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Abstract Rapid and accurate identification of the bacteria responsible for sepsis is paramount for effective patient care. Molecular diagnostic methods, such as polymerase chain reaction (PCR), encounter challenges in sepsis due to inhibitory compounds in the blood, necessitating their removal for precise analysis. In this study we present an innovative approach that utilizes vancomycin (Van) and allantoin (Al)-conjugated polydopamine (PDA)-coated magnetic nanoparticles (MNPs) for the rapid and automated enrichment of bacteria and their DNA extraction from blood without inducing clumping and aggregation of blood. Al/Van-PDA-MNPs, facilitated by IMS, eliminate the need for preliminary sample treatments, providing a swift and efficient method for bacterial concentration and DNA extraction within an hour. Employing Al/Van-PDA-MNPs within an automated framework has markedly improved our ability to pre-concentrate various Gram-negative and Gram-positive bacteria directly from blood samples. This advancement has effectively reduced the detection threshold to 102 colony-forming unit/mL by both PCR and quantitative PCR. The method's expedited processing time, combined with its precision, positions it as a feasible diagnostic tool for diverse healthcare settings, ranging from small clinics to large hospitals. Furthermore, the innovative application of nanoparticles for DNA extraction holds promising potential for advancing sepsis diagnostics, enabling earlier interventions and improving patient outcomes.

This paper presents a data-driven approach to maximize the power of a wind farm by developing a dynamic mode decomposition with input and output for reduced order model (DMDior)-based reduced order model (ROM) for model predictive control (MPC). The main goal of this research is to efficiently model and manage the complex flow field within a wind farm to enhance power production. We leveraged DMDior to transform extensive high-dimensional flow data into an accurate yet simplified ROM, which successfully represents the essential dynamic features of wind flow, including the critical interactions between turbines and their adaptive response to environmental changes. Based on this ROM, the MPC framework was carefully designed. MPC uses this model to dynamically adjust the yaw angle of a wind turbine to optimally match changing wind patterns to maximize power output. The system also incorporates an adaptive Kalman filter designed for the state estimation in MPC applications. This estimation is critical to the effective execution of the MPC in each iteration. This ensures that the MPC operates based on the most up-to-date and accurate representation of the wind farm’s state, improving the overall reliability and efficiency of the control strategy. This approach demonstrates a practical and effective way to increase the power output of a wind farm, with experimental results indicating a power increase of about 4.72%.

In this paper, we introduce a data-driven approach to wind farm control, offering an alternative to the FLORIS wind farm simulator. Our method estimates the power of a wind farm and determines the optimal yaw angle to maximize power generation. Initially, we develop a power estimation neural network using data from FLORIS for power estimation and validate its accuracy and reliability. Subsequently, this power estimation neural network is employed to determine the optimal yaw angle for maximum power production. The efficacy of this yaw decision neural network is verified through various performance metrics. We then present dynamic simulations by integrating the yaw decision neural network, constructed through our data-driven approach, with a dynamic wind farm simulator. We believe this addresses the limitations of FLORIS, a steady-state simulator. Our results demonstrate the effectiveness of the proposed yaw decision neural network in dynamic environments, underscoring the potential of a data-driven approach to overcome the challenges posed by the steady-state wind farm simulator. This study offers innovative solutions for the efficient control and optimization of wind farm.

Abstract To improve cloud simulation in a general circulation model, we develop a new cloud macrophysics scheme that treats detrained cumulus generated by convective detrainment process separately from pure stratus; prognoses two symmetric triangular probability density functions of total specific humidity for each detrained cumulus and pure stratus; and diagnoses both cloud fraction and cloud condensate in all liquid, ice, and mixed‐phases in a consistent and unified way without any adjustment to remove empty or very dense cloud. Supersaturation is allowed within ice cloud. The new scheme (“NEW”) is compared with the previous model (“OLD”) using single‐column simulations for subtropical marine stratocumulus (DYCOMS2) and continental deep convection (ARM97) cases. In DYCOMS2, both NEW and OLD produce vertical profiles of grid‐mean cloud condensate similar to large‐eddy simulation. In ARM97, compared with OLD, NEW simulates less sporadic vertical profiles of in‐cloud condensates, due to consistent diagnosis of cloud fraction and cloud condensate; more continuously‐varying detrained cumulus with time, due to prognostic treatment of detrained cumulus; and ice cloud fraction and ice condensate similar to those of OLD, in spite of completely different treatment of ice cloud processes. The global performance of NEW is similar to OLD with improved relative humidity. Compared to OLD, NEW simulates more and improved cloud condensate, but less and degraded cloud fraction, particularly, in the lower troposphere. Detrained cumulus is moister and colder and has a larger moisture variance than pure stratus. Overall, NEW simulates stronger condensation‐deposition rates than OLD, due in part to the separate treatment of detrained cumulus and pure stratus.

Abstract To improve the simulation of nocturnal precipitation, we develop a parameterization for the elevated convection that is launched from the level of maximum grid‐mean moist static energy, when grid‐mean vertical flow is upward at the launching interface. The parameterized elevated convection is forced by both cold pool‐driven and partially resolved external mesoscale organized flows. Properties of the external mesoscale flow are estimated from grid‐mean vertical velocity and three dimensional advection tendencies of temperature and moisture. The new parameterization is implemented into a unified convection scheme (UNICON) and tested for both the single‐column case at the Southern Great Plain (SGP) site in US and in global simulations. At the SGP site, the parameterized elevated convection strengthens nocturnal convection, increases nocturnal precipitation, and better simulates the observed diurnal cycle of precipitation. It appears that the elevated and surface‐based convections interact with each other by stabilizing the atmospheric column, which affects subsequent convection. Global simulation shows that the elevated convection mostly occurs over the continents during the night, and also over the oceanic mid‐latitude warm air advection and storm track regions during summer. Without degrading global mean climate, the elevated convection improves the simulation of nocturnal precipitation in the mid‐US but simulates somewhat strong nocturnal precipitation in northeastern Asia. It seems that a key to simulate observed nocturnal precipitation is to appropriately parameterize the impacts of external organized flow on the elevated convection.

