Comparing animal well-being between bile duct ligation models.

A prevailing animal model currently used to study severe human diseases like obstructive cholestasis, primary biliary or sclerosing cholangitis, biliary atresia, and acute liver injury is the common bile duct ligation (cBDL). Modifications of this model include ligation of the left hepatic bile duct (pBDL) or ligation of the left bile duct with the corresponding left hepatic artery (pBDL+pAL). Both modifications induce cholestasis only in the left liver lobe. After induction of total or partial cholestasis in mice, the well-being of these animals was evaluated by assessing burrowing behavior, body weight, and a distress score. To compare the pathological features of these animal models, plasma levels of liver enzymes, bile acids, bilirubin, and within the liver tissue, necrosis, fibrosis, inflammation, as well as expression of genes involved in the synthesis or transport of bile acids were assessed. The survival rate of the animals and their well-being was comparable between pBDL+pAL and pBDL. However, surgical intervention by pBDL+pAL caused confluent necrosis and collagen depositions at the edge of necrotic tissue, whereas pBDL caused focal necrosis and fibrosis in between portal areas. Interestingly, pBDL animals had a higher survival rate and their well-being was significantly improved compared to cBDL animals. On day 14 after cBDL liver aspartate, as well as alanine aminotransferase, alkaline phosphatase, glutamate dehydrogenase, bile acids, and bilirubin were significantly elevated, but only glutamate dehydrogenase activity was increased after pBDL. Thus, pBDL may be primarily used to evaluate local features such as inflammation and fibrosis or regulation of genes involved in bile acid synthesis or transport but does not allow to study all systemic features of cholestasis. The pBDL model also has the advantage that fewer mice are needed, because of its high survival rate, and that the well-being of the animals is improved compared to the cBDL animal model.

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.

Generalizability, Robustness and Replicability When Evaluating Wellbeing of Laboratory Mice with Various Methods.

An essential basis for objectively improving the status of animals during in vivo research is the ability to measure the wellbeing of animals in a reliable and scientific manner. Several non-invasive methods such as assessing body weight, burrowing activity, nesting behavior, a distress score and fecal corticosterone metabolites were evaluated in healthy mice and after three surgical interventions or during the progression of four gastrointestinal diseases. The performance of each method in differentiating between healthy and diseased animals was assessed using receiver operating characteristic curves. The ability to differentiate between these two states differed between distinct surgical interventions and distinct gastrointestinal diseases. Thus, the generalizability of these methods for assessing animal wellbeing was low. However, the robustness of these methods when assessing wellbeing in one gastrointestinal disease was high since the same methods were often capable of differentiating between healthy and diseased animals independent of applied drugs. Moreover, the replicability when assessing two distinct cohorts with an identical surgical intervention was also high. These data suggest that scientists can reach valid conclusions about animal wellbeing when using these methods within one specific animal model. This might be important when optimizing methodological aspects for improving animal wellbeing. The lack of generalizability, however, suggests that comparing animal models by using single methods might lead to incorrect conclusions. Thus, these data support the concept of using a combination of several methods when assessing animal welfare.

Contact Tracing in Healthcare Settings During the COVID-19 Pandemic Using Bluetooth Low Energy and Artificial Intelligence-A Viewpoint.

The COVID-19 pandemic has inflicted great damage with effects that will likely linger for a long time. This crisis has highlighted the importance of contact tracing in healthcare settings because hospitalized patients are among the high risk for complications and death. Moreover, effective contact tracing schemes are not yet available in healthcare settings. A good contact tracing technology in healthcare settings should be equipped with six features: promptness, simplicity, high precision, integration, minimized privacy concerns, and social fairness. One potential solution that addresses all of these elements leverages an indoor real-time location system based on Bluetooth Low Energy and artificial intelligence.

Analysis of Animal Well-Being When Supplementing Drinking Water with Tramadol or Metamizole during Chronic Pancreatitis.

