Novel alternative tools for metastatic pheochromocytomas/paragangliomas prediction

OBJECTIVE

The existing prediction models for metastasis in pheochromocytomas/paragangliomas (PPGLs) showed high heterogeneity in different centers. Therefore, this study aimed to establish new prediction models integrating multiple variables based on different algorithms.

DESIGN AND METHODS

Data of patients with PPGLs undergoing surgical resection at the Peking Union Medical College Hospital from 2007 to 2022 were collected retrospectively. Patients were randomly divided into the training and testing sets in a ratio of 7:3. Subsequently, decision trees, random forest, and logistic models were constructed for metastasis prediction with the training set and Cox models for metastasis-free survival (MFS) prediction with the total population. Additionally, Ki-67 index and tumor size were transformed into categorical variables for adjusting models. The testing set was used to assess the discrimination and calibration of models and the optimal models were visualized as nomograms. Clinical characteristics and MFS were compared between patients with and without risk factors.

RESULTS

A total of 198 patients with 59 cases of metastasis were included and classified into the training set (n = 138) and testing set (n = 60). Among all models, the logistic regression model showed the best discrimination for metastasis prediction with an AUC of 0.891 (95% CI, 0.793-0.990), integrating SDHB germline mutations [OR: 96.72 (95% CI, 16.61-940.79)], S-100 (-) [OR: 11.22 (95% CI, 3.04-58.51)], ATRX (-) [OR: 8.42 (95% CI, 2.73-29.24)] and Ki-67 ≥ 3% [OR: 7.98 (95% CI, 2.27-32.24)] evaluated through immunohistochemistry (IHC), and tumor size ≥ 5 cm [OR: 4.59 (95% CI, 1.34-19.13)]. The multivariate Cox model including the above risk factors also showed a high C-index of 0.860 (95% CI, 0.810-0.911) in predicting MFS after surgery. Furthermore, patients with the above risk factors showed a significantly poorer MFS (P ≤ 0.001).

CONCLUSIONS

Models established in this study provided alternative and reliable tools for clinicians to predict PPGLs patients' metastasis and MFS. More importantly, this study revealed for the first time that IHC of ATRX could act as an independent predictor of metastasis in PPGLs.

MicroRNA-encoded regulatory peptides modulate cadmium tolerance and accumulation in rice

MicroRNAs (miRNAs) are small noncoding RNAs that play a vital role in plant responses to abiotic and biotic stresses. Recently, it has been discovered that some primary miRNAs (pri-miRNAs) encode regulatory short peptides called miPEPs. However, the presence of miPEPs in rice, and their functions in response to abiotic stresses, particularly stress induced by heavy metals, remain poorly understood. Here, we identified a functional small peptide (miPEP156e) encoded by pri-miR156e that regulates the expression of miR156 and its target SPL genes, thereby affecting miR156-mediated cadmium (Cd) tolerance in rice. Overexpression of miPEP156e led to decreased uptake and accumulation of Cd and reactive oxygen species (ROS) levels in plants under Cd stress, resulting in improved rice Cd tolerance, as observed in miR156-overexpressing lines. Conversely, miPEP156e mutants displayed sensitivity to Cd stress due to the elevated accumulation of Cd and ROS. Transcriptome analysis further revealed that miPEP156e improved rice Cd tolerance by modulating Cd transporter genes and ROS scavenging genes. Our study provides insights into the regulatory mechanism of miPEP156e in rice response to Cd stress and demonstrates the potential of miPEPs as an effective tool for improving crop abiotic stress tolerance.

Targeted long-read sequencing for comprehensive detection of CYP21A2 mutations in patients with 21-hydroxylase deficiency

BACKGROUND

21-Hydroxylase deficiency (21-OHD) is caused by pathogenic CYP21A2 variations. CYP21A2 is arranged in tandem with its highly homologous pseudogene CYP21A1P; therefore, it is prone to mismatch and rearrangement, producing different types of complex variations. There were few reports on using only one method to detect different CYP21A2 variants simultaneously.

AIMS

Targeted long-read sequencing method was used to detect all types of CYP21A2 variants in a series of patients with 21-OHD.

METHODS

A total of 59 patients with 21-OHD were enrolled from Peking Union Medical College Hospital. Long-range locus-specific PCR and long-read sequencing (LRS) were performed to detect the pathogenic variants in CYP21A2.

RESULTS

Copy-number variants of CYP21A2 were found in 25.4% of patients, including 5.1% with 3 copies of CYP21A2, 16.9% with 1 copy of CYP21A2, and 3.4% with 0 copy of CYP21A2. The remaining 74.6% of patients had 2 copies of CYP21A2. Pathogenic variants were identified in all 121 alleles of 59 patients. Specifically, single-nucleotide variants and small insertions/deletions (< 50 bp) were detected in 79 alleles, of which conversed from CYP21A1P were detected in 63 alleles, and rare variants were found in the other 16 alleles. Large gene conversions (> 50 bp) from pseudogene were detected in 10 alleles, and different chimeric genes (CYP21A1P/CYP21A2 or TNXA/TNXB) formed by large deletions were detected in 32 alleles. Of all variants, p.I173N was the most common variant (19.0%).

CONCLUSIONS

Our study demonstrated that targeted long-read sequencing is a comprehensive method for detecting CYP21A2 variations, which is helpful for genetic diagnosis in 21-OHD patients.

Multi-center Dose Prediction Using Attention-aware Deep learning Algorithm Based on Transformers for Cervical Cancer Radiotherapy

AIMS

Accurate dose delivery is crucial for cervical cancer volumetric modulated arc therapy (VMAT). We aimed to develop a robust deep-learning (DL) algorithm for fast and accurate dose prediction of cervical cancer VMAT in multicenter datasets and then explore the feasibility of the DL algorithm to endometrial cancer VMAT with different prescriptions.

MATERIALS AND METHODS

We proposed the AtTranNet algorithm for three-dimensional dose prediction. A total of 367 cervical patients were enrolled in this study. Three hundred twenty-two cervical patients from 3 centers were randomly divided into 70%, 10%, and 20% as training, validation, and testing sets, respectively. Forty-five cervical patients from another center were selected for external testing. Moreover, 70 patients of endometrial cancer with different prescriptions were further selected to test the model. Prediction precision was evaluated by dosimetric difference, dose map, and dose-volume histogram metrics.

RESULTS

The prediction results were all clinically acceptable. The mean absolute error within the body in internal testing was 0.66 ± 0.63%. The maximum |δD| for planning target volume was observed in D98, which is 1.24 ± 2.73 Gy. The maximum |δD| for organs at risk was observed in Dmean of bladder, which is 4.79 ± 3.14 Gy. The maximum |δV| were observed in V40 of pelvic bones, which is 4.77 ± 4.48%.

CONCLUSION

AtTranNet showed the feasibility and reasonable accuracy in the dose prediction for cervical cancer in multiple centers. The model can also be generalized for endometrial cancer with different prescriptions without any transfer learning.

[Clinicopathological and molecular characteristics of esophageal carcinoma with ductal differentiation: analysis of 17 cases]

Objective: To investigate the clinicopathological features and molecular genetic characteristics of esophageal carcinoma with ductal differentiation, and to summarize the experiences in its diagnosis and treatment. Methods: A total of 17 cases of esophageal carcinoma with ductal differentiation diagnosed in Ningbo Clinical Pathological Diagnosis Center, Ningbo, China from June 2011 to December 2022 were collected. The clinical information and pathological diagnosis was reviewed. The tumor histological features and immunohistochemical results were analyzed. The next-generation sequencing was performed to detect and analyze the gene mutations in tumor samples. Results: The 17 patients included in this study were 54-77 years old, with a median age of 66 years. There were 16 males and 1 female. Among them, 9 cases were mainly carcinoma with ductal differentiation. The squamous epithelium on the tumor's surface was accompanied by high-grade intraepithelial neoplasia. The tumor and atypical squamous epithelium were transitional, and the focus was accompanied by various proportions of squamous cell carcinoma component (less than 10%). The other 8 cases were mostly squamous cell carcinoma, basaloid squamous cell carcinoma or sarcomatoid carcinoma with various degrees of tumor specific differentiation and focal area of carcinoma with ductal differentiation (less than 10%). The tumor cells in the area with ductal differentiation were mainly arranged in small tubes, while the tubes showed a double-layer structure, including the inner cells and outer cells of the lumen. Immunohistochemical results showed that the outer cells of the tumorous tubules expressed p63, p40, CK5/6 and CK34βE12, while the inner cells expressed CK7. Compared with esophageal squamous cell carcinoma reported in the literature, the frequency of gene mutations such as MYC (P=0.002), TP63 (P=0.002), CDKN1C (P=0.002) and NFE2L2 (P=0.045) was significantly lower in this group of cases. At the signaling pathway level, the mutation frequency of NOTCH signaling pathway (P=0.041) was significantly higher, while the mutation frequencies of NRF2 pathway (P=0.013) and PI3K pathway (P=0.009) were significantly lower than that of esophageal squamous cell carcinoma. Conclusion: Esophageal carcinoma with ductal differentiation is a type of esophageal carcinoma with unique morphology, and its molecular changes are also significantly different from those of conventional esophageal squamous cell carcinoma.

Gibberellin-Mediated Sensitivity of Rice Roots to Aluminum Stress

Aluminum toxicity poses a significant constraint on crop production in acidic soils. While phytohormones are recognized for their pivotal role in mediating plant responses to aluminum stress, the specific involvement of gibberellin (GA) in regulating aluminum tolerance remains unexplored. In this study, we demonstrate that external GA exacerbates the inhibitory impact of aluminum stress on root growth of rice seedlings, concurrently promoting reactive oxygen species (ROS) accumulation. Furthermore, rice plants overexpressing the GA synthesis gene SD1 exhibit enhanced sensitivity to aluminum stress. In contrast, the slr1 gain-of-function mutant, characterized by impeded GA signaling, displays enhanced tolerance to aluminum stress, suggesting the negative regulatory role of GA in rice resistance to aluminum-induced toxicity. We also reveal that GA application suppresses the expression of crucial aluminum tolerance genes in rice, including Al resistance transcription factor 1 (ART1), Nramp aluminum transporter 1 (OsNramp4), and Sensitive to Aluminum 1 (SAL1). Conversely, the slr1 mutant exhibits up-regulated expression of these genes compared to the wild type. In summary, our results shed light on the inhibitory effect of GA in rice resistance to aluminum stress, contributing to a theoretical foundation for unraveling the intricate mechanisms of plant hormones in regulating aluminum tolerance.

