Sex- and Age-Related Changes in Connexin 43 Expression in Normal Rat Bladder

Purpose Gap junctions are intercellular channels to facilitate electrical and metabolic communication between adjacent cells. Connexin 43 is the most predominant type of connexin expressed on rat detrusor muscle cells. We investigated the connexin 43 expressions in various age groups of either sex in normal rats. Methods Eighty Sprague-Dawley rats were used for analysis. Each group was quantified by 8 rats at 1 week, 2 weeks, 1 month, 3 months, and 6 months of age in either sex. In each animal, bladder was removed without any kind of intervention and fresh-frozen in liquid nitrogen. Total RNA extraction was done with easy-BLUE total RNA extraction kit. Reverse transcription polymerase chain reaction was done for connexin 43 and glyceraldehyde-3-phosphate dehydrogenase as an internal control using ImProm-II Reverse Transcription System. Results In female rats, no age-related change was detected in connexin 43 expressions. In male rats, connexin expression at 3 months of age showed significant decrease compared with 1 week, 2 weeks, and 6 months of age (P<0.05). When connexin expression at the same age in male and female were compared, only 3 months group in male showed significant decrease than the same age group in female. Conclusions Our data suggest that the expressions of connexin 43 mRNA in normal detrusor muscle cell showed age-related changes especially in male rats. Although it is difficult to interpret these findings at this stage, age should be considered as a possible compounding factor affecting connexin 43 expressions in male rats

GT2008-50479 A TIME-DOMAIN FLUID-STRUCTURE INTERACTION ANALYSIS OF FAN BLADES

ABSTRACT This paper presents aerodynamic and aeromechanical analyses for an entire row of fan blades (i.e. tens of blades with a finite aspect ratio) subject to a uniform incoming flow. In this regard, a new unsteady three-dimensional vortex lattice model has been developed for multiple blades in discrete time domain. Using the new model, the characteristics of the unsteady aerodynamic forces on vibrating blades, including their temporal development, are examined. Also, the new aerodynamic model is applied to examine the aeromechanical behavior of fan blades by using a standard eigenvalue analysis. For this analysis, the fan blades have been modeled as threedimensional plates, and, increasing the number of blades (or solidity) is predicted to destabilize the fan blade row. INTRODUCTION Fluid-structure interaction phenomena occur in many scientific and engineering applications, including aircraft wings and turbomachinery blades. Understanding fluid structure interactions in turbomachinery is important because such interactions lead to fatigue and ultimately structural damage of blades. The fluid structure interaction analyses require modeling of unsteady aerodynamics which can be conducted in either time or frequency domain. In the time domain analyses, Euler and Navier-Stokes solvers are used to calculate unsteady aerodynamic forces on turbomachinery blades. At each time step, for a given geometry, the flow field is solved to determine the aerodynamic forces acting on the blades. Subsequently, the forces are used to analyze the blades&apos; motions and update their displacements. The entire process is then repeated. Such time domain analyses require extensive computation time and cost [1,2]. On the other hand, unsteady aerodynamic analysis can also be carried out in the frequency domain, and the frequency domain approaches have been applied to calculate unstead

Newly designed coil tube for bowel decompression in patients with small bowel obstructions

AbstractBackgroundThe purpose of this study was to clinically evaluate a coil tube that we recently designed for bowel decompression in patients with a small bowel obstruction.MethodsThe coil tube was composed of a stainless steel coil, a polyolefin tube, and a rubber adaptor. The tube was inserted under fluoroscopic guidance in 14 consecutive patients with small bowel obstructions. Technical success was defined as insertion of the distal end of the tube into at least the proximal jejunum, and clinical success was defined as intestinal decompression and relief of obstructive symptoms.ResultsThe technical success rate was 100%. Clinical success was achieved in 12 patients (86%). The clinical failures were a patient with peritoneal carcinomatosis and an ileocolic fistula, and a patient with bezoars following intestinal hemorrhage. No coil-related complications occurred.ConclusionOur newly designed coil tube was safe and effective in patients with bowel decompression associated with a small bowel obstruction. In addition, our tube has several advantages over other currently used tube types

