A novel nomogram for predicting prolonged mechanical ventilation after acute type A aortic dissection surgery: a retrospective study investigating the impact of ventilation duration on postoperative outcomes.

OBJECTIVE: Acute type A aortic dissection (ATAAD) is a devastating cardiovascular disease with extraordinary morbidity and mortality. Prolonged mechanical ventilation (PMV) is a common complication following ATAAD surgery, leading to adverse outcomes. This study aimed to investigate the correlation between mechanical ventilation time (MVT) and prognosis and to devise a nomogram for predicting PMV after ATAAD surgery. METHODS: This retrospective study enrolled 1049 ATAAD patients from 2011 to 2019. Subgroups were divided into < 12 h, 12 h to < 24 h, 24 h to < 48 h, 48 h to < 72 h, and ≥ 72 h according to MVT. Clinical characteristics and outcomes were compared among the groups. Using multivariable logistic regression analyses, we investigated the relationship between each stratification of MVT and mortality. A nomogram was constructed based on the refined multivariable logistic regression model for predicting PMV. RESULTS: The total mortality was 11.8% (124/1049). The results showed that the groups with MVT 48 h to < 72 h and ≥ 72 h had significantly higher operative mortality compared to other MVT categories. Multivariate logistic regression analysis showed that MVT ≥72 h was significantly associated with higher short-term mortality. Thus, a nomogram was presented to elucidate the association between PMV (MVT ≥72 h) and risk factors including advanced age, preoperative cerebral ischemia, ascending aorta replacement, concomitant coronary artery bypass grafting (CABG), longer cardiopulmonary bypass (CPB), and large-volume intraoperative fresh frozen plasma (FFP) transfusion. The nomogram exhibited strong predictive performance upon validation. CONCLUSIONS: Safely extubating patients within 72 h after ATAAD surgery is crucial for achieving favorable outcomes. The developed and validated nomogram provides a valuable tool for predicting PMV and optimizing postoperative care to improve patient prognosis. This novel nomogram has the potential to guide clinical decision-making and resource allocation in the management of ATAAD patients.

Prolonged mechanical ventilation (PMV) is a common complication following ATAAD surgery, leading to adverse outcomes.Safely extubating patients within 72 hours after ATAAD surgery is crucial for achieving favourable outcomes.A novel, validated nomogram incorporating risk factors such as age, comorbidities and intraoperative factors predicts PMV after ATAAD surgery, aiding clinical decision-making and optimizing postoperative care.

Reported Xylazine Use Among Adults Aged ≥18 Years Evaluated for Substance Use Treatment - United States, July 2022-September 2023.

Xylazine has been increasingly detected in illegally manufactured fentanyl (IMF) products and overdose deaths in the United States; most xylazine-involved overdose deaths involve IMF. A convenience sample of U.S. adults aged ≥18 years was identified from those evaluated for substance use treatment during July 2022-September 2023. Data were collected using the Addiction Severity Index-Multimedia Version clinical assessment tool. Among 43,947 adults, 6,415 (14.6%) reported IMF or heroin as their primary lifetime substance-use problem; 5,344 (12.2%) reported recent (i.e., past-30-day) IMF or heroin use. Among adults reporting IMF or heroin as their primary lifetime substance-use problem, 817 (12.7%) reported ever using xylazine. Among adults reporting recent IMF or heroin use, 443 (8.3%) reported recent xylazine use. Among adults reporting IMF or heroin use recently or as their primary lifetime substance-use problem, those reporting xylazine use reported a median of two past nonfatal overdoses from any drug compared with a median of one overdose among those who did not report xylazine use; as well, higher percentages of persons who reported xylazine use reported other recent substance use and polysubstance use. Provision of nonjudgmental care and services, including naloxone, wound care, and linkage to and retention of persons in effective substance use treatment, might reduce harms including overdose among persons reporting xylazine use.

Realveolarization with inhalable mucus-penetrating lipid nanoparticles for the treatment of pulmonary fibrosis in mice.

