Towards substitution of invasive telemetry: An integrated home cage concept for unobtrusive monitoring of objective physiological parameters in rodents.

This study presents a novel concept for a smart home cage design, tools, and software used to monitor the physiological parameters of mice and rats in animal-based experiments. The proposed system focuses on monitoring key clinical parameters, including heart rate, respiratory rate, and body temperature, and can also assess activity and circadian rhythm. As the basis of the smart home cage system, an in-depth analysis of the requirements was performed, including camera positioning, imaging system types, resolution, frame rates, external illumination, video acquisition, data storage, and synchronization. Two different camera perspectives were considered, and specific camera models, including two near-infrared and two thermal cameras, were selected to meet the requirements. The developed specifications, hardware models, and software are freely available via GitHub. During the first testing phase, the system demonstrated the potential of extracting vital parameters such as respiratory and heart rate. This technology has the potential to reduce the need for implantable sensors while providing reliable and accurate physiological data, leading to refinement and improvement in laboratory animal care.

Camera-Based Respiration Monitoring of Unconstrained Rodents.

Animal research has always been crucial for various medical and scientific breakthroughs, providing information on disease mechanisms, genetic predisposition to diseases, and pharmacological treatment. However, the use of animals in medical research is a source of great controversy and ongoing debate in modern science. To ensure a high level of bioethics, new guidelines have been adopted by the EU, implementing the 3R principles to replace animal testing wherever possible, reduce the number of animals per experiment, and refine procedures to minimize stress and pain. Supporting these guidelines, this article proposes an improved approach for unobtrusive, continuous, and automated monitoring of the respiratory rate of laboratory rats. It uses the cyclical expansion and contraction of the rats' thorax/abdominal region to determine this physiological parameter. In contrast to previous work, the focus is on unconstrained animals, which requires the algorithms to be especially robust to motion artifacts. To test the feasibility of the proposed approach, video material of multiple rats was recorded and evaluated. High agreement was obtained between RGB imaging and the reference method (respiratory rate derived from electrocardiography), which was reflected in a relative error of 5.46%. The current work shows that camera-based technologies are promising and relevant alternatives for monitoring the respiratory rate of unconstrained rats, contributing to the development of new alternatives for a continuous and objective assessment of animal welfare, and hereby guiding the way to modern and bioethical research.

Dissecting the genetic heterogeneity of gastric cancer.

BACKGROUND: Gastric cancer (GC) is clinically heterogenous according to location (cardia/non-cardia) and histopathology (diffuse/intestinal). We aimed to characterize the genetic risk architecture of GC according to its subtypes. Another aim was to examine whether cardia GC and oesophageal adenocarcinoma (OAC) and its precursor lesion Barrett's oesophagus (BO), which are all located at the gastro-oesophageal junction (GOJ), share polygenic risk architecture. METHODS: We did a meta-analysis of ten European genome-wide association studies (GWAS) of GC and its subtypes. All patients had a histopathologically confirmed diagnosis of gastric adenocarcinoma. For the identification of risk genes among GWAS loci we did a transcriptome-wide association study (TWAS) and expression quantitative trait locus (eQTL) study from gastric corpus and antrum mucosa. To test whether cardia GC and OAC/BO share genetic aetiology we also used a European GWAS sample with OAC/BO. FINDINGS: Our GWAS consisting of 5816 patients and 10,999 controls highlights the genetic heterogeneity of GC according to its subtypes. We newly identified two and replicated five GC risk loci, all of them with subtype-specific association. The gastric transcriptome data consisting of 361 corpus and 342 antrum mucosa samples revealed that an upregulated expression of MUC1, ANKRD50, PTGER4, and PSCA are plausible GC-pathomechanisms at four GWAS loci. At another risk locus, we found that the blood-group 0 exerts protective effects for non-cardia and diffuse GC, while blood-group A increases risk for both GC subtypes. Furthermore, our GWAS on cardia GC and OAC/BO (10,279 patients, 16,527 controls) showed that both cancer entities share genetic aetiology at the polygenic level and identified two new risk loci on the single-marker level. INTERPRETATION: Our findings show that the pathophysiology of GC is genetically heterogenous according to location and histopathology. Moreover, our findings point to common molecular mechanisms underlying cardia GC and OAC/BO. FUNDING: German Research Foundation (DFG).

