CEACAM5-Targeted Immuno-PET in Androgen Receptor-Negative Prostate Cancer.

The incidence of androgen receptor (AR)-negative (AR-) prostate cancer, including aggressive neuroendocrine prostate cancer (NEPC), has more than doubled in the last decade, but its timely diagnosis is difficult as it lacks typical prostate cancer hallmarks. The carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) has recently been identified as an upregulated surface antigen in NEPC. We developed an immuno-PET agent targeting CEACAM5 and evaluated its ability to delineate AR- prostate cancer in vivo. Methods: CEACAM5 expression was evaluated in a panel of prostate cancer cell lines by immunohistochemistry and Western blotting. The CEACAM5-targeting antibody labetuzumab was conjugated with the chelator desferrioxamine (DFO) and radiolabeled with 89Zr. The in vivo distribution of the radiolabeled antibody was evaluated in xenograft prostate cancer models by PET imaging and ex vivo organ distribution. Results: The NEPC cell line H660 exhibited strong CEACAM5 expression, whereas expression was limited in the AR- cell lines PC3 and DU145 and absent in the AR-positive cell line LNCaP. [89Zr]Zr-DFO-labetuzumab imaging was able to clearly delineate both neuroendocrine H660 xenografts and AR- DU145 in vivo but could not detect the AR-positive xenograft LNCaP. Conclusion: Immuno-PET imaging with [89Zr]Zr-DFO-labetuzumab is a promising diagnostic tool for AR- prostate cancer.

Automatic assessment of bowel preparation by an artificial intelligence model and its clinical applicability.

BACKGROUND AND AIM: Reliable bowel preparation assessment is important in colonoscopy. However, current scoring systems are limited by laborious and time-consuming tasks and interobserver variability. We aimed to develop an artificial intelligence (AI) model to assess bowel cleanliness and evaluate its clinical applicability. METHODS: A still image-driven AI model to assess the Boston Bowel Preparation Scale (BBPS) was developed and validated using 2361 colonoscopy images. For evaluating real-world applicability, the model was validated using 113 10-s colonoscopy video clips and 30 full colonoscopy videos to identify "adequate (BBPS 2-3)" or "inadequate (BBPS 0-1)" preparation. The model was tested with an external dataset of 29 colonoscopy videos. The clinical applicability of the model was evaluated using 225 consecutive colonoscopies. Inter-rater variability was analyzed between the AI model and endoscopists. RESULTS: The AI model achieved an accuracy of 94.0% and an area under the receiver operating characteristic curve of 0.939 with the still images. Model testing with an external dataset showed an accuracy of 95.3%, an area under the receiver operating characteristic curve of 0.976, and a sensitivity of 100% for the detection of inadequate preparations. The clinical applicability study showed an overall agreement rate of 85.3% between endoscopists and the AI model, with Fleiss' kappa of 0.686. The agreement rate was lower for the right colon compared with the transverse and left colon, with Fleiss' kappa of 0.563, 0.575, and 0.789, respectively. CONCLUSIONS: The AI model demonstrated accurate bowel preparation assessment and substantial agreement with endoscopists. Further refinement of the AI model is warranted for effective monitoring of qualified colonoscopy in large-scale screening programs.

Metastasis of colon cancer requires Dickkopf-2 to generate cancer cells with Paneth cell properties.

Metastasis is the leading cause of cancer-related mortality. Paneth cells provide stem cell niche factors in homeostatic conditions, but the underlying mechanisms of cancer stem cell niche development are unclear. Here we report that Dickkopf-2 (DKK2) is essential for the generation of cancer cells with Paneth cell properties during colon cancer metastasis. Splenic injection of Dkk2-knockout (KO) cancer organoids into C57BL/6 mice resulted in a significant reduction of liver metastases. Transcriptome analysis showed reduction of Paneth cell markers such as lysozymes in KO organoids. Single cell RNA sequencing analyses of murine metastasized colon cancer cells and patient samples identified the presence of lysozyme positive cells with Paneth cell properties including enhanced glycolysis. Further analyses of transcriptome and chromatin accessibility suggested Hepatocyte nuclear factor 4-alpha (HNF4A) as a downstream target of DKK2. Chromatin immunoprecipitation followed by sequencing analysis revealed that HNF4A binds to the promoter region of Sox9, a well-known transcription factor for Paneth cell differentiation. In the liver metastatic foci, DKK2 knockout rescued HNF4A protein levels followed by reduction of lysozyme positive cancer cells. Taken together, DKK2-mediated reduction of HNF4A protein promotes the generation of lysozyme positive cancer cells with Paneth cell properties in the metastasized colon cancers.

