The roles and mechanisms of coding and noncoding RNA variations in cancer.

Functional variations in coding and noncoding RNAs are crucial in tumorigenesis, with cancer-specific alterations often resulting from chemical modifications and posttranscriptional processes mediated by enzymes. These RNA variations have been linked to tumor cell proliferation, growth, metastasis, and drug resistance and are valuable for identifying diagnostic or prognostic cancer biomarkers. The diversity of posttranscriptional RNA modifications, such as splicing, polyadenylation, methylation, and editing, is particularly significant due to their prevalence and impact on cancer progression. Additionally, other modifications, including RNA acetylation, circularization, miRNA isomerization, and pseudouridination, are recognized as key contributors to cancer development. Understanding the mechanisms underlying these RNA modifications in cancer can enhance our knowledge of cancer biology and facilitate the development of innovative therapeutic strategies. Targeting these RNA modifications and their regulatory enzymes may pave the way for novel RNA-based therapies, enabling tailored interventions for specific cancer subtypes. This review provides a comprehensive overview of the roles and mechanisms of various coding and noncoding RNA modifications in cancer progression and highlights recent advancements in RNA-based therapeutic applications.

Plant P450 forms indigo and indirubin when expressed in Escherichia coli.

Indigo and indirubin are derived from indoxyl molecules, which generally occur as indoxyl glycosides in woad (Isatis tinctoria L.) and other indigo-producing plants. Indoxyl glycosides are biosynthesized from indole via 3-hydroxylation to form indoxyl, followed by one or more glycosylations. Enzymes that attach and remove sugars to and from indoxyl have already been isolated and characterized, while enzymes that convert indole into indoxyl in plants have remained elusive, until the identification of P450s and flavin-containing monooxygenases that hydroxylate indole. A P450 gene from woad (named CYP71B102) was heterologously expressed in E. coli, resulting in the formation of indigo and indirubin, as well as isatin and 2-oxindole, which along with indoxyl are putative precursors of indirubin. The addition of either isatin or 2-oxindole to the recombinant E. coli reduced the levels of indigo and increased the amount of indirubin, whereas coexpression of CYP71B102 with isatin hydroxylase (which degrades isatin) increased the levels of indigo and decreased the amount of indirubin, albeit slightly. The results suggest that CYP71B102 hydroxylates indole at both the 2- and 3- positions to produce 2-oxindole and indoxyl, respectively, and that the coupling of indoxyl with either 2-oxindole or isatin forms indirubin, while dimerization of indoxyl forms indigo. This P450 gene is thus likely involved in the biosynthesis of indirubin in woad, as well as the formation of indigo and its glycosidic precursors, even if other types of enzymes, such as flavin-containing monooxygenases, may be involved in indole hydroxylation in other indigo-producing plants.

Ultrasonographic differential diagnosis of medial elbow pain.

Medial elbow pain is a common musculoskeletal problem among individuals engaging in repetitive activities. Medial epicondylitis is the predominant cause of this pain. However, other potential causes must be considered as part of the differential diagnosis. This article discusses several etiologies of medial elbow pain, including medial epicondylitis, ulnar neuropathy, snapping triceps syndrome, ulnar collateral ligament injury, medial antebrachial cutaneous neuropathy, and diseases of the elbow joint, with an emphasis on ultrasound (US) findings. Awareness of possible diagnoses and their US features can assist radiologists in establishing a comprehensive diagnosis for medial elbow pain.

Maxillary Reconstruction with Free Vascularized Fibula: 15-Year Experience.