Linking dysbiosis to precancerous stomach through inflammation: Deeper than and beyond imaging.

Upper gastrointestinal endoscopy is considered the gold standard for gastric lesions detection and surveillance, but it is still associated with a non-negligible rate of missing conditions. In the Era of Personalized Medicine, biomarkers could be the key to overcome missed lesions or to better predict recurrence, pushing the frontier of endoscopy to functional endoscopy. In the last decade, microbiota in gastric cancer has been extensively explored, with gastric carcinogenesis being associated with progressive dysbiosis. Helicobacter pylori infection has been considered the main causative agent of gastritis due to its interference in disrupting the acidic environment of the stomach through inflammatory mediators. Thus, does inflammation bridge the gap between gastric dysbiosis and the gastric carcinogenesis cascade and could the microbiota-inflammation axis-derived biomarkers be the answer to the unmet challenge of functional upper endoscopy? To address this question, in this review, the available evidence on the role of gastric dysbiosis and chronic inflammation in precancerous conditions of the stomach is summarized, particularly targeting the nuclear factor-κB (NF-κB), toll-like receptors (TLRs) and cyclooxygenase-2 (COX-2) pathways. Additionally, the potential of liquid biopsies as a non-invasive source and the clinical utility of studied biomarkers is also explored. Overall, and although most studies offer a mechanistic perspective linking a strong proinflammatory Th1 cell response associated with, but not limited to, chronic infection with Helicobacter pylori, promising data recently published highlights not only the diagnostic value of microbial biomarkers but also the potential of gastric juice as a liquid biopsy pushing forward the concept of functional endoscopy and personalized care in gastric cancer early diagnosis and surveillance.

For Heart Rate Assessments from Drone Footage in Disaster Scenarios.

The ability to use drones to obtain important vital signs could be very valuable for emergency personnel during mass-casualty incidents. The rapid and robust remote assessment of heart rates could serve as a life-saving decision aid for first-responders. With the flight sensor data of a specialized drone, a pipeline was developed to achieve a robust, non-contact assessment of heart rates through remote photoplethysmography (rPPG). This robust assessment was achieved through adaptive face-aware exposure and comprehensive de-noising of a large number of predicted noise sources. In addition, we performed a proof-of-concept study that involved 18 stationary subjects with clean skin and 36 recordings of their vital signs, using the developed pipeline in outdoor conditions. In this study, we could achieve a single-value heart-rate assessment with an overall root-mean-squared error of 14.3 beats-per-minute, demonstrating the basic feasibility of our approach. However, further research is needed to verify the applicability of our approach in actual disaster situations, where remote photoplethysmography readings could be impacted by other factors, such as blood, dirt, and body positioning.

Gastric cancer detection by non-blood-based liquid biopsies: A systematic review looking into the last decade of research.

Gastric cancer (GC) screening is arguable in most Western countries. Liquid biopsies are a great promise to answer the unmet need for less invasive diagnostic biomarkers in GC. Thus, we aimed at systematically reviewing the current knowledge on liquid biopsy-based biomarkers in GC screening. A systematic search on PubMed/MEDLINE and Scopus databases was performed on published articles reporting the use of non-blood specimen (saliva, gastric juice [GJ], urine and stool) on GC diagnosis. 3208 records were retrieved by June 2022. After removal of duplicate records, 2379 abstracts were screened, and 84 full texts included in this systematic review. More than 90% of studies were reported on Asian populations. Overall, 9 studies explored stool-, 12 saliva-, and 29 urine-derived biomarkers for GC detection. Additionally, 37 studies, representing the majority, analyzed GJ, focusing on nucleic acid molecules. Several miRNAs and lncRNA molecules have been associated with GC risk, particularly miR-21 (area under the curve [AUC] = 0.97, 95% CI: 0.94-1.00). Considering salivary biomarkers, the best described model in validation sets included the soybean agglutinin and Vicia villosa agglutinin lectins (AUC = 0.89, 95% CI: 0.80-0.99). Most studies in urine carried out metabolomic approaches, with two discriminatory models presenting AUC values superior to 0.97. This systematic review emphasizes the potential role of non-blood-based biomarkers, although further validation, particularly in Western countries, is mandatory, namely for non-invasive screening and/or monitoring, as well as the use of GJ as a tool to enhance upper gastrointestinal endoscopy accuracy.

