Robustness of a multivariate composite score when evaluating distress of animal models for gastrointestinal diseases.

The fundament of an evidence-based severity assessment in laboratory animal science is reliable distress parameters. Many readouts are used to evaluate and determine animal distress and the severity of experimental procedures. Therefore, we analyzed four distinct parameters like the body weight, burrowing behavior, nesting, and distress score in the four gastrointestinal animal models (pancreatic ductal adenocarcinoma (PDA), pancreatitis, CCl4 intoxication, and bile duct ligation (BDL)). Further, we determined the parameters' robustness in various experimental subgroups due to slight variations like drug treatment or telemeter implantations. We used non-parametric bootstrapping to get robust estimates and 95% confidence intervals for the experimental groups. It was found that the performance of the readout parameters is model-dependent and that the distress score is prone to experimental variation. On the other hand, we also found that burrowing and nesting can be more robust than, e.g., the body weight when evaluating PDA. However, the body weight still was highly robust in BDL, pancreatitis, and CCl4 intoxication. To address the complex nature of the multi-dimensional severity space, we used the Relative Severity Assessment (RELSA) procedure to combine multiple distress parameters into a score and mapped the subgroups and models against a defined reference set obtained by telemeter implantation. This approach allowed us to compare the severity of individual animals in the experimental subgroups using the maximum achieved severity (RELSAmax). With this, the following order of severity was found for the animal models: CCl4 < PDA ≈ Pancreatitis < BDL. Furthermore, the robustness of the RELSA procedure and outcome was externally validated with a reference set from another laboratory also obtained from telemeter implantation. Since the RELSA procedure reflects the multi-dimensional severity information and is highly robust in estimating the quantitative severity within and between models, it can be deemed a valuable tool for laboratory animal severity assessment.

MicroRNAs as systemic biomarkers to assess distress in animal models for gastrointestinal diseases.

Severity assessment of animal experiments is mainly conducted by using subjective parameters. A widely applicable biomarker to assess animal distress could contribute to an objective severity assessment in different animal models. Here, the distress of three murine animal models for gastrointestinal diseases was assessed by multiple behavioral and physiological parameters. To identify possible new biomarkers for distress 750 highly conserved microRNAs were measured in the blood plasma of mice before and after the induction of pancreatitis. Deregulated miRNA candidates were identified and further quantified in additional animal models for pancreatic cancer and cholestasis. MiR-375 and miR-203 were upregulated during pancreatitis and down regulated during cholestasis, whereas miR-132 was upregulated in all models. Correlation between miR-132 and plasma corticosterone concentrations resulted in the highest correlation coefficient, when compared to the analysis of miR-375, miR-203 and miR-30b. These results indicate that miR-132 might function as a general biomarker for distress, whereas the other miRNAs were altered in a disease specific manner. In conclusion, plasma miRNA profiling may help to better characterize the level of distress in mouse models for gastrointestinal diseases.

Development of a real-time indoor location system using bluetooth low energy technology and deep learning to facilitate clinical applications.

PURPOSE: An indoor, real-time location system (RTLS) can benefit both hospitals and patients by improving clinical efficiency through data-driven optimization of procedures. Bluetooth-based RTLS systems are cost-effective but lack accuracy because Bluetooth signal is subject to significant fluctuation. We aim to improve the accuracy of RTLS using the deep learning technique. METHODS: We installed a Bluetooth sensor network in a three-floor clinic building to track patients, staff, and devices. The Bluetooth sensors measured the strength of the signal broadcasted from Bluetooth tags, which was fed into a deep neural network to calculate the location of the tags. The proposed deep neural network consists of a long short-term memory (LSTM) network and a deep classifier for tracking moving objects. Additionally, a spatial-temporal constraint algorithm was implemented to further increase the accuracy and stability of the results. To train the neural network, we divided the building into 115 zones and collected training data in each zone. We further augmented the training data to generate cross-zone trajectories, mimicking the real-world scenarios. We tuned the parameters for the proposed neural network to achieve relatively good accuracy. RESULTS: The proposed deep neural network achieved an overall accuracy of about 97% for tracking objects in each individual zone in the whole three-floor building, 1.5% higher than the baseline neural network that was proposed in an earlier paper, when using 10 s of signals. The accuracy increased with the density of Bluetooth sensors. For tracking moving objects, the proposed neural network achieved stable and accurate results. When latency is less of a concern, we eliminated the effect of latency from the accuracy and gained an accuracy of 100% for our testing trajectories, significantly improved from the baseline method. CONCLUSIONS: The proposed deep neural network composed of a LSTM, a deep classifier and a posterior constraint algorithm significantly improved the accuracy and stability of RTLS for tracking moving objects.

