Segmenting medical images is a necessary prerequisite for disease diagnosis and treatment planning. Among various medical image segmentation tasks, U-Net-based variants have been widely used in liver ...tumor segmentation tasks. In view of the highly variable shape and size of tumors, in order to improve the accuracy of segmentation, this paper proposes a U-Net-based hybrid variable structure-RDCTrans U-Net for liver tumor segmentation in computed tomography (CT) examinations. We design a backbone network dominated by ResNeXt50 and supplemented by dilated convolution to increase the network depth, expand the perceptual field, and improve the efficiency of feature extraction without increasing the parameters. At the same time, Transformer is introduced in down-sampling to increase the network's overall perception and global understanding of the image and to improve the accuracy of liver tumor segmentation. The method proposed in this paper tests the segmentation performance of liver tumors on the LiTS (Liver Tumor Segmentation) dataset. It obtained 89.22% mIoU and 98.91% Acc, for liver and tumor segmentation. The proposed model also achieved 93.38% Dice and 89.87% Dice, respectively. Compared with the original U-Net and the U-Net model that introduces dense connection, attention mechanism, and Transformer, respectively, the method proposed in this paper achieves SOTA (state of art) results.
The rapid development of remote sensing and space technology provides multisource remote sensing image data for earth observation in the same area. Information provided by these images, however, is ...often complementary and cooperative, and multisource image fusion is still challenging. This paper proposes a novel multisource remote sensing image fusion algorithm. It integrates the contrast saliency map (CSM) and the sum-modified-Laplacian (SML) in the nonsubsampled shearlet transform (NSST) domain. The NSST is utilized to decompose the source images into low-frequency sub-bands and high-frequency sub-bands. Low-frequency sub-bands reflect the contrast and brightness of the source images, while high-frequency sub-bands reflect the texture and details of the source images. Using this information, the contrast saliency map and SML fusion rules are introduced into the corresponding sub-bands. Finally, the inverse NSST reconstructs the fusion image. Experimental results demonstrate that the proposed multisource remote image fusion technique performs well in terms of contrast enhancement and detail preservation.
Multi-focus image fusion plays an important role in the application of computer vision. In the process of image fusion, there may be blurring and information loss, so it is our goal to obtain ...high-definition and information-rich fusion images. In this paper, a novel multi-focus image fusion method via local energy and sparse representation in the shearlet domain is proposed. The source images are decomposed into low- and high-frequency sub-bands according to the shearlet transform. The low-frequency sub-bands are fused by sparse representation, and the high-frequency sub-bands are fused by local energy. The inverse shearlet transform is used to reconstruct the fused image. The Lytro dataset with 20 pairs of images is used to verify the proposed method, and 8 state-of-the-art fusion methods and 8 metrics are used for comparison. According to the experimental results, our method can generate good performance for multi-focus image fusion.
Multimodal medical image fusion aims to fuse images with complementary multisource information. In this paper, we propose a novel multimodal medical image fusion method using pulse coupled neural ...network (PCNN) and a weighted sum of eight-neighborhood-based modified Laplacian (WSEML) integrating guided image filtering (GIF) in non-subsampled contourlet transform (NSCT) domain. Firstly, the source images are decomposed by NSCT, several low- and high-frequency sub-bands are generated. Secondly, the PCNN-based fusion rule is used to process the low-frequency components, and the GIF-WSEML fusion model is used to process the high-frequency components. Finally, the fused image is obtained by integrating the fused low- and high-frequency sub-bands. The experimental results demonstrate that the proposed method can achieve better performance in terms of multimodal medical image fusion. The proposed algorithm also has obvious advantages in objective evaluation indexes VIFF, QW, API, SD, EN and time consumption.
Acute leukemia (AL) is a hematological malignancy, and the prognosis of most AL patients hasn’t improved significantly, particularly for relapsed or refractory (R/R) AL. Therefore, new treatments for ...R/R adult acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) are urgently necessary. Novel developments have been made in AL treatment, including target and immune therapies. CD38 is one of the targets due to its high expression in many hematological malignancies, including multiple myeloma, ALL and a subset of AML. Consequently, targeting CD38 therapies, including CD38 monoclonal antibodies (mAbs), bispecific antibodies, and CAR-T cell therapy, exhibit promising efficacy in treating multiple myeloma without significant toxicity and are being explored in other hematological malignancies and nonhematological diseases. Herein, this review focuses on targeting CD38 therapies in ALL and AML, which demonstrate sound antileukemic effects in acute leukemia and are expected to become effective treatment methods.
