Transcriptome sequencing analysis of bovine mammary epithelial cells induced by lipopolysaccharide

Mastitis in cows is caused by the inflammation of the mammary glands due to an infection by external pathogenic bacteria. Mammary gland epithelial cells, which are in direct contact with the external environment, are responsible for the first line of defense of the mammary gland against pathogenic bacteria, playing an essential role in immune defense. To investigate the mechanism of bovine mammary epithelial cells in the inflammatory process, we treated the cells with LPS for 12 hours and analyzed the changes in mRNA by transcriptome sequencing. The results showed that compared to the control group, the LPS treatment group had 121 up-regulated genes and 18 down-regulated genes. GO and KEGG enrichment analysis revealed that these differential genes were mainly enriched in the IL-17 signaling pathway, Legionellosis, Cytokine-cytokine receptor interaction, NF-kappa B signaling pathway, and other signaling pathways. Furthermore, the expression of GRO1 and CXCL3 mRNAs increased significantly after LPS treatment. These findings provide new insights for the treatment of mastitis in cows in the future.

Multifunctional Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9-Based Nanobomb against Carbapenem-Resistant Acinetobacter baumannii Infection through Cascade Reaction and Amplification Synergistic Effect

Carbapenems have been considered to be the preferred antibiotics against Acinetobacter baumannii thus far. However, carbapenem-resistant Acinetobacter baumannii (CRAB) has gradually escalated worldwide, and it frequently causes respiratory and bloodstream infections. Its resistance may lead to high mortality. Thus, there is an urgent need to develop antibacterial drugs. In our research, the pH-sensitive sgRNA-I/L@ZS nanosystem delivered imipenem and better released it in infected tissues to synergistically damage bacteria with nanoparticles. Gene editing of the CRISPR-Cas9 nanosystem amplified the synergistic effect by reversing the drug-resistance of imipenem. Nitric oxide, which l-arginine reacted with ROS to produce in cascade reaction and bacterial infection sites, was beneficial to heal the infected tissues and induce bacteria death for further enhancing antibacterial effects. In addition, this nanocomposite influenced host-bacteria interactions and restrained and destroyed biofilms. The sgRNA-I/L@ZS nanosystem, similar to a nanobomb, was a high-efficiency bactericide against CRAB. Eventually, in acute pneumonia and peritonitis mouse models, the sgRNA-I/L@ZS nanosystem could combat bacteria and protect tissues from infection. It had marked suppressive effects on inflammation and promoted healing and proliferation of infected tissues. This multifunctional nanosystem is expected to be an effective antibacterial agent in the clinic based on good biocompatibility and no toxic side effects. Therefore, developing the nanocomposites will take a favorable step toward solving intractable public health issues.

Transcriptomic profiling of lipopolysaccharide-challenged bovine mammary epithelial cells treated with forsythoside A

Mastitis is usually caused by a variety of pathogenic bacteria that seriously impact the health and milk-production ability of dairy cows, with consequent, economically detrimental effects on the dairy industry. Forsythoside A (FTA), isolated from the fruit and leaves of Forsythia suspensa (Thunb.) Vahl (Oleaceae), has been reported to have significant antioxidant, anti-inflammatory, and antibacterial effects. However, it is not clear whether FTA exerts a protective effect against lipopolysaccharide (LPS)-induced bovine mastitis and its potential gene signature. In this study, high-throughput sequencing technology was performed to analyze the differences between the mRNA and enrichment pathway of bovine mammary epithelial cells of the control, LPS, and LPS + FTA groups. The results showed that there were 139 differentially expressed genes (DEGs) (p-value < 0.05, |log2FoldChange| > 1, FPKM > 1) in the LPS group compared with the control group, including 121 up-regulated genes and 18 down-regulated genes, which were mainly enriched in the cellular response to lipopolysaccharide, cytokine activity, protein binding, and IL-17 signaling pathway based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, respectively. Compared with the control group and LPS + FTA group, there were 349 DEGs, including 322 up-regulated genes and 27 down-regulated genes. They were mainly enriched in protein localization to organelles, centrosomes, binding, and the IL-17 signaling pathway, based on GO and KEGG analysis. Compared to the LPS group, the LPS + FTA group had 272 DEGs, including 259 up-regulated genes and 13 down-regulated genes, which were mainly enriched in RNA processing, IL-6 receptor binding, and the lysosome pathway, based on GO and KEGG analyses. It can be seen that LPS stimulation induced the expression of inflammation-related genes, IL-17 and IL-6, whereas FTA treatment promoted the expression of the spliceosome-, lysosome-, and oxidative stress-related genes HSP70, HSPA8, and PARP2. The study utilized RNA-sequencing analysis of FTA against LPS-challenged bovine mammary epithelial cells to explore key mRNA findings that may be strongly associated with inflammation and oxidative stress, and provides a theoretical reference for further elucidation of molecular mechanisms of bovine mastitis and therapeutic effects of FTA against bovine mastitis.

Platelet-membrane camouflaged cerium nanoparticle-embedded gelatin methacryloyl hydrogel for accelerated diabetic wound healing

Impaired angiogenesis and excessive inflammation are major factors contributing to delayed wound healing in diabetic patients. This study presents the development of a novel multifunctional hydrogel, Pltm@CNPs/Gel, which incorporates platelet membrane camouflaged cerium nanoparticles into a gelatin methacryloyl matrix. The Pltm@CNPs/Gel nanocomposite hydrogel was characterized and tested for its effects on platelet activation, coagulation, cell viability, anti-oxidation, and anti-inflammation in vitro. Moreover, we evaluated the wound healing potential of the hydrogel in a diabetic rat model. Our findings demonstrate that the Pltm@CNPs/Gel hydrogel possesses anti-oxidative and anti-inflammatory properties. Furthermore, it accelerates diabetic wound healing by promoting neovascularization, cell proliferation, and collagen fiber organization. This study highlights the potential of the Pltm@CNPs/Gel hydrogel as a therapeutic option for diabetic wound healing and its promising applications as a diabetic wound dressing candidate.

Doxorubicin-Loaded Platelet Decoys for Enhanced Chemoimmunotherapy Against Triple-Negative Breast Cancer in Mice Model

Introduction

Triple-negative breast cancer (TNBC) is a highly aggressive subtype with a poor prognosis. Current single-agent checkpoint therapy has limited effectiveness in TNBC patients. In this study, we developed doxorubicin-loaded platelet decoys (PD@Dox) for chemotherapy and induction of tumor immunogenic cell death (ICD). By combining PD-1 antibody, PD@Dox has the potential to enhance tumor therapy through chemoimmunotherapy in vivo.

Methods

Platelet decoys were prepared using 0.1% Triton X-100 and co-incubated with doxorubicin to obtain PD@Dox. Characterization of PDs and PD@Dox was performed using electron microscopy and flow cytometry. We evaluated the properties of PD@Dox to retain platelets through sodium dodecyl sulfate-polyacrylamide gel electrophoresis, flow cytometry, and thromboelastometry. In vitro experiments assessed drug-loading capacity, release kinetics, and the enhanced antitumor activity of PD@Dox. The mechanism of PD@Dox was investigated through cell viability assays, apoptosis assays, Western blot analysis, and immunofluorescence staining. In vivo studies were performed using a TNBC tumor-bearing mouse model to assess the anticancer effects.

Results

Electron microscopic observations confirmed that platelet decoys and PD@Dox exhibited a round shape similar to normal platelets. Platelet decoys demonstrated superior drug uptake and loading capacity compared to platelets. Importantly, PD@Dox retained the ability to recognize and bind tumor cells. The released doxorubicin induced ICD, resulting in the release of tumor antigens and damage-related molecular patterns that recruit dendritic cells and activate antitumor immunity. Notably, the combination of PD@Dox and immune checkpoint blockade therapy using PD-1 antibody achieved significant therapeutic efficacy by blocking tumor immune escape and promoting ICD-induced T cell activation.

Conclusion

Our results suggest that PD@Dox, in combination with immune checkpoint blockade therapy, holds promise as a potential strategy for TNBC treatment.

Identification of risk factors for infection after mitral valve surgery through machine learning approaches

Background

Selecting features related to postoperative infection following cardiac surgery was highly valuable for effective intervention. We used machine learning methods to identify critical perioperative infection-related variables after mitral valve surgery and construct a prediction model.

Methods

Participants comprised 1223 patients who underwent cardiac valvular surgery at eight large centers in China. The ninety-one demographic and perioperative parameters were collected. Random forest (RF) and least absolute shrinkage and selection operator (LASSO) techniques were used to identify postoperative infection-related variables; the Venn diagram determined overlapping variables. The following ML methods: random forest (RF), extreme gradient boosting (XGBoost), Support Vector Machine (SVM), Gradient Boosting Decision Tree (GBDT), AdaBoost, Naive Bayesian (NB), Logistic Regression (LogicR), Neural Networks (nnet) and artificial neural network (ANN) were developed to construct the models. We constructed receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) was calculated to evaluate model performance.

