An EEG study on artistic and engineering mindsets in students in creative processes.

This study aims to take higher-education students as examples to understand and compare artistic and engineering mindsets in creative processes using EEG. Fifteen Master of Fine Arts (MFA) visual arts and fifteen Master of Engineering (MEng) design engineering students were recruited and asked to complete alternative uses tasks wearing an EEG headset. The results revealed that (1) the engineering-mindset students responded to creative ideas faster than artistic-mindset students. (2) Although in creative processes both artistic- and engineering-mindset students showed Theta, Alpha, and Beta wave activity, the active brain areas are slightly different. The active brain areas of artistic-mindset students in creative processes are mainly in the frontal and occipital lobes; while the whole brain (frontal, oriental, temporal, and occipital lobes) was active in creative processes of engineering-mindset students. (3) During the whole creative process, the brain active level of artistic-mindset students was higher than that of engineering-mindset students. The results of this study fills gaps in existing research where only active brain areas and band waves were compared between artistic- and engineering-mindset students in creative processes. For quick thinking in terms of fluency of generating creative ideas, engineering students have an advantage in comparison to those from the visual arts. Also, the study provided more evidence that mindset can affect the active levels of the brain areas. Finally, this study provides educators with more insights on how to stimulate students' creative ability.

Downregulation of RIP3 ameliorates the left ventricular mechanics and function after myocardial infarction via modulating NF-κB/NLRP3 pathway.

Adverse cardiac mechanical remodeling is critical for the progression of heart failure following myocardial infarction (MI). We previously demonstrated the involvement of RIP3-mediated necroptosis in the loss of functional cardiomyocytes and cardiac dysfunction post-MI. Herein, we investigated the role of RIP3 in NOD-like receptor protein 3 (NLRP3)-mediated inflammation and evaluated the effects of RIP3 knockdown on myocardial mechanics and functional changes after MI. Our findings revealed that mice with MI for 4 weeks exhibited impaired left ventricular (LV) myocardial mechanics, as evidenced by a significant decrease in strain and strain rate in each segment of the LV wall during both systole and diastole. However, RIP3 knockdown ameliorated cardiac dysfunction by improving LV myocardial mechanics not only in the anterior wall but also in other remote nonischemic segments of the LV wall. Mechanistically, knockdown of RIP3 effectively inhibited the activation of the nuclear factor kappa-B (NF-κB)/NLRP3 pathway, reduced the levels of interleukin-1ß (IL-1ß) and interleukin-18 (IL-18) in the heart tissues, and mitigated adverse cardiac remodeling following MI. These results suggest that downregulation of RIP3 holds promise for preventing myocardial inflammation and cardiac mechanical remodeling following MI by regulating the NF-κB/NLRP3 pathway.

A High-Avidity, Thermostable, and Low-Cost Synthetic Capture for Ultrasensitive Detection and Quantification of Viral Antigens and Aerosols.

Lateral flow assays (LFAs) are currently the most popular point-of-care diagnostics, rapidly transforming disease diagnosis from expensive doctor checkups and laboratory-based tests to potential on-the-shelf commodities. Yet, their sensitive element, a monoclonal antibody, is expensive to formulate, and their long-term storage depends on refrigeration technology that cannot be met in resource-limited areas. In this work, LCB1 affibodies (antibody mimetic miniproteins) were conjugated to bovine serum albumin (BSA) to afford a high-avidity synthetic capture (LCB1-BSA) capable of detecting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and virus like particles (VLPs). Substituting the monoclonal antibody 2B04 for LCB1-BSA (stable up to 60 °C) significantly improved the thermal stability, shelf life, and affordability of plasmonic-fluor-based LFAs (p-LFAs). Furthermore, this substitution significantly improved the sensitivity of p-LFAs toward the spike protein and VLPs with precise quantitative ability over 2 and 3 orders of magnitude, respectively. LCB1-BSA sensors could detect VLPs at 100-fold lower concentrations, and this improvement, combined with their robust nature, enabled us to develop an aerosol sampling technology to detect aerosolized viral particles. Synthetic captures like LCB1-BSA can increase the ultrasensitivity, availability, sustainability, and long-term accuracy of LFAs while also decreasing their manufacturing costs.

