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Prostate cancer (PCa) is a clinically heterogeneous disease. Predicting clinically significant PCa with low–intermediate prostate-specific antigen (PSA), which often includes aggressive cancers, is imperative. This study evaluated the predictive accuracy of deep learning analysis using multimodal medical data focused on clinically significant PCa in patients with PSA ≤ 20 ng/mL. Our cohort study included 178 consecutive patients who underwent ultrasound-guided prostate biopsy. Deep learning analyses were applied to predict clinically significant PCa. We generated receiver operating characteristic curves and calculated the corresponding area under the curve (AUC) to assess the prediction. The AUC of the integrated medical data using our multimodal deep learning approach was 0.878 (95% confidence interval [CI]: 0.772–0.984) in all patients without PSA restriction. Despite the reduced predictive ability of PSA when restricted to PSA ≤ 20 ng/mL (n = 122), the AUC was 0.862 (95% CI: 0.723–1.000), complemented by imaging data. In addition, we assessed clinical presentations and images belonging to representative false-negative and false-positive cases. Our multimodal deep learning approach assists physicians in determining treatment strategies by predicting clinically significant PCa in patients with PSA ≤ 20 ng/mL before biopsy, contributing to personalized medical workflows for PCa management.

Coronary artery lesions (CALs) after Kawasaki disease present complex coronary hemodynamics. We investigated the relationship between coronary fractional flow reserve (FFR), myocardial flow reserve (MFR), and myocardial blood flow volume fraction (MBF) and their clinical usefulness in CALs after Kawasaki disease. Nineteen patients (18 men, 1 woman) who underwent cardiac catheterization and 13N-ammonia positron emission tomography, with 24 coronary artery branches, were included. Five branches had inconsistent FFR and MFR values, two had normal FFR but abnormal MFR, and three had abnormal FFR and normal MFR. The abnormal MFR group had significantly higher MBF at rest than the normal group (0.86 ± 0.13 vs. 1.08 ± 0.09, p = 0.001). The abnormal FFR group had significantly lower MBF at adenosine loading than the normal group (2.23 ± 0.23 vs. 1.88 ± 0.29, p = 0.021). The three branches with abnormal FFR only had stenotic lesions, but the MFR may have been normal because blood was supplied by collateral vessels. Combining FFR, MFR, and MBF will enable a more accurate assessment of peripheral coronary circulation and stenotic lesions in CALs and help determine treatment strategy and timing of intervention.

Deep learning is being increasingly applied for obtaining digital microscopy image data of cells. Well-defined annotated cell images have contributed to the development of the technology. Cell morphology is an inherent characteristic of each cell type. Moreover, the morphology of a cell changes during its lifetime because of cellular activity. Artificial intelligence (AI) capable of recognizing a mouse-induced pluripotent stem (miPS) cell cultured in a medium containing Lewis lung cancer (LLC) cell culture-conditioned medium (cm), miPS-LLCcm cell, which is a cancer stem cell (CSC) derived from miPS cell, would be suitable for basic and applied science. This study aims to clarify the limitation of AI models constructed using different datasets and the versatility improvement of AI models. The trained AI was used to segment CSC in phase-contrast images using conditional generative adversarial networks (CGAN). The dataset included blank cell images that were used for training the AI but they did not affect the quality of predicting CSC in phase contrast images compared with the dataset without the blank cell images. AI models trained using images of 1-day culture could predict CSC in images of 2-day culture; however, the quality of the CSC prediction was reduced. Convolutional neural network (CNN) classification indicated that miPS-LLCcm cell image classification was done based on cultivation day. By using a dataset that included images of each cell culture day, the prediction of CSC remains to be improved. This is useful because cells do not change the characteristics of stem cells owing to stem cell marker expression, even if the cell morphology changes during culture.

A 60-day experiment was designed to assess the effect of different ratios of fish meal (FM): camelina meal plant protein (CM) on growth response and relative gene expression of growth-promoting factors, feed utilization potency, digestive enzymes activities, apparent digestibility (ADC), stress response, non-specific immunity of Pagrus major. Four isonitrogenous (490.7 g/kg of crude protein) and isolipidic (91.5 g/kg total lipid) experimental diets were formulated and designated as camelina meal (CM0), soyabean meal (SBM20.5), CM20.5, and CM33 based on protein contents. At the end of the feed trial, significantly higher (p < 0.05) weight gain, specific growth rate, and feed intake but lower feed conversion ratio were recorded in fish fed CM0, SBM20.5, and CM20.5 than fish fed CM33. The lowest growth, feed utilization, enzyme activity, and digestibility were recorded in fish fed CM33. Significantly higher pepsin, amylase, and protease activities were observed in fish fed CM0, SBM20.5, and CM20.5 diets than fish fed CM33. The highest ADC of protein was recorded in fish fed CM0, SBM20.5, and CM20.5 diets. Hematocrit levels were depressed CM33 while total serum protein, total cholesterol, triglyceride, blood urea nitrogen, total bilirubin, aspartate aminotransferase, and alanine aminotransferase were not significantly changed by the inclusion of CM. Non-specific immune variables (lysozyme activity, peroxidase activity in serum and nitro blue tetrazolium) in fish fed CM0, SBM20.5, and CM20.5 were significantly higher than in fish fed CM33 diet. The superoxide dismutase of fish fed CM20.5 was not significantly different from CM0 and SBM20.5 (p > 0.05). Catalase and low salinity stress test show that CM0, SBM20.5, and CM20.5 were not significantly (p > 0.05) different, while CM33 was significantly lower than the rest of the diets. TBARs show that CM20.5 and CM33 diets were significantly different (p < 0.05), but CM20.5 was not significantly different from SBM20.5. Significantly higher hepatic IGF-1 and IGF-2 mRNA expression was found in fish-fed diet groups CM0, SBM20.5, and CM20.5 than fish fed CM33. The present study indicated that the addition of CM up 205 kg/kg to diet maintains growth, digestive enzymes, nutrient digestibility, immunity, stress resistance, and feed utilization efficiency of red sea bream.

