ABSTRACT
Physical therapy is extensively employed in clinical settings. Nevertheless, the absence of suitable animal models has resulted in an incomplete understanding of the in vivo mechanisms and cellular distribution that respond to physical stimuli. The objective of this research was to create a mouse model capable of indicating the cells affected by physical stimuli. In this study, we successfully established a mouse line based on the heat shock protein 70 (Hsp70) promoter, wherein the expression of CreERT2 can be induced by physical stimuli. Following stimulation of the mouse tail, ear, or cultured calvarias with heat shock (generated by heating, ultrasound, or laser), a distinct Cre-mediated excision was observed in cells stimulated by these physical factors with minimal occurrence of leaky reporter expression. The application of heat shock to Hsp70-CreERT2; FGFR2-P253R double transgenic mice or Hsp70-CreERT2 mice infected with AAV-BMP4 at calvarias induced the activation of Cre-dependent mutant FGFR2-P253R or BMP4 respectively, thereby facilitating the premature closure of cranial sutures or the repair of calvarial defects. This novel mouse line holds significant potential for investigating the underlying mechanisms of physical therapy, tissue repair and regeneration, lineage tracing, and targeted modulation of gene expression of cells in local tissue stimulated by physical factor at the interested time points. KEY MESSAGES: In the study, an Hsp70-CreERT2 transgenic mouse was generated for heat shock-induced gene modulation. Heat shock, ultrasound, and laser stimulation effectively activated Cre expression in Hsp70-CreERT2; reporter mice, which leads to deletion of floxed DNA sequence in the tail, ear, and cultured calvaria tissues of mice. Local laser stimuli on cultured calvarias effectively induce Fgfr2-P253R expression in Hsp70-mTmG-Fgfr2-P253R mice and result in accelerated premature closure of cranial suture. Heat shock activated AAV9-FLEX-BMP4 expression and subsequently promoted the repair of calvarial defect of Hsp70-CreERT2; Rosa26-mTmG mice.
Subject(s)
Bone Morphogenetic Protein 4 , HSP70 Heat-Shock Proteins , Mice, Transgenic , Promoter Regions, Genetic , Animals , HSP70 Heat-Shock Proteins/genetics , HSP70 Heat-Shock Proteins/metabolism , Mice , Bone Morphogenetic Protein 4/metabolism , Bone Morphogenetic Protein 4/genetics , Heat-Shock Response/genetics , Skull/metabolism , Gene Expression Regulation , Integrases/metabolism , Integrases/geneticsABSTRACT
The study, using data from Chongqing, China, and employing Mendelian randomization along with bioinformatics, establishes a causal link between asthma and osteoporosis, beyond glucocorticoid effects. Asthma may contribute to osteoporosis by accelerating bone turnover through inflammatory factors, disrupting the coupling between osteoblasts and osteoclasts, ultimately leading to osteoporosis. INTRODUCTION: Asthma and osteoporosis are prevalent health conditions with substantial public health implications. However, their potential interplay and the underlying mechanisms have not been fully elucidated. Previous research has primarily focused on the impact of glucocorticoids on osteoporosis, often overlooking the role of asthma itself. METHODS: We conducted a multi-stage stratified random sampling in Chongqing, China and excluded individuals with a history of glucocorticoid use. Participants underwent comprehensive health examinations, and their clinical data, including asthma status, were recorded. Logistic regression and Mendelian randomization were employed to investigate the causal link between asthma and osteoporosis. Furthermore, bioinformatics analyses and serum biomarker assessments were conducted to explore potential mechanistic pathways. RESULTS: We found a significant association between asthma and osteoporosis, suggesting a potential causal link. Mendelian Randomization analysis provided further support for this causal link. Bioinformatics analyses revealed that several molecular pathways might mediate the impact of asthma on bone health. Serum alkaline phosphatase levels were significantly elevated in the asthma group, suggesting potential involvement in bone turnover. CONCLUSION: Our study confirms a causal link between asthma and osteoporosis and highlights the importance of considering asthma in osteoporosis prediction models. It also suggests that asthma may accelerate osteoporosis by increasing bone turnover through inflammatory factors, disrupting the coupling between osteoblasts and osteoclasts, ultimately leading to bone loss.
Subject(s)
Asthma , Computational Biology , Mendelian Randomization Analysis , Osteoporosis , Humans , Mendelian Randomization Analysis/methods , Asthma/genetics , Asthma/physiopathology , Asthma/epidemiology , Osteoporosis/genetics , Osteoporosis/etiology , Osteoporosis/epidemiology , Osteoporosis/physiopathology , Female , Middle Aged , Computational Biology/methods , Male , Cross-Sectional Studies , Aged , Bone Remodeling/physiology , Bone Remodeling/genetics , Adult , Biomarkers/blood , Polymorphism, Single Nucleotide , China/epidemiology , Genetic Predisposition to Disease , Osteoclasts , Bone Density/genetics , Bone Density/physiologyABSTRACT
PURPOSE: To identify the risk factors for training-related lower extremity muscle injuries in young males by a non-invasive method of body composition analysis. METHODS: A total of 282 healthy young male volunteers aged 18 - 20 years participated in this cohort study. Injury location, degree, and injury rate were adjusted by a questionnaire based on the overuse injury assessment methods used in epidemiological studies of sports injuries. The occurrence of training injuries is monitored and diagnosed by physicians and treated accordingly. The body composition was measured using the BodyStat QuadScan 4000 multifrequency Bio-impedance system at 5, 50, 100 and 200 kHz to obtain 4 impedance values. The Shapiro-Wilk test was used to check whether the data conformed to a normal distribution. Data of normal distribution were shown as mean ± SD and analyzed by t-test, while those of non-normal distribution were shown as median (Q1, Q3) and analyzed by Wilcoxon rank sum test. The receiver operator characteristic curve and logistic regression analysis were performed to investigate risk factors for developing training-related lower extremity injuries and accuracy. RESULTS: Among the 282 subjects, 78 (27.7%) developed training injuries. Lower extremity training injuries revealed the highest incidence, accounting for 23.4% (66 cases). These patients showed higher percentages of lean body mass (p = 0.001), total body water (TBW, p = 0.006), extracellular water (p = 0.020) and intracellular water (p = 0.010) as well as a larger ratio of basal metabolic rate/total weight (p = 0.006), compared with those without lower extremity muscle injuries. On the contrary, the percentage of body fat (p = 0.001) and body fat mass index (p = 0.002) were lower. Logistic regression analysis showed that TBW percentage > 65.35% (p = 0.050, odds ratio = 3.114) and 3rd space water > 0.95% (p = 0.045, odds ratio = 2.342) were independent risk factors for lower extremity muscle injuries. CONCLUSION: TBW percentage and 3rd space water measured with bio-impedance method are potential risk factors for predicting the incidence of lower extremity muscle injuries in young males following training.