The stemness loss-associated dysregeneration of impaired alveolar type 2 epithelial (AT2) cells abolishes the reversible therapy of idiopathic pulmonary fibrosis (IPF). We here report an inhalable mucus-penetrating lipid nanoparticle (LNP) for codelivering dual mRNAs, promoting realveolarization via restoring AT2 stemness for IPF treatment. Inhalable LNPs were first formulated with dipalmitoylphosphatidylcholine and our in-house-made ionizable lipids for high-efficiency pulmonary mucus penetration and codelivery of dual messenger RNAs (mRNAs), encoding cytochrome b5 reductase 3 and bone morphogenetic protein 4, respectively. After being inhaled in a bleomycin model, LNPs reverses the mitochondrial dysfunction through ameliorating nicotinamide adenine dinucleotide biosynthesis, which inhibits the accelerated senescence of AT2 cells. Concurrently, pathological epithelial remodeling and fibroblast activation induced by impaired AT2 cells are terminated, ultimately prompting alveolar regeneration. Our data demonstrated that the mRNA-LNP system exhibited high protein expression in lung epithelial cells, which markedly extricated the alveolar collapse and prolonged the survival of fibrosis mice, providing a clinically viable strategy against IPF.

Advances in precision gene editing for liver fibrosis: From technology to therapeutic applications.

This review presents a comprehensive exploration of gene editing technologies and their potential applications in the treatment of liver fibrosis, a condition often leading to serious complications such as liver cancer. Through an in-depth review of current literature and critical analysis, the study delves into the intricate signaling pathways underlying liver fibrosis development and examines the promising role of gene editing in alleviating this disease burden. Gene editing technologies offer precise, efficient, and reproducible tools for manipulating genetic material, holding significant promise for basic research and clinical practice. The manuscript highlights the challenges and potential risks associated with gene editing technology. By synthesizing existing knowledge and exploring future perspectives, this study aims to provide valuable insights into the potential of precision gene editing to combat liver fibrosis and its associated complications, ultimately contributing to advances in liver fibrosis research and therapy.

Stimulation of tumoricidal immunity via bacteriotherapy inhibits glioblastoma relapse.

Glioblastoma multiforme (GBM) is a highly aggressive brain tumor characterized by invasive behavior and a compromised immune response, presenting treatment challenges. Surgical debulking of GBM fails to address its highly infiltrative nature, leaving neoplastic satellites in an environment characterized by impaired immune surveillance, ultimately paving the way for tumor recurrence. Tracking and eradicating residual GBM cells by boosting antitumor immunity is critical for preventing postoperative relapse, but effective immunotherapeutic strategies remain elusive. Here, we report a cavity-injectable bacterium-hydrogel superstructure that targets GBM satellites around the cavity, triggers GBM pyroptosis, and initiates innate and adaptive immune responses, which prevent postoperative GBM relapse in male mice. The immunostimulatory Salmonella delivery vehicles (SDVs) engineered from attenuated Salmonella typhimurium (VNP20009) seek and attack GBM cells. Salmonella lysis-inducing nanocapsules (SLINs), designed to trigger autolysis, are tethered to the SDVs, eliciting antitumor immune response through the intracellular release of bacterial components. Furthermore, SDVs and SLINs administration via intracavitary injection of the ATP-responsive hydrogel can recruit phagocytes and promote antigen presentation, initiating an adaptive immune response. Therefore, our work offers a local bacteriotherapy for stimulating anti-GBM immunity, with potential applicability for patients facing malignancies at a high risk of recurrence.

Hepatitis B-related hepatocellular carcinoma: classification and prognostic model based on programmed cell death genes.