Pyroptotic macrophages induce disruption of glutamate metabolism in periodontal ligament stem cells contributing to their compromised osteogenic potential.

Macrophage pyroptosis is of key importance to host defence against pathogen infections and may participate in the progression and recovery of periodontitis. However, the role of pyroptotic macrophages in regulating periodontal ligament stem cells (PDLSCs), the main cell source for periodontium renewal, remains unclear. First, we found that macrophage pyroptosis were enriched in gingiva tissues from periodontitis patients compared with those of healthy people through immunofluorescence. Then the effects of pyroptotic macrophages on the PDLSC osteogenic differentiation were investigated in a conditioned medium (CM)-based coculture system in vitro. CM derived from pyroptotic macrophages inhibited the osteogenic differentiation-related gene and protein levels, ALP activity and mineralized nodule formation of PDLSCs. The osteogenic inhibition of CM was alleviated when pyroptosis was inhibited by VX765. Further, untargeted metabolomics showed that glutamate limitation may be the underlying mechanism. However, exogenous glutamate supplementation aggravated the CM-inhibited osteogenic differentiation of PDLSCs. Moreover, CM increased extracellular glutamate and decreased intracellular glutamate levels of PDLSCs, and enhanced the gene and protein expression levels of system xc - (a cystine/glutamate antiporter). After adding cystine to CM-based incubation, the compromised osteogenic potency of PDLSCs was rescued. Our data suggest that macrophage pyroptosis is related to the inflammatory lesions of periodontitis. Either pharmacological inhibition of macrophage pyroptosis or nutritional supplements to PDLSCs, can rescue the compromised osteogenic potency caused by pyroptotic macrophages.

Landscape of tumoral ecosystem for enhanced anti-PD-1 immunotherapy by gut Akkermansia muciniphila.

Gut Akkermansia muciniphila (Akk) has been implicated in impacting immunotherapy or oncogenesis. This study aims to dissect the Akk-associated tumor immune ecosystem (TIME) by single-cell profiling coupled with T cell receptor (TCR) sequencing. We adopted mouse cancer models under anti-PD-1 immunotherapy, combined with oral administration of three forms of Akk, including live Akk, pasteurized Akk (Akk-past), or its membrane protein Amuc_1100 (Amuc). We show that live Akk is most effective in activation of CD8 T cells by rescuing the exhausted type into cytotoxic subpopulations. Remarkably, only live Akk activates MHC-II-pDC pathways, downregulates CXCL3 in Bgn(+)Dcn(+) cancer-associated fibroblasts (CAFs), blunts crosstalk between Bgn(+)Dcn(+) CAFs and PD-L1(+) neutrophils by a CXCL3-PD-L1 axis, and further suppresses the crosstalk between PD-L1(+) neutrophils and CD8 T cells, leading to the rescue of exhausted CD8 T cells. Together, this comprehensive picture of the tumor ecosystem provides deeper insights into immune mechanisms associated with gut Akk-dependent anti-PD-1 immunotherapy.

Clinical significance of small extracellular vesicles in cholangiocarcinoma.

Cholangiocarcinoma is an aggressive and heterogeneous malignancy originating from the bile duct epithelium. It is associated with poor prognosis and high mortality. The global incidence of cholangiocarcinoma is rising, and there is an urgent need for effective early diagnosis and treatment strategies to reduce the burden of this devastating tumor. Small extracellular vesicles, including exosomes and microparticles, are nanoscale vesicles formed by membranes that are released both normally and pathologically from cells, mediating the intercellular transfer of substances and information. Recent studies have demonstrated the involvement of small extracellular vesicles in numerous biological processes, as well as the proliferation, invasion, and metastasis of tumor cells. The present review summarizes the tumorigenic roles of small extracellular vesicles in the cholangiocarcinoma microenvironment. Owing to their unique composition, accessibility, and stability in biological fluids, small extracellular vesicles have emerged as ideal biomarkers for use in liquid biopsies for diagnosing and outcome prediction of cholangiocarcinoma. Specific tissue tropism, theoretical biocompatibility, low clearance, and strong biological barrier penetration of small extracellular vesicles make them suitable drug carriers for cancer therapy. Furthermore, the potential value of small extracellular vesicle-based therapies for cholangiocarcinoma is also reviewed.