Non-destructive identification of Pseudostellaria heterophylla from different geographical origins by Vis/NIR and SWIR hyperspectral imaging techniques

The composition of Pseudostellaria heterophylla (Tai-Zi-Shen, TZS) is greatly influenced by the growing area of the plants, making it significant to distinguish the origins of TZS. However, traditional methods for TZS origin identification are time-consuming, laborious, and destructive. To address this, two or three TZS accessions were selected from four different regions of China, with each of these resources including distinct quality grades of TZS samples. The visible near-infrared (Vis/NIR) and short-wave infrared (SWIR) hyperspectral information from these samples were then collected. Fast and high-precision methods to identify the origins of TZS were developed by combining various preprocessing algorithms, feature band extraction algorithms (CARS and SPA), traditional two-stage machine learning classifiers (PLS-DA, SVM, and RF), and an end-to-end deep learning classifier (DCNN). Specifically, SWIR hyperspectral information outperformed Vis/NIR hyperspectral information in detecting geographic origins of TZS. The SPA algorithm proved particularly effective in extracting SWIR information that was highly correlated with the origins of TZS. The corresponding FD-SPA-SVM model reduced the number of bands by 77.2% and improved the model accuracy from 97.6% to 98.1% compared to the full-band FD-SVM model. Overall, two sets of fast and high-precision models, SWIR-FD-SPA-SVM and SWIR-FD-DCNN, were established, achieving accuracies of 98.1% and 98.7% respectively. This work provides a potentially efficient alternative for rapidly detecting the origins of TZS during actual production.

Demonstrating Agreement between Radio and Fluorescence Measurements of the Depth of Maximum of Extensive Air Showers at the Pierre Auger Observatory

We show, for the first time, radio measurements of the depth of shower maximum (X_{max}) of air showers induced by cosmic rays that are compared to measurements of the established fluorescence method at the same location. Using measurements at the Pierre Auger Observatory we show full compatibility between our radio and the previously published fluorescence dataset, and between a subset of air showers observed simultaneously with both radio and fluorescence techniques, a measurement setup unique to the Pierre Auger Observatory. Furthermore, we show radio X_{max} resolution as a function of energy and demonstrate the ability to make competitive high-resolution X_{max} measurements with even a sparse radio array. With this, we show that the radio technique is capable of cosmic-ray mass composition studies, both at Auger and at other experiments.

Activating two-dimensional semiconductors for photocatalysis: a cross-dimensional strategy

The emerging two-dimensional (2D) semiconductors substantially extend materials bases for versatile applications such as semiconductor photocatalysis demanding semiconductive matrices and large surface areas. The dimensionality, while endowing 2D semiconductors the unique properties to host photocatalytic functionality of pollutant removal and hydrogen evolution, hurdles the activation paths to form heterogenous photocatalysts where the photochemical processes are normally superior over these on the mono-compositional counterparts. In this perspective, we present a cross-dimensional strategy to employ thenD (n= 0-2) clusters or nanomaterials as activation partners to boost the photocatalytic activities of the 2D semiconductors. The formation principles of heterogenous photocatalysts are illustrated specifically for the 2D matrices, followed by selection criteria of them among the vast 2D database. The computer investigations are illustrated in the density functional theory route and machine learning benefitted from the vast samples in the 2D library. Synthetic realizations and characterizations of the 2D heterogenous systems are introduced with an emphasis on chemical methods and advanced techniques to understand materials and mechanistic studies. The perspective outlooks cross-dimensional activation strategies of the 2D materials for other applications such as CO2removal, and materials matrices in other dimensions which may inspire incoming research within these fields.

[Progress in pathophysiology research and update on diagnosis and treatment strategies for fecal incontinence]

The traditional barrier theory believes that fecal incontinence is related to an imbalance of the recto-anal barrier and the characteristics of stool. However, in clinical practice this theory proves unable to explain all types of fecal incontinence. In recent years, research on the mechanisms related to fecal incontinence has shifted to a new integrative concept with the rectum and anus as functional units, and the central-peripheral nervous system and internal and external anal sphincters as a control loop. The diagnosis and treatment strategy of fecal incontinence, which is replaced by sacral neuromodulation, is undergoing a quiet change. With the progressively aging population in China, the need to improve the diagnosis and treatment of fecal incontinence has become increasingly urgent. This article explores the trends in diagnosis and treatment and mechanism research from the perspective of recent advances in pathophysiological research and updated diagnosis and treatment methods for fecal incontinence.

[A follow-up study on the pain changes trend and effects in patients diagnosed with herpes zoster in Beijing City]

Objective: To understand the changes in pain and its effects in patients with the diagnosis of herpes zoster. Methods: A total of 3 487 patients diagnosed with herpes zoster (HZ) for the first time at the outpatient department of Miyun District Hospital from January 1, 2017, to December 31, 2019, were included in the study. The information of patients was registered and issued with a record card. Patients were required to record the time of pain and rash by themselves. Telephone follow-up was conducted at 21, 90, 180 and 365 days after the onset of rashes, including hospitalization, location of rash and pain, and the time of start and end. The impact of pain on life was evaluated by the Zoster Brief Pain Inventory (ZBPI). Results: The age of 2 999 HZ patients included in the analysis were (53±16) years old, including 1 377 (45.91%) males and 1 903 (63.45%) patients aged 50 years and older. After 21 days of rash, mild, moderate and severe pain accounted for 20.87% (626 cases), 37.98% (1 139 cases) and 33.81% (1 014 cases), respectively. Only 5.07% (152 cases) had no pain or discomfort, and 2.27% (68 cases) had no pain but discomfort. Most of the pain sites were consistent with the rash sites. The chest and back and waist and abdomen were the most common, accounting for 35.58% (1 067 cases) and 29.18% (875 cases), respectively, followed by the limbs and face and neck, accounting for 16.74% (502 cases) and 16.40% (492 cases), respectively. The M (Q1, Q3) of pain days in the HZ patients was 14 (8, 20) days, and the incidence of post-herpetic neuralgia (PHN) was 6.63% (171/2 580) (excluding 419 patients who refused to visit or lost to visit on 90 days after the onset of rash). The pain score of HZ patients within 21 days after the rash was (5.19±2.73) points, and the pain score of PHN patients was (7.61±2.13) points, which was significantly higher than that of non-PHN patients [(5.04±2.69) points] (P<0.001). Daily activities, emotions, walking ability, work, social interaction, sleep and recreation were affected for 21 days after the rash in HZ patients, ranging from 60.79% to 83.83%, with sleep being the most affected (83.83%). The impact scores of pain and life dimensions in PHN patients ranged from 4.59 to 7.61 points on the ZBPI scale, which were higher than those in non-PHN patients (2.49-5.04) (t values ranged from 8.86 to 11.67, all P values <0.001). Conclusion: The proportion of pain in HZ patients after the diagnosis is high, and the pain is more obvious in patients with PHN and HZ patients aged 50 and older, which has a greater impact on their daily lives.

Integration of transcriptome and metabolome analyses reveals the role of OsSPL10 in rice defense against brown planthopper

KEY MESSAGE

OsSPL10 is a negative regulator of rice defense against BPH, knockout of OsSPL10 enhances BPH resistance through upregulation of defense-related genes and accumulation of secondary metabolites. Rice (Oryza sativa L.), one of the most important staple foods worldwide, is frequently attacked by various herbivores, including brown planthopper (BPH, Nilaparvata lugens). BPH is a typical monophagous, phloem-sucking herbivore that has been a substantial threat to rice production and global food security. Understanding the regulatory mechanism of defense responses to BPH is essential for improving BPH resistance in rice. In this study, a SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE 10 (OsSPL10) transcription factor was found to play a negative role in the defenses of rice against BPH. To gain insights into the molecular and biochemical mechanisms of OsSPL10, we performed combined analyses of transcriptome and metabolome, and revealed that knockout of OsSPL10 gene improved rice resistance against BPH by enhancing the direct and indirect defenses. Genes involved in plant hormone signal transduction, MAPK signaling pathway, phenylpropanoid biosynthesis, and plant-pathogen interaction pathway were significantly upregulated in spl10 mutant. Moreover, spl10 mutant exhibited increased accumulation of defense-related secondary metabolites in the phenylpropanoid and terpenoid pathways. Our findings reveal a novel role for OsSPL10 gene in regulating the rice defense responses, which can be used as a potential target for genetic improvement of BPH resistance in rice.

Global analysis of seed transcriptomes reveals a novel PLATZ regulator for seed size and weight control in soybean

Seed size and weight are important factors that influence soybean yield. Combining the weighted gene co-expression network analysis (WGCNA) of 45 soybean accessions and gene dynamic changes in seeds at seven developmental stages, we identified candidate genes that may control the seed size/weight. Among these, a PLATZ-type regulator overlapping with 10 seed weight QTLs was further investigated. This zinc-finger transcriptional regulator, named as GmPLATZ, is required for the promotion of seed size and weight in soybean. The GmPLATZ may exert its functions through direct binding to the promoters and activation of the expression of cyclin genes and GmGA20OX for cell proliferation. Overexpression of the GmGA20OX enhanced seed size/weight in soybean. We further found that the GmPLATZ binds to a 32-bp sequence containing a core palindromic element AATGCGCATT. Spacing of the flanking sequences beyond the core element facilitated GmPLATZ binding. An elite haplotype Hap3 was also identified to have higher promoter activity and correlated with higher gene expression and higher seed weight. Orthologues of the GmPLATZ from rice and Arabidopsis play similar roles in seeds. Our study reveals a novel module of GmPLATZ-GmGA20OX/cyclins in regulating seed size and weight and provides valuable targets for breeding of crops with desirable agronomic traits.

Polyglucosan body density in the aged mouse hippocampus is controlled by a novel modifier locus on chromosome 1

Aging can be associated with the accumulation of hypobranched glycogen molecules (polyglucosan bodies, PGBs), particularly in astrocytes of the hippocampus. While PGBs have a detrimental effect on cognition in diseases such as adult polyglucosan body disease and Lafora disease, the underlying mechanism and clinical relevance of age-related PGB accumulation remains unknown. Here, we have investigated the genetic basis and functional impact of age-related PGB accumulation in 32 fully sequenced BXD-type strains of mice which exhibit a 400-fold variation in PGB burden in 16-18 month old females. We mapped a major locus controlling PGB density in the hippocampus to chromosome 1 at 72-75 Mb (linkage of 4.9 -logP), which we defined as the Pgb1 locus. To identify potentially causal gene variants within Pgb1, we generated extensive hippocampal transcriptome datasets and identified two strong candidate genes for which mRNA correlates with PGB density-Smarcal1 and Usp37. In addition, both Smarcal1 and Usp37 contain non-synonymous allele variations likely to impact protein function. A phenome-wide association analysis highlighted a trans-regulatory effect of the Pgb1 locus on expression of Hp1bp3, a gene known to play a role in age-related changes in learning and memory. To investigate the potential impact of PGBs on cognition, we performed conditioned fear memory testing on strains displaying varying degrees of PGB burden, and a phenome-wide association scan of ~12,000 traits. Importantly, we did not find any evidence suggesting a negative impact of PGB burden on cognitive capacity. Taken together, we have identified a major modifier locus controlling PGB burden in the hippocampus and shed light on the genetic architecture and clinical relevance of this strikingly heterogeneous hippocampal phenotype.