Single Cell Analysis of Treatment-Resistant Prostate Cancer: Implications of Cell State Changes for Cell Surface Antigen Targeted Therapies.

Targeting cell surface molecules using radioligand and antibody-based therapies has yielded considerable success across cancers. However, it remains unclear how the expression of putative lineage markers, particularly cell surface molecules, varies in the process of lineage plasticity, wherein tumor cells alter their identity and acquire new oncogenic properties. A notable example of lineage plasticity is the transformation of prostate adenocarcinoma (PRAD) to neuroendocrine prostate cancer (NEPC)--a growing resistance mechanism that results in the loss of responsiveness to androgen blockade and portends dismal patient survival. To understand how lineage markers vary across the evolution of lineage plasticity in prostate cancer, we applied single cell analyses to 21 human prostate tumor biopsies and two genetically engineered mouse models, together with tissue microarray analysis (TMA) on 131 tumor samples. Not only did we observe a higher degree of phenotypic heterogeneity in castrate-resistant PRAD and NEPC than previously anticipated, but also found that the expression of molecules targeted therapeutically, namely PSMA, STEAP1, STEAP2, TROP2, CEACAM5, and DLL3, varied within a subset of gene-regulatory networks (GRNs). We also noted that NEPC and small cell lung cancer (SCLC) subtypes shared a set of GRNs, indicative of conserved biologic pathways that may be exploited therapeutically across tumor types. While this extreme level of transcriptional heterogeneity, particularly in cell surface marker expression, may mitigate the durability of clinical responses to novel antigen-directed therapies, its delineation may yield signatures for patient selection in clinical trials, potentially across distinct cancer types.

Dataset on passenger acceptance during autonomous ferry public trials: Questionnaires and interviews.

This paper presents a dataset from the first public trial of an urban autonomous passenger ferry. The dataset contains questionnaires designed to assess passenger acceptance in terms of perceived safety, trustworthiness, and reliability. Questionnaires and their responses are paired samples collected before and after use (N = 884). The dataset also contains transcripts of semi-structured interviews on the themes of perceived safety, trustworthiness, and reliability (N = 25). The public trial was held in Trondheim, Norway, during the period September-October 2022. The autonomous ferry used in the trial was the "milliAmpere2," which is owned and operated by the Norwegian University of Science and Technology (NTNU). The data represents a state-of-the-art data collection effort owing to on-site data collection immediately before and after interactions with an Autonomous Vehicle (AV) in a public transportation context. The dataset is suitable for producing quantitative and qualitative analyses and for developing indicators of technology acceptance and related social phenomena regarding AVs, either in the maritime context or beyond.

Utilizing machine learning for reactive material selection and width design in permeable reactive barrier (PRB).

Permeable reactive barrier (PRB) is an important groundwater treatment technology. However, selecting the optimal reactive material and estimating the width remain critical and challenging problems in PRB design. Machine learning (ML) has advantages in predicting evolution and tracing contaminants in temporal and spatial distribution. In this study, ML was developed to design PRB, and its feasibility was validated through experiments and a case study. ML algorithm showed a good prediction about the Freundlich equilibrium parameter (R2 0.94 for KF, R2 0.96 for n). After SHapley Additive exPlanation (SHAP) analysis, redefining the range of the significant impact factors (initial concentration and pH) can further improve the prediction accuracy (R2 0.99 for KF, R2 0.99 for n). To mitigate model bias and ensure comprehensiveness, evaluation index with expert opinions was used to determine the optimal material from candidate materials. Meanwhile, the ML algorithm was also applied to predict the width of the mass transport zone in the adsorption column. This procedure showed excellent accuracy with R2 and root-mean-square-error (RMSE) of 0.98 and 1.2, respectively. Compared with the traditional width design methodology, ML can enhance design efficiency and save experiment time. The novel approach is based on traditional design principles, and the limitations and challenges are highlighted. After further expanding the data set and optimizing the algorithm, the accuracy of ML can make up for the existing limitations and obtain wider applications.

