Dual-domain faster Fourier convolution based network for MR image reconstruction.

Deep learning methods for fast MRI have shown promise in reconstructing high-quality images from undersampled multi-coil k-space data, leading to reduced scan duration. However, existing methods encounter challenges related to limited receptive fields in dual-domain (k-space and image domains) reconstruction networks, rigid data consistency operations, and suboptimal refinement structures, which collectively restrict overall reconstruction performance. This study introduces a comprehensive framework that addresses these challenges and enhances MR image reconstruction quality. Firstly, we propose Faster Inverse Fourier Convolution (FasterIFC), a frequency domain convolutional operator that significantly expands the receptive field of k-space domain reconstruction networks. Expanding the information extraction range to the entire frequency spectrum according to the spectral convolution theorem in Fourier theory enables the network to easily utilize richer redundant long-range information from adjacent, symmetrical, and diagonal locations of multi-coil k-space data. Secondly, we introduce a novel softer Data Consistency (softerDC) layer, which achieves an enhanced balance between data consistency and smoothness. This layer facilitates the implementation of diverse data consistency strategies across distinct frequency positions, addressing the inflexibility observed in current methods. Finally, we present the Dual-Domain Faster Fourier Convolution Based Network (D2F2), which features a centrosymmetric dual-domain parallel structure based on FasterIFC. This architecture optimally leverages dual-domain data characteristics while substantially expanding the receptive field in both domains. Coupled with the softerDC layer, D2F2 demonstrates superior performance on the NYU fastMRI dataset at multiple acceleration factors, surpassing state-of-the-art methods in both quantitative and qualitative evaluations.

High-Q metasurface signal isolator for 1.5T surface coil magnetic resonance imaging on the go.

The combination of surface coils and metamaterials remarkably enhance magnetic resonance imaging (MRI) performance for significant local staging flexibility. However, due to the coupling in between, impeded signal-to-noise ratio (SNR) and low-contrast resolution, further hamper the future growth in clinical MRI. In this paper, we propose a high-Q metasurface decoupling isolator fueled by topological LC loops for 1.5T surface coil MRI system, increasing the magnetic field up to fivefold at 63.8 MHz. We have employed a polarization conversion mechanism to effectively eliminate the coupling between the MRI metamaterial and the radio frequency (RF) surface transmitter-receiver coils. Furthermore, a high-Q metasurface isolator was achieved by taking advantage of bound states in the continuum (BIC) for extremely high-resolution MRI and spectroscopy. An equivalent physical model of the miniaturized metasurface design was put forward through LC circuit analysis. This study opens up a promising route for the easy-to-use and portable surface coil MRI scanners.

DIRECTION: Deep cascaded reconstruction residual-based feature modulation network for fast MRI reconstruction.

Deep cascaded networks have been extensively studied and applied to accelerate Magnetic Resonance Imaging (MRI) and have shown promising results. Most existing works employ a large cascading number for the sake of superior performances. However, due to the lack of proper guidance, the reconstruction performance can easily reach a plateau and even face degradation if simply increasing the cascading number. In this paper, we aim to boost the reconstruction performance from a novel perspective by proposing a parallel architecture called DIRECTION that fully exploits the guiding value of the reconstruction residual of each subnetwork. Specifically, we introduce a novel Reconstruction Residual-Based Feature Modulation Mechanism (RRFMM) which utilizes the reconstruction residual of the previous subnetwork to guide the next subnetwork at the feature level. To achieve this, a Residual Attention Modulation Block (RAMB) is proposed to generate attention maps using multi-scale residual features to modulate the image features of the corresponding scales. Equipped with this strategy, each subnetwork within the cascaded network possesses its unique optimization objective and emphasis rather than blindly updating its parameters. To further boost the performance, we introduce the Cross-Stage Feature Reuse Connection (CSFRC) and the Reconstruction Dense Connection (RDC), which can reduce information loss and enhance representative ability. We conduct sufficient experiments and evaluate our method on the fastMRI knee dataset using multiple subsampling masks. Comprehensive experimental results show that our method can markedly boost the performance of cascaded networks and significantly outperforms other compared state-of-the-art methods quantitatively and qualitatively.

The government-production nexus of energy efficiency in China's construction industry: regional difference and factor analysis.