Aorta Dilatation in Unrepaired Tetralogy of Fallot

Background Aortic root dilation is an increasingly recognized feature in repaired tetralogy of Fallot (TOF) patients. However, the dilation at the aortic root and ascending aorta in unrepaired TOF is rarely studied. This study aims to confirm whether aortic dilation is a common feature in unrepaired TOF and investigate the factors attributed to aortic dilation. Methodology Patients with an echocardiographic diagnosis of TOF undergoing computed tomography angiography were retrospectively studied. Diameters and z scores of aortic annular (Ao1), aortic sinotubular junction (Ao2), ascending aorta (Ao3), and distal transverse aortic arch (Ao4) were measured. Preoperative body surface area (BSA), hemoglobin (Hb), hematocrit (HCT), arterial oxygen saturation (SaO2), and platelet (PLT) count were recorded. Results A total of 101 TOF patients aged 6.8 ± 9.5 years were included in this study, whose mean BSA (m2), Hb (g/L), HCT, SaO2 (%), and PLT (109/L) were 0.7 ± 0.4, 162.1 ± 3.8, 0.5 ± 0.1, 85.1 ± 9.3, and 238.1 ± 101.1, respectively. The mean z score of Ao1, Ao2, Ao3, and Ao4 were 10.3 ± 3.5, 4.7 ± 2.9, 4.0 ± 2.7, and 4.1 ± 2.4, respectively. Age and BSA were positively correlated with the z scores of Ao1 and Ao2. Preoperative Hb and HCT were positively correlated with the z scores of Ao1, Ao2, Ao3, and Ao4. Preoperative SaO2 and PLT were negatively correlated with the z scores of Ao1, Ao2, Ao3, and Ao4. Conclusions Aortic dilation is common in unrepaired TOF patients. The dilation of different levels of the aorta was correlated with age, BSA, preoperative Hb, HCT, SaO2, and PLT.

[Mediating effects of obesity and metabolic factors in hyperuricemia and prehypertension]

Objective: To assess the mediating effects of obesity and metabolic factors in the relationship between hyperuricemia (HUA) and prehypertension. Methods: A total of 9 399 individuals were selected using a multistage stratified whole-group random sampling method from 90 villages (neighborhood committees) in 30 towns (streets) of 5 districts (counties) in Fuzhou. A total of 4 754 study subjects were included. A linear regression model was used to analyze the association of HUA with obesity and metabolic factors. Single-factor and multi-factor logistic regression models were used to analyze the association of HUA, obesity, and metabolic factors with prehypertension. Mediating effects models were used to analyze the mediating effects of obesity and metabolic factors on the association between HUA and prehypertension. Results: After adjusting for confounders, the association between HUA and cholesterol, triglycerides, HDL-C, LDL-C, BMI, waist circumference, creatinine, and urea nitrogen were significantly correlated (P<0.001). HUA, waist circumference, BMI, and triglycerides were significantly associated with prehypertension (P<0.001). Waist circumference, BMI, and triglycerides mediated the relationship between HUA and prehypertension, with OR (95%CI) of 1.018 (1.007-1.027), 1.010 (1.002-1.018), and 1.010 (1.003-1.017) (P<0.001), with mediating proportions of 7.76%, 4.31%, and 4.31% respectively. No mediating effect of cholesterol, HDL-C, LDL-C, creatinine, and urea nitrogen was found on the relationship (P>0.05). Conclusions: Waist circumference, BMI, and triglycerides all had mediating effects in the association between HUA and prehypertension. For the general population, weight control, waist circumference, and a high-fat diet should be used to reduce the occurrence of prehypertension.

Deep Learning-Based Multi-Modality Segmentation of Primary Gross Tumor Volume in CT and MRI for Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

The delineation of primary gross tumor volume (GTV) of nasopharyngeal carcinoma (NPC) is an essential step for radiotherapy planning. In clinical practice, radiation oncologists manually delineate the GTV in planning CT with the help of diagnostic MRI. This is because NPC tumors are closely adjacent to many important anatomic structures, and CT and MRI provide complementary strength to accurately determine the tumor extension boundary. Manual delineation is time-consuming with the potential registration errors between MRI and CT decreasing the delineation accuracy. In this study, we propose a fully automated GTV segmentation method based on CT and MRI by first aligning MRI to CT, and then, segmenting the GTV using a multi-modality deep learning model.

MATERIALS/METHODS

We collected 104 nasopharyngeal carcinoma patients with both planning CT and diagnostic MRI scans (T1 & T2 phases). An experienced radiation oncologists manually delineated the GTV, which was further examined by another senior radiation oncologist. Then, a coarse to fine cross-modality registration from MRI to CT was conducted as follows: (1) A rigid transformation was performed on MRI to roughly align MRI to CT with similar anatomic position. (2) Then, the region of interest (RoI) on both CT and rigid-transformed MRI were cropped. (3) A leading cross-modality deformable registration algorithm, named DEEDS, was applied on the cropped MRI and CT RoIs to find an accurate local alignment. Next, using CT and registered MRI as the combined input, a multi-modality deep segmentation network based on nnUNet was trained to generate the GTV prediction. 20% patients were randomly selected as the unseen testing set to quantitatively evaluate the performance.

RESULTS

The quantitative NPC GTV segmentation performance is summarized in Table 1. The deep segmentation model using CT alone achieved reasonable high performance with 76.6% Dice score and 1.34mm average surface distance (ASD). When both CT and registered MRI were used, the segmentation model further improved the performance by 0.9% Dice score increase and 11% relative ASD error reduction, demonstrating the complementary strength of CT and MRI in determining NPC GTV. Notably, the achieved 77.5% Dice score and 1.19mm ASD by the multimodality model is among the top performing results reported in recent automatic NPC GTV segmentation using either CT or MRI modality.

CONCLUSION

We developed a fully automated multi-modal deep-learning model for NPC GTV segmentation. The developed model can segment the NPC GTV in high accuracy. With further optimization and validation, this automated model has potential to standardize the NPC GTV segmentation and significantly decrease the workload of radiation oncologists in clinical practice.

A Novel Strategy to Enhance Radiotherapy Efficacy: Results from the Prospective Phase I Clinical Trial of MR-Guided Focused Ultrasound-Stimulated Microbubbles (MRgFUS+MB) Treatment for Breast Cancer

PURPOSE/OBJECTIVE(S)

Preclinical in vitro and in vivo studies have demonstrated that tumor cell death can be enhanced 10- to 40-fold when radiotherapy (RT) is combined with focused-ultrasound (FUS)-stimulated microbubbles (MB) treatment. MBs are gas microspheres used as intravascular contrast agents. The acoustic exposure of MBs within the target volume causes bubbles cavitation that induces perturbation of tumor vasculature. This activates apoptotic pathways responsible for the ablative effect of stereotactic body radiotherapy, which would otherwise require high-dose radiotherapy (>8-10 Gy/fraction) to be activated. Subsequent irradiation of an MB-sensitized tumor causes increased anoxic tumor killing, which occurs in addition to canonical RT-induced DNA damage. Given the compelling results of preclinical data, we conducted a phase I clinical trial of magnetic resonance (MR)-guided FUS-stimulated MBs (MRgFUS+MB) treatment for breast cancer patients (pts). We report the safety and efficacy results of this new radio enhancement treatment.

MATERIALS/METHODS

This is a single-center, single-arm, investigator-initiated phase 1 clinical trial (NCT04431674). We included pts with stage I-IV breast cancer with tumor in situ for whom breast or chest wall RT was deemed adequate by a multidisciplinary team. Pts were excluded if they had contraindications for contrast-enhanced MR or MB administration. Pts underwent 2-3 MRgFUS+MB treatments throughout the RT course. We used an MR-coupled FUS-device operating at 500 KHz and 540 kPa peak negative pressure to deliver the treatment. The FUS sonicated intravenously administrated MB within the MR-guided target volume. Pts were monitored for 30-min post-procedure and subsequently treated with RT. The primary outcome was acute toxicity per Common Terminology for Adverse Events V5.0. Secondary outcomes were radiological response at 3 months and local control (LC) at 1 year. Kaplan-Meier method was used to estimate local control. All pts signed a written consent form before study participation.

RESULTS

We enrolled 18 females with 20 primary breast cancer treated with MRgFUS+MB therapy. The median age was 60 years (range, 44-90). The molecular subtypes consisted of basal-like (n = 3/20), luminal (n = 11/20), and HER2-enriched (n = 6/20). The prescribed dose was 20 Gy/5 fractions (n = 8/20), 30-35 Gy/5 fractions (n = 7/20), 30-40 Gy/10 fractions (n = 3/20), and 66 Gy/33 fractions (n = 2/20). The median follow-up was 9 months (range, 0.3-29). All pts completed the planned MRgFUS+MB treatments. The only MRgFUS+MB treatment-related toxicity consisted of Grade 1 allergic reaction (mild cough) 30 minutes after the last MB injection. All worst acute toxicities were radiation dermatitis (Grade 3 = 2/20, Grade 2 = 2/20, Grade 1 = 14/20). At 3 months, 75% had partial (n = 6/20) or complete (n = 9/20) response, with a single progression. The LC rate at 1 year was 86%.

CONCLUSION

MRgFUS+MB was a safe and efficient treatment that provided durable responses.

Deep Learning for Automatic Prediction of Lymph Node Station Metastasis in Esophageal Cancer Patients from Contrast-Enhanced CT

PURPOSE/OBJECTIVE(S)

The diagnosis of lymph node (LN) metastasis in computed tomography (CT) is an essential yet challenging task in esophageal cancer staging and treatment planning. Although criteria (e.g., RECIST, morphological/texture features) are proposed to predict LN metastasis, the diagnostic accuracy remains low with sensitivity <50% and specificity <75%, as reported in previous studies. Deep learning (DL) has the potential to address this issue by learning from large-scale labeled data. However, due to the practical surgery procedure in lymph node dissection, it is difficult to pair the metastasis of individual LN reported in the pathology report to the LN instance found in the CT image. Hence, in this study, we first use pathology reports to determine the LNS metastasis, then develop a multiple instance deep learning (MIDL) model to predict lymph node station (LNS) metastasis.

MATERIALS/METHODS

We collected 1200 esophageal cancer patients with preoperative contrast-enhanced CT before surgery. A recently developed automatic mediastinal LNS segmentation model was first applied to segment LNS of 1 to 8 based on the IASLC protocol. For each LNS, the local CT region of interest (ROI) was cropped to generate a station-wise CT patch, where the LNS was labeled as metastatic if at least one metastatic LN was indicated in the pathology report. Using the station-wise CT patch and LNS label, we train a 3D MIDL model, MobileNetV3, to predict LNS metastasis. To better provide the LN position priors in MIDL, LN instances (with a short axis >4mm) were also segmented using an automatic LN detection algorithm and were added to the MIDL model as an auxiliary input. Five-fold cross-validation was conducted to evaluate the MIDL performance.

