systematically describes the biological roles and mechanisms of exosomal circRNAs in gastrointestinal tumors. This article also summarizes the detection methodology of exosomal circRNAs and discusses their clinical significance as biomarkers and targets for gastrointestinal tumors.

The gut microecological network is a complex microbial community within the human body that plays a key role in linking dietary nutrition and host physiology. To understand the complex relationships among microbes and their functions within this community, network analysis has emerged as a powerful tool. By representing the interactions between microbes and their associated omics data as a network, we can gain a comprehensive understanding of the ecological mechanisms that drive the human gut microbiota. In addition, the network-based approach provides a more intuitive analysis of the gut microbiota, simplifying the study of its complex dynamics and interdependencies. This review provides a comprehensive overview of the methods used to construct and analyze networks in the context of gut microecological background. We discuss various types of network modeling approaches, including co-occurrence networks, causal networks, dynamic networks, and multi-omics networks, and describe the analytical techniques used to identify important network properties. We also highlight the challenges and limitations of network modeling in this area, such as data scarcity and heterogeneity, and provide future research directions to overcome these limitations. By exploring these network-based methods, researchers can gain valuable insights into the intricate relationships and functional roles of microbial communities within the gut, ultimately advancing our understanding of the gut microbiota’s impact on human health. [ABSTRACT FROM AUTHOR]

Epithelial malignant transformation and tumorous development were believed to be closely associated with the loss of its microenvironment integrity and homeostasis. The tumor-suppressive molecules Maspin and p53 were demonstrated to play a crucial role in body epithelial and immune homeostasis. Downregulation of Maspin and mutation of p53 were frequently associated with malignant transformation and poor prognosis in various human cancers. In this review, we focused on summarizing the progress of the molecular network of Maspin in studying epithelial tumorous development and its response to clinic treatment and try to clarify the underlying antitumor mechanism. Notably, Maspin expression was reported to be transcriptionally activated by p53, and the transcriptional activity of p53 was demonstrated to be enhanced by its acetylation through inhibition of HDAC1. As an endogenous inhibitor of HDAC1, Maspin possibly potentiates the transcriptional activity of p53 by acetylating the p53 protein. Hereby, it could form a “self-propelling” antitumor mechanism. Thus, we summarized that, upon stimulation of cellular stress and by integrating with p53, the aroused Maspin played the epigenetic surveillant role to prevent the epithelial digressional process and retune the epithelial homeostasis, which is involved in activating host immune surveillance, regulating the inflammatory factors, and fine-tuning its associated cell signaling pathways. Consequentially, in a normal physiological condition, activation of the above “self-propelling” antitumor mechanism of Maspin and p53 could reduce cellular stress (e.g., chronic infection/inflammation, oxidative stress, transformation) effectively and achieve cancer prevention. Meanwhile, designing a strategy of mimicking Maspin’s epigenetic regulation activity with integrating p53 tumor-suppressive activity could enhance the chemotherapy efficacy theoretically in a pathological condition of cancer.

The maturation of wireless connectivity, blockchain (distributed ledger technologies), and intelligent systems has fostered a comprehensive ecosystem for the Internet of Things (IoT). However, the growing volume of data generated by IoT devices creates substantial pressure on blockchain storage and computation capabilities, impeding the further development of the IoT ecosystem. Decentralizing data storage across multiple chains and utilizing cross-chain technology for data exchange eliminates the need for expensive centralized infrastructure, lowers data transfer costs, and improves accessibility. Hence, the issue of computational and storage pressure in blockchain can be improved. Nonetheless, the data of IoT devices are constantly updating, and ensuring consistency for dynamic data across heterogeneous chains remains a significant challenge. To address the aforementioned challenge, we propose a blockchain-based distributed and lightweight data consistency verification model (BDCA), which leverages a batch verification dynamic Merkle hash tree (BV-MHT) and an advanced gamma multi-signature scheme (AGMS) to enable consistent verification of dynamic data while ensuring secure and private data transmission. The AGMS scheme is reliable and robust based on security analysis while the dependability and consistency of BDCA are verified through inductive reasoning. Experimental results indicate that BDCA outperforms CPVPA and Fortress in communication and computation overhead for data preprocessing and auditing in a similar condition, and the AGMS scheme exhibits superior performance when compared to other widely adopted multi-signature schemes such as Cosi, BLS, and RSA. Furthermore, BDCA provides up to 99% data consistency guarantees, demonstrating its practicality.

Abstract Background Circular RNAs (circRNAs) play important roles in cancer development and progression. The purpose of this study is to identify aberrantly expressed circRNAs in gastric cancer (GC), unravel their roles in GC progression, and provide new targets for GC diagnosis and therapy. Methods Bioinformatic analyses were performed to identify the aberrantly expression of hsa_circ_0061137 (termed as circDIDO1) in GC. Gain- and loss-of-function studies were performed to examine the biological roles of circDIDO1 in GC progression. Tagged RNA affinity purification, mass spectrometry, immunofluorescence, co-immunoprecipitation, and Western blot were used to identify circRNA-interacting and circRNA-encoded proteins. RNA sequencing, qRT-PCR, and Western blot were performed to analyze circRNA-regulated downstream target genes and signaling pathways. Mouse tumor models were used to analyze the effects of circDIDO1 on GC growth and metastasis. Results CircDIDO1 was transcribed from human DIDO1 (death-inducer obliterator 1) gene and formed by back-splicing of exons 2–6 of the linear transcript. circDIDO1 was down-regulated in GC tissues and its low levels were associated with larger tumor size, distal metastasis, and poor prognosis. CircDIDO1 overexpression inhibited while knockdown promoted GC cell proliferation, migration and invasion. CircDIDO1 overexpression suppressed GC growth and metastasis in mouse tumor models. Mechanistically, circDIDO1 encoded a novel 529aa protein that directly interacted with poly ADP-ribose polymerase 1 (PARP1) and inhibited its activity. CircDIDO1 also specifically bound to peroxiredoxin 2 (PRDX2) and promoted RBX1-mediated ubiquitination and degradation of PRDX2, which led to the inactivation of its downstream signaling pathways. Conclusions CircDIDO1 is a new circRNA that has tumor suppressor function in GC and it may serve as a potential prognostic biomarker and therapeutic target for GC.