## 1 Introduction  
Biobank biological fluid samples (e.g., serum, urine, joint fluid) is an essential component of prospective clinical studies and a means of maximizing the efficiency of using obtained samples. These biological samples and the contents therein (i.e., cellular, molecular) are at risk of being compromised during the pre-analytical phase of projects. The pre-analytical phase is where sample collection technique, handling, and storage protocols may inadvertently alter the components of interest. Cryopreservation of biological fluids requires standardized protocols, reliable inventory, and specialized facilities to preserve valuable samples. Factors that have been shown to impact the stability of the samples during the storage phase are temperature, storage time, and freeze-thaw cycles. The impact of these factors on various biomarkers and sample components has been investigated in previous studies [1; 2; 3]. However, recommendations for optimal storage variables vary depending on the stability of the target components (e.g., molecule being measured) and measurement technique. The use of mid-infrared (MIR) spectral patterns of biological fluids to detect variability between disease states as a novel approach to disease pattern recognition has been investigated at an increasing rate in the past few decades [4; 5; 6; 7; 8; 9; 10; 11; 12]. The spectral pattern of a given sample is the sum of all MIR light absorbance by the infrared-active molecular bonds within the sample, which is displayed as a unique waveform (spectrum) [13]. These unique patterns of spectra of complex samples such as serum can be used as \"fingerprints\" to distinguish between samples that have significantly different absorption patterns due to their composition. These differences in molecular composition can be due to changes caused by underlying disease processes (e.g., inflammatory diseases such as osteoarthritis). Fourier-transform infrared spectroscopy (FTIR) is one of the techniques utilized in acquiring MIR spectra of biological samples that is adjuvant-free, cost-effective, simple, and requires a small volume of samples [5; 6; 7; 8; 9]. Spectral variables (i.e., fingerprints) based on this method have been successfully used in differentiating various types of arthritis in humans [4]. Research in experimental and clinical models of osteoarthritis (OA) in various joints of animal models has also been able to demonstrate the ability to distinguish OA from control samples with high accuracy rates based on the MIR spectra of biological samples (i.e., serum, synovial fluid) [5; 6; 7; 8; 9]. Short-term (\(\sim\)one year) longitudinal studies using spectral variables in serum and joint fluid of animals have shown reproducible spectral characteristics of OA that, despite changes over time, remain distinguishable from control samples [7; 8; 9]. Studies investigating long-term changes in clinical OA in larger animal models (e.g., dogs) and human models require at least several years that warrant biobanking of collected biological samples to allow for batch analysis. These biobanked biological samples (e.g., serum, synovial fluid) are typically stored in \(-80\) degrees Celsius for long-term storage to minimize the impact of time (e.g., degradation of molecules). However, the impact of long-term storage on the spectral pattern of these biological samples has not been previously investigated. The first aim of this study was to evaluate whether long-term storage results in changes in the MIR spectral pattern of serum and synovial samples of dogs with and without knee OA as measured by FTIR spectroscopy. The second aim of this study was to evaluate the impact of any observed changes due to long-term storage on the ability to discriminate between the serum and synovial fluid spectra patterns of dogs with and without knee OA. The hypothesis of the study was that long-term storage would have minimal impact on MIR spectral patterns of serum and synovial fluid of dogs with or without knee OA.