A Shape-Consistent Deep-Learning Segmentation Architecture for Low-Quality and High-Interference Myocardial Contrast Echocardiography.

OBJECTIVE: Myocardial contrast echocardiography (MCE) plays a crucial role in diagnosing ischemia, infarction, masses and other cardiac conditions. In the realm of MCE image analysis, accurate and consistent myocardial segmentation results are essential for enabling automated analysis of various heart diseases. However, current manual diagnostic methods in MCE suffer from poor repeatability and limited clinical applicability. MCE images often exhibit low quality and high noise due to the instability of ultrasound signals, while interference structures can further disrupt segmentation consistency. METHODS: To overcome these challenges, we proposed a deep-learning network for the segmentation of MCE. This architecture leverages dilated convolutions to capture high-scale information without sacrificing positional accuracy and modifies multi-head self-attention to enhance global context and ensure consistency, effectively overcoming issues related to low image quality and interference. Furthermore, we also adapted the cascade application of transformers with convolutional neural networks for improved segmentation in MCE. RESULTS: In our experiments, our architecture achieved the best Dice score of 84.35% for standard MCE views compared with that of several state-of-the-art segmentation models. For non-standard views and frames with interfering structures (mass), our models also attained the best Dice scores of 83.33% and 83.97%, respectively. CONCLUSION: These studies proved that our architecture is of excellent shape consistency and robustness, which allows it to deal with segmentation of various types of MCE. Our relatively precise and consistent myocardial segmentation results provide fundamental conditions for the automated analysis of various heart diseases, with the potential to discover underlying pathological features and reduce healthcare costs.

Epigenetic identification of LTBP4 as a putative tumor suppressor in breast cancer.

Aim: To explore the LTBP4's expression, prognostic significance and molecular mechanism of action in breast cancer (BC).Methods: On the basis of omics datasets and experiments, we conducted a synthetical analysis of LTBP4 in BC.Results & conclusion: LTBP4 was downregulated in BC with high promoter methylation and low genetic alteration. DNA methylation was negatively associated with LTBP4 mRNA expression. Higher LTBP4 associated with better survival. LTBP4 was enrichment in extracellular matrix receptor interactions, cell adhesion molecules, cell cycle and MAPK pathway. LTBP4 expression and methylation were positively and negatively associated with tumor infiltrating immune cells, respectively. In conclusion, LTBP4 is a putative tumor suppressor in BC, which expression is regulated by DNA methylation and relates with prognosis.

[Box: see text].

STRAP upregulates antiviral innate immunity against PRV by targeting TBK1.

Serine/threonine kinase receptor-associated protein (STRAP) serves as a scaffold protein and is engaged in a variety of cellular activities, although its importance in antiviral innate immunity is unknown. We discovered that STRAP works as an interferon (IFN)-inducible positive regulator, facilitating type I IFN signaling during pseudorabies virus infection. Mechanistically, STRAP interacts with TBK1 to activate type I IFN signaling. Both the CT and WD40 7 - 6 domains contribute to the function of STRAP. Furthermore, TBK1 competes with PRV-UL50 for binding to STRAP, and STRAP impedes the degradation of TBK1 mediated by PRV-UL50, thereby increasing the interaction between STRAP and TBK1. Overall, these findings reveal a previously unrecognized role for STRAP in innate antiviral immune responses during PRV infection. STRAP could be a potential therapeutic target for viral infectious diseases.

Skin metastasis from ovarian cancer with somatic BRCA1 mutation: A case report and literature review.

Skin metastasis from ovarian cancer is rare, and its prognosis is poor. Effective therapeutic strategies are currently lacking, but the combination of various treatment methods shrink the tumor and relieve symptoms. The present study reports a rare case of advanced ovarian cancer with skin metastases and intestinal wall thickening, along with a BRCA1 DNA repair associated (BRCA1) mutation. After standard first-line treatment and non-standard second-line treatment, the patient developed skin metastases. The patient's skin itching, pain and lesions were completely relieved after administering bevacizumab in combination with paclitaxel and carboplatin. After 4 months, skin metastases recurred along with anal distension during maintenance treatment with oral poly(ADP ribose) polymerase (PARP) inhibitors. The patient was treated again with bevacizumab combined with docetaxel, and the anal distension was significantly relieved. Angiogenesis therapy combined with chemotherapy is effective, but that the disease-free survival time is short, and PARP inhibitor maintenance effect is limited even in cases with a BRCA1 gene mutation.

