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Optimal mass transport (OMT) theory, the goal of which is to move any irregular 3D object (i.e., the brain) without causing significant distortion, is used to preprocess brain tumor datasets for the first time in this paper. The first stage of a two-stage OMT (TSOMT) procedure transforms the brain into a unit solid ball. The second stage transforms the unit ball into a cube, as it is easier to apply a 3D convolutional neural network to rectangular coordinates. Small variations in the local mass-measure stretch ratio among all the brain tumor datasets confirm the robustness of the transform. Additionally, the distortion is kept at a minimum with a reasonable transport cost. The original 240 × 240 × 155 × 4 dataset is thus reduced to a cube of 128 × 128 × 128 × 4 , which is a 76.6% reduction in the total number of voxels, without losing much detail. Three typical U-Nets are trained separately to predict the whole tumor (WT), tumor core (TC), and enhanced tumor (ET) from the cube. An impressive training accuracy of 0.9822 in the WT cube is achieved at 400 epochs. An inverse TSOMT method is applied to the predicted cube to obtain the brain results. The conversion loss from the TSOMT method to the inverse TSOMT method is found to be less than one percent. For training, good Dice scores (0.9781 for the WT, 0.9637 for the TC, and 0.9305 for the ET) can be obtained. Significant improvements in brain tumor detection and the segmentation accuracy are achieved. For testing, postprocessing (rotation) is added to the TSOMT, U-Net prediction, and inverse TSOMT methods for an accuracy improvement of one to two percent. It takes 200 seconds to complete the whole segmentation process on each new brain tumor dataset.

Monoclonal antibodies (mAbs) are a major targeted therapy for malignancies, infectious diseases, autoimmune diseases, transplant rejection and chronic inflammatory diseases due to their antigen specificity and longer half-life than conventional drugs. However, long-term systemic antigen neutralization by mAbs may cause severe adverse events. Improving the selectivity of mAbs to distinguish target antigens at the disease site from normal healthy tissue and reducing severe adverse events caused by the mechanisms-of-action of mAbs is still a pressing need. Development of pro-antibodies (pro-Abs) by installing a protease-cleavable Ab lock is a novel and advanced recombinant Ab-based strategy that efficiently masks the antigen binding ability of mAbs in the normal state and selectively “turns on” the mAb activity when the pro-Ab reaches the proteolytic protease-overexpressed diseased tissue. In this review, we discuss the design and advantages/disadvantages of different Ab lock strategies, focusing particularly on spatial-hindrance-based and affinity peptide-based approaches. We expect that the development of different masking strategies for mAbs will benefit the local reactivity of mAbs at the disease site, increase the therapeutic efficacy and safety of long-term treatment with mAbs in chronic diseases and even permit scientists to develop Ab drugs for formerly undruggable targets and satisfy the unmet medical needs of mAb therapy.

A challenge in accurately identifying and classifying left ventricular hypertrophy (LVH) is distinguishing it from hypertrophic cardiomyopathy (HCM) and Fabry disease. The reliance on imaging techniques often requires the expertise of multiple specialists, including cardiologists, radiologists, and geneticists. This variability in the interpretation and classification of LVH leads to inconsistent diagnoses. LVH, HCM, and Fabry cardiomyopathy can be differentiated using T1 mapping on cardiac magnetic resonance imaging (MRI). However, differentiation between HCM and Fabry cardiomyopathy using echocardiography or MRI cine images is challenging for cardiologists. Our proposed system named the MRI short-axis view left ventricular hypertrophy classifier (MSLVHC) is a high-accuracy standardized imaging classification model developed using AI and trained on MRI short-axis (SAX) view cine images to distinguish between HCM and Fabry disease. The model achieved impressive performance, with an F1-score of 0.846, an accuracy of 0.909, and an AUC of 0.914 when tested on the Taipei Veterans General Hospital (TVGH) dataset. Additionally, a single-blinding study and external testing using data from the Taichung Veterans General Hospital (TCVGH) demonstrated the reliability and effectiveness of the model, achieving an F1-score of 0.727, an accuracy of 0.806, and an AUC of 0.918, demonstrating the model’s reliability and usefulness. This AI model holds promise as a valuable tool for assisting specialists in diagnosing LVH diseases.

