Complex Organ Mask Guided Radiology Report Generation

The goal of automatic report generation is to generate a clinically accurate and coherent phrase from a single given X-ray image, which could alleviate the workload of traditional radiology reporting. However, in a real-world scenario, radiologists frequently face the challenge of producing extensive reports derived from numerous medical images, thereby medical report generation from multi-image perspective is needed. In this paper, we propose the Complex Organ Mask Guided (termed as COMG) report generation model, which incorporates masks from multiple organs (e.g., bones, lungs, heart, and mediastinum), to provide more detailed information and guide the model's attention to these crucial body regions. Specifically, we leverage prior knowledge of the disease corresponding to each organ in the fusion process to enhance the disease identification phase during the report generation process. Additionally, cosine similarity loss is introduced as target function to ensure the convergence of cross-modal consistency and facilitate model optimization.Experimental results on two public datasets show that COMG achieves a 11.4% and 9.7% improvement in terms of BLEU@4 scores over the SOTA model KiUT on IU-Xray and MIMIC, respectively. The code is publicly available at https://github.com/GaryGuTC/COMG_model.Comment: 12 pages, 7 images. Accepted by WACV 202

Exploring Annotation-free Image Captioning with Retrieval-augmented Pseudo Sentence Generation

Training an image captioner without annotated image-sentence pairs has gained traction in recent years. Previous approaches can be categorized into two strategies: crawling sentences from mismatching corpora and aligning them with the given images as pseudo annotations, or pre-training the captioner using external image-text pairs. However, the aligning setting seems to reach its performance limit due to the quality problem of pairs, and pre-training requires significant computational resources. To address these challenges, we propose a new strategy ``LPM + retrieval-augmented learning" where the prior knowledge from large pre-trained models (LPMs) is leveraged as supervision, and a retrieval process is integrated to further reinforce its effectiveness. Specifically, we introduce Retrieval-augmented Pseudo Sentence Generation (RaPSG), which adopts an efficient approach to retrieve highly relevant short region descriptions from the mismatching corpora and use them to generate a variety of pseudo sentences with distinct representations as well as high quality via LPMs. In addition, a fluency filter and a CLIP-guided training objective are further introduced to facilitate model optimization. Experimental results demonstrate that our method surpasses the SOTA pre-training model (Flamingo3B) by achieving a CIDEr score of 78.1 (+5.1) while utilizing only 0.3% of its trainable parameters (1.3B VS 33M). Importantly, our approach eliminates the need of computationally expensive pre-training processes on external datasets (e.g., the requirement of 312M image-text pairs for Flamingo3B). We further show that with a simple extension, the generated pseudo sentences can be deployed as weak supervision to boost the 1% semi-supervised image caption benchmark up to 93.4 CIDEr score (+8.9) which showcases the versatility and effectiveness of our approach.Comment: 10 pages 5 figure

Strawberry Mixed Gel 3D Printing Formula Optimization

In order to improve the utilization rate of strawberry tail fruit and expand the product categories of strawberry processing, strawberry pulping was combined with xanthan gum and carrageenan to form a base material suitable for 3D printing. The optimal formula of strawberry mixed gel 3D printing was obtained by using single factor and response surface optimization experiments. The results showed that: The influence of different raw materials on the printing accuracy was in the order of K-carrageenan>strawberry pulp>xanthan gum, and the optimal process formula was strawberry pulp additive amount of 40 g, xanthan gum additive amount of 2 g, K-carrageenan additive amount of 3 g. Under this condition, the printing accuracy of strawberry 3D printing products was 98.39%, and strawberry 3D printing products were most consistent with the set model (cube: The upper side length was 15 mm, the lower side length was 15 mm, the height was 15 mm), at this time, the material could be well extruded and the support capacity was the best