Establishment of human acute monocytic leukemia model with systemic infiltration in NPG mice.

A model construction of systemic acute leukemia is challenging. Herein, we established a systemic leukemia mouse model using highly immunodeficient NPG mice without any immunosuppressive treatments. NPG mice received tail intravenous injection of SHI-1 cells at the concentration of 1×107 cells (group A) or 5×107 cells (group B) and randomly sacrificed each seven days post-inoculation. Tumor development was monitored using nested-PCR, peripheral blood-smear analysis, flow cytometry, pathological examinations, and immunohistochemistry. The median survival of mice in groups A and B were 33.0 and 30.0 days, respectively. Blast cells in peripheral blood appeared on day 14 in group B, and on day 21 in group A. In addition, SHI-1 cell specific MLL-AF6 mRNA was detected in both spleen and bone marrow on day 14 post-inoculation. 21 days after inoculation, we observed human CD45+CD33+ cells with an SH-1-immunophenotype in the peripheral blood, spleen, and bone marrow, as well as solid neoplasms in multiple organs. Moreover, the histologically infiltrated leukemic cells expressed CD45. In conclusion, the current study demonstrated the normal growth of SHI-1 cells in the NPG mice without immunosuppression, which caused systemic leukemia similar to that observed in acute leukemia patients. We developed an efficient and reproducible model to study leukemia pathogenesis and progression.

Contribution of the transcription factor SfGATAe to Bt Cry toxin resistance in Spodoptera frugiperda through reduction of ABCC2 expression.

Insect resistance evolution poses a significant threat to the advantages of biopesticides and transgenic crops utilizing insecticidal Cry-toxins from Bacillus thuringiensis (Bt). However, there is limited research on the relationship between transcriptional regulation of specific toxin receptors in lepidopteran insects and their resistance to Bt toxins. Here, we report the positive regulatory role of the SfGATAe transcription factor on the expression of the ABCC2 gene in Spodoptera frugiperda. DNA regions in the SfABCC2 promoter that are vital for regulation by SfGATAe, utilizing DAP-seq technology and promoter deletion mapping. Through yeast one-hybrid assays, DNA pull-down experiments, and site-directed mutagenesis, we confirmed that the transcription factor SfGATAe regulates the core control site PBS2 in the ABCC2 target gene. Tissue-specific expression analysis has revealed that SfGATAe is involved in the regulation and expression of midgut cells in the fall armyworm. Silencing SfGATAe in fall armyworm larvae resulted in reduced expression of SfABCC2 and decreased sensitivity to Cry1Ac toxin. Overall, this study elucidated the regulatory mechanism of the transcription factor SfGATAe on the expression of the toxin receptor gene SfABCC2 and this transcriptional control mechanism impacts the resistance of the fall armyworm to Bt toxins.

XTransCT: ultra-fast volumetric CT reconstruction using two orthogonal x-ray projections for image-guided radiation therapy via a transformer network.

Objective.The aim of this study was to reconstruct volumetric computed tomography (CT) images in real-time from ultra-sparse two-dimensional x-ray projections, facilitating easier navigation and positioning during image-guided radiation therapy.Approach.Our approach leverages a voxel-sapce-searching Transformer model to overcome the limitations of conventional CT reconstruction techniques, which require extensive x-ray projections and lead to high radiation doses and equipment constraints.Main results.The proposed XTransCT algorithm demonstrated superior performance in terms of image quality, structural accuracy, and generalizability across different datasets, including a hospital set of 50 patients, the large-scale public LIDC-IDRI dataset, and the LNDb dataset for cross-validation. Notably, the algorithm achieved an approximately 300% improvement in reconstruction speed, with a rate of 44 ms per 3D image reconstruction compared to former 3D convolution-based methods.Significance.The XTransCT architecture has the potential to impact clinical practice by providing high-quality CT images faster and with substantially reduced radiation exposure for patients. The model's generalizability suggests it has the potential applicable in various healthcare settings.

The relationship between healthy lifestyles and cognitive function in Chinese older adults: the mediating effect of depressive symptoms.

