Gut Roseburia is a protective marker for peritoneal metastasis of gastric cancer.

BACKGROUND: Gastric cancer (GC), particularly for advanced stage of GC, commonly undergoes peritoneal metastasis (PM), which is the leading cause of GC-related death. However, there currently has no reliable biomarker to predict the onset of GCPM. It is well known that the imbalance of gut microbiota contributes to the development and metastasis of gastrointestinal tumors. Unfortunately, little is known about how the alternation in gut microbiota is associated with the onset of GCPM. METHODS: Our current study analyzed structural characteristics and functional prediction of gut microbiota in GC patients with PM (PM group) and without PM (non-PM group). Fresh fecal samples were collected from a discovery cohort (PM = 38, non-PM = 54) and a validation cohort (PM = 15, non-PM = 21) of GC patients and their 16S ribosomal RNA (16s rRNA) gene amplicons were sequenced, followed by bioinformatics. RESULTS: The results indicated an increase in the biodiversity of gut microbiota in the non-PM group of the discovery cohort, compared with the PM group. Moreover, LEfSe analysis found 31 significantly different microorganisms, of which the Roseburia ranked the fifth in the random forest (RF) model. The characteristics of intestinal microbiota in GCPM patients were changed, and the abundance of Roseburia in gut microbiota from the GCPM patients was reduced and receiver operating characteristic (ROC) analysis revealed that the reduced abundance of gut Roseburia effectively predicted the onset of GCPM. CONCLUSION: This signature was also observed in the validation cohort. Therefore, Roseburia is a protective microbial marker and the reduced abundance of Roseburia in gut microbiota may help early diagnosis of GCPM.

The Effects of Parental Food Education on Children's Food Literacy: The Mediating Role of Parent-Child Relationship and Learning Motivation.

Parental food education has been recognized among the important factors influencing children's food literacy; however, the intrinsic mechanisms through which this influence occurs are unclear. In this study, a mediation model was constructed to explore this issue, using the parent-child relationship and learning motivation as mediating variables. In total, 204 children, aged 9-14 years old, responded to questionnaires on parental food education, children's food literacy, the parent-child relationship, and learning motivation, which were used to measure the variables of interest. The results showed that parental food education was significantly and positively related to the parent-child relationship, learning motivation, and children's food literacy; the parent-child relationship was significantly and positively related to learning motivation; and learning motivation was significantly and positively related to children's food literacy. Parental food education influenced children's food literacy in the following two main ways: the mediating role of learning motivation and the chain-mediating roles of the parent-child relationship and learning motivation. In addition, we attempt to explore the moderating role of the teaching stage between parental food education and the parent-child relationship, learning motivation, and children's food literacy. In this paper, we discuss possible guidelines for family food education and children's health based on the findings of the current study.

Closed-Loop Control of Macrophage Engineering Enabled by Focused-Ultrasound Responsive Mechanoluminescence Nanoplatform for Precise Cancer Immunotherapy.

Macrophage engineering has emerged as a promising approach for modulating the anti-tumor immune response in cancer therapy. However, the spatiotemporal control and real-time feedback of macrophage regulatory process is still challenging, leading to off-targeting effect and delayed efficacy monitoring therefore raising risk of immune overactivation and serious side effects. Herein, a focused ultrasound responsive immunomodulator-loaded optical nanoplatform (FUSION) is designed to achieve spatiotemporal control and status reporting of macrophage engineering in vivo. Under the stimulation of focused ultrasound (FUS), the immune agonist encapsulated in FUSION can be released to induce selective macrophage M1 phenotype differentiation at tumor site and the near-infrared mechanoluminescence of FUSION is generated simultaneously to indicate the initiation of immune activation. Meanwhile, the persistent luminescence of FUSION is enhanced due to hydroxyl radical generation in the pro-inflammatory M1 macrophages, which can report the effectiveness of macrophage regulation. Then, macrophages labeled with FUSION as a living immunotherapeutic agent (FUSION-M) are utilized for tumor targeting and focused ultrasound activated, immune cell-based cancer therapy. By combining the on-demand activation and feedback to form a closed loop, the nanoplatform in this work holds promise in advancing the controllability of macrophage engineering and cancer immunotherapy for precision medicine.

Identification of toll-like receptor 2 as a key regulator of neuronal apoptosis in vascular dementia by bioinformatics analysis and experimental validation.