Chemoresistance is a major cause of treatment failure in many cancers. However, the life cycle of cancer cells as they respond to and survive environmental and therapeutic stress is understudied. In this study, we utilized a microfluidic device to induce the development of doxorubicin-resistant (DOXR) cells from triple negative breast cancer (TNBC) cells within 11 days by generating gradients of DOX and medium. In vivo chemoresistant xenograft models, an unbiased genome-wide transcriptome analysis, and a patient data/tissue analysis all showed that chemoresistance arose from failed epigenetic control of the nuclear protein-1 (NUPR1)/histone deacetylase 11 (HDAC11) axis, and high NUPR1 expression correlated with poor clinical outcomes. These results suggest that the chip can rapidly induce resistant cells that increase tumor heterogeneity and chemoresistance, highlighting the need for further studies on the epigenetic control of the NUPR1/HDAC11 axis in TNBC.

Induced pluripotent stem cell (iPSC)-derived cardiac organoids offer a versatile platform for personalized cardiac toxicity assessment, drug screening, disease modeling, and regenerative therapies. While previous image-based contractility analysis techniques allowed the assessment of contractility of two-dimensional cardiac models, they face limitations, including encountering high noise levels when applied to three-dimensional organoid models and requiring expensive equipment. Additionally, they offer fewer functional parameters compared to commercial software. To address these challenges, we developed an open-source, particle image velocimetry-based software (PIV-MyoMonitor) and demonstrated its capacity for accurate contractility analysis in both two- and three-dimensional cardiac models using standard lab equipment. Comparisons with four other open-source software programs highlighted the capability of PIV-MyoMonitor for more comprehensive quantitative analysis, providing 22 functional parameters and enhanced video outputs. We showcased its applicability in drug screening by characterizing the response of cardiac organoids to a known isotropic drug, isoprenaline. In sum, PIV-MyoMonitor enables reliable contractility assessment across various cardiac models without costly equipment or software. We believe this software will benefit a broader scientific community.

Abstract Engineered three-dimensional (3D) tissue constructs have emerged as a promising solution for regenerating damaged muscle tissue resulting from traumatic or surgical events. 3D architecture and function of the muscle tissue constructs can be customized by selecting types of biomaterials and cells that can be engineered with desired shapes and sizes through various nano- and micro-fabrication techniques. Despite significant progress in this field, further research is needed to improve, in terms of biomaterials properties and fabrication techniques, the resemblance of function and complex architecture of engineered constructs to native muscle tissues, potentially enhancing muscle tissue regeneration and restoring muscle function. In this review, we discuss the latest trends in using nano-biomaterials and advanced nano-/micro-fabrication techniques for creating 3D muscle tissue constructs and their regeneration ability. Current challenges and potential solutions are highlighted, and we discuss the implications and opportunities of a future perspective in the field, including the possibility for creating personalized and biomanufacturable platforms.

Abstract The current standard method of diagnosing coronavirus disease 2019 (COVID-19) involves uncomfortable and invasive nasopharyngeal (NP) sampling using cotton swabs (CS), which can be unsuitable for self-testing. Although mid-turbinate sampling is an alternative, it has a lower diagnostic yield than NP sampling. Nasal wash (NW) has a similar diagnostic yield to NP sampling, but is cumbersome to perform. In this study, we introduce a 3D printed fluidic swab (3DPFS) that enables easy NW sampling for COVID-19 testing with improved diagnostic yield. The 3DPFS comprises a swab head, microchannel, and socket that can be connected to a syringe containing 250 µL of NW solution. The 3DPFS efficiently collects nasal fluid from the surface of the nasal cavity, resulting in higher sensitivity than CS for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This was confirmed by both reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and lateral flow assays (LFA) in virus-spiked nasal samples and clinical samples. Additionally, users reported greater comfort when using the 3DPFS compared to CS. These findings suggest that the 3DPFS can improve the performance of COVID-19 testing by facilitating efficient and less painful nasal sample collection.

Abstract The COVID‐19 outbreak has caused public and global health crises. However, the lack of on‐site fast, reliable, sensitive, and low‐cost reverse transcription polymerase chain reaction (RT‐PCR) testing limits early detection, timely isolation, and epidemic prevention and control. Here, the authors report a rapid mobile efficient diagnostics of infectious diseases via on‐chip ‐RT‐quantitative PCR (RT‐qPCR): MEDIC‐PCR. First, the authors use a roll‐to‐roll printing process to accomplish low‐cost carbon‐black‐based disposable PCR chips that enable rapid LED‐induced photothermal PCR cycles. The MEDIC‐PCR can perform RT (3 min), and PCR (9 min) steps. Further, the cohort of 89 COVID‐19 and 103 non‐COVID‐19 patients testing is completed by the MEDIC‐PCR to show excellent diagnostic accuracy of 97%, sensitivity of 94%, and specificity of 98%. This MEDIC‐PCR can contribute to the preventive global health in the face of a future pandemic.

IntroductionThe phenotypic screening of drugs against Balamuthia mandrillaris, a neuropathogenic amoeba, involves two simultaneous phases: an initial step to test amoebicidal activity followed by an assay for cytotoxicity to host cells. The emergence of three-dimensional (3D) cell cultures has provided a more physiologically relevant model than traditional 2D cell culture for studying the pathogenicity of B. mandrillaris. However, the measurement of ATP, a critical indicator of cell viability, is complicated by the overgrowth of B. mandrillaris in coculture with host cells during drug screening, making it challenging to differentiate between amoebicidal activity and drug toxicity to human cells.MethodsTo address this limitation, we introduce a novel assay that utilizes three-dimensional hanging spheroid plates (3DHSPs) to evaluate both activities simultaneously on a single platform.Results and discussionOur study showed that the incubation of neurospheroids with clinically isolated B. mandrillaris trophozoites resulted in a loss of neurospheroid integrity, while the ATP levels in the neurospheroids decreased over time, indicating decreased host cell viability. Conversely, ATP levels in isolated trophozoites increased, indicating active parasite metabolism. Our findings suggest that the 3DHSP-based assay can serve as an endpoint for the phenotypic screening of drugs against B. mandrillaris, providing a more efficient and accurate approach for evaluating both parasite cytotoxicity and viability.