Updated Review Article: Cyclin-Dependent Kinase 4/6 Inhibitor Impact, FDA Approval, and Resistance Pathways.

Objective: To describe the mechanism of cyclin-dependent kinase (CDK) 4/6 inhibitors, mechanisms of resistance, and summarize various clinical trials used to determine the efficacy and safety of CDK4/6 inhibitor used for the treatment of hormone receptor-positive (HR+), human epidermal growth factor receptor 2 negative (HER2-), advanced or metastatic breast cancer. Data Sources: An extensive literature search using PubMed and notable sources was performed (2016 to February 2022) using the following search terms: CDK4/6 inhibitors, palbociclib, abemaciclib, ribociclib, CDK4/6 inhibitor resistance, FAT1 gene, luminal A breast cancer, luminal B breast cancer, HR+/HER2- breast cancer. Abstracts from conferences, national clinical trials, and drug monographs were reviewed. Study Selection and Data Extraction: Relevant clinical studies or those conducted in humans and updated clinical trials were considered. Data synthesis: The various clinical trials reviewed and results have led to numerous studies and expansions of U.S. Food and Drug Administration (FDA) approval. Although the use of CDK4/6 inhibitors has improved progression-free survival in patients with HR+, HER2- breast cancer, studies have shown that resistance pathways can cause cells to be insensitive to CDK4/6 inhibitors, leading to continued cell proliferation. Conclusions: CDK4/6 inhibitors are recommended as first-line therapy in combination with endocrine therapy for patients with HR+/HER2- advanced breast cancer. However, mutations and acquired resistance can occur that affect a patient's response to treatment. Additional research needs to be conducted on strategies to overcome resistance and determine how ethnicity plays a role in resistance pathways.

Heart failure in a cat due to hypertrophic cardiomyopathy phenotype caused by chronic uncontrolled hyperthyroidism.

A 16-year-old castrated male Persian cat was presented with weight loss, anorexia and dyspnoea. Tachycardia and tachypnoea were observed upon presentation. The cat was previously diagnosed with hyperthyroidism and left ventricular hypertrophy and received methimazole, but was subsequently not followed up and treated appropriately. Thoracic radiography revealed mild pleural effusion, interstitial lung pattern, moderate cardiomegaly and moderate-to-severe dilation of the pulmonary artery and pulmonary vein. On echocardiography, the left ventricular hypertrophy, identified earlier, shoed partial regression. Therefore, the previous myocardial hypertrophy was diagnosed as a hypertrophic cardiomyopathy phenotype related to hyperthyroidism. ST-segment elevation was identified on electrocardiography, and the thyroid profile examination revealed increased total thyroxine and free thyroxine and decreased thyroid-stimulating hormone levels, suggesting myocardial injury and uncontrolled hyperthyroidism, respectively. In addition, normal N-terminal pro-B-type natriuretic peptide and high cardiac troponin I levels were found. Based on these findings, the observed congestive heart failure was considered as a sequel of myocardial injury caused by uncontrolled hyperthyroidism. Clinical signs resolved after intravenous administration of furosemide and butorphanol, oxygen supply and thoracocentesis. Furosemide and pimobendan were additionally administered, and the cat was discharged. This case demonstrates that myocardial damage due to chronic uncontrolled hyperthyroidism may cause heart failure in cats.

TRPV1 inhibition overcomes cisplatin resistance by blocking autophagy-mediated hyperactivation of EGFR signaling pathway.

Cisplatin resistance along with chemotherapy-induced neuropathic pain is an important cause of treatment failure for many cancer types and represents an unmet clinical need. Therefore, future studies should provide evidence regarding the mechanisms of potential targets that can overcome the resistance as well as alleviate pain. Here, we show that the emergence of cisplatin resistance is highly associated with EGFR hyperactivation, and that EGFR hyperactivation is arisen by a transcriptional increase in the pain-generating channel, TRPV1, via NANOG. Furthermore, TRPV1 promotes autophagy-mediated EGF secretion via Ca2+ influx, which activates the EGFR-AKT signaling and, consequentially, the acquisition of cisplatin resistance. Importantly, TRPV1 inhibition renders tumors susceptible to cisplatin. Thus, our findings indicate a link among cisplatin resistance, EGFR hyperactivation, and TRPV1-mediated autophagic secretion, and implicate that TRPV1 could be a crucial drug target that could not only overcome cisplatin resistance but also alleviate pain in NANOG+ cisplatin-resistant cancer.

