The characteristics of intratumoral microbial community reflect the development of lung adenocarcinoma.

Introduction: An increasing number of studies have demonstrated the pivotal role of microbiota changes in the onset, progression, diagnosis, treatment, and prognosis of lung adenocarcinoma (LUAD). However, a comprehensive analysis of intratumoral microbiome variation across distinct LUAD stages has not been performed. The aim of this study was to identify the microbial markers that significantly vary during tumor stage of LUAD. Methods: Here, we used the cancer genome atlas (TCGA) database to comprehensively compare and analyze the differences in microbial composition between 267 patients with early and 224 patients with advanced LUAD. In order to determine the best biomarkers, we used the random forest (RF) model and found that the microbial markers have a certain ability in predicting the stage of LUAD. Results: We found that there were certain differences in the microbiome of patients with LUAD at different stages, especially in the tumor tissues of patients with advanced LUAD, whose co-abundance network was significantly more complex. We also found that five bacterial biomarkers (Pseudoalteromonas, Luteibacter, Caldicellulosiruptor, Loktanella, and Serratia) were correlated with LUAD stage, among which Pseudoalteromonas, Luteibacter, Caldicellulosiruptor, and Serratia were significantly overexpressed in patients with advanced LUAD. In particular, after integrating the biomarkers of mRNA, we achieved an area under the curve (AUC) of 0.70. Discussion: Our study revealed the microbial profile of patients with LUAD and the intrinsic pathogenic mechanism between the microbiome and the disease, and established a multi-omics model to determine LUAD tumor stage.

Logic-Based Strategy for Spatiotemporal Release of Dual Extracellular Vesicles in Osteoarthritis Treatment.

To effectively treat osteoarthritis (OA), the existing inflammation must be reduced before the cartilage damage can be repaired; this cannot be achieved with a single type of extracellular vesicles (EVs). Here, a hydrogel complex with logic-gates function is proposed that can spatiotemporally controlled release two types of EVs: interleukin 10 (IL-10)+ EVs to promote M2 polarization of macrophage, and SRY-box transcription factor 9 (SOX9)+ EVs to increase cartilage matrix synthesis. Following dose-of-action screening, the dual EVs are loaded into a matrix metalloporoteinase 13 (MMP13)-sensitive self-assembled peptide hydrogel (KM13E) and polyethylene glycol diacrylate/gelatin methacryloyl-hydrogel microspheres (PGE), respectively. These materials are mixed to form a "microspheres-in-gel" KM13E@PGE system. In vitro, KM13E@PGE abruptly released IL-10+ EVs after 3 days and slowly released SOX9+ EVs for more than 30 days. In vivo, KM13E@PGE increased the CD206+ M2 macrophage proportion in the synovial tissue and decreased the tumor necrosis factor-α and IL-1ß levels. The aggrecan and SOX9 expressions in the cartilage tissues are significantly elevated following inflammation subsidence. This performance is not achieved using anti-inflammatory or cartilage repair therapy alone. The present study provides an injectable, integrated delivery system with spatiotemporal control release of dual EVs, and may inspire logic-gates strategies for OA treatment.

FOXF1 reverses lung fibroblasts transdifferentiation via inhibiting TGF-ß/SMAD2/3 pathway in silica-induced pulmonary fibrosis.

Silicosis is one of the most common and severe types of pneumoconiosis and is characterized by lung dysfunction, persistent lung inflammation, pulmonary nodule formation, and irreversible pulmonary fibrosis. The transdifferentiation of fibroblasts into myofibroblasts is one of the main reasons for the exacerbation of silicosis. However, the underlying mechanism of transcription factors regulating silicosis fibrosis has not been clarified. The aim of this study was to investigate the potential mechanism of transcription factor FOXF1 in fibroblast transdifferentiation in silica-induced pulmonary fibrosis. Therefore, a silicosis mouse model was established, and we found that FOXF1 expression level was significantly down-regulated in the silicosis group, and after overexpression of FOXF1 by adeno-associated virus (AAV), FOXF1 expression level was up-regulated, and silicosis fibrosis was alleviated. In order to further explore the specific regulatory mechanism of FOXF1 in silicosis, we established a fibroblasts transdifferentiation model induced by TGF-ß in vitro. In the model, the expression levels of SMAD2/3 and P-SMAD2/3 were up-regulated, but the expression levels of SMAD2/3 and P-SMAD2/3 were down-regulated, inhibiting transdifferentiation and accumulation of extracellular matrix after the overexpressed FOXF1 plasmid was constructed. However, after silencing FOXF1, the expression levels of SMAD2/3 and P-SMAD2/3 were further up-regulated, aggravating transdifferentiation and accumulation of extracellular matrix. These results indicate that the activation of FOXF1 in fibroblasts can slow down the progression of silicosis fibrosis by inhibiting TGF-ß/SMAD2/3 classical pathway, which provides a new idea for further exploration of silicosis treatment.

