Magnetic resonance imaging (MRI), ultrasound (US), and contrast-enhanced ultrasound (CEUS) can provide different image data about uterus, which have been used in the preoperative assessment of ...endometrial cancer. In practice, not all the patients have complete multi-modality medical images due to the high cost or long examination period. Most of the existing methods need to perform data cleansing or discard samples with missing modalities, which will influence the performance of the model. In this work, we propose an incomplete multi-modality images data fusion method based on latent relation shared to overcome this limitation. The shared space contains the common latent feature representation and modality-specific latent feature representation from the complete and incomplete multi-modality data, which jointly exploits both consistent and complementary information among multiple images. The experimental results show that our method outperforms the current representative approaches in terms of classification accuracy, sensitivity, specificity, and area under curve (AUC). Furthermore, our method performs well under varying imaging missing rates.
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•An incomplete multi-modality medical images classification method is introduced•Latent relation shared learning boosts sensitivity in incomplete multimodality models•The fusion of MRI, US and CEUS methods enhances diagnostic performance
Cancer; Image-guided intervention; Machine learning
•The D-shaped fiber is deposited with Fe3O4 nanoparticles.•The stable dark solitons are obtained at the pump power of 350 mW.•The bright-dark soliton pairs are also observed at the pump power of ...400 mW.
The study presents the dark solitons generation in Er-doped mode-locked fiber laser based on ferroferric-oxide (Fe3O4) nanoparticles. The D-shaped fiber deposited with Fe3O4 nanoparticles is used as the birefringence and nonlinearity device. The dark solitons with repetition rate of 13.5 MHz are obtained in the pump power of 350 mW. The bright-dark soliton pairs are also observed by properly adjusting the polarization state at the pump power of 400 mW. The results in this paper demonstrate that Fe3O4 nanoparticles are the promising materials for generating dark solitons in fiber lasers.
Abnormal anillin (ANLN) expression has been observed in multiple tumours and is closely associated with patient prognosis and clinical features. In this study, we systematically elucidated the ...clinical significance and biological roles of ANLN in patients with clear cell renal cell carcinoma (ccRCC).
We obtained transcriptome and clinical data of patients with ccRCC from public databases. Multi-omics data and clinical samples were combined to analyse the correlation between ANLN expression and the clinical characteristics of patients with renal cancer. Additionally, the immune cell landscape of ANLN expression was evaluated using different immune algorithms in the tumour microenvironment. The tumour-promoting potential of ANLN was confirmed using in vitro assays, including CCK8 and Transwell assays.
Bioinformatics analysis showed that ANLN is over-expressed in patients with ccRCC, as validated by clinical samples. Publicly available clinical data suggest that high ANLN expression may indicate poor outcomes in patients with ccRCC. Moreover, biological function analysis revealed a marked enrichment of the cell cycle and PI3K-Akt pathways. The distribution of immune cells, particularly M2 macrophages, differed in patients with ccRCC. Furthermore, ANLN silencing inhibited the proliferation, migration, and invasion of renal cancer cells in vitro. After ANLN expression was knocked down in 786-O cells, the protein levels of important PI3K signalling pathway components, including PI3K, Akt, and mTOR, drastically decreased.
These findings suggest that ANLN is dysregulated in renal cancer tissues and promotes tumour progression by activating the PI3K/Akt/mTOR signalling pathway.
The UK is planning to ban the sale of fuel vehicles entirely by 2035 and electric vehicles will be a potential alternative to fuel vehicles. The increase in electric vehicles will increase the ...charging demand. Standalone charging stations are a potential solution to alleviate the grid challenges of increased charging demand. In this work, the authors investigate a reliability analysis of a 2 MW standalone photovoltaic electric vehicle charging station (PVEVCS) using the loss of power supply probability(LPSP). The PVEVCS model consists of a PV system, a battery energy storage system (BESS) and a CS, using the climate data from Camborne, UK and classifying it into high and low irradiation sections. Next, four different charging demand profiles are selected to examine the models’ LPSP. Later, the chosen charging demand profiles are optimised using various combinations of PV systems, BESS and CS. It is concluded that the different solar irradiation had a significant effect on the LPSP. Under the same combination, higher PV capacity has a more positive impact on reducing daytime LPSP, higher BESS capacity has a more significant effect on lowering nighttime LPSP and larger CS capacity has a more significant impact on declining hourly LPSP.
Cellular senescence is a tumor suppressive response in which the cell cycle is in a state of permanent arrest and can inhibit tumor cell proliferation. In recent years, induction of cellular ...senescence has been shown to be important for antitumor therapy, and the link between cellular senescence and clinical prognosis and immunotherapy of hepatocellular carcinoma is still unknown.
We performed enrichment analysis of genes in three cellular senescence gene sets, screened for gene sets significantly enriched in hepatocellular carcinoma and extracted genes from them. Signature were constructed using senescence-related genes, and their expression was verified at the protein and RNA levels. Survival, clinical staging and grading, immune infiltration, immunotherapy, and drug sensitivity were also analyzed between risk groups.
The q-PCR and immunohistochemistry results revealed significant differences in the expression of the signature genes between normal and tumor tissues. Significant differences in clinicopathological features, prognosis and immune infiltration were observed between risk groups. In the low-risk group, better OS and lower TMB scores were demonstrated, while the high-risk group had higher immune checkpoint expression, as well as lower risk of immune escape. In addition, we found that the High-risk group was more sensitive to sorafenib.