BACKGROUND: Reconstruction of the midface after maxillectomy is extremely challenging due to the need to reestablish the contour of the midface, maintain oronasal separation, support the orbit, and to restore the dentition. In this study, we present our specific technique, surgical and functional outcomes, and pitfalls to avoid for reconstruction of the midface with the fibula osteocutaneous free flap. METHODS: A retrospective review of patients who underwent maxillary reconstruction with a fibula osteocutaneous free flap was performed. RESULTS: Eighty-five flaps were performed in 73 patients (61 patients received a fibula flap only; 12 patients received an additional soft tissue free flap). Reconstructions were performed for 82.2% Cordeiro type 2 and 18.8 % Cordeiro type 3a defects. Osseointegrated dental implants were placed in 95.9% of patients, 13.7% of whom underwent immediate implant placement. Concurrent orbital floor reconstruction was performed in 16.2% of patients. The rate of operative takeback was 18.9%, and total flap loss occurred in 2.7%. Hardware exposure occurred in 11.0% at a mean of 4.4 years postoperatively and palatal fistulae occurred in 5.5%, usually within the first 3 weeks following reconstruction. Functionally, 79.5% demonstrated excellent speech and 80.9% had unrestricted diet postoperatively. The mean follow-up period was 3.4 years. CONCLUSIONS: The present study shows that maxillary reconstruction with free fibula flap provides reliable reconstruction that restores dental, orbital, and midfacial support. Modifications and nuances to the reconstructive technique learned over time to avoid complications and improve outcomes are described herein.

Metabolomic analysis combined with machine learning algorithms enables the evaluation of postharvest pecan color stability.

Nut kernel color is a crucial quality indicator affecting the consumers first impression of the product. While growing evidence suggests that plant phenolics and their derivatives are linked to nut kernel color, the compounds (biomarkers) responsible for kernel color stability during storage remain elusive. Here, pathway-based metabolomics with machine learning algorithms were employed to identify key metabolites of postharvest pecan color stability. Metabolites in phenylpropanoid, flavonoid, and anthocyanin biosynthetic pathways were analyzed in the testa of nine pecan cultivars using liquid chromatography-mass spectrometry. With color measurements, different machine learning models were compared to find relevant biomarkers of pecan color phenotypes. Results revealed potential marker compounds that included flavonoid precursors and anthocyanidins as well as anthocyanins (e.g., peonidin, delphinidin-3-O-glucoside). Our findings provide a foundation for future research in the area, and will help select genes/proteins for the breeding of pecans with stable and desirable kernel color.

Nanoscale single-vesicle analysis: High-throughput approaches through AI-enhanced super-resolution image analysis.

The analysis of membrane vesicles at the nanoscale level is crucial for advancing the understanding of intercellular communication and its implications for health and disease. Despite their significance, the nanoscale analysis of vesicles at the single particle level faces challenges owing to their small size and the complexity of biological fluids. This new vesicle analysis tool leverages the single-molecule sensitivity of super-resolution microscopy (SRM) and the high-throughput analysis capability of deep-learning algorithms. By comparing classical clustering methods (k-means, DBSCAN, and SR-Tesseler) with deep-learning-based approaches (YOLO, DETR, Deformable DETR, and Faster R-CNN) for the analysis of super-resolution fluorescence images of exosomes, we identified the deep-learning algorithm, Deformable DETR, as the most effective. It showed superior accuracy and a reduced processing time for detecting individual vesicles from SRM images. Our findings demonstrate that image-based deep-learning-enhanced methods from SRM images significantly outperform traditional coordinate-based clustering techniques in identifying individual vesicles and resolving the challenges related to misidentification and computational demands. Moreover, the application of the combined Deformable DETR and ConvNeXt-S algorithms to differently labeled exosomes revealed its capability to differentiate between them, indicating its potential to dissect the heterogeneity of vesicle populations. This breakthrough in vesicle analysis suggests a paradigm shift towards the integration of AI into super-resolution imaging, which is promising for unlocking new frontiers in vesicle biology, disease diagnostics, and the development of vesicle-based therapeutics.

Association between secondhand smoke exposure and anxiety among adolescents: A nationwide cross-sectional study.