RESULTS

The MIDL model's performance is summarized in Table 1. The MIDL model incorporating an additional LN instance mask demonstrated a superior overall AUC of 0.7539, surpassing the model without the LN mask input by 2.93%. The specificity was evaluated at a threshold resulting in a recall of 0.7, and the best model outperformed the CT input model in terms of specificity by 2.11%. This highlights the value of including the LN position prior to the MIDL model. Notably, when a threshold was set to result in a specificity of 75%, the best MIDL model demonstrated a significantly higher recall compared to the previously reported clinical diagnostic recall (39.7% vs. 63.21%).

CONCLUSION

We developed a MIDL classification model to predict LNS metastasis using CT scans of 1200 patients. Our findings suggest that the MIDL model can substantially improve LNS metastasis prediction and has the potential to play an essential role in cancer staging, treatment planning, and prognostic analysis.

Anatomy-Guided Deep Learning Model for Accurate and Robust Gross Tumor Volume Segmentation in Lung Cancer Radiation Therapy

PURPOSE/OBJECTIVE(S)

In lung cancer radiation therapy, clinicians must outline the gross tumor volume (GTV) precisely on the planning computed tomography (pCT) for accurate radiation dose delivery. However, due to the limited contrast between tumor and normal tissues in lung parenchyma, accurate delineation of tumor boundaries is difficult leading to large inter-observer variation. In this study, we develop an anatomy-guided lung GTV deep segmentation model using a training cohort of multi-center datasets. The quantitative segmentation performance is evaluated on an independent dataset, where the inter-observer delineation variation is also assessed.

MATERIALS/METHODS

We collected and curated four publicly available lung datasets with GTV annotations (Lung-PET-CT-Dx, LIDC-IDRI, NSCLC-Radiogenomics and RIDER-CT) for deep learning model development. A total of 871 CT scans of patients, who were diagnosed with T1-T4 NSCLC, were available for training after data curation. The GTV annotations of primary tumor were examined and edited by two experienced radiation oncologists following the RTOG 1106 protocol. An anatomy-guided deep learning model was proposed, which consisted two deep networks. The first deep network used CT scan as input and segmented 4 anatomic organs (airway, heart, pulmonary artery and pulmonary vein), while the second deep network took both CT scan and these pre-segmented 4 organs as input and segmented the lung GTV. With the help of anatomic priors from 4 pre-segmented organs, the second deep network could more easily locate the GTV. We used nnUNet as the deep segmentation network. For evaluation, we used NSCLC-Radiomics as the testing dataset, which contains 20 CT scans each annotated by 5 radiation oncologists. The auto-segmented GTV were compared against each of the manual GTV reference. Inter-observer variation was also assessed using the 5 manual GTV references.

RESULTS

The proposed anatomic-guided lung GTV segmentation model achieved a mean Dice score of 82.4% and 95% Hausdorff distance (HD95) of 6.9mm when averaged cross 20 patients and 5 GTV references (Table 1), which outperformed the basic deep GTV segmentation model by markedly reducing 19.4% HD95 error. The performance of proposed model was also comparable to the inter-observer variation (Dice score: 82.4% vs. 81.9%, HD95 6.9 vs. 6.4mm), indicating that our model had similar reproducibility as human observers.

CONCLUSION

We developed and tested an anatomy-guided deep learning model for segmenting GTV in NSCLC patients. The model achieves high quantitative segmentation performance, which is comparable to the human observer variation. It can be potentially used in radiotherapy practice to improve GTV delineation consistency and reduce workloads of radiation oncologists.

A Meta-analysis Assessing the Efficacy of Balloon Pulmonary Angioplasty in Resolving Chronic Thromboembolic Pulmonary Hypertension

Background and Purpose

Chronic thromboembolic pulmonary hypertension (CTEPH) is the fourth most common form of pulmonary hypertension (PH), representing a pre-capillary manifestation of the disorder. This meta-analysis aims to evaluate the role of balloon pulmonary angioplasty (BPA) in the treatment of CTEPH.

Methods

Our investigation was conducted using PubMed, Embase, Cochrane Library, and Web of Science platforms.

Results

This meta-analysis includes the analysis of seven studies. BPA demonstrated a significant reduction in pulmonary arterial pressure in CTEPH patients (Mean difference (MD) = -9.80, 95% CI: -1.10 to -8.59, P < .00001). BPA also resulted in a decrease in pulmonary vascular resistance in CTEPH patients (MD = -4.70, 95% CI: -7.17 to -2.22, P = .0002). Moreover, BPA was associated with improved 6-minute walk distance of CTEPH patients (MD = 43.86, 95% CI: 26.19 to 61.53, P < .00001). Additionally, BPA led to a reduction in NT-proBNP levels in CTEPH patients (MD = -3.46, 95% CI: -10.63 to 3.71, p-value = 0.34). BPA also resulted in an improvement in the WHO functional class of CTEPH patients, with an increase in class I-II (MD = 0.28, 95% CI: 0.22 to 0.35, P < .00001) and a decrease in class III-IV (MD = 0.16, 95% CI: 0.10 to 0.26, P < .00001).

Conclusion

These findings support the effectiveness of BPA as an alternative treatment option for CTEPH patients, leading to improvements in prognostic factors such as hemodynamics, functional ability, and biomarkers. BPA may offer enhanced therapeutic benefits and potentially serve as an alternative treatment for select CTEPH patients.

MRI-based brain age prediction model for children under 3 years old using deep residual network

Early identification and intervention of abnormal brain development individual subjects are of great significance, especially during the earliest and most active stage of brain development in children aged under 3. Neuroimage-based brain's biological age has been associated with health, ability, and remaining life. However, the existing brain age prediction models based on neuroimage are predominantly adult-oriented. Here, we collected 658 T1-weighted MRI scans from 0 to 3 years old healthy controls and developed an accurate brain age prediction model for young children using deep learning techniques with high accuracy in capturing age-related changes. The performance of the deep learning-based model is comparable to that of the SVR-based model, showcasing remarkable precision and yielding a noteworthy correlation of 91% between the predicted brain age and the chronological age. Our results demonstrate the accuracy of convolutional neural network (CNN) brain-predicted age using raw T1-weighted MRI data with minimum preprocessing necessary. We also applied our model to children with low birth weight, premature delivery history, autism, and ADHD, and discovered that the brain age was delayed in children with extremely low birth weight (less than 1000 g) while ADHD may cause accelerated aging of the brain. Our child-specific brain age prediction model can be a valuable quantitative tool to detect abnormal brain development and can be helpful in the early identification and intervention of age-related brain disorders.

A multicenter study on two-stage transfer learning model for duct-dependent CHDs screening in fetal echocardiography

Duct-dependent congenital heart diseases (CHDs) are a serious form of CHD with a low detection rate, especially in underdeveloped countries and areas. Although existing studies have developed models for fetal heart structure identification, there is a lack of comprehensive evaluation of the long axis of the aorta. In this study, a total of 6698 images and 48 videos are collected to develop and test a two-stage deep transfer learning model named DDCHD-DenseNet for screening critical duct-dependent CHDs. The model achieves a sensitivity of 0.973, 0.843, 0.769, and 0.759, and a specificity of 0.985, 0.967, 0.956, and 0.759, respectively, on the four multicenter test sets. It is expected to be employed as a potential automatic screening tool for hierarchical care and computer-aided diagnosis. Our two-stage strategy effectively improves the robustness of the model and can be extended to screen for other fetal heart development defects.

GmJAZ3 interacts with GmRR18a and GmMYC2a to regulate seed traits in soybean

Seed weight is usually associated with seed size and is one of the important agronomic traits that determine yield. Understanding of seed weight control is limited, especially in soybean plants. Here we show that Glycine max JASMONATE-ZIM DOMAIN 3 (GmJAZ3), a gene identified through gene co-expression network analysis, regulates seed-related traits in soybean. Overexpression of GmJAZ3 promotes seed size/weight and other organ sizes in stable transgenic soybean plants likely by increasing cell proliferation. GmJAZ3 interacted with both G. max RESPONSE REGULATOR 18a (GmRR18a) and GmMYC2a to inhibit their transcriptional activation of cytokinin oxidase gene G. max CYTOKININ OXIDASE 3-4 (GmCKX3-4), which usually affects seed traits. Meanwhile, the GmRR18a binds to the promoter of GmMYC2a and activates GmMYC2a gene expression. In GmJAZ3-overexpressing soybean seeds, the protein contents were increased while the fatty acid contents were reduced compared to those in the control seeds, indicating that the GmJAZ3 affects seed size/weight and compositions. Natural variation in JAZ3 promoter region was further analyzed and Hap3 promoter correlates with higher promoter activity, higher gene expression and higher seed weight. The Hap3 promoter may be selected and fixed during soybean domestication. JAZ3 orthologs from other plants/crops may also control seed size and weight. Taken together, our study reveals a novel molecular module GmJAZ3-GmRR18a/GmMYC2a-GmCKXs for seed size and weight control, providing promising targets during soybean molecular breeding for better seed traits.

An Innovative Three-Stage Model for Prenatal Genetic Disorder Detection Based on Region-of-Interest in Fetal Ultrasound

A global survey has revealed that genetic syndromes affect approximately 8% of the population, but most genetic diagnoses are typically made after birth. Facial deformities are commonly associated with chromosomal disorders. Prenatal diagnosis through ultrasound imaging is vital for identifying abnormal fetal facial features. However, this approach faces challenges such as inconsistent diagnostic criteria and limited coverage. To address this gap, we have developed FGDS, a three-stage model that utilizes fetal ultrasound images to detect genetic disorders. Our model was trained on a dataset of 2554 images. Specifically, FGDS employs object detection technology to extract key regions and integrates disease information from each region through ensemble learning. Experimental results demonstrate that FGDS accurately recognizes the anatomical structure of the fetal face, achieving an average precision of 0.988 across all classes. In the internal test set, FGDS achieves a sensitivity of 0.753 and a specificity of 0.889. Moreover, in the external test set, FGDS outperforms mainstream deep learning models with a sensitivity of 0.768 and a specificity of 0.837. This study highlights the potential of our proposed three-stage ensemble learning model for screening fetal genetic disorders. It showcases the model's ability to enhance detection rates in clinical practice and alleviate the burden on medical professionals.

A computer-aided diagnosis system for brain tumors based on artificial intelligence algorithms

The choice of treatment and prognosis evaluation depend on the accurate early diagnosis of brain tumors. Many brain tumors go undiagnosed or are overlooked by clinicians as a result of the challenges associated with manually evaluating magnetic resonance imaging (MRI) images in clinical practice. In this study, we built a computer-aided diagnosis (CAD) system for glioma detection, grading, segmentation, and knowledge discovery based on artificial intelligence algorithms. Neuroimages are specifically represented using a type of visual feature known as the histogram of gradients (HOG). Then, through a two-level classification framework, the HOG features are employed to distinguish between healthy controls and patients, or between different glioma grades. This CAD system also offers tumor visualization using a semi-automatic segmentation tool for better patient management and treatment monitoring. Finally, a knowledge base is created to offer additional advice for the diagnosis of brain tumors. Based on our proposed two-level classification framework, we train models for glioma detection and grading, achieving area under curve (AUC) of 0.921 and 0.806, respectively. Different from other systems, we integrate these diagnostic tools with a web-based interface, which provides the flexibility for system deployment.