Breathing Pattern Monitoring by Using Remote Sensors.

The ability to continuously and unobtrusively monitor and classify breathing patterns can be very valuable for automated health assessments because respiration is tightly coupled to many physiological processes. Pathophysiological changes in these processes often manifest in altered breathing patterns and can thus be immediately detected. In order to develop a breathing pattern monitoring system, a study was conducted in which volunteer subjects were asked to breathe according to a predefined breathing protocol containing multiple breathing patterns while being recorded with color and thermal cameras. The recordings were used to develop and compare several respiratory signal extraction algorithms. An algorithm for the robust extraction of multiple respiratory features was developed and evaluated, capable of differentiating a wide range of respiratory patterns. These features were used to train a one vs. one multiclass support vector machine, which can distinguish between breathing patterns with an accuracy of 95.79 %. The recorded dataset was published to enable further improvement of contactless breathing pattern classification, especially for complex breathing patterns.

Consciousness Detection on Injured Simulated Patients Using Manual and Automatic Classification via Visible and Infrared Imaging.

In a disaster scene, triage is a key principle for effectively rescuing injured people according to severity level. One main parameter of the used triage algorithm is the patient's consciousness. Unmanned aerial vehicles (UAV) have been investigated toward (semi-)automatic triage. In addition to vital parameters, such as heart and respiratory rate, UAVs should detect victims' mobility and consciousness from the video data. This paper presents an algorithm combining deep learning with image processing techniques to detect human bodies for further (un)consciousness classification. The algorithm was tested in a 20-subject group in an outside environment with static (RGB and thermal) cameras where participants performed different limb movements in different body positions and angles between the cameras and the bodies' longitudinal axis. The results verified that the algorithm performed better in RGB. For the most probable case of 0 degrees, RGB data obtained the following results: Mathews correlation coefficient (MMC) of 0.943, F1-score of 0.951, and precision-recall area under curve AUC (PRC) score of 0.968. For the thermal data, the MMC was 0.913, F1-score averaged 0.923, and AUC (PRC) was 0.960. Overall, the algorithm may be promising along with others for a complete contactless triage assessment in disaster events during day and night.

An Anatomical Thermal 3D Model in Preclinical Research: Combining CT and Thermal Images.

Even though animal trials are a controversial topic, they provide knowledge about diseases and the course of infections in a medical context. To refine the detection of abnormalities that can cause pain and stress to the animal as early as possible, new processes must be developed. Due to its noninvasive nature, thermal imaging is increasingly used for severity assessment in animal-based research. Within a multimodal approach, thermal images combined with anatomical information could be used to simulate the inner temperature profile, thereby allowing the detection of deep-seated infections. This paper presents the generation of anatomical thermal 3D models, forming the underlying multimodal model in this simulation. These models combine anatomical 3D information based on computed tomography (CT) data with a registered thermal shell measured with infrared thermography. The process of generating these models consists of data acquisition (both thermal images and CT), camera calibration, image processing methods, and structure from motion (SfM), among others. Anatomical thermal 3D models were successfully generated using three anesthetized mice. Due to the image processing improvement, the process was also realized for areas with few features, which increases the transferability of the process. The result of this multimodal registration in 3D space can be viewed and analyzed within a visualization tool. Individual CT slices can be analyzed axially, sagittally, and coronally with the corresponding superficial skin temperature distribution. This is an important and successfully implemented milestone on the way to simulating the internal temperature profile. Using this temperature profile, deep-seated infections and inflammation can be detected in order to reduce animal suffering.

Genetic Variations in Prostaglandin E2 Pathway Identified as Susceptibility Biomarkers for Gastric Cancer in an Intermediate Risk European Country.

