American journal of translational research最新文献

Objective: To analyze the risk factors for bloodstream infection after immunosuppressive therapy in patients with aplastic anemia using logistic regression.

Methods: A retrospective analysis was conducted on the clinical data from 70 patients with aplastic anemia admitted to the People's Hospital of Zitong County and the Infectious Disease Hospital in Jiangyou City from March 2011 to March 2023. Patients were divided into two groups based on whether they developed an infection after treatment: the infection group (n = 18) and the non-infection group (n = 52). Risk factors for bloodstream infection following immunosuppressive therapy were analyzed, and the predictive value of independent risk factors was assessed.

Results: Univariate analysis identified age, diabetes, disease severity, albumin levels, neutrophil count, and concurrent infections before treatment as significant risk factors for bloodstream infection following immunosuppressive therapy (all P<0.05). Multivariate analysis further confirmed that age, diabetes, disease severity, albumin levels, and neutrophil count were independent risk factors for bloodstream infection (all P<0.05). ROC curve analysis revealed that age, diabetes, disease severity, albumin levels, and neutrophil count had area under the curve (AUC) values of 0.678, 0.728, 0.698, 0.740, and 0.739, respectively, in predicting bloodstream infection after immunosuppressive therapy. The sensitivity values were 65.39%, 78.85%, 67.31%, 67.31%, and 76.92%, respectively, while the specificity values were 72.22%, 66.67%, 72.22%, 77.78%, and 61.11%, respectively.

Conclusion: Age, diabetes, disease severity, albumin levels, and neutrophil count are key factors influencing bloodstream infection after immunosuppressive therapy in patients with aplastic anemia. These findings highlight the need for careful monitoring of these factors during immunosuppressive therapy to reduce the risk of bloodstream infection.

Objective: To evaluate the biomechanical performance of polyetheretherketone (PEEK) and titanium alloys in a base-type fixation system for mandibular defect reconstruction following partial resection due to tumors, trauma, or cancer, using finite element analysis.

Methods: Finite element analysis was conducted to simulate a fixation system made from titanium alloys, including pure titanium (Ti), Ti6Al4V (TC4), and Ti35Nb7Zr5Ta (TiNb), as well as PEEK materials, including unmodified PEEK, glass fiber-reinforced PEEK (GFR-PEEK), and carbon fiber-reinforced PEEK (CFR-PEEK). The biomechanical performance of these materials was compared.

Results: The PEEK-based fixation systems generated higher maximum stress on the mandible and fibula compared to the titanium alloy systems, particularly with the GFR-PEEK fixation system. When loaded in the anterior region, the maximum stress on the mandible exceeded its yield strength, indicating that both PEEK and GFR-PEEK are unsuitable for mandibular defect repair. CFR-PEEK, however, exhibited more favorable stress distribution, making it a better candidate for these applications.

Conclusion: Prolonged low stress on the bone may result in resorption or degeneration. Among the materials analyzed, CFR-PEEK demonstrated the most stable performance, suggesting it as the optimal choice for mandibular defect repair in fixation systems.

Background: To evaluate the prognostic value of echocardiography parameters, T lymphocyte subpopulations, NF-κB, and CD64 levels in neonatal sepsis.

Methods: A retrospective analysis was conducted on 78 neonates treated for sepsis between January 2018 and December 2022, comprising 64 with poor prognosis and 14 with good prognosis. Among them, 51 were critically ill and 27 were non-critically ill. Echocardiographic parameters, T-lymphocyte subpopulations, NF-κB, and CD64 levels were compared across different prognosis and severity groups. Factors influencing prognosis were identified through multivariate logistic regression analysis.

Results: The left ventricular ejection fraction (LVEF), left ventricular fractional shortening (LVFS), CD3+, and CD4+ T lymphocyte levels in critically ill neonates were (61.15±8.22)%, (32.26±6.61)%, (45.56±7.12)%, and (26.61±6.80)%, respectively, significantly lower than those of non-critically ill neonates (all P < 0.05). The levels of NF-κB and CD64 in critically ill neonates were (18.11±2.61) mg/L and (7.42±1.15)%, respectively, significantly higher than those of non-critically ill neonates (all P < 0.05). Logistic regression analysis showed that LVEF, LVFS, CD4+, CD64, and disease severity were the factors influencing prognosis in neonatal sepsis (all P < 0.05). The area under the ROC curve for the logistic regression equation in predicting prognosis in neonatal sepsis was 0.878, with sensitivity and specificity of 85.30% and 84.10%, respectively.