Grading Distress of Different Animal Models for Gastrointestinal Diseases Based on Plasma Corticosterone Kinetics.

Comparative studies for evaluating distress in established animal models are still rare. However, this issue is becoming more important as a consequence of worldwide appreciation of animal welfare. One good parameter for evaluating distress is the quantification of corticosterone. We hypothesized that not just the absolute value but also the duration of increased corticosterone concentration in the blood is an important aspect for evaluating animal distress. Therefore, we analyzed plasma corticosterone concentrations 30, 60, 120, and 240 min after induction of pancreatitis by cerulein, liver damage by carbon tetrachloride, liver damage by bile duct ligation, and after orthotopic injection of pancreatic cancer cells. We also evaluated corticosterone kinetics after injection of distinct carrier substances. Compared to phosphate buffered saline, dimethyl sulfoxide leads to dose-dependent higher and longer-lasting circulating corticosterone concentrations. In all disease models, we observed significantly increased corticosterone concentration 30 min after stress induction. However, the corticosterone kinetics differed among the animal models. Both the absolute value of corticosterone concentration and the duration correlated positively with the quantification of animal distress by a score sheet. This suggests that both variables of corticosterone kinetics might provide a solid basis for comparing and grading distress of different animal models.

Pancreaticoduodenectomy is justified in a subset of elderly patients with pancreatic ductal adenocarcinoma: A population-based retrospective cohort study of 4,283 patients.

BACKGROUND: The survival benefit of pancreaticoduodenectomy (PD) in elderly patients with pancreatic ductal adenocarcinoma (PDAC) is still unclear. METHODS: Data pertaining to elderly (age ≥75 years) and younger (age <75 years) patients with potentially curable PDAC who underwent pancreaticoduodenectomy in the period 2004-2013 were extracted from the Surveillance, Epidemiology, and End Results database. The Cox proportional hazards model and stratified Kaplan-Meier survival analyses were performed. RESULTS: A total of 4283 patients (3256 younger patients and 1027 elderly patients) were included. On multivariate analysis, advanced age (age ≥75 years) was not found to be an independent risk factor for diseases specific survival (DSS). Survival analysis disaggregated by gender, tumor size, American Joint Committee on Cancer stage, and tumor differentiation showed comparable DSS in younger and elderly patients (log-rank test). Among patients with poorly-differentiated or undifferentiated tumors, those in the elderly age-group experienced shorter DSS as compared to that of younger patients (poorly-differentiated: elderly vs. younger, 32.779 months vs. 42.198 months, P = 0.043; undifferentiated: elderly vs. younger, 17.500 months vs. 43.028 months, P = 0.210). However, PD was still warranted for elderly patients with poorly-differentiated tumors (surgery vs. without surgery, 32.779 months vs. 11.490 months, P < 0.001). Patients with undifferentiated tumors experienced a non-significant survival benefit after PD (surgery vs. without surgery, 17.500 months vs. 11.699 months, P = 0.330). CONCLUSIONS: Advanced age (age ≥75 years) is not an independent risk factor for DSS. PD is justified in a subset of elderly PDAC patients; however, it should be performed in a high-volume center to minimize the risk of post operative complications. Future studies should explore individualized treatment strategies for elderly patients with undifferentiated tumors.