Exosome secretion related gene signature predicts chemoresistance in patients with colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a highly heterogeneous malignancy, and patients often have different responses to treatment. In this study, the genetic characteristics related to exosome formation and secretion procedure were used to predict chemoresistance and guide the individualized treatment of patients. METHODS: Firstly, seven microarray datasets in Gene Expression Omnibus (GEO) and RNA-Seq dataset from the Cancer Genome Atlas (TCGA) were used to analysis the transcriptome profiles and associated characteristics of CRC patients. Then, a predictive model based on gene features linked to exosome formation and secretion was created and validated using Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) machine learning. Finally, we evaluated the model using chemoresistant/chemosensitive cells and tissues by immunofluorescence (IF), western blot (WB), quantitative real-time PCR (qRT-PCR) and immunocytochemistry (IHC) experiments, and the predictive value of integrated model in the clinical validation cohort were performed by Receiver Operating Characteristic (ROC) and Kaplan-Meier (K-M) curves analyses. RESULTS: We established a risk score signature based on three genes related to exosome secretion in CRC. Better Overall Survival (OS) and greater chemosensitivity were seen in the low-risk group, whereas the high-risk group exhibited chemoresistance and a subpar response to immune checkpoint blockade (ICB) therapy. Higher expression of the model genes EXOC2, EXOC3 and STX4 were observed in chemoresistant cells and specimens. The AUC of 5-year disease-free survival (DFS) was 0.804. Compared with that in the low-risk group, patients' DFS was found to be significantly worse in the high-risk group. CONCLUSIONS: In summary, the gene signature related to exosome formation and secretion could reliably predict patients' chemosensitivity and ICB treatment response, which providing new independent biomarkers for the treatment of CRC.

Advancing Dermatological Diagnostics: Interpretable AI for Enhanced Skin Lesion Classification.

A crucial challenge in critical settings like medical diagnosis is making deep learning models used in decision-making systems interpretable. Efforts in Explainable Artificial Intelligence (XAI) are underway to address this challenge. Yet, many XAI methods are evaluated on broad classifiers and fail to address complex, real-world issues, such as medical diagnosis. In our study, we focus on enhancing user trust and confidence in automated AI decision-making systems, particularly for diagnosing skin lesions, by tailoring an XAI method to explain an AI model's ability to identify various skin lesion types. We generate explanations using synthetic images of skin lesions as examples and counterexamples, offering a method for practitioners to pinpoint the critical features influencing the classification outcome. A validation survey involving domain experts, novices, and laypersons has demonstrated that explanations increase trust and confidence in the automated decision system. Furthermore, our exploration of the model's latent space reveals clear separations among the most common skin lesion classes, a distinction that likely arises from the unique characteristics of each class and could assist in correcting frequent misdiagnoses by human professionals.

The heterogeneity of tumour-associated macrophages contributes to the clinical outcomes and indications for immune checkpoint blockade in colorectal cancer patients.

Tumor-associated macrophages (TAMs), one of the major immune cell types in colorectal cancer (CRC) tumor microenvironment (TME), play indispensable roles in immune responses against tumor progression. In this study, we aimed to know whether the extensive inter and intra heterogeneity of TAMs contributes to the clinical outcomes and indications for immune checkpoint blockade (ICB) in CRC. We used single-cell RNA sequencing (scRNA-Seq) data from 60 CRC patients and charactrized TAMs based on anatomic locations, tumor regions, stages, grades, metastatic status, MSS/MSI classification and pseudotemporal differentiation status. We then defined a catalog of 21 gene modules that determine macrophage status, and identified 7 of them as relevant to clinical outcomes and 11 as indications for ICB therapy. On this basis, we constructed a unique TAM subgroup profile, aiming to find features that may be highly responsive to immunotherapy for the CRC with poor prognosis under conventional treatment. This TAM subpopulation is enriched in tumors and is associated with poor prognosis, but exhibits a high immunotherapy response signature (HIM TAM). Further spatial transcriptome analysis and ligand-receptor interaction analysis confirmed that HIM TAM is involved in shaping TIME, especially the regulation of T cells. Our study provides insights into different TAM subtypes, highlights the importance of TAM heterogeneity in relation to patient prognosis and immunotherapy response, and reveals potential immunotherapy strategies based on TAM characteristics for CRC that does not respond well to conventional therapy.