Whether isocitrate dehydrogenase 2 (IDH2) R140 and R172 gene mutations affect the prognosis of patients with acute myeloid leukemia (AML) is controversial. Here, we performed a meta-analysis to ...assess their prognostic value.
Eligible studies were systematically searched from PubMed, Embase, the Cochrane Library and Chinese databases up to June 1, 2022. We extracted the hazard ratios (HRs) and their 95% confidence intervals (CIs) of overall survival (OS) and progression-free survival (PFS) to carry out a meta-analysis by a fixed effect model or random effect model according to the heterogeneity between studies.
A total of 12725 AML patients from 11 studies were included in this meta-analysis, of which 1111 (8.7%) and 305 (2.4%) had IDH2R140 and IDH2R172 mutations, respectively. The results revealed that both IDH2R140 and IDH2R172 mutations had no significant effect on OS (IDH2R140: HR = 0.92, 95% CI: 0.77-1.10, P = 0.365; IDH2R172: HR = 0.91, 95% CI: 0.65-1.28, P = 0.590) or PFS (IDH2R140: HR = 1.02, 95% CI: 0.75-1.40, P = 0.881; IDH2R172: HR = 1.31, 95% CI: 0.78-2.22, P = 0.306) in AML patients. Subgroup analysis of AML patients with IDH2R140 mutation revealed that studies from the USA (HR = 0.60, 95% CI: 0.41-0.89, P = 0.010) and ≤ 50 years old (HR = 0.63, 95% CI: 0.50-0.80, P = 0.000) had longer OS. However, studies from Sweden (HR = 1.94, 95% CI: 1.07-3.53, P = 0.030) had shorter OS. Meanwhile, subgroup analysis of AML patients with IDH2R172 mutation showed that studies from Germany/Austria (HR = 0.76, 95% CI: 0.61-0.94, P = 0.012) and from Sweden (HR = 0.22, 95% CI: 0.07-0.74, P = 0.014) had longer OS, whereas studies from the UK (HR = 1.49, 95% CI: 1.13-1.96, P = 0.005) and studies with nonmultivariate analysis of data type (HR = 1.35, 95% CI: 1.06-1.73, P = 0.014) had shorter OS. In addition, our study also found that patients with IDH2R140 mutation had significantly longer OS (HR = 0.61, 95% CI: 0.39-0.96, P = 0.032) and PFS (HR = 0.31, 95% CI: 0.18-0.52, P = 0.021) than patients with IDH2R172 mutation, despite some degree of heterogeneity.
This meta-analysis demonstrates that IDH2R140 mutation improves OS in younger AML patients and that the prognostic value of IDH2R172 mutation is significantly heterogeneous. Differences in region and data type have a significant impact on the prognosis of AML patients with IDH2R140 and/or IDH2R172 mutations. Additionally, AML patients with IDH2R140 mutation have a better prognosis than those with IDH2R172 mutations, albeit with some degree of heterogeneity.
Despite major scientific discoveries and novel therapies over the past four decades, the treatment outcomes of acute myeloid leukemia (AML), especially in the adult patient population remain dismal. ...In the past few years, an increasing number of targets such as CD33, CD123, CLL-1, CD47, CD70, and TIM3, have been developed for immunotherapy of AML. Among them, CLL-1 has attracted the researchers' attention due to its high expression in AML while being absent in normal hematopoietic stem cell. Accumulating evidence have demonstrated CLL-1 is an ideal target for AML. In this paper, we will review the expression of CLL-1 on normal cells and AML, the value of CLL-1 in diagnosis and follow-up, and targeting CLL-1 therapy-based antibody and chimeric antigen receptor T cell therapy as well as providing an overview of CLL-1 as a target for AML.
Staphylococcus aureus
is a major threat in infectious diseases due to its varied infection types and increased resistance.