INTRODUCTION: Adolescents are especially susceptible to the harmful effects of secondhand smoke exposure. Mental health issues may be one of these negative consequences. This study aimed to explore the association between secondhand smoke exposure and anxiety among Korean adolescents. METHODS: This study used the nationwide representative cross-sectional data obtained from the 4-year (2020-2023) Korea Youth Risk Behavior Survey. In total, 214514 individuals aged 12-18 years were included in this study (109910 males and 104604 females). Secondhand smoke exposure was assessed based on responses to questions concerning the days they were exposed (at home and in public places), while anxiety levels were measured using the Generalized Anxiety Disorder 7 scale. Multivariable logistic regression analysis divided by sex was performed to explore the association (p=0.0173 for interaction by secondhand smoke exposure and sex), and adjusted odds ratios (ORs) with 95% confidence intervals (CI) were calculated. RESULTS: Among the study population, 8.8% of the male and 15.6% of the female participants had anxiety. After adjusting for covariates, adolescents with secondhand smoke exposure had a higher likelihood of reporting anxiety than those without the exposure (male, OR=1.23; 95% CI: 1.16-1.29; female, OR=1.27; 95% CI: 1.21-1.33). In additional stratified analyses, this association was more prominent among those who were never smokers, were exposed for more days, and had severe levels of anxiety. CONCLUSIONS: This study found that secondhand smoke exposure was associated with anxiety in adolescents; hence, proper political interventions to reduce secondhand smoke exposure may be required.

Semi-supervised abdominal multi-organ segmentation by object-redrawing.

BACKGROUND: Multi-organ segmentation is a critical task in medical imaging, with wide-ranging applications in both clinical practice and research. Accurate delineation of organs from high-resolution 3D medical images, such as CT scans, is essential for radiation therapy planning, enhancing treatment outcomes, and minimizing radiation toxicity risks. Additionally, it plays a pivotal role in quantitative image analysis, supporting various medical research studies. Despite its significance, manual segmentation of multiple organs from 3D images is labor-intensive and prone to low reproducibility due to high interoperator variability. Recent advancements in deep learning have led to several automated segmentation methods, yet many rely heavily on labeled data and human anatomy expertise. PURPOSE: In this study, our primary objective is to address the limitations of existing semi-supervised learning (SSL) methods for abdominal multi-organ segmentation. We aim to introduce a novel SSL approach that leverages unlabeled data to enhance the performance of deep neural networks in segmenting abdominal organs. Specifically, we propose a method that incorporates a redrawing network into the segmentation process to correct errors and improve accuracy. METHODS: Our proposed method comprises three interconnected neural networks: a segmentation network for image segmentation, a teacher network for consistency regularization, and a redrawing network for object redrawing. During training, the segmentation network undergoes two rounds of optimization: basic training and readjustment. We adopt the Mean-Teacher model as our baseline SSL approach, utilizing labeled and unlabeled data. However, recognizing significant errors in abdominal multi-organ segmentation using this method alone, we introduce the redrawing network to generate redrawn images based on CT scans, preserving original anatomical information. Our approach is grounded in the generative process hypothesis, encompassing segmentation, drawing, and assembling stages. Correct segmentation is crucial for generating accurate images. In the basic training phase, the segmentation network is trained using both labeled and unlabeled data, incorporating consistency learning to ensure consistent predictions before and after perturbations. The readjustment phase focuses on reducing segmentation errors by optimizing the segmentation network parameters based on the differences between redrawn and original CT images. RESULTS: We evaluated our method using two publicly available datasets: the beyond the cranial vault (BTCV) segmentation dataset (training: 44, validation: 6) and the abdominal multi-organ segmentation (AMOS) challenge 2022 dataset (training:138, validation:16). Our results were compared with state-of-the-art SSL methods, including MT and dual-task consistency (DTC), using the Dice similarity coefficient (DSC) as an accuracy metric. On both datasets, our proposed SSL method consistently outperformed other methods, including supervised learning, achieving superior segmentation performance for various abdominal organs. These findings demonstrate the effectiveness of our approach, even with a limited number of labeled data. CONCLUSIONS: Our novel semi-supervised learning approach for abdominal multi-organ segmentation addresses the challenges associated with this task. By integrating a redrawing network and leveraging unlabeled data, we achieve remarkable improvements in accuracy. Our method demonstrates superior performance compared to existing SSL and supervised learning methods. This approach holds great promise in enhancing the precision and efficiency of multi-organ segmentation in medical imaging applications.