In summary, the signature constructed using aging-related genes can reliably predict patient prognosis and immunotherapy efficacy, providing a new idea for immune system therapy of hepatocellular carcinoma.
The precise radiotherapy of esophageal cancer may cause different degrees of radiation damage for lung tissues and cause radioactive pneumonia. However, the occurrence of radioactive pneumonia is ...related to many factors. To further clarify the correlation between the occurrence of radioactive pneumonia and related factors, a random forest model was used to build a risk prediction model for patients with esophageal cancer undergoing radiotherapy. In this study, we retrospectively reviewed 118 patients with esophageal cancer confirmed by pathology in our hospital. The health characteristics and related parameters of all patients were analyzed, and the predictive effect of radiation pneumonia was discussed using the random forest algorithm. After treatment, 71 patients developed radioactive pneumonia (60.17%). In univariate analyses, age, planning target volume length, Karnofsky performance score (KPS), pulmonary emphysema, with or without chemotherapy, and the ratio of planning target volume to planning gross tumor volume (PTV/PGTV) in mediastinum were significantly associated with radioactive pneumonia (P < 0.05 for each comparison). Multivariate analysis revealed that with or without pulmonary emphysema (OR = 7.491, P = 0.001), PTV/PGTV (OR = 0.205, P = 0.007), and KPS (OR = 0.251, P = 0.011) were independent predictors for radiation pneumonia. The results concluded that the analysis of radiation pneumonia-related factors based on the random forest algorithm could build a mathematical prediction model for the easily obtained data. This algorithm also could effectively analyze the risk factors of radiation pneumonia and formulate the appropriate treatment plan for esophageal cancer.
The magnetization dynamics of ultrathin epitaxial Fe films on GaAs (0 0 1) with different thicknesses have been investigated by all-optical time-resolved magneto-optical Kerr effect. For the Fe film ...with thickness of 8 monolayers, the magnetic damping constant along orientation increases by 66% compared with that along orientation, showing the uniaxial anisotropy of magnetic damping. By the measurement of angular dependent time-resolved magneto-optical Kerr effect, the uniaxial magnetic damping is clearly correlated to the in-plane uniaxial anisotropy field of the Fe film. In addition, the anisotropy of the damping constants is found to disappear for the Fe films thicker than 15 monolayers, suggesting that the anisotropic damping originates from the interfacial effect between Fe and GaAs.
Fluidized bed combustion is a well-established and widely used technology for treatment of combustible wastewater. However, agglomeration is always encountered in industrial practice when dealing ...with wastewater that is rich in alkali metals. The objective of this present paper is to illustrate the agglomeration behaviors during fluidized bed incineration of salty wastewater. Various operational parameters were presented, viz. salt content, bed temperature, fluidizing gas velocity, static bed height, bed materials, and different additives. On the basis of SEM/EDX and XRD analysis of agglomerate samples, the mechanisms of agglomerate formation as well as the inhibition mechanisms of agglomeration for different additives were also discussed. The results show that agglomeration is promoted by the increasing of salt content, bed temperature, bed height, particle size, and by the decline of fluidizing gas velocity. All the additives tested, including CaCO3, Al2O3, Fe2O3 and Kaolin, are effective to different extents in inhibiting agglomeration. Physical effects were found to be the main inhibition mechanisms of agglomeration when the bed temperature is below 850°C. Moreover, better results were also observed with increasing of additive amounts.
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•Agglomeration is sensitive to operational parameters and salt contents.•Low-melting eutectics are not produced until the bed temperature exceeds 700°C.•Al2O3 is most effective in the inhibition of agglomeration.•Additives inhibit agglomeration through physical effects within 800°C.•Increasing additive amounts leads to better inhibition results on agglomeration.
Tactile sensors are utilized to measure multichannel pulse signals in pulse wave analysis (PWA). Owing to noise interferences, researchers have applied various denoising algorithms on multichannel ...pulse signals. To comprehensively assess these algorithms, numerous evaluation metrics have been proposed. However, these studies did not investigate the noise mechanisms in depth and lacked reference pulse signals, thus making the evaluations insufficiently objective.
An applicable denoising evaluation approach for multichannel pulse signal algorithms based on an arterial pulse acquisition system is established by superimposing real-world multichannel noise to the reference signals. The system, comprising a SphygmoCor and a uniaxial noise acquisition device, allows us to acquire single-reference pulse signals as well as real-world multichannel noise.
We assess eight popular denoising algorithms with three evaluation metrics, including amplitude relative error (ARE), mean square error (MSE) and increased percentage signal-noise ratio (SNR%). Our proposed approach provides accurate and objective evaluations of multichannel pulse signal denoising. Notably, classic algorithms for single-channel denoising are not recommended for multichannel denoising. Comparatively, RPCA-based algorithms can denoise pulse signals independently for each channel.
This study sets the stage for the establishment of accurate and objective pulse signal denoising evaluations and provides insights for data-driven clinical diagnoses in cardiovascular medicine.
•Propose a reliable evaluation approach for multichannel signal denoising algorithms.•Design a device to acquire single-reference signals and real-world multichannel noise.•Assess eight popular denoising algorithms with objective metrics.
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