Search

Mean radiant temperature (MRT), which is a crucial factor for thermal comfort, varies within a space. This renders deriving the representative values for radiant heating and cooling control challenging. This study reviewed existing methods for deriving MRT in previous research and addressed their limitations by proposing a method for determining a representative MRT value. The existing methods were categorized as air temperature, single location, and area weighted. Three methods for deriving representative MRT values were proposed, considering the building’s usage, scale, and applicable system installations. The proposed methods were categorized as single-zone averaged, multi-zone averaged, and point-zone MRT. Experiments were conducted by distinguishing cases based on the control of equipment systems during heating and cooling periods. During the cooling season, the single-zone averaged MRT and air temperature differed by up to 4 °C, and the difference between the multi-zone averaged MRT and MRT at a point in the perimeter zone reached up to 7 °C. During the heating season, the single-zone averaged MRT and air temperature differed by up to 2.2 °C. Thus, the results of this study emphasize the importance of applying different methods of deriving representative MRT values depending on the size and usage of the building, and demonstrate that this facilitated more effective heating and cooling control systems.

In this paper, we propose an amount estimation method for food intake based on both color and depth images. Two pairs of color and depth images are captured pre- and post-meals. The pre- and post-meal color images are employed to detect food types and food existence regions using Mask R-CNN. The post-meal color image is spatially transformed to match the food region locations between the pre- and post-meal color images. The same transformation is also performed on the post-meal depth image. The pixel values of the post-meal depth image are compensated to reflect 3D position changes caused by the image transformation. In both the pre- and post-meal depth images, a space volume for each food region is calculated by dividing the space between the food surfaces and the camera into multiple tetrahedra. The food intake amounts are estimated as the difference in space volumes calculated from the pre- and post-meal depth images. From the simulation results, we verify that the proposed method estimates the food intake amount with an error of up to 2.2%.

A metastatic brain tumor is the most common type of malignancy in the central nervous system, which is one of the leading causes of death in patients with lung cancer. The purpose of this study is to evaluate the efficacy of a novel treatment for metastatic brain tumors with lung cancer using neural stem cells (NSCs), which encode rabbit carboxylesterase (rCE) and the secretion form of tumor necrosis factor-related apoptosis-inducing ligand (sTRAIL). rCE and/or sTRAIL were transduced in immortalized human fetal NSCs, HB1.F3. The cytotoxic effects of the therapeutic cells on human lung cancer cells were evaluated in vitro with the ligands and decoy receptor expression for sTRAIL in the presence of CPT-11. Human NSCs encoding rCE (F3.CE and F3.CE.sTRAIL) significantly inhibited the growth of lung cancer cells in the presence of CPT-11 in vitro. Lung cancer cells were inoculated in immune-deficient mice, and therapeutic cells were transplanted systematically through intracardiac arterial injection and then treated with CPT-11. In resting state, DR4 expression in lung cancer cells and DcR1 in NSCs increased to 70% and 90% after CPT-11 addition, respectively. The volumes of the tumors in immune-deficient mice were reduced significantly in mice with F3.CE.sTRAIL transplantation and CPT-11 treatment. The survival was also significantly prolonged with treatment with F3.sTRAIL and F3.CE plus CPT-11 as well as F3.CE.sTRAIL plus CPT-11. NSCs transduced with rCE and sTRAIL genes showed a significant anti-cancer effect on brain metastatic lung cancer in vivo and in vitro, and the effect may be synergistic when rCE/CPT-11 and sTRAIL are combined. This stem-cell-based study using two therapeutic genes of different biological effects can be translatable to clinical application.

This paper proposes a method to classify food types and to estimate meal intake amounts in pre- and post-meal images through a deep learning object detection network. The food types and the food regions are detected through Mask R-CNN. In order to make both pre- and post-meal images to a same capturing environment, the post-meal image is corrected through a homography transformation based on the meal plate regions in both images. The 3D shape of the food is determined as one of a spherical cap, a cone, and a cuboid depending on the food type. The meal intake amount is estimated as food volume differences between the pre-meal and post-meal images. As results of the simulation, the food classification accuracy and the food region detection accuracy are up to 97.57% and 93.6%, respectively.