Effects of processing parameters on microstructure of semi-solid magnesium alloy

In this paper, the effects of pouring temperature of magnesium melt, preheating temperature of the barrel of the screw mixer, and shear rate on the solidified microstructures of semi-solid slurry were investigated by a mechanical stirring semi-solid process. The appropriate processing parameters of slurry preparation were obtained, and the mold filling ability of semi-solid slurry for thin-walled casting was examined. Results indicate that the solid volume fraction of non-dendritic mi-crostructure increases with a decrease in pouring temperature of magnesium melt and the barrel preheating temperature of the screw mixer. Also the grain size of primary a-phase is reduced. Furthermore, the solid volume fraction of semi-solid non-dendritic structure decreases with an increase of shear rate. The fine and round granular microstructure with 30一50 Nm insize of semi-solid AZ91D magnesium alloy was presented. Finally, a 1.0 mm thin-walled casting with a clear contour and good soundness was successfully made by semi-solid rheo-diecasting

Progress of MRI in predicting the circumferential resection margin of rectal cancer: A narrative review

Rectal cancer (RC) is the third most frequently diagnosed cancer worldwide, and the status of its circumferential resection margin (CRM) is of paramount significance for treatment strategies and prognosis. CRM involvement is defined as tumor touching or within 1 mm from the outermost part of tumor or outer border of the mesorectal or lymph node deposits to the resection margin. The incidence of involved CRM varied from 5.4 % to 36 %, which may associate with an in consistent definition of CRM, the quality of surgeries, and the different examination modalities. Although T and N status are essential factors in determining whether a patient should receive neoadjuvant therapy before surgery, CRM status is a powerful predictor of local and distant recurrence as well as survival rate. This review explores the significance of CRM, the various assessment methods, and the role of magnetic resonance imaging (MRI) and artificial intelligence-based MRI in predicting CRM status. MRI showed potential advantage in predicting CRM status with a high sensitivity and specificity compared to computed tomography (CT). We also discuss MRI advancements in RC imaging, including conventional MRI with body coil, high-resolution MRI with phased-array coil, and endorectal MRI. Along with a discussion of artificial intelligence-based MRI techniques to predict the CRM status of RCs before and after treatments

In vitro antioxidant capacities of eight different kinds of apples and their effects on lipopolysaccharide-induced oxidative damage in mice.

In the present study, the DPPH and ABTS+ radical scavenging activity of eight types of apples decreased (P < 0.05) during the 70-day storage at 4°C. The Fushi (F2) apples from Xin Jiang showed the highest radical scavenging activity. For in vivo study, 40 male Kunming mice (body weight 20-25 g) were selected and randomly assigned to four groups (10 mice per group). The F2 groups (F2S, F2 + sterile saline and F2L, F2 + lipopolysaccharide) were administered with 0.3 mL F2 filtrate via gastric intubation daily for 28 days. The control groups (CS, CON + sterile saline and CL, CON + lipopolysaccharide) were treated with sterile saline at the same volume. At day 29, mice of F2L and CL groups were injected with 100 μg/kg body weight of lipopolysaccharide (LPS) intraperitoneally, while those of F2S and CS groups were injected equal volume of sterile saline. In comparison to the CS group, the CL group showed a decrease (P < 0.05) in serum, liver, and hepatic mitochondrial antioxidant capacity, reduction (P < 0.05) in the expression of hepatic antioxidant-related genes, and an increase (P < 0.05) in serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), malondialdehyde (MDA), protein carbonyl (PC), and reactive oxygen species (ROS). In comparison to the CL group, the F2L group showed lower (P < 0.05) levels of serum ALT, AST, and ROS, higher (P < 0.05) level of serum, liver, and hepatic mitochondrial antioxidant capacity, increased mitochondrial membrane potential (MMP), and enhanced (P < 0.05) expression of hepatic antioxidant-related genes. These results suggest that F2 may exert protective effect against LPS-induced oxidative damage by improving the antioxidant capacity

Direct Growth of CuO Nanorods on Graphitic Carbon Nitride with Synergistic Effect on Thermal Decomposition of Ammonium Perchlorate

