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Background and Aims: Hepatocellular carcinoma (HCC) is a highly aggressive tumor with limited treatment options and high mortality. Senecavirus A (SVA) has shown potential in selectively targeting tumors while sparing healthy tissues. This study aimed to investigate the effects of SVA on HCC cells in vitro and in vivo and to elucidate its mechanisms of action. Methods: The cell counting kit-8 assay and colony formation assay were conducted to examine cell proliferation. Flow cytometry and nuclear staining were employed to analyze cell cycle distribution and apoptosis occurrence. A subcutaneous tumor xenograft HCC mouse model was created in vivo using HepG2 cells, and Ki67 expression in the tumor tissues was assessed. The terminal deoxynucleotidyl transferase dUTP nick end labeling assay and hematoxylin and eosin staining were employed to evaluate HCC apoptosis and the toxicity of SVA on mouse organs. Results: In vitro, SVA effectively suppressed the growth of tumor cells by inducing apoptosis and cell cycle arrest. However, it did not have a notable effect on normal hepatocytes (MIHA cells). In an in vivo setting, SVA effectively suppressed the growth of HCC in a mouse model. SVA treatment resulted in a significant decrease in Ki67 expression and an increase in apoptosis of tumor cells. No notable histopathological alterations were observed in the organs of mice during SVA administration. Conclusions: SVA inhibits the growth of HCC cells by inducing cell cycle arrest and apoptosis. It does not cause any noticeable toxicity to vital organs.
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OBJECTIVE: Breast cancer has become the most prevalent malignant tumor in women, and the occurrence of distant metastasis signifies a poor prognosis. Utilizing predictive models to forecast distant metastasis in breast cancer presents a novel approach. This study aims to utilize readily available clinical data and advanced machine learning algorithms to establish an accurate clinical prediction model. The overall objective is to provide effective decision support for clinicians. METHODS: Data from 239 patients from two centers were analyzed, focusing on clinical blood biomarkers (tumor markers, liver and kidney function, lipid profile, cardiovascular markers). Spearman correlation and the least absolute shrinkage and selection operator regression were employed for feature dimension reduction. A predictive model was built using LightGBM and validated in training, testing, and external validation cohorts. Feature importance correlation analysis was conducted on the clinical model and the comprehensive model, followed by univariate and multivariate regression analysis of these features. RESULTS: Through internal and external validation, we constructed a LightGBM model to predict de novo bone metastasis in newly diagnosed breast cancer patients. The area under the receiver operating characteristic curve values of this model in the training, internal validation test, and external validation test1 cohorts were 0.945, 0.892, and 0.908, respectively. Our validation results indicate that the model exhibits high sensitivity, specificity, and accuracy, making it the most accurate model for predicting bone metastasis in breast cancer patients. Carcinoembryonic Antigen, creatine kinase, albumin-globulin ratio, Apolipoprotein B, and Cancer Antigen 153 (CA153) play crucial roles in the model's predictions. Lipoprotein a, CA153, gamma-glutamyl transferase, α-Hydroxybutyrate dehydrogenase, alkaline phosphatase, and creatine kinase are positively correlated with breast cancer bone metastasis, while white blood cell ratio and total cholesterol are negatively correlated. CONCLUSION: This study successfully utilized clinical blood biomarkers to construct an artificial intelligence model for predicting distant metastasis in breast cancer, demonstrating high accuracy. This suggests potential clinical utility in predicting and identifying distant metastasis in breast cancer. These findings underscore the potential prospect of developing economically efficient and readily accessible predictive tools in clinical oncology.