Observation of high-energy neutrinos from the Galactic plane

The origin of high-energy cosmic rays, atomic nuclei that continuously impact Earth's atmosphere, is unknown. Because of deflection by interstellar magnetic fields, cosmic rays produced within the Milky Way arrive at Earth from random directions. However, cosmic rays interact with matter near their sources and during propagation, which produces high-energy neutrinos. We searched for neutrino emission using machine learning techniques applied to 10 years of data from the IceCube Neutrino Observatory. By comparing diffuse emission models to a background-only hypothesis, we identified neutrino emission from the Galactic plane at the 4.5σ level of significance. The signal is consistent with diffuse emission of neutrinos from the Milky Way but could also arise from a population of unresolved point sources.

[Exploration of clinical pathway-oriented optimal management diagnosis and treatment model for rare diseases]

This study takes Cushing's syndrome, a rare disease, as a model, and adopts the path of "Plan, Do, Check, Action" (PDCA) to explore new methods to optimize the clinical path, can improve the quality and efficiency of diagnosis and treatment of rare diseases. After sorting out the problems existing in the previous diagnosis and treatment mode, our team optimizes the path in various ways and establishes a standard operation procedure (SOP) for the new path. In the evaluation of the optimized mode, 55 patients with Cushing's syndrome were admitted to the Department of Endocrinology, Peking Union Medical College Hospital, including 19 males and 36 females, aged (41.8±14.4) years (6-68 years). The pathway group (28 cases) and the control group (27 cases) were divided according to whether they were included in the new path management at the time of admission, and the effect of path optimization was assessed in terms of time, efficacy, safety and cost. The results showed that compared with the control group, the pathway group had a shorter time of hospitalization in the Department of Endocrinology and critical tests, such as blood cortisol rhythm, low-dose dexamethasone inhibition test, and bilateral inferior petrosal sinus sampling (all P<0.05). There was no significant differences in the decrease of total cortisol after operation, the incidence of postoperative complications, and hospitalization expenses (all P>0.05). The optimized path improves the medical efficiency while ensuring medical quality, safety and no increase in cost. This study proposes PDCA path optimization for complex diseases and establishes SOP process, which provides experience in management optimization for the patient-centered and clinical path-oriented diagnosis and treatment mode of rare diseases.

A Deep-Learning-Based Method Can Detect Both Common and Rare Genetic Disorders in Fetal Ultrasound

A global survey indicates that genetic syndromes affect approximately 8% of the population, but most genetic diagnoses can only be performed after babies are born. Abnormal facial characteristics have been identified in various genetic diseases; however, current facial identification technologies cannot be applied to prenatal diagnosis. We developed Pgds-ResNet, a fully automated prenatal screening algorithm based on deep neural networks, to detect high-risk fetuses affected by a variety of genetic diseases. In screening for Trisomy 21, Trisomy 18, Trisomy 13, and rare genetic diseases, Pgds-ResNet achieved sensitivities of 0.83, 0.92, 0.75, and 0.96, and specificities of 0.94, 0.93, 0.95, and 0.92, respectively. As shown in heatmaps, the abnormalities detected by Pgds-ResNet are consistent with clinical reports. In a comparative experiment, the performance of Pgds-ResNet is comparable to that of experienced sonographers. This fetal genetic screening technology offers an opportunity for early risk assessment and presents a non-invasive, affordable, and complementary method to identify high-risk fetuses affected by genetic diseases. Additionally, it has the capability to screen for certain rare genetic conditions, thereby enhancing the clinic's detection rate.

[The past, present and future of sleep medicine in China]

Sleep is a highly conserved phenomenon in endotherms, and has a universal physiological function across all species. In mammals, sleep can be divided into two stages: rapid eye movement (REM) sleep and non-REM (NREM) sleep, which alternate in a cyclic manner. Humans spend about one-third of their lives asleep. Sufficient sleep is necessary for humans to sustain everyday functioning. Sleep plays an important role in regulating energy metabolism, immune defense, endocrine function, and the consolidation of memory process. With the development of social economy and the change of life style, sleep duration of the residents has gradually decreased and the incidence of sleep disturbances has increased. Sleep disturbances can lead to severe mental disorders, such as depression, anxiety disorders, dementia, and other mental diseases, and may increase the risk of physical diseases, such as chronic inflammation, heart disease, diabetes, hypertension, atherosclerosis and others. Maintaining good sleep is of great significance for developing social productive forces, promoting sustainable development of economic society, and is a necessary condition for carrying out the "Healthy China Strategy". The sleep research in China started in 1950s. After decades of development, researchers have made great progress in the molecular mechanisms of sleep and wakefulness, the pathogenesis of sleep disorders and the development of new therapies. With the advancement of science and technology and the public's attention to sleep, the level of clinical diagnosis and therapy of sleep disorders in China is gradually brought in line with international standards. The publication of diagnosis and treatment guidelines in the field of sleep medicine will promote the standardization of the construction. In the future, it is still necessary to promote the development of sleep medicine in the following aspects: Strengthening the professional training and discipline construction, improving the cooperation of sleep research, promoting the intelligent diagnosis and treatment of sleep disorders, and developing the new intervention strategies. Therefore, this review will comprehensively summarize the origin, current situation, and future expectations of sleep medicine in China, including discipline construction of sleep medicine, the number of sleep project grants, research findings, the status and progress of diagnosis and treatment of sleep disorders, and the development direction of sleep medicine.

[A region-level contrastive learning-based deep model for glomerular ultrastructure segmentation on electron microscope images]

OBJECTIVE

We propose a novel region- level self-supervised contrastive learning method USRegCon (ultrastructural region contrast) based on the semantic similarity of ultrastructures to improve the performance of the model for glomerular ultrastructure segmentation on electron microscope images.

METHODS

USRegCon used a large amount of unlabeled data for pre- training of the model in 3 steps: (1) The model encoded and decoded the ultrastructural information in the image and adaptively divided the image into multiple regions based on the semantic similarity of the ultrastructures; (2) Based on the divided regions, the first-order grayscale region representations and deep semantic region representations of each region were extracted by region pooling operation; (3) For the first-order grayscale region representations, a grayscale loss function was proposed to minimize the grayscale difference within regions and maximize the difference between regions. For deep semantic region representations, a semantic loss function was introduced to maximize the similarity of positive region pairs and the difference of negative region pairs in the representation space. These two loss functions were jointly used for pre-training of the model.

RESULTS

In the segmentation task for 3 ultrastructures of the glomerular filtration barrier based on the private dataset GlomEM, USRegCon achieved promising segmentation results for basement membrane, endothelial cells, and podocytes, with Dice coefficients of (85.69 ± 0.13)%, (74.59 ± 0.13)%, and (78.57 ± 0.16)%, respectively, demonstrating a good performance of the model superior to many existing image-level, pixel-level, and region-level self-supervised contrastive learning methods and close to the fully- supervised pre-training method based on the large- scale labeled dataset ImageNet.

CONCLUSION

USRegCon facilitates the model to learn beneficial region representations from large amounts of unlabeled data to overcome the scarcity of labeled data and improves the deep model performance for glomerular ultrastructure recognition and boundary segmentation.

Diimidazolium Salt HBDIM: An Easily Available, Low-Cost CageCarbene Precursor with Broad Applications in Transition Metal-Catalyzed Reactions

The preparation of diimidazolium salt HBDIM 1, a precursor for di-NHCs ligand, from cheap and easily available agent hexabenzylhexaazaisowurtzitane (HBIW) was reported. Under basic conditions, HBDIM underwent facile deprotonation to in situ generate CageCarbene which could efficiently coordinate to transition-metals such as Au, Cu or Pd to give the corresponding bimetallic complexes 2-4. These complexes were isolated and fully characterized including X-ray diffraction of their single crystals. It was found that the steric hinderance of CageCarbene is similar to that of SIMes but smaller than that of IPr, and electronically, CageCarbene is a strong σ-donator silimar to SIMs and a stronger σ-donator than IPr. Further studies showed that complexes 2-4 were highly reactive to catalyze up to 17 reactions. Control experiments utilizing N-benzyl-substituted monoimidazolium salt showed much low catalytic reactivity when it was bounded to Au or Cu, but exhibited similar reactivity for the Pd-complex. Kenetic studies showed that the low reactivity of the monodentate carbene-ligated Au or Cu complex was due to the low stability of the complex under the reaction condions.

Research on the articulated coupling effect of carbon tax policy under resource endowment in China

The carbon tax is a policy tool that internalizes external costs through a tax mechanism, which helps to reduce the consumption of fossil energy and lower carbon dioxide emissions. China, as the largest carbon emitter, introducing a carbon tax can further enhance the effectiveness of emission reduction. However, the introduction of a carbon tax may exacerbate contradictions in other aspects of the social system. To this end, the paper establishes a dynamic model of the carbon tax system by combining grey system theory and the IPAT model and then explores the coupling effect of the carbon tax on the economy, energy, and environment under the premise of China's resource endowment. It is found that carbon tax will not only distort consumer behavior but also aggravate the degree of capital market distortion. In the time-series simulation, it is found that the emission reduction efficiency of the carbon tax will show an oscillation decline. The carbon tax undermines the carbon peak target by dampening demand for energy consumption. In addition, we also find that the change of energy structure is the root of driving the failure of the "Jevons Paradox" and the realization of the "environmental Kuznets curve," and the panel data of energy and economy are only the manifestation of these two phenomena. China needs to adjust its energy structure to achieve its carbon peaking target. These results are helpful for policymakers to rationally view the carbon peaking target and formulate reasonable emission reduction policies.