Cytokine receptor γc effectuates the generation of proinflammatory innate CD8 T cells by non-classical MHC-I molecules.

Innate CD8 T cells correspond to a population of terminally differentiated effector T cells that phenotypically appear as antigen-experienced memory cells and functionally resemble proinflammatory CD8 T cells, expressing copious amounts of IFNγ. Innate CD8 T cells, however, are distinct from conventional effector-memory CD8 T cells as they acquire functional maturity during their generation in the thymus. Understanding the molecular mechanisms that drive their thymic development and differentiation is an intensely studied subject in T cell immunity, and here we identified the cytokine receptor γc as a critical mediator of innate CD8 T cell generation that promotes their selection even in the absence of classical MHC-I molecules. Consequently, overexpression of γc resulted in a dramatic increase of innate CD8 T cells in KbDb-deficient mice. We mapped its underlying mechanism to the expansion of IL-4-producing invariant NKT cells, so that it is the increased availability of intrathymic IL-4 which augments the selection of innate CD8 T cells. Collectively, these results unravel the selection of innate CD8 T cells being mediated by non-classical MHC-I molecules and being modulated by the abundance of the γc cytokine, IL-4.

A Phase II/III, Multicenter, Observer-blinded, Randomized, Non-inferiority and Safety, study of typhoid conjugate vaccine (EuTCV) compared to Typbar-TCV® in healthy 6 Months-45 years aged participants.

The typhoid conjugate vaccine (TCV) ensures a long-lasting protective immune response, requires fewer doses and is fit for children under 2 years of age. From Phase I study, EuTCV displayed considerable immunogenicity and reliable safety, thus endorsing further examination in Phase II/III trials. Therefore, a clinical Phase II/III study (NCT04830371) was conducted to evaluate its efficacy in healthy Filipino participants aged 6 months to 45 years through administration of the test vaccine (Arm A, B, and C) or comparator vaccine Typbar-TCV® (Arm D). Sera samples were collected pre-vaccination (Visit 1) and post-vaccination (Visit 4, Day 28) to assess the immunogenicity of EuTCV and Typbar-TCV®. During the study, participants were regularly monitored through scheduled visits to the clinic to report any adverse events associated with the vaccine. For vaccine safety, the proportion of solicited and unsolicited Treatment-Emergent Adverse Events was all comparable between EuTCV and Typbar-TCV® groups. A single dose of EuTCV produced seroconversion in 99.4% of treated participants, with seroconversion rates non-inferior to that of Typbar-TCV®. Batch-to-batch consistency was concluded based on the 90% Confidence Interval of the geometric mean ratio (EuTCV Arm A, B, and C) at Week 4, lying within the equivalence margin of 0.5 to 2.0 for all batches. Results from this Phase II/III clinical trial of EuTCV in healthy volunteers show comparable safety and considerable immunogenicity, compared to Typbar-TCV®, meeting the objectives of this pivotal study. ClinicalTrials.gov registration number: NCT04830371.

Regenerative Potential of Bone Morphogenetic Protein 7-Engineered Mesenchymal Stem Cells in Ligature-Induced Periodontitis.