Understanding Heterogeneity in Individual Responses to Digital Lifestyle Intervention Through Self-Monitoring Adherence Trajectories in Adults With Overweight or Obesity: Secondary Analysis of a 6-Month Randomized Controlled Trial.

BACKGROUND: Achieving clinically significant weight loss through lifestyle interventions for obesity management is challenging for most individuals. Improving intervention effectiveness involves early identification of intervention nonresponders and providing them with timely, tailored interventions. Early and frequent self-monitoring (SM) adherence predicts later weight loss success, making it a potential indicator for identifying nonresponders in the initial phase. OBJECTIVE: This study aims to identify clinically meaningful participant subgroups based on longitudinal adherence to SM of diet, activity, and weight over 6 months as well as psychological predictors of participant subgroups from a self-determination theory (SDT) perspective. METHODS: This was a secondary data analysis of a 6-month digital lifestyle intervention for adults with overweight or obesity. The participants were instructed to perform daily SM on 3 targets: diet, activity, and weight. Data from 50 participants (mean age: 53.0, SD 12.6 y) were analyzed. Group-based multitrajectory modeling was performed to identify subgroups with distinct trajectories of SM adherence across the 3 SM targets. Differences between subgroups were examined for changes in clinical outcomes (ie, body weight, hemoglobin A1c) and SDT constructs (ie, eating-related autonomous motivation and perceived competence for diet) over 6 months using linear mixed models. RESULTS: Two distinct SM trajectory subgroups emerged: the Lower SM group (21/50, 42%), characterized by all-around low and rapidly declining SM, and the Higher SM group (29/50, 58%), characterized by moderate and declining diet and weight SM with high activity SM. Since week 2, participants in the Lower SM group exhibited significantly lower levels of diet (P=.003), activity (P=.002), and weight SM (P=.02) compared with the Higher SM group. In terms of clinical outcomes, the Higher SM group achieved a significant reduction in body weight (estimate: -6.06, SD 0.87 kg; P<.001) and hemoglobin A1c (estimate: -0.38, SD 0.11%; P=.02), whereas the Lower SM group exhibited no improvements. For SDT constructs, both groups maintained high levels of autonomous motivation for over 6 months. However, the Lower SM group experienced a significant decline in perceived competence (P=.005) compared with the Higher SM group, which maintained a high level of perceived competence throughout the intervention (P=.09). CONCLUSIONS: The presence of the Lower SM group highlights the value of using longitudinal SM adherence trajectories as an intervention response indicator. Future adaptive trials should identify nonresponders within the initial 2 weeks based on their SM adherence and integrate intervention strategies to enhance perceived competence in diet to benefit nonresponders. TRIAL REGISTRATION: ClinicalTrials.gov NCT05071287; https://clinicaltrials.gov/study/NCT05071287. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1016/j.cct.2022.106845.

SIRT3 and SIRT4 double-genes remodeled the mitochondrial network to induce hepatocellular carcinoma cell line differentiation and suppress malignant phenotypes.