Abstract Background Sepsis is caused mainly by infection in the blood with a broad range of bacterial species. It can be diagnosed by molecular diagnostics once compounds in the blood that interfere with molecular diagnostics are removed. However, this removal relies on ultracentrifugation. Immunomagnetic separation (IMS), which typically uses antibody-conjugated silica-coated magnetic nanoparticles (Ab-SiO2-MNPs), has been widely applied to isolate specific pathogens in various types of samples, such as food and environmental samples. However, its direct use in blood samples containing bacteria is limited due to the aggregation of SiO2-MNPs in the blood and inability to isolate multiple species of bacteria causing sepsis. Results In this study, we report the synthesis of vancomycin-conjugated polydopamine-coated (van-PDA-MNPs) enabling preconcentration of multiple bacterial species from blood without aggregation. The presence of PDA and van on MNPs was verified using transmission electron microscopy, X-ray photoelectron spectroscopy, and energy disruptive spectroscopy. Unlike van-SiO2-MNPs, van-PDA-MNPs did not aggregate in the blood. Van-PDA-MNPs were able to preconcentrate several species of Gram-positive bacteria in the blood, lowering the limit of detection (LOD) to 10 colony forming units/mL by polymerase chain reaction (PCR) and quantitative PCR (qPCR). This is 10 times more sensitive than the LOD obtained by PCR and qPCR using van-SiO2-MNPs. Conclusion These results suggest that PDA-MNPs can avoid aggregation in blood and be conjugated with receptors, thereby improving the sensitivity of molecular diagnostics of bacteria in blood samples.

Abstract The contaminated healthcare environment plays an important role in the spread of multidrug-resistant organisms (MDROs) and Clostridioides difficile. This study aimed to evaluate the antimicrobial effects of ozone generated by a dielectric barrier discharge (DBD) plasma reactor on various materials that were contaminated by vancomycin-resistant Enterococcus faecium (VRE), carbapenem-resistant Klebsiella pneumoniae (CRE), carbapenem-resistant Pseudomonas aeruginosa (CRPA), carbapenem-resistant Acinetobacter baumannii (CRAB) and C. difficile spores. Various materials contaminated by VRE, CRE, CRPA, CRAB and C. difficile spores were treated with different ozone concentrations and exposure times. Atomic force microscopy (AFM) demonstrated bacterial surface modifications following ozone treatment. When an ozone dosage of 500 ppm for 15 min was applied to VRE and CRAB, about 2 or more log10 reduction was observed in stainless steel, fabric and wood, and a 1–2 log10 reduction in glass and plastic. Spores of C. difficile were more resistant to ozone than were all other tested organisms. On AFM, the bacterial cells, following ozone treatment, were swollen and distorted. The ozone generated by the DBD plasma reactor provided a simple and valuable decontamination tool for the MDROs and C. difficile spores, which are known as common pathogens in healthcare-associated infections.

Abstract Bacterial contamination of blood products is a major problem in transfusion medicine, in terms of both morbidity and mortality. Platelets (PLTs) are stored at room temperature (under constant agitation) for more than 5 days, and bacteria can thus grow significantly from a low level to high titers. However, conventional methods like blood culture and lateral flow assay have disadvantages such as long detection time, low sensitivity, and the need for a large volume of blood components. We used real-time polymerase chain reaction (PCR) assays with antibiotic-conjugated magnetic nanobeads (MNBs) to detect enriched Gram-positive and -negative bacteria. The MNBs were coated with polyethylene glycol (PEG) to prevent aggregation by blood components. Over 80% of all bacteria were captured by the MNBs, and the levels of detection were 101 colony forming unit [CFU]/mL and 102 CFU/mL for Gram-positive and -negative bacteria, respectively. The detection time is

Abstract Background Most high-throughput screening (HTS) systems studying the cytotoxic effect of chimeric antigen receptor (CAR) T cells on tumor cells rely on two-dimensional cell culture that does not recapitulate the tumor microenvironment (TME). Tumor spheroids, however, can recapitulate the TME and have been used for cytotoxicity assays of CAR T cells. But a major obstacle to the use of tumor spheroids for cytotoxicity assays is the difficulty in separating unbound CAR T and dead tumor cells from spheroids. Here, we present a three-dimensional hanging spheroid plate (3DHSP), which facilitates the formation of spheroids and the separation of unbound and dead cells from spheroids during cytotoxicity assays. Results The 3DHSP is a 24-well plate, with each well composed of a hanging dripper, spheroid wells, and waste wells. In the dripper, a tumor spheroid was formed and mixed with CAR T cells. In the 3DHSP, droplets containing the spheroids were deposited into the spheroid separation well, where unbound and dead T and tumor cells were separated from the spheroid through a gap into the waste well by tilting the 3DHSP by more than 20°. Human epidermal growth factor receptor 2 (HER2)-positive tumor cells (BT474 and SKOV3) formed spheroids of approximately 300–350 μm in diameter after 2 days in the 3DHSP. The cytotoxic effects of T cells engineered to express CAR recognizing HER2 (HER2-CAR T cells) on these spheroids were directly measured by optical imaging, without the use of live/dead fluorescent staining of the cells. Our results suggest that the 3DHSP could be incorporated into a HTS system to screen for CARs that enable T cells to kill spheroids formed from a specific tumor type with high efficacy or for spheroids consisting of tumor types that can be killed efficiently by T cells bearing a specific CAR. Conclusions The results suggest that the 3DHSP could be incorporated into a HTS system for the cytotoxic effects of CAR T cells on tumor spheroids. Graphical Abstract

Nanoparticles (NPs) are commonly used in healthcare and nanotherapy, but their toxicity at high concentrations is well-known. Recent research has shown that NPs can also cause toxicity at low concentrations, disrupting various cellular functions and leading to altered mechanobiological behavior. While researchers have used different methods to investigate the effects of NPs on cells, including gene expression and cell adhesion assays, the use of mechanobiological tools in this context has been underutilized. This review emphasizes the importance of further exploring the mechanobiological effects of NPs, which could reveal valuable insights into the mechanisms behind NP toxicity. To investigate these effects, different methods, including the use of polydimethylsiloxane (PDMS) pillars to study cell motility, traction force production, and rigidity sensing contractions, have been employed. Understanding how NPs affect cell cytoskeletal functions through mechanobiology could have significant implications, such as developing innovative drug delivery systems and tissue engineering techniques, and could improve the safety of NPs for biomedical applications. In summary, this review highlights the significance of incorporating mechanobiology into the study of NP toxicity and demonstrates the potential of this interdisciplinary field to advance our knowledge and practical use of NPs.