Pain management during in vivo experiments is an animal welfare concern and is in many countries also legally required. In this study, we evaluated C57Bl/6J mice when 3 g/L metamizole or 1 g/L tramadol was provided via drinking water, before and during cerulein-induced chronic pancreatitis. Supplementation of drinking water with metamizole or tramadol did not significantly reduce the amount of consumed water. In order to evaluate the wellbeing of mice, a distress score, burrowing activity, nesting behavior, and body weight was assessed. Before induction of pancreatitis, neither tramadol nor metamizole influenced these readout parameters. Chronic pancreatitis caused a significantly increased distress score, decreased burrowing activity and a reduction in body weight. Mice drinking tramadol-supplemented water experienced less loss in body weight and consumed more water than mice drinking metamizole, at a few time-points during chronic pancreatitis. Pancreatic atrophy, a characteristic feature of chronic pancreatitis was not differentially influenced by either analgesic. In conclusion, both analgesics can be used during 33 days of chronic pancreatitis, but tramadol seems to be moderately advantageous when compared to metamizole.

Comparing distress of mouse models for liver damage.

In order to foster animal welfare as well as high quality of research, many countries regulate by law that the severity of animal experiments must be evaluated and considered when performing biomedical research. It is well accepted that multiple parameters rather than a single readout parameter should be applied to describe animal distress or suffering. However, since the performance of readout parameters for animal distress is rarely defined and methods for multivariate analysis have only in rare cases been used, it is not known which methodology is most appropriate to define animal distress. This study used receiver operating characteristic curve analysis to quantify the performance of burrowing activity, body weight change and a distress score of mice after induction of liver damage by bile duct ligation or carbon tetrachloride. In addition, Support Vector Machine classification was used to compare the distress of these mouse models. This approach demonstrated that bile duct ligation causes much more distress than carbon tetrachloride-induced liver damage. This study, therefore, provides a prototype how to compare two animal models by considering several readout parameters. In the future these or similar methods for multivariate analysis will be necessary, when assessing and comparing the severity of animal models.

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.

A rational approach of early humane endpoint determination in a murine model for cholestasis.

Reduction of animal suffering during in vivo experiments is usually ensured by continuously monitoring the health status using a score sheet and by applying humane endpoints. However, most studies do not evaluate the plausibility of score sheets and do not attempt to reduce the suffering of animals by determining earlier and, therefore, more humane endpoints. The present study uses data from BALB/cANCrl mice after bile duct ligation to retrospectively analyze which score sheet criteria are informative to determine humane endpoints. The performance of each single as well as com­binations of multiple animal welfare parameters was analyzed by a Cox proportional-hazards model followed by Harrell's concordance index. The addition of behavioral parameters, such as burrowing activity, helped to define a more humane early endpoint for euthanizing these animals. Using this approach, we determined that a body weight loss of 10-20% combined with a reduction of burrowing activity by more than 79.4% was able to predict that these animals would die within two days. Thus, this approach successfully determined an earlier humane endpoint and will reduce the suffering of animals in future experiments. Application of such an approach or similar methods can contribute to the refinement of various animal experiments.

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.

Application of a discontinuous Galerkin time domain method to simulation of optical properties of dielectric particles.

We applied a discontinuous Galerkin time domain (DGTD) method, using a fourth-order Runga-Kutta time stepping of the Maxwell equations, to the simulation of the optical properties of dielectric particles in two-dimensional (2D) geometry. As examples of the numerical implementation of this method, the single-scattering properties of 2D circular and hexagonal particles are presented. In the case of circular particles, the scattering phase matrix was computed using the DGTD method and compared with the exact solution. For hexagonal particles, the DGTD method was used to compute single-scattering properties of randomly oriented 2D hexagonal ice crystals, and results were compared with those calculated using a geometric optics method. We consider both shortwave (visible) and longwave (infrared) cases, with particle size parameters 50 and 100. In the hexagonal case, scattering results are also presented as a function of both incident and scattering angles, revealing a structure apparently not reported before. Using the geometric optics method, we are able to interpret this structure in terms of contributions from varying numbers of internal reflections within the crystal.