Experimental Biology and Medicine最新文献

The sex difference in depression has long been an unsolved issue. Women are twice as likely to suffer from depression as men. However, there were significant differences in the composition of gut microbiota between women and men. There is a lack of studies linking sex differences in depression to microbiota, and the specific mechanisms of this process have not been explained in detail. The main purpose of this study was to explore the gender differences in the intestinal tract of male and female depressed mice. In this study, chronic restraint stress (CRS) mouse models were used to simulate chronic stress, and behavioral tests were conducted, including the open field test (OFT), tail suspension test (TST) and forced swimming test (FST). Microbial diversity analysis and metabolomics were performed on collected mouse feces. The results showed that female mice were highly active and prone to anxious behavior before stress, and the levels of f-Rikenellaceae, f-Ruminococcaceae and 16α-hydroxyestrone were significantly different from those in male mice. After 21 days (Days) of stress, female mice showed depression-like behavior, and the levels of f-Erysipelotrichaceae, 5α-pregnane-3,20-dione, and 2-hydroxyestradiol were significantly different from those in male mice. After 14 days of stress withdrawal, the depression-like behavior continued to worsen in female mice, and the levels of 5α-pregnane-3,20-dione, estrone glucuronide and f-Erysipelotrichaceae were significantly different from those in male mice. In summary, female mice have stronger stress sensitivity and weaker resilience than male mice, which may be related to differences in bacterial diversity and estrogen metabolism disorders.

In recent years, the relationship between the immunosuppressive niche of the bone marrow and therapy resistance in acute myeloid leukemia (AML) has become a research focus. The abnormal number and function of immunosuppressive cells, including regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs), along with the dysfunction and exhaustion of immunological effector cells, including cytotoxic T lymphocytes (CTLs), dendritic cells (DCs) and natural killer cells (NKs), can induce immune escape of leukemia cells and are closely linked to therapy resistance in leukemia. This article reviews the research progress on the relationship between immune cells in the marrow microenvironment and chemoresistance in AML, aiming to provide new ideas for the immunotherapy of AML.

Bone fractures and bone loss represent significant global health challenges, with their incidence rising due to an aging population. Despite autologous bone grafts remain the gold standard for treatment, challenges such as limited bone availability, immune reactions, and the risk of infectious disease transmission have driven the search for alternative cell-based therapies for bone regeneration. Stem cells derived from oral tissues and umbilical cord mesenchymal stem cells (MSCs) have shown potential in both preclinical and clinical studies for bone tissue regeneration. However, their limited differentiation capacity and wound healing abilities necessitate the exploration of alternative cell sources. In this study, we generated induced pluripotent stem cells (iPSCs) using a safe, nonviral and mRNA-based approach from human periodontal ligament fibroblasts (PDLF), an easily accessible cell source. These iPSCs were subsequently differentiated into MSCs, referred to as induced MSCs (iMSCs). The resulting iMSCs were homogeneous, highly proliferative, and possessed anti-inflammatory properties, suggesting their potential as a superior alternative to traditional MSCs for regenerative therapy. These iMSCs demonstrated trilineage differentiation potential, giving rise to osteocytes, chondrocytes, and adipocytes. The iMSC-derived osteocytes (iOSTs) were homogeneous, patient-specific and showed excellent attachment and growth on commercial collagen-based membranes, highlighting their suitability for bone tissue regeneration applications. Given their promising characteristics compared to traditional MSCs, PDLF-derived iMSCs are strong candidates for future clinical studies in bone regeneration and other regenerative dental therapies.

Investigations on some innate immunity proteins can yield misleading information, as investigators often rely on static measurements and assume a direct correlation to function. As protein function is often not directly proportional to protein abundance, and mechanistic pathways are interconnected and under constant feedback regulatory control, functional analysis is required. In this study, we used functional mass spectrometry to measure anti-protease and complement activity in plasma obtained from coronavirus disease 2019 (COVID-19) patients. Our data suggests that within 48 h of hospital admission, COVID-19 patients undergo a protease storm with significantly elevated neutrophil elastase (p < 0.001) and lymphocyte granzyme B (p < 0.01), while, anti-protease activity is significantly increased, including alpha-1 antitrypsin (AAT; p < 0.001) and alpha-1-antichymotrypsin (ACT; p < 0.001). Concurrently, the ratio of C3a to C3beta activity significantly decreased with increasing COVID-19 severity, suggesting more complement activation (Mild COVID-19 p < 0.05; Severe COVID-19 p < 0.001). Activity levels of AAT, ACT and C3a/C3beta remained unchanged over 10 hospital days. Our data suggests that COVID-19 is associated with both a protease storm and complement activation, with the former somewhat balanced with increased anti-protease activity. Evaluation of the AAT/ACT ratio and C3a/C3beta ratio indicated that COVID-19 severity is associated with both neutrophil elastase neutralization and complement activation.

Periostin and osteopontin are matricellular proteins abundantly expressed in bone fracture callus. Null mutation of either the periostin (Postn) gene or the osteopontin (Spp1) gene can impair bone fracture healing. However, the cell and molecular pathways affected by loss of POSTN or SPP1 which lead to impaired fracture healing are not well understood. To identify potential pathways, a detailed radiological, histological, and immunohistochemical analysis of femur fracture healing in Postn-null (PostnKO), Spp1-null (Spp1KO), and normal (WT) mice was performed. Apparent changes in specific protein levels identified by immunohistochemistry were confirmed by mRNA quantitation. Comparisons between the PostnKO and Spp1KO fracture calluses were confounded by interactions between the two genes; loss of Postn reduced Spp1 expression and loss of Spp1 reduced Postn expression. Consequently, alterations in fracture healing between mice heterozygous for the Postn-null allele (PostnHET) as well as the PostnKO and Spp1KO mice were similar. Calluses from PostnHET, PostnKO, and Spp1KO mice all had dysmorphic chondro-osseous junctions and reduced numbers of osteoclasts. The dysmorphic chondro-osseous junctions in the PostnHET, PostnKO, and Spp1KO calluses were associated with reduced numbers of MMP-13 expressing hypertrophic chondrocytes, consistent with delayed cartilage resolution. Unlike collagen X expressing callus chondrocytes, chondrocytes only expressed MMP-13 when localized to the chondro-osseous junction or after traversing the chondro-osseous junction. Cyclooxygenase-2 (COX-2) expression also appeared to be reduced in osteoclasts from the PostnHET, PostnKO, and Spp1KO calluses, including in those osteoclasts localized at the chondro-osseous junction. The results indicate that POSTN and SPP1 are necessary for normal chondro-osseous junction formation and that signaling from the chondro-osseous junction, possibly from COX-2 expressing osteoclasts, regulates callus vasculogenesis and chondrocyte hypertrophy necessary for endochondral ossification during fracture healing.

[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.

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.