For decades, the construction industry has contributed significantly to China's economic growth. The heavy energy consumption inevitably leads to the release of large amounts of carbon emissions. Improving energy efficiency has been a crucial solution for mitigating the environmental impacts while boosting its green economy in the construction industry. Measuring the energy efficiency in the construction industry considering the quality of government sector is still limited. Using panel provincial data in China from 2011 to 2020, this paper proposes a two-stage dynamic data envelopment analysis (DEA) framework integrating the government sector with the production sector in the construction industry, and calculates energy efficiency. The spatial Durbin model is used to analyze the driving forces of energy efficiency. The research findings include (1) the energy efficiency in the eastern region is higher than that in the central and western regions. The mean values of energy efficiency in the eastern, central, and western regions are 0.42, 0.34, and 0.37. (2) Even though governance efficiency is lower than production efficiency, there is a positive correlation between governance efficiency and production efficiency with a correlation coefficient of 0.48. Improving governance efficiency is a significant step to increase the production efficiency and further increase energy efficiency of the construction industry. (3) Digital transformation has a positive effect on governance efficiency but has no effect on production efficiency. The government-production nexus framework provides implications for clarifying the role of government intervention in improving energy efficiency.

Cluster Analysis on Gastrointestinal Symptoms during Menopausal Transition.

The purpose of this secondary analysis was to determine the clusters of midlife women by gastrointestinal (GI) symptoms and to explore differences in the clusters by race/ethnicity. This analysis used the data from two internet-based studies among 1,054 midlife women. The analysis was conducted with the data on background characteristics, health and menopausal status, and GI symptoms (collected using the GI Symptom Index for Midlife Women). The data were analyzed using factor analyses, hierarchical cluster analyses, chi-square tests, multinomial logistic regression analyses, and analyses of covariance. Three clusters were adopted: Cluster 1 (with low total numbers and severity scores of symptoms; 46.0%), Cluster 2 (with moderate total numbers and severity scores of symptoms; 44.0%), and Cluster 3 (with high total numbers and severity scores of symptoms; 10.0%). Only in Cluster 2, there were significant racial/ethnic differences in individual GI symptoms. These results provide directions for future GI symptom management among midlife women.

Dual-domain reconstruction network with V-Net and K-Net for fast MRI.

PURPOSE: To introduce a dual-domain reconstruction network with V-Net and K-Net for accurate MR image reconstruction from undersampled k-space data. METHODS: Most state-of-the-art reconstruction methods apply U-Net or cascaded U-Nets in the image domain and/or k-space domain. Nevertheless, these methods have the following problems: (1) directly applying U-Net in the k-space domain is not optimal for extracting features; (2) classical image-domain-oriented U-Net is heavyweighted and hence inefficient when cascaded many times to yield good reconstruction accuracy; (3) classical image-domain-oriented U-Net does not make full use of information of the encoder network for extracting features in the decoder network; and (4) existing methods are ineffective in simultaneously extracting and fusing features in the image domain and its dual k-space domain. To tackle these problems, we present 3 different methods: (1) V-Net, an image-domain encoder-decoder subnetwork that is more lightweight for cascading and effective in fully utilizing features in the encoder for decoding; (2) K-Net, a k-space domain subnetwork that is more suitable for extracting hierarchical features in the k-space domain, and (3) KV-Net, a dual-domain reconstruction network in which V-Nets and K-Nets are effectively combined and cascaded. RESULTS: Extensive experimental results on the fastMRI dataset demonstrate that the proposed KV-Net can reconstruct high-quality images and outperform state-of-the-art approaches with fewer parameters. CONCLUSIONS: To reconstruct images effectively and efficiently from incomplete k-space data, we have presented a dual-domain KV-Net to combine K-Nets and V-Nets. The KV-Net achieves better results with 9% and 5% parameters than comparable methods (XPD-Net and i-RIM).

Immigration transition and gastrointestinal symptoms during menopausal transition: midlife women in the US.