Results

We identified 47 and 35 variables with RF and LASSO, respectively. Twenty-one overlapping variables were finally selected for model construction: age, weight, hospital stay, total red blood cell (RBC) and total fresh frozen plasma (FFP) transfusions, New York Heart Association (NYHA) class, preoperative creatinine, left ventricular ejection fraction (LVEF), RBC count, platelet (PLT) count, prothrombin time, intraoperative autologous blood, total output, total input, aortic cross-clamp (ACC) time, postoperative white blood cell (WBC) count, aspartate aminotransferase (AST), alanine aminotransferase (ALT), PLT count, hemoglobin (Hb), and LVEF. The prediction models for infection after mitral valve surgery were established based on these variables, and they all showed excellent discrimination performance in the test set (AUC > 0.79).

Conclusions

Key features selected by machine learning methods can accurately predict infection after mitral valve surgery, guiding physicians in taking appropriate preventive measures and diminishing the infection risk.

Study on the Role of an Erythrocyte Membrane-Coated Nanotheranostic System in Targeted Immune Regulation of Alzheimer's Disease

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases in the elderly population. Despite significant advances in studies of the pathobiology on AD, there is still no effective treatment. Here, an erythrocyte membrane-camouflaged nanodrug delivery system (TR-ZRA) modified with transferrin receptor aptamers that can be targeted across the blood-brain barrier to ameliorate AD immune environment is established. Based on metal-organic framework (Zn-CA), TR-ZRA is loaded with CD22shRNA plasmid to silence the abnormally high expression molecule CD22 in aging microglia. Most importantly, TR-ZRA can enhance the ability of microglia to phagocytose Aβ and alleviate complement activation, which can promote neuronal activity and decrease inflammation level in the AD brain. Moreover, TR-ZRA is also loaded with Aβ aptamers, which allow rapid and low-cost monitoring of Aβ plaques in vitro. After treatment with TR-ZRA, learning, and memory abilities are enhanced in AD mice. In conclusion, the biomimetic delivery nanosystem TR-ZRA in this study provides a promising strategy and novel immune targets for AD therapy.

Bioengineered stem cell membrane functionalized nanoparticles combine anti-inflammatory and antimicrobial properties for sepsis treatment

BACKGROUND

Sepsis is a syndrome of physiological, pathological and biochemical abnormalities caused by infection. Although the mortality rate is lower than before, many survivors have persistent infection, which means sepsis calls for new treatment. After infection, inflammatory mediators were largely released into the blood, leading to multiple organ dysfunction. Therefore, anti-infection and anti-inflammation are critical issues in sepsis management.

RESULTS

Here, we successfully constructed a novel nanometer drug loading system for sepsis management, FZ/MER-AgMOF@Bm. The nanoparticles were modified with LPS-treated bone marrow mesenchymal stem cell (BMSC) membrane, and silver metal organic framework (AgMOF) was used as the nanocore for loading FPS-ZM1 and meropenem which was delivery to the infectious microenvironments (IMEs) to exert dual anti-inflammatory and antibacterial effects. FZ/MER-AgMOF@Bm effectively alleviated excessive inflammatory response and eliminated bacteria. FZ/MER-AgMOF@Bm also played an anti-inflammatory role by promoting the polarization of macrophages to M2. When sepsis induced by cecal ligation and puncture (CLP) challenged mice was treated, FZ/MER-AgMOF@Bm could not only reduce the levels of pro-inflammatory factors and lung injury, but also help to improve hypothermia caused by septic shock and prolong survival time.

CONCLUSIONS

Together, the nanoparticles played a role in combined anti-inflammatory and antimicrobial properties, alleviating cytokine storm and protecting vital organ functions, could be a potential new strategy for sepsis management.

Combination therapy based on dual-target biomimetic nano-delivery system for overcoming cisplatin resistance in hepatocellular carcinoma

Strategies to overcome toxicity and drug resistance caused by chemotherapeutic drugs for targeted therapy against hepatocellular carcinoma (HCC) are urgently needed. Previous studies revealed that high oxidored-nitro domain-containing protein 1(NOR1) expression in HCC was associated with cisplatin (DDP) resistance. Herein, a novel dual-targeting nanocarrier system AR-NADR was generated for the treatment of DDP resistance in HCC. The core of the nanocarrier system is the metal-organic frameworks (MOF) modified with nuclear location sequence (NLS), which loading with DDP and NOR1 shRNA (R). The shell is an A54 peptide inserted into the erythrocyte membrane (AR). Our results show that AR-NADR efficiently internalized by tumor cells due to its specific binding to the A54 receptors that are abundantly expressed on the surface of HCC cells and NLS peptide-mediated nuclear entry. Additionally, DDP is more likely to be released due to the degradation of Ag-MOF in the acidic tumor microenvironment. Moreover, by acting as a vector for gene delivery, AR-NADR effectively inhibits tumor drug resistance by suppressing the expression of NOR1, which induces intracellular DDP accumulation and makes cells sensitive to DDP. Finally, the anti-HCC efficacy and mechanisms of AR-NADR were systematically elucidated by a HepG2/DDP cell model as well as a tumor model. Therefore, AR-NADR constitutes a key strategy to achieve excellent gene silencing and antitumor efficacy, which provides effective gene therapy and precise treatment strategies for cisplatin resistance in HCC.

Oligosaccharides isolated from Rehmannia glutinosa protect LPS-induced intestinal inflammation and barrier injury in mice

Objectives

We investigated the protective effect of Rehmannia glutinosa oligosaccharides (RGO) on lipopolysaccharide (LPS)-induced intestinal inflammation and barrier injury among mice.

Methods

RGO is prepared from fresh rehmannia glutinosa by water extraction, active carbon decolorization, ion exchange resin impurity removal, macroporous adsorption resin purification, and decompression drying. LPS could establish the model for intestinal inflammation and barrier injury in mice. Three different doses of RGO were administered for three consecutive weeks. Then the weight, feces, and health status of the mice were recorded. After sacrificing the mice, their colon length and immune organ index were determined. The morphological changes of the ileum and colon were observed using Hematoxylin-eosin (H&E) staining, followed by measuring the villus length and recess depth. RT-qPCR was utilized to detect the relative mRNA expression of intestinal zonula occludens-1 (ZO-1) and occludin. The expression of inflammatory factors and oxidation markers within ileum and colon tissues and the digestive enzyme activities in the ileum contents were detected using ELISA. The content of short-chain fatty acids (SCFAs) in the colon was determined with GC. The gut microbial composition and diversity changes were determined with 16S-rRNA high-throughput sequencing. The association between intestinal microorganisms and SCFAs, occludins, digestive enzymes, inflammatory factor contents, and antioxidant indexes was also analyzed.

Results

RGO significantly increased the weight, pancreatic index, thymus index, and colon length of mice compared with the model group. Moreover, it also improved the intestinal tissue structure and increased the expression of intestinal barrier-related junction proteins ZO-1 and Occludin. The contents of IL-6, IL-17, IL-1β, and TNF-α in the intestinal tissues of mice were significantly reduced. Additionally, the activities of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) were elevated. In contrast, the malondialdehyde (MDA) content decreased. Trypsin and pancreatic lipase activities in the ileum enhanced, and the SCFA contents such as acetic acid, propionic acid, and butyric acid in the colon increased. The study on intestinal flora revealed that RGO could enhance the abundance of intestinal flora and improve the flora structure. After RGO intervention, the relative abundance of Firmicutes, Lactobacillus, and Akkermania bacteria in the intestinal tract of mice increased compared with the model group, while that of Actinomycetes decreased. The intestinal microbiota structure changed to the case, with probiotics playing a dominant role. The correlation analysis indicated that Lactobacillus and Ackermann bacteria in the intestinal tract of mice were positively associated with SCFAs, Occludin, ZO-1, pancreatic amylase, SOD, and CAT activities. Moreover, they were negatively correlated with inflammatory factors IL-6, IL-17, IL-1β, and TNF-α.

Conclusions

RGO can decrease LPS-induced intestinal inflammation and intestinal barrier injury in mice and protect their intestinal function. RGO can ameliorate intestinal inflammation and maintain the intestinal barrier by regulating intestinal flora.