BACKGROUND: Vascular dementia (VaD), the second most prevalent type of dementia, lacks a well-defined cause and effective treatment. Our objective was to utilize bioinformatics analysis to discover the fundamental disease-causing genes and pathological mechanisms in individuals diagnosed with VaD. METHODS: To identify potential pathogenic genes associated with VaD, we conducted weighted gene co-expression network analysis (WGCNA), differential expression analysis, and protein-protein interaction (PPI) analysis. The exploration of potential biological mechanisms involved the utilization of Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis. Moreover, a bilateral common carotid artery stenosis (BCAS) mouse model of VaD was established, and the expression of the hub gene, its relationship with cognitive function and its potential pathogenic mechanism were verified by cognitive behavior tests, cerebral blood flow measurement, Western blotting, and immunofluorescence experiments. RESULTS: This study identified 293 DEGs from the brain cortex of VaD patients and healthy controls, among these genes, the Toll-like receptor 2 (TLR2) gene was identified as hub gene, and it was associated with the apoptosis-related pathway PI3K/AKT.The BCAS model demonstrated that the use of TLR2 inhibitors greatly enhanced the cognitive function of the mice (p < 0.05). Additionally, there was a notable decrease in the number of apoptotic cells in the brain cortex of the mice (p < 0.01). Moreover, significant alterations in the levels of proteins related to the PI3K/AKT pathway and cleaved-caspase3 proteins were detected (p < 0.05). CONCLUSIONS: TLR2 plays a role in the pathophysiology of VaD by enhancing the neuronal apoptotic pathway, suggesting it could be a promising therapeutic target.

Therapeutic efficacy of acupuncture point stimulation for stomach cancer pain: a systematic review and meta-analysis.

Purpose: In recent years, traditional Chinese medicine has received widespread attention in the field of cancer pain treatment. This meta-analysis is the first to evaluate the effectiveness and safety of acupuncture point stimulation in the treatment of stomach cancer pain. Methods: For this systematic review and meta-analysis, we searched PubMed, Web of Science, Cochrane Library, Embase, WANFANG, China National Knowledge Infrastructure (CNKI), and Chinese Journal of Science and Technology (VIP) databases as well as forward and backward citations to studies published between database creation to July 27, 2023. All randomized controlled trials (RCTs) on acupuncture point stimulation for the treatment of patients with stomach cancer pain were included without language restrictions. We assessed all outcome indicators of the included trials. The evidence from the randomized controlled trials was synthesized as the standardized mean difference (SMD) of symptom change. The quality of the evidence was assessed using the Cochrane Risk of Bias tool. This study is registered on PROSPERO under the number CRD42023457341. Results: Eleven RCTs were included. The study included 768 patients, split into 2 groups: acupuncture point stimulation treatment group (n = 406), medication control group (n = 372). The results showed that treatment was more effective in the acupuncture point stimulation treatment group than in the medication control group (efficacy rate, RR = 1.63, 95% CI 1.37 to 1.94, p < 0.00001), decreasing in NRS score was greater in acupuncture point stimulation treatment group than in the medication control group (SMD = -1.30, 95% CI -1.96 to -0.63, p < 0.001). Systematic Review Registration: https://clinicaltrials.gov/, identifier CRD42023457341.

Deciphering a Prognostic Signature Based on Soluble Mediators Defines the Immune Landscape and Predicts Prognosis in HNSCC.

BACKGROUND: The study on Head and Neck Squamous Cell Carcinoma (HNSCC), a prevalent and aggressive form of head and neck cancer, focuses on the often-overlooked role of soluble mediators. The objective is to leverage a transcriptome-based risk analysis utilizing soluble mediator-related genes (SMRGs) to provide novel insights into prognosis and immunotherapy efficacy in HNSCC patients. METHODS: We analyzed the expression and prognostic significance of 10,859 SMRGs using 502 HNSCC and 44 normal samples from the TCGA-HNSC cohort in The Cancer Genome Atlas (TCGA). The samples were divided into training and test sets in a 7:3 ratio, with an additional external validation using 40 tumor samples from the International Cancer Genome Consortium (ICGC). Key differentially expressed genes (DEGs) with prognostic significance were identified through univariate and Lasso-Cox regression analyses. A prognostic model based on 20 SMRGs was developed using Lasso and multivariate Cox regression. We assessed the clinical outcomes and immune status in high-risk (HR) and low-risk (LR) HNSCC patients utilizing the BEST databases and single-sample Gene Set Enrichment Analysis (ssGSEA). RESULTS: The 20 SMRGs were crucial in predicting the prognosis of HNSCC, with the SMRG signature emerging as an independent prognostic indicator. Patients classified in the HR group exhibited poorer outcomes compared to those in the LR group. A nomogram, integrating clinical characteristics and risk scores, demonstrated substantial prognostic value. Immunotherapy appeared to be more effective in the LR group, possibly attributed to enhanced immune infiltration and expression of immune checkpoints. CONCLUSIONS: The model based on soluble mediator-associated genes offers a fresh perspective for assessing the pre-immune efficacy and showcases robust predictive capabilities. This innovative approach holds significant promise in advancing the field of precision immuno-oncology research, providing valuable insights for personalized treatment strategies in HNSCC.