BACKGROUND: Previous studies have proven the positive relationship between healthy lifestyles and cognitive function in older adults. However, the specific impacts and mechanisms require further investigation. Therefore, this study aimed to investigate whether healthy lifestyles and cognitive function were associated with Chinese older adults and whether depressive symptoms mediated their association. METHODS: 8272 valid samples were included using the latest data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Pearson's test was applied to investigate the relationship between the key variables. Regression models were employed to examine the mediating effects of healthy lifestyles, using Sobel's test and the bootstrap method to confirm path effects. RESULTS: There was a significant correlation between healthy lifestyles, depressive symptoms, and cognitive function (p < 0.01). Healthy lifestyles directly impact cognitive function (ß = 0.162, p < 0.01). Healthy lifestyles had a significant effect on depressive symptoms (ß=-0.301, p < 0.01), while depressive symptoms have a significant impact on cognitive function (ß=-0.108, p < 0.01). Depressive symptoms partially mediated the effect of healthy lifestyles on cognitive function (ß = 0.032, p < 0.01). The Sobel and bootstrap tests confirmed the robustness of the regression analysis results. CONCLUSION: Depressive symptoms mediate the relationship between healthy lifestyles and cognitive function. Our findings suggest that prevention strategies for cognitive impairment in older adults should focus on healthy lifestyles and mental health.

Cutaneous Metastasis of Ovarian Cancer on 68 Ga-FAPI PET/CT.

ABSTRACT: Ovarian cancer with cutaneous metastases is quite rare. We report the findings of cutaneous metastases from ovarian cancer on 68 Ga-FAPI PET/CT imaging. A 53-year-old woman with cutaneous metastases from ovarian cancer was enrolled in 68 Ga-FAPI PET/CT clinical trial. The images showed intense FAPI activity in the known cutaneous metastases.

Study on predictive models for swallowing risk in patients with AECOPD.

BACKGROUND: Dysphagia is considered a complication in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). However, AECOPD may have risk factors for dysphagia. METHODS: Through a cross-sectional study, which included 100 patients with AECOPD. General information, Pulmonary function, COPD assessment test (CAT) and modified Medical Research Council (mMRC) were collected by questionnaire. The questionnaires were administered by uniform-trained investigators using standard and neutral language, and swallowing risk was assessed by using a water swallow test (WST) on the day of patient admission. RESULTS: Among the 100 included patients, 50(50%) were at risk of swallowing. Multivariate analysis using logistic regression analysis showed that age ≥ 74 years old, mMRC ≥ level 2, hospitalization days ≥ 7 days and the use of BIPAP assisted ventilation were important influencing factors for swallowing risk in patients with AECOPD. CONCLUSION: Patients with AECOPD are at risk for dysphagia, assessing age, mMRC, hospitalization days and the use of BIPAP assisted ventilation can be used to screen for swallowing risk, thus contributing to the implementation of early prevention measures.

Screening for Resistance Resources against Bacterial Wilt in Wild Potato.

Potato is an important crop, used not only for food production but also for various industrial applications. With the introduction of the potato as a staple food strategy, the potato industry in China has grown rapidly. However, issues related to bacterial wilt, exacerbated by factors such as seed potato transportation and continuous cropping, have become increasingly severe in the primary potato cultivation regions of China, leading to significant economic losses. The extensive genetic diversity of Ralstonia solanacearum (R. solanacearum), which is the pathogen of bacterial wilt, has led to a lack of highly resistant potato genetic resources. There is a need to identify and cultivate potato varieties with enhanced resistance to reduce the adverse impact of this disease on the industry. We screened 55 accessions of nine different wild potato species against the bacterial wilt pathogen R. solanacearum PO2-1, which was isolated from native potato plants and belongs to phylotype II. Three accessions of two species (ACL24-2, PNT880-3, and PNT204-23) were identified with high resistance phenotypes to the tested strains. We found these accessions also showed high resistance to different phylotype strains. Among them, only PNT880-3 was capable of flowering and possessed viable pollen, and it was diploid. Consistent with the high resistance, decreased growth of R. solanacearum was detected in PNT880-3. All these findings in our study reveal that the wild potato PNT880-3 was a valuable resistance source to bacterial wilt with breeding potential.