Discovering common pathogenetic processes between COVID-19 and sepsis by bioinformatics and system biology approach

Corona Virus Disease 2019 (COVID-19), an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread rapidly worldwide, resulting in a pandemic with a high mortality rate. In clinical practice, we have noted that many critically ill or critically ill patients with COVID-19 present with typical sepsis-related clinical manifestations, including multiple organ dysfunction syndrome, coagulopathy, and septic shock. In addition, it has been demonstrated that severe COVID-19 has some pathological similarities with sepsis, such as cytokine storm, hypercoagulable state after blood balance is disrupted and neutrophil dysfunction. Considering the parallels between COVID-19 and non-SARS-CoV-2 induced sepsis (hereafter referred to as sepsis), the aim of this study was to analyze the underlying molecular mechanisms between these two diseases by bioinformatics and a systems biology approach, providing new insights into the pathogenesis of COVID-19 and the development of new treatments. Specifically, the gene expression profiles of COVID-19 and sepsis patients were obtained from the Gene Expression Omnibus (GEO) database and compared to extract common differentially expressed genes (DEGs). Subsequently, common DEGs were used to investigate the genetic links between COVID-19 and sepsis. Based on enrichment analysis of common DEGs, many pathways closely related to inflammatory response were observed, such as Cytokine-cytokine receptor interaction pathway and NF-kappa B signaling pathway. In addition, protein-protein interaction networks and gene regulatory networks of common DEGs were constructed, and the analysis results showed that ITGAM may be a potential key biomarker base on regulatory analysis. Furthermore, a disease diagnostic model and risk prediction nomogram for COVID-19 were constructed using machine learning methods. Finally, potential therapeutic agents, including progesterone and emetine, were screened through drug-protein interaction networks and molecular docking simulations. We hope to provide new strategies for future research and treatment related to COVID-19 by elucidating the pathogenesis and genetic mechanisms between COVID-19 and sepsis.

Multi-center Retrospective Study of Factors Affecting Perioperative Transfusion of Packed Red Blood Cells for Pelvic Fracture Patients

Objective

To analyze the use of packed red blood cells (PRBCs) for patients with pelvic fracture and evaluate factors associated with PRBC transfusion for patients with pelvic fracture.

Methods

This retrospective cohort study collected 551 patients with pelvic fractures from six hospitals between September 1, 2012, and June 31, 2019. The age span of patients varied from 10 to 95 years old, and they were classified into two groups based on high‐energy pelvic fractures (HE‐PFs) or low‐energy pelvic fractures (LE‐PFs). The study's outcome was the use of PRBCs, fresh frozen plasma (FFP), and albumin. Demographic data, characteristics, laboratory tests, clinical treatment details, and clinical outcomes were compared between the two groups. Factors that were statistically associated with perioperative PRBCs in univariate analyses were included to conduct an optimal scale regression to determine the independent factors for perioperative PRBCs.

Results

A total of 551 patients were screened from six hospitals, and after inclusion and exclusion, 319 were finally included and finished the follow‐up from admission to discharge, while four patients died during hospitalization. Three hundred and nineteen patients were classified into two groups by their injury mechanisms. A total of 230/319 (72.1%) patients were classified into the HE‐PF group, and 89/319 (27.8%) patients were classified into the LE‐PF group. Patients in the HE‐PF group were transfused with 4.5 (3–8) units of PRBCs, 300 (0–600) ml of FFP, and 0 (0–30) g of albumin, while patients in the LE‐PF group were transfused with 3.5 (2–4.5) units of PRBCs, 0 (0–295) ml of FFP, and 0 (0–0) g of albumin (all P < 0.001). There were higher proportions of male patients and patients under 65 in the HE‐PF group (all P < 0.001). HE‐PF group patients were more severely injured and likely to take external fixation. The optimal scale regression revealed four significant factors associated with perioperative transfused PRBCs, which were patients on admission with hemorrhagic shock (importance = 0.283, P = 0.004), followed by fracture types identified by Tile classification (importance = 0.156, P < 0.001), hemoglobin levels below 70 g/L on admission (importance = 0.283, P = 0.004), followed by fracture types identified by Tile classification (importance = 0.156, P < 0.001), hemoglobin levels below 70 g/L on admission (importance = 0.148, P = 0.039), and methods of pelvic fixation (importance = 0.008, P = 0.026), ranked by the importance.

Conclusion

Patients with HE‐PFs had increased transfusions of PRBCs, FFP, and albumin, and hemorrhagic shock on admission, Tile classification, Hb levels, and stabilization methods were found to be associated with perioperative PRBCs.

A Novel Mutation Eliminates GATA-1 and RUNX1-Mediated Promoter Activity in Galactosyltransferase Gene

Introduction

Mutations in the promoter region and exons of ABO gene may cause changes in the expression of blood group antigens, often showing a weak ABO phenotype. Here, we identified a novel weak ABO subgroup allele that caused B_el phenotype and explored its mechanisms.

Methods

The ABO phenotype of subjects (Chinese Han nationality) was classified by serological method. The plasma activity of erythrocyte glycosyltransferase was detected by the phosphate coupling method. ABO subtype genotyping was performed by PCR-SSP and exon sequencing. The activity of the promoter was evaluated by a dual-luciferase reporter assay.

Results

We identified a mutation exon 1 c.15_16insTGTTG of the B allele in a B_el subject. Genealogical investigation showed that the mutation was inherited from her mother. The mutation was located in the promoter region of the ABO gene. The dual-luciferase reporter assay showed that the mutation inactivated GATA-1 and RUNX1-mediated activity of the ABO gene promoter, leading to a decrease in the expression and activity of B glycosyltransferase.

Conclusion

A novel B_var ABO subgroup allele was identified. The novel mutation can reduce the promoter activity that activated by GATA-1 and RUNX1, subsequently causing the B_el phenotype.

Combined Microbiome and Metabolome Analysis Reveals a Novel Interplay Between Intestinal Flora and Serum Metabolites in Lung Cancer

As the leading cause of cancer death, lung cancer seriously endangers human health and quality of life. Although many studies have reported the intestinal microbial composition of lung cancer, little is known about the interplay between intestinal microbiome and metabolites and how they affect the development of lung cancer. Herein, we combined 16S ribosomal RNA (rRNA) gene sequencing and liquid chromatography-mass spectrometry (LC-MS) technology to analyze intestinal microbiota composition and serum metabolism profile in a cohort of 30 lung cancer patients with different stages and 15 healthy individuals. Compared with healthy people, we found that the structure of intestinal microbiota in lung cancer patients had changed significantly (Adonis, p = 0.021). In order to determine how intestinal flora affects the occurrence and development of lung cancer, the Spearman rank correlation test was used to find the connection between differential microorganisms and differential metabolites. It was found that as thez disease progressed, L-valine decreased. Correspondingly, the abundance of Lachnospiraceae_UCG-006, the genus with the strongest association with L-valine, also decreased in lung cancer groups. Correlation analysis showed that the gut microbiome and serum metabolic profile had a strong synergy, and Lachnospiraceae_UCG-006 was closely related to L-valine. In summary, this study described the characteristics of intestinal flora and serum metabolic profiles of lung cancer patients with different stages. It revealed that lung cancer may be the result of the mutual regulation of L-valine and Lachnospiraceae_UCG-006 through the aminoacyl-tRNA biosynthesis pathway, and proposed that L-valine may be a potential marker for the diagnosis of lung cancer.

CircRNA-011235 Counteracts The Deleterious Effect of Irradiation Treatment on Bone Mesenchymal Stem Cells by Regulating The miR-741-3p/CDK6 Pathway

OBJECTIVE

The present work was aimed at uncovering the effect of circRNA-011235 (circ-011235) on irradiation-induced bone mesenchymal stem cells (BMSCs) injury and its regulatory mechanism, with a view to establish a scientific basis for its possible medical applications.

MATERIALS AND METHODS

In this experimental study, after irradiation with different doses (0, 2, 4, 6 GY), the relative expression levels of circ-011235, miR-741-3p, and cyclin-dependent kinases 6 (CDK6) were detected in the BMSCs, using the real time-quantitative polymerase chain reaction (RT-qPCR). The overexpression effects of circ-011235 and CDK6 on the cell proliferation in irradiation-treated BMSCs were measured by the Cell Counting Kit-8 (CCK8) assay. And also, their effects on the cell cycle were evaluated by flow cytometry. RT-qPCR and immunoblotting were performed to detect the effects of pcDNA-circ-011235 and pcDNA-CDK6 on the expression of cyclin D1 and cyclindependent kinases 4 (CDK6) at the gene and protein levels, respectively.

RESULTS

Irradiation treatment elevated the expression of circ-011235 and CDK6, but reduced miR-741-3p expression in the BMSCs with a dose-dependent effect. The proliferation of BMSCs was significantly inhibited in the irradiation treatment group, while the overexpression of circ-011235 and CDK6 effectively attenuated this inhibition. Also, overexpression of circ-011235 and CDK6 elevated the expression of cyclin D1 in irradiation-treated BMSCs, but had no significant effect on the CDK4 expression.

CONCLUSION

Our results demonstrated that circ-011235 up-regulated the expression of cyclin D1 via miR-741-3p/ CDK6 signal pathway, thereby promoting cell cycle progression and proliferation of irradiation-treated BMSCs. This finding suggested circ-011235/ miR-741-3p/CDK6 pathway exerted a protective role in the response to irradiation and will be a potential new target for future research on the mechanism involved in the resistance of BMSCs to radiation.