The cyclooxygenase-2 (COX-2)/prostaglandin E2 (PGE2) pathway exerts deleterious pleiotropic effects in inflammation-induced gastric carcinogenesis. We aimed to assess the association of genetic variants in prostaglandin-endoperoxide synthase 2 (PTGS2), ATP binding cassette subfamily C member 4 (ABCC4), hydroxyprostaglandin dehydrogenase 15-(NAD) (HPGD), and solute carrier organic anion transporter family member 2A1 (SLCO2A1) PGE2 pathway-related genes with gastric cancer (GC) risk in a European Caucasian population. A hospital-based case-control study gathering 260 GC cases and 476 cancer-free controls was implemented. Using a tagSNP approach, 51 single nucleotide polymorphisms (SNPs) were genotyped through MassARRAY® iPLEX Gold Technology or allelic discrimination by real-time polymerase chain reaction (PCR). Homozygous carriers of the minor allele for both rs689466 and rs10935090 SNPs were associated with a 2.98 and 4.30-fold increased risk for GC, respectively (95% confidence interval (CI): 1.14-7.74, p = 0.027; 95% CI: 1.22-15.16, p = 0.026), with the latter also being associated with an anticipated diagnosis age. A multifactor dimensionality reduction analysis identified an overall three-factor best interactive model composed of age, rs689466, and rs1678374 that was associated with a 17.6-fold GC increased risk (95% CI: 11.67-26.48, p < 0.0001, (cross-validation) CV consistency of 8/10 and accuracy of 0.807). In this preliminary study, several tagSNPs in PGE2 pathway-related genes were identified as risk biomarkers for GC development. This approach may help to identify higher-risk individuals and may contribute to the tailoring screening of GC in intermediate-risk European countries.

ASCT2 and LAT1 Contribution to the Hallmarks of Cancer: From a Molecular Perspective to Clinical Translation.

The role of the amino acid transporters ASCT2 and LAT1 in cancer has been explored throughout the years. In this review, we report their impact on the hallmarks of cancer, as well as their clinical significance. Overall, both proteins have been associated with cell death resistance through dysregulation of caspases and sustainment of proliferative signaling through mTOR activation. Furthermore, ASCT2 appears to play an important role in cellular energetics regulation, whereas LAT1 expression is associated with angiogenesis and invasion and metastasis activation. The molecular impact of these proteins on the hallmarks of cancer translates into various clinical applications and both transporters have been identified as prognostic factors in many types of cancer. Concerning their role as therapeutic targets, efforts have been undertaken to synthesize competitive or irreversible ASCT2 and LAT1 inhibitors. However, JHP203, a selective inhibitor of the latter, is, to the best of our knowledge, the only compound included in a Phase 1 clinical trial. In conclusion, considering the usefulness of ASCT2 and LAT1 in a variety of cancer-related pathways and cancer therapy/diagnosis, the development and testing of novel inhibitors for these transporters that could be evaluated in clinical trials represents a promising approach to cancer prognosis improvement.

Infection Probability Index: Implementation of an Automated Chronic Wound Infection Marker.

The number of people suffering from chronic wounds is increasing due to demographic changes and the global epidemics of obesity and diabetes. Innovative imaging techniques within the field of chronic wound diagnostics are required to improve wound care by predicting and detecting wound infections to accelerate the application of treatments. For this reason, the infection probability index (IPI) is introduced as a novel infection marker based on thermal wound imaging. To improve usability, the IPI was implemented to automate scoring. Visual and thermal image pairs of 60 wounds were acquired to test the implemented algorithms on clinical data. The proposed process consists of (1) determining various parameters of the IPI based on medical hypotheses, (2) acquiring data, (3) extracting camera distortions using camera calibration, and (4) preprocessing and (5) automating segmentation of the wound to calculate (6) the IPI. Wound segmentation is reviewed by user input, whereas the segmented area can be refined manually. Furthermore, in addition to proof of concept, IPIs' correlation with C-reactive protein (CRP) levels as a clinical infection marker was evaluated. Based on average CRP levels, the patients were clustered into two groups, on the basis of the separation value of an averaged CRP level of 100. We calculated the IPIs of the 60 wound images based on automated wound segmentation. Average runtime was less than a minute. In the group with lower average CRP, a correlation between IPI and CRP was evident.

Prostaglandin E2 Pathway Is Dysregulated in Gastric Adenocarcinoma in a Caucasian Population.