Subject(s)
Artificial Intelligence , Biomarkers, Tumor , Bone Neoplasms , Breast Neoplasms , Humans , Breast Neoplasms/pathology , Female , Bone Neoplasms/secondary , Bone Neoplasms/blood , Middle Aged , Biomarkers, Tumor/blood , Adult , Aged , ROC Curve , Machine Learning , Predictive Value of TestsABSTRACT
Objective: This study aims to develop an artificial intelligence model utilizing clinical blood markers, ultrasound data, and breast biopsy pathological information to predict the distant metastasis in breast cancer patients. Methods: Data from two medical centers were utilized, Clinical blood markers, ultrasound data, and breast biopsy pathological information were separately extracted and selected. Feature dimensionality reduction was performed using Spearman correlation and LASSO regression. Predictive models were constructed using LR and LightGBM machine learning algorithms and validated on internal and external validation sets. Feature correlation analysis was conducted for both models. Results: The LR model achieved AUC values of 0.892, 0.816, and 0.817 for the training, internal validation, and external validation cohorts, respectively. The LightGBM model achieved AUC values of 0.971, 0.861, and 0.890 for the same cohorts, respectively. Clinical decision curve analysis showed a superior net benefit of the LightGBM model over the LR model in predicting distant metastasis in breast cancer. Key features identified included creatine kinase isoenzyme (CK-MB) and alpha-hydroxybutyrate dehydrogenase. Conclusion: This study developed an artificial intelligence model using clinical blood markers, ultrasound data, and pathological information to identify distant metastasis in breast cancer patients. The LightGBM model demonstrated superior predictive accuracy and clinical applicability, suggesting it as a promising tool for early diagnosis of distant metastasis in breast cancer.
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Pulmonary fibrosis is characterized by pathological accumulation of scar tissue in the lung parenchyma. Many of the processes that are implicated in fibrosis, including increased extracellular matrix synthesis, also occur following pneumonectomy (PNX), but PNX instead results in regenerative compensatory growth of the lung. As fibroblasts are the major cell type responsible for extracellular matrix production, we hypothesized that comparing fibroblast responses to PNX and bleomycin (BLM) would unveil key differences in the role they play during regenerative versus fibrotic lung responses. RNA-sequencing was performed on flow-sorted fibroblasts freshly isolated from mouse lungs 14 days after BLM, PNX, or sham controls. RNA-sequencing analysis revealed highly similar biological processes to be involved in fibroblast responses to both BLM and PNX, including TGF-ß1 and TNF-α. Interestingly, we observed smaller changes in gene expression after PNX than BLM at Day 14, suggesting that the fibroblast response to PNX may be muted by expression of transcripts that moderate pro-fibrotic pathways. Itpkc, encoding inositol triphosphate kinase C, was a gene uniquely up-regulated by PNX and not BLM. ITPKC overexpression in lung fibroblasts antagonized the pro-fibrotic effect of TGF-ß1. RNA-sequencing analysis has identified considerable overlap in transcriptional changes between fibroblasts following PNX and those overexpressing ITPKC.
Subject(s)
Bleomycin , Fibroblasts , Mice, Inbred C57BL , Pneumonectomy , Pulmonary Fibrosis , Bleomycin/pharmacology , Animals , Fibroblasts/metabolism , Fibroblasts/drug effects , Mice , Pulmonary Fibrosis/metabolism , Pulmonary Fibrosis/genetics , Pulmonary Fibrosis/pathology , Lung/metabolism , Lung/cytology , Lung/pathology , Male , Sequence Analysis, RNA/methods , Transforming Growth Factor beta1/metabolism , Transforming Growth Factor beta1/genetics , Cells, CulturedABSTRACT
Breast cancer metastasis significantly impacts women's health globally. This study aimed to construct predictive models using clinical blood markers and ultrasound data to predict distant metastasis in breast cancer patients, ensuring clinical applicability, cost-effectiveness, relative non-invasiveness, and accessibility of these models. Analysis was conducted on data from 416 patients across two centers, focusing on clinical blood markers (tumor markers, liver and kidney function indicators, blood lipid markers, cardiovascular biomarkers) and maximum lesion diameter from ultrasound. Feature reduction was performed using Spearman correlation and LASSO regression. Two models were built using LightGBM: a clinical model (using clinical blood markers) and a combined model (incorporating clinical blood markers and ultrasound features), validated in training, internal test, and external validation (test1) cohorts. Feature importance analysis was conducted for both models, followed by univariate and multivariate regression analyses of these features. The AUC values of the clinical model in the training, internal test, and external validation (test1) cohorts were 0.950, 0.795, and 0.883, respectively. The combined model showed AUC values of 0.955, 0.835, and 0.918 in the training, internal test, and external validation (test1) cohorts, respectively. Clinical utility curve analysis indicated the combined model's superior net benefit in identifying breast cancer with distant metastasis across all cohorts. This suggests the combined model's superior discriminatory ability and strong generalization performance. Creatine kinase isoenzyme (CK-MB), CEA, CA153, albumin, creatine kinase, and maximum lesion diameter from ultrasound played significant roles in model prediction. CA153, CK-MB, lipoprotein (a), and maximum lesion diameter from ultrasound positively correlated with breast cancer distant metastasis, while indirect bilirubin and magnesium ions showed negative correlations. This study successfully utilized clinical blood markers and ultrasound data to develop AI models for predicting distant metastasis in breast cancer. The combined model, incorporating clinical blood markers and ultrasound features, exhibited higher accuracy, suggesting its potential clinical utility in predicting and identifying breast cancer distant metastasis. These findings highlight the potential prospects of developing cost-effective and accessible predictive tools in clinical oncology.