Instruction: Hepatitis B virus (HBV) infection is a major risk factor for hepatocellular carcinoma (HCC). Programmed cell death (PCD) is a critical process in suppressing tumor growth, and alterations in PCD-related genes may contribute to the progression of HBV-HCC. This study aims to develop a prognostic model that incorporates genomic and clinical information based on PCD-related genes, providing novel insights into the molecular heterogeneity of HBV-HCC through bioinformatics analysis and experimental validation. Methods: In this study, we analyzed 139 HBV-HCC samples from The Cancer Genome Atlas (TCGA) and validated them with 30 samples from the Gene Expression Omnibus (GEO) database. Various bioinformatics tools, including differential expression analysis, gene set variation analysis, and machine learning algorithms were used for comprehensive analysis of RNA sequencing data from HBV-HCC patients. Furthermore, among the PCD-related genes, we ultimately chose DLAT for further research on tissue chips and patient cohorts. Besides, immunohistochemistry, qRT-PCR and Western blot analysis were conducted. Results: The cluster analysis identified three distinct subgroups of HBV-HCC patients. Among them, Cluster 2 demonstrated significant activation in DNA replication-related pathways and tumor-related processes. Analysis of copy number variations (CNVs) of PCD-related genes also revealed distinct patterns in the three subgroups, which may be associated with differences in pathway activation and survival outcomes. DLAT in tumor tissues of HBV-HCC patients is upregulated. Discussion: Based on the PCD-related genes, we developed a prognostic model that incorporates genomic and clinical information and provided novel insights into the molecular heterogeneity of HBV-HCC. In our study, we emphasized the significance of PCD-related genes, particularly DLAT, which was examined in vitro to explore its potential clinical implications.

Development of a Human B7-H3-Specific Antibody with Activity against Colorectal Cancer Cells through a Synthetic Nanobody Library.

Nanobodies have emerged as promising tools in biomedicine due to their single-chain structure and inherent stability. They generally have convex paratopes, which potentially prefer different epitope sites in an antigen compared to traditional antibodies. In this study, a synthetic phage display nanobody library was constructed and used to identify nanobodies targeting a tumor-associated antigen, the human B7-H3 protein. Combining next-generation sequencing and single-clone validation, two nanobodies were identified to specifically bind B7-H3 with medium nanomolar affinities. Further characterization revealed that these two clones targeted a different epitope compared to known B7-H3-specific antibodies, which have been explored in clinical trials. Furthermore, one of the clones, dubbed as A6, exhibited potent antibody-dependent cell-mediated cytotoxicity (ADCC) against a colorectal cancer cell line with an EC50 of 0.67 nM, upon conversion to an Fc-enhanced IgG format. These findings underscore a cost-effective strategy that bypasses the lengthy immunization process, offering potential rapid access to nanobodies targeting unexplored antigenic sites.

Antibacterial activity of cinnamon essential oil and its main component of cinnamaldehyde and the underlying mechanism.

Background: Plant essential oils have long been regarded as repositories of antimicrobial agents. In recent years, they have emerged as potential alternatives or supplements to antimicrobial drugs. Although literature reviews and previous studies have indicated that cinnamon essential oil (CIEO) and its major component, cinnamaldehyde (CID), possess potent antibacterial activities, their antibacterial mechanisms, especially the in vivo antibacterial mechanisms, remain elusive. Methods: In this study, we utilized the in vivo assessment system of Caenorhabditis elegans (C. elegans) to investigate the effects and mechanisms of high dose (100 mg/L) and low dose (10 mg/L) CIEO and CID in inhibiting Pseudomonas aeruginosa (P. aeruginosa). In addition, we also examined the in vitro antibacterial abilities of CIEO and CID against other common pathogens including P. aeruginosa and 4 other strains. Results: Our research revealed that both high (100 mg/L) and low doses (10 mg/L) of CIEO and CID treatment significantly alleviated the reduction in locomotion behavior, lifespan, and accumulation of P. aeruginosa in C. elegans infected with the bacteria. During P. aeruginosa infection, the transcriptional expression of antimicrobial peptide-related genes (lys-1 and lys-8) in C. elegans was upregulated with low-dose CIEO and CID treatment, while this trend was suppressed at high doses. Further investigation suggested that the PMK-1 mediated p38 signaling pathway may be involved in the regulation of CIEO and CID during nematode defense against P. aeruginosa infection. Furthermore, in vitro experimental results also revealed that CIEO and CID exhibit good antibacterial effects, which may be associated with their antioxidant properties. Conclusion: Our results indicated that low-dose CIEO and CID treatment could activate the p38 signaling pathway in C. elegans, thereby regulating antimicrobial peptides, and achieving antimicrobial effects. Meanwhile, high doses of CIEO and CID might directly participate in the internal antimicrobial processes of C. elegans. Our study provides research basis for the antibacterial properties of CIEO and CID both in vivo and in vitro.