APC mutations disrupt ß-catenin destruction complex condensates organized by Axin phase separation.

The Wnt/ß-catenin pathway is critical to maintaining cell fate decisions. Recent study showed that liquid-liquid-phase separation (LLPS) of Axin organized the ß-catenin destruction complex condensates in a normal cellular state. Mutations inactivating the APC gene are found in approximately 80% of all human colorectal cancer (CRC). However, the molecular mechanism of the formation of ß-catenin destruction complex condensates organized by Axin phase separation and how APC mutations impact the condensates are still unclear. Here, we report that the ß-catenin destruction complex, which is constructed by Axin, was assembled condensates via a phase separation process in CRC cells. The key role of wild-type APC is to stabilize destruction complex condensates. Surprisingly, truncated APC did not affect the formation of condensates, and GSK 3ß and CK1α were unsuccessfully recruited, preventing ß-catenin phosphorylation and resulting in accumulation in the cytoplasm of CRCs. Besides, we propose that the phase separation ability of Axin participates in the nucleus translocation of ß-catenin and be incorporated and concentrated into transcriptional condensates, affecting the transcriptional activity of Wnt signaling pathway.

A statistical deformation model-based data augmentation method for volumetric medical image segmentation.

The accurate delineation of organs-at-risk (OARs) is a crucial step in treatment planning during radiotherapy, as it minimizes the potential adverse effects of radiation on surrounding healthy organs. However, manual contouring of OARs in computed tomography (CT) images is labor-intensive and susceptible to errors, particularly for low-contrast soft tissue. Deep learning-based artificial intelligence algorithms surpass traditional methods but require large datasets. Obtaining annotated medical images is both time-consuming and expensive, hindering the collection of extensive training sets. To enhance the performance of medical image segmentation, augmentation strategies such as rotation and Gaussian smoothing are employed during preprocessing. However, these conventional data augmentation techniques cannot generate more realistic deformations, limiting improvements in accuracy. To address this issue, this study introduces a statistical deformation model-based data augmentation method for volumetric medical image segmentation. By applying diverse and realistic data augmentation to CT images from a limited patient cohort, our method significantly improves the fully automated segmentation of OARs across various body parts. We evaluate our framework on three datasets containing tumor OARs from the head, neck, chest, and abdomen. Test results demonstrate that the proposed method achieves state-of-the-art performance in numerous OARs segmentation challenges. This innovative approach holds considerable potential as a powerful tool for various medical imaging-related sub-fields, effectively addressing the challenge of limited data access.

Volumetric tumor tracking from a single cone-beam X-ray projection image enabled by deep learning.

Radiotherapy serves as a pivotal treatment modality for malignant tumors. However, the accuracy of radiotherapy is significantly compromised due to respiratory-induced fluctuations in the size, shape, and position of the tumor. To address this challenge, we introduce a deep learning-anchored, volumetric tumor tracking methodology that employs single-angle X-ray projection images. This process involves aligning the intraoperative two-dimensional (2D) X-ray images with the pre-treatment three-dimensional (3D) planning Computed Tomography (CT) scans, enabling the extraction of the 3D tumor position and segmentation. Prior to therapy, a bespoke patient-specific tumor tracking model is formulated, leveraging a hybrid data augmentation, style correction, and registration network to create a mapping from single-angle 2D X-ray images to the corresponding 3D tumors. During the treatment phase, real-time X-ray images are fed into the trained model, producing the respective 3D tumor positioning. Rigorous validation conducted on actual patient lung data and lung phantoms attests to the high localization precision of our method at lowered radiation doses, thus heralding promising strides towards enhancing the precision of radiotherapy.

Association between late gadolinium enhancement and outcome in dilated cardiomyopathy: A meta-analysis.