Computed tomography radiogenomics: A potential tool for prediction of molecular subtypes in gastric stromal tumor.

BACKGROUND: Preoperative knowledge of mutational status of gastrointestinal stromal tumors (GISTs) is essential to guide the individualized precision therapy. AIM: To develop a combined model that integrates clinical and contrast-enhanced computed tomography (CE-CT) features to predict gastric GISTs with specific genetic mutations, namely KIT exon 11 mutations or KIT exon 11 codons 557-558 deletions. METHODS: A total of 231 GIST patients with definitive genetic phenotypes were divided into a training dataset and a validation dataset in a 7:3 ratio. The models were constructed using selected clinical features, conventional CT features, and radiomics features extracted from abdominal CE-CT images. Three models were developed: ModelCT sign, modelCT sign + rad, and model CTsign + rad + clinic. The diagnostic performance of these models was evaluated using receiver operating characteristic (ROC) curve analysis and the Delong test. RESULTS: The ROC analyses revealed that in the training cohort, the area under the curve (AUC) values for modelCT sign, modelCT sign + rad, and modelCT sign + rad + clinic for predicting KIT exon 11 mutation were 0.743, 0.818, and 0.915, respectively. In the validation cohort, the AUC values for the same models were 0.670, 0.781, and 0.811, respectively. For predicting KIT exon 11 codons 557-558 deletions, the AUC values in the training cohort were 0.667, 0.842, and 0.720 for modelCT sign, modelCT sign + rad, and modelCT sign + rad + clinic, respectively. In the validation cohort, the AUC values for the same models were 0.610, 0.782, and 0.795, respectively. Based on the decision curve analysis, it was determined that the modelCT sign + rad + clinic had clinical significance and utility. CONCLUSION: Our findings demonstrate that the combined modelCT sign + rad + clinic effectively distinguishes GISTs with KIT exon 11 mutation and KIT exon 11 codons 557-558 deletions. This combined model has the potential to be valuable in assessing the genotype of GISTs.

Neoadjuvant and/or adjuvant chemotherapy for gastric cancer patients with microsatellite instability or deficient mismatch repair: a systematic review and meta-analysis study protocol.

INTRODUCTION: Whether gastric cancer (GC) patients with deficient mismatch repair or microsatellite instability-high (dMMR/MSI-H) benefit from perioperative (neoadjuvant and/or adjuvant) chemotherapy is controversial. This protocol delineates the planned scope and methods for a systematic review and meta-analysis that aims to compare the efficacy of perioperative chemotherapy with surgery alone in resectable dMMR/MSI-H GC patients. METHODS AND ANALYSIS: This study protocol is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols-P guideline. PubMed, Embase, Cochrane (CENTRAL), and the Web of Science databases will be searched, supplemented by a secondary screening of relevant records. Both randomised controlled trials and non-randomised studies will be included in this study. The primary and secondary outcomes under scrutiny will be overall survival, disease-free survival and progression-free survival. Two reviewers will independently screen studies, extract data and assess the risk of bias. We will analyse different treatment settings (eg, neoadjuvant or adjuvant or combined as perioperative chemotherapies) separately and conduct sensitivity analyses. ETHICS AND DISSEMINATION: No ethics approval is required for this systematic review and meta-analysis, as no individual patient data will be collected. The findings of our study will be published in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42023494276.

Harnessing Mechanical Stress with Viscoelastic Biomaterials for Periodontal Ligament Regeneration.