Subject(s)
Biomarkers, Tumor , Breast Neoplasms , Neoplasm Metastasis , Humans , Breast Neoplasms/blood , Breast Neoplasms/pathology , Breast Neoplasms/diagnostic imaging , Female , Biomarkers, Tumor/blood , Middle Aged , Adult , Ultrasonography/methods , AgedABSTRACT
Fibrosis in the lung is thought to be driven by epithelial cell dysfunction and aberrant cell-cell interactions. Unveiling the molecular mechanisms of cellular plasticity and cell-cell interactions is imperative to elucidate lung regenerative capacity and aberrant repair in pulmonary fibrosis. By mining publicly available RNA-seq datasets, we identified loss of CCAAT enhancer-binding protein alpha (CEBPA) as a candidate contributor to idiopathic pulmonary fibrosis (IPF). We used conditional knockout mice, scRNA-seq, lung organoids, small-molecule inhibition and novel gene manipulation methods to investigate the role of CEBPA in lung fibrosis and repair. Long term (6 month+) of Cebpa loss in AT2 cells caused spontaneous fibrosis and increased susceptibility to bleomycin-induced fibrosis. Cebpa knockout in these mice significantly decreased AT2 cell numbers in the lung and reduced expression of surfactant homeostasis genes, while increasing inflammatory cell recruitment as well as upregulating S100a8/a9 in AT2 cells. In vivo treatment with an S100A8/A9 inhibitor alleviated experimental lung fibrosis. Restoring CEBPA expression in lung organoids ex vivo and during experimental lung fibrosis in vivo rescued CEBPA deficiency-mediated phenotypes. Our study establishes a direct mechanistic link between CEBPA repression, impaired AT2 cell identity, disrupted tissue homeostasis, and lung fibrosis.
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Scattering and localization dynamics of charge carriers in the soft lattice of lead-halide perovskites impact polaron formation and recombination, which are key mechanisms of material function in optoelectronic devices. In this study, we probe the photoinduced lattice and carrier dynamics in perovskite thin films (CsFAPbX3, X = I, Br) using time-resolved infrared spectroscopy. We examine the CN stretching mode of formamidinium (FA) cations located within the lead-halide octahedra of the perovskite structure. Our investigation reveals the formation of an infrared mode due to spatial symmetry breaking within a hundred picoseconds in 3D perovskites. Experiments at cryogenic temperatures show much-reduced carrier localization, in agreement with a localization mechanism that is driven by the dynamic disorder. We extend our analysis to 2D perovskites, where the precise nature of charge carriers is uncertain. Remarkably, the signatures of charge localization we found in bulk perovskites are not observed for 2D Ruddlesden-Popper perovskites ((HexA)2FAPb2I7). This observation implies that the previously reported stabilization of free charge carriers in these materials follows different mechanisms than polaron formation in bulk perovskites. Through the exploration of heterostructures with electron/hole excess, we provide evidence that holes drive the formation of the emerging infrared mode.