Tumor cells with damaged mitochondria undergo metabolic reprogramming, but gene therapy targeting mitochondria has not been comprehensively reported. In this study, plasmids targeting the normal hepatocyte cell line (L-O2) and hepatocellular carcinoma cell line were generated using three genes SIRT3, SIRT4, and SIRT5. These deacetylases play a variety of regulatory roles in cancer and are related to mitochondrial function. Compared with L-O2, SIRT3 and SIRT4 significantly ameliorated mitochondrial damage in HCCLM3, Hep3B and HepG2 cell lines and regulated mitochondrial biogenesis and mitophagy, respectively. We constructed double-gene plasmid for co-express SIRT3 and SIRT4 using the internal ribosome entry site (IRES). The results indicated that the double-gene plasmid effectively expressed SIRT3 and SIRT4, significantly improved mitochondrial quality and function, and reduced mtDNA level and oxidative stress in HCC cells. MitoTracker analysis revealed that the mitochondrial network was restored. The proliferation, migration capabilities of HCC cells were reduced, whereas their differentiation abilities were enhanced. This study demonstrated that the use of IRES-linked SIRT3 and SIRT4 double-gene vectors induced the differentiation of HCC cells and inhibited their development by ameliorating mitochondrial dysfunction. This intervention helped reverse metabolic reprogramming, and may provide a groundbreaking new framework for HCC treatment.

Sonography-based multimodal information platform for identifying the surgical pathology of ductal carcinoma in situ.

BACKGROUND: The risk of ductal carcinoma in situ (DCIS) identified by biopsy often increases during surgery. Therefore, confirming the DCIS grade preoperatively is necessary for clinical decision-making. PURPOSE: To train a three-classification deep learning (DL) model based on ultrasound (US), combining clinical data, mammography (MG), US, and core needle biopsy (CNB) pathology to predict low-grade DCIS, intermediate-to-high-grade DCIS, and upstaged DCIS. MATERIALS AND METHODS: Data of 733 patients with 754 DCIS cases confirmed by biopsy were retrospectively collected from May 2013 to June 2022 (N1), and other data (N2) were confirmed by biopsy as low-grade DCIS. The lesions were randomly divided into training (n=471), validation (n=142), and test (n = 141) sets to establish the DCIS-Net. Information on the DCIS-Net, clinical (age and sign), US (size, calcifications, type, breast imaging reporting and data system [BI-RADS]), MG (microcalcifications, BI-RADS), and CNB pathology (nuclear grade, architectural features, and immunohistochemistry) were collected. Logistic regression and random forest analyses were conducted to develop Multimodal DCIS-Net to calculate the specificity, sensitivity, accuracy, receiver operating characteristic curve, and area under the curve (AUC). RESULTS: In the test set of N1, the accuracy and AUC of the multimodal DCIS-Net were 0.752-0.766 and 0.859-0.907 in the three-classification task, respectively. The accuracy and AUC for discriminating DCIS from upstaged DCIS were 0.751-0.780 and 0.829-0.861, respectively. In the test set of N2, the accuracy and AUC of discriminating low-grade DCIS from upstaged low-grade DCIS were 0.769-0.987 and 0.818-0.939, respectively. DL was ranked from one to five in the importance of features in the multimodal-DCIS-Net. CONCLUSION: By developing the DCIS-Net and integrating it with multimodal information, diagnosing low-grade DCIS, intermediate-to high-grade DCIS, and upstaged DCIS is possible. It can also be used to distinguish DCIS from upstaged DCIS and low-grade DCIS from upstaged low-grade DCIS, which could pave the way for the DCIS clinical workflow.

An artificial intelligence model based on transrectal ultrasound images of biopsy needle tract tissues to differentiate prostate cancer.

PURPOSE: We aimed to develop an artificial intelligence (AI) model based on transrectal ultrasonography (TRUS) images of biopsy needle tract (BNT) tissues for predicting prostate cancer (PCa) and to compare the PCa diagnostic performance of the radiologist model and clinical model. METHODS: A total of 1696 2D prostate TRUS images were involved from 142 patients between July 2021 and May 2022. The ResNet50 network model was utilized to train classification models with different input methods: original image (Whole model), BNT (Needle model), and combined image [Feature Pyramid Networks (FPN) model]. The training set, validation set, and test set were randomly assigned, then randomized 5-fold cross-validation between the training set and validation set was performed. The diagnostic effectiveness of AI models and image combination was accessed by an independent testing set. Then, the optimal AI model and image combination were selected to compare the diagnostic efficacy with that of senior radiologists and the clinical model. RESULTS: In the test set, the area under the curve, specificity, and sensitivity of the FPN model were 0.934, 0.966, and 0.829, respectively; the diagnostic efficacy was improved compared with the Whole and Needle models, with statistically significant differences (P < 0.05), and was better than that of senior radiologists (area under the curve: 0.667). The FPN model detected more PCa compared with senior physicians (82.9% vs. 55.8%), with a 61.3% decrease in the false-positive rate and a 23.2% increase in overall accuracy (0.887 vs. 0.655). CONCLUSION: The proposed FPN model can offer a new method for prostate tissue classification, improve the diagnostic performance, and may be a helpful tool to guide prostate biopsy.