The viscoelasticity of mechanically sensitive tissues such as periodontal ligaments (PDLs) is key in maintaining mechanical homeostasis. Unfortunately, PDLs easily lose viscoelasticity (e.g., stress relaxation) during periodontitis or dental trauma, which disrupt cell-extracellular matrix (ECM) interactions and accelerates tissue damage. Here, Pluronic F127 diacrylate (F127DA) hydrogels with PDL-matched stress relaxation rates and high elastic moduli are developed. The hydrogel viscoelasticity is modulated without chemical cross-linking by controlling precursor concentrations. Under cytomechanical loading, F127DA hydrogels with fast relaxation rates significantly improved the fibrogenic differentiation potential of PDL stem cells (PDLSCs), while cells cultured on F127DA hydrogels with various stress relaxation rates exhibited similar fibrogenic differentiation potentials with limited cell spreading and traction forces under static conditions. Mechanically, faster-relaxing F127DA hydrogels leveraged cytomechanical loading to activate PDLSC mechanotransduction by upregulating integrin-focal adhesion kinase pathway and thus cytoskeletal rearrangement, reinforcing cell-ECM interactions. In vivo experiments confirm that faster-relaxing F127DA hydrogels significantly promoted PDL repair and reduced abnormal healing (e.g., root resorption and ankyloses) in delayed replantation of avulsed teeth. This study firstly investigated how matrix nonlinear viscoelasticity influences the fibrogenesis of PDLSCs under mechanical stimuli, and it reveals the underlying mechanobiology, which suggests novel strategies for PDL regeneration.

Modeling the extracellular matrix in cell migration and morphogenesis: a guide for the curious biologist.

The extracellular matrix (ECM) is a highly complex structure through which biochemical and mechanical signals are transmitted. In processes of cell migration, the ECM also acts as a scaffold, providing structural support to cells as well as points of potential attachment. Although the ECM is a well-studied structure, its role in many biological processes remains difficult to investigate comprehensively due to its complexity and structural variation within an organism. In tandem with experiments, mathematical models are helpful in refining and testing hypotheses, generating predictions, and exploring conditions outside the scope of experiments. Such models can be combined and calibrated with in vivo and in vitro data to identify critical cell-ECM interactions that drive developmental and homeostatic processes, or the progression of diseases. In this review, we focus on mathematical and computational models of the ECM in processes such as cell migration including cancer metastasis, and in tissue structure and morphogenesis. By highlighting the predictive power of these models, we aim to help bridge the gap between experimental and computational approaches to studying the ECM and to provide guidance on selecting an appropriate model framework to complement corresponding experimental studies.

Activation of the FOXM1/ASF1B/PRDX3 axis confers hyperproliferative and antioxidative stress reactivity to gastric cancer.

Nucleosome assembly during DNA replication is dependent on histone chaperones. Recent studies suggest that dysregulated histone chaperones contribute to cancer progression, including gastric cancer (GC). Further studies are required to explore the prognostic and therapeutic implications of histone chaperones and their mechanisms of action in GC progression. Here we identified histone chaperone ASF1B as a potential biomarker for GC proliferation and prognosis. ASF1B was significantly upregulated in GC, which was associated with poor prognosis. In vitro and in vivo experiments demonstrated that the inhibition of ASF1B suppressed the malignant characteristics of GC, while overexpression of ASF1B had the opposite effect. Mechanistically, transcription factor FOXM1 directly bound to the ASF1B-promoter region, thereby regulating its transcription. Treatment with thiostrepton, a FOXM1 inhibitor, not only suppressed ASF1B expression, but also inhibited GC progression. Furthermore, ASF1B regulated the mitochondrial protein peroxiredoxin 3 (PRDX3) transcription in a FOXM1-dependent manner. The crucial role of ASF1B-regulated PRDX3 in GC cell proliferation and oxidative stress balance was also elucidated. In summary, our study suggests that the FOXM1-ASF1B-PRDX3 axis is a potential therapeutic target for treating GC.

Examining arterial pulsation to identify and risk-stratify heart failure subjects with deep neural network.