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Background: Emerging infectious diseases pose a significant threat to global public health. Timely detection and response are crucial in mitigating the spread of such epidemics. Inferring the onset time and epidemiological characteristics is vital for accelerating early interventions, but accurately predicting these parameters in the early stages remains challenging. Methods: We introduce a Bayesian inference method to fit epidemic models to time series data based on state-space modeling, employing a stochastic Susceptible-Exposed-Infectious-Removed (SEIR) model for transmission dynamics analysis. Our approach uses the particle Markov chain Monte Carlo (PMCMC) method to estimate key epidemiological parameters, including the onset time, the transmission rate, and the recovery rate. The PMCMC algorithm integrates the advantageous aspects of both MCMC and particle filtering methodologies to yield a computationally feasible and effective means of approximating the likelihood function, especially when it is computationally intractable. Results: To validate the proposed method, we conduct case studies on COVID-19 outbreaks in Wuhan, Shanghai and Nanjing, China, respectively. Using early-stage case reports, the PMCMC algorithm accurately predicted the onset time, key epidemiological parameters, and the basic reproduction number. These findings are consistent with empirical studies and the literature. Conclusion: This study presents a robust Bayesian inference method for the timely investigation of emerging infectious diseases. By accurately estimating the onset time and essential epidemiological parameters, our approach is versatile and efficient, extending its utility beyond COVID-19.
Subject(s)
Algorithms , Bayes Theorem , COVID-19 , Communicable Diseases, Emerging , Markov Chains , Humans , Communicable Diseases, Emerging/epidemiology , COVID-19/epidemiology , COVID-19/transmission , China/epidemiology , Monte Carlo Method , SARS-CoV-2 , Disease Outbreaks/statistics & numerical data , Time Factors , Epidemiological ModelsABSTRACT
Compared with traditional electrical logic gates, optical or terahertz (THz) computing logic gates have faster computing speeds and lower power consumption, and can better meet the huge data computing needs. However, there are limitations inherent in existing optical logic gates, such as single input/output channels and susceptibility to interference. Here, we proposed a new approach utilizing polarization-sensitive graphene-vanadium dioxide metasurface THz logic gates. Benefitting from two actively tunable materials, the proposed controlled-NOT logic gate(CNOT LG) enables versatile functionality through a dual-parameter control system. This system allows for the realization of multiple output states under diverse polarized illuminating conditions, aligning with the expected input-output logic relationship of the CNOT LG. Furthermore, to demonstrate the robustness of the designed THz CNOT LG metasurface, we designed an imaging array harnessing the dynamic control capabilities of tunable meta-atoms, facilitating clear near-field imaging. This research is promising for advancing CNOT LG applications in the THz spectrum. It has potential applications in telecommunications, sensing, and imaging.
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CRISPR-Cas technology is a widely utilized gene-editing tool that involves gRNA-guided sequence recognition and Cas nuclease-mediated cleavage. The design and evaluation of gRNA are essential for enhancing CRISPR/Cas editing efficiency. Various assays such as single-strand annealing, in vitro cleavage, and T7 endonuclease I (T7EI) are commonly used to assess gRNA-mediated Cas protein cleavage activity. In this study, a firefly luciferase and Renilla luciferase co-expressed and a cleavage-based single-plasmid dual-luciferase surrogate reporter was built to evaluate the gRNA-mediated Cas12a cleavage efficiency. The cleavage activities of CRISPR-Cas12a can be quantitatively determined by the recovery degree of firefly luciferase activity. The cleavage efficiency of CRISPR-Cas12a can be quantitatively measured by the recovery of firefly luciferase activity. By using this system, the cleavage efficiency of CRISPR-Cas12a on hepatitis B virus (HBV)/D expression plasmid was evaluated, revealing a negative correlation between gRNA cleavage efficiency and HBV gene expression measured using an enzyme-linked immunosorbent assay. This simple, efficient, and quantifiable system only requires the dual-luciferase vector and CRISPR-Cas12a vector, making it a valuable tool for selecting effective gRNAs for gene editing.