Abstract Filamin A (FLNa) belongs to an actin-binding protein family in binding and cross-linking actin filaments into a three-dimensional structure. However, little attention has been given to its mechanobiological role in cancer cells. Here, we quantitatively investigated the role of FLNa by analyzing the following parameters in negative control (NC) and FLNa-knockdown (KD) U87 glioma cells using submicron pillars (900 nm diameter and 2 μm height): traction force (TF), rigidity sensing ability, cell aspect ratio, migration speed, and invasiveness. During the initial phase of cell adhesion (

This paper conducts a comparative analysis of three wind farm simulators, examining the influence of wake on the local wind speed and power output for downstream turbines using experimental data. The study features experiments in three distinct scenarios, evaluating differences among the simulators by calculating the local wind speed and power for each. Each simulator employs a unique wake model, which substantially affects the local wind speed experienced by downstream turbines. Furthermore, the experiment involves adjusting parameter values for each simulator to assess their respective impacts on wind farm performance. The findings of this research are expected to play an important role in investigations related to power optimization and wake effects in the wind farm control.

Abstract Background Nanoparticles are being increasingly used in biomedical applications owing to their unique physical and chemical properties and small size. However, their biophysical assessment and evaluation of side-effects remain challenging. We addressed this issue by investigating the effects of silica-coated magnetic nanoparticles containing rhodamine B isothiocyanate [MNPs@SiO2(RITC)] on biophysical aspects, such as membrane fluidity and traction force of human embryonic kidney 293 (HEK293) cells. We further extended our understanding on the biophysical effects of nanoparticles on cells using a combination of metabolic profiling and transcriptomic network analysis. Results Overdose (1.0 μg/µL) treatment with MNPs@SiO2(RITC) induced lipid peroxidation and decreased membrane fluidity in HEK293 cells. In addition, HEK293 cells were morphologically shrunk, and their aspect ratio was significantly decreased. We found that each traction force (measured in micropillar) was increased, thereby increasing the total traction force in MNPs@SiO2(RITC)-treated HEK293 cells. Due to the reduction in membrane fluidity and elevation of traction force, the velocity of cell movement was also significantly decreased. Moreover, intracellular level of adenosine triphosphate (ATP) was also decreased in a dose-dependent manner upon treatment with MNPs@SiO2(RITC). To understand these biophysical changes in cells, we analysed the transcriptome and metabolic profiles and generated a metabotranscriptomics network, which revealed relationships among peroxidation of lipids, focal adhesion, cell movement, and related genes and metabolites. Furthermore, in silico prediction of the network showed increment in the peroxidation of lipids and suppression of focal adhesion and cell movement. Conclusion Taken together, our results demonstrated that overdose of MNPs@SiO2(RITC) impairs cellular movement, followed by changes in the biophysical properties of cells, thus highlighting the need for biophysical assessment of nanoparticle-induced side-effects.

Abstract Background Nanoparticles (NPs) can enter cells and cause cellular dysfunction. For example, reactive oxygen species generated by NPs can damage the cytoskeleton and impair cellular adhesion properties. Previously, we reported that cell spreading and protrusion structures such as lamellipodia and filopodia was reduced when cells are treated with silica-coated magnetic nanoparticles incorporating rhodamine B isothiocyanate (MNPs@SiO2(RITC)), even at 0.1 μg/μL. These protruded structures are involved in a cell’s rigidity sensing, but how these NPs affect rigidity sensing is unknown. Results Here, we report that the rigidity sensing of human embryonic kidney (HEK293) cells was impaired even at 0.1 μg/μL of MNPs@SiO2(RITC). At this concentration, cells were unable to discern the stiffness difference between soft (5 kPa) and rigid (2 MPa) flat surfaces. The impairment of rigidity sensing was further supported by observing the disappearance of locally contracted elastomeric submicron pillars (900 nm in diameter, 2 μm in height, 24.21 nN/μm in stiffness k) under MNPs@SiO2(RITC) treated cells. A decrease in the phosphorylation of paxillin, which is involved in focal adhesion dynamics, may cause cells to be insensitive to stiffness differences when they are treated with MNPs@SiO2(RITC). Conclusions Our results suggest that NPs may impair the rigidity sensing of cells even at low concentrations, thereby affecting cell adhesion and spreading.

Mitotic spindle orientation is postulated to be regulated by two mechanisms: (1) Hertwig’s rule in which cells divide perpendicular to their major axis and (2) cortical cues arising from the spatial distribution of extracellular matrix. It was shown that cortical cues override cell geometry in dictating mitotic spindle orientation for cells cultured on 2D surfaces. In this study, we seek to investigate the interplay between cell geometry and cortical cues in determining mitotic spindle orientation for cells cultured on 3D microgratings. Here, cell geometry is manipulated by culturing RPE-1 and HeLa cells on different micrograting widths while cortical cues are modified by ablating focal adhesion contacts using cytochalasin D. We find a significant correlation between cell aspect ratio and spindle angles. Unexpectedly, disruption of cortical cues through focal adhesion inhibition did not lead to spindle misorientation in both RPE-1 and HeLa. Instead, spindle orientation was perturbed by disruption of microtubules (MTs) to a greater degree than abolishment of cortical focal adhesion cues. These results indicate that cell geometry is more important than cortical cues in maintaining proper spindle orientation and that MTs play an important role in spindle orientation for cells grown on 3D microgratings. To incorporate our findings of cell geometry and MTs as important players in spindle orientation, we developed a computational force balance model that relates both cell elongation, astral MTs to spindle angles and found good agreement between the model and experimental data.

Abstract The previously proposed parameterization for the integrated vertical overlap of cumulus and stratus is generalized to handle both conventional exponential‐random stratus overlap and nonconventional (i.e., other than exponential‐random) cumulus overlap in a simultaneous way. With the parameterization of the decorrelation length scale of stratus as a function of vertical wind shear, our parameterization simulates various interactive feedback between vertical cloud overlap and other physical processes. This interactive vertical overlap parameterization of cumulus and stratus was implemented into all relevant physics parameterizations (i.e., convection, stratus microphysics, radiation, aerosol wet deposition, and aerosol activation at the base of stratus) of the Seoul National University Atmosphere Model version 0 with a Unified Convection Scheme (SAM0‐UNICON) in a fully consistent way. It is shown that the overall performance of the interactive cloud overlap parameterization to simulate the observed mean climate is similar to that of the original overlap parameterization. Given that an intensive tuning has not yet been performed with the new overlap parameterization, this result is quite encouraging.

