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Abstract Neoantigens are ideal targets for cancer immunotherapy because they are expressed de novo in tumor tissue but not in healthy tissue and are therefore recognized as foreign by the immune system. Advances in next-generation sequencing and bioinformatics technologies have enabled the quick identification and prediction of tumor-specific neoantigens; however, only a small fraction of predicted neoantigens are immunogenic. To improve the predictability of immunogenic neoantigens, we developed the in silico neoantigen prediction workflows VACINUSpMHC and VACINUSTCR: VACINUSpMHC incorporates physical binding between peptides and MHCs (pMHCs), and VACINUSTCR integrates T cell reactivity to the pMHC complex through deep learning-based pairing with T cell receptors (TCRs) of putative tumor-reactive CD8 tumor-infiltrating lymphocytes (TILs). We then validated our neoantigen prediction workflows both in vitro and in vivo in patients with hepatocellular carcinoma (HCC) and in a B16F10 mouse melanoma model. The predictive abilities of VACINUSpMHC and VACINUSTCR were confirmed in a validation cohort of 8 patients with HCC. Of a total of 118 neoantigen candidates predicted by VACINUSpMHC, 48 peptides were ultimately selected using VACINUSTCR. In vitro validation revealed that among the 48 predicted neoantigen candidates, 13 peptides were immunogenic. Assessment of the antitumor efficacy of the candidate neoepitopes using a VACINUSTCR in vivo mouse model suggested that vaccination with the predicted neoepitopes induced neoantigen-specific T cell responses and enabled the trafficking of neoantigen-specific CD8 + T cell clones into the tumor tissue, leading to tumor suppression. This study showed that the prediction of immunogenic neoantigens can be improved by integrating a tumor-reactive TIL TCR-pMHC ternary complex.

Abstract Implantable cell therapies and tissue transplants require sufficient oxygen supply to function and are limited by a delay or lack of vascularization from the transplant host. Previous exogenous oxygenation strategies have been bulky and had limited oxygen production or regulation. Here, we show an electrocatalytic approach that enables bioelectronic control of oxygen generation in complex cellular environments to sustain engineered cell viability and therapy under hypoxic stress and at high cell densities. We find that nanostructured sputtered iridium oxide serves as an ideal catalyst for oxygen evolution reaction at neutral pH. We demonstrate that this approach exhibits a lower oxygenation onset and selective oxygen production without evolution of toxic byproducts. We show that this electrocatalytic on site oxygenator can sustain high cell loadings (>60k cells/mm3) in hypoxic conditions in vitro and in vivo. Our results showcase that exogenous oxygen production devices can be readily integrated into bioelectronic platforms, enabling high cell loadings in smaller devices with broad applicability.

Background To investigate the efficacy and safety of moderate-intensity rosuvastatin/ezetimibe combination compared to highintensity rosuvastatin in high atherosclerotic cardiovascular disease (ASCVD) risk patients with type 2 diabetes mellitus (T2DM). Methods This study was a randomized, multicenter, open, parallel phase 4 study, and enrolled T2DM subjects with an estimated 10-year ASCVD risk ≥7.5%. The primary endpoint was the low-density lipoprotein cholesterol (LDL-C) change rate after 24-week rosuvastatin 10 mg/ezetimibe 10 mg treatment was non-inferior to that of rosuvastatin 20 mg. The achievement proportion of 10-year ASCVD risk

This study was conducted to confirm the utilization of Pleurospermum camtschaticum root extract as an organic agricultural material. Antioxidant activity of P. camtschaticum root extract, closely related to antibacterial activity, increased in a dose-dependent manner. In mycelial growth inhibitory activity, 100% P. camtschaticum root extract supressed over 70% for Colletotrichum coccodes and over 68% for Colletotrichum dematium. In the pepper fruit anthracnose development test, the size of the lesion decreased in a dose-dependent manner, which showed the same tendency as the previous results in inhibitory activity on mycelial growth. In the pepper seed germination and red pepper growth promotion test of P. camtschaticum root extract, oposite results was confirmed. The lower the concentration, the more the seed germination and growth promotion effects were shown. The phenol content of pepper leaves was also measured after pepper growth promotion test have been completed. The phenol content related to antibacterial activity increased in all treated groups compared to the untreated group. Therefore, the results of this study showed the possibility of development as an organic material.