Advancing Prediction of Risk of Intraoperative Massive Blood Transfusion in Liver Transplantation With Machine Learning Models. A Multicenter Retrospective Study

Background

Liver transplantation surgery is often accompanied by massive blood loss and massive transfusion (MT), while MT can cause many serious complications related to high mortality. Therefore, there is an urgent need for a model that can predict the demand for MT to reduce the waste of blood resources and improve the prognosis of patients.

Objective

To develop a model for predicting intraoperative massive blood transfusion in liver transplantation surgery based on machine learning algorithms.

Methods

A total of 1,239 patients who underwent liver transplantation surgery in three large grade lll-A general hospitals of China from March 2014 to November 2021 were included and analyzed. A total of 1193 cases were randomly divided into the training set (70%) and test set (30%), and 46 cases were prospectively collected as a validation set. The outcome of this study was an intraoperative massive blood transfusion. A total of 27 candidate risk factors were collected, and recursive feature elimination (RFE) was used to select key features based on the Categorical Boosting (CatBoost) model. A total of ten machine learning models were built, among which the three best performing models and the traditional logistic regression (LR) method were prospectively verified in the validation set. The Area Under the Receiver Operating Characteristic Curve (AUROC) was used for model performance evaluation. The Shapley additive explanation value was applied to explain the complex ensemble learning models.

Results

Fifteen key variables were screened out, including age, weight, hemoglobin, platelets, white blood cells count, activated partial thromboplastin time, prothrombin time, thrombin time, direct bilirubin, aspartate aminotransferase, total protein, albumin, globulin, creatinine, urea. Among all algorithms, the predictive performance of the CatBoost model (AUROC: 0.810) was the best. In the prospective validation cohort, LR performed far less well than other algorithms.

Conclusion

A prediction model for massive blood transfusion in liver transplantation surgery was successfully established based on the CatBoost algorithm, and a certain degree of generalization verification is carried out in the validation set. The model may be superior to the traditional LR model and other algorithms, and it can more accurately predict the risk of massive blood transfusions and guide clinical decision-making.

Machine Learning for the Prediction of Complications in Patients After Mitral Valve Surgery

Background: This study intended to use a machine learning model to identify critical preoperative and intraoperative variables and predict the risk of several severe complications (myocardial infarction, stroke, renal failure, and hospital mortality) after cardiac valvular surgery.

Study Design and Methods: A total of 1,488 patients undergoing cardiac valvular surgery in eight large tertiary hospitals in China were examined. Fifty-four perioperative variables, such as essential demographic characteristics, concomitant disease, preoperative laboratory indicators, operation type, and intraoperative information, were collected. Machine learning models were developed and validated by 10-fold cross-validation. In each fold, Recursive Feature Elimination was used to select key variables. Ten machine learning models and logistic regression were developed. The area under the receiver operating characteristic (AUROC), accuracy (ACC), Youden index, sensitivity, specificity, F1-score, positive predictive value (PPV), and negative predictive value (NPV) were used to compare the prediction performance of different models. The SHapley Additive ex Planations package was applied to interpret the best machine learning model. Finally, a model was trained on the whole dataset with the merged key variables, and a web tool was created for clinicians to use.

Results: In this study, 14 vital variables, namely, intraoperative total input, intraoperative blood loss, intraoperative colloid bolus, Classification of New York Heart Association (NYHA) heart function, preoperative hemoglobin (Hb), preoperative platelet (PLT), age, preoperative fibrinogen (FIB), intraoperative minimum red blood cell volume (Hct), body mass index (BMI), creatinine, preoperative Hct, intraoperative minimum Hb, and intraoperative autologous blood, were finally selected. The eXtreme Gradient Boosting algorithms (XGBOOST) algorithm model presented a significantly better predictive performance (AUROC: 0.90) than the other models (ACC: 81%, Youden index: 70%, sensitivity: 89%, specificity: 81%, F1-score:0.26, PPV: 15%, and NPV: 99%).

Conclusion: A model for predicting several severe complications after cardiac valvular surgery was successfully developed using a machine learning algorithm based on 14 perioperative variables, which could guide clinical physicians to take appropriate preventive measures and diminish the complications for patients at high risk.

A novel biomimetic nanomedicine system with anti-inflammatory and anti-osteoporosis effects improves the therapy efficacy of steroid-resistant nephrotic syndrome

Clinically, steroid-resistant nephrotic syndrome (SRNS) is always prolonged and difficult to treat and easily develops into end-stage renal disease, resulting in a low survival rate. Strategies to reverse steroid resistance and reduce the long-term use of high doses of steroid medicines are urgently needed. In this study, a novel nanoparticle drug system (Pm-GCH) with a core–shell structure was designed. Metal–organic frameworks, synthesized by glycyrrhizic acid (G) and calcium ions (Ca²⁺) loaded with hydrocortisone (H) were the core of the nanoparticles. Platelet membrane vesicles were the shells. The natural platelet membrane endows Pm-GCH with good biocompatibility and the ability to promote immune escape. In addition, under the chemotaxis of inflammatory factors, platelet membranes assist Pm-GCH in nonspecific targeting of the inflammatory sites of the kidney. Under an inflammatory acid environment, GCH slowly degrades and releases glycyrrhizic acid and hydrocortisone. Glycyrrhizic acid inhibits the inactivation of hydrocortisone, jointly inhibits the activity of phospholipase A2 (PLA2) and the classic activation pathway of complement C2, blocks the production of inflammatory factors, plays an anti-inflammatory role, and enhances the efficacy of hydrocortisone in the treatment of SRNS. Moreover, glycyrrhizic acid alleviates osteoporosis induced by long-term use of glucocorticoids. These results indicate that Pm-GCH is a promising treatment strategy for SRNS.

Identification and Validation of the Pyroptosis-Related Molecular Subtypes of Lung Adenocarcinoma by Bioinformatics and Machine Learning

Lung cancer remains the leading cause of cancer death globally, with lung adenocarcinoma (LUAD) being its most prevalent subtype. Due to the heterogeneity of LUAD, patients given the same treatment regimen may have different responses and clinical outcomes. Therefore, identifying new subtypes of LUAD is important for predicting prognosis and providing personalized treatment for patients. Pyroptosis-related genes play an essential role in anticancer, but there is limited research investigating pyroptosis in LUAD. In this study, 33 pyroptosis gene expression profiles and clinical information were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. By bioinformatics and machine learning analyses, we identified novel subtypes of LUAD based on 10 pyroptosis-related genes and further validated them in the GEO dataset, with machine learning models performing up to an AUC of 1 for classifying in GEO. A web-based tool was established for clinicians to use our clustering model (http://www.aimedicallab.com/tool/aiml-subphe-luad.html). LUAD patients were clustered into 3 subtypes (A, B, and C), and survival analysis showed that B had the best survival outcome and C had the worst survival outcome. The relationships between pyroptosis gene expression and clinical characteristics were further analyzed in the three molecular subtypes. Immune profiling revealed significant differences in immune cell infiltration among the three molecular subtypes. GO enrichment and KEGG pathway analyses were performed based on the differential genes of the three subtypes, indicating that differentially expressed genes (DEGs) were involved in multiple cellular and biological functions, including RNA catabolic process, mRNA catabolic process, and pathways of neurodegeneration-multiple diseases. Finally, we developed an 8-gene prognostic model that accurately predicted 1-, 3-, and 5-year overall survival. In conclusion, pyroptosis-related genes may play a critical role in LUAD, and provide new insights into the underlying mechanisms of LUAD.

Environmental level bisphenol A accelerates alterations of the reno-cardiac axis by the MAPK cascades in male diabetic rats: An analysis based on transcriptomic profiling and bioinformatics

In humans and animal models, the kidneys and cardiovascular systems are negatively affected by BPA from the environment. It is considered that BPA have some potential estrogen-like and non-hormone-like properties. In this study, RNA-sequencing and its-related bioinformatics was used as the basic strategy to clarify the characteristic mechanisms of kidney-heart axis remodeling and dysfunction in diabetic male rats under BPA exposure. We found that continuous BPA exposure in diabetic rats aggravated renal impairment, and caused hemodynamic disorders and dysfunctions. There were 655 and 125 differentially expressed genes in the kidney and heart, respectively. For the kidneys, functional annotation and enrichment, and gene set enrichment analyses identified bile acid secretion related to lipid synthesis and transport, and MAPK cascade pathways. For the heart, these bioinformatics analyses clearly pointed to MAPKs pathways. A total of 12 genes and another total of 6 genes were identified from the kidney tissue and heart tissue, respectively. Western blotting showed that exposure to BPA activated MAPK cascades in both organs. In this study, the exacerbated remodeling of diabetic kidney-heart axis under BPA exposure and diabetes might occur through hemodynamics, metabolism disorders, and the immune-inflammatory response, as well as continuous estrogen-like stimulation, with focus on the MAPK cascades.

