LRFNet: A real-time medical image fusion method guided by detail information.

Multimodal medical image fusion (MMIF) technology plays a crucial role in medical diagnosis and treatment by integrating different images to obtain fusion images with comprehensive information. Deep learning-based fusion methods have demonstrated superior performance, but some of them still encounter challenges such as imbalanced retention of color and texture information and low fusion efficiency. To alleviate the above issues, this paper presents a real-time MMIF method, called a lightweight residual fusion network. First, a feature extraction framework with three branches is designed. Two independent branches are used to fully extract brightness and texture information. The fusion branch enables different modal information to be interactively fused at a shallow level, thereby better retaining brightness and texture information. Furthermore, a lightweight residual unit is designed to replace the conventional residual convolution in the model, thereby improving the fusion efficiency and reducing the overall model size by approximately 5 times. Finally, considering that the high-frequency image decomposed by the wavelet transform contains abundant edge and texture information, an adaptive strategy is proposed for assigning weights to the loss function based on the information content in the high-frequency image. This strategy effectively guides the model toward preserving intricate details. The experimental results on MRI and functional images demonstrate that the proposed method exhibits superior fusion performance and efficiency compared to alternative approaches. The code of LRFNet is available at https://github.com/HeDan-11/LRFNet.

Multilocus Sequence Analysis and Detection of Copper Ion Resistance of Xanthomonas phaseoli pv. manihotis Causing Bacterial Blight in Cassava.

Cassava (Manihot esculenta Crantz) is an important tropical tuber crop around the world. Cassava bacterial blight, caused by Xanthomonas phaseoli pv. manihotis, is a key disease that influences cassava production worldwide. Between 2008 and 2020, 50 X. phaseoli pv. manihotis strains were isolated from diseased plant samples or acquired from China, Uganda, Cambodia, Colombia, Malaysia, and Micronesia. Using multilocus sequence analysis, the genetic diversity of X. phaseoli pv. manihotis strains was evaluated. A neighbor-joining phylogenetic dendrogram was constructed based on partial sequences of five housekeeping genes (atpD-dnaK-gyrB-efp-rpoD). The strains clustered into three groups whose clusters were consistent with atpD and RpoD gene sequences. Group I contained 46 strains from China, Uganda, Cambodia, and Micronesia, and the other two groups were comprised of strains from Colombia and Malaysia, respectively. The resistance of all these strains to copper ion (Cu2+) was determined, the minimal inhibitory concentration was between 1.3 and 1.7 mM, and there was no significant difference between strains from different geographic region. During genome annotation of the X. phaseoli pv. manihotis strain CHN01, homologous gene clusters of copLAB and xmeRSA were identified. The predicted amino acid sequences of two gene clusters were highly homologous with the copper-resistant protein from Xanthomonas strains. CopLAB and xmeRSA were amplified from all these strains, suggesting that the regulation of copper resistance is associated with two distinct metabolic pathways. CopLAB and xmeRSA were highly conserved among strains from different geographic regions, possibly associated with other conserved function.

Evaluating the screening value of serum light chain ratio, ß2 microglobulin, lactic dehydrogenase and immunoglobulin in patients with multiple myeloma using ROC curves.