S. aureus
could form persister cells under certain condition and could also ...attach on medical apparatus to form biofilms, which exhibited extremely high resistance to antibiotics. 3-Acetyl-11-keto-beta-boswellic acid (AKBA) is a well-studied anti-tumor and antioxidant drug. This study is aimed to determine the antimicrobial effects of AKBA against
S. aureus
and its persister cells and biofilms. The in vitro antimicrobial susceptibility of AKBA was assessed by micro-dilution assay, disc diffusion assay and time-killing assay. Drug combination between AKBA and conventional antibiotics was detected by checkerboard assay. And the antibiofilm effects of AKBA against
S. aureus
were explored by crystal violet staining combined with SYTO/PI probes staining. Next, RBC lysis activity and CCK-8 kit were used to determine the cytotoxicity of AKBA. In addition, murine subcutaneous abscess model was used to assess the antimicrobial effects of AKBA in vivo. Our results revealed that AKBA was found to show effective antimicrobial activity against methicillin-resistant
S. aureus
(MRSA) with the minimal inhibitory concentration of 4–8 µg/mL with undetectable cytotoxicity. And no resistant mutation was induced by AKBA after 20 days of consecutive passage. Further, we found that AKBA could be synergy with gentamycin or amikacin against
S. aureus
and its clinical isolates. By crystal violet and SYTO9/PI staining, AKBA exhibited strong biofilm inhibitory and eradication effects at the concentration of 1 ~ 4 µg/mL. In addition, the effective antimicrobial effect was verified in vivo in a mouse model. And no detectable in vivo toxicity was found. These results indicated that AKBA has great potential to development as an alternative treatment for the refractory
S. aureus
infections.
Ovarian cancer is a highly lethal malignancy in the field of oncology. Generally speaking, the segmentation of ovarian medical images is a necessary prerequisite for the diagnosis and treatment ...planning. Therefore, accurately segmenting ovarian tumors is of utmost importance. In this work, we propose a hybrid network called PMFFNet to improve the segmentation accuracy of ovarian tumors. The PMFFNet utilizes an encoder-decoder architecture. Specifically, the encoder incorporates the ViTAEv2 model to extract inter-layer multi-scale features from the feature pyramid. To address the limitation of fixed window size that hinders sufficient interaction of information, we introduce Varied-Size Window Attention (VSA) to the ViTAEv2 model to capture rich contextual information. Additionally, recognizing the significance of multi-scale features, we introduce the Multi-scale Feature Fusion Block (MFB) module. The MFB module enhances the network's capacity to learn intricate features by capturing both local and multi-scale information, thereby enabling more precise segmentation of ovarian tumors. Finally, in conjunction with our designed decoder, our model achieves outstanding performance on the MMOTU dataset. The results are highly promising, with the model achieving scores of 97.24%, 91.15%, and 87.25% in mACC, mIoU, and mDice metrics, respectively. When compared to several Unet-based and advanced models, our approach demonstrates the best segmentation performance.
As the power density and integration level of electronic devices increase, there are growing demands to improve the thermal conductivity of polymers for addressing the thermal management issues. On ...the basis of the ultrahigh intrinsic thermal conductivity, graphene has exhibited great potential as reinforcing fillers to develop polymer composites, but the resultant thermal conductivity of reported graphene-based composites is still limited. Here, an interconnected and highly ordered graphene framework (HOGF) composed of high-quality and horizontally aligned graphene sheets was developed by a porous film-templated assembly strategy, followed by a stress-induced orientation process and graphitization post-treatment. After embedding into the epoxy (EP), the HOGF/EP composite (24.7 vol %) exhibits a record-high in-plane thermal conductivity of 117 W m–1 K–1, equivalent to ≈616 times higher than that of neat epoxy. This thermal conductivity enhancement is mainly because the HOGF as a filler concurrently has high intrinsic thermal conductivity, relatively high density, and a highly ordered structure, constructing superefficient phonon transport paths in the epoxy matrix. Additionally, the use of our HOGF/EP as a heat dissipation plate was demonstrated, and it achieved 75% enhancement in practical thermal management performance compared to that of conventional alumina for cooling the high-power LED.
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