Combination of Breast Ultrasound With Magnetic Resonance Imaging in the Diagnosis of Non-mass-like Breast Lesions Detected on Ultrasound: A New Integrated Strategy to Improve Diagnostic Performance.

OBJECTIVE: The aim of the work described here was to evaluate the diagnostic performance of a new integrated strategy using breast ultrasound (US) combined with magnetic resonance imaging (MRI) to differentiate benign and malignant breast non-mass-like lesions (NMLs) detected on US. METHODS: From October 2017 to January 2021, 183 NMLs detected on US that had undergone MRI examinations were included in this respective study. Pathological results were used as the reference standard. The integrated diagnostic strategy of breast US combined with MRI based on a combination of MRI Breast Imaging Reporting and Data System (BI-RADS) with discriminant sonographic indicators highly associated with malignancy was established and validated in a cohort of 61 women. The diagnostic performances of US, MRI and the combined method were calculated and compared. RESULTS: In the training set, the area under the receiver operating characteristic curve (AUC), sensitivity and specificity of US, MRI and the integrated diagnostic strategy using US combined with MRI for NMLs were 0.730, 93.7% and 52.3%; 0.849, 94.7% and 75.0%; and 0.901, 92.6% and 87.5%, respectively. Compared with US or MRI alone, the integrated diagnostic strategy significantly increased the AUC (p < 0.001, p = 0.007) and specificity (p < 0.001, p = 0.034) while maintaining high sensitivity (p = 0.774, p = 0.551). In the validation set, the integrated strategy of US combined with MRI (AUC = 0.899) also had good performance compared with US (AUC = 0.728) or MRI (AUC = 0.838). CONCLUSION: The integrated diagnostic strategy of US combined with MRI exhibited good performance for breast NMLs compared with either modality used alone, which can improve the diagnostic specificity while maintaining high sensitivity.

The role of gut microbiota and metabolites in cancer chemotherapy.

BACKGROUND: The microbiota inhabits the epithelial surfaces of hosts, which influences physiological functions from helping digest food and acquiring nutrition to regulate metabolism and shaping host immunity. With the deep insight into the microbiota, an increasing amount of research reveals that it is also involved in the initiation and progression of cancer. Intriguingly, gut microbiota can mediate the biotransformation of drugs, thereby altering their bioavailability, bioactivity, or toxicity. AIM OF REVIEW: The review aims to elaborate on the role of gut microbiota and microbial metabolites in the efficacy and adverse effects of chemotherapeutics. Furthermore, we discuss the clinical potential of various ways to harness gut microbiota for cancer chemotherapy. KEY SCIENTIFIC CONCEPTS OF REVIEW: Recent evidence shows that gut microbiota modulates the efficacy and toxicity of chemotherapy agents, leading to diverse host responses to chemotherapy. Thereinto, targeting the microbiota to improve efficacy and diminish the toxicity of chemotherapeutic drugs may be a promising strategy in tumor treatment.

Tumor-repopulating cell-derived microparticles elicit cascade amplification of chemotherapy-induced antitumor immunity to boost anti-PD-1 therapy.

Immune checkpoint blockade (ICB) therapy, particularly antibodies targeting the programmed death receptor 1 (PD-1) and its ligand (PD-L1), has revolutionized cancer treatment. However, its efficacy as a standalone therapy remains limited. Although ICB therapy in combination with chemotherapy shows promising therapeutic responses, the challenge lies in amplifying chemotherapy-induced antitumor immunity effectively. This relies on efficient drug delivery to tumor cells and robust antigen presentation by dendritic cells (DCs). Here, we developed tumor-repopulating cell (TRC)-derived microparticles with exceptional tumor targeting to deliver doxorubicin (DOX@3D-MPs) for improve anti-PD-1 therapy. DOX@3D-MPs effectively elicit immunogenic tumor cell death to release sufficient tumor antigens. Heat shock protein 70 (HSP70) overexpressed in DOX@3D-MPs contributes to capturing tumor antigens, promoting their phagocytosis by DCs, and facilitating DCs maturation, leading to the activation of CD8+ T cells. DOX@3D-MPs significantly enhance the curative response of anti-PD-1 treatment in large subcutaneous H22 hepatoma, orthotopic 4T1 breast tumor and Panc02 pancreatic tumor models. These results demonstrate that DOX@3D-MPs hold promise as agents to improve the response rate to ICB therapy and generate long-lasting immune memory to prevent tumor relapse.