A Novel Intercellular Communication-Associated Gene Signature for Prognostic Prediction and Clinical Value in Patients With Lung Adenocarcinoma

Background

Lung cancer remains the leading cause of cancer death globally, with lung adenocarcinoma (LUAD) being its most prevalent subtype. This study aimed to identify the key intercellular communication-associated genes (ICAGs) in LUAD.

Methods

Eight publicly available datasets were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The prognosis-related ICAGs were identified and a risk score was developed by using survival analysis. Machine learning models were trained to predict LUAD recurrence based on the selected ICAGs and clinical information. Comprehensive analyses on ICAGs and tumor microenvironment were performed. A single-cell RNA-sequencing dataset was assessed to further elucidate aberrant changes in intercellular communication.

Results

Eight ICAGs with prognostic potential were identified in the present study, and a risk score was derived accordingly. The best machine-learning model to predict relapse was developed based on clinical information and the expression levels of these eight ICAGs. This model achieved a remarkable area under receiver operator characteristic curves of 0.841. Patients were divided into high- and low-risk groups according to their risk scores. DNA replication and cell cycle were significantly enriched by the differentially expressed genes between the high- and the low-risk groups. Infiltrating immune cells, immune functions were significantly related to ICAGs expressions and risk scores. Additionally, the changes of intercellular communication were modeled by analyzing the single-cell sequencing dataset.

Conclusion

The present study identified eight key ICAGs in LUAD, which could contribute to patient stratification and act as novel therapeutic targets.

Ability of a Machine Learning Algorithm to Predict the Need for Perioperative Red Blood Cells Transfusion in Pelvic Fracture Patients: A Multicenter Cohort Study in China

Background: Predicting the perioperative requirement for red blood cells (RBCs) transfusion in patients with the pelvic fracture may be challenging. In this study, we constructed a perioperative RBCs transfusion predictive model (ternary classifications) based on a machine learning algorithm.

Materials and Methods: This study included perioperative adult patients with pelvic trauma hospitalized across six Chinese centers between September 2012 and June 2019. An extreme gradient boosting (XGBoost) algorithm was used to predict the need for perioperative RBCs transfusion, with data being split into training test (80%), which was subjected to 5-fold cross-validation, and test set (20%). The ability of the predictive transfusion model was compared with blood preparation based on surgeons' experience and other predictive models, including random forest, gradient boosting decision tree, K-nearest neighbor, logistic regression, and Gaussian naïve Bayes classifier models. Data of 33 patients from one of the hospitals were prospectively collected for model validation.

Results: Among 510 patients, 192 (37.65%) have not received any perioperative RBCs transfusion, 127 (24.90%) received less-transfusion (RBCs < 4U), and 191 (37.45%) received more-transfusion (RBCs ≥ 4U). Machine learning-based transfusion predictive model produced the best performance with the accuracy of 83.34%, and Kappa coefficient of 0.7967 compared with other methods (blood preparation based on surgeons' experience with the accuracy of 65.94%, and Kappa coefficient of 0.5704; the random forest method with an accuracy of 82.35%, and Kappa coefficient of 0.7858; the gradient boosting decision tree with an accuracy of 79.41%, and Kappa coefficient of 0.7742; the K-nearest neighbor with an accuracy of 53.92%, and Kappa coefficient of 0.3341). In the prospective dataset, it also had a food performance with accuracy 81.82%.

Conclusion: This multicenter retrospective cohort study described the construction of an accurate model that could predict perioperative RBCs transfusion in patients with pelvic fractures.

Circulating exosomal circFoxp1 confers cisplatin resistance in epithelial ovarian cancer cells

Objective

Early detection and treatment are particularly important to epithelial ovarian cancer (EOC). Studies have shown that circular RNA (circRNA) dysregulation is associated with the proliferation and metastasis of ovarian cancer cells. This study focused on the role of serum exosomal circular forkhead box protein P1 (circFoxp1) on survival outcome and cisplatin (DDP) resistance in patients with EOC.

Methods

Quantitative polymerase chain reaction, 5-ethynyl-2′-deoxyuridine (EdU) staining, CCK-8, luciferase reporter assay, RNA immunoprecipitation, tumor xenograft in nude mice, and bioinformatic analysis were performed.

Results

Circulating exosomal circFoxp1 was significantly increased in patients with EOC, especially in DDP-resistant EOC patients. circFoxp1 expression was positively associated with International Federation of Gynecology and Obstetrics stage, primary tumor size, lymphatic metastasis, distant metastasis, residual tumor diameter, and clinical response. Exosomal circFoxp1 also was an independent factor predicting survival and disease recurrence in patients with EOC. Overexpression of circFoxp1 could promote cell proliferation and confer DDP resistance, while knockdown of circFoxp1 could inhibit cell proliferation and enhance DDP sensitivity in vitro and in vivo. In addition, miR-22 and miR-150-3p mimic treatment attenuated circFoxp1-meadiated DDP resistance, while miR-22 and miR-150-3p inhibitor treatment enhanced DDP resistance that mitigated by circFoxp1 knockdown. Furthermore, circFoxp1 positively regulated the expression of CCAAT enhancer binding protein gamma (CEBPG) and formin like 3 (FMNL3) through miR-22 and miR-150-3p.

Conclusions

circFoxp1 is an oncogene in EOC cells and can confer DDP resistance to EOC cells. Circulating exosomal circFoxp1 can be used as a biomarker and potential therapeutic target for EOC.

Platelet membrane-camouflaged silver metal-organic framework drug system against infections caused by methicillin-resistant Staphylococcus aureus

Background

Due to the intelligent survival strategy and self-preservation of methicillin-resistant Staphylococcus aureus (MRSA), many antibiotics are ineffective in treating MRSA infections. Nano-drug delivery systems have emerged as a new method to overcome this barrier. The aim of this study was to construct a novel nano-drug delivery system for the treatment of MRSA infection, and to evaluate the therapeutic effect and biotoxicity of this system. We prepared a nano silver metal-organic framework using 2-methylimidazole as ligand and silver nitrate as ion provider. Vancomycin (Vanc) was loaded with Ag-MOF, and nano-sized platelet vesicles were prepared to encapsulate Ag-MOF-Vanc, thus forming the novel platelet membrane-camouflaged nanoparticles PLT@Ag-MOF-Vanc.

Results

The synthesized Ag-MOF particles had uniform size and shape of radiating corona. The mean nanoparticle size and zeta potential of PLT@Ag-MOF-Vanc were 148 nm and − 25.6 mV, respectively. The encapsulation efficiency (EE) and loading efficiency (LE) of vancomycin were 81.0 and 64.7 %, respectively. PLT@Ag-MOF-Vanc was shown to be a pH-responsive nano-drug delivery system with good biocompatibility. Ag-MOF had a good inhibitory effect on the growth of three common clinical strains (Escherichia coli, Pseudomonas aeruginosa, and S. aureus). PLT@Ag-MOF-Vanc showed better antibacterial activity against common clinical strains in vitro than free vancomycin. PLT@Ag-MOF-Vanc killed MRSA through multiple approaches, including interfering with the metabolism of bacteria, catalyzing reactive oxygen species production, destroying the integrity of cell membrane, and inhibiting biofilm formation. Due to the encapsulation of the platelet membrane, PLT@Ag-MOF-Vanc can bind to the surface of the MRSA bacteria and the sites of MRSA infection. PLT@Ag-MOF-Vanc had a good anti-infective effect in mouse MRSA pneumonia model, which was significantly superior to free vancomycin, and has no obvious toxicity.

Conclusions

PLT@Ag-MOF-Vanc is a novel effective targeted drug delivery system, which is expected to be used safely in anti-infective therapy of MRSA.

