Biomechanical Characteristics of Osteoporotic Fracture Healing in Ovariectomized Rats: A Systematic Review

Biomechanical tests are widely used in animal studies on osteoporotic fracture healing. However, the biomechanical recovery process is still unknown, leading to difficulty in choosing time points for biomechanical tests and in correctly assessing osteoporotic fracture healing. To determine the biomechanical recovery process during osteoporotic fracture healing, studies on osteoporotic femur fracture healing with biomechanical tests in ovariectomized rat (OVX) models were collected from PUBMED, EMBASE, and Chinese databases. Quadratic curves of fracture healing time and maximum load were fitted with data from the analyzed studies. In the fitted curve for normal fractures, the predicted maximum load was 145.56 N, and the fracture healing time was 88.0 d. In the fitted curve for osteoporotic fractures, the predicted maximum load was 122.30 N, and the fracture healing time was 95.2 d. The maximum load of fractured femurs in OVX rats was also lower than that in sham rats at day 84 post-fracture (D84 PF). The fracture healing time was prolonged and maximum load at D84 PF decreased in OVX rats with closed fractures. The maximum load of Wister rats was higher than that of Sprague-Dawley (SD) rats, but the fracture healing time of SD and Wister rats was similar. Osteoporotic fracture healing was delayed in rats that were < = 12 weeks old when ovariectomized, and at D84 PF, the maximum load of rats < = 12 weeks old at ovariectomy was lower than that of rats >12 weeks old at ovariectomy. There was no significant difference in maximum load at D84 PF between rats with an osteoporosis modeling time <12 weeks and > = 12 weeks. In conclusion, fracture healing was delayed and biomechanical property decreased by osteoporosis. Time points around D95.2 PF should be considered for biomechanical tests of osteoporotic femur fracture healing in OVX rat models. Osteoporotic fracture healing in OVX rats was affected by the fracture type but not by the strain of the rat.     

中华绒螯蟹蜕壳生长及其与相关基因表达的关联分析

蜕壳是甲壳动物常见的生长发育现象,但对调控蜕壳与生长的内在机制尚缺乏足够了解。本研究在室内条件下,对中华绒螯蟹(Eriocheir sinensis)一个蜕壳周期内的个体蜕壳与生长现象进行了连续观察,分析了2个蜕壳相关基因,即蜕皮激素受体基因(Ec R)和维甲类X受体基因(RXR),以及1个生长相关基因肌肉生长抑制素基因(MSTN)的表达及其与生长性状的相关性。结果发现,中华绒螯蟹在蜕壳后会出现一个跳跃式生长期,之后进入了一个缓慢持续上升过程,当营养物质积累到一定程度(肥满度达60%左右时)时启动下一次蜕壳;MSTN基因的表达与壳长(r=﹣0.450,P0.05)、壳宽(r=﹣0.410,P0.05)增长率呈显著负相关,而与肥满度呈显著正相关(r=0.450,P0.05),Ec R和RXR基因的表达与体重、壳长和壳宽的增长率均没有显著相关性;相对来说,MSTN在蜕壳后的表达量越高,则增重率越小;而Ec R和RXR在蜕壳后表达量越高,其增重率越大。本研究结果表明,中华绒螯蟹在蜕壳后其生长具有一定的规律性,肥满度可以作为衡量中华绒螯蟹体内营养积累启动蜕壳的指标,Ec R、RXR及MSTN基因表达与生长表型具有一定的相关性。     

Study on the interaction between pelargonidin‐3‐O‐glucoside and bovine serum albumin using spectroscopic,transmission electron microscopy and molecular modeling techniques

The aim of this study is to evaluate the binding behavior between pelargonidin‐3‐O‐glucoside (P3G) and bovine serum albumin (BSA) using multi‐spectroscopic, transmission electron microscopy (TEM) and molecular docking methods under physiological conditions. Fluorescence spectroscopy and time‐resolved fluorescence showed that the fluorescence of BSA could be quenched remarkably by P3G via a static quenching mechanism, and there is a single class of binding site on BSA. In addition, the thermodynamic functions ΔH and ΔS were –21.69 kJ/mol and 24.46 J/mol/K, indicating that an electrostatic interaction was a main acting force. The distance between BSA and P3G was 2.74 nm according to Förster's theory, illustrating that energy transfer occurred. In addition, the secondary structure of BSA changed with a decrease in the α‐helix content from 66.2% to 64.0% as seen using synchronous fluorescence, UV/vis, circular dichroism and Fourier transform infrared spectroscopies, whereas TEM images showed that P3G led to BSA aggregation and fibrillation. Furthermore, site marker competitive experiments and molecular docking indicated that P3G could bind with subdomain IIA of BSA. The calculated results of the equilibrium fraction showed that the concentration of free P3G in plasma was high enough to be stored and transported from the circulatory system to its target sites to provide therapeutic effects. Copyright © 2015 John Wiley & Sons, Ltd.     

Dual‐function fluorescent probe for cancer imaging and therapy

To date, several fluorescent probes modified by a single targeting agent have been explored. However, studies on the preparation of dual‐function quantum dot (QD) fluorescent probes with dual‐targeting action and a therapeutic effect are rare. Here, a dual‐targeting CdTe/CdS QD fluorescent probe with a bovine serum albumin–glycyrrhetinic acid conjugate and arginine‐glycine‐aspartic acid was successfully prepared that could induce the apoptosis of liver cancer cells and showed enhanced targeting in in vitro cell imaging. Therefore, the as‐prepared fluorescent probe in this work is an efficient diagnostic tool for the simultaneous detection of liver cancer and breast cancer cells. Copyright © 2015 John Wiley & Sons, Ltd.     

Stage 2 Process Performance Qualification (PPQ): a Scientific Approach to Determine the Number of PPQ Batches

The approach documented in this article reviews data from earlier process validation lifecycle stages with a described statistical model to provide the “best estimate” on the number of process performance qualification (PPQ) batches that should generate sufficient information to make a scientific and risk-based decision on product robustness. This approach is based upon estimation of a statistical confidence from the current product knowledge (Stage 1), historical variability for similar products/processes (batch-to-batch), and label claim specifications such as strength. The analysis is to determine the confidence level with the measurements of the product quality attributes and to compare them with the specifications. The projected minimum number of PPQ batches required will vary depending on the product, process understanding, and attributes, which are critical input parameters for the current statistical model. This new approach considers the critical finished product CQAs (assay, dissolution, and content uniformity), primarily because assay/content uniformity and dissolution as well as strength are the components of the label claim. The key CQAs determine the number of PPQ batches. This approach will ensure that sufficient scientific data is generated to demonstrate process robustness as desired by the 2011 FDA guidance.