Maize near-isogenic lines with enhanced flavonoids alleviated dextran sodium sulfate-induced murine colitis via modulation of the gut microbiota.

The rising incidence of inflammatory bowel disease (IBD) has necessitated the search for safe and effective novel therapeutic strategies. Dietary flavonoids exhibited antioxidant, antiproliferative, and anticarcinogenic activities in several model systems with proven abilities to reduce inflammation and oxidative stress, thus they could be promising therapeutic agents for IBD prevention/treatment. However, understanding the role of a specific class of compounds in foods that promote health is difficult because of the chemically complex food matrices. This study aimed to utilize four maize near-isogenic lines to determine the anti-colitis effects of specific classes of flavonoids, anthocyanins and/or phlobaphenes, in a whole-food matrix. Results showed that the intake of anthocyanin and phlobaphene-enriched maize diets effectively alleviated dextran sodium sulfate (DSS)-induced colitis in mice via reducing the intestinal permeability and restoring the barrier function. Anthocyanin diets were more effective in maintaining the crypt structure and muc2 protein levels and reducing inflammation. Bacterial communities of mice consuming diets enriched with anthocyanins and phlobaphenes were more similar to the healthy control compared to the DSS control group, suggesting the role of flavonoids in modulating the gut microbiota to retrieve intestinal homeostasis. Microbiota depletion rendered these compounds ineffective against colitis. Lower serum concentrations of several phenolic acids were detected in the microbiota-depleted mice, indicating that gut microbiota plays a role in flavonoid metabolism and bioavailability.

Hierarchical Fluid Interface Enables Spatiotemporal Regulation of Ligand Distribution to Increase Kinetics and Thermodynamics of Interfacial Binding Reaction.

In nature, regulation of the spatiotemporal distribution of interfacial receptors and ligands leads to optimum binding kinetics and thermodynamics of receptor-ligand binding reactions within interfaces. Inspired by this, we report a hierarchical fluid interface (HieFluidFace) to regulate the spatiotemporal distribution of interfacial ligands to increase the rate and thermodynamic favorability of interfacial binding reactions. Each aptamer-functionalized gold nanoparticle, termed spherical aptamer (SAPT), is anchored on a supported lipid bilayer without fluidity, like an "island", and is surrounded by many fluorescent aptamers (FAPTs) with free fluidity, like "rafts". Such ligand "island-rafts" model provides a large reactive cross-section for rapid binding to cellular receptors. The synergistic multivalency of SAPTs and FAPTs improves interfacial affinity for tight capture. Moreover, FAPTs accumulate at binding sites to bind to cellular receptors with clustered fluorescence to "lighten" cells for direct identification. Thus, HieFluidFace in a microfluidic chip achieves high-performance capture and identification of circulating tumor cells from clinical samples, providing a new paradigm to optimize the kinetics and thermodynamics of interfacial binding reactions.

Clinical indicators combined with S100A12/TLR2 signaling molecules to establish a new scoring model for coronary artery lesions in Kawasaki disease.

