Experimental Biology and Medicine最新文献

[This retracts the article DOI: 10.1258/ebm.2011.010361.].

Blood-based biomarkers for motor neuron disease are needed for better diagnosis, progression prediction, and clinical trial monitoring. We used whole blood-derived total RNA and performed whole transcriptome analysis to compare the gene expression profiles in (motor neurone disease) MND patients to the control subjects. We compared 42 MND patients to 42 aged and sex-matched healthy controls and described the whole transcriptome profile characteristic for MND. In addition to the formal differential analysis, we performed functional annotation of the genomics data and identified the molecular pathways that are differentially regulated in MND patients. We identified 12,972 genes differentially expressed in the blood of MND patients compared to age and sex-matched controls. Functional genomic annotation identified activation of the pathways related to neurodegeneration, RNA transcription, RNA splicing and extracellular matrix reorganisation. Blood-based whole transcriptomic analysis can reliably differentiate MND patients from controls and can provide useful information for the clinical management of the disease and clinical trials.

Screening tests for disease have their performance measured through sensitivity and specificity, which inform how well the test can discriminate between those with and without the condition. Typically, high values for sensitivity and specificity are desired. These two measures of performance are unaffected by the outcome prevalence of the disease in the population. Research projects into the health of the American Indian frequently develop Machine learning algorithms as predictors of conditions in this population. In essence, these models serve as in silico screening tests for disease. A screening test's sensitivity and specificity values, typically determined during the development of the test, inform on the performance at the population level and are not affected by the prevalence of disease. A screening test's positive predictive value (PPV) is susceptible to the prevalence of the outcome. As the number of artificial intelligence and machine learning models flourish to predict disease outcomes, it is crucial to understand if the PPV values for these in silico methods suffer as traditional screening tests in a low prevalence outcome environment. The Strong Heart Study (SHS) is an epidemiological study of the American Indian and has been utilized in predictive models for health outcomes. We used data from the SHS focusing on the samples taken during Phases V and VI. Logistic Regression, Artificial Neural Network, and Random Forest were utilized as in silico screening tests within the SHS group. Their sensitivity, specificity, and PPV performance were assessed with health outcomes of varying prevalence within the SHS subjects. Although sensitivity and specificity remained high in these in silico screening tests, the PPVs' values declined as the outcome's prevalence became rare. Machine learning models used as in silico screening tests are subject to the same drawbacks as traditional screening tests when the outcome to be predicted is of low prevalence.

Malaria causes significant morbidity and mortality worldwide, disproportionately impacting sub-Saharan Africa. Disease phenotypes associated with Plasmodium falciparum infection can vary widely, from asymptomatic to life-threatening. To date, prevention efforts, particularly those related to vaccine development, have been hindered by an incomplete understanding of which factors impact host immune responses resulting in these divergent outcomes. Here, we conducted a field study of 224 individuals to determine host-parasite factors associated with symptomatic malaria "patients" compared to asymptomatic malaria-positive "controls" at both the community and healthy facility levels. We further performed comprehensive immune profiling to obtain deeper insights into differences in response between the pair. First, we determined the relationship between host age and parasite density in patients (n = 134/224) compared to controls (n = 90/224). Then, we applied single-cell RNA sequencing to compare the immunological phenotypes of 18,176 peripheral blood mononuclear cells isolated from a subset of the participants (n = 11/224), matched on age, sex, and parasite density. Patients had higher parasite densities compared to the controls, although the levels had a negative correlation with age in both groups, suggesting that they are key indicators of disease pathogenesis. On average, patients were characterized by a higher fractional abundance of monocytes and an upregulation of innate immune responses, including those to type I and type II interferons and tumor necrosis factor-alpha signaling via NFκB. Further, in the patients, we identified more putative interactions between antigen-presenting cells and proliferating CD4 T cells, and naïve CD8 T cells driven by MHC-I and MHC-II signaling pathways, respectively. Together, these findings highlight transcriptional differences between immune cell subsets associated with disease phenotypes that may help guide the development of improved malaria vaccines and new therapeutic interventions.

Macrophages are effector cells of the immune system and essential modulators of immune responses. Different functional phenotypes of macrophages with specific roles in the response to stimuli have been described. The C57BL/6 and BALB/c mouse strains tend to selectively display distinct macrophage activation states in response to pathogens, namely, the M1 and M2 phenotypes, respectively. Herein we used RNA-Seq and differential expression analysis to characterize the baseline gene expression pattern of unstimulated resident peritoneal macrophages from C57BL/6 and BALB/c mice. Our aim is to determine if there is a possible predisposition of these mouse strains to any activation phenotype and how this may affect the interpretation of results in studies concerning their interaction with pathogens. We found differences in basal gene expression patterns of BALB/c and C57BL/6 mice, which were further confirmed using RT-PCR for a subset of relevant genes. Despite these differences, our data suggest that baseline gene expression patterns of both mouse strains do not appear to determine by itself a specific macrophage phenotype.

Hypertrophic cardiomyopathy (HCM) is a genetic cardiac disorder associated with an increased risk of arrhythmias, heart failure, and sudden cardiac death. Current imaging and clinical markers are not fully sufficient in accurate diagnosis and patient risk stratification. Although known cardiac biomarkers in blood are used, they lack specificity for HCM and primarily stratify for death due to heart failure in overt cases. Non-coding RNAs, particularly microRNAs, have emerged as promising biomarkers due to their role in regulating gene expression in both healthy and pathological hearts. Circulating microRNA signatures may dynamically reflect the progression of HCM, offering potential utility in diagnosis and disease monitoring as well as inform biologic pathways for innovative therapeutic strategies. However, studying microRNAs in cardiovascular diseases is still in its early stages and poses many challenges. This review focuses on emerging research perspectives using advanced cardiac magnetic resonance techniques. We presume, that the search for circulating miR signatures associated with specific adverse myocardial features observed on cardiac magnetic resonance imaging - such as fibrosis, disarray, and microvascular disease - represents a promising direction in HCM research.