Customized Enhancement of Thermal Sensitivity of Tumors at Different Subcutaneous Depths by Multichannel Lanthanide Nanocomposites.

The photothermal therapeutic effect on tumors located at different subcutaneous depths varies due to the attenuation of light by tissue. Here, based on the wavelength-dependent optical attenuation properties of tissues, the tumor depth is assessed using a multichannel lanthanide nanocomposite. A zeolitic imidazolate framework (ZIF-8)-coated nanocomposite is able to deliver high amounts of the hydrophilic heat shock protein 90 inhibitor epigallocatechin gallate through a hydrogen-bonding network formed by the encapsulated highly polarized polyoxometalate guest. It is superior to both bare and PEGylated ZIF-8 for drug delivery. With the assessment of tumor depth and accumulated amount of nanocomposite by fluorescence, an irradiation prescription can be customized to release sufficient HSP90 inhibitor and generate heat for sensitized photothermal treatment of tumors, which not only ensured therapeutic efficacy but also minimized damage to the surrounding tissues.

Unraveling the role of disulfidptosis-related LncRNAs in colon cancer: a prognostic indicator for immunotherapy response, chemotherapy sensitivity, and insights into cell death mechanisms.

Background: Colon cancer, a prevalent and deadly malignancy worldwide, ranks as the third leading cause of cancer-related mortality. Disulfidptosis stress triggers a unique form of programmed cell death known as disulfidoptosis, characterized by excessive intracellular cystine accumulation. This study aimed to establish reliable bioindicators based on long non-coding RNAs (LncRNAs) associated with disulfidptosis-induced cell death, providing novel insights into immunotherapeutic response and prognostic assessment in patients with colon adenocarcinoma (COAD). Methods: Univariate Cox proportional hazard analysis and Lasso regression analysis were performed to identify differentially expressed genes strongly associated with prognosis. Subsequently, a multifactorial model for prognostic risk assessment was developed using multiple Cox proportional hazard regression. Furthermore, we conducted comprehensive evaluations of the characteristics of disulfidptosis response-related LncRNAs, considering clinicopathological features, tumor microenvironment, and chemotherapy sensitivity. The expression levels of prognosis-related genes in COAD patients were validated using quantitative real-time fluorescence PCR (qRT-PCR). Additionally, the role of ZEB1-SA1 in colon cancer was investigated through CCK8 assays, wound healing experiment and transwell experiments. Results: disulfidptosis response-related LncRNAs were identified as robust predictors of COAD prognosis. Multifactorial analysis revealed that the risk score derived from these LncRNAs served as an independent prognostic factor for COAD. Patients in the low-risk group exhibited superior overall survival (OS) compared to those in the high-risk group. Accordingly, our developed Nomogram prediction model, integrating clinical characteristics and risk scores, demonstrated excellent prognostic efficacy. In vitro experiments demonstrated that ZEB1-SA1 promoted the proliferation and migration of COAD cells. Conclusion: Leveraging medical big data and artificial intelligence, we constructed a prediction model for disulfidptosis response-related LncRNAs based on the TCGA-COAD cohort, enabling accurate prognostic prediction in colon cancer patients. The implementation of this model in clinical practice can facilitate precise classification of COAD patients, identification of specific subgroups more likely to respond favorably to immunotherapy and chemotherapy, and inform the development of personalized treatment strategies for COAD patients based on scientific evidence.

GRg1 inhibits the TLR4/NF-kB signaling pathway by upregulating miR-216a-5p to reduce growth factors and inflammatory cytokines in DR.