OBJECTIVE: Several laboratory and imaging assays are required to diagnose multiple myeloma (MM). Serum and urine immunofixation electrophoresis are two key assays to diagnose MM, while they have not been extensively utilized in Chinese hospitals. Serum light chain (sLC), ß2 microglobulin (ß2-MG), lactic dehydrogenase (LDH), and immunoglobulin (Ig) are routinely measured in the majority of Chinese hospitals. Imbalance of sLC ratio (involved light chain/uninvolved light chain) is frequently observed in MM patients. This study aimed to evaluate the screening value of sLC ratio, ß2-MG, LDH, and Ig in MM patients using receiver operating characteristic (ROC) curves. METHODS: Data of 303 suspected MM patients, who were admitted to the Taizhou Central Hospital between March 2015 and July 2021, were retrospectively analyzed. In total, 69 patients (MM arm) met the International Myeloma Working Group (IMWG) updated criteria for the diagnosis of MM, while 234 patients were non-MM (non-MM arm). All patients' sLC, ß2-MG, LDH, and Ig were measured using commercially available kits according to the manufacturer's instructions. The ROC curve analysis was employed to assess the screening value of sLC ratio, ß2-MG, LDH, creatinine (Cr) and Ig. The statistical analysis was carried out by SPSS 26.0 (IBM, Armonk, NY, USA) and MedCalc 19.0.4 (Ostend, Belgium) software. RESULTS: There was no significant difference between the MM and non-MM arms in terms of gender, age and Cr. The median sLC ratio in the MM arm was 11.5333, which was significantly higher than that of 1.9293 in the non-MM arm (P<0.001). The area under the curve (AUC) of sLC ratio was 0.875, which indicated a robust screening value. The optimal sensitivity and specificity were 81.16% and 94.87% respectively, when the sLC ratio was set as 3.2121. The serum levels of ß2-MG and Ig were higher in the MM arm than those in the non-MM arm (P<0.001). The AUC values of ß2-MG, LDH, and Ig were 0.843 (P<0.001), 0.547 (P = 0.2627), and 0.723 (P<0.001), respectively. The optimal cutoff values of ß2-MG, LDH, and Ig were 1.95 mg/L, 220 U/L, and 46.4 g/L respectively, in the context of screening value. The triple combination of sLC ratio (3.2121), ß2-MG (1.95 mg/L), and Ig (46.4 g/L) yielded a higher screening value compared with that of sLC ratio alone (AUC, 0.952; P<0.0001). The triple combination had a sensitivity of 94.20% and a specificity of 86.75%. The addition of LDH to the triple combination and formation of quadruple combination did not optimize the screening value, with AUC, sensitivity, and specificity of 0.952, 94.20%, and 85.47%, respectively. CONCLUSION: The triple combination strategy (sLC ratio, 3.2121; ß2-MG, 1.95 mg/L; Ig, 46.4 g/L) is accompanied by remarkable sensitivity and specificity for screening MM in Chinese hospitals.

Hypoxia and TNF-α Synergistically Induce Expression of IL-6 and IL-8 in Human Fibroblast-like Synoviocytes via Enhancing TAK1/NF-κB/HIF-1α Signaling.

Hypoxia and increased levels of inflammatory cytokines in the joints are characteristics of rheumatoid arthritis (RA). However, the effects of hypoxia and tumor necrosis factor-α (TNF-α) on interleukin (IL)-6 and IL-8 production on fibroblast-like synoviocytes (FLSs) remain to be clarified. This study aimed to explore how hypoxia and TNF-α affect the expression of IL-6 and IL-8 in human FLSs isolated from RA patients. Hypoxia or TNF-α treatment alone significantly increased the expression and promoter activity of IL-6, IL-8, and hypoxia-inducible factor-1α (HIF-1α). Treatment of hypoxic FLSs with TNF-α further significantly elevated the expression of these cytokines and enhanced promoter activity of HIF-1α, which was abrogated by treatment with the HIF-1α inhibitor YC-1. Similarly, TNF-α alone elevated the phosphorylation and promoter activity of nuclear factor-κBp65 (NF-κBp65) in the FLSs. These effects were further enhanced by the combined treatment of hypoxia and TNFα but were attenuated by the NF-κB inhibitor BAY11-7082. NF-κB-p65 inhibition decreased the effect of TNF-α on HIF-1α upregulation in the FLSs in response to hypoxia. The combination of hypoxia and TNF-α also significantly upregulated transforming growth factor-ß-activated kinase 1 (TAK1) expression, and silencing TAK1 dramatically decreased NF-κB-p65, HIF-1α, IL-6, and IL-8 expression under the same conditions. Our results indicate that hypoxia and TNF-α synergistically increase IL-6 and IL-8 expression in human FLSs via enhancing TAK1/NF-κB/HIF-1α signaling.

The effectiveness of web-based interventions on non-alcoholic fatty liver disease (NAFLD) in obese children: A study protocol for a randomized controlled trial.