Unveiling NUSAP1 as a common gene signature linking chronic HBV infection and HBV-related HCC.

BACKGROUND: Hepatitis B virus (HBV) is a significant contributor to the development of hepatocellular carcinoma (HCC). Chronic HBV infection (CHB) facilitates disease progression through various mechanisms. However, the specific factor responsible for the progression of HBV infection to HCC remains unresolved. This study aims to identify the hub gene linking CHB and HBV-related HCC through bioinformatic analysis and experimental verification. METHODS: Differentially expressed genes (DEGs) were identified in datasets encompassing CHB and HBV-HCC patients from the GEO database. Enriched pathways were derived from GO and KEGG analysis. Hub genes were screened by protein-protein interaction (PPI) analysis and different modules in Cytoscape software. The significance of the selected hub gene in prognosis was further assessed in validated datasets. The effects of hub genes on cell growth and apoptosis were further determined in functional experiments. RESULTS: The study revealed upregulation of NUSAP1 in CHBs and HBV-HCCs. High expression of NUSAP1 served as an independent predictor for poor prognosis of liver cancers. Functional experiments demonstrated that NUSAP1 promotes cell growth, influences cell cycle process, and protects cells from apoptosis in HepG2.2.15 cells. CONCLUSION: NUSAP1 serves as a poor prognostic indicator for liver cancers, and potentially plays a crucial role in HBV-HCC progression by promoting proliferation and inhibiting apoptosis.

p53/E2F7 axis promotes temozolomide chemoresistance in glioblastoma multiforme.

BACKGROUND: Glioblastoma multiforme (GBM) is the most aggressive form of brain cancer, and chemoresistance poses a significant challenge to the survival and prognosis of GBM. Although numerous regulatory mechanisms that contribute to chemoresistance have been identified, many questions remain unanswered. This study aims to identify the mechanism of temozolomide (TMZ) resistance in GBM. METHODS: Bioinformatics and antibody-based protein detection were used to examine the expression of E2F7 in gliomas and its correlation with prognosis. Additionally, IC50, cell viability, colony formation, apoptosis, doxorubicin (Dox) uptake, and intracranial transplantation were used to confirm the role of E2F7 in TMZ resistance, using our established TMZ-resistance (TMZ-R) model. Western blot and ChIP experiments provided confirmation of p53-driven regulation of E2F7. RESULTS: Elevated levels of E2F7 were detected in GBM tissue and were correlated with a poor prognosis for patients. E2F7 was found to be upregulated in TMZ-R tumors, and its high levels were linked to increased chemotherapy resistance by limiting drug uptake and decreasing DNA damage. The expression of E2F7 was also found to be regulated by the activation of p53. CONCLUSIONS: The high expression of E2F7, regulated by activated p53, confers chemoresistance to GBM cells by inhibiting drug uptake and DNA damage. These findings highlight the significant connection between sustained p53 activation and GBM chemoresistance, offering the potential for new strategies to overcome this resistance.

Prediction of acute kidney injury after cardiac surgery with fibrinogen-to-albumin ratio: a prospective observational study.