Periodontitis is an oral disease caused by bacterial infection that has stages according to the severity of tissue destruction. The advanced stage of periodontitis presents irreversible destruction of soft and hard tissues, which finally results in loss of teeth. When conventional treatment modalities show limited results, tissue regeneration therapy is required in patients with advanced periodontitis. In the present study, we aimed to evaluate the effect of bone marrow-derived mesenchymal stem cells (BM-MSCs) delivering bone morphogenetic protein 7 (BMP7) on tissue regeneration in a periodontitis model. BMP7 is a member of the BMP family that shows bone-forming ability; however, BMPs rapid clearing and degradation and unproven efficacy make it difficult to apply it in clinical dentistry. To overcome this, we established BMP7-expressing engineered BM-MSCs (BMP7-eBMSCs) that showed superior osteogenic differentiation potential when subcutaneously transplanted with a biphasic calcium phosphate scaffold into immunocompromised mice. Furthermore, the efficacy of BMP7-eBMSC transplantation for periodontal tissue regeneration was evaluated in a rat ligature-induced periodontitis model. Upon measuring two-dimensional and three-dimensional amounts of regenerated alveolar bone using microcomputed tomography, the amounts were found to be significantly higher in the BMP7-eBMSC transplantation group than in the eBMSC transplantation group. Most importantly, fibrous periodontal ligament (PDL) tissue regeneration was also achieved upon BMP7-eBMSC transplantation, which was evaluated by calculating the modified relative connective tissue attachment. The amount of connective tissue attachment in the BMP7-eBMSC transplantation group was significantly higher than that in the ligature-induced periodontitis group, although the increase was comparable between the BMP7-eBMSC and human PDL stem cell transplantation groups. Taken together, our results suggested that sustainable release of BMP7 induces periodontal tissue regeneration and that transplantation of BMP7-eBMSCs is a feasible treatment option for periodontal regeneration. Impact Statement Periodontitis is the second most common human dental disease affecting chronic systemic diseases. Despite the tremendous efforts trying to cure the damaged periodontal tissues using tissue engineering technologies, a definitive regenerative method has not been in consensus. Researchers are seeking more feasible and abundant source of mesenchymal stem cells (MSCs), and furthermore, how to use reliable growth factors under more efficient control are the issues to be solved. In this study, we aimed to evaluate the effect of bone morphogenetic protein 7 (BMP7) gene delivering bone marrow-derived MSCs on periodontal tissue regeneration to evaluate the efficacy of BMP7 and engineered BMSCs for periodontal tissue regeneration.

Smartphone Sensor-Based Human Motion Characterization with Neural Stochastic Differential Equations and Transformer Model.

With many conveniences afforded by advances in smartphone technology, developing advanced data analysis methods for health-related information from smartphone users has become a fast-growing research topic in the healthcare field. Along these lines, this paper addresses smartphone sensor-based characterization of human motions with neural stochastic differential equations (NSDEs) and a Transformer model. NSDEs and modeling via Transformer networks are two of the most prominent deep learning-based modeling approaches, with significant performance yields in many applications. For the problem of modeling dynamical features, stochastic differential equations and deep neural networks are frequently used paradigms in science and engineering, respectively. Combining these two paradigms in one unified framework has drawn significant interest in the deep learning community, and NSDEs are among the leading technologies for combining these efforts. The use of attention has also become a widely adopted strategy in many deep learning applications, and a Transformer is a deep learning model that uses the mechanism of self-attention. This concept of a self-attention based Transformer was originally introduced for tasks of natural language processing (NLP), and due to its excellent performance and versatility, the scope of its applications is rapidly expanding. By utilizing the techniques of neural stochastic differential equations and a Transformer model along with data obtained from smartphone sensors, we present a deep learning method capable of efficiently characterizing human motions. For characterizing human motions, we encode the high-dimensional sequential data from smartphone sensors into latent variables in a low-dimensional latent space. The concept of the latent variable is particularly useful because it can not only carry condensed information concerning motion data, but also learn their low-dimensional representations. More precisely, we use neural stochastic differential equations for modeling transitions of human motion in a latent space, and rely on a Generative Pre-trained Transformer 2 (GPT2)-based Transformer model for approximating the intractable posterior of conditional latent variables. Our experiments show that the proposed method can yield promising results for the problem of characterizing human motion patterns and some related tasks including user identification.

Public interest in the digital transformation accelerated by the COVID-19 pandemic and perception of its future impact.