Subject(s)
CRISPR-Associated Proteins , CRISPR-Cas Systems , Gene Editing , Genes, Reporter , Luciferases , Plasmids , RNA, Guide, CRISPR-Cas Systems , Gene Editing/methods , RNA, Guide, CRISPR-Cas Systems/genetics , Plasmids/genetics , Humans , Luciferases/genetics , Luciferases/metabolism , CRISPR-Associated Proteins/genetics , CRISPR-Associated Proteins/metabolism , Hepatitis B virus/genetics , Endodeoxyribonucleases/metabolism , Endodeoxyribonucleases/genetics , Luciferases, Firefly/genetics , Luciferases, Firefly/metabolism , Clustered Regularly Interspaced Short Palindromic Repeats/genetics , Bacterial Proteins/genetics , Bacterial Proteins/metabolismABSTRACT
Herpes zoster (HZ) is rare in healthy children, but more prevalent in those with leukemia. Optimal timing of chemotherapy reinitiation after HZ treatment is challenging because chemotherapy suppresses immunity and increases risk of HZ relapse. We aimed to optimize the timing of chemotherapy reinitiation after HZ therapy in children with leukemia. The study included 31 children with acute leukemia and HZ infection. General information, clinical symptoms, laboratory test results, duration of HZ treatment, and prognosis were compared with those of children with leukemia alone. Correlation analysis was performed for 20 children who restarted chemotherapy after HZ treatment. Of 31 children with leukemia and HZ, 67.74% had lesions at multiple sites. The median time from chemotherapy initiation to HZ onset was 14.1 (1.5-29.5) months. Among 27 children included in the follow-up, there was one case of HZ relapse. After excluding children who did not continue chemotherapy after HZ treatment, the median interval between completion of HZ therapy and chemotherapy reinitiation in the remaining 20 children was 8.00 (- 3 to 27) days. Lymphocyte counts (LY#) on restarting chemotherapy correlated inversely with HZ lesion healing time (p < 0.05). LY# at the time of HZ onset were lower than those pre- and post-onset, and lower than those in the control group (p < 0.05). In conclusion, children with leukemia have a good HZ prognosis, but an increased risk of HZ recurrence. LY# at the time of chemotherapy reinitiation may be a useful indicator for selecting the optimal interval between antiviral therapy completion and chemotherapy reinitiation.
Subject(s)
Antiviral Agents , Herpes Zoster , Leukemia , Adolescent , Child , Child, Preschool , Female , Humans , Infant , Male , Antiviral Agents/therapeutic use , Antiviral Agents/administration & dosage , Herpes Zoster/drug therapy , Leukemia/drug therapy , Leukemia/complications , Lymphocyte Count , Prognosis , Retrospective Studies , Time FactorsABSTRACT
OBJECTIVE: The CYP2D6 enzyme is crucial for the metabolism and disposition of a variety of drugs. This study was conducted to examine the relationship between CYP2D6 gene polymorphisms and the response to angiotensin receptor blocker (ARB)-based treatment in patients of Chinese Bai ethnicity with hypertension. METHODS: Seventy-two hypertensive adults from the Chinese Bai ethnic group, exhibiting systolic blood pressure (SBP)â ≥â 140â mmHg or diastolic blood pressure (DBP)â ≥â 90â mmHg, were recruited. Targeted regional sequencing was utilized to genotype single nucleotide polymorphisms in the CYP2D6 gene, aiming to assess their frequency and to evaluate their influence on the therapeutic efficacy of ARB medications. RESULTS: Our research identified nine significant CYP2D6 polymorphisms associated with the efficacy of ARB treatment in the Bai hypertensive cohort. Specifically, patients possessing certain mutant genotype at rs111564371 exhibited substantially greater reductions in SBP and DBP, with P -values of 0.021 and 0.016, respectively, compared to those carrying the wild genotype. Additionally, these mutant genotype at rs111564371 and rs112568578 were linked to approximately 20% higher overall efficacy rates and a 10% increased achievement rate relative to the wild genotype. CONCLUSION: Our research with the Bai hypertensive group shows that certain CYP2D6 polymorphisms significantly influence ARB treatment outcomes. Mutations at rs111564371 led to better blood pressure control ( P -values: 0.021 for SBP, 0.016 for DBP), improving ARB efficacy by appromixately 20% and increasing treatment goal achievement by 10% over the wild-type genotype. STATEMENTS: Our investigation into CYP2D6 polymorphisms within the Bai hypertensive cohort marks a substantial advancement towards personalized healthcare, underscoring the pivotal influence of genetic constitution on the effectiveness of ARB therapy.