Background: The occurrence of acute kidney injury (AKI) following cardiac surgery is common and linked to unfavorable consequences while identifying it in its early stages remains a challenge. The aim of this research was to examine whether the fibrinogen-to-albumin ratio (FAR), an innovative inflammation-related risk indicator, has the ability to predict the development of AKI in individuals after cardiac surgery. Methods: Patients who underwent cardiac surgery from February 2023 to March 2023 and were admitted to the Cardiac Surgery Intensive Care Unit of a tertiary teaching hospital were included in this prospective observational study. AKI was defined according to the KDIGO criteria. To assess the diagnostic value of the FAR in predicting AKI, calculations were performed for the area under the receiver operating characteristic curve (AUC), continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: Of the 260 enrolled patients, 85 developed AKI with an incidence of 32.7%. Based on the multivariate logistic analyses, FAR at admission [odds ratio (OR), 1.197; 95% confidence interval (CI), 1.064-1.347, p = 0.003] was an independent risk factor for AKI. The receiver operating characteristic (ROC) curve indicated that FAR on admission was a significant predictor of AKI [AUC, 0.685, 95% CI: 0.616-0.754]. Although the AUC-ROC of the prediction model was not substantially improved by adding FAR, continuous NRI and IDI were significantly improved. Conclusions: FAR is independently associated with the occurrence of AKI after cardiac surgery and can significantly improve AKI prediction over the clinical prediction model.

The Complement Component 4 Binding Protein α Gene: A Versatile Immune Gene That Influences Lipid Metabolism in Bovine Mammary Epithelial Cell Lines.

Complement component 4 binding protein α (C4BPA) is an immune gene which is responsible for the complement regulation function of C4BP by binding and inactivating the Complement component C4b (C4b) component of the classical Complement 3 (C3) invertase pathway. Our previous findings revealed that C4BPA was differentially expressed by comparing the transcriptome in high-fat and low-fat bovine mammary epithelial cell lines (BMECs) from Chinese Holstein dairy cows. In this study, a C4BPA gene knockout BMECs line model was constructed via using a CRISPR/Cas9 system to investigate the function of C4BPA in lipid metabolism. The results showed that levels of triglyceride (TG) were increased, while levels of cholesterol (CHOL) and free fatty acid (FFA) were decreased (p < 0.05) after knocking out C4BPA in BMECs. Additionally, most kinds of fatty acids were found to be mainly enriched in the pathway of the biosynthesis of unsaturated fatty acids, linoleic acid metabolism, fatty acid biosynthesis, and regulation of lipolysis in adipocyte. Meanwhile, the RNA-seq showed that most of the differentially expressed genes (DEGs) are related to PI3K-Akt signaling pathway. The expressions of 3-Hydroxy-3-Methylglutaryl-CoA Synthase 1 (HMGCS1), Carnitine Palmitoyltransferase 1A (CPT1A), Fatty Acid Desaturase 1 (FADS1), and Stearoyl-Coenzyme A desaturase 1 (SCD1) significantly changed when the C4BPA gene was knocked out. Collectively, C4BPA gene, which is an immune gene, played an important role in lipid metabolism in BMECs. These findings provide a new avenue for animal breeders: this gene, with multiple functions, should be reasonably utilized.

mRNA-Laden Lipid-Nanoparticle-Enabled in Situ CAR-Macrophage Engineering for the Eradication of Multidrug-Resistant Bacteria in a Sepsis Mouse Model.

Sepsis, which is the most severe clinical manifestation of acute infection and has a mortality rate higher than that of cancer, represents a significant global public health burden. Persistent methicillin-resistant Staphylococcus aureus (MRSA) infection and further host immune paralysis are the leading causes of sepsis-associated death, but limited clinical interventions that target sepsis have failed to effectively restore immune homeostasis to enable complete eradication of MRSA. To restimulate anti-MRSA innate immunity, we developed CRV peptide-modified lipid nanoparticles (CRV/LNP-RNAs) for transient in situ programming of macrophages (MΦs). The CRV/LNP-RNAs enabled the delivery of MRSA-targeted chimeric antigen receptor (CAR) mRNA (SasA-CAR mRNA) and CASP11 (a key MRSA intracellular evasion target) siRNA to MΦs in situ, yielding CAR-MΦs with boosted bactericidal potency. Specifically, our results demonstrated that the engineered MΦs could efficiently phagocytose and digest MRSA intracellularly, preventing immune evasion by the "superbug" MRSA. Our findings highlight the potential of nanoparticle-enabled in vivo generation of CAR-MΦs as a therapeutic platform for multidrug-resistant (MDR) bacterial infections and should be confirmed in clinical trials.