Gastric cancer (GC) represents the third leading cause of cancer-related deaths worldwide. The levels of prostaglandin E2, a key player in the hallmarks of cancer, are mainly regulated by prostaglandin-endoperoxide synthase 2 (PTGS2) and ATP-binding cassette subfamily C member 4 (ABCC4), involved in its synthesis and exportation, respectively, and 15-hydroxyprostaglandin dehydrogenase (15-PGDH) and solute carrier organic anion transporter family member 2A1 (SLCO2A1), responsible for its inactivation. Even though there are distinct molecular signatures across ethnic populations, most published studies focus on Asian populations. Our main aim was to explore the genetic expression of the aforementioned molecules in a Caucasian population. 94 "Normal" and 89 tumoral formalin-fixed paraffin-embedded (FFPE) samples from GC patients were used to assess the mRNA expression of PTGS2, ABCC4, hydroxyprostaglandin dehydrogenase 15-(NAD) (HPGD), SLCO2A1 by Real-Time PCR. We found an upregulation for the PTGS2 gene mean factor of 2.51 and a downregulation for the HPGD and SLCO2A1 genes (mean factor of 0.10 and 0.37, respectively) in tumorous mucosa in a gender-independent manner. In females, we observed an ABCC4 downregulation and a PTGS2 mRNA upregulation compared to males in tumoral mucosa (mean factor of 0.61 and 1.64, respectively). We reported dysregulation of the inflammation triggered PGE2 pathway in a Caucasian population with an intermediate risk for GC, which might highlight the applicability of aspirin in the treatment of GC patients.

Glycans as Immune Checkpoints: Removal of Branched N-glycans Enhances Immune Recognition Preventing Cancer Progression.

Tumor growth is accompanied with dramatic changes in the cellular glycome, such as the aberrant expression of complex branched N-glycans. However, the role of this protumoral N-glycan in immune evasion and whether its removal contributes to enhancement of immune recognition and to unleashing an antitumor immune response remain elusive. We demonstrated that branched N-glycans are used by colorectal cancer cells to escape immune recognition, instructing the creation of immunosuppressive networks through inhibition of IFNγ. The removal of this "glycan-mask" exposed immunogenic mannose glycans that potentiated immune recognition by DC-SIGN-expressing immune cells, resulting in an effective antitumor immune response. We revealed a glycoimmune checkpoint in colorectal cancer, highlighting the therapeutic efficacy of its deglycosylation to potentiate immune recognition and, thus, improving cancer immunotherapy.

Evaluation of a bronchoscopy guidance system for bronchoscopy training, a randomized controlled trial.

BACKGROUND: Conventional training in bronchoscopy is performed either on patients (apprenticeship model) or phantoms. While the former is associated with increased rate of patient complications, procedure time, and amount of sedation, the latter does not offer any form of feedback to the trainee. This paper presents a study which investigates whether a bronchoscopy guidance system may be a helpful tool for training of novice bronchoscopists. METHODS: A randomized controlled study with 48 medical students was carried out with two different groups (control and test group, each N = 24). Whereas the control group performed a conventional bronchoscopy on phantom the test group carried out an Electromagnetic Navigation Bronchoscopy (ENB) for tracking of the bronchoscopal tip in the bronchial system. All volunteers had a common task: to perform a complete and systematic diagnostic bronchoscopy within 10 min. RESULTS: The test group examined significantly more lobes than the control group (p = 0.009). Due to the real-time feedback of the system, all students of test group felt more confident having analyzed the entire lung. Additionally, they were unanimous that the system would be helpful during the next bronchoscopy. CONCLUSIONS: In sum, this technology may play a major role in unsupervised learning by improving accuracy, dexterity but above all by increasing the confidence of novices, students as well as physicians. Due to good acceptance, there may be a great potential of this tool in clinical routine.

Contactless monitoring of heart and respiratory rate in anesthetized pigs using infrared thermography.