Airflow in a multi-zone building can be a major cause of pollutant transfer, excessive energy consumption, and occupants discomfort. The key to monitoring airflows and mitigating related problems is to obtain a comprehensive understanding of pressure relationships within the buildings. This study proposes a visualization method for representing pressure distribution within a multi-zone building by using a novel pressure-sensing system. The system consists of a Master device and a couple of Slave devices that are connected with each other by a wireless sensor network. A 4-story office building and a 49-story residential building were installed with the system to detect pressure variations. The spatial and numerical mapping relationships of each zone were further determined through grid-forming and coordinate-establishing processes for the building floor plan. Lastly, 2D and 3D visualized pressure mappings of each floor were generated, illustrating the pressure difference and spatial relationship between adjacent zones. It is expected that the pressure mappings derived from this study will allow building operators to intuitively perceive the pressure variations and the spatial layouts of the zones. These mappings also make it possible for operators to diagnose the differences in pressure conditions between adjacent zones and plan a control scheme for the HVAC system more efficiently.

The main cause of erectile dysfunction (ED) is the damage in penile cavernous endothelial cells (EC). Murine primary ECs have a limited growth potential, and the easy availability of murine ECs will facilitate the study of cavernous endothelial dysfunction in rats. This study was performed to establish immortalized rat penile cavernous ECs (rEC) and investigate how they could repair erectile dysfunction in rats with cavernous nerve injury (CNI). rEC was isolated enzymatically by collagenase digestion and were cultured. An amphotropic replication-incompetent retroviral vector encoding v-myc oncogene was used to transfect rEC for immortalization (vREC). Morphological and immunohistochemical properties of vREC were examined. Eight-week-old male Sprague-Dawley rats were divided into three groups of five rats each, including group 1 = sham operation, group 2 = bilateral CN injury, group 3 = vREC (1 × 106 cells) treatment after CNI. Erectile response was assessed at 2, 4 weeks after transplantation of vREC., Penile tissue were harvested at 4 weeks after transplantation and immune–histochemical examination was performed. vREC showed the expression of CD31, vWF, cell type-specific markers for EC by RT-PCR and flowcytometry. At 2, 4 weeks after transplantation, rats with CNI had significantly lower erectile function than control group (p < 0.05). The group transplanted with vREC showed higher erectile function than the group without vRECs (p < 0.05). vREC was established and repaired erectile dysfunction in rats with CNI. This cell line may be useful for studying mechanisms and drug screening of erectile dysfunction of rats.

In this paper, we propose an intra-picture prediction method for depth video by a block clustering through a neural network. The proposed method solves a problem that the block that has two or more clusters drops the prediction performance of the intra prediction for depth video. The proposed neural network consists of both a spatial feature prediction network and a clustering network. The spatial feature prediction network utilizes spatial features in vertical and horizontal directions. The network contains a 1D CNN layer and a fully connected layer. The 1D CNN layer extracts the spatial features for a vertical direction and a horizontal direction from a top block and a left block of the reference pixels, respectively. 1D CNN is designed to handle time-series data, but it can also be applied to find the spatial features by regarding a pixel order in a certain direction as a timestamp. The fully connected layer predicts the spatial features of the block to be coded through the extracted features. The clustering network finds clusters from the spatial features which are the outputs of the spatial feature prediction network. The network consists of 4 CNN layers. The first 3 CNN layers combine two spatial features in the vertical and horizontal directions. The last layer outputs the probabilities that pixels belong to the clusters. The pixels of the block are predicted by the representative values of the clusters that are the average of the reference pixels belonging to the clusters. For the intra prediction for various block sizes, the block is scaled to the size of the network input. The prediction result through the proposed network is scaled back to the original size. In network training, the mean square error is used as a loss function between the original block and the predicted block. A penalty for output values far from both ends is introduced to the loss function for clear network clustering. In the simulation results, the bit rate is saved by up to 12.45% under the same distortion condition compared with the latest video coding standard.