BACKGROUND: Diabetic retinopathy (DR) is a common diabetic neurodegenerative disease that affects vision in severe cases. Current therapeutic drugs are ineffective for some patients with severe side effects, and ginsenoside-Rg1 (GRg1) has been shown to protect against DR and may serve as a new potential drug for DR. This study aimed to confirm the protective effect of GRg1 against DR and its molecular mechanism. METHODS: Human retinal microvascular endothelial cells (hRMECs) and rats were used to construct DR models in vitro and in vivo. Cell proliferation was detected by BrdU assays, the cell cycle was detected by flow cytometry, and TNF-α, IL-6 and IL-1ß levels were detected by ELISA. qRT‒PCR, Western blotting and immunohistochemistry were used to detect the expression of related genes and proteins, and angiogenesis assays were used to assess angiogenesis. RIP and RNA pull down assays were used to determine the relationship between miR-216a-5p and TLR4; retinal structure and changes were observed by HE staining and retinal digestive spread assays. RESULTS: GRg1 effectively inhibited HG-induced hRMEC proliferation, cell cycle progression and angiogenesis and reduced the levels of intracellular inflammatory cytokines and growth factors. HG downregulated the expression of miR-216a-5p and upregulated the expression of TLR4/NF-kB signaling pathway-related proteins. Importantly, GRg1 inhibited TLR4/NF-kB signaling pathway activation by upregulating miR-216a-5p, thereby inhibiting HG-induced cell proliferation, cell cycle progression, angiogenesis, and the production of inflammatory cytokines and growth factors. In addition, animal experiments confirmed the results of the cell experiments. CONCLUSIONS: GRg1 inhibits TLR4/NF-kB signaling by upregulating miR-216a-5p to reduce growth factors and inflammatory cytokines in DR, providing a potential therapeutic strategy for DR.

The integrated single-cell analysis developed an immunogenic cell death signature to predict lung adenocarcinoma prognosis and immunotherapy.

BACKGROUND: Research on immunogenic cell death (ICD) in lung adenocarcinoma (LUAD) has been relatively limited. This study aims to create ICD-related signatures for accurate survival prognosis prediction in LUAD patients, addressing the challenge of lacking reliable early prognostic indicators for this type of cancer. METHODS: Using single-cell RNA sequencing (scRNA-seq) analysis, ICD activity in cells was calculated by AUCell algorithm, divided into high- and low-ICD groups according to median values, and key ICD regulatory genes were identified through differential analysis, and these genes were integrated into TCGA data to construct prognostic signatures using LASSO and COX regression analysis, and multi-dimensional analysis of ICD-related signatures in terms of prognosis, immunotherapy, tumor microenvironment (TME), and mutational landscape. RESULTS: The constructed signature reveals a pronounced disparity in prognosis between the high- and low-risk groups of LUAD patients. The statistical discrepancies in survival times among LUAD patients from both the TCGA and GEO databases further corroborate this observation. Additionally, heightened levels of immune cell infiltration expression are evidenced in the low-risk group, suggesting a potential benefit from immunotherapeutic interventions for these patients. The expression levels of pivotal risk-associated genes in tissue samples were assessed utilizing qRT-PCR, thereby unveiling PITX3 as a plausible therapeutic target in the context of LUAD. CONCLUSIONS: Our constructed ICD-related signatures provide help in predicting the prognosis and immunotherapy of LUAD patients, and to some extent guide the clinical treatment of LUAD patients.

Deciphering the role of HPV-mediated metabolic regulation in shaping the tumor microenvironment and its implications for immunotherapy in HNSCC.

Head and neck squamous cell carcinoma (HNSCC), as a complex and variable malignancy, poses a significant threat to human health. Since the intricate association between HPV and HNSCC emerged, its role within the TME has garnered extensive attention. HPV+HNSCC exhibits distinct immunological characteristics within the TME, intricately intertwined with mechanisms of immune evasion. HPV employs multifaceted pathways to intervene in metabolic regulation within the TME, exerting influence over immune cell functionality and neoplastic cell genesis. Furthermore, the heightened immune reactivity exhibited by HPV+HNSCC within the TME augments responses to immune interventions such as immune checkpoint inhibitors. Therefore, amidst the current limitations of therapeutic approaches, immunotherapy stands as a promising strategy to overcome the conventional confines of treating HNSCC. This article comprehensively outlines the impact of HPV on the inception and progression of HNSCC while discussing the amalgamation of metabolic regulation within the TME and immunotherapeutic strategies. By intervening in the reciprocal interactions between HPV and HNSCC within the TME, the potential to modulate the efficacy of immune-based treatments becomes evident. Concurrently, a synthesis of pertinent biomarker development is summarized. Such endeavors hold paramount significance for personalized therapeutic approaches and the more effective management of HNSCC patients.