This paper develops deep learning (DL) based beamforming approaches for multi-antenna interference channels where several base stations (BSs) individually optimize their own beamforming vectors in a decentralized manner. By exploiting the optimal beam structure, we propose an efficient method for beam decisions and coordination among BSs based solely on local information. Moreover, we show that the proposed approach allows a scalable design with respect to the number of users. We also present novel training strategies for the proposed deep neural networks, validating its potential as an innovative decentralized beamforming methodology. Consequently, the proposed DL based decentralized beamforming framework can achieve various optimal beamforming strategies. Numerical results demonstrate the advantages of the proposed framework over conventional methods.

In this paper, we consider long range air-to-ground (AG) communication systems which support aeronautical platforms including unmanned aerial vehicles (UAVs) in the ultra high frequency (UHF) band. For such a system, we present the measurement based path loss analysis and multipath characteristic results at the distance of hundreds of kilometers. To this end, the experimental AG channel measurement system is implemented at the aircraft with various ground station (GS) environments. Through realistic flight tests, we observe the path loss behaviors for long range UHF channels with sea and ground earth surface reflections. By comparing the measurement results with the empirical path loss model and the spherical earth two-ray model, we demonstrate that our measurement results match well with the model. Moreover, for the multipath channel characterization, we provide field test results on the occurrence probability, delay, and power of multipath components in hilly and mountainous environments with various altitudes of the aircraft.

Abstract Disruption of bone homeostasis caused by metastatic osteolytic breast cancer cells increases inflammatory osteolysis and decreases bone formation, thereby predisposing patients to pathological fracture and cancer growth. Alteration of osteoblast function induces skeletal diseases due to the disruption of bone homeostasis. We observed increased activation of pERK1/2 in osteolytic breast cancer cells and osteoblasts in human pathological specimens with aggressive osteolytic breast cancer metastases. We confirmed that osteolytic breast cancers with high expression of pERK1/2 disrupt bone homeostasis via osteoblastic ERK1/2 activation at the bone-breast cancer interface. The process of inflammatory osteolysis modulates ERK1/2 activation in osteoblasts and breast cancer cells through dominant-negative MEK1 expression and constitutively active MEK1 expression to promote cancer growth within bone. Trametinib, an FDA-approved MEK inhibitor, not only reduced breast cancer-induced bone destruction but also dramatically reduced cancer growth in bone by inhibiting the inflammatory skeletal microenvironment. Taken together, these findings suggest that ERK1/2 activation in both breast cancer cells and osteoblasts is required for osteolytic breast cancer-induced inflammatory osteolysis and that ERK1/2 pathway inhibitors may represent a promising adjuvant therapy for patients with aggressive osteolytic breast cancers by altering the shared cancer and bone microenvironment.

The research of deployment and management of small heterogeneous cells toward the 5th generation of mobile cellular networks has been extensively investigated in both academia and industry. With the densification of small cells, the traffic requirements within each cell will fluctuate noticeably, so the traffic distribution and user behavior need to be studied based on different deployment and management scenarios. Furthermore, it is envisioned that 5G networks will be mostly for data-centric applications rather than voice-centric applications. Rethinking the systems architecture for “5G” in various deployment and management of small heterogeneous cells, supporting ultra-reliable and low latency communications, is needed to support a variety of new services, e.g., automotive, health, energy, and manufacturing. Therefore, designing ultra-dense cellular networks using new transmission technologies is a promising and challenging field.

Frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) systems introduce a large overhead in downlink channel estimation in contrast to the time division duplex (TDD) mode. This overhead results in a considerable spectral efficiency (SE) gap between the FDD and TDD modes. In this paper, we consider the performance of the TDD and FDD massive MIMO systems with a spatially correlated channel in the presence of jamming in the network. We show how a smart jammer can effectively design its attack signal to degrade the network performance in terms of the downlink SE. Since the jammer can obtain different information about the channels in the TDD and FDD modes, two distinct jamming strategies are proposed for each mode. In the numerical results, the performance of both the TDD and FDD modes under the optimized jamming designs are evaluated and compared. Our results show that despite more attention to the TDD mode in current massive MIMO systems, it is more vulnerable to smart jamming attacks compared to the FDD mode which results in a smaller SE-gap between the modes. Furthermore, a countermeasure technique is proposed to combat this jamming attack in both the TDD and FDD modes by estimating the jamming power, grouping users, and allocating power among them. The numerical results demonstrate the effectiveness of the proposed countermeasure techniques in both the TDD and FDD modes.

In this paper, we consider long range air-to-ground (AG) communication systems which support airborne platforms including unmanned aerial vehicles (UAVs) for real-time applications. In this system, we design tracking techniques for directional ground antennas which enable reliable AG communication regardless of dynamic maneuvers of the UAV. We apply a simple monopulse method and a fixed gain filtering algorithm to develop a single channel monopulse tracking system with an angular estimation filtering, which exploits a downlink signal without requiring a dedicated channel. Through the AG communication prototype and realistic flight tests, we evaluate the tracking accuracy performance at the distance of hundreds of kilometers and demonstrate the auto-tracking capability of the angular estimation filter. The flight test results show that the tracking accuracy of our proposed system is sufficient for long range transmission with a narrow beam antenna. Also, in the absence of the downlink signal, it is observed that the ground prototype can resume the monopulse tracking procedure, and successfully maintains the tracking accuracy.

Extracellular vesicles (EVs) are nanovesicles that are naturally released from cells in a lipid bilayer-bound form. A subset population with a size of 200 nm, small EVs (sEVs), is enticing in many ways. Initially perceived as mere waste receptacles, sEVs have revealed other biological functions, such as cell-to-cell signal transduction and communication. Besides their notable biological functions, sEVs have profound advantages as future drug modalities: (i) excellent biocompatibility, (ii) high stability, and (iii) the potential to carry undruggable macromolecules as cargo. Indeed, many biopharmaceutical companies are utilizing sEVs, not only as diagnostic biomarkers but as therapeutic drugs. However, as all inchoate fields are challenging, there are limitations and hindrances in the clinical translation of sEV therapeutics. In this review, we summarize different types of sEV therapeutics, future improvements, and current strategies in large-scale production.

Heat recovery from a high-temperature wastewater is the major concern in the conventional textile industry. However, limited space in the textile plant is an important constraint for the process enhancement. Therefore, an easily applicable heat recovery system with a small amount of additional equipment to the existing dyeing process is required. To meet the needs from the industry, this study suggests an integrated heat recovery and supply system consisting of single heat exchanger and single storage tank using freshwater as a thermal carrier to utilize the reusable heat in the wastewater. Freshwater is stored in a tank after direct heat exchange with wastewater and is supplied to the next dyeing process. Three different designs of the integrated system were compared based on the lower limit of the wastewater temperature: above 50 °C, 40 °C, and 30 °C for Cases 1, 2, and 3, respectively. The energy and energy flow analyses showed Case 2 to be well balanced between the quality and quantity of the recovered heat, and there was no heat loss via drainage. The heat demand for Case 2 was 795.5 kW, which was the lowest among all cases. Furthermore, an economic analysis showed that the total cost for Case 2 was reduced by 63.2% compared with the base case. Despite the use of an additional heat exchanger and water storage tank, the proposed system was more economical because of the reduced operating costs. Finally, a detailed analysis was conducted by determining the more efficient temperature for heat recovery and supply.