In Alzheimer’s disease, reactive oxygen species (ROS) are generated by the deposition of amyloid-beta oligomers (AβOs), which represent one of the important causes of neuronal cell death. Additionally, AβOs are known to induce autophagy via ROS induction. Previous studies have shown that autophagy upregulation aggravates neuronal cell death. In this study, the effects of peroxiredoxin 2 (Prx2), a member of the peroxidase family of antioxidant enzymes, on regulating AβO-mediated autophagy were investigated. Prx2 decreased AβO-mediated oxidative stress and autophagy in N2a-APPswe cells. Further, we examined the relationship between the neuronal protective effect of Prx2 and a decrease in autophagy. Similar to the effects of N-acetyl cysteine, Prx2 decreased AβO-induced ROS and inhibited p62 protein expression levels by downregulating the activation of NRF2 and its translocation to the nucleus. In addition, treatment with 3-methyladenine, an autophagy inhibitor, ameliorates neuronal cell death. Overall, these results demonstrate that the Prx2-induced decrease in autophagy was associated with the inhibition of ROS via the ROS–NRF2–p62 pathway in N2a-APPswe cells. Therefore, our results revealed that Prx2 is a potential therapeutic target in anti-Alzheimer therapy.

By virtue of their upright locomotion, similar to that of humans, motion analysis of non-human primates has been widely used in order to better understand musculoskeletal biomechanics and neuroscience problems. Given the difficulty of conducting a marker-based infrared optical tracking system for the behavior analysis of primates, a 2-dimensional (D) video analysis has been applied. Distinct from a conventional marker-based optical tracking system, a depth image sensor system provides 3-D information on movement without any skin markers. The specific aim of this study was to develop a novel algorithm to analyze the behavioral patterns of non-human primates in a home cage using a depth image sensor. The behavioral patterns of nine monkeys in their home cage, including sitting, standing, and pacing, were captured using a depth image sensor. Thereafter, these were analyzed by observers’ manual assessment and the newly written automated program. We confirmed that the measurement results from the observers’ manual assessments and the automated program with depth image analysis were statistically identical.

Glutathione peroxidase 1 (Gpx1) and peroxiredoxin 2 (Prdx2) belong to the thiol peroxidase family of antioxidants, and have been studied for their antioxidant functions and roles in cancers. However, the physiological significance of Gpx1 and Prdx2 during vertebrate embryogenesis are lacking. Currently, we investigated the functional roles of Gpx1 and Prdx2 during vertebrate embryogenesis using Xenopus laevis as a vertebrate model. Our investigations revealed the zygotic nature of gpx1 having its localization in the eye region of developing embryos, whereas prdx2 exhibited a maternal nature and were localized in embryonic ventral blood islands. Furthermore, the gpx1-morphants exhibited malformed eyes with incompletely detached lenses. However, the depletion of prdx2 has not established its involvement with embryogenesis. A molecular analysis of gpx1-depleted embryos revealed the perturbed expression of a cryba1-lens-specific marker and also exhibited reactive oxygen species (ROS) accumulation in the eye regions of gpx1-morphants. Additionally, transcriptomics analysis of gpx1-knockout embryos demonstrated the involvement of Wnt, cadherin, and integrin signaling pathways in the development of malformed eyes. Conclusively, our findings indicate the association of gpx1 with a complex network of embryonic developmental pathways and ROS responses, but detailed investigation is a prerequisite in order to pinpoint the mechanistic details of these interactions.

Canines are useful in mammalian preclinical studies because they are larger than rodents and share many diseases with humans. Canine fetal fibroblast cells (CFFs) are an easily accessible source of somatic cells. However, they are easily driven to senescence and become unusable with continuous in vitro culture. Therefore, to overcome these deficiencies, we investigated whether tetracycline-inducible L-myc gene expression promotes self-renewal activity and tumorigenicity in the production of induced conditional self-renewing fibroblast cells (iCSFCs). Here, we describe the characterization of a new iCSFC line immortalized by transduction with L-myc that displays in vitro self-renewal ability without tumorigenic capacity. We established conditionally inducible self-renewing fibroblast cells by transducing CFF-3 cells with L-myc under the tetracycline-inducible gene expression system. In the absence of doxycycline, the cells did not express L-myc or undergo self-renewal. The iCSFCs had a fibroblast-like morphology, normal chromosome pattern, and expressed fibroblast-specific genes and markers. However, the iCSFCs did not form tumors in a soft agar colony-forming assay. We observed higher expression of three ES modules (core pluripotency genes, polycomb repressive complex genes (PRC), and MYC-related genes) in the iCSFCs than in the CFF-3 cells; in particular, the core pluripotency genes (OCT4, SOX2, and NANOG) were markedly up-regulated compared with the PRC and MYC module genes. These results demonstrated that, in canine fetal fibroblasts, L-myc tetracycline-inducible promoter-driven gene expression induces self-renewal capacity but not tumor formation. This study suggests that L-myc gene-induced conditional self-renewing fibroblast cells can be used as an in vitro tool in a variety of biomedical studies related to drug screening.

