Development of novel thermal imaging techniques for pain detection in wild animals

Kipu on subjektiivinen tunne, jota on usein vaikea tulkita tai tutkia. Niiden kipu, jotka eivät voi sitä kommunikoida, on usein vaikeaa tunnistaa. IASP:n vuonna 2020 päivitetyn kivun määritelmän mukaan verbaalinen kuvailu on vain yksi tavoista ilmaista kipua. Kyvyttömyys ilmaista kipua verbaalisesta ei tarkoita, ettei sitä olisi. Tämä lisäys kivun määritelmään kertoo siitä, että esimerkiksi muut eläimet kuin ihmiset voivat sekä kokea että kommunikoida kipua. Kuinka ihmiset voivat tulkita eläinten kipua luotettavalla tavalla, ja niin että se olisi kunnioittavaa ja non- invasiivistä eläimelle? Lämpökuvantaminen on teknologia, jossa kuva muodostuu kappaleen lähettämän infrapunasäteilyn vaikutuksesta. Näistä kuvista voidaan irrottaa lämpötila-arvoja. Säteilyn intensiivisyys riippuu kuvattavan kohteen pintalämpötilasta, joten lämpökuvantamista voidaan käyttää mittaamaan muutoksia kyseisessä pintalämpötilassa. Kipu ja stressi voivat aiheuttaa autonomisen hermoston aktivaatiota, mikä vuorostaan voi vaikuttaa kehon pintalämpötiloihin. Lämpökuvantamisella pystytään havainnoimaan näitä hienovaraisia pintalämpötilojen vaihteluita. Lämpökuvantamalla voitaisiin mahdollisesti tulevaisuudessa tutkia esimerkiksi kipuun liittyviä ilmiöitä, jos ne aiheuttavat vaihtelua ihon pintalämpötiloissa. Tässä tutkimuksessa selvitin, että oliko tutkimallani villieläinotannalla havaittavissa pintalämpötilavaihteluja kasvojen alueella, voisivatko ne johtua kivusta, ja voisiko näiden perusteella lämpökuvantamista käyttää kiputilojen havainnointiin. Spesifimmin tutkin sitä, että muuttuuko potilaiden päänalueen pintalämpötilat alkututkimuksen aikana, joka suoritetaan aina uuden potilaan saapuessa Korkeasaaren Villieläinsairaalaan, jossa keräsin datani. Toinen kysymys oli, että ovatko nämä erot erilaisia niillä potilailla, joilla on todettu kiputila, verrattuna niihin, joilla ei ole todettua kiputilaa. Tutkimuksen tarkoitus oli myös kehittää tämän teknologian käyttöä villieläinten kohdalla. Tutkimukseni osoitti, että joillakin parametreilla (esim. pään lämpötila linnuilla) erot kipu- ja ei-kipu-potilailla olivat erilaisia. Kuitenkin merkittävämpi havainto oli se, että useiden parametrien kohdalla ja useiden potilasluokkien kohdalla pintalämpötilat laskivat alkututkimuksen jälkeen, mahdollisesti johtuen stressiin liittyvästä sympaattisen hermoston aktivaatiosta. Tutkimukseni ei yksiselitteisesti osoita sitä, että lämpökuvannusta voisi käyttää kivun havainnointiin. Sen sijaan se antaa vahvistusta ajatukselle, että pintalämpötilaerot voisivat olla potentiaalinen mittauskohde non-invasiiviselle autonomisen hermoston aktivaatiovaihtelun havainnoinnille.Pain is a subjective feeling often difficult to interpret or study and thus, pain of those unable to communicate their pain is difficult to recognize. According to the new definition of pain by IASP (Raja et al 2020), verbal description is only one of the many behaviours that can be used to express pain, and the inability to communicate pain does not negate the possibility of experiencing it. This addition to the definition points out that non-human animals, too, even if they cannot express it in words, are capable of both experiencing and communicating pain. Can we as humans interpret a state of pain in an animal in a trustworthy way – and in a manner that would be respectful and non-invasive to the animal? Infrared thermography (IRT) is a technology based on using infrared radiation instead of normal light to form images. These images can be used to quantify the surface temperature of an object with high resolution. The intensity of the radiation emitted by the object being imaged depends on the surface temperature and for this reason thermal imaging enables detecting and measuring changes of surface temperature. Pain and stress might manifest physiologically as activation of the autonomic nervous system, which in turn might result in changes in surface temperatures of the body. These changes might be detectable with a thermal camera. If we could establish a link between certain intricate temperature changes of the head area to certain type of activation of the sympathetic nervous system resulting from pain, thermal imaging could have the potential to detect this. In this study I investigated if there were detectable temperature changes in animal patients before and after a standard examination conducted to each patient admitted to the Wildlife Hospital of Helsinki Zoo, where my data was gathered. Another question was whether the patients that had pain differed in their temperature changes as compared to other patients. The question at the heart of my research was whether there would be a change in peripheral facial temperatures of patients before and after the examination. Another question was whether thermal patterns would be different for pain- and non-pain patients. I found that for some parameters, the temperature differences between pain- and non-pain patients were indeed different, for example the crown temperature of birds seemed to change with examination for patients without pain but not for patients with pain. A more prominent finding was that temperatures decrease across many parameters after an examination as compared to prior to it, across all or many patient groups. My research does not univocally show that thermal imaging could be used to detect pain; rather it affirms the thought that the measurement of changes in peripheral temperatures could be a potential window to non-invasively detect some changes of activation of the sympathetic nervous system in animals