Decoding tumor heterogeneity in uveal melanoma: basement membrane genes as novel biomarkers and therapeutic targets revealed by multi-omics approaches for cancer immunotherapy.

Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients' visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment. Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay. Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments. Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.

M2 macrophage inhibits the antitumor effects of Lenvatinib on intrahepatic cholangiocarcinoma.

Background and objectives: The relationship between the tumor microenvironment and the network of key signaling pathways in cancer plays a key role in the occurrence and development of tumors. Tumor-associated macrophages (TAMs) are important inflammatory cells in the tumor microenvironment and play an important role in tumorigenesis and progression. Macrophages in malignant tumors, mainly the M2 subtype, promote tumor progression by producing cytokines and down-regulating anti-inflammatory immune responses. Several articles have investigated the effect of macrophages on the sensitivity of cancer chemotherapeutic agents, but few such articles have been reported in cholangiocarcinoma, so we investigated the effect of M2 macrophage on the sensitivity of cholangiocarcinoma cells to Lenvatinib compared to M1. Methods: THP-1 monocytes were polarized to M0 macrophage by phorbol 12-myristate 13-acetate (PMA) and then induced to differentiate into M1 and M2 macrophages by LPS, IFN-γ and IL-4 and IL-13, respectively. Macrophages and cholangiocarcinoma cells were co-cultured prior to 24 hours of Lenvatinib administration, cancer cell apoptosis was detected by western-blot, FACS analysis of Annexin V and PI staining. Furthermore, we use xCELLigence RTCA SP Instrument (ACEA Bio-sciences) to monitor cell viability of Lenvatinib administration in co-culture of cholangiocarcinoma cells and macrophages. After tumorigenesis in immunodeficient mice, Lenvatinib was administered, and the effects of M2 on biological characteristics of cholangiocarcinoma cells were investigated by immuno-histochemistry. Results: mRNA and protein expression of M1 and M2 markers confirmed the polarization of THP-1 derived macrophages, which provided a successful and efficient model of monocyte polarization to TAMs. Lenvatinib-induced apoptosis of cholangiocarcinoma cells was significantly reduced when co-cultured with M2 macrophage, whereas apoptosis of cholangiocarcinoma cells co-cultured with M1 macrophage was increased. In the CDX model, Lenvatinib-induced cancer cell apoptosis was markedly reduced, and proliferative cells increased in the presence of M2 macrophages. Angiogenesis related factors was significantly increased in cholangiocarcinoma cells co-cultured with M2. Conclusion: Compared with M1, M2 macrophages can inhibit the anti-tumor effect of Lenvatinib on cholangiocarcinoma through immune regulation, which may be related to the tumor angiogenesis factor effect of M2 macrophage.

Application of diffusion tensor imaging in the diagnosis of post-stroke aphasia: a meta-analysis and systematic review.