The mean radiant temperature (MRT) is an indicator for evaluating the radiant heat environment near occupants and is determined by the radiant heat exchange between the occupants and their surroundings. To control various heating and cooling systems according to the occupants’ thermal comfort, it is essential to consider MRTs in the real-time evaluation of thermal environment. This study proposes a pan–tilt infrared (IR) scanning method to estimate the MRTs at multiple occupant locations in real buildings. The angle factor was calculated by defining the specific classification criteria for dividing the entire indoor surface into sub-surfaces. The coupling IR camera and pan–tilt motor were applied to enable storing data pairs of IR thermal image frame (IR image frame) and pan–tilt angle so each surface area taken by the IR camera can have its direction information. The measurement method of the mean surface temperature using the pan–tilt IR system was presented. The pan–tilt IR system hardware and MRT monitoring software were developed. An experiment was performed to verify the applicability of the proposed pan–tilt IR scanning method. By comparing the surface temperatures measured using a contact thermometer and the proposed IR system, the contact thermometer could cause inaccurate measurement of surfaces with a non-uniform distribution of temperature. The difference between surface temperatures increased by up to 15 °C and, accordingly, the MRT distributions differed by up to 6 °C within the same space. The proposed IR scanning method showed good applicability in various aspects. This paper reports that the MRT has a significant effect on the occupants’ thermal comfort and also suggests considering MRTs in the real-time evaluation of thermal environment to control various heating and cooling systems appropriately.

The overall five-year survival rate for late-stage patients of ovarian cancer is below 29% due to disease recurrence and drug resistance. Cancer stem cells (CSCs) are known as a major contributor to drug resistance and recurrence. Accordingly, therapies targeting ovarian CSCs are needed to overcome the limitations of present treatments. This study evaluated the effect of trimebutine maleate (TM) targeting ovarian CSCs, using A2780-SP cells acquired by a sphere culture of A2780 epithelial ovarian cancer cells. TM is indicated as a gastrointestinal motility modulator and is known to as a peripheral opioid receptor agonist and a blocker for various channels. The GI50 of TM was approximately 0.4 µM in A2780-SP cells but over 100 µM in A2780 cells, demonstrating CSCs specific growth inhibition. TM induced G0/G1 arrest and increased the AV+/PI+ dead cell population in the A2780-SP samples. Furthermore, TM treatment significantly reduced tumor growth in A2780-SP xenograft mice. Voltage gated calcium channels (VGCC) and calcium-activated potassium channels (BKCa) were overexpressed on ovarian CSCs and targeted by TM; inhibition of both channels reduced A2780-SP cells viability. TM reduced stemness-related protein expression; this tendency was reproduced by the simultaneous inhibition of VGCC and BKCa compared to single channel inhibition. In addition, TM suppressed the Wnt/β-catenin, Notch, and Hedgehog pathways which contribute to many CSCs characteristics. Specifically, further suppression of the Wnt/β-catenin pathway by simultaneous inhibition of BKCa and VGCC is necessary for the effective and selective action of TM. Taken together, TM is a potential therapeutic drug for preventing ovarian cancer recurrence and drug resistance.

