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1.
Injury ; 55(8): 111658, 2024 Jun 11.
Article in English | MEDLINE | ID: mdl-38879923

ABSTRACT

BACKGROUND: Accidental impact on a player's head by a powerful soccer ball may lead to brain injuries and concussions during games. It is crucial to assess these injuries promptly and accurately on the field. However, it is challenging for referees, coaches, and even players themselves to accurately recognize potential injuries and concussions following such impacts. Therefore, it is necessary to establish a list of minimum ball velocity thresholds that can result in concussions at different impact locations on the head. Additionally, it is important to identify the affected brain regions responsible for impairments in brain function and potential clinical symptoms. METHODS: By using a full human finite element model, dynamic responses and brain injuries caused by unintentional soccer ball impacts on six distinct head locations (forehead, tempus, crown, occiput, face, and jaw) at varying ball velocities (10, 15, 20, 25, 30, 35, 40, and 60 m/s) were simulated and investigated. Intracranial pressure, Von-Mises stress, and first principal strain were analyzed, the ball velocity thresholds resulting in concussions at different impact locations were evaluated, and the damage evolution patterns in the brain tissue were analyzed. RESULTS: The impact on the occiput is most susceptible to induce brain injuries compared to all other impact locations. For a conservative assessment, the risk of concussion is present once the soccer ball reaches 17.2 m/s in a frontal impact, 16.6 m/s in a parietal impact, 14.0 m/s in an occipital impact, 17.8 m/s in a temporal impact, 18.5 m/s in a facial impact or 19.2 m/s in a mandibular impact. The brain exhibits the most significant dynamic responses during the initial 10-20 ms, and the damaged regions are primarily concentrated in the medial temporal lobe and the corpus callosum, potentially causing impairments in brain functions. CONCLUSIONS: This work offers a framework for quantitatively assessing brain injuries and concussions induced by an unintentional soccer ball impact. Determining the ball velocity thresholds at various impact locations provides a benchmark for evaluating the risks of concussion. The examination of brain tissue damage evolution introduces a novel approach to linking biomechanical responses with possible clinical symptoms.

2.
J Ren Nutr ; 2024 May 29.
Article in English | MEDLINE | ID: mdl-38821451

ABSTRACT

OBJECTIVES: Chronic kidney disease (CKD) significantly contributes to the socio-economic burden both in China and worldwide. Previous research has shown that experiencing childhood famine is linked to various chronic conditions like diabetes, hypertension, and proteinuria. However, the long-term effects of early-life famine exposure on adult kidney function remain unclear. This study investigates whether exposure to the Chinese Great Famine (1959-1962) is associated with a decline in glomerular filtration rate (GFR) later in life. DESIGN AND METHODS: China Health and Retirement Longitudinal Study is a population-based observational study. We analyzed data from 8,828 participants in the 2011-2012 baseline survey, updated in 2014. Participants were categorized based on their birth year into fetal-exposed (1959-1962), childhood-exposed (1949-1958), adolescence/adult-exposed (1912-1948), and nonexposed (1963-1989) groups. The estimated GFR (eGFR) was calculated using the CKD-EPI-Cr-Cys equation (2021), with CKD defined as an eGFR below 60 mL/min/1.73 m2. RESULTS: Average eGFR values were 103.0, 96.8, 91.2, and 76.3 mL/min/1.73 m2 for the fetal-exposed, childhood-exposed, adolescence/adult-exposed, and nonexposed groups, respectively. The eGFR in the exposed groups was significantly lower compared to the nonexposed group. Specifically, famine exposure correlated with a lower eGFR (coefficient estimates [CE] -9.14, 95% confidence interval [CI] -9.46, -8.82), with the strongest association observed in the adolescence/adult-exposed group (CE -26.74, 95% CI -27.75, -25.74). Adjusting for variables such as demographics, physical and laboratory tests, complications, and personal habits like smoking and drinking did not qualitatively alter this association (CE -1.38, 95% CI -1.72, -1.04). Further stratification by sex, body mass index, alcohol consumption history, hypertension, diabetes, Center for Epidemiologic Studies Depression score, and education level showed that the association remained consistent. CONCLUSIONS: Exposure to famine during different life stages can have enduring effects on GFR decline in humans.

3.
Dis Markers ; 2022: 2700392, 2022.
Article in English | MEDLINE | ID: mdl-36092962

ABSTRACT

Background: Diabetic nephropathy (DN), a significant cause of chronic kidney disease (CKD), is a devastating disease worldwide. Objective: The aim of this study was to reveal crucial genes closely linked to the molecular mechanism of tubulointerstitial injury in DN. Methods: The Gene Expression Omnibus (GEO) database was used to download the datasets. Based on this, a weighted gene coexpression network analysis (WGCNA) network was constructed to detect DN-related modules and hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichments were performed on the selected hub genes and modules. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed on the obtained gene signature. Results: The WGCNA network was constructed based on 3019 genes, and nine gene coexpression modules were generated. A total of 57 genes, including 34 genes in the magenta module and 23 genes in the purple module, were adapted as hub genes. 61 significantly downregulated and 119 upregulated genes were screened as differentially expressed genes (DEGs). 25 overlapping genes between hub genes chosen from WGCNA and DEG were identified. Through LASSO analysis, a 9-gene signature may be a potential prognostic biomarker for DN. To further explore the potential mechanism of DN, the different immune cell infiltrations between tubulointerstitial samples of DN and healthy samples were estimated. Conclusions: This bioinformatics study identified CX3CR1, HRG, LTF, TUBA1A, GADD45B, PDK4, CLIC5, NDNF, and SOCS2 as candidate biomarkers for the diagnosis of DN. Moreover, DN tends to own a higher proportion of memory B cell.


Subject(s)
Diabetes Mellitus , Gene Expression Profiling , Biomarkers , Gene Regulatory Networks , Humans , Prognosis
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