BACKGROUND/AIMS: The coronavirus disease 2019 (COVID-19) pandemic has accelerated digital transformation (DT). We investigated the trend of the public interest in technologies regarding the DT and Koreans' experiences and their perceptions of the future impact of these technologies. METHODS: Using Google Trends, the relative search volume (RSV) for topics including "coronavirus," "artificial intelligence," "cloud," "big data," and "metaverse" were retrieved for the period from January 2020 to January 2022. A survey was conducted to assess the population's knowledge, experience, and perceptions regarding the DT. RESULTS: The RSV for "metaverse" showed an increasing trend, in contrast to those for "cloud," "big data," and "coronavirus." The RSVs for DT-related keywords had a negative correlation with the number of new weekly COVID-19 cases. In our survey, 78.1% responded that the positive impact of the DT on future lives would outweigh the negative impact. The predictors for this positive perception included experiences with the metaverse (4.0-fold) and virtual reality (VR)/augmented reality (AR) education (3.8-fold). Respondents predicted that the biggest change would occur in the healthcare sector after transportation/ communication. CONCLUSION: Koreans' search interest for "metaverse" showed an increasing trend during the COVID-19 pandemic. Koreans believe that DT will bring about big changes in the healthcare sector. Most of the survey respondents have a positive outlook about the impact of DT on future life, and the predictors for this positive perception include the experiences with the metaverse or VR/AR education. Healthcare professionals need to accelerate the adoption of DT in clinical practice, education and training.

Improved performance and robustness of multi-task representation learning with consistency loss between pretexts for intracranial hemorrhage identification in head CT.

With the recent development of deep learning, the classification and segmentation tasks of computer-aided diagnosis (CAD) using non-contrast head computed tomography (NCCT) for intracranial hemorrhage (ICH) has become popular in emergency medical care. However, a few challenges remain, such as the difficulty of training due to the heterogeneity of ICH, the requirement for high performance in both sensitivity and specificity, patient-level predictions demanding excessive costs, and vulnerability to real-world external data. In this study, we proposed a supervised multi-task aiding representation transfer learning network (SMART-Net) for ICH to overcome these challenges. The proposed framework consists of upstream and downstream components. In the upstream, a weight-shared encoder of the model is trained as a robust feature extractor that captures global features by performing slice-level multi-pretext tasks (classification, segmentation, and reconstruction). Adding a consistency loss to regularize discrepancies between classification and segmentation heads has significantly improved representation and transferability. In the downstream, the transfer learning was conducted with a pre-trained encoder and 3D operator (classifier or segmenter) for volume-level tasks. Excessive ablation studies were conducted and the SMART-Net was developed with optimal multi-pretext task combinations and a 3D operator. Experimental results based on four test sets (one internal and two external test sets that reflect a natural incidence of ICH, and one public test set with a relatively small amount of ICH cases) indicate that SMART-Net has better robustness and performance in terms of volume-level ICH classification and segmentation over previous methods. All code is available at https://github.com/babbu3682/SMART-Net.

Evaluation of the blood neutrophil-to-lymphocyte ratio as a biomarker for meningoencephalitis of unknown etiology in dogs.

BACKGROUND: The neutrophil-to-lymphocyte ratio (NLR) has been identified as a biomarker in several inflammatory and autoimmune diseases. Multiple sclerosis (MS) has been found to be associated with changes in the NLR in humans. OBJECTIVES: To examine the diagnostic value of the NLR in meningoencephalitis of unknown etiology (MUE) in dogs. ANIMALS: Thirty-eight MUE dogs, 20 hydrocephalic dogs, 10 brain tumor (BT) dogs, 32 idiopathic epilepsy (IE) dogs, and 41 healthy dogs. METHODS: Retrospective study. Medical records were reviewed to identify dogs with a diagnosis of neurologic disease. The NLR was determined in all dogs. RESULTS: The median NLR was significantly higher in MUE dogs (6.08) than in healthy (1.78, P < .001), IE (2.50, P < .05), and hydrocephalic dogs (1.79, P < .05). The area under the receiver operating characteristic curve of the NLR for differentiation between MUE and healthy dogs was 0.96, and between the MUE dogs and dogs with other forebrain diseases was 0.86. An optimal cutoff of 4.16 for the NLR had a sensitivity of 71.1% and specificity of 83.9% to differentiate the MUE dogs from the dogs with other forebrain diseases. CONCLUSIONS AND CLINICAL IMPORTANCE: The NLR could be a biomarker for diagnosing MUE and distinguishing it from other intracranial diseases in dogs.

Reduced diversity of intestinal T-cell receptor repertoire in patients with Crohn's disease.