The Role of Prolactin in Amniotic Membrane Regeneration: Therapeutic Potential for Premature Rupture of Membranes.

Premature rupture of membranes (PROM) is defined as rupture of fetal membranes before the onset of labor. Prolactin (PRL) is secreted by decidual membranes and accumulated significantly in the amniotic fluid during pregnancy. PRL could ameliorate inflammation and collagen degradation in fetal membranes. However, the role of PRL in amniotic membrane is not well characterized. We isolated human amniotic epithelial stem cells (hAESCs) from human fetal membranes to study the effect of PRL on proliferation, migration, and antioxidative stress. Amniotic pore culture technique (APCT) model was constructed to evaluate the tissue regeneration effect in vitro. The potential targets and pathways of PRL acting in amnion via integrated bioinformatic methods. PRL had a dose-dependent effect on hAESCs in vitro. PRL (500 ng/mL) significantly improved the viability of hAESCs and inhibited cell apoptosis, related to the upregulation of CCN2 expression and downregulation of Bax, Caspase 3, and Caspase 8. PRL accelerated migration process in hAESCs via downregulation of MMP2, MMP3, and MMP9. PRL attenuated the cellular damage and mitochondrial dysfunction induced by hydrogen peroxide in hAESCs. PRL accelerated the healing process in the APCT model significantly. The top 10 specific targets (IGF1R, SIRT1, MAP2K1, CASP8, MAPK14, MCL1, NFKB1, HIF1A, MTOR, and HSP90AA1) and signaling pathways (such as HIF signaling pathway) were selected using an integrated bioinformatics approach. PRL improves the viability and antioxidative stress function of hAESCs and the regeneration of ruptured amniotic membranes in vitro. Thus, PRL has great therapeutic potential for prevention and treatment of ruptured membranes.

Subjective Study on Pediatric Emergency Department Nurses' Perceptions of Urgency Using Q Methodology.

PURPOSE: In the emergency department (ED), triage significantly impacts patient safety. Therefore, triage nurses must make decisions accurately and timeously. This study aims to investigate how South Korean pediatric emergency nurses perceive urgency and classify severity using the Q methodology, which examines individuals' subjectivity. METHODS: We collected 84 statements from a Q population based on a literature review and interviews and selected 33 Q samples. The P samples included 30 pediatric emergency nurses at a Seoul tertiary care hospital. The principal component factor analysis method was used to analyze data using the PC-QUANL program. RESULTS: Four urgency perception types were identified among pediatric ED nurses-Type 1: "Experiential coping"; Type 2: "Careful reasoning"; Type 3: "Patient-centered thinking"; and Type 4: "Intuitive prediction." These types appear to be an integrated process of knowledge and clinical experience that considers children's characteristics and developmental stages. CONCLUSION: This study may serve as a basis for future education to improve pediatric ED nurses' urgency judgment and severity classification skills.

Leveraging altered lipid metabolism in treating B cell malignancies.

B cell malignancies, comprising over 80 heterogeneous blood cancers, pose significant prognostic challenges due to intricate oncogenic signaling. Emerging evidence emphasizes the pivotal role of disrupted lipid metabolism in the development of these malignancies. Variations in lipid species, such as phospholipids, cholesterol, sphingolipids, and fatty acids, are widespread across B cell malignancies, contributing to uncontrolled cell proliferation and survival. Phospholipids play a crucial role in initial signaling cascades leading to B cell activation and malignant transformation through constitutive B cell receptor (BCR) signaling. Dysregulated cholesterol and sphingolipid homeostasis support lipid raft integrity, crucial for propagating oncogenic signals. Sphingolipids impact malignant B cell stemness, proliferation, and survival, while glycosphingolipids in lipid rafts modulate BCR activation. Additionally, cancer cells enhance fatty acid-related processes to meet heightened metabolic demands. In obese individuals, the obesity-derived lipids and adipokines surrounding adipocytes rewire lipid metabolism in malignant B cells, evading cytotoxic therapies. Genetic drivers such as MYC translocations also intrinsically alter lipid metabolism in malignant B cells. In summary, intrinsic and extrinsic factors converge to reprogram lipid metabolism, fostering aggressive phenotypes in B cell malignancies. Therefore, targeting altered lipid metabolism has translational potential for improving risk stratification and clinical management of diverse B cell malignancy subtypes.