A global sensitivity analysis approach for morphogenesis models

{\bf Background} %if any Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such `black-box' models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. {\bf Results} %if any To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of \emph{in silico} sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. {\bf Conclusions} %if any We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all `black-box' models, including high-throughput \emph{in vitro} models in which output measures are affected by a set of experimental perturbations

Automated image analysis of keratin 7 staining can predict disease outcome in primary sclerosing cholangitis

Background and AimsPrimary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease that obstructs the bile ducts and causes liver cirrhosis and cholangiocarcinoma. Efficient surrogate markers are required to measure disease progression. The cytokeratin 7 (K7) load in a liver specimen is an independent prognostic indicator that can be measured from digitalized slides using artificial intelligence (AI)-based models. MethodsA K7-AI model 2.0 was built to measure the hepatocellular K7 load area of the parenchyma, portal tracts, and biliary epithelium. K7-stained PSC liver biopsy specimens (n = 295) were analyzed. A compound endpoint (liver transplantation, liver-related death, and cholangiocarcinoma) was applied in Kaplan-Meier survival analysis to measure AUC values and positive likelihood ratios for each histological variable detected by the model. ResultsThe K7-AI model 2.0 was a better prognostic tool than plasma alkaline phosphatase, the fibrosis stage evaluated by Nakanuma classification, or K7 score evaluated by a pathologist based on the AUC values of measured variables. A combination of parameters, such as portal tract volume and area of K7-positive hepatocytes analyzed by the model, produced an AUC of 0.81 for predicting the compound endpoint. Portal tract volume measured by the model correlated with the histological fibrosis stage. ConclusionsThe K7 staining of histological liver specimens in PSC provides significant information on disease outcomes through objective and reproducible data, including variables that cannot be measured by a human pathologist. The K7-AI model 2.0 could serve as a prognostic tool for clinical endpoints and as a surrogate marker in drug trials.Peer reviewe

Chronic cholestasis detection by a novel tool : automated analysis of cytokeratin 7-stained liver specimens

Background The objective was to build a novel method for automated image analysis to locate and quantify the number of cytokeratin 7 (K7)-positive hepatocytes reflecting cholestasis by applying deep learning neural networks (AI model) in a cohort of 210 liver specimens. We aimed to study the correlation between the AI model's results and disease progression. The cohort of liver biopsies which served as a model of chronic cholestatic liver disease comprised of patients diagnosed with primary sclerosing cholangitis (PSC). Methods In a cohort of patients with PSC identified from the PSC registry of the University Hospital of Helsinki, their K7-stained liver biopsy specimens were scored by a pathologist (human K7 score) and then digitally analyzed for K7-positive hepatocytes (K7%area). The digital analysis was by a K7-AI model created in an Aiforia Technologies cloud platform. For validation, values were human K7 score, stage of disease (Metavir and Nakunuma fibrosis score), and plasma liver enzymes indicating clinical cholestasis, all subjected to correlation analysis. Results The K7-AI model results (K7%area) correlated with the human K7 score (0.896; p < 2.2e(- 16)). In addition, K7%area correlated with stage of PSC (Metavir 0.446; p < 1.849e(- 10) and Nakanuma 0.424; p < 4.23e(- 10)) and with plasma alkaline phosphatase (P-ALP) levels (0.369, p < 5.749e(- 5)). Conclusions The accuracy of the AI-based analysis was comparable to that of the human K7 score. Automated quantitative image analysis correlated with stage of PSC and with P-ALP. Based on the results of the K7-AI model, we recommend K7 staining in the assessment of cholestasis by means of automated methods that provide fast (9.75 s/specimen) quantitative analysis.Peer reviewe

The developmental influence of collaborative games in the Grade 6 mathematics classroom