This paper presents an efficient three-dimensional (3D) Dubins path design and a new continuous curvature path-smoothing algorithm. The proposed 3D Dubins path is a simple extension of the 2D path and serves as a reference path generator to guide the proposed smoothing algorithm. In the smoothing algorithm, the reference path is approximated by several cubic Bezier curves to generate a parametric path that simultaneously satisfies curvature continuity and maximum curvature requirements. The algorithm also provides a criterion to select a required number of Bezier curves to strictly meet the maximum curvature constraint. Therefore, our algorithm can be used for 3D path-following applications in many areas such as aerospace and robotics. The numerical simulation results show that the proposed algorithm produces a continuous curvature path that passes through all waypoints with a slight increase in path length compared with the original 3D Dubins reference path.

Abstract Modifications in cumulus parameterizations that improve Madden‐Julian oscillation (MJO) simulation tend to degrade the mean state—known as the MJO‐mean state trade‐off. The impacts of parameterizing mesoscale convective organization on the relationship between the MJO and the mean state simulation fidelity are examined. A series of experiments are made with a general circulation model that parameterizes the mesoscale convective organization and simulates well both the MJO and the mean state. In the control simulation, a prognostic nondimensional variable (Ω) represents the degree of convective organization. In order to examine the effect of the parameterized convective organization, fixed Ω values are imposed in a series of constrained experiments. The fixed‐Ω simulations show a negative relationship between the MJO and the mean state simulation fidelity. The control simulation is deviated from the negative relationship, suggesting the parameterized mesoscale convective organization helps general circulation models to mitigate the MJO‐mean state trade‐off.

In the contemporary battlefield where complexity has increased, the enhancement of the role and ability of missiles has become crucial. Thus, missile guidance systems are required to be further developed in a more intelligent and autonomous way to deal with complicated environments. In this paper, we propose novel missile guidance laws using reinforcement learning, which can autonomously avoid obstacles and terrains in complicated environments with limited prior information and even without the need of off-line trajectory or waypoint generation. The proposed guidance laws are focused on two mission scenarios: the first is with planar obstacles, which is used to cope with maritime operations, and the second is with complex terrain, which is used to cope with land operations. We present the detailed design processes for both scenarios, including a neural network architecture, reward function selection, and training method. Simulation results are provided to show the feasibility and effectiveness of the proposed guidance laws and some important aspects are discussed in terms of their advantages and limitations.

Abstract Most general circulation models compute radiation fluxes by assuming that water vapor is uniform within individual grid layers, which leads to an underestimation of satellite‐observed longwave (LW) cloud radiative forcing (LWCF). To fix this problem, we calculated water vapor content separately for clear and cloudy portions and used them to compute LW radiation. The impacts of this modification were examined by comparing two global simulations with and without the modification (NEW and OLD, respectively). Global‐annual mean LWCF from NEW was 1.8 W m−2 higher than that of OLD, thus remedying a long‐standing negative bias of LWCF. This improvement is a combined result of more clear‐sky and less all‐sky upward LW flux at the top of the atmosphere than OLD. Large increases in LWCF and clear‐sky LW flux occurred in the tropical deep convection and midlatitude storm track regions where upper‐ and middle‐level clouds are abundant. Although only the LW radiation scheme was modified, global‐annual mean shortwave cloud radiative forcing also increased, particularly in the vicinity of the eastern subtropical marine stratocumulus decks through radiative feedback processes. With this improved treatment, it may be possible to tune general circulation models in a more flexible and physical way without introducing compensating errors.

Extracellular vesicles (EVs) are a group of membrane vesicles that play important roles in cell-to-cell and interspecies/interkingdom communications by modulating the pathophysiological conditions of recipient cells. Recent evidence has implied their potential roles in the gut–brain axis (GBA), which is a complex bidirectional communication system between the gut environment and brain pathophysiology. Despite the evidence, the roles of EVs in the gut microenvironment in the GBA are less highlighted. Moreover, there are critical challenges in the current GBA models and analyzing techniques for EVs, which may hinder the research. Currently, advances in organ-on-a-chip (OOC) technologies have provided a promising solution. Here, we review the potential effects of EVs occurring in the gut environment on brain physiology and behavior and discuss how to apply OOCs to research the GBA mediated by EVs in the gut microenvironment.

Shiga toxin-producing Escherichia coli (STEC) infects humans by colonizing the large intestine, and causes kidney damage by secreting Shiga toxins (Stxs). The increased secretion of Shiga toxin 2 (Stx2) by some antibiotics, such as ciprofloxacin (CIP), increases the risk of hemolytic–uremic syndrome (HUS), which can be life-threatening. However, previous studies evaluating this relationship have been conflicting, owing to the low frequency of EHEC infection, very small number of patients, and lack of an appropriate animal model. In this study, we developed gut–kidney axis (GKA) on chip for co-culturing gut (Caco-2) and kidney (HKC-8) cells, and observed both STEC O157:H7 (O157) infection and Stx intoxication in the gut and kidney cells on the chip, respectively. Without any antibiotic treatment, O157 killed both gut and kidney cells in GKA on the chip. CIP treatment reduced O157 infection in the gut cells, but increased Stx2-induced damage in the kidney cells, whereas the gentamycin treatment reduced both O157 infection in the gut cells and Stx2-induced damage in the kidney cells. This is the first report to recapitulate a clinically relevant situation, i.e., that CIP treatment causes more damage than gentamicin treatment. These results suggest that GKA on chip is very useful for simultaneous observation of O157 infections and Stx2 poisoning in gut and kidney cells, making it suitable for studying the effects of antibiotics on the risk of HUS.

Nanoparticles (NPs) in biomedical applications have benefits owing to their small size. However, their intricate and sensitive nature makes an evaluation of the adverse effects of NPs on health necessary and challenging. Since there are limitations to conventional toxicological methods and omics analyses provide a more comprehensive molecular profiling of multifactorial biological systems, omics approaches are necessary to evaluate nanotoxicity. Compared to a single omics layer, integrated omics across multiple omics layers provides more sensitive and comprehensive details on NP-induced toxicity based on network integration analysis. As multi-omics data are heterogeneous and massive, computational methods such as machine learning (ML) have been applied for investigating correlation among each omics. This integration of omics and ML approaches will be helpful for analyzing nanotoxicity. To that end, mechanobiology has been applied for evaluating the biophysical changes in NPs by measuring the traction force and rigidity sensing in NP-treated cells using a sub-elastomeric pillar. Therefore, integrated omics approaches are suitable for elucidating mechanobiological effects exerted by NPs. These technologies will be valuable for expanding the safety evaluations of NPs. Here, we review the integration of omics, ML, and mechanobiology for evaluating nanotoxicity.