Novel graphitic carbon nitride/CuO (g-C3N4/CuO) nanocomposite was synthesized through a facile precipitation method. Due to the strong ion-dipole interaction between copper ions and nitrogen atoms of g-C3N4, CuO nanorods (length 200–300 nm, diameter 5–10 nm) were directly grown on g-C3N4, forming a g-C3N4/CuO nanocomposite, which was confirmed via X-ray diffraction (XRD), transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM), and X-ray photoelectron spectroscopy (XPS). Finally, thermal decomposition of ammonium perchlorate (AP) in the absence and presence of the prepared g-C3N4/CuO nanocomposite was examined by differential thermal analysis (DTA), and thermal gravimetric analysis (TGA). The g-C3N4/CuO nanocomposite showed promising catalytic effects for the thermal decomposition of AP. Upon addition of 2 wt % nanocomposite with the best catalytic performance (g-C3N4/20 wt % CuO), the decomposition temperature of AP was decreased by up to 105.5 °C and only one decomposition step was found instead of the two steps commonly reported in other examples, demonstrating the synergistic catalytic activity of the as-synthesized nanocomposite. This study demonstrated a successful example regarding the direct growth of metal oxide on g-C3N4 by ion-dipole interaction between metallic ions, and the lone pair electrons on nitrogen atoms, which could provide a novel strategy for the preparation of g-C3N4-based nanocomposite

Screening the Reference Genes for Quantitative Gene Expression by RT-qPCR During SE Initial Dedifferentiation in Four Gossypium hirsutum Cultivars that Have Different SE Capability

RNA sequencing (RNA-Seq)-based gene expression analysis is applicable to a wide range of biological purposes in various species. Reverse transcription quantitative PCR (RT-qPCR) is also used to assess target gene expression utilizing stably expressed reference genes as internal control under a given set of conditions. However, investigations of the reference genes for RT-qPCR normalization in the process of somatic embryogenesis (SE) initial dedifferentiation in Gossypium hirsutum are rarely reported. In this study, on the basis of our previous transcriptome data of three different induction stages during SE initial dedifferentiation process in four G. hirsutum cultivars that have different SE capability, 15 candidate genes were selected during SE initial dedifferentiation process, and their expression stability was evaluated by geNorm, NormFinder, and BestKeeper. The results indicated that the two genes of endonuclease 4 (ENDO4) and 18S ribosomal RNA (18S rRNA) showed stable expression in the four different G. hirsutum cultivars, endowing them to be appropriate reference genes during three induction stages in the four cotton cultivars. In addition, the stability and reliability of the two reference genes of ENDO4 and 18S rRNA were further verified by comparing the expressions of auxin-responsive protein 22 (AUX22) and ethylene-responsive transcription factor 17 (ERF17) between RT-qPCR results and the RNA-seq data, which showed strong positive correlation coefficient (R2 = 0.8396&ndash;0.9984), validating again the steady expression of ENDO4 and 18S rRNA as the reliable reference genes. Our results provide effective reference genes for RT-qPCR normalization during SE process in different G. hirsutum cultivars

Constructing Sheet-On-Sheet Structured Graphitic Carbon Nitride/Reduced Graphene Oxide/Layered MnO2 Ternary Nanocomposite with Outstanding Catalytic Properties on Thermal Decomposition of Ammonium Perchlorate

We unprecedentedly report that layered MnO2 nanosheets were in situ formed onto the surface of covalently bonded graphitic carbon nitride/reduced graphene oxide nanocomposite (g-C3N4/rGO), forming sheet-on-sheet structured two dimension (2D) graphitic carbon nitride/reduced graphene oxide/layered MnO2 ternary nanocomposite (g-C3N4/rGO/MnO2) with outstanding catalytic properties on thermal decomposition of ammonium perchlorate (AP). The covalently bonded g-C3N4/rGO was firstly prepared by the calcination of graphene oxide-guanidine hydrochloride precursor (GO-GndCl), following by its dispersion into the KMnO4 aqueous solution to construct the g-C3N4/rGO/MnO2 ternary nanocomposite. FT-IR, XRD, Raman as well as the XPS results clearly demonstrated the chemical interaction between g-C3N4, rGO and MnO2. TEM and element mapping indicated that layered g-C3N4/rGO was covered with thin MnO2 nanosheets. Furthermore, the obtained g-C3N4/rGO/MnO2 nanocomposite exhibited promising catalytic capacity on thermal decomposition of AP. Upon addition of 2 wt % g-C3N4/rGO/MnO2 ternary nanocomposite as catalyst, the thermal decomposition temperature of AP was largely decreased up by 142.5 °C, which was higher than that of pure g-C3N4, g-C3N4/rGO and MnO2, respectively, demonstrating the synergistic catalysis of the as-prepared nanocomposite