Comparison of laser and traditional lancing devices for capillary blood sampling in patients with diabetes mellitus and high bleeding risk.

PURPOSE: Despite the importance of self-monitoring blood glucose (SMBG) for management of diabetes mellitus (DM), frequent blood sampling is discouraged by bleeding risk due to dual-antiplatelet agent therapy (DAPT) or thrombocytopenia. METHODS: We compared the bleeding time (BT) of sampling by using a laser-lancing-device (LMT-1000) and a conventional lancet in patients with DM and thrombocytopenia or patients undergoing DAPT. BT was measured using the Duke method, and pain and satisfaction scores were assessed using numeric rating scale (NRS) and visual analog scale (VAS). The consistency in the values of glucose and glycated-hemoglobin (HbA1c) sampled using the LMT-1000 or lancet were compared. RESULTS: The BT of sampling with the LMT-1000 was shorter than that with the lancet in patients with thrombocytopenia (60s vs. 85s, P = 0.024). The NRS was lower and the VAS was higher in laser-applied-sampling than lancet-applied sampling in the DAPT-user group (NRS: 1 vs. 2, P = 0.010; VAS: 7 vs. 6, P = 0.003), whereas the group with thrombocytopenia only showed improvement in the VAS score (8 vs. 7, P = 0.049). Glucose and HbA1c sampled by the LMT-1000 and lancet were significantly correlated in both the DAPT-user and the thrombocytopenia groups. CONCLUSION: The LMT-1000 can promote SMBG by shortening BT in subject with thrombocytopenia and by increasing satisfaction score, as well as by showing reliable glucose and HbA1c value.

The potential utility of (2S,4R)-4-[18F] fluoroglutamine as a novel metabolic imaging marker for inflammation explored by rat models of arthritis and paw edema.

Purpose: (2S,4R)-4-[18F]fluoroglutamine ([18F]FGln) is a promising metabolic imaging marker in cancer. Based on the fact that major inflammatory cells are heavily dependent on glutamine metabolism like cancer cells, we explored the potential utility of [18F]FGln as a metabolic imaging marker for inflammation in two rat models: carrageenan-induced paw edema (CIPE) and collagen-induced arthritis (CIA). Procedures: The CIPE model (n = 4) was generated by injecting 200 µL of 3% carrageenan solution into the left hind paw three hours before the PET. The CIA model (n = 4) was generated by injecting 200 µg of collagen emulsion subcutaneously at the tail base 3-4 weeks before the PET. A qualitative scoring system was used to assess the severity of paw inflammation. After a CT scan, 15.7 ± 4.9 MBq of [18F]FGln was injected via the tail vein, followed by a dynamic micro-PET scan for 90 minutes under anesthesia with isoflurane. The standard uptake value of [18F]FGln was measured by placing a volume of interest in each paw. The non-injected right hind paws of the CIPE model rats served as controls for both models. The paws with CIA were pathologically examined after PET. Results: In CIPE models, uptake in the injected paw was higher compared to the non-injected paw by 52-83%. In CIA models, uptake in the paws with severe inflammation was higher than the averaged controls by 54-173%, while that with mild and no inflammation was slightly higher (33%) and lower (-7%), respectively. Combined overall, the [18F]FGln uptake in CIA showed a significant positive correlation with inflammation severity (r = 0.88, P = 0.009). The pathological findings confirmed profound inflammation in CIA. Conclusions: [18F]FGln uptake was increased in both acute and chronic inflammation, and the uptake level was significantly correlated with the severity, suggesting its potential utility as a novel metabolic imaging marker for inflammation.