Circulating tumor cells (CTCs) are an indicator of metastatic progression and relapse. Since non-CTC cells such as red blood cells outnumber CTCs in the blood, the separation and enrichment of CTCs is key to improving their detection sensitivity. The ATP luminescence assay can measure intracellular ATP to detect cells quickly but has not yet been used for CTC detection in the blood because extracellular ATP in the blood, derived from non-CTCs, interferes with the measurement. Herein, we report on the improvement of the ATP luminescence assay for the detection of CTCs by separating and concentrating CTCs in the blood using a 3D printed immunomagnetic concentrator (3DPIC). Because of its high-aspect-ratio structure and resistance to high flow rates, 3DPIC allows cancer cells in 10 mL to be concentrated 100 times within minutes. This enables the ATP luminescence assay to detect as low as 10 cells in blood, thereby being about 10 times more sensitive than when commercial kits are used for CTC concentration. This is the first time that the ATP luminescence assay was used for the detection of cancer cells in blood. These results demonstrate the feasibility of 3DPIC as a concentrator to improve the detection limit of the ATP luminescence assay for the detection of CTCs.

Formaldehyde (FA) is a colorless, flammable, foul-smelling chemical used in building materials and in the production of numerous household chemical goods. Herein, a fluorescent chemosensor for FA is designed and prepared using a selective organ-targeting probe containing naphthalimide as a fluorophore and hydrazine as a FA-binding site. The amine group of the hydrazine reacts with FA to form a double bond and this condensation reaction is accompanied by a shift in the absorption band of the probe from 438 nm to 443 nm upon the addition of FA. Further, the addition of FA is shown to enhance the emission band at 532 nm relative to the very weak fluorescent emission of the probe itself. Moreover, a high specificity is demonstrated towards FA over other competing analytes such as the calcium ion (Ca2+), magnesium ion (Mg2+), acetaldehyde, benzaldehyde, salicylaldehyde, glucose, glutathione, sodium sulfide (Na2S), sodium hydrosulfide (NaHS), hydrogen peroxide (H2O2), and the tert-butylhydroperoxide radical. A typical two-photon dye incorporated into the probe provides intense fluorescence upon excitation at 800 nm, thus demonstrating potential application as a two-photon fluorescent probe for FA sensing. Furthermore, the probe is shown to exhibit a fast response time for the sensing of FA at room temperature and to facilitate intense fluorescence imaging of breast cancer cells upon exposure to FA, thus demonstrating its potential application for the monitoring of FA in living cells. Moreover, the presence of the phenylsulfonamide group allows the probe to visualize dynamic changes in the targeted Golgi apparatus. Hence, the as-designed probe is expected to open up new possibilities for unique interactions with organ-specific biological molecules with potential application in early cancer cell diagnosis.

Despite the potential in fabrication of microfluidic paper-based analytical devices (μPADs) for point-of-care testing (POCT) kits, the development of simple, accurate, and rapid devices with higher sensitivity remains challenging. Here, we report a novel method for 3D-μPAD fabrication with enclosed channels using vat photopolymerization to avoid fluid evaporation. In detail, height of the enclosed channels was adjusted from 0.3 to 0.17 mm by varying the UV exposure time from 1 to 4 s for the top barrier, whereas the exposure time for the bottom and side barriers was fixed. As a result, sample flow in the enclosed channels of 3D-μPADs showed lesser wicking speed with very scant evaporation compared to that in the hemi channels in the 3D-μPADs. The stoppage of evaporation in the enclosed channels significantly improved the gray intensity and uniformity in the detection zone of the 3D-μPADs, resulting in as low as 0.3 mM glucose detection. Thus 3D-μPADs with enclosed channels showed enhanced sensitivity compared to the 3D-μPADs with hemi channels when dealing with a small volume sample. Our work provides a new insight into 3D-μPAD design with enclosed channels, which redefines the methodology in 3D printing.

A new simple and practical guidance logic is proposed for a vehicle to follow a general continuous curvature path defined in a three-dimensional space. The proposed guidance logic is formulated in such a way that the guidance law is to generate the command acceleration such that a vehicle pursues the designed moving virtual target, and this eventually makes a vehicle to follow a desired path. The position and velocity of the virtual target are specified explicitly by introducing the concept of the projection point and the tangentially receding distance. Numerical simulations are conducted to evaluate the precise path-following capability of the proposed guidance logic.

This paper proposes that the deep neural network-based guidance (DNNG) law replace the proportional navigation guidance (PNG) law. This approach is performed by adopting a supervised learning (SL) method using a large amount of simulation data from the missile system with PNG. Then, the proposed DNNG is compared with the PNG, and its performance is evaluated via the hitting rate and the energy function. In addition, the DNN-based only line-of-sight (LOS) rate input guidance (DNNLG) law, in which only the LOS rate is an input variable, is introduced and compared with the PN and DNNG laws. Then, the DNNG and DNNLG laws examine behavior in an initial position other than the training data.

Paper-based microfluidic analysis devices (μPADs) have attracted attention as a cost-effective platform for point-of-care testing (POCT), food safety, and environmental monitoring. Recently, three-dimensional (3D)-μPADs have been developed to improve the performance of μPADs. For accurate diagnosis of diseases, however, 3D-μPADs need to be developed to simultaneously detect multiple biomarkers. Here, we report a 3D-μPADs platform for the detection of multiple biomarkers that can be analyzed and diagnosed with a smartphone. The 3D-μPADs were fabricated using a 3D digital light processing printer and consisted of a sample reservoir (300 µL) connected to 24 detection zones (of 4 mm in diameter) through eight microchannels (of 2 mm in width). With the smartphone application, eight different biomarkers related to various diseases were detectable in concentrations ranging from normal to abnormal conditions: glucose (0–20 mmol/L), cholesterol (0–10 mmol/L), albumin (0–7 g/dL), alkaline phosphatase (0–800 U/L), creatinine (0–500 µmol/L), aspartate aminotransferase (0–800 U/L), alanine aminotransferase (0–1000 U/L), and urea nitrogen (0–7.2 mmol/L). These results suggest that 3D-µPADs can be used as a POCT platform for simultaneous detection of multiple biomarkers.