Subject(s)
Cytochrome P-450 CYP2D6 , Hypertension , Polymorphism, Single Nucleotide , Humans , Cytochrome P-450 CYP2D6/genetics , Hypertension/drug therapy , Hypertension/genetics , Male , Female , Middle Aged , Aged , Angiotensin Receptor Antagonists/therapeutic use , Blood Pressure/drug effects , Blood Pressure/genetics , Asian People/genetics , Genotype , Adult , Antihypertensive Agents/therapeutic use , Antihypertensive Agents/administration & dosage , Antihypertensive Agents/pharmacology , Treatment OutcomeABSTRACT
Two lanthanide 3D coordination polymers [Ln2(L)4Cl2(H2O)4]n (Ln = Eu (1), Gd (2)) with quinoline-2-carboxylic acid (HL) as the ligand were successfully synthesized and characterized. Complex 1 exhibits a highly sensitive and selective luminescent response to 2,6-dipicolinic acid (DPA) in tap water and is virtually unaffected by interferences such as amino acids, aromatic carboxylic acids, and ions. With the addition of DPA, the luminescence intensity of complex 1 decreases rapidly to the naked eye. The detection limit of 1 toward DPA is 3.36 µM, which is much less than the infectious dose (60 µM) of the anthrax spores, indicating the high sensitivity of 1 to DPA. This study offers a basis for employing lanthanide complexes in real sample analysis, enabling direct and efficient detection of DPA with high sensitivity and specificity. Additionally, it is noteworthy that at a magnetic field strength of 7 T and a temperature of 3 K, the maximum entropy change for complex 2 attains a value of 23.56 J kg-1 K-1.
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The World Health Organization's end TB strategy promotes the use of symptom and chest radiograph screening for tuberculosis (TB) disease. However, asymptomatic early states of TB beyond latent TB infection and active disease can go unrecognized using current screening criteria. We conducted a longitudinal cohort study enrolling household contacts initially free of TB disease and followed them for the occurrence of incident TB over 1 year. Among 1,747 screened contacts, 27 (52%) of the 52 persons in whom TB subsequently developed during follow-up had a baseline abnormal radiograph. Of contacts without TB symptoms, persons with an abnormal radiograph were at higher risk for subsequent TB than persons with an unremarkable radiograph (adjusted hazard ratio 15.62 [95% CI 7.74-31.54]). In young adults, we found a strong linear relationship between radiograph severity and time to TB diagnosis. Our findings suggest chest radiograph screening can extend to detecting early TB states, thereby enabling timely intervention.
Subject(s)
Family Characteristics , Mass Screening , Radiography, Thoracic , Humans , Peru/epidemiology , Male , Female , Adult , Adolescent , Young Adult , Mass Screening/methods , Longitudinal Studies , Middle Aged , Child , Tuberculosis, Pulmonary/epidemiology , Tuberculosis, Pulmonary/diagnosis , Tuberculosis, Pulmonary/diagnostic imaging , Contact Tracing/methods , Child, Preschool , Latent Tuberculosis/diagnosis , Latent Tuberculosis/epidemiology , Latent Tuberculosis/diagnostic imaging , Infant , Tuberculosis/epidemiology , Tuberculosis/diagnosis , Tuberculosis/diagnostic imagingABSTRACT
Hepatitis B virus (HBV) infection is a major global health burden with 820 000 deaths per year. In our previous study, we found that the knockdown of autophagy-related protein 5 (ATG5) significantly upregulated the interferon-stimulated genes (ISGs) expression to exert the anti-HCV effect. However, the regulation of ATG5 on HBV replication and its underlying mechanism remains unclear. In this study, we screened the altered expression of type I interferon (IFN-I) pathway genes using RT² Profiler™ PCR array following ATG5 knock-down and we found the bone marrow stromal cell antigen 2 (BST2) expression was significantly increased. We then verified the upregulation of BST2 by ATG5 knockdown using RT-qPCR and found that the knockdown of ATG5 activated the Janus kinase/signal transducer and activator of transcription (JAK-STAT) signaling pathway. ATG5 knockdown or BST2 overexpression decreased Hepatitis B core Antigen (HBcAg) protein, HBV DNA levels in cells and supernatants of HepAD38 and HBV-infected NTCP-HepG2. Knockdown of BST2 abrogated the anti-HBV effect of ATG5 knockdown. Furthermore, we found that ATG5 interacted with BST2, and further formed a ternary complex together with HBV-X (HBx). In conclusion, our finding indicates that ATG5 promotes HBV replication through decreasing BST2 expression and interacting with it directly to antagonize its antiviral function.