BACKGROUND: The prognostic value of late gadolinium enhancement (LGE) derived from cardiovascular magnetic resonance (CMR) is well studied, and several new metrics of LGE have emerged. However, some controversies remain; therefore, further discussion is needed, and more precise risk stratification should be explored. AIM: To investigate the associations between the positivity, extent, location, and pattern of LGE and multiple outcomes in dilated cardiomyopathy (DCM). METHODS: PubMed, Ovid MEDLINE, and Cochrane Library were searched for studies that investigated the prognostic value of LGE in patients with DCM. Pooled hazard ratios (HRs) and 95% confidence intervals were calculated to assess the role of LGE in the risk stratification of DCM. RESULTS: Nineteen studies involving 7330 patients with DCM were included in this meta-analysis and covered a wide spectrum of DCM, with a mean left ventricular ejection fraction between 21% and 50%. The meta-analysis revealed that the presence of LGE was associated with an increased risk of multiple adverse outcomes (all-cause mortality, HR: 2.14; arrhythmic events, HR: 5.12; and composite endpoints, HR: 2.38; all P < 0.001). Furthermore, every 1% increment in the extent of LGE was associated with an increased risk of all-cause mortality. Analysis of a subgroup revealed that the prognostic value varied based on different location and pattern of LGE. Additionally, we found that LGE was a stronger predictor of arrhythmic events in patients with greater left ventricular ejection fraction. CONCLUSION: LGE by CMR in patients with DCM exhibited a substantial value in predicting adverse outcomes, and the extent, location, and pattern of LGE could provide additional information for risk stratification.

Volumetric feature points integration with bio-structure-informed guidance for deformable multi-modal CT image registration.

Objective.Medical image registration represents a fundamental challenge in medical image processing. Specifically, CT-CBCT registration has significant implications in the context of image-guided radiation therapy (IGRT). However, traditional iterative methods often require considerable computational time. Deep learning based methods, especially when dealing with low contrast organs, are frequently entangled in local optimal solutions.Approach.To address these limitations, we introduce a registration method based on volumetric feature points integration with bio-structure-informed guidance. Surface point cloud is generated from segmentation labels during the training stage, with both the surface-registered point pairs and voxel feature point pairs co-guiding the training process, thereby achieving higher registration accuracy.Main results.Our findings have been validated on paired CT-CBCT datasets. In comparison with other deep learning registration methods, our approach has improved the precision by 6%, reaching a state-of-the-art status.Significance.The integration of voxel feature points and bio-structure feature points to guide the training of the medical image registration network has achieved promising results. This provides a meaningful direction for further research in medical image registration and IGRT.

The negative effect of concomitant medications on immunotherapy in non-small cell lung cancer: An umbrella review.

BACKGROUND: Conflicting results about the effect of concomitant medications on immunotherapy in non-small cell lung cancer (NSCLC) were reported by many meta-analyses (MAs), and the certainty of evidence linking concomitant medications with immunotherapy efficacy has not been quantified, which may cause some evidence to be misinterpreted. METHODS: Four databases including Embase, Cochrane Library, PubMed, and Web of Science were searched from inception to January 2023 in English. Based on prospective or retrospective clinical controlled trials including immunotherapy with concomitant medications or not in NSCLC, quantitative MAs reporting the efficacy of immunotherapy with binary direct comparison and enough extractable data were collected. The methodological quality, reporting quality, and risk of bias of included MAs were evaluated respectively. New meta-analyses were conducted and their evidence certainty was classified as nonsignificant, weak, suggestive, highly suggestive, or convincing. RESULTS: Fifteen MAs with 5 medications were included. After being assessed by AMSTAR-2, PRISMA, and ROBIS, the major shortcomings were focused on the registration of protocol, literature retrieval or data extraction, implementation of sensitivity analysis or evidence certainty assessment, and incomplete reporting in the section of method and result. New pooled analyses indicated that antibiotics (HR = 1.545[1.318-1.811]), steroids (HR = 1.784[1.520-2.093]), proton pump inhibitors (PPIs) (HR = 1.303[1.048-1.621]) and opioids (HR = 1.910[1.213-3.006]) could shorten overall survival (OS) in patients with NSCLC receiving immunotherapy. Besides, antibiotics (HR = 1.285[1.129-1.462]) and steroids (HR = 1.613[1.315-1.979]) were harmful to progression-free survival (PFS) in these patients significantly. No negative effect was found in nonsteroidal anti-inflammatory drugs and the objective response rate of all medications. High-level evidence suggested that using PPIs before or after the initiation of immunotherapy and using steroids during the first-course immunotherapy could weaken the OS of patients with NSCLC. Meanwhile, the negative effects of antibiotics and opioids on OS or PFS were only supported by moderate or low-level evidence. CONCLUSIONS: The concurrent usage of PPIs or steroids adversely affects the survival of patients with NSCLC receiving immunotherapy. Future investigations are required to ascertain whether these adverse effects are primarily attributed to the comorbidities or the concurrent medications.