Reinforcement learning is generating considerable interest in terms of building guidance law and solving optimization problems that were previously difficult to solve. Since reinforcement learning-based guidance laws often show better robustness than a previously optimized algorithm, several studies have been carried out on the subject. This paper presents a new approach to training missile guidance law by reinforcement learning and introducing some notable characteristics. The novel missile guidance law shows better robustness to the controller-model compared to the proportional navigation guidance. The neural network in this paper has identical inputs with proportional navigation guidance, which makes the comparison fair, distinguishing it from other research. The proposed guidance law will be compared to the proportional navigation guidance, which is widely known as quasi-optimal of missile guidance law. Our work aims to find effective missile training methods through reinforcement learning, and how better the new method is. Additionally, with the derived policy, we contemplated which is better, and in which circumstances it is better. A novel methodology for the training will be proposed first, and the performance comparison results will be continued therefrom.

This paper presents two amplitude comparison monopulse algorithms and their covariance prediction equation. The proposed algorithms are based on the iterated least-squares estimation method and include the conventional monopulse algorithm as a special case. The proposed covariance equation is simple but predicts RMS errors very accurately. This equation quantitatively states estimation accuracy in terms of major parameters of amplitude comparison monopulse radar, and is also applicable to the conventional monopulse algorithm. The proposed algorithms and covariance prediction equations are validated by the numerical simulations with 100,000 Monte Carlo runs.

An in vitro screening system for anti-cancer drugs cannot exactly reflect the efficacy of drugs in vivo, without mimicking the tumour microenvironment (TME), which comprises cancer cells interacting with blood vessels and fibroblasts. Additionally, the tumour size should be controlled to obtain reliable and quantitative drug responses. Herein, we report a bioprinting method for recapitulating the TME with a controllable spheroid size. The TME was constructed by printing a blood vessel layer consisting of fibroblasts and endothelial cells in gelatine, alginate, and fibrinogen, followed by seeding multicellular tumour spheroids (MCTSs) of glioblastoma cells (U87 MG) onto the blood vessel layer. Under MCTSs, sprouts of blood vessels were generated and surrounding MCTSs thereby increasing the spheroid size. The combined treatment involving the anti-cancer drug temozolomide (TMZ) and the angiogenic inhibitor sunitinib was more effective than TMZ alone for MCTSs surrounded by blood vessels, which indicates the feasibility of the TME for in vitro testing of drug efficacy. These results suggest that the bioprinted vascularized tumour is highly useful for understanding tumour biology, as well as for in vitro drug testing.

This paper presents the optimal control approach to solve both Lambert’s problem and Gibbs’ method, which are commonly used for preliminary orbit determination. Lambert’s problem is reinterpreted with Hamilton’s principle and is converted to an optimal control problem. Various extended Lambert’s problems are formulated by modifying the weighting and constraint settings within the optimal control framework. Furthermore, Gibbs’ method is also converted to an extended Lambert’s problem with two position vectors and one orbit energy with the help of the proposed orbital energy computation algorithm. The proposed extended Lambert’s problem and Gibbs’ method are numerically solved with the Lobatto pseudospectral method, and their accuracies are verified by numerical simulations.

Influenza A viruses are often present in environmental and clinical samples at concentrations below the limit of detection (LOD) of molecular diagnostics. Here we report an integrated microfluidic preconcentration and nucleic amplification system (μFPNAS) which enables both preconcentration of influenza A virus H1N1 (H1N1) and amplification of its viral RNA, thereby lowering LOD for H1N1. H1N1 virus particles were first magnetically preconcentrated using magnetic nanoparticles conjugated with an antibody specific for the virus. Their isolated RNA was amplified to cDNA through thermocycling in a trapezoidal chamber of the μFPNAS. A detection limit as low as 100 TCID50 (50% tissue culture infective dose) in saliva can be obtained within 2 hours. These results suggest that the LOD of molecular diagnostics for virus can be lowered by systematically combining immunomagnetic separation and reverse transcriptase-polymerase chain reaction (RT-PCR) in one microfluidic device.

Molecular diagnostics for sepsis is still a challenge due to the presence of compounds that interfere with gene amplification and bacteria at concentrations lower than the limit of detection (LOD). Here, we report on the development of a 3D printed modular microfluidic device (3DpmμFD) that preconcentrates bacteria of interest in whole blood and purifies their genomic DNA (gDNA). It is composed of a W-shaped microchannel and a conical microchamber. Bacteria of interest are magnetically captured from blood in the device with antibody conjugated magnetic nanoparticles (Ab-MNPs) at 5 mL/min in the W-shaped microchannel, while purified gDNA of the preconcentrated bacteria is obtained with magnetic silica beads (MSBs) at 2 mL/min in the conical microchamber. The conical microchamber was designed to be connected to the microchannel after the capturing process using a 3D-printed rotary valve to minimize the exposure of the MSBs to interfering compounds in blood. The pretreatment process of spiked blood (2.5 mL) can be effectively completed within about 50 min. With the 3DpmμFD, the LOD for the target microorganism Escherichia coli O157:H7 measured by both polymerase chain reaction (PCR) with electrophoresis and quantitative PCR was 10 colony forming unit (CFU) per mL of whole blood. The results suggest that our method lowers the LOD of molecular diagnostics for pathogens in blood by providing bacterial gDNA at high purity and concentration.

Using the Seoul National University Earth System Model Version 0 (SEM0) and Community Earth System Model version 1 (CESM1), we analyzed the impacts of El Niño-Southern oscillation (ENSO) and Madden–Julian oscillation (MJO) on the genesis of tropical cyclones (TG). SEM0 is known to simulate ENSO, MJO, and TG reasonably well, all of which are difficult to simulate with general circulation models (GCMs). Observational analysis revealed that both ENSO and MJO have substantial impacts on global TG and that the impact of ENSO (MJO) on regional TG varies in a complex manner depending on the phase of MJO (ENSO). Both GCMs underestimate the observed TG over the North Atlantic and have relatively poor performance for simulating the TG anomalies associated with ENSO compared to simulating those associated with MJO. Overall, SEM0 shows much better performance than CESM1 in terms of reproducing the observed impacts of MJO and combined impacts of ENSO and MJO on TG. Therefore, SEM0 can serve as a useful tool for studying the interactions among them to improve the forecasting of tropical cyclones.