Graphic abstract

Novel Multifunctional Silver Nanocomposite Serves as a Resistance-Reversal Agent to Synergistically Combat Carbapenem-Resistant Acinetobacter baumannii

In the face of the abundant production of various types of carbapenemases, the antibacterial efficiency of imipenem, seen as "the last line of defense", is weakening. Following, the incidence of carbapenem-resistant Acinetobacter baumannii (CRAB), which can generate antibiotic-resistant biofilms, is increasing. Based on the superior antimicrobial activity of silver nanoparticles against multifarious bacterial strains compared with common antibiotics, we constructed the IPM@AgNPs-PEG-NOTA nanocomposite (silver nanoparticles were coated with SH-PEG-NOTA as well as loaded by imipenem) whose core was a silver nanoparticle to address the current challenge, and IPM@AgNPs-PEG-NOTA was able to function as a novel smart pH-sensitive nanodrug system. Synergistic bactericidal effects of silver nanoparticles and imipenem as well as drug-resistance reversal via protection of the β-ring of carbapenem due to AgNPs-PEG-NOTA were observed; thus, this nanocomposite confers multiple advantages for efficient antibacterial activity. Additionally, IPM@AgNPs-PEG-NOTA not only offers immune regulation and accelerates tissue repair to improve therapeutic efficacy in vivo but also can prevent the interaction of pathogens and hosts. Compared with free imipenem or silver nanoparticles, this platform significantly enhanced antibacterial efficiency while increasing reactive oxygen species (ROS) production and membrane damage, as well as affecting cell wall formation and metabolic pathways. According to the results of crystal violet staining, LIVE/DEAD backlight bacterial viability staining, and real-time quantitative polymerase chain reaction (RT-qPCR), this silver nanocomposite downregulated the levels of ompA expression to prevent formation of biofilms. In summary, this research demonstrated that the IPM@AgNPs-PEG-NOTA nanocomposite is a promising antibacterial agent of security, pH sensitivity, and high efficiency in reversing resistance and synergistically combatting carbapenem-resistant A. baumannii. In the future, various embellishments and selected loads for silver nanoparticles will be the focus of research in the domains of medicine and nanotechnology.

Identification of a Ferroptosis-Related LncRNA Signature as a Novel Prognosis Model for Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is a highly heterogeneous malignancy, which makes prognosis prediction of LUAD very challenging. Ferroptosis is an iron-dependent cell death mechanism that is important in the survival of tumor cells. Long non-coding RNAs (lncRNAs) are considered to be key regulators of LUAD development and are involved in ferroptosis of tumor cells, and ferroptosis-related lncRNAs have gradually emerged as new targets for LUAD treatment and prognosis. It is essential to determine the prognostic value of ferroptosis-related lncRNAs in LUAD. In this study, we obtained RNA sequencing (RNA-seq) data and corresponding clinical information of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and ferroptosis-related lncRNAs by co-expression analysis. The best predictors associated with LUAD prognosis, including C5orf64, LINC01800, LINC00968, LINC01352, PGM5-AS1, LINC02097, DEPDC1-AS1, WWC2-AS2, SATB2-AS1, LINC00628, LINC01537, LMO7DN, were identified by Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis, and the LUAD risk prediction model was successfully constructed. Kaplan-Meier analysis, receiver operating characteristic (ROC) time curve analysis and univariate and multivariate Cox regression analysis and further demonstrated that the model has excellent robustness and predictive ability. Further, based on the risk prediction model, functional enrichment analysis revealed that 12 prognostic indicators involved a variety of cellular functions and signaling pathways, and the immune status was different in the high-risk and low-risk groups. In conclusion, a risk model of 12 ferroptosis related lncRNAs has important prognostic value for LUAD and may be ferroptosis-related therapeutic targets in the clinic.

Biomimetic nanotherapy: core-shell structured nanocomplexes based on the neutrophil membrane for targeted therapy of lymphoma

Background

Non-Hodgkin’s lymphoma (NHL) is a malignant disease of lymphoid tissue. At present, chemotherapy is still the main method for the treatment of NHL. R-CHOP can significantly improve the survival rate of patients. Unfortunately, DOX is the main cytotoxic drug in R-CHOP and it can lead to adverse reactions. Therefore, it is particularly important to uncover new treatment options for NHL.

Results

In this study, a novel anti-tumor nanoparticle complex Nm@MSNs-DOX/SM was designed and constructed in this study. Mesoporous silica nanoparticles (MSNs) loaded with Doxorubicin (DOX) and anti-inflammatory drugs Shanzhiside methylester (SM) were used as the core of nanoparticles. Neutrophil membrane (Nm) can be coated with multiple nanonuclei as a shell. DOX combined with SM can enhance the anti-tumor effect, and induce apoptosis of lymphoma cells and inhibit the expression of inflammatory factors related to tumorigenesis depending on the regulation of Bcl-2 family-mediated mitochondrial pathways, such as TNF-α and IL-1β. Consequently, the tumor microenvironment (TME) was reshaped, and the anti-tumor effect of DOX was amplified. Besides, Nm has good biocompatibility and can enhance the EPR effect of Nm@MSNs-DOX/SM and increase the effect of active targeting tumors.

Conclusions

This suggests that the Nm-modified drug delivery system Nm@MSNs-DOX/SM is a promising targeted chemotherapy and anti-inflammatory therapy nanocomplex, and may be employed as a specific and efficient anti-Lymphoma therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-021-00922-4.

Effect of time delay in a bistable synthetic gene network

The essence of logical stochastic resonance is the dynamic manipulation of potential wells. The effect of time delay on the depth of potential wells and the width of a bistable region can be inferred by logic operations in the bistable system with time delay. In a time-delayed synthetic gene network, time delay in the synthesis process can increase the depth of the potential wells, while that in the degradation process, it can reduce the depth of the potential wells, which will result in a decrease in the width of the bistable region (the reason for time delay to induce logic operations without external driving force) and the instability of the system (oscillation). These two opposite effects imply stretching and folding, leading to complex dynamical behaviors of the system, including period, chaos, bubble, chaotic bubble, forward and reverse period doubling bifurcation, intermittency, and coexisting attractors.

Zirconia Nanoparticles Induce HeLa Cell Death Through Mitochondrial Apoptosis and Autophagy Pathways Mediated by ROS

Zirconia nanoparticles (ZrO₂ NPs) are commonly used in the field of biomedical materials, but their antitumor activity and mechanism is unclear. Herein, we evaluated the anti-tumor activity of ZrO₂ NPs and explored the anti-tumor mechanism. The results of in vitro and in vivo experiments showed that the level of intracellular reactive oxygen species (ROS) in HeLa cells was elevated after ZrO₂ NPs treatment. Transmission electron microscopy (TEM) showed that after treatment with ZrO₂ NPs, the mitochondria of HeLa cells were swollen, accompanied with the induction of autophagic vacuoles. In addition, flow cytometry analysis showed that the apoptotic rate of HeLa cells increased significantly by Annexin staining after treatment with ZrO₂ NPs, and the mitochondrial membrane potential (MMP) was reduced significantly. The proliferation of HeLa cells decreased as indicated by reduced Ki-67 labeling. In contrast, TUNEL-positive cells in tumor tissues increased after treatment with ZrO₂ NPs, which is accompanied by increased expression of mitochondrial apoptotic proteins including Bax, Caspase-3, Caspase-9, and Cytochrome C (Cyt C) and increased expression of autophagy-related proteins including Atg5, Atg12, Beclin-1, and LC3-II. Treating HeLa cells with N-acetyl-L-cysteine (NAC) significantly reduced ROS, rate of apoptosis, MMP, and in vivo anti-tumor activity. In addition, apoptosis- and autophagy-related protein expressions were also suppressed. Based on these observations, we conclude that ZrO₂ NPs induce HeLa cell death through ROS mediated mitochondrial apoptosis and autophagy.

Machine Learning for the Prediction of Red Blood Cell Transfusion in Patients During or After Liver Transplantation Surgery

Aim: This study aimed to use machine learning algorithms to identify critical preoperative variables and predict the red blood cell (RBC) transfusion during or after liver transplantation surgery. Study Design and Methods: A total of 1,193 patients undergoing liver transplantation in three large tertiary hospitals in China were examined. Twenty-four preoperative variables were collected, including essential population characteristics, diagnosis, symptoms, and laboratory parameters. The cohort was randomly split into a train set (70%) and a validation set (30%). The Recursive Feature Elimination and eXtreme Gradient Boosting algorithms (XGBOOST) were used to select variables and build machine learning prediction models, respectively. Besides, seven other machine learning models and logistic regression were developed. The area under the receiver operating characteristic (AUROC) was used to compare the prediction performance of different models. The SHapley Additive exPlanations package was applied to interpret the XGBOOST model. Data from 31 patients at one of the hospitals were prospectively collected for model validation. Results: In this study, 72.1% of patients in the training set and 73.2% in the validation set underwent RBC transfusion during or after the surgery. Nine vital preoperative variables were finally selected, including the presence of portal hypertension, age, hemoglobin, diagnosis, direct bilirubin, activated partial thromboplastin time, globulin, aspartate aminotransferase, and alanine aminotransferase. The XGBOOST model presented significantly better predictive performance (AUROC: 0.813) than other models and also performed well in the prospective dataset (accuracy: 76.9%). Discussion: A model for predicting RBC transfusion during or after liver transplantation was successfully developed using a machine learning algorithm based on nine preoperative variables, which could guide high-risk patients to take appropriate preventive measures.