Subject(s)
Antigens, CD , Autophagy-Related Protein 5 , Bone Marrow Stromal Antigen 2 , GPI-Linked Proteins , Hepatitis B virus , Virus Replication , Humans , Antigens, CD/genetics , Antigens, CD/metabolism , Autophagy-Related Protein 5/genetics , Autophagy-Related Protein 5/metabolism , Gene Knockdown Techniques , GPI-Linked Proteins/metabolism , GPI-Linked Proteins/genetics , Hep G2 Cells , Hepatitis B/virology , Hepatitis B/genetics , Hepatitis B virus/physiology , Hepatitis B virus/genetics , Host-Pathogen Interactions , Signal Transduction , Bone Marrow Stromal Antigen 2/metabolismABSTRACT
BACKGROUND: Venous thromboembolism (VTE), is a noteworthy complication in individuals with gastric cancer, but the current diagnosis and treatment methods lack accuracy. In this study, we developed a t-PAIC chemiluminescence kit and employed chemiluminescence to detect the tissue plasminogen activator inhibitor complex (t-PAIC), thrombin-antithrombin III complex (TAT), plasmin-α2-plasmin inhibitor complex (PIC) and thrombomodulin (TM), combined with D-dimer and fibrin degradation products (FDP), to investigate their diagnostic potential for venous thrombosis in gastric cancer patients. The study assessed variations in six indicators among gastric cancer patients at different stages. RESULTS: The t-PAIC reagent showed LOD is 1.2 ng/mL and a linear factor R greater than 0.99. The reagents demonstrated accurate results, with all accuracy deviations being within 5%. The intra-batch and inter-batch CVs for the t-PAIC reagent were both within 8%. The correlation coefficient R between this method and Sysmex was 0.979. Gastric cancer patients exhibited elevated levels of TAT, PIC, TM, D-D, FDP compared to the healthy population, while no significant difference was observed in t-PAIC. In the staging of gastric cancer, patients in III-IV stages exhibit higher levels of the six markers compared to those in I-II stages. The ROC curve indicates an enhancement in sensitivity and specificity of the combined diagnosis of four or six indicators. CONCLUSION: Our chemiluminescence assay performs comparably to Sysmex's method and at a reduced cost. The use of multiple markers, including t-PAIC, TM, TAT, PIC, D-D, and FDP, is superior to the use of single markers for diagnosing VTE in patients with malignant tumors. Gastric cancer patients should be screened for the six markers to facilitate proactive prophylaxis, determine the most appropriate treatment timing, ameliorate their prognosis, decrease the occurrence of venous thrombosis and mortality, and extend their survival.
Subject(s)
Luminescent Measurements , Stomach Neoplasms , Humans , Stomach Neoplasms/diagnosis , Male , Middle Aged , Luminescent Measurements/methods , Female , Aged , Antithrombin III/metabolism , Antithrombin III/analysis , Thrombomodulin/blood , Fibrin Fibrinogen Degradation Products/analysis , Fibrin Fibrinogen Degradation Products/metabolism , alpha-2-Antiplasmin/metabolism , alpha-2-Antiplasmin/analysis , Adult , Fibrinolysin/metabolism , Fibrinolysin/analysis , Venous Thromboembolism/diagnosis , Venous Thromboembolism/blood , Peptide HydrolasesABSTRACT
Pathogen infections including Shigella flexneri have posed a significant threat to human health for numerous years. Although culturing and qPCR were the gold standards for pathogen detection, time-consuming and instrument-dependent restrict their application in rapid diagnosis and economically less-developed regions. Thus, it is urgently needed to develop rapid, simple, sensitive, accurate, and low-cost detection methods for pathogen detection. In this study, an immunomagnetic beads-recombinase polymerase amplification-CRISPR/Cas12a (IMB-RPA-CRISPR/Cas12a) method was built based on a cascaded signal amplification strategy for ultra-specific, ultra-sensitive, and visual detection of S. flexneri in the laboratory. Firstly, S. flexneri was specifically captured and enriched by IMB (Shigella antibody-coated magnetic beads), and the genomic DNA was released and used as the template in the RPA reaction. Then, the RPA products were mixed with the pre-loaded CRISPR/Cas12a for fluorescence visualization. The results were observed by naked eyes under LED blue light, with a sensitivity of 5 CFU/mL in a time of 70 min. With no specialized equipment or complicated technical requirements, the IMB-RPA-CRISPR/Cas12a diagnostic method can be used for visual, rapid, and simple detection of S. flexneri and can be easily adapted to monitoring other pathogens.