Conclusion: Echocardiography parameters, T lymphocyte subpopulations, NF-κB, and CD64 levels are associated with neonatal sepsis severity. LVEF, LVFS, CD4+ T lymphocytes, CD64, and disease severity are linked to prognosis, suggesting their potential as prognostic indicators for neonatal sepsis.

Objective: To identify independent risk factors for protein-energy malnutrition (PEM) in children aged 8-10 years and to develop and validate a nomogram model for estimating PEM risk.

Methods: In this retrospective study, a cohort of 1,412 children from The Fifth Affiliated Hospital of Guangzhou Medical University, spanning January 2022 to December 2023, was identified. Participants were randomly classified into a training set (n=988) and a validation set (n=424). Patients in the training set were divided into normal (n=667) and PEM (n=321) groups. Data collection involved demographic, sociological, physical, and biochemical assessments. Independent risk factors for PEM were identified using univariate and multivariate logistic regression. A nomogram risk model was constructed from significant predictors, and its performance was assessed using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). An independent dataset further validated the nomogram model.

Results: Among the 1,412 children, 497 (35.2%) had PEM, which included stunting (11.83%), underweight (11.61%), and wasting (11.76%). Multivariate analysis identified six independent risk factors for PEM: gestational age (OR (95% CI)=5.830 (3.604-9.431), P<0.001), household income (OR (95% CI)=0.383 (0.281-0.523), P<0.001), sleep duration (OR (95% CI)=1.800 (1.319-2.457), P<0.001), mood disorders (OR (95% CI)=6.924 (4.437-10.805), P<0.001), and physical activity time (OR (95% CI)=3.210 (2.342-4.400), P<0.001). The nomogram model demonstrated good predictive performance (AUC=0.803 (0.773-0.832)) and was validated well on an independent dataset (AUC=0.783 (0.739-0.828)).

Conclusion: The study identified key independent risk factors for PEM in children and established a robust nomogram model for clinical risk assessment. The model's high predictive accuracy and clinical applicability suggest it may be a valuable tool for the early identification and intervention strategies for PEM in clinical practice.

The objective of this study was to evaluate the incidence of hypoglycemia in patients with diabetic kidney disease (DKD) undergoing maintenance hemodialysis (MHD) and to identify key factors influencing its occurrence. A comprehensive literature search was conducted across databases including CNKI, Wanfang data, VIP, SinoMed, PubMed, Cochrane Library, Web of Science and Embase from their inception to March 31, 2023. The search focused on studies addressing the incidence and influencing factors for hypoglycemia in DKD patients receiving hemodialysis. Eligible studies were selected based on predefined inclusion and exclusion criteria, and data were analyzed using Stata 15.0 software. A total of 24 studies involving 2388 patients were included in this meta-analysis, with 22 studies from China and 2 studies from English-speaking countries. The findings indicated that the incidence of hypoglycemia among hemodialysis patients with DKD was 41.7% (95% confidence interval (CI): 32.6% to 50.9%). Influencing factors associated with hypoglycemia in hemodialysis patients with DKD included age (odds ratio (OR) = 4.507, 95% CI: 3.272 to 6.209), course of DKD (OR = 3.547, 95% CI: 2.523 to 4.988), use of oral hypoglycemic drugs (OR = 4.643, 95% CI: 2.566 to 8.402), fasting plasma glucose (FPG) levels (risk ratio (RR) = 4.033, 95% CI: 2.594 to 6.269), insulin use (OR = 8.242, 95% CI: 4.517 to 15.042), application of glucose-free dialysate (RR = 7.987, 95% CI: 4.605 to 13.855), coefficient of variation in blood glucose (CVBG) (OR = 3.241, 95% CI: 2.071 to 5.071), mean blood glucose (MBG) (OR = 2.930, 95% CI: 1.635 to 5.248), medication compliance (OR = 4.300, 95% CI: 2.047 to 9.031) and self-care ability (OR = 3.543, 95% CI: 1.766 to 7.108). Specifically, risk factors identified were age > 60 years, DKD course > 1 year, use of oral hypoglycemic drugs, FPG < 6.1 mmol/L, insulin administration before dialysis, application of glucose-free dialysate, CVBG ≥ 0.26, MBG < 8.92 mmol/L, poor medication compliance, and poor self-care ability.