Aim: Non-alcoholic fatty liver disease (NAFLD) is currently the most prevalent liver disease in the world, increasing the risk of cirrhosis and hepatocellular carcinoma, and contributing to the development of type 2 diabetes, cardiovascular disease, and chronic kidney disease. This study aims to carry out a web-based continuum of a care intervention model to provide comprehensive care interventions for obese children with NAFLD, to improve the effectiveness of treatment of children with NAFLD. Design: A 1-year single-blinded randomized clinical trial in hospital in Zhejiang Province. Methods: Eighty subjects will implement the program in a randomized order. The interventions for the control group mainly consisted of the routine distribution of health education materials and health education by holding health-themed lectures, and the preliminary proposed interventions including establishing management teams, regularly delivering related health knowledge, daily uploading of health intervention records, regular supervision and mutual encouragement, home visiting and psychological guidance. The primary outcomes are serum biomarkers such as alanine aminotransferase (ALT) and gamma-glutamyl transferase (GGT), aspartate aminotransferase, and imaging (liver ultrasound and magnetic resonance imaging). Second outcomes are: BMI, waist-to-hip ratio and quality of life. In addition, socio-demographic characteristics such as age, gender and ethnicity will be recorded. Children aged 7-18 years old and diagnosed with NAFLD will be included, patients will be not eligible if they do not agree to participate or are participating in other health intervention programs. This study was registered on ClinicalTrials.gov (NCT05527938). Results: Over the past 30 years, NAFLD has been recognized as one of the most common liver diseases in adults and children. The current studies have focused on promoting lifestyle changes in children with NASH by providing some education and advice to children and their families to improve the histological features of NASH and lose weight. Because of the convenience and efficiency of the internet can provide some new strategies and ways for lifestyle interventions for children with NAFLD. In addition, we have designed a high-quality RCT based on the SPIRIT guidelines, which also provides strong evidence in this area.

Medical Image Fusion and Denoising Algorithm Based on a Decomposition Model of Hybrid Variation-Sparse Representation.

Medical image fusion technology integrates the contents of medical images of different modalities, thereby assisting users of medical images to better understand their meaning. However, the fusion of medical images corrupted by noise remains a challenge. To solve the existing problems in medical image fusion and denoising algorithms related to excessive blur, unclean denoising, gradient information loss, and color distortion, a novel medical image fusion and denoising algorithm is proposed. First, a new image layer decomposition model based on hybrid variation-sparse representation and weighted Schatten p-norm is proposed. The alternating direction method of multipliers is used to update the structure, detail layer dictionary, and detail layer coefficient map of the input image while denoising. Subsequently, appropriate fusion rules are employed for the structure layers and detail layer coefficient maps. Finally, the fused image is restored using the fused structure layer, detail layer dictionary, and detail layer coefficient maps. A large number of experiments confirm the superiority of the proposed algorithm over other algorithms. The proposed medical image fusion and denoising algorithm can effectively remove noise while retaining the gradient information without color distortion.

A multiscale double-branch residual attention network for anatomical-functional medical image fusion.

Medical image fusion technology synthesizes complementary information from multimodal medical images. This technology is playing an increasingly important role in clinical applications. In this paper, we propose a new convolutional neural network, which is called the multiscale double-branch residual attention (MSDRA) network, for fusing anatomical-functional medical images. Our network contains a feature extraction module, a feature fusion module and an image reconstruction module. In the feature extraction module, we use three identical MSDRA blocks in series to extract image features. The MSDRA block has two branches. The first branch uses a multiscale mechanism to extract features of different scales with three convolution kernels of different sizes, while the second branch uses six 3 × 3 convolutional kernels. In addition, we propose the Feature L1-Norm fusion strategy to fuse the features obtained from the input images. Compared with the reference image fusion algorithms, MSDRA consumes less fusion time and achieves better results in visual quality and the objective metrics of Spatial Frequency (SF), Average Gradient (AG), Edge Intensity (EI), Quality-Aware Clustering (QAC), Variance (VAR), and Visual Information Fidelity for Fusion (VIFF).

Medical image fusion based on hybrid three-layer decomposition model and nuclear norm.

The aim of medical image fusion technology is to synthesize multiple-image information to assist doctors in making scientific decisions. Existing studies have focused on preserving image details while avoiding halo artifacts and color distortions. This paper proposes a novel medical image fusion algorithm based on this research objective. First, the input image is decomposed into structure, texture, and local mean brightness layers using a hybrid three-layer decomposition model that can fully extract the features of the original images without the introduction of artifacts. Secondly, the nuclear norm of the patches, which are obtained using a sliding window, are calculated to construct the weight maps of the structure and texture layers. The weight map of the local mean brightness layer is constructed by calculating the local energy. Finally, remapping functions are applied to enhance each fusion layer, which reconstructs the final fusion image with the inverse operation of decomposition. Subjective and objective experiments confirm that the proposed algorithm has a distinct advantage compared with other state-of-the-art algorithms.