Subject(s)
Antibodies , Shigella flexneri , Humans , Blue Light , Fluorescence , RecombinasesABSTRACT
Respiratory infections pose a serious threat to global public health, underscoring the urgent need for rapid, accurate, and large-scale diagnostic tools. In recent years, the CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated) system, combined with isothermal amplification methods, has seen widespread application in nucleic acid testing (NAT). However, achieving a single-tube reaction system containing all necessary components is challenging due to the competitive effects between recombinase polymerase amplification (RPA) and CRISPR/Cas reagents. Furthermore, to enable precision medicine, distinguishing between bacterial and viral infections is essential. Here, we have developed a novel NAT method, termed one-pot-RPA-CRISPR/Cas12a, which combines RPA with CRISPR molecular diagnostic technology, enabling simultaneous detection of 12 common respiratory pathogens, including six bacteria and six viruses. RPA and CRISPR/Cas12a reactions are separated by paraffin, providing an independent platform for RPA reactions to generate sufficient target products before being mixed with the CRISPR/Cas12a system. Results can be visually observed under LED blue light. The sensitivity of the one-pot-RPA-CRISPR/Cas12a method is 2.5 × 100 copies/µL plasmids, with no cross-reaction with other bacteria or viruses. Additionally, the clinical utility was evaluated by testing clinical isolates of bacteria and virus throat swab samples, demonstrating favorable performance. Thus, our one-pot-RPA-CRISPR/Cas12a method shows immense potential for accurate and large-scale detection of 12 common respiratory pathogens in point-of-care testing.
Subject(s)
Bacteria , CRISPR-Cas Systems , Molecular Diagnostic Techniques , Respiratory Tract Infections , Viruses , Bacteria/genetics , Bacteria/isolation & purification , Bacterial Infections/diagnosis , Bacterial Infections/microbiology , Molecular Diagnostic Techniques/methods , Nucleic Acid Amplification Techniques/methods , Recombinases/genetics , Recombinases/metabolism , Respiratory Tract Infections/diagnosis , Respiratory Tract Infections/virology , Respiratory Tract Infections/microbiology , Sensitivity and Specificity , Virus Diseases/diagnosis , Viruses/genetics , Viruses/isolation & purificationABSTRACT
Moon dust presents a significant hazard to manned moon exploration missions, yet our understanding of its toxicity remains limited. The objective of this study is to investigate the pattern and mechanism of lung inflammation induced by subacute exposure to moon dust simulants (MDS) in rats. SD rats were exposed to MDS and silica dioxide through oral and nasal inhalation for 6â¯hours per day continuously for 15 days. Pathological analysis indicated that the toxicity of MDS was lower than that of silica dioxide. MDS led to a notable recruitment and infiltration of macrophages in the rat lungs. Material characterization and biochemical analysis revealed that SiO2, Fe2O3, and TiO2 could be crucial sources of MDS toxicity. The study revealed that MDS-induced oxidative stress response can lead to pulmonary inflammation, which potentially may progress to lung fibrosis. Transcriptome sequencing revealed that MDS suppresses the PI3K-AKT signaling pathway, triggers the Tnfr2 non-classical NF-kB pathway and IL-17 signaling pathway, ultimately causing lung inflammation and activating predominantly antioxidant immune responses. Moreover, the study identified the involvement of upregulated genes IL1b, csf2, and Sod2 in regulating immune responses in rat lungs, making them potential key targets for preventing pulmonary toxicity related to moon dust exposure. These findings are expected to aid in safeguarding astronauts against the hazardous effects of moon dust and offer fresh insights into the implications and mechanisms of moon dust toxicity.