Objective: To investigate the regulatory effect of glycyrrhizin (GL) on the release of neutrophil extracellular traps (NETs) from neutrophils in sepsis.

Methods: HL-60 cells were induced to differentiate into neutrophil-like dHL-60 cells to establish a neutrophil-like sepsis model. Expression levels of high-mobility group box 1 (HMGB1), citrullinated histone H3 (Cit-H3), and Toll-like receptor 9 (TLR9) were assessed by Western blotting. Free DNA, a component of NETs, was quantified using a fluorescence microplate reader. Cellular immunofluorescence analysis was used to detect the expression of the key NETs protein, Cit-H3.

Results: dHL-60 cells stimulated with 200 ng/ml LPS exhibited the highest expression of Cit-H3. The neutrophil-like sepsis model showed significantly increased levels of Cit-H3 and HMGB1. GL intervention significantly reduced the expression levels of HMGB1 and Cit-H3 and decreased the free DNA level. These findings suggest that GL decreases HMGB1 expression and NET release in the neutrophil-like sepsis model. TLR9 expression was significantly elevated in the sepsis model. Exogenous recombinant human HMGB1 protein further increased TLR9 expression, while GL inhibited this increase.

Conclusion: GL may inhibit NET release in sepsis through the HMGB1/TLR9 pathway.

Background: After percutaneous coronary intervention (PCI), patients with acute ST-segment elevation myocardial infarction (STEMI) could have an inflammatory response, which may lead to the risk of no-reflow due to microvascular obstruction. However, the association between changes in the levels of inflammatory response-related factors and no-reflow after PCI in patients with acute STEMI is still controversial.

Methods: In this study, a meta-analysis was conducted. Studies from the database established before April 2024 were retrieved in PubMed, Web of Science, and EMBASE. Case-control or cohort studies were included. Repetitive publications, studies without full access and successful data extraction, fragmentary information, animal experiments, summary, and systematic reviews were excluded, and Review Manager 5.3 software was used to process the data.

Results: The meta-analysis showed that elevated levels of high-sensitivity C-reactive protein (Hs-CRP) (Z = 22.87, P < 0.001), platelet/lymphocyte ratio (PLR) (Z = 19.17, P < 0.001), leukocyte (Z = 9.98, P < 0.001), and neutrophil count (Z = 5.75, P < 0.001) were significantly related with the risk of no-reflow. In addition, the increase of red blood cell volume width (RDW) was also a risk factor for no-reflow.

Conclusion: Refined results of Hs-CRP, PLR, RDW, leukocytes, and neutrophil can provide clinicians with effective tools to reduce the risk of no-reflow in patients with acute STEMI after PCI.

Objective: Acute ST-segment elevation myocardial infarction (STEMI) remains a major contributor to morbidity and mortality worldwide. The no-reflow phenomenon following percutaneous coronary intervention (PCI) complicates the clinical outcome of STEMI. This study aimed to identify a valuable predictor for no-reflow phenomenon.

Methods: This retrospective study analyzed clinical data from 378 STEMI patients with metabolic syndrome who underwent PCI between January 2023 and December 2023. Patients were divided into normal reflow (n = 311) and no-reflow (n = 67) groups based on post-PCI coronary angiography results. Data collected included patient demographics, medication usage, lipid profiles, cardiac biomarkers, and the triglyceride-glucose (TyG) index.