The three major conventional treatments: surgery, chemotherapy, and radiation therapy, have been commonly performed for lung cancer. However, lung cancer is still the leading cause of cancer-related mortality. Immunotherapy has recently emerged as a very effective new treatment modality, and there is now growing enthusiasm for cancer immunotherapy worldwide. However, the results of clinical studies using immunotherapy are not always favorable. Understanding the steps involved in the recognition and eradication of cancer cells by the immune system seems essential to understanding why past immunotherapies have failed and how current therapies can be optimally utilized. In addition, the combination of immunotherapies, such as cancer vaccines and immune checkpoint inhibitors, as well as the combination of these therapies with three conventional therapies, may pave the way for personalized immunotherapy. In this review, we summarize the results of immunotherapies used in phase III clinical trials, including immune checkpoint inhibitors, and discuss the future prospects of immunotherapies in lung cancer treatment.

Hyperlipidemia or dyslipidemia is a major risk factor for atherosclerotic diseases. Experimental animals play an important role in elucidating the molecular mechanisms of the pathophysiology of hyperlipidemia as well as in drug development. Rabbits are one of the most suitable models to study human hyperlipidemia because many features of the lipoprotein metabolism of rabbits are similar to those of humans such as LDL-rich lipoproteins in plasma, apolipoprotein B mRNA editing, and cholesteryl ester transfer protein. Currently, three types of rabbit models are commonly used for studying hyperlipidemia: (1) diet-induced hyperlipidemic rabbits, (2) spontaneous hyperlipidemic rabbits, and (3) gene-manipulated rabbits (transgenic and knockout rabbits). In this review, we give an overview of the features of hyperlipidemic rabbits and discuss the usefulness of rabbits for the development of anti-atherogenic drugs.

Deep-learning workflows of microscopic image analysis are sufficient for handling the contextual variations because they employ biological samples and have numerous tasks. The use of well-defined annotated images is important for the workflow. Cancer stem cells (CSCs) are identified by specific cell markers. These CSCs were extensively characterized by the stem cell (SC)-like gene expression and proliferation mechanisms for the development of tumors. In contrast, the morphological characterization remains elusive. This study aims to investigate the segmentation of CSCs in phase contrast imaging using conditional generative adversarial networks (CGAN). Artificial intelligence (AI) was trained using fluorescence images of the Nanog-Green fluorescence protein, the expression of which was maintained in CSCs, and the phase contrast images. The AI model segmented the CSC region in the phase contrast image of the CSC cultures and tumor model. By selecting images for training, several values for measuring segmentation quality increased. Moreover, nucleus fluorescence overlaid-phase contrast was effective for increasing the values. We show the possibility of mapping CSC morphology to the condition of undifferentiation using deep-learning CGAN workflows.

Taxanes including paclitaxel and docetaxel are effective anticancer agents preferably sufficient for liposomal drug delivery. However, the encapsulation of these drugs with effective amounts into conventional liposomes is difficult due to their high hydrophobicity. Therefore, an effective encapsulation strategy for liposomal taxanes has been eagerly anticipated. In this study, the mixture of polyethoxylated castor oil (Cremophor EL) and ethanol containing phosphate buffered saline termed as CEP was employed as a solvent of the inner hydrophilic core of liposomes where taxanes should be incorporated. Docetaxel-, paclitaxel-, or 7-oxacetylglycosylated paclitaxel-encapsulating liposomes were successfully prepared with almost 100% of encapsulation efficiency and 29.9, 15.4, or 29.1 mol% of loading efficiency, respectively. We then applied the docetaxel-encapsulating liposomes for targeted drug delivery. Docetaxel-encapsulating liposomes were successfully developed HER2-targeted drug delivery by coupling HER2-specific binding peptide on liposome surface. The HER2-targeting liposomes exhibited HER2-specific internalization and enhanced anticancer activity in vitro. Therefore, we propose the sophisticated preparation of liposomal taxanes using CEP as a promising formulation for effective cancer therapies.