This paper investigates wireless powered communication network (WPCN) systems aided by unmanned aerial vehicle (UAV) where a UAV-mounted access point (AP) serves multiple energy-constrained ground terminals (GTs). Specifically, the UAVs first transmit the wireless energy transfer (WET) signals to charge the GTs in the downlink. Then, by utilizing the harvested energy, the GTs send their wireless information transmission (WIT) signals to the UAVs in the uplink. In this paper, depending on the operations of the UAVs, we consider two different scenarios, namely integrated and separated UAV WPCNs. First, in the integrated system, a UAV acts as a hybrid AP in which both energy transfer and information reception are performed at a single UAV. In contrast, for the separated UAV WPCN, we consider two UAVs each of which behaves as an information AP and an energy AP independently, and thus the information decoding and the energy transfer are separately processed at two different UAVs. In each system, we formulate two optimization problems taking into account a linear energy harvesting (EH) model and a practical non-linear model. To maximize the minimum throughput of the GTs, we jointly optimize the trajectories of the UAVs, the uplink power control, and the time resource allocation for the WET and the WIT. Since the formulated problems are non-convex, in the linear EH model-based system, we apply the concave-convex procedure by deriving appropriate convex bounds for non-convex constraints and identify the suboptimal solution for the problem by a proposed iterative algorithm. In the non-linear model-based system, we propose another algorithm to obtain an efficient solution by adopting the successive convex approximation method with the alternating optimization framework. Simulation results demonstrate the efficiency and the performance of the proposed algorithms compared to conventional schemes.

The hydrogen liquefaction process is highly energy-intensive owing to its cryogenic characteristics, and a large proportion of the total energy is consumed in the subcooling cycle. This study aimed to develop an efficient configuration for the subcooling cycle in the hydrogen liquefaction process. The He-Ne Brayton cycle is one of the most energy-efficient cycles of the various proposed hydrogen liquefaction processes, and it was selected as the base case configuration. To improve its efficiency and economic potential, two different process configurations were proposed: (configuration 1) a dual-pressure cycle that simplified the process configuration, and (configuration 2) a split triple-pressure cycle that decreased the flow rate of the medium- and high-pressure compressors. The ortho–para conversion heat of hydrogen is considered by using heat capacity data of equilibrium hydrogen. Genetic algorithm-based optimization was also conducted to minimize the energy consumption of each configuration, and the optimization results showed that the performance of configuration 1 was worse than that of the base case configuration. In this respect, although less equipment was used, the compression load on each compressor was very intensive, which increased the energy requirements and costs. Configuration 2 provided the best results with a specific energy consumption of 5.69 kWh/kg (3.2% lower than the base case configuration). The total expense of configuration 2 shows the lowest value which is USD 720 million. The process performance improvements were analyzed based on the association between the refrigerant composition and the heat exchange efficiency. The analysis demonstrated that energy efficiency and costs were both improved by dividing the pressure levels and splitting the refrigerant flow rate in configuration 2.

Naringin is a naturally occurring flavonoid found in plants of the Citrus genus that has historically been used in traditional Chinese medical regimens for the treatment of osteoporosis. Naringin modulates signaling through numerous molecular pathways critical to musculoskeletal development, cellular differentiation, and inflammation. Administration of naringin increases in vitro expression of bone morphogenetic proteins (BMPs) and activation of the Wnt/β-catenin and extracellular signal-related kinase (Erk) pathways, thereby promoting osteoblastic proliferation and differentiation from stem cell precursors for bone formation. Naringin also inhibits osteoclastogenesis by both modifying RANK/RANKL interactions and inducing apoptosis in osteoclasts in vitro . In addition, naringin acts on the estrogen receptor in bone to mimic the native bone-preserving effects of estrogen, with few systemic side effects on other estrogen-sensitive tissues. The efficacy of naringin therapy in reducing the osteolysis characteristic of common musculoskeletal pathologies such as osteoporosis, degenerative joint disease, and osteomyelitis, as well as inflammatory conditions affecting bone such as diabetes mellitus, has been extensively demonstrated in vitro and in animal models. Naringin thus represents a naturally abundant, cost-efficient agent whose potential for use in novel musculoskeletal biotherapies warrants re-visiting and further exploration through human studies. Here, we review the cellular mechanisms of action that have been elucidated regarding the action of naringin on bone resident cells and the bone microenvironment, in vivo evidence of naringin’s osteostimulative and chondroprotective properties in the setting of osteolytic bone disease, and current limitations in the development of naringin-containing translational therapies for common musculoskeletal conditions.