CircRNA-016901 silencing attenuates irradiation-induced injury in bone mesenchymal stem cells via regulating the miR-1249-5p/HIPK2 axis

Currently, bone marrow transplantation remains the basic treatment for various hematological tumors and irradiation is one of the most important pretreatment methods. However, irradiation pretreatment may result in damage to bone mesenchymal stem cells (BMSCs). The present study aimed to investigate the effect of circular RNA-016901 (circ-016901) on the injury of irradiation-induced BMSCs and the underlying mechanism. The expression levels of circ-016901, microRNA-1249-5p (miR-1249-5p) and homeodomain interacting protein kinase 2 (HIPK2) in irradiation-induced mouse BMSCs at various irradiation doses were detected via reverse transcription-quantitative PCR (RT-qPCR). The effect of circ-016901 on cell proliferation was examined using Cell Counting Kit-8 assays following silencing or overexpression of circ-016901. Cell apoptosis was detected by flow cytometry and caspase-3/7 activity. The expression of autophagy-related markers, including Beclin-1 and LC3-II/I, was detected at the mRNA and protein levels by RT-qPCR and western blotting, respectively. Irradiation treatment upregulated the expression of circ-016901 and HIPK2 and downregulated miR-1249-5p expression. The expression levels of LC3-II/I and Beclin-1 in BMSCs were downregulated in a dose-dependent manner. Silencing of circ-016901 promoted proliferation of irradiation-induced BMSCs and attenuated irradiation-induced apoptosis. Moreover, silencing of circ-016901 elevated the expressions of LC3-II/I and Beclin-1 in irradiation-induced BMSCs. Similar results were obtained with miR-1249-5p overexpression and HIPK2 silencing. These results demonstrated that circ-016901 silencing attenuated injury in irradiation-induced mouse BMSCs by regulating the miR-1249-5p/HIPK2 axis, providing a novel target for future research on the mechanism of radiation resistance in BMSCs.

A survey of laboratory biosafety and protective measures in blood transfusion departments during the COVID-19 pandemic

Background and objectives

Thousands of healthcare workers (HCWs) have been infected with 2019 novel coronavirus pneumonia (COVID‐19) during the COVID‐19 pandemic. Laboratory personnel in blood transfusion departments may be infected with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) if laboratory biosafety protection is insufficient. Therefore, we investigated the current situation of laboratory biosafety protection in blood transfusion departments to determine how to improve the safety of laboratory processes.

Materials and methods

An online survey was conducted in blood transfusion departments from 1st to 6th May 2020 in China. A total of 653 individuals completed the questionnaire. The questionnaire was designed with reference to COVID‐19 laboratory biosafety summarized in Annex II. All responses were summarized using only descriptive statistics and expressed as frequencies and ratios [n (%)].

Results

Most participants were concerned about COVID‐19. Some participants had inadequate knowledge of COVID‐19. Two participants stated that there were laboratory personnel infected with SARS‐CoV‐2 in their departments. A total of 31 (4.7%) participants did not receive any safety and security training. In terms of laboratory biosafety protection practices, the major challenges were suboptimal laboratory safety practices and insufficient laboratory conditions.

Conclusion

The major deficiencies were insufficient security and safety training, and a lack of personal protective equipment, automatic cap removal centrifuges and biosafety cabinets. Consequently, we should enhance the security and safety training of laboratory personnel to improve their laboratory biosafety protection practices and ensure that laboratory conditions are sufficient to improve the safety of laboratory processes.

Enhanced logical chaotic resonance

It was demonstrated recently that logical chaotic resonance (LCR) can be observed in a bistable system. In other words, the system can operate robustly as a specific logic gate in an optimal window of chaotic signal intensity. Here, we report that the size of the optimal window of chaotic signal intensity can be remarkably extended by exploiting the constructive interaction of chaotic signal and periodic force, as well as coupling, in a coupled bistable system. In addition, medium-frequency periodic force and an increasing system size can also lead to an improvement in the response speed of logic devices. The results are corroborated by circuit experiments. Taken together, a reliable and rapid-response logic operation can be realized based on periodic force- and array-enhanced LCR.

Construction of homologous cancer cell membrane camouflage in a nano-drug delivery system for the treatment of lymphoma

BACKGROUND

Non-Hodgkin's lymphoma (NHL) possesses great heterogeneity in cytogenetics, immunophenotype and clinical features, and chemotherapy currently serves as the main treatment modality. Although employing monoclonal antibody targeted drugs has significantly improved its overall efficacy, various patients continue to suffer from drug resistance or recurrence. Chinese medicine has long been used in the treatment of malignant tumors. Therefore, we constructed a low pH value sensitivity drug delivery system based on the cancer cell membrane modified mesoporous silica nanoparticles loaded with traditional Chinese medicine, which can reduce systemic toxicity and improve the therapeutic effect for the targeted drug delivery of tumor cells.

RESULTS

Accordingly, this study put forward the construction of a nano-platform based on mesoporous silica nanoparticles (MSNs) loaded with the traditional Chinese medicine isoimperatorin (ISOIM), which was camouflaged by the cancer cell membrane (CCM) called CCM@MSNs-ISOIM. The proposed nano-platform has characteristics of immune escape, anti-phagocytosis, high drug loading rate, low pH value sensitivity, good biocompatibility and active targeting of the tumor site, blocking the lymphoma cell cycle and promoting mitochondrial-mediated apoptosis.

CONCLUSIONS

Furthermore, this study provides a theoretical basis in finding novel clinical treatments for lymphoma.

Long Non-coding RNA GAS5 Maintains Insulin Secretion by Regulating Multiple miRNAs in INS-1 832/13 Cells

Type-2 diabetes mellitus (T2DM) is a complex disease characterized by reduced pancreatic islets β-cell mass and impaired insulin release from these cells. Non-coding RNAs, including microRNAs (miRNA) and long non-coding RNAs (lncRNAs), play a role in the progression of T2DM. Decreased serum lncRNA GAS5 levels were reported to be associated with T2DM. However, the role of GAS5 in regulating islet cell functions remain unknown. In this study, we found that the serum levels of GAS5 were significantly lower in patients with T2DM compared with healthy control subjects, and the low serum GAS5 levels were associated with high levels of HbAlc and fasting glucose in patients with T2DM. In addition, we found that serum GAS5 levels were negatively correlated with the serum levels of miR-29a-3p, miR-96-3p, and miR-208a-3p in patients with T2DM. Consequently, using INS-1 832/13 rat β-cell line, we found that overexpression of GAS5 by lentivirus infection increased glucose-stimulated insulin secretion and insulin content compared with negative control, whereas knockdown of GAS5 expression reduced both them. Moreover, GAS5 interacted with miR-29a-3p, miR-96-3p, and miR-208a-3p in INS-1 832/13 cells, as judged by pull-down assay and dual luciferase reporter assay. GAS5 overexpression caused the decrease in expression of miR-29a-3p, miR-96-3p, and miR-208a-3p in INS-1 832/13 cells and conversely caused the increase in expression of insulin receptor, insulin receptor substrate, and phosphoinositide-3-kinase regulatory subunit 1. Thus, these results reveal a novel mechanism whereby GAS5 is involved in maintaining insulin secretion and may represent a novel therapeutic target for T2DM.

Correlation analysis of coagulation dysfunction and liver damage in patients with novel coronavirus pneumonia: a single-center, retrospective, observational study

BACKGROUND

The novel coronavirus disease 2019 (COVID-19) is currently breaking out worldwide. COVID-19 patients may have different degrees of coagulopathy, but the mechanism is not yet clear. We aimed to analyse the relationship between coagulation dysfunction and liver damage in patients with COVID-19.

METHODS

A retrospective analysis of 74 patients with COVID-19 admitted to the First People's Hospital of Yueyang from 1 January to 30 March 2020 was carried out. According to the coagulation function, 27 cases entered the coagulopathy group and 47 cases entered the control group. A case control study was conducted to analyse the correlation between the occurrence of coagulation dysfunction and liver damage in COVID-19 patients.

RESULTS

Alanine aminotransferase (ALT) and aspartate aminotransferase (AST), markers of liver damage, were positively correlated with coagulopathy (p = 0.039, OR 2.960, 95% CI 1.055-8.304; and p = 0.028, OR 3.352, 95% CI 1.137-9.187). Alkaline phosphatase (ALP), γ-glutamyl transpeptidase (γ-GT), and total bilirubin (TBIL) were not statistically correlated with coagulopathy. According to the diagnosis and treatment plan, the included cases were classified into mild, moderate, severe, and critical. The results showed that the occurrence of coagulation dysfunction had no statistical correlation with the severity of COVID-19.

CONCLUSION

Coagulation dysfunction in patients with COVID-19 is closely related to liver damage. A longer course of the disease may cause a vicious circle of coagulopathy and liver damage. Clinicians need to closely monitor coagulation and liver function tests and to give prophylactic or supportive therapy when needed.