The proteolytic processing of amyloid precursor protein (APP) by β-secretase (BACE1) and γ-secretase releases amyloid-β peptide (Aβ), which deposits in amyloid plaques and contributes to the initial causative events of Alzheimer’s disease (AD). In the present study, the regulatory mechanism of APP processing of three phlorotannins was elucidated in Swedish mutant APP overexpressed N2a (SweAPP N2a) cells. Among the tested compounds, dieckol exhibited the highest inhibitory effect on both intra- and extracellular Aβ accumulation. In addition, dieckol regulated the APP processing enzymes, such as α-secretase (ADAM10), β-secretase, and γ-secretase, presenilin-1 (PS1), and their proteolytic products, sAPPα and sAPPβ, implying that the compound acts on both the amyloidogenic and non-amyloidogenic pathways. In addition, dieckol increased the phosphorylation of protein kinase B (Akt) at Ser473 and GSK-3β at Ser9, suggesting dieckol induced the activation of Akt, which phosphorylated GSK-3β. The specific phosphatidylinositol 3-kinase (PI3K) inhibitor LY294002 triggered GSK-3β activation and Aβ expression. In addition, co-treatment with LY294002 noticeably blocked the effect of dieckol on Aβ production, demonstrating that dieckol promoted the PI3K/Akt signaling pathway, which in turn inactivated GSK-3β, resulting in the reduction in Aβ levels.

Glutathione peroxidase 3 (GPx3) belongs to the glutathione peroxidase family of selenoproteins and is a key antioxidant enzyme in multicellular organisms against oxidative damage. Downregulation of GPx3 affects tumor progression and metastasis and is associated with liver and heart disease. However, the physiological significance of GPx3 in vertebrate embryonic development remains poorly understood. The current study aimed to investigate the functional roles of gpx3 during embryogenesis. To this end, we determined gpx3’s spatiotemporal expression using Xenopus laevis as a model organism. Using reverse transcription polymerase chain reaction (RT-PCR), we demonstrated the zygotic nature of this gene. Interestingly, the expression of gpx3 enhanced during the tailbud stage of development, and whole mount in situ hybridization (WISH) analysis revealed gpx3 localization in prospective tail region of developing embryo. gpx3 knockdown using antisense morpholino oligonucleotides (MOs) resulted in short post-anal tails, and these malformed tails were significantly rescued by glutathione peroxidase mimic ebselen. The gene expression analysis indicated that gpx3 knockdown significantly altered the expression of genes associated with Wnt, Notch, and bone morphogenetic protein (BMP) signaling pathways involved in tailbud development. Moreover, RNA sequencing identified that gpx3 plays a role in regulation of cell death in the developing embryo. Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) and phospho-histone 3 (PH3) staining confirmed the association of gpx3 knockdown with increased cell death and decreased cell proliferation in tail region of developing embryos, establishing the involvement of gpx3 in tailbud development by regulating the cell death. Furthermore, these findings are inter-related with increased reactive oxygen species (ROS) levels in gpx3 knockdown embryos, as measured by using a redox-sensitive fluorescent probe HyPer. Taken together, our results suggest that gpx3 plays a critical role in posterior embryonic development by regulating cell death and proliferation during vertebrate embryogenesis.

In this study, an estimation method for human height is proposed using color and depth information. Color images are used for deep learning by mask R-CNN to detect a human body and a human head separately. If color images are not available for extracting the human body region due to low light environment, then the human body region is extracted by comparing between current frame in depth video and a pre-stored background depth image. The topmost point of the human head region is extracted as the top of the head and the bottommost point of the human body region as the bottom of the foot. The depth value of the head top-point is corrected to a pixel value that has high similarity to a neighboring pixel. The position of the body bottom-point is corrected by calculating a depth gradient between vertically adjacent pixels. Two head-top and foot-bottom points are converted into 3D real-world coordinates using depth information. Two real-world coordinates estimate human height by measuring a Euclidean distance. Estimation errors for human height are corrected as the average of accumulated heights. In experiment results, we achieve that the estimated errors of human height with a standing state are 0.7% and 2.2% when the human body region is extracted by mask R-CNN and the background depth image, respectively.