Seven new compounds, including one dimer novel skeleton, chamaecyformosanin A (1); three diterpenes, chamaecyformosanins B–D (2–4); one sesquiterpene, chamaecyformosanin E (5); and two monoterpenes, chamaecyformosanins F and G (6 and 7) were isolated from the methanol extract of the bark of Chamaecyparis obtusa var. formosana. Their structures were established by the mean of spectroscopic analysis and the comparison of NMR data with those of known analogues. Their structures were elucidated on the basis of physicochemical evidence, in-depth NMR spectroscopic analysis, and high-resolution mass spectrometry. Furthermore, the isolated compounds were subjected to an evaluation of their antimicrobial activity. Metabolites 1, 3, and 4 present antibacterial activities. It is worth mentioning that the chemical composition of the bark of C. obtusa var. formosana has never been studied in the past. This is the first time the barks from C. obtusa var. formosana were studied and two new skeleton compounds, 1 and 7, were obtained.

Utilizing the optimal mass transportation (OMT) technique to convert an irregular 3D brain image into a cube, a required input format for a U-net algorithm, is a brand new idea for medical imaging research. We develop a cubic volume-measure-preserving OMT (V-OMT) model for the implementation of this conversion. The contrast-enhanced histogram equalization grayscale of fluid-attenuated inversion recovery (FLAIR) in a brain image creates the corresponding density function. We then propose an effective two-phase residual U-net algorithm combined with the V-OMT algorithm for training and validation. First, we use the residual U-net and V-OMT algorithms to precisely predict the whole tumor (WT) region. Second, we expand this predicted WT region with dilation and create a smooth function by convolving the step-like function associated with the WT region in the brain image with a 5 × 5 × 5 blur tensor. Then, a new V-OMT algorithm with mesh refinement is constructed to allow the residual U-net algorithm to effectively train Net1–Net3 models. Finally, we propose ensemble voting postprocessing to validate the final labels of brain images. We randomly chose 1000 and 251 brain samples from the Brain Tumor Segmentation (BraTS) 2021 training dataset, which contains 1251 samples, for training and validation, respectively. The Dice scores of the WT, tumor core (TC) and enhanced tumor (ET) regions for validation computed by Net1–Net3 were 0.93705, 0.90617 and 0.87470, respectively. A significant improvement in brain tumor detection and segmentation with higher accuracy is achieved.

During rheumatoid arthritis (RA) treatment, long-term injection of antitumor necrosis factor α antibodies (anti-TNFα Abs) may induce on-target toxicities, including severe infections (tuberculosis [TB] or septic arthritis) and malignancy. Here, we used an immunoglobulin G1 (IgG1) hinge as an Ab lock to cover the TNFα-binding site of Infliximab by linking it with matrix metalloproteinase (MMP) -2/9 substrate to generate pro-Infliximab that can be specifically activated in the RA region to enhance the selectivity and safety of treatment. The Ab lock significantly inhibits the TNFα binding and reduces the anti-idiotypic (anti-Id) Ab binding to pro-Infliximab by 395-fold, 108-fold compared with Infliximab, respectively, and MMP-2/9 can completely restore the TNFα neutralizing ability of pro-Infliximab to block TNFα downstream signaling. Pro-Infliximab was only selectively activated in the disease site (mouse paws) and presented similar pharmacokinetics (PKs) and bio-distribution to Infliximab. Furthermore, pro-Infliximab not only provided equivalent therapeutic efficacy to Infliximab but also maintained mouse immunity against Listeria infection in the RA mouse model, leading to a significantly higher survival rate (71%) than that of the Infliximab treatment group (0%). The high-selectivity pro-Infliximab maintains host immunity and keeps the original therapeutic efficiency, providing a novel strategy for RA therapy.