OBJECTIVES: This study aimed to explore the associations of immigration transition to gastrointestinal (GI) symptoms experienced during the menopausal transition among 974 midlife women in the US. METHODS: The data from 974 midlife women from 2 national Internet survey studies were used for this secondary analysis. Only the data related to background characteristics and, health/menopausal status, immigration transition, and the Gastrointestinal Symptom Index for Midlife Women were included. The data were analyzed using descriptive and inferential statistics including analyses of covariance, logistic regression analyses, and hierarchical multiple regression analyses. RESULTS: There were statistical differences in total numbers and total severity scores of total GI symptoms between immigrants and nonimmigrants (F = 7.08 and 6.20, respectively; both P < 0.05); Immigrants had fewer total numbers and lower total severity scores of GI symptoms than nonimmigrants. All immigration transition variables including immigration status, the length of stay in the US, and the acculturation level accounted for 11.8% of the total numbers (F = 32.79, P < 0.001) and 12.5% of the total severity scores of GI symptoms (F = 35.10, P < 0.001). However, only immigration status (being nonimmigrant) was a significant factor that was associated with greater total numbers and higher total severity scores of GI symptoms (ß = 0.62, P < 0.001 and ß = 0.65, P < 0.001, respectively). CONCLUSIONS: This study supports that immigration status is a significant factor that influences GI symptoms during the menopausal transition.

Effect of botulinum toxin type A on flap surgery in animal models: a systematic review and meta-analysis.

Flaps are common technical choices in aesthetic and reconstructive surgeries. However, the poor flap survival rate remains to be a difficult issue that troubles plastic surgeon. Recent research evidence supports that the use of Botulinum toxin type A (BTXA) can increase the flap survival rate. For verification, the present study was carried out to evaluate the effect of BTXA on flap surgery. Eight databases (PubMed, Cochrane Library, Ovid, Web of Science, Embase, Scopus, CBM, CNKI and WANFANG database) were searched for related published literature up to September 2020. A meta-analysis was then conducted to compare the effect of using BTXA with that of using saline or no treatment in flap surgery. Seventeen studies with a total of 565 animals were finally included in this review after strict exclusion and inclusion. Compared with saline/no treatment + flap group, BTXA + flap group showed a significantly higher flap tissue survival rate (mean difference [MD] 15.55, p < 0.00001), blood flow (standardized mean difference [SMD] 1.97, p < 0.00001) and vascular endothelial growth factor (VEGF) expression (at mRNA level: SMD 6.01, p = 0.02; at protein level: SMD 3.35, p < 0.00001). BTXA combined with flap surgery may have a positive effect on improving the flap tissue survival rate, blood flow of flaps and VEGF expression. Besides, the timing of BTXA injection may be an important factor for exerting its effect on flap surgery.

Bioinformatic analysis of differentially expressed genes as prognostic markers in pheochromocytoma and paraganglioma tumors.

The pathogenesis of pheochromocytoma and paraganglioma (PCPG) catecholamine-producing tumors is exceedingly complicated. Here, we sought to identify important genes affecting the prognosis and survival rate of patients suffering from PCPG. We analyzed 95 samples obtained from two microarray data series, GSE19422 and GSE60459, from the Gene Expression Omnibus (GEO) repository. First, differentially expressed genes (DEGs) were identified by comparing 87 PCPG tumor samples and eight normal adrenal tissue samples using R language. The GEO2R tool and Venn diagram software were applied to the Database for Annotation, Visualization and Integrated Discovery (DAVID) to analyze Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO). We further employed Cytoscape with the Molecular Complex Detection (MCODE) tool to make protein-protein interactions visible for the Search Tool for Retrieval of Interacting Genes (STRING). These procedures resulted in 30 candidate DEGs, which were subjected to Kaplan-Meier analysis and validated by Gene Expression Profiling Interactive Analysis (GEPIA) to determine their influence on overall survival rate. Finally, we identified ALDH3A2 and AKR1B1, two genes in the glycerolipid metabolism pathway, as being particularly enriched in PCPG tumors and correlated with T and B tumor-infiltrating immune cells. Our results suggest that these two DEGs are closely associated with the prognosis of malignant PCPG tumors.

Stigma and its influencing factors among breast cancer survivors in China: A cross-sectional study.