This study optimized the preparation of electrosprayed microspheres containing leuprolide and developed an in vitro−in vivo correlation (IVIVC) model that enables mutual prediction between in vitro and in vivo dissolution. The pharmacokinetic (PK) and pharmacodynamic (PD) study of leuprolide was carried out in normal rats after subcutaneous administration of electrosprayed microspheres. The parameters of the IVIVC model were estimated by fitting the PK profile of Lucrin depot® to the release compartment of the IVIVC model, thus the in vivo dissolution was predicted from the in vitro dissolution. From this correlation, the PK profile of leuprolide was predicted from the results of in vivo dissolution. The IVIVC model was validated by estimating percent prediction error (%PE) values. Among prepared microspheres, an optimal formulation was selected using the IVIVC model. The maximum plasma concentration and the area under the plasma concentration−time curve from zero to infinity from the predicted PK profile were 4.01 ng/mL and 52.52 h·ng/mL, respectively, and from the observed PK profile were 4.14 ng/mL and 56.95 h·ng/mL, respectively. The percent prediction error values of all parameters did not exceed 15%, thus the IVIVC model satisfies the validation criteria of the Food and Drug Administration (FDA) guidance. The PK/PD evaluation suggests that the efficacy of OL5 is similar to Lucrin depot®, but the formulation was improved by reducing the initial burst release.

In this paper, a virtual touch sensor using a depth camera is proposed. Touch regions are detected by finding each region that consists of pixels within a certain distance from a touch surface. Touch points are detected by finding a pixel in each touch region whose neighboring pixels are closest to surfaces. A touch path error due to noise in the depth picture is corrected through a filter that introduces a weight parameter in order to respond quickly even with sudden changes. The virtual touch sensor is implemented by using the proposed methods for the touch point detection and the touch path correction. In the virtual touch sensor, a touch surface and pixels of a depth picture can be regarded as a virtual touch panel and virtual touch units, respectively. The virtual touch sensor can be applied to wide fields of touch interfaces. Results of simulations show the implementation of the touch-pen interface using the virtual touch sensor.

This study developed the pharmacokinetic (PK)–pharmacodynamic (PD) model of the testosterone-suppressive effect of leuprolide for evaluation of the sustained release (SR) depot and leuprolide solution in rats with or without prostate cancer. Six groups of rats were divided by the routes of administration (intravenous and subcutaneous injection) and kinds of formulation (vehicle, leuprolide solution, and SR depot). The PK profile after subcutaneous injection of leuprolide solution could be well-described by the one-compartment model. The absorption rate constant, the total body clearance, and the volume of distribution were estimated at 16.67 h−1, 514.46 mL/h, and 487.40 mL. Using PK parameters in the solution-administered group, the PK model for the SR depot was developed. The PK–PD model was constructed by describing the testosterone-suppressive effect of leuprolide using the feedback turnover model. The response of testosterone after administration of each formulation was well described using this PK–PD model for the estimation of PD parameters (EC50, Emax, h) and systemic parameters (kin, kout, kf on, kf off). The developed PK–PD model containing an inhibitory feedback system could successfully describe the testosterone-suppressive effect of leuprolide in the type of formulation. The PK–PD model developed would be useful for evaluating the formulation of similar drugs whose effect is regulated through the feedback mechanism.

Since the thermal environment of large space buildings such as stadiums can vary depending on the location of the stands, it is important to divide them into different zones and evaluate their thermal environment separately. The thermal environment can be evaluated using physical values measured with the sensors, but the occupant density of the stadium stands is high, which limits the locations available to install the sensors. As a method to resolve the limitations of installing the sensors, we propose a method to predict the thermal environment of each zone in a large space. We set six key thermal factors affecting the thermal environment in a large space to be predicted factors (indoor air temperature, mean radiant temperature, and clothing) and the fixed factors (air velocity, metabolic rate, and relative humidity). Using artificial neural network (ANN) models and the outdoor air temperature and the surface temperature of the interior walls around the stands as input data, we developed a method to predict the three thermal factors. Learning and verification datasets were established using STAR CCM+ (2016.10, Siemens PLM software, Plano, TX, USA). An analysis of each model’s prediction results showed that the prediction accuracy increased with the number of learning data points. The thermal environment evaluation process developed in this study can be used to control heating, ventilation, and air conditioning (HVAC) facilities in each zone in a large space building with sufficient learning by ANN models at the building testing or the evaluation stage.