CX3CR1+ macrophages interact with hepatic stellate cells to promote hepatocellular carcinoma through CD8+ T cell suppression.

BACKGROUND AND AIMS: Hepatic stellate cells (HSCs) contribute to hepatocellular carcinoma (HCC) progression by regulating multiple factors. However, the entire immunoregulatory functions of HSCs are still obscure. Here, we aim to investigate whether HSCs impose CX3CR1+ macrophages to pro-tumorigenic properties in the peritumoral area. APPROACH AND RESULTS: In single cell RNA-sequencing analysis of HCC patients, a subpopulation of macrophages specifically expressed Arg1 and Cx3cr1 in the peritumoral area, and were highly enriched with retinol metabolism-related genes. Flow cytometry analysis showed significantly increased frequencies of CD14+CD11b+HLA-DR‒ macrophages with CX3CR1 in the HCC adjacent region where α-SMA-expressing activated HSCs (aHSCs) showed co-localized expression of CX3CL1. Accordingly, in tumor-bearing mice, Cx3cl1 mRNA expression was notably increased in aHSCs within the adjacent HCC, where infiltration of CX3CR1+Ly6C+ macrophages was mostly observed with decreased CD8+ T cells. In adoptive transfer and in vitro co-culture of myeloid cells, we demonstrated that CX3CR1+Ly6C+ macrophages migrated and highly expressed arginase-1 by interacting with retinoid-enriched aHSCs in the adjacent HCC. Direct treatment of retinoids or co-culturing with retinol-storing mouse aHSCs or human LX-2 cells significantly increased arginase-1 expression in CX3CR1+Ly6C+ macrophages and human blood CD14+ cells, leading to the suppression of CD8+ T cell proliferation. Moreover, genetic deficiency of CX3CR1 in myeloid cells or pharmacological inhibition of retinol metabolism remarkably attenuated HCC development. CONCLUSION: We showed that CX3CR1+Ly6C+ macrophages migrate and interact with aHSCs in the peritumoral region where retinoids induce arginase-1 expression in CX3CR1+Ly6C+ macrophages, subsequently depriving CD8+ T cells of arginine and promoting HCC.

Time-Restricted Feeding Protects against Renal Ischemia-Reperfusion Injury in Mice.

Ischemia-reperfusion injury (IRI) in the kidneys is a major cause of acute kidney injury (AKI). Time-restricted feeding (TRF), known for its metabolic health benefits and alleviation of various chronic diseases without calorie restriction, was investigated for its potential protective effects against IRI-induced AKI. Male C57BL/6 mice underwent unilateral IRI, with their kidneys collected after two days. For two weeks before IRI induction, the TRF group had unlimited access to standard chow but within an 8-hour feeding window during the dark cycle. The study groups were Control, TRF, IRI, and TRF + IRI. In the TRF + IRI group, tubular damage scores significantly decreased compared to the IRI group. Furthermore, the TRF + IRI mice had lower levels of phosphorylated NF-κB and fewer F4/80-positive macrophages than the IRI group. Oxidative stress markers for lipids and proteins were also notably lower in the TRF + IRI group. Additionally, TUNEL-positive tubular cells and cleaved caspase-3 expression were reduced in the TRF + IRI group. Without calorie restriction, TRF mitigated renal damage by reducing inflammation, oxidative stress, and tubular apoptosis in renal IRI. This suggests that TRF could be a promising dietary strategy to prevent IRI-induced AKI.

Association between living alone and generalized anxiety disorder in Korean adults.