Coronary artery lesions (CALs) are the most common and serious complication of Kawasaki disease (KD), and the pathogenesis is unknown. Exploring KD-specific biomarkers and related risk factors is significant for clinical diagnosis and treatment. This study aimed to explore the feasibility of combining clinical indicators with S100A12/TLR2-associated signaling molecules for the predictive modeling of CALs in KD. A total of 346 patients (224 males and 122 females) with KD who visited the rheumatology department of Wuhan Children's Hospital between April 2022 and March 2025 were enrolled and divided into two groups according to the presence or absence of CALS (292 patients had CALs and 54 patients did not). Forty-one variables were collected from the two groups, including demographic characteristics, clinical manifestations, and laboratory data. Single nucleated cells from each patient were extracted, and the expression of the S100A12/TLR2 signal transduction-related molecules S100A12, TLR2, MYD88, and NF-κB were detected by real-time fluorescent quantitative polymerase chain reaction. Statistically significant variables were subjected to logistic regression analysis to determine the independent risk factors for KD with CALs, and a new risk score model was established to assess the predictive efficacy based on receiver operating characteristic curves. Sixteen variables significantly differed between the no-CALs and CALs groups: gender, fever duration, white blood cells (WBC), hemoglobin (HGB), Ce reactive protein (CRP), procalcitonin, serum ferritin (SF), erythrocyte sedimentation rate (ESR), fibrinogen (FIB), aspartate aminotransferase-to-alanine aminotransferase ratio (AST/ALT), serum albumin (ALB), sodium (Na), Interleukin (IL-10), tumor necrosis factor (TNF-α), S100 calcium binding protein A12 (S100A12), and Myeloid Differentiation Factor 88 (MYD88) (p < 0.05). After performing a univariate analysis, 12 variables (gender, fever duration, WBC, HGB, CRP, SF, ESR, FIB, AST/ALT, ALB, Na, and S100A12) were included in the multifactorial binary logistic regression, which showed that fever duration ≥ 6.5 days, ESR ≥ 46.5 mm/h, AST/ALT ≤ 1.51, and S100A12 ≥ 10.02 were independent risk factors for KD with CALs and were assigned scores of 3, 2, 1, and 2, respectively, according to the odds ratio (OR). The total score of each patient was counted, and a new prediction model for KD combined with CALs was established, where < 3.5 was considered low risk and ≥ 3.5 was regarded as high risk; the sensitivity, specificity, Jorden index, and area under the curve of this scoring system were 0.667, 0.836, 0.502, and 0.838, respectively. This new scoring model has good efficacy for predicting the occurrence of KD with CALs. The expression of S100A12 was significantly increased in the CALs group and was an independent risk factor for the occurrence of CALs, and has the potential as a biomarker for predicting KD with CALs.

Hydrophobicity-Adaptive Polymers Trigger Fission of Tumor-Cell-Derived Microparticles for Enhanced Anticancer Drug Delivery.

Tumor-cell-derived microparticles (MPs) can function as anticancer drug-delivery carriers. However, short blood circulation time, large-size-induced insufficient tumor accumulation and penetration into tumor parenchyma, as well as limited cellular internalization by tumor cells and cancer stem cells (CSCs), and difficult intracellular drug release restrict the anticancer activity of tumor-cell-derived MP-based drug-delivery systems. In this work, hydrophobicity-adaptive polymers based on poly(N-isopropylacrylamide) are anchored to tumor-cell-derived MPs for enhanced delivery of the anticancer drug doxorubicin (DOX). The polymers are hydrophilic in blood to prolong the circulation time of DOX-loaded MPs (DOX@MPs), while rapidly switching to hydrophobic at the tumor acidic microenvironment. The hydrophobicity of polymers drives the fission of tumor-cell-derived MPs to form small vesicles, facilitating tumor accumulation, deep tumor penetration, and efficient internalization of DOX@MPs into tumor cells and CSCs. Subsequently, the hydrophobicity of polymers in acidic lysosomes further promotes DOX release to nuclei for strong cytotoxicity against tumor cells and CSCs. The work provides a facile and simple strategy for improved anticancer drug delivery of tumor-cell-derived MPs.

Cell microparticles loaded with tumor antigen and resiquimod reprogram tumor-associated macrophages and promote stem-like CD8+ T cells to boost anti-PD-1 therapy.