Introduction: Diffusion Tensor Imaging (DTI) indicators of different white matter (WM) fibers and brain region lesions for post-stroke aphasia (PSA) are inconsistent in existing studies. Our study examines the consistency and differences between PSA tests performed with DTI. In addition, obtaining consistent and independent conclusions between studies was made possible by utilizing DTI in PSA assessment. Methods: In order to gather relevant studies using DTI for diagnosing PSA, we searched the Web of Science, PubMed, Embase, and CNKI databases. Based on the screening and evaluation of the included studies, the meta-analysis was used to conduct a quantitative analysis. Narrative descriptions were provided for studies that met the inclusion criteria but lacked data. Results: First, we reported on the left hemisphere. The meta-analysis showed that fractional anisotropy (FA) of the arcuate fasciculus (AF) and superior longitudinal fasciculus (SLF), inferior frontal-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), and uncinate fasciculus (UF) were decreased in the PSA group in comparison with the healthy controls (p < 0.00001). However, in the comparison of axial diffusivity (AD), there was no statistically significant difference in white matter fiber tracts in the dual-stream language model of the PSA group. Elevated radial diffusivity (RD) was seen only in the IFOF and ILF (PIFOF = 0.01; PILF = 0.05). In the classic Broca's area, the FA of the PSA group was decreased (p < 0.00001) while the apparent diffusion coefficient was elevated (p = 0.03). Secondly, we evaluated the white matter fiber tracts in the dual-stream language model of the right hemisphere. The FA of the PSA group was decreased only in the IFOF (p = 0.001). AD was elevated in the AF and UF (PAF < 0.00001; PUF = 0.009). RD was elevated in the AF and UF (PAF = 0.01; PUF = 0.003). The other fiber tracts did not undergo similar alterations. Conclusion: In conclusion, DTI is vital for diagnosing PSA because it detects WM changes effectively, but it still has some limitations. Due to a lack of relevant language scales and clinical manifestations, diagnosing and differentiating PSA independently remain challenging. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=365897.

Proposing new early detection indicators for pancreatic cancer: Combining machine learning and neural networks for serum miRNA-based diagnostic model.

Background: Pancreatic cancer (PC) is a lethal malignancy that ranks seventh in terms of global cancer-related mortality. Despite advancements in treatment, the five-year survival rate remains low, emphasizing the urgent need for reliable early detection methods. MicroRNAs (miRNAs), a group of non-coding RNAs involved in critical gene regulatory mechanisms, have garnered significant attention as potential diagnostic and prognostic biomarkers for pancreatic cancer (PC). Their suitability stems from their accessibility and stability in blood, making them particularly appealing for clinical applications. Methods: In this study, we analyzed serum miRNA expression profiles from three independent PC datasets obtained from the Gene Expression Omnibus (GEO) database. To identify serum miRNAs associated with PC incidence, we employed three machine learning algorithms: Support Vector Machine-Recursive Feature Elimination (SVM-RFE), Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest. We developed an artificial neural network model to assess the accuracy of the identified PC-related serum miRNAs (PCRSMs) and create a nomogram. These findings were further validated through qPCR experiments. Additionally, patient samples with PC were classified using the consensus clustering method. Results: Our analysis revealed three PCRSMs, namely hsa-miR-4648, hsa-miR-125b-1-3p, and hsa-miR-3201, using the three machine learning algorithms. The artificial neural network model demonstrated high accuracy in distinguishing between normal and pancreatic cancer samples, with verification and training groups exhibiting AUC values of 0.935 and 0.926, respectively. We also utilized the consensus clustering method to classify PC samples into two optimal subtypes. Furthermore, our investigation into the expression of PCRSMs unveiled a significant negative correlation between the expression of hsa-miR-125b-1-3p and age. Conclusion: Our study introduces a novel artificial neural network model for early diagnosis of pancreatic cancer, carrying significant clinical implications. Furthermore, our findings provide valuable insights into the pathogenesis of pancreatic cancer and offer potential avenues for drug screening, personalized treatment, and immunotherapy against this lethal disease.

An erythrocyte membrane-modified biomimetic synergistic nanosystem for cancer anti-vascular therapy and initial efficacy monitoring.

Tumor vascular disruption has become a promising strategy for cancer therapy in recent decades. Nanocomposites loaded with therapeutic materials and drugs are expected to improve the accuracy of anti-vascular therapy and minimize side effects. However, how to prolong blood circulation of therapeutic nanocomposites for enhanced accumulation in tumor vasculature and how to monitor the initial efficacy of anti-vascular therapy for early evaluation of prognosis remain unsolved. Herein, a biomimetic nanosystem consisting of erythrocyte membrane modified nanocomposites (CMNCs) is developed for cooperation to achieve anti-vascular cancer therapy and initial efficacy monitoring. By utilizing poly(lactic-co-glycolic acid) (PLGA) as the interface material, functional nanomaterials and drug molecules are successfully integrated into CMNCs. The long circulation and immune escape features of the erythrocyte membrane facilitate CMNCs loaded with photothermal agents and chemodrugs to be delivered to the tumor region for anti-vascular treatment. Furthermore, the vascular damage-induced haemorrhage and the following coagulation process is labelled by near infrared emissive CMNCs to indicate the initial therapeutic efficacy of the treatment. This work not only points to a biomimetic strategy for conquering the challenges in anti-vascular cancer therapy, but also provides insights into the biological responses of erythrocyte membrane modified nanocomposites to exploit their biomedical applications.