Pig experiments have played an important role in medical breakthroughs during the last century. In fact, pigs are one of the major animal species used in translational research, surgical models and procedural training due to their anatomical and physiological similarities to humans. To ensure high bioethical standards in animal trials, new directives have been implemented, among others, to refine the procedures and minimize animals' stress and pain. This paper presents a contactless motion-based approach for monitoring cardiorespiratory signals (heart rate and respiratory rate) in anesthetized pigs using infrared thermography. Heart rate monitoring is estimated by measuring the vibrations (precordial motion) of the chest caused by the heartbeat. Respiratory rate, in turn, is computed by measuring the mechanical chest movements that accompany the respiratory cycle. To test the feasibility of this approach, thermal videos of 17 anesthetized pigs were acquired and analyzed. A high agreement between infrared thermography and a gold standard (electrocardiography and capnography-derived respiratory rate) was achieved. The mean absolute error averaged 3.43 ± 3.05 bpm and 0.27 ± 0.48 breaths/min for heart rate and respiratory rate, respectively. In sum, infrared thermography is capable of assessing cardiorespiratory signals in pigs. Future work should be conducted to evaluate infared thermography capability of capturing information for long term monitoring of research animals in a diverse set of facilities.

Remote vitals monitoring in rodents using video recordings.

Laboratory animal research was always crucial for scientific breakthroughs in the fields of medicine and biology. Animal trials offer insights into various disease mechanisms, genetics, drug therapy and the effect of different external factors onto living organisms. However, conducting animal trials is highly controversial. To ensure high ethical standards, a number of directives have been adopted in the European Union, which seek to replace, reduce and refine animal trials. Hence, severity assessment plays an important role in today's laboratory animal research. Currently, severity of trials is assessed by highly rater dependent scoring systems. In this paper, we propose a method for unobtrusive, automated and contactless measurement of respiratory rate (RR) and heart rate (HR). We were able to extract RR and HR with an high agreement between our method and a contact-based reference method. The Root Mean Squared Error (RMSE) averaged 0.32 ± 0.11 breaths/min for RR and 1.28 ± 0.62 beats/min for HR in rats, respectively. In mice, the RMSE averaged 1.42 ± 0.97 breaths/min for RR and 1.36 ± 0.87 beats/min, respectively. In the future, these parameters can be used for new, objective scoring systems, which are not susceptible to inter-rater variability.

Cost-utility analysis of genetic polymorphism universal screening in colorectal cancer prevention by detection of high-risk individuals.

BACKGROUND: In the past 15 years numerous studies have been published on the involvement of low-penetrance susceptibility genes on the risk for developing colorectal cancer (CRC). AIM: To perform an economic analysis of blood genetic testing in CRC screening in a population-based nationwide setting using polymorphisms in prostaglandin E2 pathway genes as proof of concept. METHODS: A cost-utility analysis was performed from a societal perspective in Portugal comparing two strategies: blood genetic testing by the age of 40 versus no genetic screening under different assumptions of the cost of genetic testing (€10 and €30) and expected risk (1.5 to 5-fold). The adopted threshold was set at €44,870 (USD 50,000). The primary outcome was the incremental cost-effectiveness ratio (ICER) for a base case scenario. RESULTS: Polymorphism genotyping provided cost-utility only under the assumption of a 5-fold increased risk in the general population, providing ICERs of €44,356 and €30,389 for €30 and €10 tests, respectively. CONCLUSION: Blood genetic screening for colorectal cancer has cost-utility only under specific assumptions of increased CRC risk and conservative cost estimates. Future studies should focus on defining genetic profiles because single-gene approaches are very unlikely to be cost-effective considering their modest predictive value.

Perspective review of optical imaging in welfare assessment in animal-based research.

To refine animal research, vital signs, activity, stress, and pain must be monitored. In chronic studies, some measures can be assessed using telemetry sensors. Although this methodology provides high-precision data, an initial surgery for device implantation is necessary, potentially leading to stress, wound infections, and restriction of motion. Recently, camera systems have been adapted for animal research. We give an overview of parameters that can be assessed using imaging in the visible, near-infrared, and thermal spectrum of light. It focuses on heart activity, respiration, oxygen saturation, and motion, as well as on wound analysis. For each parameter, we offer recommendations on the minimum technical requirements of appropriate systems, regions of interest, and light conditions, among others. In general, these systems demonstrate great performance. For heart and respiratory rate, the error was <4 beats / min and 5 breaths/min. Furthermore, the systems are capable of tracking animals during different behavioral tasks. Finally, studies indicate that inhomogeneous temperature distribution around wounds might be an indicator of (pending) infections. In sum, camera-based techniques have several applications in animal research. As vital parameters are currently only assessed in sedated animals, the next step should be the integration of these modalities in home-cage monitoring.