Genome and transcriptome analysis of the fungal pathogen Fusarium oxysporum f. sp. cubense causing banana vascular wilt disease.

BACKGROUND: The asexual fungus Fusarium oxysporum f. sp. cubense (Foc) causing vascular wilt disease is one of the most devastating pathogens of banana (Musa spp.). To understand the molecular underpinning of pathogenicity in Foc, the genomes and transcriptomes of two Foc isolates were sequenced. METHODOLOGY/PRINCIPAL FINDINGS: Genome analysis revealed that the genome structures of race 1 and race 4 isolates were highly syntenic with those of F. oxysporum f. sp. lycopersici strain Fol4287. A large number of putative virulence associated genes were identified in both Foc genomes, including genes putatively involved in root attachment, cell degradation, detoxification of toxin, transport, secondary metabolites biosynthesis and signal transductions. Importantly, relative to the Foc race 1 isolate (Foc1), the Foc race 4 isolate (Foc4) has evolved with some expanded gene families of transporters and transcription factors for transport of toxins and nutrients that may facilitate its ability to adapt to host environments and contribute to pathogenicity to banana. Transcriptome analysis disclosed a significant difference in transcriptional responses between Foc1 and Foc4 at 48 h post inoculation to the banana 'Brazil' in comparison with the vegetative growth stage. Of particular note, more virulence-associated genes were up regulated in Foc4 than in Foc1. Several signaling pathways like the mitogen-activated protein kinase Fmk1 mediated invasion growth pathway, the FGA1-mediated G protein signaling pathway and a pathogenicity associated two-component system were activated in Foc4 rather than in Foc1. Together, these differences in gene content and transcription response between Foc1 and Foc4 might account for variation in their virulence during infection of the banana variety 'Brazil'. CONCLUSIONS/SIGNIFICANCE: Foc genome sequences will facilitate us to identify pathogenicity mechanism involved in the banana vascular wilt disease development. These will thus advance us develop effective methods for managing the banana vascular wilt disease, including improvement of disease resistance in banana.

Enterobacter mori sp. nov., associated with bacterial wilt on Morus alba L.

Two isolates of mulberry-pathogenic bacteria isolated from diseased mulberry roots were investigated in a polyphasic taxonomic study. Comparative 16S rRNA gene sequence analysis combined with rpoB gene sequence analysis allocated strains R18-2(T) and R3-3 to the genus Enterobacter, with Enterobacter asburiae, E. amnigenus, E. cancerogenus, E. cloacae subsp. cloacae, E. cloacae subsp. dissolvens and E. nimipressuralis as their closest relatives. Cells of the isolates were Gram-negative, facultatively anaerobic rods, 0.3-1.0 µm wide and 0.8-2.0 µm long, with peritrichous flagella, showing a DNA G+C content of 55.1 ± 0.5 mol%. Calculation of a similarity index based on phenotypic features and fatty acid methyl ester (FAME) analysis suggested that these isolates are members of E. cancerogenus or E. asburiae or a closely related species. Biochemical data revealed that the isolates could be differentiated from their nearest neighbours by the presence of lysine decarboxylase activity and their ability to utilize d-arabitol. DNA-DNA relatedness also distinguished the two isolates from phylogenetically closely related Enterobacter strains. Based on these data, it is proposed that the isolates represent a novel species of the genus Enterobacter, named Enterobacter mori sp. nov. The type strain is R18-2(T) ( = CGMCC 1.10322(T) = LMG 25706(T)).

Enterobacter spp.: a new evidence causing bacterial wilt on mulberry.

Thirty-six pathogenetic bacterial strains were isolated from wilted mulberry plants in Hangzhou, Zhejiang province of China. The six representative strains were confirmed to be involved in more than one Enterobacter species by common bacteriological test, electron microscope observation, hypersensitive reaction, Koch's postulates, physiological and biochemical test, biology, fatty acid methyl esters analysis (FAMEs), enterobacterial repetitive intergenic consensus-PCR (ERIC-PCR), 16s rRNA sequences analysis, and comparative analysis with 7 type strains and 3 reference strains. This is the first report on mulberry disease caused by Enterobacter spp. in the world providing new evidence on induction of the plant disease in this genus. The results are not only important in the mulberry disease management but also have significant scientific value for further studies of opportunistic human pathogens and environmental strains in Enterobacter.