Background: The intestinal microenvironment directly determines the human T-cell receptor (TCR) repertoire. Despite its extreme diversity, TCR repertoire analysis may provide a better understanding of the immune system in patients with inflammatory bowel disease. Methods: To investigate TCR repertoires in the intestinal mucosa, RNA sequencing was performed for inflamed and non-inflamed intestinal mucosa samples obtained from 13 patients with Crohn's disease (CD) and healthy mucosa from nine non-IBD controls. Results: The gene expression frequency of the TCR repertoire showed a clear separation between inflamed mucosa of patients with CD and healthy mucosa of non-IBD controls in the hierarchical clustering heatmap. The richness of TCR repertoires measured by the Chao1 index did not show a significant difference among groups, whereas diversity measured by the D50 diversity index was decreased in the inflamed mucosa of CD patients. Rare/small TCR clonotypes occupied a large proportion of TCR repertoires in healthy mucosa of controls, whereas expanded clonotypes were common in inflamed mucosa of patients with CD. Segment usages of TRAV2, TRAV22, TRAV40, TRJ14, TRAJ51, TRBV1, TRBV21.1, and TRBJ1.5 were significantly decreased in CD patients. KEGG enrichment analysis identified the enrichment of several KEGG pathways, including inflammatory bowel disease (p = 0.0012), Th1 and Th2 cell differentiation (p = 0.0011), and intestinal immune network for IgA production (p = 0.0468). Conclusions: The diversity of the TCR repertoire is reduced in inflamed mucosa of CD patients, which might contribute to intestinal inflammation.

Evaluation of 18F-fluorodeoxyglucose uptake of beagle dogs for different durations of isoflurane anesthesia.

18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is used for tumor evaluation. In veterinary medicine, anesthesia is an essential tool during the PET scanning process. However, the changes in FDG uptake in dogs that have undergone anesthesia for a longer duration have not been studied. This study aimed to analyze the influence of isoflurane anesthesia on FDG uptake in dogs undergoing PET. A crossover design was implemented by exposing 3 groups of 6 dogs to different durations of anesthesia (60, 90, and 150 minutes). Inhalation anesthesia was maintained throughout the scanning process (30 minutes) and FDG was injected 1 hour before the start of the PET scan. The standard uptake value of FDG was obtained for the 7 gross structures (whole brain, lung, salivary gland, liver, spleen, mediastinal blood pool, and kidney cortex) as well as for the 7 intracranial structures (frontal, parietal, temporal and occipital lobes, cerebellum, brain stem, and caudal colliculus). The whole brain and intracranial structures showed significantly lower FDG uptake in dogs with a longer duration of anesthesia, whereas other gross structures did not. Our results suggest that the duration of anesthesia should be considered when evaluating the uptake of FDG by the brain.

La tomographie par émission de positrons (PET) au 18F-fluorodésoxyglucose (FDG) est utilisée pour l'évaluation des tumeurs. En médecine vétérinaire, l'anesthésie est un outil essentiel lors du processus de PET. Cependant, les modifications de l'absorption du FDG chez les chiens ayant subi une anesthésie de plus longue durée n'ont pas été étudiées. Cette étude visait à analyser l'influence de l'anesthésie à l'isoflurane sur l'absorption du FDG chez les chiens subissant une PET. Un modèle croisé a été mis en oeuvre en exposant trois groupes de six chiens à différentes durées d'anesthésie (60, 90 et 150 minutes). L'anesthésie par inhalation a été maintenue tout au long du processus de numérisation (30 minutes) et le FDG a été injecté 1 heure avant le début de la PET. La valeur d'absorption standard du FDG a été obtenue pour les sept structures macroscopiques (cerveau entier, poumon, glande salivaire, foie, rate, pool sanguin médiastinal et cortex rénal) ainsi que pour les sept structures intracrâniennes (frontale, pariétale, temporale et lobes occipitaux, cervelet, tronc cérébral et colliculus caudal). L'ensemble du cerveau et les structures intracrâniennes ont montré une absorption de FDG significativement plus faible chez les chiens avec une durée d'anesthésie plus longue, contrairement aux autres structures. Nos résultats suggèrent que la durée de l'anesthésie doit être prise en compte lors de l'évaluation de la captation du FDG par le cerveau.(Traduit par Docteur Serge Messier).