Atherosclerosis is an inflammatory disease characterized by lipid deposits in the subendothelial space leading to severe inflammation. Nonalcoholic fatty liver disease (NAFLD) shares several risk factors with atherosclerosis, including dyslipidemia, type 2 diabetes mellitus, and metabolic syndrome, all of which lead to lipid deposition in the liver causing inflammation and fibrosis. Several clinical trials have shown that certain Chinese herbal medicines with anti-inflammatory effects can be used as adjuvant therapy to prevent the development of cardiovascular events and liver disease. Ling Zhi 8 (LZ8) is an immunomodulatory protein isolated from a medicinal mushroom and has been well documented to possess a broad range of pharmacological properties. This study aimed to evaluate the protective effects of recombinant Lactococcus lactis expressing LZ8 protein on NAFLD and atherogenesis in a cholesterol-fed rabbit model. Twelve rabbits were divided into three groups and fed with syrup only, L. lactis vehicle, or recombinant L. lactis-LZ8 once a day on weekdays for five weeks, respectively. The gene expression of IL-1β in the aorta was significantly suppressed after oral administration of L. lactis-LZ8. Moreover, in hematoxylin and eosin staining of the aorta, the intima-medial thickness was decreased, and foam cells were significantly reduced in the subendothelial space. LZ8 also inhibited the expression of IL-1β in the liver, decreased fat droplet deposits and infiltration of inflammatory cells, and improved liver function by decreasing liver enzymes in an animal model. Our results suggest that the Lactococcus-expressing LZ8 appears to be a promising medicine for improving both NAFLD and early atherogenesis owing to its anti-inflammatory effect. Furthermore, it is available as a low-cost food-grade product.

Surface parameterizations have been widely applied to computer graphics and digital geometry processing. In this paper, we propose a novel stretch energy minimization (SEM) algorithm for the computation of equiareal parameterizations of simply connected open surfaces with very small area distortions and highly improved computational efficiencies. In addition, the existence of nontrivial limit points of the SEM algorithm is guaranteed under some mild assumptions of the mesh quality. Numerical experiments indicate that the accuracy, effectiveness, and robustness of the proposed SEM algorithm outperform the other state-of-the-art algorithms. Applications of the SEM on surface remeshing, registration and morphing for simply connected open surfaces are demonstrated thereafter. Thanks to the SEM algorithm, the computation for these applications can be carried out efficiently and reliably.

Inflammation plays a crucial role in atherosclerosis and nonalcoholic fatty liver disease (NAFLD). We previously engineered a recombinant Lactococcus lactis strain expressing the Ling-Zhi immunomodulatory protein (L. lactis-LZ8). This study investigated the anti-atherosclerotic effects of L. lactis-LZ8 in rabbits fed a high-fat diet (HFD). Changes in body weight, serum lipid profiles, and liver function were monitored. The aorta and liver tissues were analyzed for gross pathology and histopathology. Eight-week administration of L. lactis-LZ8 with HFD ameliorated atherosclerosis by downregulating protein and gene expression associated with lipid metabolism and inflammation in the aortas. The rabbits receiving L. lactis-LZ8 exhibited a significant dose-dependent reduction in hepatic fat accumulation. RNA sequencing of the livers revealed that inflammatory genes in the L. lactis-LZ8 groups were downregulated compared to the HFD group. Disease ontology enrichment analysis indicated that these genes were involved in atherosclerosis. Gene set enrichment analysis plots revealed significant enrichment in the gene sets related to cholesterol homeostasis. CIBERSORT immune cell fraction analysis indicated significant infiltration by regulatory T cells, CD8+ T cells, activated dendritic cells, and natural killer cells in the L. lactis-LZ8 group. Our studies underscore LZ8’s role in precision nutrition, providing a potential solution to the current challenges in modifying atherosclerosis and NAFLD.

Tissue angiogenesis is intimately regulated during embryogenesis and postnatal development. Defected angiogenesis contributes to aberrant development and is the main complication associated with ischemia-related diseases. We previously identified the increased expression of RUNX1T1 in umbilical cord blood-derived endothelial colony-forming cells (ECFCs) by gene expression microarray. However, the biological relevance of RUNX1T1 in endothelial lineage is not defined clearly. Here, we demonstrate RUNX1T1 regulates the survival, motility and tube forming capability of ECFCs and EA.hy926 endothelial cells by loss-and gain-of function assays, respectively. Second, embryonic vasculatures and quantity of bone marrow-derived angiogenic progenitors are found to be reduced in the established Runx1t1 heterozygous knockout mice. Finally, a central RUNX1T1-regulated signature is uncovered and VEGFA, BMP4 as well as TGF-β2 are demonstrated to mediate RUNX1T1-orchested angiogenic activities. Taken together, our results reveal that RUNX1T1 serves as a common angiogenic driver for vaculogenesis and functionality of endothelial lineage cells. Therefore, the discovery and application of pharmaceutical activators for RUNX1T1 will improve therapeutic efficacy toward ischemia by promoting neovascularization.