This paper presents a three-dimensional path following guidance logic. The proposed guidance logic is composed of the guidance law and the motion strategy of virtual target along the desired path. The guidance law makes a vehicle purse the virtual target, and the motion strategy explicitly specifies the motion of virtual target by introducing the concept of the projection point and the tangentially receding distance. The proposed logic is simple and efficient and yet provides precise path following. Numerical simulations are performed to demonstrate the effectiveness of the proposed guidance logic.

For stem cell-based therapies, the fate and distribution of stem cells should be traced using non-invasive or histological methods and a nanomaterial-based labelling agent. However, evaluation of the biophysical effects and related biological functions of nanomaterials in stem cells remains challenging. Here, we aimed to investigate the biophysical effects of nanomaterials on stem cells, including those on membrane fluidity, using total internal reflection fluorescence microscopy, and traction force, using micropillars of human bone marrow-derived mesenchymal stem cells (hBM-MSCs) labelled with silica-coated magnetic nanoparticles incorporating rhodamine B isothiocyanate (MNPs@SiO2(RITC)). Furthermore, to evaluate the biological functions related to these biophysical changes, we assessed the cell viability, reactive oxygen species (ROS) generation, intracellular cytoskeleton, and the migratory activity of MNPs@SiO2(RITC)-treated hBM-MSCs. Compared to that in the control, cell viability decreased by 10% and intracellular ROS increased by 2-fold due to the induction of 20% higher peroxidized lipid in hBM-MSCs treated with 1.0 µg/µL MNPs@SiO2(RITC). Membrane fluidity was reduced by MNPs@SiO2(RITC)-induced lipid oxidation in a concentration-dependent manner. In addition, cell shrinkage with abnormal formation of focal adhesions and ~30% decreased total traction force were observed in cells treated with 1.0 µg/µL MNPs@SiO2(RITC) without specific interaction between MNPs@SiO2(RITC) and cytoskeletal proteins. Furthermore, the migratory activity of hBM-MSCs, which was highly related to membrane fluidity and cytoskeletal abnormality, decreased significantly after MNPs@SiO2(RITC) treatment. These observations indicated that the migratory activity of hBM-MSCs was impaired by MNPs@SiO2(RITC) treatment due to changes in stem-cell biophysical properties and related biological functions, highlighting the important mechanisms via which nanoparticles impair migration of hBM-MSCs. Our findings indicate that nanoparticles used for stem cell trafficking or clinical applications should be labelled using optimal nanoparticle concentrations to preserve hBM-MSC migratory activity and ensure successful outcomes following stem cell localisation.

Three-dimensional (3D) cell culture is considered more clinically relevant in mimicking the structural and physiological conditions of tumors in vivo compared to two-dimensional cell cultures. In recent years, high-throughput screening (HTS) in 3D cell arrays has been extensively used for drug discovery because of its usability and applicability. Herein, we developed a microfluidic spheroid culture device (μFSCD) with a concentration gradient generator (CGG) that enabled cells to form spheroids and grow in the presence of cancer drug gradients. The device is composed of concave microwells with several serpentine micro-channels which generate a concentration gradient. Once the colon cancer cells (HCT116) formed a single spheroid (approximately 120 μm in diameter) in each microwell, spheroids were perfused in the presence of the cancer drug gradient irinotecan for three days. The number of spheroids, roundness, and cell viability, were inversely proportional to the drug concentration. These results suggest that the μFSCD with a CGG has the potential to become an HTS platform for screening the efficacy of cancer drugs.

As the wind turbine size has been increasing and their mechanical components are built lighter, the reduction of the structural loads becomes a very important task of wind turbine control in addition to maximum wind power capture. In this paper, we present a separate set of collective and individual pitch control algorithms. Both pitch control algorithms use the LQR control technique with integral action (LQRI), and utilize Kalman filters to estimate system states and wind speed. Compared to previous works in this area, our pitch control algorithms can control rotor speed and blade bending moments at the same time to improve the trade-off between rotor speed regulation and load reduction, while both collective and individual pitch controls can be designed separately. Simulation results show that the proposed collective and individual pitch controllers achieve very good rotor speed regulation and significant reduction of blade bending moments.

As the wind turbine size has been increasing and their mechanical components are built lighter, the reduction of the structural loads becomes a very important task of wind turbine control in addition to maximum wind power capture. In this paper, we present a separate set of collective and individual pitch control algorithms. Both pitch control algorithms use the LQR control technique with integral action (LQRI), and utilize Kalman filters to estimate system states and wind speed. Compared to previous works in this area, our pitch control algorithms can control rotor speed and blade bending moments at the same time to improve the trade-off between rotor speed regulation and load reduction, while both collective and individual pitch controls can be designed separately. Simulation results show that the proposed collective and individual pitch controllers achieve very good rotor speed regulation and significant reduction of blade bending moments.

A distributed set of accelerometers based on the minimum number of 12 accelerometers allows for computation of the magnitude of angular rate without using the integration operation. However, it is not easy to extract the magnitude of angular rate in the presence of the accelerometer noises, and even worse, it is difficult to determine the direction of a rotation because the angular rate is present in its quadratic form within the inertial measurement system equations. In this paper, an extended Kalman filter scheme to correctly estimate both the direction and magnitude of the angular rate through fusion of the angular acceleration and quadratic form of the angular rate is proposed. We also provide observability analysis for the general distributed accelerometers-based inertial measurement unit, and show that the angular rate can be correctly estimated by general nonlinear state estimators such as an extended Kalman filter, except under certain extreme conditions.

This paper describes a robust and simple algorithm for an attitude and heading reference system (AHRS) based on low-cost MEMS inertial and magnetic sensors. The proposed approach relies on a gain-scheduled complementary filter, augmented by an acceleration-based switching architecture to yield robust performance, even when the vehicle is subject to strong accelerations. Experimental results are provided for a road captive test during which the vehicle dynamics are in high-acceleration mode and the performance of the proposed filter is evaluated against the output from a conventional linear complementary filter.