PURPOSE: Although stigma has attracted considerable scholarly attention, few studies have focused on its influencing factors among discharged breast cancer survivors, especially in a Chinese cultural context. The present study therefore explores stigma and its influencing factors among breast cancer survivors in China. METHOD: Between December 2017 and May 2018, 103 breast cancer survivors at the outpatient clinic of a tertiary cancer center in southern China were enrolled in a cross-sectional study. The research instruments comprised the Social Impact Scale (SIS), the General Self-Efficacy Scale (GSES), the Medical Coping Modes Questionnaire (MCMQ), and sociodemographic and disease-related questionnaires. Descriptive statistics, univariate analysis, and multivariable linear regression were used to explore the current status of stigma and to identify influencing factors. RESULTS: Of the respondents, 76.7% and 8.7%, respectively, reported moderate and high levels of stigma. The mean SIS score was 55.20 ± 12.15 (moderate), and the SIS subscale with the highest average score was financial insecurity. The results of a multivariable linear regression showed that body image (ß = 0.32, P＜0.001), spousal support (ß = -0.47, P < 0.001), personal acceptance of the disease (ß = -0.22, P＜0.001), coping modes (resignation) (ß = 0.14, P < 0.001), support from medical staff (ß = -0.23, P < 0.001) and self-efficacy (ß = -0.10, P = 0.037) were the main factors influencing stigma among breast cancer survivors (R2 = 0.83). CONCLUSIONS: Stigma, among breast cancer survivors, which is influenced by various sociocultural factors, is a neglected issue requiring attention. Healthcare professionals should therefore formulate effective measures for alleviating stigma in this group by improving their self-efficacy and acceptance of the disease, reducing their poor body image and negative coping mode, and eliciting more support from their spouses and medical staff.

A Bioinformatics Research on Novel Mechanism of Compound Kushen Injection for Treating Breast Cancer by Network Pharmacology and Molecular Docking Verification.

Compound Kushen injection (CKI) has been extensively used in treating breast cancer (BC). However, the molecular mechanism remains unclear. In this study, 16 active compounds of CKI were obtained from 3 articles for target prediction. Then, a compound-predicted target network and a compound-BC target network were conducted by Cytoscape 3.6.1. The gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the DAVID database. The binding energy between the key targets of CKI and the active compounds was studied by molecular docking. As a result, 16 active compounds of CKI were identified, corresponding to 285 putative targets. The key targets of CKI for BC are HSD11B1, DPP4, MMP9, CDK1, MMP2, PTGS2, and CA14. The function enrichment analysis obtained 13 GO entries and 6 KEGG pathways, including bladder cancer, cancer pathways, chemical carcinogenesis, estrogen signaling pathway, TNF signaling pathway, and leukocyte transendothelial migration. The result of molecular docking indicated that DPP4 had strong binding activity with matrine, alicyclic protein, and sophoridine, and MMP9 had strong binding activity with adenine and sophoridine. In conclusion, the therapeutic effect of CKI on BC is based on the overall pharmacological effect formed by the combined effects of multiple components, multiple targets, and multiple pathways. This study provides a theoretical basis for further experimental research in the future.

Comparative Efficacy and Safety of Chinese Herbal Injections Combined With Cyclophosphamide and 5-Fluorouracil Chemotherapies in Treatment of Breast Cancer: A Bayesian Network Meta-Analysis.

Background: Given the limitations of chemotherapy for the treatment of breast cancer (BC) and the wide exploration of Chinese herbal injections (CHIs), this network meta-analysis (NMA) was conducted to analyze the comparative efficacy and safety of nine CHIs combined with CF (Cyclophosphamide and 5-Fluorouracil) chemotherapy regimens in the treatment of BC. Methods: Several electronic databases were searched to identify randomized controlled trials (RCTs) from inception to January 6, 2020. RCTs were screened by pre-established eligibility criteria, and the quality of which was assessed using the Cochrane risk of bias tool. Outcomes such as the clinical effectiveness rate, performance status, peripheral hemogram, and detection of T-lymphocyte subsets were analyzed using the Winbugs 1.4.3 and Stata 13.0 software. Surface under the cumulative ranking curve (SUCRA) probability values were applied to rank the examined treatments. Cluster analysis was performed to compare the effect of CHIs between two or three different outcomes. Results: A total of 84 RCTs involving 7855 patients and nine CHIs were included. The results showed that compared to CF chemotherapy regimens alone, the ones injected along with Aidi, Shenmai, Shenqi Fuzheng, Kangai, Kanglaite, or Shengmai combined with CF can improve the clinical effectiveness rate. Aidi, Shenmai, Shenqi Fuzheng, Compound Kushen, Kangai, and Kanglaite injection combined with CF can improve the performance status. Shenqi Fuzheng injection was considered as a favorable choice for relieving adverse reactions. According to the results of cluster analysis, Aidi injection and Compound Kushen injection plus CF were more favorable for the clinical effectiveness rate and performance status. Conclusion: In conclusion, Shenqi Fuzheng, Compound Kushen, Aidi, and Kangai injection combined with CF chemotherapy regimen have more significant effects for patients with BC. However, more high-quality clinical RCTs, especialy which correctly use blinding and allocation concealment, are required to support the conclusions.