BACKGROUND: Globally, the rise in single-person households poses a potential risk to mental health, with generalized anxiety disorder (GAD) being a prominent concern. The proliferation of single-person households may exacerbate social isolation and foster loneliness and anxiety. Notably, research investigating the association between single-person households and GAD remains limited. Therefore, this study aimed to investigate the association between single-person households and GAD across sexes in Korea. METHODS: We utilized data from the Korea National Health and Nutrition Examination Survey conducted in 2021 and 2022, comprising a sample of 9936 participants aged 19 or older. The Generalized Anxiety Disorder Screening Tool (GAD-7) was employed to assess anxiety levels in adults. Multiple logistic regression analysis was conducted to investigate the correlation between single-person households and GAD. RESULTS: The reference variable used in the analysis was multi-person households (consisting of two or more individuals). The association between single-person households and GAD was statistically significant across sexes (male: odds ratio [OR]: 1.92, 95 % CI: 1.15-3.20; female: OR: 1.56, 95 % CI: 1.03-2.36). Participants in single-person households exhibited higher scores on the GAD-7 compared with those in multi-person households. Notably, marital status and education level displayed disparate effects based on sex, whereas physical activity demonstrated consistent effects irrespective of sex. LIMITATIONS: Given the use of cross-sectional data, only correlations could be established. CONCLUSION: The findings indicate an elevated risk of GAD in single-person households compared with multi-person households. Furthermore, promoting physical activity emerged as a potential strategy for mitigating GAD in single-person households.

Effect of patent complete revascularization on the akinetic myocardial segments.

OBJECTIVES: The aims of the study were (i) to examine the changes in echocardiographic parameters and (ii) to compare the fate of myocardial segments with akinesia and without akinesia on preoperative echocardiography after coronary artery bypass grafting. METHODS: One hundred one patients who underwent complete revascularization, who were assessed by preoperative, before discharge, postoperative 3- and 12-month echocardiographic examinations, and who showed all patent grafts at postoperative 1-year angiograms were included. Echocardiographic left ventricular ejection fraction was assessed, and a 16-segment model was adopted for regional analysis of the left ventricle. A total of 1616 segments were analysed based on a 6-point scale: 1 = normal (N = 1083), 2 = mild hypokinesia (N = 2), 3 = moderate hypokinesia (N = 74), 4 = severe hypokinesia (N = 150), 5 = akinesia without thinning (N = 259) and 6 = akinesia with thinning (N = 48). RESULTS: The serial left ventricular ejection fraction measured preoperatively, before discharge, at postoperative 3- and 12-months were 0.48 ± 0.14, 0.49 ± 0.12, 0.49 ± 0.10 and 0.54 ± 0.10, respectively. The left ventricular ejection fraction significantly increased over time during the postoperative 12 months (P < 0.001). Wall motion scores tended to decrease over time in both segment groups with akinesia and without akinesia (P < 0.001), and improvement of the wall motion was significantly higher in the segment group with akinesia than in the segment group without akinesia (P < 0.001). CONCLUSIONS: The left ventricular ejection fraction and regional wall motion improved over time during the postoperative 12 months, regardless of the presence of an akinetic segment. Complete revascularization including akinetic myocardium should be considered when performing coronary artery bypass grafting.

Multi-modal co-learning with attention mechanism for head and neck tumor segmentation on 18FDG PET-CT.

PURPOSE: Effective radiation therapy requires accurate segmentation of head and neck cancer, one of the most common types of cancer. With the advancement of deep learning, people have come up with various methods that use positron emission tomography-computed tomography to get complementary information. However, these approaches are computationally expensive because of the separation of feature extraction and fusion functions and do not make use of the high sensitivity of PET. We propose a new deep learning-based approach to alleviate these challenges. METHODS: We proposed a tumor region attention module that fully exploits the high sensitivity of PET and designed a network that learns the correlation between the PET and CT features using squeeze-and-excitation normalization (SE Norm) without separating the feature extraction and fusion functions. In addition, we introduce multi-scale context fusion, which exploits contextual information from different scales. RESULTS: The HECKTOR challenge 2021 dataset was used for training and testing. The proposed model outperformed the state-of-the-art models for medical image segmentation; in particular, the dice similarity coefficient increased by 8.78% compared to U-net. CONCLUSION: The proposed network segmented the complex shape of the tumor better than the state-of-the-art medical image segmentation methods, accurately distinguishing between tumor and non-tumor regions.