The Effects of Progressive Resistance Exercise on Recovery Rate of Bone and Muscle in a Rodent Model of Hindlimb Suspension

Purpose: This study aimed to examine the exercise-mediated musculoskeletal recovery following hindlimb suspension (HS) in order to identify whether bone modeling and muscle hypertrophy would eventuate in a synchronized manner during recovery stage.Methods: To identify whether 2-week HS would be sufficient to induce a significant reduction of physiological indices in both tibia and adjacent hindlimb muscles, a total of 20 rats was randomized into 2-week HS (n = 10) and age-matched control group (n = 10, CON). Another batch of rats were randomly assigned to three different groups to identify recovery intervention effects following suspension: (1) 2-week HS followed by 4-week spontaneous reloading recovery (HRE, n = 7). (2) 2-week HS followed by 4-week progressive resistance ladder climbing exercise (HEX, n = 7). (3) Age-matched control (CON, n = 7). DXA, micro-CT, and 18F-sodium fluoride (NaF) imaging, and EIA analysis were utilized to measure tibia bone indices. Hindlimb muscle wet weight and grip strength were measured to evaluate muscle mass and strength, respectively.Results: In study 1, bone quality values [bone volume/total volume (BV/TV): -27%, areal bone mineral density (aBMD): -23%, mineral contents: -7.9%, mineral density: –4.1%, and bone density: -38.9%] and skeletal muscle weight (soleus: -46.8%, gastrocnemius: -19.6%, plantaris: -20.8%, TA: -22.8%, and EDL: -9.9%) were significantly lower in HS group compared to CON group. In study 2, micro-CT and DXA-based bone morphology (bone density, BT/TV, and aBMD) were fully recovered in HRE or HEX group. However, suspension-induced dysregulation of bone mineral metabolism was returned to age-matched control group in only HEX group, but not in HRE group. A greater level of biomarkers of bone formation (P1NF) and resorption (CTX-1) was observed in only HRE group compared to CON. The hindlimb skeletal muscle mass was significantly lower in both HRE and HEX groups compared to CON group. Hindlimb grip strength was the greatest in HEX group, followed by CON and HRE groups.Conclusion: Following HS, progressive resistance exercise promotes recovery rates of bone and skeletal muscle strength without a significant increase in muscular mass, suggesting that exercise-induced reacquisition of bone and muscle strength is independent of muscle hypertrophy during early recovery stage

Development of a Computational Framework for Big Data-Driven Prediction of Long-Term Bridge Performance and Traffic Flow

Consistent efforts with dense sensor deployment and data gathering processes for bridge big data have accumulated profound information regarding bridge performance, associated environments, and traffic flows. However, direct applications of bridge big data to long-term decision-making processes are hampered by big data-related challenges, including the immense size and volume of datasets, too many variables, heterogeneous data types, and, most importantly, missing data. The objective of this project was to develop a foundational computational framework that can facilitate data collection, data squashing, data merging, data curing, and, ultimately, data prediction. By using the framework, practitioners and researchers can learn from past data, predict various information regarding long-term bridge performance, and conduct data-driven efficient planning for bridge management and improvement. This research project developed and validated several computational tools for the aforementioned objectives. The programs include (1) a data-squashing tool that can shrink years-long bridge strain sensor data to manageable datasets, (2) a data-merging tool that can synchronize bridge strain sensor data and traffic flow sensor data, (3) a data-curing framework that can fill in arbitrarily missing data with statistically reliable values, and (4) a data-prediction tool that can accurately predict bridge and traffic data. In tandem, this project performed a foundational investigation into dense surface sensors, which will serve as a new data source in the near future. The resultant hybrid datasets, detailed manuals, and examples of all programs have been developed and are shared via web folders. The conclusion from this research was that the developed framework will serve practitioners and researchers as a powerful tool for making big data-driven predictions regarding the long-term behavior of bridges and relevant traffic information