ABSTRACT Type 2 diabetes mellitus (T2DM) is a multisystemic disease that afflicts more than 415 million people globally—the incidence and prevalence of T2DM continues to rise. It is well‐known that T2DM has detrimental effects on bone quality that increase skeletal fragility, which predisposes subjects to an increased risk of fracture and fracture healing that results in non‐ or malunion. Diabetics have been found to have perturbations in metabolism, hormone production, and calcium homeostasis—particularly PTH expression—that contribute to the increased risk of fracture and decreased fracture healing. Given the perturbations in PTH expression and the establishment of hPTH (1–34) for use in age‐related osteoporosis, it was determined logical to attempt to ameliorate the bone phenotype found in T2DM using hPTH (1–34). Therefore, the present study had two aims: (i) to establish a suitable murine model of the skeletal fragility present in T2DM because no current consensus model exists; and (ii) to determine the effects of hPTH (1–34) on bone fractures in T2DM. The results of the present study suggest that the polygenic mouse of T2DM, TALLYHO/JngJ, most accurately recapitulates the diabetic osteoporotic phenotype seen in humans and that the intermittent systemic administration of hPTH (1–34) increases fracture healing in T2DM murine models by increasing the proliferation of mesenchymal stem cells. © 2020 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.

In this paper, we consider a multi-user (MU) radio-frequency (RF) beam training scenario with user selection. We propose a new beam training scheme that alleviates the latency issue in the conventional IEEE 802.11ad by adopting a sequential downlink-downlink transmit sector sweep combination. Then, we analyze the average rate performance of several RF beam training schemes in two different asymptotic scenarios. In addition, we characterize the performance gain of the proposed method over other schemes. Our analytic results confirm that the proposed method achieves the average rate performance of the optimal fullsearch method in the asymptotic region with much reduced training overhead. It is shown from the simulation results that the proposed scheme outperforms the conventional beam training schemes and achieves a 35% performance gain over the optimal full search scheme when considering the beam training overhead in practical MU millimeter-wave channel environments. We also confirm that our analytical results match well with the numerical results.

This paper describes data of an integrated process, cryogenic energy storage system combined with liquefied natural gas (LNG) regasification process. The data in this paper is associated with the article entitled âConceptual Design and Exergy Analysis of Combined Cryogenic Energy Storage and LNG Regasification Processes: Cold and Power Integrationâ (Lee et al., 2017) [1]. The data includes the sensitivity case study dataset of the air flow rate and the heat exchanging feasibility data by composite curves. The data is expected to be helpful to the cryogenic energy process development.

Amplify-and-forward (AF) relaying is an efficient way to extend radio range and improve link reliability with a low implementation cost. While the research on the AF relaying in a single-antenna scenario has matured, its application to broadband radio transmission utilizing multiple-input multiple-output techniques still needs more effort to overcome several practical challenges, such as large overheads for channel estimation and vulnerability to the channel estimation errors. This paper reviews some recently proposed linear transceiver designs based on the minimum mean squared error (MSE) criterion and shows that the proposed MSE decomposition and relaxation method can lead to an efficient solution for those challenges. Insightful observations and comprehensive discussions are also made on both analytical and numerical results from practical implementation perspectives.