[A descriptive analysis of hyperlipidemia in adult twins in China]

Objective: To describe the distribution characteristics of hyperlipidemia in adult twins in the Chinese National Twin Registry (CNTR) and explore the effect of genetic and environmental factors on hyperlipidemia. Methods: Twins recruited from the CNTR in 11 project areas across China were included in the study. A total of 69 130 (34 565 pairs) of adult twins with complete information on hyperlipidemia were selected for analysis. The random effect model was used to characterize the population and regional distribution of hyperlipidemia among twins. The concordance rates of hyperlipidemia were calculated in monozygotic twins (MZ) and dizygotic twins (DZ), respectively, to estimate the heritability. Results: The age of all participants was (34.2±12.4) years. This study's prevalence of hyperlipidemia was 1.3% (895/69 130). Twin pairs who were men, older, living in urban areas, married,had junior college degree or above, overweight, obese, insufficient physical activity, current smokers, ex-smokers, current drinkers, and ex-drinkers had a higher prevalence of hyperlipidemia (P<0.05). In within-pair analysis, the concordance rate of hyperlipidemia was 29.1% (118/405) in MZ and 18.1% (57/315) in DZ, and the difference was statistically significant (P<0.05). Stratified by gender, age, and region, the concordance rate of hyperlipidemia in MZ was still higher than that in DZ. Further, in within-same-sex twin pair analyses, the heritability of hyperlipidemia was 13.04% (95%CI: 2.61%-23.47%) in the northern group and 18.59% (95%CI: 4.43%-32.74%) in the female group, respectively. Conclusions: Adult twins were included in this study and were found to have a lower prevalence of hyperlipidemia than in the general population study, with population and regional differences. Genetic factors influence hyperlipidemia, but the genetic effect may vary with gender and area.

[A descriptive analysis on hypertension in adult twins in China]

Objective: To describe the distribution characteristics of hypertension among adult twins in the Chinese National Twin Registry (CNTR) and to provide clues for exploring the role of genetic and environmental factors on hypertension. Methods: A total of 69 220 (34 610 pairs) of twins aged 18 and above with hypertension information were selected from CNTR registered from 2010 to 2018. Random effect models were used to describe the population and regional distribution of hypertension in twins. To estimate the heritability, the concordance rates of hypertension were calculated and compared between monozygotic twins (MZ) and dizygotic twins (DZ). Results: The age of all participants was (34.1±12.4) years. The overall self-reported prevalence of hypertension was 3.8%(2 610/69 220). Twin pairs who were older, living in urban areas, married, overweight or obese, current smokers or ex-smokers, and current drinkers or abstainers had a higher self-reported prevalence of hypertension (P<0.05). Analysis within the same-sex twin pairs found that the concordance rate of hypertension was 43.2% in MZ and 27.0% in DZ, and the difference was statistically significant (P<0.001). The heritability of hypertension was 22.1% (95%CI: 16.3%- 28.0%). Stratified by gender, age, and region, the concordance rate of hypertension in MZ was still higher than that in DZ. The heritability of hypertension was higher in female participants. Conclusions: There were differences in the distribution of hypertension among twins with different demographic and regional characteristics. It is indicated that genetic factors play a crucial role in hypertension in different genders, ages, and regions, while the magnitude of genetic effects may vary.

Radiomics model and clinical scale for the preoperative diagnosis of silent corticotroph adenomas

OBJECTIVE

Silent corticotroph adenomas (SCAs) are a subtype of nonfunctioning pituitary adenomas that exhibit more aggressive behavior. However, rapid and accurate preoperative diagnostic methods are currently lacking.

DESIGN

The purpose of this study was to examine the differences between SCA and non-SCA features and to establish radiomics models and a clinical scale for rapid and accurate prediction.

METHODS

A total of 260 patients (72 SCAs vs. 188 NSCAs) with nonfunctioning adenomas from Peking Union Medical College Hospital were enrolled in the study as the internal dataset. Thirty-five patients (6 SCAs vs. 29 NSCAs) from Fuzhou General Hospital were enrolled as the external dataset. Radiomics models and an SCA scale to preoperatively diagnose SCAs were established based on MR images and clinical features.

RESULTS

There were more female patients (internal dataset: p < 0.001; external dataset: p = 0.028) and more multiple microcystic changes (internal dataset: p < 0.001; external dataset: p = 0.012) in the SCA group. MRI showed more invasiveness (higher Knosp grades, p ≤ 0.001). The radiomics model achieved AUCs of 0.931 and 0.937 in the internal and external datasets, respectively. The clinical scale achieved an AUC of 0.877 and a sensitivity of 0.952 in the internal dataset and an AUC of 0.899 and a sensitivity of 1.0 in the external dataset.

CONCLUSIONS

Based on clinical information and imaging characteristics, the constructed radiomics model achieved high preoperative diagnostic ability. The SCA scale achieved the purpose of rapidity and practicality while ensuring sensitivity, which is conducive to simplifying clinical work.

[Resting heart rate correlates with major adverse cardiovascular and cerebrovascular events in patients with post-myocardial infarction ventricular aneurysms: a retrospective cohort study]

OBJECTIVE

To analyze the association of resting heart rate (RHR) with the prognosis of patients with post-infarction ventricular aneurysms.

METHODS

We retrospectively analyzed the clinical data of 227 patients with post-infarction ventricular aneurysms admitted to our hospital during 2017-2019. The endpoint event was the occurrence of any major adverse cardiovascular and cerebrovascular events (MACCEs) during the follow-up for 24 months. According to RHR measurements, the patients were divided into 3 groups with baseline RHR < 10%, 10%-90%, and >90%. The Cox proportional risk model and restricted cubic spline (RCS) model were used to analyze the effect of RHR on MACCEs.

RESULTS

During the 24-month followup, 90 patients (39.6%) experienced MACCEs. The fully adjusted RCS curves showed a nonlinear "U" shaped correlation between RHR and the occurrence of MACCEs. In the fully adjusted model, the risk of MACCEs increased by 3.01-fold (Hazard ratio [HR]=4.01, 95% CI: 2.07-7.76, P < 0.001) in patients with RHR>90%, as compared with patients with RHR of 10%-90%. In patients with RHR in 1-9th percentile, 10th-90th percentile and 91st-100th percentile, the incidences of MACCEs were 39.1%, 36.6% and 66.7% (P=0.027), the incidences of ventricular tachycardia/ventricular fibrillation (VT/VF) were 17.4%, 2.7% and 4.8% (P=0.005), and the incidences of readmission for heart failure were 8.7%, 26.8% and 42.9% (P=0.036), respectively.

CONCLUSION

Continuous monitoring and management of heart rate range may provide guidance for prognosis prediction in patients with post-infarction ventricular aneurysms.

A35 FORECASTING THE INCIDENCE AND PREVALENCE OF INFLAMMATORY BOWEL DISEASE: A CANADIAN NATION-WIDE ANALYSIS

Background

Canada is currently in the third epidemiological stage in the evolution of IBD: compounding prevalence. A high incidence of IBD, in conjunction with low mortality, leads to a steadily rising prevalence over time. By understanding historical epidemiological trends, we can forecast incidence and prevalence into the future to inform healthcare systems in Canada of the rising burden of IBD to society.

Purpose

To analyze past epidemiological trends in order to forecast the overall incidence and prevalence of IBD, Crohn’s disease (CD), and ulcerative colitis (UC) and stratified by age (<18, 18-64, 65+).

Method

Canadian population-based administrative data was acquired from: AB, BC, SK, MB, QC, and ON. Data were age and sex standardized to the matching year and provincial data aggregated into a representative sample of the Canadian population for prevalence (2002-2014) and incidence (2007-2014: 5-year washout period). Incidence and prevalence (per 100,000 persons) were calculated, with 95% confidence intervals (CI), using Canadian population estimates from Statistics Canada for IBD, CD, UC (IBD-unclassifiable+UC). Autoregressive Integrated Moving Average models were created, and rates forecasted from 2014 to 2035 with 95% prediction intervals (PI). Poisson (or negative binomial) for incidence and log binomial regression for prevalence estimated the Average Annual Percentage Change (AAPC), with 95% CIs, of the forecasted data.

Result(s)

The 2014 incidence of IBD in Canada was 28.4 per 100,000 (95%CI: 27.8, 29.0) and forecasted to significantly increase (AAPC: 0.58%; 95%CI: 0.04, 1.04) from 30.0 per 100,000 in 2023 to 32.1 (95%PI: 27.9, 36.3) in 2035. Pediatric onset IBD was 13.9 per 100,000 (95%CI: 13.0, 14.9) in 2014 and is forecasted to significantly increase to 18.0 per 100,000 (95%PI: 15.7, 20.2) in 2035 with an AAPC of 1.23% (95%CI: 0.76, 1.63). Adult and elderly onset incidence rates were forecasted to remain stable. Prevalence of IBD increased between 2002 (389 per 100,000) and 2014 (636 per 100,000) and is forecasted to continue to climb by an AAPC of 2.44% (95%CI: 2.34, 2.53). In 2023, the prevalence of IBD is 825 per 100,000. By 2035 prevalence is forecasted to climb to 1075 per 100,000 (95%PI: 1047, 1103) with 470,000 Canadians living with IBD. Prevalence across all age strata were forecasted to significantly increase. The highest AAPC was seen in the elderly (2.76%; 95%CI: 2.73, 2.79) with a prevalence of 841 per 100,000 (95%CI: 834, 849) in 2014 and forecasted to climb to 1534 per 100,000 (95%PI: 1519, 1550) in 2035.

Image

Conclusion(s)

Incidence of IBD continues to rise in Canada, driven by pediatric-onset IBD. In 2023, over 320,000 Canadians (0.83%) will be living with IBD. By 2035 prevalence will exceed 1% of the population with approximately 470,000 individuals in Canada with IBD. Future research should establish the environmental determinates of IBD that may influence temporal trends in the incidence of IBD, while healthcare systems adapt to the compounding prevalence of IBD.

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CIHR, Other

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The Leona M. and Harry B. Helmsley Charitable Trust