Results: Patients in the no-reflow group were older (59.98 ± 3.45 vs. 58.69 ± 3.57 years, P = 0.007), with higher fasting glucose (118.57 ± 7.23 vs. 113.59 ± 7.62 mg/dL, P < 0.001) and triglycerides (185.36 ± 10.17 vs. 176.56 ± 10.38 mg/dL, P < 0.001). The TyG index was notably higher in the no-reflow group (8.97 ± 1.15 vs. 7.49 ± 1.17, P < 0.001), showing the strongest correlation with no-reflow (r = 0.420, P < 0.001). Receiver Operating Characteristic (ROC) analysis identified the TyG index as the best predictor, with an AUC of 0.818 at a threshold of 8.1. Multivariable logistic regression identified TyG index ≥ 8.1 as the strongest independent predictor of no-reflow (OR, 9.591; 95% CI, 4.469-20.587, P < 0.001). The AUC of the TyG for predicting no-reflow was 0.869, with specificity and sensitivity of 0.891 and 0.791, respectively.

Conclusion: The TyG index is a powerful predictor of the no-reflow phenomenon in STEMI patients with metabolic syndrome undergoing PCI. Its robust sensitivity and specificity underscore its utility for risk stratification, enabling clinicians to identify high-risk patients and tailor preventive strategies.

Objectives: Ovarian cancer is a highly lethal gynecological malignancy, often diagnosed late, resulting in high mortality. While BRCA1 and BRCA2 mutations are known risk factors, the broader genetic landscape needs comprehensive profiling to identify additional diagnostic markers or therapeutic targets. The current study aims to explore the genetic landscape of various cancer-susceptible genes in ovarian cancer patients.

Methods: The genetic landscape of ovarian cancer was investigated by analyzing 27 genes via next-generation sequencing (NGS) in 50 ovarian cancer patients.

Results: Mutations were detected in four genes: Breast Cancer 1 (BRCA1) (62%), Cyclin-Dependent Kinase 4 (CDK4) (58%), MutS Homolog 2 (MSH2) (48%), and Phosphatase and Tensin Homolog (PTEN) (22%). Pathogenic mutations were identified in BRCA1 (p.Tyr1853Ter and p.Gln1848Ter), CDK4 (p.Arg24His), and PTEN (p.Tyr29Ter), occurring in 11 patients. Interestingly, these pathogenic mutations were absent in The Cancer Genome Atlas (TCGA) dataset and the gnomAD for the Asian population, suggesting their unique presence in the Pakistani cohort. Functional assays revealed that these mutations significantly reduced the mRNA and protein expression levels of BRCA1, CDK4, and PTEN, as demonstrated by Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) and Immunohistochemistry (IHC) analyses. Receiver Operating Characteristic (ROC) curve analysis confirmed the potential of these genes as biomarkers, with downregulated expression accurately distinguishing between normal and cancerous tissues. Structural validation of mutated proteins using Ramachandran plots and Protein Structure Analysis (ProSA-web) analysis confirmed the stability of the mutations. Drug prediction and molecular docking identified Resveratrol as a potential therapeutic agent, indicating strong binding affinities with BRCA1, CDK4, and PTEN proteins.

Conclusion: These findings provide novel insights into the genetic underpinnings of ovarian cancer in the Pakistani population and suggest potential targets for therapeutic intervention.

Objective: To identify risk factors for postoperative recurrence in patients with eosinophilic chronic rhinosinusitis with nasal polyps (ECRSwNP) and develop a nomogram prediction model for identifying patients at high risk of recurrence.

Methods: A cohort study involving 200 ECRSwNP patients analyzed clinical data for recurrence predictors using univariate and multivariate logistic regression analyses. A nomogram model was developed and validated using Receiver Operating Characteristic (ROC) curves. Mean absolute error (MAE) calculations evaluated the model's predictive accuracy.

Results: At six-month follow-up, 39 patients (19.5%) experienced recurrence. Factors such as preoperative tissue eosinophil percentage, eosinophil cationic protein (ECP), serum-specific immunoglobulin E (IgE), interleukin-5 (IL-5), and postoperative nasal environment were identified as risk factors for recurrence. The nomogram incorporating these factors demonstrated high predictive accuracy (AUC = 0.989, MAE = 0.026).

Conclusion: This study underscores the significance of individualized risk assessment in managing ECRSwNP recurrence. The developed nomogram provides a robust tool for clinical prognostication, aiding personalized treatment strategies and improving patient outcomes.