StMLP1, as a Kunitz trypsin inhibitor, enhances potato resistance and specifically expresses in vascular bundles during Ralstonia solanacearum infection.

Miraculin-like proteins (MLPs), members of the Kunitz trypsin inhibitor (KTI) family that are present in various plants, have been discovered to have a role in defending plants against pathogens. In this study, we identified a gene StMLP1 in potato that belongs to the KTI family. We found that the expression of StMLP1 gradually increases during Ralstonia solanacearum (R. solanacearum) infection. We characterized the promoter of StMLP1 as an inducible promoter that can be triggered by R. solanacearum and as a tissue-specific promoter with specificity for vascular bundle expression. Our findings demonstrate that StMLP1 exhibits trypsin inhibitor activity, and that its signal peptide is essential for proper localization and function. Overexpression of StMLP1 in potato can enhance the resistance to R. solanacearum. Inhibiting the expression of StMLP1 during infection accelerated the infection by R. solanacearum to a certain extent. In addition, the RNA-seq results of the overexpression-StMLP1 lines indicated that StMLP1 was involved in potato immunity. All these findings in our study reveal that StMLP1 functions as a positive regulator that is induced and specifically expressed in vascular bundles in response to R. solanacearum infection.

Advance of echocardiography in cardiac amyloidosis.

Cardiac amyloidosis (CA) occurs when the insoluble fibrils formed by misfolded precursor proteins deposit in cardiac tissues. The early clinical manifestations of CA are not evident, but it is easy to progress to refractory heart failure with an inferior prognosis. Echocardiography is the most commonly adopted non-invasive modality of imaging to visualize cardiac structures and functions, and the preferred modality in the evaluation of patients with cardiac symptoms and suspected CA, which plays a vital role in the diagnosis, prognosis, and long-term management of CA. The present review summarizes the echocardiographic manifestations of CA, new echocardiographic techniques, and the application of multi-parametric echocardiographic models in CA diagnosis.

An unsupervised dual contrastive learning framework for scatter correction in cone-beam CT image.

PURPOSE: Cone-beam computed tomography (CBCT) is widely utilized in modern radiotherapy; however, CBCT images exhibit increased scatter artifacts compared to planning CT (pCT), compromising image quality and limiting further applications. Scatter correction is thus crucial for improving CBCT image quality. METHODS: In this study, we proposed an unsupervised contrastive learning method for CBCT scatter correction. Initially, we transformed low-quality CBCT into high-quality synthetic pCT (spCT) and generated forward projections of CBCT and spCT. By computing the difference between these projections, we obtained a residual image containing image details and scatter artifacts. Image details primarily comprise high-frequency signals, while scatter artifacts consist mainly of low-frequency signals. We extracted the scatter projection signal by applying a low-pass filter to remove image details. The corrected CBCT (cCBCT) projection signal was obtained by subtracting the scatter artifacts projection signal from the original CBCT projection. Finally, we employed the FDK reconstruction algorithm to generate the cCBCT image. RESULTS: To evaluate cCBCT image quality, we aligned the CBCT and pCT of six patients. In comparison to CBCT, cCBCT maintains anatomical consistency and significantly enhances CT number, spatial homogeneity, and artifact suppression. The mean absolute error (MAE) of the test data decreased from 88.0623 ± 26.6700 HU to 17.5086 ± 3.1785 HU. The MAE of fat regions of interest (ROIs) declined from 370.2980 ± 64.9730 HU to 8.5149 ± 1.8265 HU, and the error between their maximum and minimum CT numbers decreased from 572.7528 HU to 132.4648 HU. The MAE of muscle ROIs reduced from 354.7689 ± 25.0139 HU to 16.4475 ± 3.6812 HU. We also compared our proposed method with several conventional unsupervised synthetic image generation techniques, demonstrating superior performance. CONCLUSIONS: Our approach effectively enhances CBCT image quality and shows promising potential for future clinical adoption.