Disclosure of Interest

S. Coward: None Declared, E. Benchimol Consultant of: Hoffman La-Roche Limited and Peabody & Arnold LLP for matters unrelated to medications used to treat inflammatory bowel disease and McKesson Canada and the Dairy Farmers of Ontario for matters unrelated to medications used to treat inflammatory bowel disease., C. Bernstein Grant / Research support from: Unrestricted educational grants from Abbvie Canada, Janssen Canada, Pfizer Canada, Bristol Myers Squibb Canada, and Takeda Canada. Has received research grants from Abbvie Canada, Amgen Canada, Pfizer Canada, and Sandoz Canada and contract grants from Janssen, Abbvie and Pfizer, Consultant of: Abbvie Canada, Amgen Canada, Bristol Myers Squibb Canada, JAMP Pharmaceuticals, Janssen Canada, Pfizer Canada, Sandoz Canada, and Takeda., Speakers bureau of: Abbvie Canada, Janssen Canada, Pfizer Canada and Takeda Canada, J. A. Avina-Zubieta: None Declared, A. Bitton: None Declared, L. Hracs: None Declared, J. Jones Consultant of: Janssen, Abbvie, Pfizer, Takeda, Speakers bureau of: Janssen, Abbvie, Pfizer, Takeda, E. Kuenzig: None Declared, L. Lu: None Declared, S. Murthy: None Declared, Z. Nugent: None Declared, A. Otley Grant / Research support from: Unrestricted educational grants from AbbVie Canada and Janssen Canada, Consultant of: Advisory boards of AbbVie Canada, Janssen Canada and Nestle, R. Panaccione Consultant of: Abbott, AbbVie, Alimentiv (formerly Robarts), Amgen, Arena Pharmaceuticals, AstraZeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Celltrion, Cosmos Pharmaceuticals, Eisai, Elan, Eli Lilly, Ferring, Galapagos, Fresenius Kabi, Genentech, Gilead Sciences, Glaxo-Smith Kline, JAMP Bio, Janssen, Merck, Mylan, Novartis, Oppilan Pharma, Organon, Pandion Pharma, Pendopharm, Pfizer, Progenity, Protagonist Therapeutics, Roche, Sandoz, Satisfai Health, Shire, Sublimity Therapeutics, Takeda Pharmaceuticals, Theravance Biopharma, Trellus, Viatris, UCB. Advisory Boards for: AbbVie, Alimentiv (formerly Robarts), Amgen, Arena Pharmaceuticals, AstraZeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Ferring, Fresenius Kabi, Genentech, Gilead Sciences, Glaxo-Smith Kline, JAMP Bio, Janssen, Merck, Mylan, Novartis, Oppilan Pharma, Organon, Pandion Pharma, Pfizer, Progenity, Protagonist Therapeutics, Roche, Sandoz Shire, Sublimity Therapeutics, Takeda Pharmaceuticals, Speakers bureau of: AbbVie, Amgen, Arena Pharmaceuticals, Bristol-Myers Squibb, Celgene, Eli Lilly, Ferring, Fresenius Kabi, Gilead Sciences, Janssen, Merck, Organon, Pfizer, Roche, Sandoz, Shire, Takeda Pharmaceuticals, J.-N. Pena-Sanchez: None Declared, H. Singh Consultant of: Pendopharm, Amgen Canada, Bristol Myers Squibb Canada, Roche Canada, Sandoz Canada, Takeda Canada, and Guardant Health, Inc., L. Targownik Grant / Research support from: Investigator initiated funding from Janssen Canada, Consultant of: [Advisory board] AbbVie Canada, Takeda Canada, Merck Canada, Pfizer Canada, Janssen Canada, Roche Canada, and Sandoz Canada, J. Windsor: None Declared, G. Kaplan Grant / Research support from: Ferring, Janssen, AbbVie, GlaxoSmith Kline, Merck, and Shire, Consultant of: Gilead, Speakers bureau of: AbbVie, Janssen, Pfizer, Amgen, and Takeda

A210 THE BURDEN OF IBD HOSPITALIZATION IN CANADA: AN ASSESSMENT OF THE CURRENT AND FUTURE BURDEN IN A NATION-WIDE ANALYSIS

Background

Hospitalizations pose a significant burden on both the individual and the healthcare system. Those with inflammatory bowel disease (IBD) are at increased risk of hospitalization as compared to the general population due to flaring of disease activity and complications related to IBD. The advent of biologics over the past twenty years may have influenced the rates of hospitalization for IBD.

Purpose

To assess current and forecast the overall hospitalization rates of those with IBD stratified by types of hospitalizations (all cause hospitalizations, IBD-related, and IBD-specific).

Method

Population-based administrative data on hospitalization of IBD (2002-2014) were obtained from: AB, BC, MB, and SK. Data were age and sex standardized to the matching year and aggregated into a representative sample of the Canadian population. Hospitalization rates were assessed as follows: 1. All cause hospitalizations: all admissions regardless of indication; 2. IBD-specific: an admission directly resulting from IBD (e.g., IBD-flare); 3. IBD-related: an admission for IBD, or a symptom or comorbidity associated with IBD (e.g. rheumatoid arthritis). Using prevalence estimates from the provinces, hospitalization rates (per 100 persons with IBD) were calculated, with 95% confidence intervals (CI). Autoregressive Integrated Moving Average models were created to estimate number of hospitalizations and corresponding prevalence to forecast hospitalization rates to 2030 with 95% prediction intervals (PI). Poisson (or negative binomial) regression estimated the Average Annual Percentage Change (AAPC), with 95% CIs, of the forecasted data.

Result(s)

In 2002 there were 35.3 per 100 (95%CI: 34.7, 35.9) all cause hospitalizations for IBD patients and this decreased to 24.9 per 100 (24.5, 25.2) in 2014. Similar trends were seen for IBD-specific hospitalizations [16.8 per 100 (95%CI: 16.4, 17.2) in 2002 to 8.7 per 100 (95%CI: 8.5, 9.0) in 2014] and IBD-related (22.6 per 100 (95%CI: 22.1, 23.1) in 2002 to 13.4 per 100 (95%CI: 13.2, 13.7) in 2014). When forecasted out to 2030 all hospitalization types were significantly decreasing—the AAPC for all cause hospitalizations was -2.12% (95%CI: -2.31, -1.93), -3.77% (95%CI: -4.63, -3.08) for IBD-specific, and -3.09% (95%CI: -3.65, -2.62) for IBD-related. By 2030, the rates of hospitalization are forecasted to be 17.0 per 100 (95%PI: 16.2, 17.9), 4.6 per 100 (95%PI: 3.7, 5.4), and 7.9 per 100 (95%PI: 6.9, 8.9) for all cause, IBD-specific, and IBD-related, respectively.

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Conclusion(s)

In Canada, rates of hospitalizations for those with IBD have decreased from 2002 to 2014. The use of anti-TNF therapy in conjunction with the evolution of clinical monitoring, management and guidelines, likely has contributed to dropping hospitalization rates. Forecast models estimate a continued drop in hospitalization rates out to 2030. Importantly, healthcare resource planning should account for the shift from hospital-based to clinic-centric models of IBD care.

Please acknowledge all funding agencies by checking the applicable boxes below

CIHR

Disclosure of Interest

S. Coward: None Declared, E. Benchimol Consultant of: Hoffman La-Roche Limited and Peabody & Arnold LLP for matters unrelated to medications used to treat inflammatory bowel disease and McKesson Canada and the Dairy Farmers of Ontario for matters unrelated to medications used to treat inflammatory bowel disease., C. Bernstein Grant / Research support from: Unrestricted educational grants from Abbvie Canada, Janssen Canada, Pfizer Canada, Bristol Myers Squibb Canada, and Takeda Canada. Has received research grants from Abbvie Canada, Amgen Canada, Pfizer Canada, and Sandoz Canada and contract grants from Janssen, Abbvie and Pfizer, Consultant of: Abbvie Canada, Amgen Canada, Bristol Myers Squibb Canada, JAMP Pharmaceuticals, Janssen Canada, Pfizer Canada, Sandoz Canada, and Takeda., Speakers bureau of: Abbvie Canada, Janssen Canada, Pfizer Canada and Takeda Canada, J. A. Avina-Zubieta: None Declared, A. Bitton: None Declared, L. Hracs: None Declared, J. Jones Consultant of: Janssen, Abbvie, Pfizer, Takeda, Speakers bureau of: Janssen, Abbvie, Pfizer, Takeda, E. Kuenzig: None Declared, L. Lu: None Declared, S. Murthy: None Declared, Z. Nugent: None Declared, A. Otley Grant / Research support from: Unrestricted educational grants from AbbVie Canada and Janssen Canada, Consultant of: Advisory boards of AbbVie Canada, Janssen Canada and Nestle, R. Panaccione Consultant of: Abbott, AbbVie, Alimentiv (formerly Robarts), Amgen, Arena Pharmaceuticals, AstraZeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Celltrion, Cosmos Pharmaceuticals, Eisai, Elan, Eli Lilly, Ferring, Galapagos, Fresenius Kabi, Genentech, Gilead Sciences, Glaxo-Smith Kline, JAMP Bio, Janssen, Merck, Mylan, Novartis, Oppilan Pharma, Organon, Pandion Pharma, Pendopharm, Pfizer, Progenity, Protagonist Therapeutics, Roche, Sandoz, Satisfai Health, Shire, Sublimity Therapeutics, Takeda Pharmaceuticals, Theravance Biopharma, Trellus, Viatris, UCB. Advisory Boards for: AbbVie, Alimentiv (formerly Robarts), Amgen, Arena Pharmaceuticals, AstraZeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Ferring, Fresenius Kabi, Genentech, Gilead Sciences, Glaxo-Smith Kline, JAMP Bio, Janssen, Merck, Mylan, Novartis, Oppilan Pharma, Organon, Pandion Pharma, Pfizer, Progenity, Protagonist Therapeutics, Roche, Sandoz Shire, Sublimity Therapeutics, Takeda Pharmaceuticals, Speakers bureau of: AbbVie, Amgen, Arena Pharmaceuticals, Bristol-Myers Squibb, Celgene, Eli Lilly, Ferring, Fresenius Kabi, Gilead Sciences, Janssen, Merck, Organon, Pfizer, Roche, Sandoz, Shire, Takeda Pharmaceuticals, J.-N. Pena-Sanchez: None Declared, H. Singh Consultant of: Pendopharm, Amgen Canada, Bristol Myers Squibb Canada, Roche Canada, Sandoz Canada, Takeda Canada, and Guardant Health, Inc.,, L. Targownik Grant / Research support from: Investigator initiated funding from Janssen Canada, Consultant of: [Advisory board] AbbVie Canada, Takeda Canada, Merck Canada, Pfizer Canada, Janssen Canada, Roche Canada, and Sandoz Canada, J. Windsor: None Declared, G. Kaplan Grant / Research support from: Ferring, Janssen, AbbVie, GlaxoSmith Kline, Merck, and Shire, Consultant of: Gilead, Speakers bureau of: AbbVie, Janssen, Pfizer, Amgen, and Takeda

A169 THE DIRECT COSTS OF INFLAMMATORY BOWEL DISEASE IN CANADA: A POPULATION-BASED ANALYSIS OF HISTORICAL AND CURRENT COSTS

Background

Inflammatory bowel disease (IBD) is a costly disease to manage due to hospitalizations, regular ambulatory monitoring, and expensive pharmaceutical therapies. While hospitalization rates have fallen, the increased use of biologics have escalated the cost of care to the healthcare system.

Purpose

To assess historical direct healthcare costs of the IBD population in Canada.

Method

Population-based administrative costing data were obtained from: Alberta, British Columbia, and Manitoba. Costs were calculated based on administrative data (2009 to 2016) which captured: hospitalizations, physician costs, ambulatory care such as: emergency visits, day surgery, and colonoscopy (AB only), and medication costs of IBD-specific medications, such as: mesalamine, biologics, steroids, and immunomodulators. Costs were converted to 2020 dollars using the consumer price index. Average annual cost per person (ACPP) was calculated for each province. Using province specific IBD prevalence estimates these ACPP were meta-analyzed to obtain the annual weighted costs, with 95% confidence intervals (CI), and these costs underwent meta-regression to ascertain the average annual change in cost per year. An Autoregressive Integrated Moving Average model was created to estimate the ACPP in 2023 with 95% prediction intervals (PI). Canada-wide total direct care costs of IBD patients, in billions (B), were calculated using the ACPP, Canada-specific IBD prevalence estimates (historical and forecasted), and total Canadian population calculations from Statistics Canada (historical and forecasted).