This study investigated the developmental influence of collaborative games, in the form of game-based worksheets, on the performance and attitudes of sixth-graders in the mathematics classroom. It is posited that games have the potential to enhance learning through positive emotional experiences. Non-digital game-based learning methodologies are accessible in terms of cost effectiveness, providing opportunities for social interactions while learning, and demanding few prerequisite skills. This study investigated the opportunities for learning that non-digital, textbook-based game worksheets could afford mathematics learners. In this case study, a quasi-experimental design was implemented and pre- and post-tests were conducted around an intervention. From a statistical analysis of the test data, using the Mann–Whitney U-test, it was concluded that the intervention on the topics of multiplication and division had a positive impact on the experimental group of this sample. The experimental group was observed while participating in the games and the observation schedule was member-checked. The Game Object Model provided the conceptual framework. The results indicated that learners benefited from the incorporation of the combination of collaboration and games and that their achievement improved. The findings also suggest that the collaborative games positively influenced learners’ confidence, skills and understanding in mathematics.Appendix 1. Example game worksheetsAppendix 2. Observation scheduleshttp://www.tandfonline.com/loi/tmes202021-10-15hj2021Science, Mathematics and Technology Educatio

Automatic Posture and Movement Tracking of Infants with Wearable Movement Sensors

Infants' spontaneous and voluntary movements mirror developmental integrity of brain networks since they require coordinated activation of multiple sites in the central nervous system. Accordingly, early detection of infants with atypical motor development holds promise for recognizing those infants who are at risk for a wide range of neurodevelopmental disorders (e.g., cerebral palsy, autism spectrum disorders). Previously, novel wearable technology has shown promise for offering efficient, scalable and automated methods for movement assessment in adults. Here, we describe the development of an infant wearable, a multi-sensor smart jumpsuit that allows mobile accelerometer and gyroscope data collection during movements. Using this suit, we first recorded play sessions of 22 typically developing infants of approximately 7 months of age. These data were manually annotated for infant posture and movement based on video recordings of the sessions, and using a novel annotation scheme specifically designed to assess the overall movement pattern of infants in the given age group. A machine learning algorithm, based on deep convolutional neural networks (CNNs) was then trained for automatic detection of posture and movement classes using the data and annotations. Our experiments show that the setup can be used for quantitative tracking of infant movement activities with a human equivalent accuracy, i.e., it meets the human inter-rater agreement levels in infant posture and movement classification. We also quantify the ambiguity of human observers in analyzing infant movements, and propose a method for utilizing this uncertainty for performance improvements in training of the automated classifier. Comparison of different sensor configurations also shows that four-limb recording leads to the best performance in posture and movement classification.Peer reviewe

Clinical impact of additional findings detected by genome-wide non-invasive prenatal testing:Follow-up results of the TRIDENT-2 study

In the TRIDENT-2 study, all pregnant women in the Netherlands are offered genome-wide non-invasive prenatal testing (GW-NIPT) with a choice of receiving either full screening or screening solely for common trisomies. Previous data showed that GW-NIPT can reliably detect common trisomies in the general obstetric population and that this test can also detect other chromosomal abnormalities (additional findings). However, evidence regarding the clinical impact of screening for additional findings is lacking. Therefore, we present follow-up results of the TRIDENT-2 study to determine this clinical impact based on the laboratory and perinatal outcomes of cases with additional findings. Between April 2017 and April 2019, additional findings were detected in 402/110,739 pregnancies (0.36%). For 358 cases, the origin was proven to be either fetal (n = 79; 22.1%), (assumed) confined placental mosaicism (CPM) (n = 189; 52.8%), or maternal (n = 90; 25.1%). For the remaining 44 (10.9%), the origin of the aberration could not be determined. Most fetal chromosomal aberrations were pathogenic and associated with severe clinical phenotypes (61/79; 77.2%). For CPM cases, occurrence of pre-eclampsia (8.5% [16/189] vs 0.5% [754/159,924]; RR 18.5), and birth weigh

Human Complement Regulators C4b-Binding Protein and C1 Esterase Inhibitor Interact with a Novel Outer Surface Protein of Borrelia recurrentis

The spirochete Borrelia recurrentis is the causal agent of louse-borne relapsing fever and is transmitted to humans by the infected body louse Pediculus humanus. We have recently demonstrated that the B. recurrentis surface receptor, HcpA, specifically binds factor H, the regulator of the alternative pathway of complement activation, thereby inhibiting complement mediated bacteriolysis. Here, we show that B. recurrentis spirochetes express another potential outer membrane lipoprotein, termed CihC, and acquire C4b-binding protein (C4bp) and human C1 esterase inhibitor (C1-Inh), the major inhibitors of the classical and lectin pathway of complement activation. A highly homologous receptor for C4bp was also found in the African tick-borne relapsing fever spirochete B. duttonii. Upon its binding to B. recurrentis or recombinant CihC, C4bp retains its functional potential, i.e. facilitating the factor I-mediated degradation of C4b. The additional finding that ectopic expression of CihC in serum sensitive B. burgdorferi significantly increased spirochetal resistance against human complement suggests this receptor to substantially contribute, together with other known strategies, to immune evasion of B. recurrentis