Construction of biomimetic silver nanoparticles in the treatment of lymphoma

Lymphoma is a well-known malignant tumor in the human body. Although many anticancer drugs have been developed to improve the survival rate of patients, about 40% of patients continue to be recurrent or refractory, a key issue needing remedy. Therefore, it is necessary to identify alternative treatments to reduce the disease's mortality. To this effect, a new type of anti-lymphoma nanocomplex FA@RBCm-AgNPs was prepared using AgNPs as the core of nanoparticles along with the targeting molecule folic acid inserted erythrocyte membrane as the shell. The biomimetic properties of red blood cell membrane (RBCm) endow F-RAN with good biocompatibility as well as the ability to evade clearance of the reticuloendothelial system. In addition, F-RAN was modified with folic acid to actively and selectively identify tumor cells. In vivo and in vitro experiments demonstrate that F-RAN can inhibit lymphoma cells and induce apoptosis of stem cells while promoting apoptosis of lymphoma with no obvious side effects. Hence, F-RAN may serve as a new treatment for lymphoma.

A novel epigenetic regulation of circFoxp1 on Foxp1 in colon cancer cells

Foxp1 is a tumor suppressor in colon cancer. However, circFoxp1 derived from Foxp1 is an oncogene. In this study, we aim to investigate the role of circFoxp1 in colon cancer and the regulatory mechanism between circFoxp1 and Foxp1. 78 human colon tumor tissues and the matched paracancerous tissues were collected. Quantitative polymerase chain reaction, immunohistochemistry, quantitative methylation-specific PCR, chromatin immunoprecipitation assay, CCK-8 assay, and Tumor xenograft in nude mice were performed. The expression of circFoxp1 was increased and Foxp1 was reduced in colon cancer tissues, which were associated with a poor overall survival rate of the patients with colon cancer. CircFoxp1 recruited DNMT1 to the promoter of Foxp1, leading to promotor hypermethylation, thereby inhibiting Foxp1 transcription. Interfering circFoxp1 by siRNA in SW620 cells significantly inhibited cell viability, while knockdown Foxp1 expression partially restored SW620 cell viability. In addition, knockdown of circFoxp1 significantly sensitized colon cancer cells to Capecitabine in vitro and vivo through regulating Foxp1. We discovered a novel epigenetic pathway that circFoxp1 regulated Foxp1 in colon cancer cells. CircFoxp1 may regulate DNA methylation and demethylation to coordinate colon cancer cell proliferation and participate in chemotherapy drug responses. Therefore, circFoxp1 may be a potential therapeutic target for colon cancer.

Diagnostic value of exosomal circMYC in radioresistant nasopharyngeal carcinoma

BACKGROUND

The relationship between circulating exosomal circular RNA (circRNA) and prognosis of patients with nasopharyngeal carcinoma (NPC) remain unknown. This study focused on the expression of exosomal circMYC and its relationship with the recurrence and prognosis of patients with NPC.

METHODS

The circulating exosomes were obtained from 210 patients with NPC. Quantitative polymerase chain reaction, 5-ethynyl-2'-deoxyuridine (EdU) staining, colony formation, and bioinformatic analysis were performed.

RESULTS

Circulating exosomal circMYC was significantly increased in patients with NPC and was associated with tumor size, lymph node metastasis, TNM stage, survival rate, and disease recurrence. Gain-functional and loss-functional experiments revealed that overexpression of circMYC promoted cell proliferation and reduce radiosensitivity, while knockdown of circMYC inhibited cell proliferation and enhanced radiotherapy.

CONCLUSION

circMYC is an oncogene in NPC cells and can enhance the radiotherapy resistance of NPC cells. Circulating exosomal circMYC can be used as a potential therapeutic target for NPC.

Circulating Exosomal CircMYC Is Associated with Recurrence and Bortezomib Resistance in Patients with Multiple Myeloma

Objective

Studies have shown that serum circRNA can be used as a biomarker for many tumors. However, the role of exosomal circRNA in prognostic evaluation in patients with multiple myeloma (MM) remains unclear. In this study, we aimed to analyze the role of circulating exosomal circMYC in the relapse and prognosis of patients with MM.

Materials and Methods

Circulating exosomes from 122 patients with MM and 54 healthy people were isolated. Quantitative polymerase chain reaction was performed to measure circMYC exosomal expression. Kaplan-Meier survival curves with log-rank testing were used for estimating significance in survival rates. A Cox regression model was used for univariate and multivariate analysis.

Results

Compared with healthy people, the expression level of serum exosomal circMYC was significantly increased in patients with MM. In addition, the expression of circMYC in circulating exosomes in bortezomib-resistant patients was significantly higher than that in non-resistant patients. The expression level of exosomal circMYC was correlated with deletion 17p, t(4;14), Durie-Salmon staging, and the International Staging System. Univariate and multivariate Cox regression analysis found that a high exosomal circMYC level was an independent predictor of poor prognosis in patients with MM. The patients with high exosome circMYC expression had higher relapse rates and higher mortality rates. The overall survival rate and progression-free survival rate of MM patients with high exosomal circMYC expression were lower than those of patients with low exosomal circMYC expression.

Conclusion

These findings suggest that circulating exosomal circMYC has great potential as a biomarker for the diagnosis and prognosis of MM.

A Nano-Traditional Chinese Medicine Against Lymphoma That Regulates the Level of Reactive Oxygen Species

Jolkinolide B (JB) is a bioactive compound isolated from a Chinese herbal medicine that exerts antitumor activity. However, the anti-lymphoma effect of JB and its mechanism are yet to be revealed. Because free JB has poor pharmacokinetics and weak antitumor efficacy, we opted to use black phosphorus quantum dot (BPQD) nanomaterials as a drug loading platform to synthesize a nano-traditional Chinese medicine (nano-TCM) called BPQDs@JB. Compared with free JB, Raji cells administrated with BPQDs@JB exhibited the cell viability of 19.85 ± 1.02%, and the production of intracellular reactive oxygen species (ROS) was promoted. Likewise, BPQDs@JB was capable of rising the apoptosis rate of Raji cells to 34.98 ± 1.76%. In nude mice transplanted tumor model administrated with BPQDs@JB, the tumor tissue sections administrated with BPQDS@JB achieved a conspicuous red fluorescence, demonstrating the presence of most ROS production in the BPQDS@JB. TUNEL achieved a number of positive (brown) nuclei in vivo, revealing that BPQDS@JB could significantly induce tumor tissue apoptosis. As revealed from the mentioned results, BPQDs@JB can generate considerable ROS and interfere with the redox state to inhibit tumor. In brief, BPQDs@JB may be adopted as a treatment option for lymphoma.

Stochastic Dynamics of Gene Switching and Energy Dissipation for Gene Expression

Stochastic dynamics of gene switching and energy dissipation for gene expression are largely unknown, mainly due to the complexity of non-equilibrium mechanisms. Here, based on an important double-deck loop model, the stochastic mechanisms of gene switching and energy dissipation are studied. First, the probability distributions of steady states are calculated theoretically. It is found that the signal can strengthen the choice of gene switching between the "off" and "on" states. Our analysis of energy consumption illustrates that, compared with the synthesis and degradation of proteins, the process of gene switching costs little energy. Our theoretical analysis reveals some interesting insights into the determination of cell state and energy dissipation for gene expression.

Periodic and aperiodic force-induced logical stochastic resonance in a bistable system

It was demonstrated recently that there are optimal windows of noise intensity or frequency and amplitude of the periodic driving force, which let a bistable system operate reliably as logic gates. These phenomena are called logical stochastic resonance (LSR). Given that the driving force is not always perfect regular, there may be phase disturbance in driving force; therefore, the Wiener process is used here to model phase disturbance of driving force, and then the effects of phase disturbance on reliability and agility of logic gates are explored in detail. Comparing with the periodic force, the aperiodic force with appropriate intensity phase disturbance can drive a bistable system to yield phenomena similar to LSR in a wider reliable region and can reduce mean switching time to obtain a faster response of logic devices to the input signal. On the other hand, depending on the amplitude and average angular frequency, moderate-intensity phase disturbance may also reduce success probability and increase mean switching time and thus lead to the instability and the slower response of logic devices.

Coagulation and immune function indicators for monitoring of coronavirus disease 2019 and the clinical significance

OBJECTIVES

To explore the significance of coagulation and immune function indicators in clinical diagnosis and treatment of coronavirus disease 2019 (COVID-19).

METHODS

All patients with COVID-19 diagnosed and treated in First People's Hospital of Yueyang from January to March 2020 were enrolled. The general data of patients were collected. The patients were assigned into a light group (n=20), an ordinary group (n=33), a severe group (n=23), and a critically severe group (n=7) according to the severity of the disease. Coagulation and immune function indicators of each group were compared, and the relevance of coagulation and immune function indicators was analyzed.

RESULTS

The age of COVID-19 patients in Yueyang City was mainly between 45 and 65 years old. There was a significant difference in the coagulation function and immune-related indicators in each group of patients (all P<0.05).

CONCLUSIONS

There are some abnormalities in coagulation and immune function in patients with COVID-19, which possess significance for clinical diagnosis and treatment of the disease.