Result(s)

In 2009 the ACPP was $7000 (95%CI: 5389, 8610), representing $1.18B (95%CI: 0.91B, 1.45B) in direct healthcare costs in Canada for all IBD patients. The ACPP in 2016 was increased to $10,336 (95%CI: 6803, 13869), which equates to $2.37B (95%CI: 1.56B, 3.18B) per year in direct healthcare costs. From 2009 to 2016, the ACPP increased an average of $450 (95%CI: 132, 767) per year. If these historical trends continue to 2023 the ACPP is forecasted to be $13,333 (95%PI: 12827, 13839) per person per year. The largest contributor to these costs is medications—accounting for an estimated 50% of the total costs of IBD patients.

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Conclusion(s)

The direct healthcare cost of IBD has risen steadily from 2009 to 2016 when the healthcare system spent over $10,000 per person with IBD and $2.37B nationwide. The primary driver of costs is medical management. Forecast models estimate that the annual cost may be over $13,000 per person in 2023. However, these estimates do not account for advent and increased uptake of novel biologics and small molecules, nor the downward cost pressure of biosimilars. These costs are those paid directly by the healthcare system and do not account for those born by the individual—it is estimated that the true cost of IBD (direct and indirect) is much higher.

Please acknowledge all funding agencies by checking the applicable boxes below

CIHR

Disclosure of Interest

S. Coward: None Declared, E. Benchimol Consultant of: Hoffman La-Roche Limited and Peabody & Arnold LLP for matters unrelated to medications used to treat inflammatory bowel disease and McKesson Canada and the Dairy Farmers of Ontario for matters unrelated to medications used to treat inflammatory bowel disease., C. Bernstein Grant / Research support from: Unrestricted educational grants from Abbvie Canada, Janssen Canada, Pfizer Canada, Bristol Myers Squibb Canada, and Takeda Canada. Has received research grants from Abbvie Canada, Amgen Canada, Pfizer Canada, and Sandoz Canada and contract grants from Janssen, Abbvie and Pfizer, Consultant of: Abbvie Canada, Amgen Canada, Bristol Myers Squibb Canada, JAMP Pharmaceuticals, Janssen Canada, Pfizer Canada, Sandoz Canada, and Takeda., Speakers bureau of: Abbvie Canada, Janssen Canada, Pfizer Canada and Takeda Canada, J. A. Avina-Zubieta: None Declared, A. Bitton: None Declared, L. Hracs: None Declared, J. Jones Consultant of: Janssen, Abbvie, Pfizer, Takeda, Speakers bureau of: Janssen, Abbvie, Pfizer, Takeda, E. Kuenzig: None Declared, L. Lu: None Declared, S. Murthy: None Declared, Z. Nugent: None Declared, A. Otley Grant / Research support from: Unrestricted educational grants from AbbVie Canada and Janssen Canada, Consultant of: Advisory boards of AbbVie Canada, Janssen Canada and Nestle, R. Panaccione Consultant of: Abbott, AbbVie, Alimentiv (formerly Robarts), Amgen, Arena Pharmaceuticals, AstraZeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Celltrion, Cosmos Pharmaceuticals, Eisai, Elan, Eli Lilly, Ferring, Galapagos, Fresenius Kabi, Genentech, Gilead Sciences, Glaxo-Smith Kline, JAMP Bio, Janssen, Merck, Mylan, Novartis, Oppilan Pharma, Organon, Pandion Pharma, Pendopharm, Pfizer, Progenity, Protagonist Therapeutics, Roche, Sandoz, Satisfai Health, Shire, Sublimity Therapeutics, Takeda Pharmaceuticals, Theravance Biopharma, Trellus, Viatris, UCB. Advisory Boards for: AbbVie, Alimentiv (formerly Robarts), Amgen, Arena Pharmaceuticals, AstraZeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Ferring, Fresenius Kabi, Genentech, Gilead Sciences, Glaxo-Smith Kline, JAMP Bio, Janssen, Merck, Mylan, Novartis, Oppilan Pharma, Organon, Pandion Pharma, Pfizer, Progenity, Protagonist Therapeutics, Roche, Sandoz Shire, Sublimity Therapeutics, Takeda Pharmaceuticals, Speakers bureau of: AbbVie, Amgen, Arena Pharmaceuticals, Bristol-Myers Squibb, Celgene, Eli Lilly, Ferring, Fresenius Kabi, Gilead Sciences, Janssen, Merck, Organon, Pfizer, Roche, Sandoz, Shire, Takeda Pharmaceuticals, J.-N. Pena-Sanchez: None Declared, H. Singh Consultant of: Pendopharm, Amgen Canada, Bristol Myers Squibb Canada, Roche Canada, Sandoz Canada, Takeda Canada, and Guardant Health, Inc.,, L. Targownik Grant / Research support from: Investigator initiated funding from Janssen Canada, Consultant of: [Advisory board] AbbVie Canada, Takeda Canada, Merck Canada, Pfizer Canada, Janssen Canada, Roche Canada, and Sandoz Canada, J. Windsor: None Declared, G. Kaplan Grant / Research support from: Ferring, Janssen, AbbVie, GlaxoSmith Kline, Merck, and Shire, Consultant of: Gilead, Speakers bureau of: AbbVie, Janssen, Pfizer, Amgen, and Takeda

Insect Herbivory on Main Stem Enhances Induced Defense of Primary Tillers in Rice (Oryza sativa L.)

Clonal plants are interconnected to form clonal plant networks with physiological integration, enabling the reassignment as well as sharing of resources among the members. The systemic induction of antiherbivore resistance via clonal integration may frequently operate in the networks. Here, we used an important food crop rice (Oryza sativa), and its destructive pest rice leaffolder (LF; Cnaphalocrocis medinalis) as a model to examine defense communication between the main stem and clonal tillers. LF infestation and MeJA pretreatment on the main stem for two days reduced the weight gain of LF larvae fed on the corresponding primary tillers by 44.5% and 29.0%, respectively. LF infestation and MeJA pretreatment on the main stem also enhanced antiherbivore defense responses in primary tillers: increased levels of a trypsin protease inhibitor, putative defensive enzymes, and jasmonic acid (JA), a key signaling compound involved in antiherbivore induced defenses; strong induction of genes encoding JA biosynthesis and perception; and rapid activation of JA pathway. However, in a JA perception OsCOI RNAi line, LF infestation on main stem showed no or minor effects on antiherbivore defense responses in primary tillers. Our work demonstrates that systemic antiherbivore defense operate in the clonal network of rice plants and JA signaling plays a crucial role in mediating defense communication between main stem and tillers in rice plants. Our findings provide a theoretical basis for the ecological control of pests by using the systemic resistance of cloned plants themselves.

Zinc-finger protein GmZF351 improves both salt and drought stress tolerance in soybean

Abiotic stress is one of the most important factors reducing soybean yield. It is essential to identify regulatory factors contributing to stress responses. A previous study found that the tandem CCCH zinc-finger protein GmZF351 is an oil level regulator. In this study, we discovered that the GmZF351 gene is induced by stress and that the overexpression of GmZF351 confers stress tolerance to transgenic soybean. GmZF351 directly regulates the expression of GmCIPK9 and GmSnRK, leading to stomata closing, by binding to their promoter regions, which carry two CT(G/C)(T/A)AA elements. Stress induction of GmZF351 is mediated through reduction in the H3K27me3 level at the GmZF351 locus. Two JMJ30-demethylase-like genes, GmJMJ30-1 and GmJMJ30-2, are involved in this demethylation process. Overexpression of GmJMJ30-1/2 in transgenic hairy roots enhances GmZF351 expression mediated by histone demethylation and confers stress tolerance to soybean. Yield-related agronomic traits were evaluated in stable GmZF351-transgenic plants under mild drought stress conditions. Our study reveals a new mode of GmJMJ30-GmZF351 action in stress tolerance, in addition to that of GmZF351 in oil accumulation. Manipulation of the components in this pathway is expected to improve soybean traits and adaptation under unfavorable environments.

Limits to Gauge Coupling in the Dark Sector Set by the Nonobservation of Instanton-Induced Decay of Super-Heavy Dark Matter in the Pierre Auger Observatory Data

Instantons, which are nonperturbative solutions to Yang-Mills equations, provide a signal for the occurrence of quantum tunneling between distinct classes of vacua. They can give rise to decays of particles otherwise forbidden. Using data collected at the Pierre Auger Observatory, we search for signatures of such instanton-induced processes that would be suggestive of super-heavy particles decaying in the Galactic halo. These particles could have been produced during the post-inflationary epoch and match the relic abundance of dark matter inferred today. The nonobservation of the signatures searched for allows us to derive a bound on the reduced coupling constant of gauge interactions in the dark sector: α_{X}≲0.09, for 10^{9}≲M_{X}/GeV<10^{19}. Conversely, we obtain that, for instance, a reduced coupling constant α_{X}=0.09 excludes masses M_{X}≳3×10^{13}  GeV. In the context of dark matter production from gravitational interactions alone, we illustrate how these bounds are complementary to those obtained on the Hubble rate at the end of inflation from the nonobservation of tensor modes in the cosmological microwave background.

The Two-Stage Ensemble Learning Model Based on Aggregated Facial Features in Screening for Fetal Genetic Diseases

With the advancement of medicine, more and more researchers have turned their attention to the study of fetal genetic diseases in recent years. However, it is still a challenge to detect genetic diseases in the fetus, especially in an area lacking access to healthcare. The existing research primarily focuses on using teenagers' or adults' face information to screen for genetic diseases, but there are no relevant directions on disease detection using fetal facial information. To fill the vacancy, we designed a two-stage ensemble learning model based on sonography, Fgds-EL, to identify genetic diseases with 932 images. Concretely speaking, we use aggregated information of facial regions to detect anomalies, such as the jaw, frontal bone, and nasal bone areas. Our experiments show that our model yields a sensitivity of 0.92 and a specificity of 0.97 in the test set, on par with the senior sonographer, and outperforming other popular deep learning algorithms. Moreover, our model has the potential to be an effective noninvasive screening tool for the early screening of genetic diseases in the fetus.

Evidence for neutrino emission from the nearby active galaxy NGC 1068

A supermassive black hole, obscured by cosmic dust, powers the nearby active galaxy NGC 1068. Neutrinos, which rarely interact with matter, could provide information on the galaxy’s active core. We searched for neutrino emission from astrophysical objects using data recorded with the IceCube neutrino detector between 2011 and 2020. The positions of 110 known gamma-ray sources were individually searched for neutrino detections above atmospheric and cosmic backgrounds. We found that NGC 1068 has an excess of 79 − 20 + 22 neutrinos at tera–electron volt energies, with a global significance of 4.2σ, which we interpret as associated with the active galaxy. The flux of high-energy neutrinos that we measured from NGC 1068 is more than an order of magnitude higher than the upper limit on emissions of tera–electron volt gamma rays from this source.