[This corrects the article DOI: 10.1177/15353702231182214.].

Patients with type 2 diabetes mellitus (T2DM) have increased hip fracture risk. And the association between urine albumin to creatinine ratio (ACR) and an increased risk of hip fracture in patients with T2DM remains controversial. This study aimed to investigate the association between urinary ACR and hip fracture risk in postmenopausal women and aged men with T2DM. The study included 219 postmenopausal women and 216 older men (mean age >60 years) with T2DM. Women and men were divided into control group (ACR<30 mg/g), microalbuminuria group (30 mg/g ≤ ACR<300 mg/g), and macroalbuminuria group (ACR≥300 mg/g) respectively. Demographic characteristics and clinical history were collected in patients. Biochemical indexes and bone turnover-related markers were measured in patients. In the study, we found that several factors, including age, T2DM duration, cerebral infarction history, serum corrected calcium levels and urine ACR were positively associated with hip fracture risk. However, 25-Hydroxyvitamin D and areal BMD were negatively associated with hip fracture risk. Furthermore, multiple regression analysis showed that urinary ACR level (β = 0.003, p = 0.044) and duration of T2DM (β = 0.015, p = 0.018) were positively and independently correlated with hip fracture risk in older men. In contrast, femoral neck BMD (β = -6.765, p < 0.001) was independently and negatively correlated with hip fracture risk in older men. This study indicated that the elevated ACR levels and longer T2DM duration were related to higher hip fracture risk in older men with T2DM, which could be beneficial for developing a predictive model for osteoporotic fractures in patients with type 2 diabetes in the future. However, results were inconsistent in women, hip fracture risk didn't alter by changes in urinary microalbuminuria level in postmenopausal women with T2DM.

Advanced glycation end products (AGEs) have adverse effects on the development of diabetic complications. Berberine (BBR), a natural alkaloid, has demonstrated its ability to promote the delayed healing of skin wounds. However, the impact of BBR on AGEs-induced ferroptosis in skin cells and the underlying molecular mechanisms remains unexplored. This study investigated the involvement of ferroptosis in AGEs-induced keratinocyte death, and the impact of BBR on ferroptosis in a db/db mouse model with long-term hyperglycemia was elucidated. A remarkable reduction in cell viability was observed along with increased malondialdehyde (MDA) production in AGEs-induced HaCaT cells. Intracellular reactive oxygen species (ROS) and iron levels were elevated in cells exposed to AGEs. Meanwhile, the protein expression of glutathione peroxidase 4 (GPX4) and ferritin light chain (FTL) was significantly decreased in AGEs-treated cells. However, pretreatment with BBR markedly protected cell viability and inhibited MDA levels, attenuating the intracellular ROS and iron levels and increased expression of GPX4 and FTL in vitro. Significantly diminished antiferroptotic effects of BBR on AGEs-treated keratinocytes were observed upon the knockdown of the nuclear factor E2-related factor 2 (NRF2) gene. In vivo, GPX4, FTL, and FTH expression in the epidermis of diabetic mice was significantly reduced, accompanied by enhanced lipid peroxidation. Treatment with BBR effectively rescued lipid peroxidation accumulation and upregulated GPX4, FTL, FTH, and NRF2 levels in diabetic skin. Collectively, the findings indicate that ferroptosis may play a significant role in AGEs-induced keratinocyte death. BBR protects diabetic keratinocytes against ferroptosis, partly by activating NRF2.

Gastric cancer (GC) is the kind of carcinoma that has the highest rates of morbidity and death worldwide. In the early stages of GC, there is currently an absence of sensitive and specific biomarkers. The newly-discovered class of non-coding RNAs (ncRNAs) known as transfer RNA-derived small RNAs (tsRNAs) is highly expressed in bodily fluids and neoplastic cells. High-throughput sequencing was initially employed to identify differentially expressed tsRNAs in early GC patients, followed by validation in patient serum, GC tissues, and cell lines by quantitative real-time polymerase chain reaction (qRT-PCR). We identified dysregulated tsRNAs (the up-regulated tsRNAs included tRF-31-PNR8YP9LON4VD, tRF-30-MIF91SS2P4FI, and tRF-30-IK9NJ4S2I7L7, whereas the down-regulated tsRNAs included tRF-38-W6RM7KYUPRENRHD2, tRF-37-LBRY73W0K5KKOV2, tRF-36-JB59V3WD8YQ84VD, tRF-25-MBQ4NKKQBR, and tRF-36-0KFMNKYUHRF867D) in GC, and we verified that the serum of patients, GC cells and tissues both consistently expressed these tsRNAs. Additionally, GC patients' serum had considerably greater expression levels of the three up-regulated tsRNAs than did healthy controls. Receiver operating characteristic (ROC) curve analysis demonstrated that the sensitivity and specificity of the three up-regulated tsRNAs were superior to those of CEA, CA199, and CA724 in the process of diagnosing GC, particularly in its early stages. This suggests that tsRNAs have great diagnostic efficacy and potential as new "liquid biopsy" biomarkers for the diagnosis of GC. Using bioinformatics software, we predicted that dysregulation of tsRNAs may be a potential regulatory mechanism for the development of GC.