Veterinary systems biology for bridging the phenotype-genotype gap via computational modeling for disease epidemiology and animal welfare.

Veterinary systems biology is an innovative approach that integrates biological data at the molecular and cellular levels, allowing for a more extensive understanding of the interactions and functions of complex biological systems in livestock and veterinary science. It has tremendous potential to integrate multi-omics data with the support of vetinformatics resources for bridging the phenotype-genotype gap via computational modeling. To understand the dynamic behaviors of complex systems, computational models are frequently used. It facilitates a comprehensive understanding of how a host system defends itself against a pathogen attack or operates when the pathogen compromises the host's immune system. In this context, various approaches, such as systems immunology, network pharmacology, vaccinology and immunoinformatics, can be employed to effectively investigate vaccines and drugs. By utilizing this approach, we can ensure the health of livestock. This is beneficial not only for animal welfare but also for human health and environmental well-being. Therefore, the current review offers a detailed summary of systems biology advancements utilized in veterinary sciences, demonstrating the potential of the holistic approach in disease epidemiology, animal welfare and productivity.

Diagnostic Roots Radiofrequency Sensory Stimulation Looking for Symptomatic Injured Roots in Multiple Lumbar Stenosis.

Objective: We present how to perform radiofrequency sensory stimulation (RFSS) and whether RFSS could be helpful in identifying symptomatic injured roots in multilevel lumbar stenosis. Methods: Consecutive patients who underwent RFSS from 2010 to 2012 were enrolled. To identify pathologic lesions, RFSS was performed for suspicious roots, as determined using lumbar magnetic resonance imaging (MRI). The RFSS procedure resembled transforaminal root block. During RFSS of the suspicious root, patients could indicate whether stimulation induced their usual pain and/or sensory changes and could indicate whether the same leg area was affected. The number of possible symptomatic roots on MRI was evaluated before and after RFSS. Based on the RFSS results, we confirmed the presence of symptomatic nerve root(s) and performed surgical decompression. Surgical results, such as numeric rating scale (NRS) scores for low back pain (LBP) and leg pain (LP), and Oswestry disability index (ODI), were evaluated. Results: Ten patients were enrolled in the study. Their mean age was 70.1±9.7 years. Clinically, NRS-LBP, NRS-LP, and ODI before surgery were 5.1%, 7.5%, and 53.2%, respectively. The mean number of suspicious roots was 2.6±0.8. After RFSS, the mean number of symptomatic roots was 1.6±1.0. On average, 1.4 lumbar segments were decompressed. The follow-up period was 35.3±12.8 months. At the last follow-up, NRS-LBP, NRS-LP, and ODI were 3.1%, 1.5%, and 35.3%, respectively. There was no recurrence or need for further surgical treatment for lumbar stenosis. Conclusion: RFSS is a potentially helpful diagnostic tool for verifying and localizing symptomatic injured root lesions, particularly in patients with multilevel spinal stenosis.