The durable response rate to immune checkpoint blockade such as anti-programmed cell death-1 (PD-1) antibody remains relatively low in hepatocellular carcinoma (HCC), mainly depending on an immunosuppressive microenvironment with limited number of CD8+ T cells, especially stem-like CD8+ T cells, in tumor tissues. Here we develop engineered microparticles (MPs) derived from alpha-fetoprotein (AFP)-overexpressing macrophages to load resiquimod (R848@M2pep-MPsAFP) for enhanced anti-PD-1 therapy in HCC. R848@M2pep-MPsAFP target and reprogram immunosuppressive M2-like tumor-associated macrophages (TAMs) into M1-like phenotype. Meanwhile, R848@M2pep-MPsAFP-reprogrammed TAMs act as antigen-presenting cells, not only presenting AFP antigen to activate CD8+ T cell-mediated antitumor immunity, but also providing an intra-tumoral niche to maintain and differentiate stem-like CD8+ T cells. Combination immunotherapy with anti-PD-1 antibody generates strong antitumor immune memory and induces abundant stem-like CD8+ T cell proliferation and differentiation to terminally exhausted CD8+ T cells for long-term immune surveillance in orthotopic and autochthonous HCC preclinical models in male mice. We also show that the R848-loaded engineered MPs derived from macrophages overexpressing a model antigen ovalbumin (OVA) can improve anti-PD-1 therapy in melanoma B16-OVA tumor-bearing mice. Our work presents a facile and generic strategy for personalized cancer immunotherapy to boost anti-PD-1 therapy.

Left-primary & right-auxiliary operation mode in mediastinoscope-assisted radical esophagectomy.

BACKGROUND: Mediastinoscope-assisted transhiatal esophagectomy (MATHE) is the most minimally invasive esophagectomy procedure. It is a more challenging procedure and more difficult to be popularized than thoracoscopic surgery. We developed a new MATHE operation mode that provides a clearer visual field and makes the procedures simpler. METHODS: A total of 80 patients with esophageal cancer were divided into a control group (n = 29) and a study group (n = 51). The control group underwent classic MATHE, while the study group received modified MATHE. We compared the two groups on operation time; intraoperative blood loss; blood transfusion amount; incidence rate of lung infection, recurrent laryngeal nerves (RLNs) injury, chylothorax, and anastomotic leakage; and upper mediastinal lymph node dissection. RESULTS: The study group was significantly better than the control group in operation time (271.78 min vs. 322.90 min, p < 0.05), intraoperative blood loss (48.63 mL vs. 68.97 mL, p < 0.05), and left paratracheal lymph node (No. 4L) dissection rate (88.24% vs. 24.14%, p < 0.01). No significant differences were identified in the incidence rate of anastomotic leakage, lung complications, or RLNs injury between the two groups. CONCLUSION: The modified MATHE is easier to perform. Modified MATHE is significantly superior to classic MATHE in operation time, intraoperative blood loss, and upper mediastinal lymph node dissection rate.

PECAM-1 drives ß-catenin-mediated EndMT via internalization in colon cancer with diabetes mellitus.

BACKGROUND: Diabetes mellitus (DM) is considered to be a risk factor in carcinogenesis and progression, although the biological mechanisms are not well understood. Here we demonstrate that platelet-endothelial cell adhesion molecule 1 (PECAM-1) internalization drives ß-catenin-mediated endothelial-mesenchymal transition (EndMT) to link DM to cancer. METHODS: The tumor microenvironment (TME) was investigated for differences between colon cancer with and without DM by mRNA-microarray analysis. The effect of DM on colon cancer was determined in clinical patients and animal models. Furthermore, EndMT, PECAM-1 and Akt/GSK-3ß/ß-catenin signaling were analyzed under high glucose (HG) and human colon cancer cell (HCCC) supernatant (SN) or coculture conditions by western and immunofluorescence tests. RESULTS: DM promoted the progression and EndMT occurrence of colon cancer (CC). Regarding the mechanism, DM induced PECAM-1 defection from the cytomembrane, internalization and subsequent accumulation around the cell nucleus in endothelial cells, which promoted ß-catenin entry into the nucleus, leading to EndMT occurrence in CC with DM. Additionally, Akt/GSK-3ß signaling was enhanced to inhibit the degradation of ß-catenin, which regulates the process of EndMT. CONCLUSIONS: PECAM-1 defects and/or internalization are key events for ß-catenin-mediated EndMT, which is significantly boosted by enhanced Akt/GSK-3ß signaling in the DM-associated TME. This contributes to the mechanism by which DM promotes the carcinogenesis and progression of CC. Video Abstract.

Surgical site infection following open lobectomy in patients with lung cancer: A prospective study.