Trends in innovative pediatric drug development in China based on clinical trial registration data.

In China, the focus of drug research and development has gradually shifted from generic to innovative drugs. Using the Chinese Clinical Trials Registry and Information Transparency Platform, we retrospectively analyzed clinical trials of innovative pediatric drugs conducted in mainland China over the last decade. The goal of this work was to better understand the characteristics of and historical changes in innovative pediatric drug research and development (R&D) in China and to provide effective data support for policy makers and other stakeholders. This study included 198 innovative pediatric drug clinical trials. The data showed that, although some progress has been made in the R&D of innovative pediatric drugs in China, many factors limiting this progress still exist, such as concentrated R&D areas, inadequate pediatric participants, and unbalanced source distributions. The level of innovative pediatric drug R&D in China currently lags behind the global level and has not kept pace with anti-neoplastic drug R&D in China. To promote the innovative development of pediatric drugs in China, the Chinese government must develop an R&D supervision framework, improve the motivation and innovation capabilities of pharmaceutical companies, and optimize the source distribution between regions.

The novel GATA1-interacting protein HES6 is an essential transcriptional cofactor for human erythropoiesis.

Normal erythropoiesis requires the precise regulation of gene expression patterns, and transcription cofactors play a vital role in this process. Deregulation of cofactors has emerged as a key mechanism contributing to erythroid disorders. Through gene expression profiling, we found HES6 as an abundant cofactor expressed at gene level during human erythropoiesis. HES6 physically interacted with GATA1 and influenced the interaction of GATA1 with FOG1. Knockdown of HES6 impaired human erythropoiesis by decreasing GATA1 expression. Chromatin immunoprecipitation and RNA sequencing revealed a rich set of HES6- and GATA1-co-regulated genes involved in erythroid-related pathways. We also discovered a positive feedback loop composed of HES6, GATA1 and STAT1 in the regulation of erythropoiesis. Notably, erythropoietin (EPO) stimulation led to up-regulation of these loop components. Increased expression levels of loop components were observed in CD34+ cells of polycythemia vera patients. Interference by either HES6 knockdown or inhibition of STAT1 activity suppressed proliferation of erythroid cells with the JAK2V617F mutation. We further explored the impact of HES6 on polycythemia vera phenotypes in mice. The identification of the HES6-GATA1 regulatory loop and its regulation by EPO provides novel insights into human erythropoiesis regulated by EPO/EPOR and a potential therapeutic target for the management of polycythemia vera.

MRI-based radiomics for pretreatment prediction of response to concurrent chemoradiotherapy in locally advanced cervical squamous cell cancer.

PURPOSE: To investigate the value of magnetic resonance imaging (MRI)-based radiomics in predicting the treatment response to concurrent chemoradiotherapy (CCRT) in patients with locally advanced cervical squamous cell cancer (LACSC). METHODS: In total, 198 patients (training: n = 138; testing: n = 60) with LACSC treated with CCRT between January 2014 and December 2019 were retrospectively enrolled in this study. Responses were evaluated by MRI and clinical data performed at one month after completion of CCRT according to RECIST standards, and patients were divided into the residual group and nonresidual group. Overall, 200 radiomics features were extracted from T2-weighted imaging and apparent diffusion coefficient maps. The radiomics score (Rad-score) was constructed with a feature selection strategy. Logistic regression analysis was used for multivariate analysis of radiomics features and clinical variables. The performance of all models was assessed using receiver operating characteristic curves. RESULTS: Among the clinical variables, tumor grade and FIGO stage were independent risk factors, and the areas under the curve (AUCs) of the clinical model were 0.741 and 0.749 in the training and testing groups. The Rad-score, consisting of 4 radiomics features selected from 200 radiomics features, showed good predictive performance with an AUC of 0.819 in the training group and 0.776 in the testing group, which were higher than the clinical model, but the difference was not statistically significant. The combined model constructed with tumor grade, FIGO stage, and Rad-score achieved the best performance, with an AUC of 0.857 in the training group and 0.842 in the testing group, which were significantly higher than the clinical model. CONCLUSION: MRI-based radiomics features could be used as a noninvasive biomarker to improve the ability to predict the treatment response to CCRT in patients with LACSC.