Hemodynamic parameters derived from pulse wave analysis have been shown to predict long-term outcomes in patients with heart failure (HF). Here we aimed to develop a deep-learning based algorithm that incorporates pressure waveforms for the identification and risk stratification of patients with HF. The first study, with a case-control study design to address data imbalance issue, included 431 subjects with HF exhibiting typical symptoms and 1545 control participants with no history of HF (non-HF). Carotid pressure waveforms were obtained from all the participants using applanation tonometry. The HF score, representing the probability of HF, was derived from a one-dimensional deep neural network (DNN) model trained with characteristics of the normalized carotid pressure waveform. In the second study of HF patients, we constructed a Cox regression model with 83 candidate clinical variables along with the HF score to predict the risk of all-cause mortality along with rehospitalization. To identify subjects using the HF score, the sensitivity, specificity, accuracy, F1 score, and area under receiver operating characteristic curve were 0.867, 0.851, 0.874, 0.878, and 0.93, respectively, from the hold-out cross-validation of the DNN, which was better than other machine learning models, including logistic regression, support vector machine, and random forest. With a median follow-up of 5.8 years, the multivariable Cox model using the HF score and other clinical variables outperformed the other HF risk prediction models with concordance index of 0.71, in which only the HF score and five clinical variables were independent significant predictors (p < 0.05), including age, history of percutaneous coronary intervention, concentration of sodium in the emergency room, N-terminal pro-brain natriuretic peptide, and hemoglobin. Our study demonstrated the diagnostic and prognostic utility of arterial waveforms in subjects with HF using a DNN model. Pulse wave contains valuable information that can benefit the clinical care of patients with HF.

Development and validation of a prospective study to predict the risk of readmission within 365 days of respiratory failure: based on a random survival forest algorithm combined with COX regression modeling.

BACKGROUND: There is a need to develop and validate a widely applicable nomogram for predicting readmission of respiratory failure patients within 365 days. METHODS: We recruited patients with respiratory failure at the First People's Hospital of Yancheng and the People's Hospital of Jiangsu. We used the least absolute shrinkage and selection operator regression to select significant features for multivariate Cox proportional hazard analysis. The Random Survival Forest algorithm was employed to construct a model for the variables that obtained a coefficient of 0 following LASSO regression, and subsequently determine the prediction score. Independent risk factors and the score were used to develop a multivariate COX regression for creating the line graph. We used the Harrell concordance index to quantify the predictive accuracy and the receiver operating characteristic curve to evaluate model performance. Additionally, we used decision curve analysiso assess clinical usefulness. RESULTS: The LASSO regression and multivariate Cox regression were used to screen hemoglobin, diabetes and pneumonia as risk variables combined with Score to develop a column chart model. The C index is 0.927 in the development queue, 0.924 in the internal validation queue, and 0.922 in the external validation queue. At the same time, the predictive model also showed excellent calibration and higher clinical value. CONCLUSIONS: A nomogram predicting readmission of patients with respiratory failure within 365 days based on three independent risk factors and a jointly developed random survival forest algorithm has been developed and validated. This improves the accuracy of predicting patient readmission and provides practical information for individualized treatment decisions.

Extraction, structural characterization and immunoactivity of glucomannan type polysaccahrides from Lilium brownii var. viridulum Baker.

Homogeneous polysaccharide (LBP) was extracted and purified from the bulblets of Lilium brownii var. viridulum Baker with a molecular weight of 312 kDa. The monosaccharides are composed of mannose and glucose, and the corresponding molar ratios are 0.582 and 0.418, respectively. FT-IR, LC-MS, NMR, GC-MS and HPAEC were used to analyze the functional groups, glycosidic linkages and chemical structure of LBP, which was a 1-4-linked glucomannan and contained a dodecasaccharide repeating units of →4)-ß-D-Manp-(1 â†’ 4)-ß-D-Manp-(1 â†’ 4)-ß-D-Manp-(1 â†’ 4)-ß-D-Glcp-(1 â†’ 4)-ß-D-Manp-(1 â†’ 4)-ß-D-Manp-(1 â†’ 4)-ß-D-Glcp-(1 â†’ 4)-α-D-Glcp-(1 â†’ 4)-ß-D-Glcp-(1 â†’ 4)-ß-D-Glcp-(1 â†’ 4)-ß-D-Manp-(1 â†’ 4)-ß-D-Manp-(1 â†’ . In vitro experimental results showed that LBP had noble biocompatibility, and a low dose of 5 µg/mL LBP significantly up-regulated the mRNA expression of TNF-α, iNOS, IL-6, IL-1ß and Toll-like receptors family (TLRs) in RAW 264.7 cells. In conclusion, LBP played an important role in immunomodulation, and further studies on the specific immunomodulatory mechanisms of LBP on RAW 264.7 cells are still needed.