Intracavitary Spraying of Nanoregulator-Encased Hydrogel Modulates Cholesterol Metabolism of Glioma-Supportive Macrophage for Postoperative Glioblastoma Immunotherapy.

Glioblastoma multiforme (GBM) is notoriously resistant to immunotherapy due to its intricate immunosuppressive tumor microenvironment (TME). Dysregulated cholesterol metabolism is implicated in the TME and promotes tumor progression. Here, it is found that cholesterol levels in GBM tissues are abnormally high, and glioma-supportive macrophages (GSMs), an essential "cholesterol factory", demonstrate aberrantly hyperactive cholesterol metabolism and efflux, providing cholesterol to fuel GBM growth and induce CD8+ T cells exhaustion. Bioinformatics analysis confirms that high 7-dehydrocholesterol reductase (DHCR7) level in GBM tissues associates with increased cholesterol biosynthesis, suppressed tumoricidal immune response, and poor patient survival, and DHCR7 expression level is significantly elevated in GSMs. Therefore, an intracavitary sprayable nanoregulator (NR)-encased hydrogel system to modulate cholesterol metabolism of GSMs is reported. The degradable NR-mediated ablation of DHCR7 in GSMs effectively suppresses cholesterol supply and activates T-cell immunity. Moreover, the combination of Toll-like receptor 7/8 (TLR7/8) agonists significantly promotes GSM polarization to antitumor phenotypes and ameliorates the TME. Treatment with the hybrid system exhibits superior antitumor effects in the orthotopic GBM model and postsurgical recurrence model. Altogether, the findings unravel the role of GSMs DHCR7/cholesterol signaling in the regulation of TME, presenting a potential treatment strategy that warrants further clinical trials.

Application of deep learning in the diagnosis and evaluation of ulcerative colitis disease severity.

Background: Achieving endoscopic and histological remission is a critical treatment objective in ulcerative colitis (UC). Nevertheless, interobserver variability can significantly impact overall assessment performance. Objectives: We aimed to develop a deep learning algorithm for the real-time and objective evaluation of endoscopic disease activity and prediction of histological remission in UC. Design: This is a retrospective diagnostic study. Methods: Two convolutional neural network (CNN) models were constructed and trained using 12,257 endoscopic images and biopsy results sourced from 1124 UC patients who underwent colonoscopy at a single center from January 2018 to December 2022. Mayo Endoscopy Subscore (MES) and UC Endoscopic Index of Severity Score (UCEIS) assessments were conducted by two experienced and independent reviewers. Model performance was evaluated in terms of accuracy, sensitivity, and positive predictive value. The output of the CNN models was also compared with the corresponding histological results to assess histological remission prediction performance. Results: The MES-CNN model achieved 97.04% accuracy in diagnosing endoscopic remission of UC, while the MES-CNN and UCEIS-CNN models achieved 90.15% and 85.29% accuracy, respectively, in evaluating endoscopic severity of UC. For predicting histological remission, the CNN models achieved accuracy and kappa values of 91.28% and 0.826, respectively, attaining higher accuracy than human endoscopists (87.69%). Conclusion: The proposed artificial intelligence model, based on MES and UCEIS evaluations from expert gastroenterologists, offered precise assessment of inflammation in UC endoscopic images and reliably predicted histological remission.

Application of deep learning in the diagnosis and evaluation of ulcerative colitis disease severity Why was this study done? This study aimed to develop a real-time and objective diagnostic tool to reduce subjectivity when evaluating ulcerative colitis (UC) endoscopic disease activity and to predict histological remission without mucosal biopsy. What did the researchers do? We developed and validated a deep learning algorithm that uses UC endoscopic images to predict the Mayo Endoscopic Score (MES), US Endoscopic Index of Severity Score (UCEIS), and histological remission. What did the researchers find? The constructed MES- and UCEIS-based models both achieved high accuracy and performance in predicting histological remission, outperforming human endoscopists. What do the findings mean? The efficiency and performance of the deep learning algorithm rivaled that of expert assessments, which may assist endoscopists in making more objective evaluations of UC severity and in predicting histological remission.