OBJECTIVE: To assess the incidence and risk factors of surgical site infection after open pulmonary lobectomy and to quantify their clinical and economic burden. METHODS: A prospective nested case-control study was performed on patients with lung cancer who underwent open lobectomy in the lung cancer center of West China Hospital from January 2017 to December 2019. Demographic, clinical data and medical costs were recorded. Logistic regression was used to evaluate risk factors associated with surgical site infection. A Mann-Whitney U test was carried out to evaluate the differences in medical costs. RESULTS: A total of 1395 patients were eligible, and the surgical site infection incidence was 13.47% (188/1395). Of the 188 instances of surgical site infection, 171 (90.96%) were classified as organ/space infection, 8 (4.25%) as superficial incisional infection and 9 (4.79%) as deep incisional infection. The patients with surgical site infection had significantly higher mortality (3.19% vs. 0.41%, p < 0.001), higher median medical cost (90774.95 yuan vs. 63079.38 yuan, p < 0.001), and longer postoperative length of stay (15 days vs. 9 days, p < 0.001). Multivariate logistic regression analysis indicated that age (odds ratio (OR) = 1.560, p = 0.007), respiratory failure (OR = 5.984, p = 0.0012), American Society of Anesthesiologists score (OR = 1.584, p = 0.005), operating time (OR = 1.950, p < 0.001), and operation team (OR = 1.864, p < 0.001) were independent risk factors for surgical site infection. CONCLUSIONS: The high incidence of surgical site infection indicates that postoperative infections remain a significant clinical burden in patients who underwent open lobectomy. Identifying risk factors timely through prospective surveillance may assist clinical decisions against surgical site infection.

A Visual Color Response Test Paper for the Detection of Hydrogen Sulfide Gas in the Air.

Hydrogen sulfide (H2S) is widely found in oil and natural gas wells and industrial wastewater tanks. Owing to its high toxicity, the monitoring and detection of H2S in the air is essential. However, recent techniques for the quantitative detection of H2S gas suffer from limitations such as high cost, complicated operation, and insufficient sensitivity, preventing their practical application in industry. Thus, we have developed a portable test paper for real-time and inexpensive monitoring of H2S gas by color changes. The test paper had a significantly low H2S detection limit of 200 ppb, which is considered safe for humans. Moreover, the color of the test paper did not change noticeably when exposed to CO2, N2, O2, and air environments, indicating that the test paper is selective for H2S gas and can be stored for a long time. In addition, we fitted a color difference linear model between the color difference values (ΔE) and the concentrations of H2S gas. The establishment of the linear model substantiates that the test paper can provide accurate intensity information when detecting H2S gas leakage.

Comprehensive analysis of the expression and prognosis for RAI2: A promising biomarker in breast cancer.

Introduction: Retinoic acid-induced 2 (RAI2) was initially related to cell differentiation and induced by retinoic acid. RAI2 has been identified as an emerging tumor suppressor in breast cancer and colorectal cancer. Methods: In this study, we performed systematic analyses of RAI2 in breast cancer. Meta-analysis and Kaplan-Meier survival curves were applied to identify the survival prediction potential of RAI2. Moreover, the association between RAI2 expression and the abundance of six tumor-infiltrating immune cells was investigated by TIMER, including B cells, CD8+ T cells, CD4+ T cells, B cells, dendritic cells, neutrophils, and macrophages. The expression profiles of high and low RAI2 mRNA levels in GSE7390 were compared to identify differentially expressed genes (DEGs) and the biological function of these DEGs was analyzed by R software, which was further proved in GSE7390. Results: Our results showed that the normal tissues had more RAI2 expression than breast cancer tissues. Patients with high RAI2 expression were related to a favorable prognosis and more immune infiltrates. A total of 209 DEGs and 182 DEGs were identified between the expression profiles of high and low RAI2 mRNA levels in the GSE7390 and GSE21653 databases, respectively. Furthermore, Gene Ontology (GO) enrichment indicated that these DEGs from two datasets were both mainly distributed in "biological processes" (BP), including "organelle fission" and "nuclear division". Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis demonstrated that these DEGs from two datasets were both significantly enriched in the "cell cycle". Common hub genes between the DEGs in GSE7390 and GSE21653 were negatively associated with RAI2 expression, including CCNA2, MAD2L1, MELK, CDC20, and CCNB2. Discussions: These results above suggested that RAI2 might play a pivotal role in preventing the initiation and progression of breast cancer. The present study may contribute to understanding the molecular mechanisms of RAI2 and enriching biomarkers to predict patient prognosis in breast cancer.