Impact of IL-1ß on lung pathology caused by Mycobacterium abscessus infection and its association with IL-17 production.

Mycobacterium abscessus (MAB), a non-tuberculous mycobacterium (NTM), causes chronic pulmonary inflammation in humans. The NLRP3 inflammasome is a multi-protein complex that triggers IL-1ß maturation and pyroptosis through the cleavage of caspase-1. In this study, we investigated the roles of NLRP3 and IL-1ß in the host's defense against MAB. The IL-1ß production by MAB was completely abolished in NLRP3, but not NLRC4, deficient macrophages. The NLRP3 inflammasome components, which are ASC and caspase-1 were also found to be essential for IL-1ß production in response to MAB. NLRP3 and IL-1ß deficiency did not affect the intracellular growth of MAB in macrophages, and the bacterial burden in lungs of NLRP3- and IL-1ß-deficient mice was also comparable to the burden observed in WT mice. In contrast, IL-1ß deficiency ameliorated lung pathology in MAB-infected mice. Notably, the lung homogenates of IL-1ß-deficient mice had reduced levels of IL-17, but not IFN-γ and IL-4 when compared with WT counterparts. Furthermore, in vitro co-culture analysis showed that IL-1ß signaling was essential for IL-17 production in response to MAB. Finally, we observed that the anti-IL-17 antibody administration moderately mitigated MAB-induced lung pathology. These findings indicated that IL-1ß production contribute to MAB-induced lung pathology via the elevation of IL-17 production.

Tumor Pre-Targeting System Using Streptavidin-Expressing Bacteria.

PURPOSE: A major obstacle to targeted cancer therapy is identifying suitable targets that are specifically and abundantly expressed by solid tumors. Certain bacterial strains selectively colonize solid tumors and can deliver genetically encoded cargo molecules to the tumor cells. Here, we engineered bacteria to express monomeric streptavidin (mSA) in tumors, and developed a novel tumor pre-targeting system by visualizing the presence of tumor-associated mSA using a biotinylated imaging probe. PROCEDURES: We constructed a plasmid expressing mSA fused to maltose-binding protein and optimized the ribosome binding site sequence to increase solubility and expression levels. E. coli MG1655 was transformed with the recombinant plasmid, expression of which is driven by the pBAD promotor. Expression of mSA was induced by L-arabinose 4 days after injection of bacteria into mice bearing CT26 mouse colon carcinoma cells. Selective accumulation of mSA in tumor tissues was visualized by optical imaging after administration of a biotinylated fluorescent dye. Counting of viable bacterial cells was also performed. RESULTS: Compared with a conventional system, the novel expression system resulted in significantly higher expression of mSA and sustained binding to biotin. Imaging signals in tumor tissues were significantly stronger in the mSA-expressing group than in non-expressing group (P = 0.0005). Furthermore, the fluorescent signal in tumor tissues became detectable again after multiple inductions with L-arabinose. The bacterial counts in tumor tissues showed no significant differences between conditions with and without L-arabinose (P = 0.45). Western blot analysis of tumor tissues confirmed expression and binding of mSA to biotin. CONCLUSIONS: We successfully engineered tumor-targeting bacteria carrying a recombinant plasmid expressing mSA, which was targeted to, and expressed in, tumor tissues. These data demonstrate the potential of this novel tumor pre-targeting system when combined with biotinylated imaging probes or therapeutic agents.

DeepPI: Alignment-Free Analysis of Flexible Length Proteins Based on Deep Learning and Image Generator.

With the rapid development of NGS technology, the number of protein sequences has increased exponentially. Computational methods have been introduced in protein functional studies because the analysis of large numbers of proteins through biological experiments is costly and time-consuming. In recent years, new approaches based on deep learning have been proposed to overcome the limitations of conventional methods. Although deep learning-based methods effectively utilize features of protein function, they are limited to sequences of fixed-length and consider information from adjacent amino acids. Therefore, new protein analysis tools that extract functional features from proteins of flexible length and train models are required. We introduce DeepPI, a deep learning-based tool for analyzing proteins in large-scale database. The proposed model that utilizes Global Average Pooling is applied to proteins of flexible length and leads to reduced information loss compared to existing algorithms that use fixed sizes. The image generator converts a one-dimensional sequence into a distinct two-dimensional structure, which can extract common parts of various shapes. Finally, filtering techniques automatically detect representative data from the entire database and ensure coverage of large protein databases. We demonstrate that DeepPI has been successfully applied to large databases such as the Pfam-A database. Comparative experiments on four types of image generators illustrated the impact of structure on feature extraction. The filtering performance was verified by varying the parameter values and proved to be applicable to large databases. Compared to existing methods, DeepPI outperforms in family classification accuracy for protein function inference.

AutoSCAN: automatic detection of DBSCAN parameters and efficient clustering of data in overlapping density regions.

The density-based clustering method is considered a robust approach in unsupervised clustering technique due to its ability to identify outliers, form clusters of irregular shapes and automatically determine the number of clusters. These unique properties helped its pioneering algorithm, the Density-based Spatial Clustering on Applications with Noise (DBSCAN), become applicable in datasets where various number of clusters of different shapes and sizes could be detected without much interference from the user. However, the original algorithm exhibits limitations, especially towards its sensitivity on its user input parameters minPts and ɛ. Additionally, the algorithm assigned inconsistent cluster labels to data objects found in overlapping density regions of separate clusters, hence lowering its accuracy. To alleviate these specific problems and increase the clustering accuracy, we propose two methods that use the statistical data from a given dataset's k-nearest neighbor density distribution in order to determine the optimal ɛ values. Our approach removes the burden on the users, and automatically detects the clusters of a given dataset. Furthermore, a method to identify the accurate border objects of separate clusters is proposed and implemented to solve the unpredictability of the original algorithm. Finally, in our experiments, we show that our efficient re-implementation of the original algorithm to automatically cluster datasets and improve the clustering quality of adjoining cluster members provides increase in clustering accuracy and faster running times when compared to earlier approaches.

Effects of L-Type Voltage-Gated Calcium Channel (LTCC) Inhibition on Hippocampal Neuronal Death after Pilocarpine-Induced Seizure.

Epilepsy, marked by abnormal and excessive brain neuronal activity, is linked to the activation of L-type voltage-gated calcium channels (LTCCs) in neuronal membranes. LTCCs facilitate the entry of calcium (Ca2+) and other metal ions, such as zinc (Zn2+) and magnesium (Mg2+), into the cytosol. This Ca2+ influx at the presynaptic terminal triggers the release of Zn2+ and glutamate to the postsynaptic terminal. Zn2+ is then transported to the postsynaptic neuron via LTCCs. The resulting Zn2+ accumulation in neurons significantly increases the expression of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase subunits, contributing to reactive oxygen species (ROS) generation and neuronal death. Amlodipine (AML), typically used for hypertension and coronary artery disease, works by inhibiting LTCCs. We explored whether AML could mitigate Zn2+ translocation and accumulation in neurons, potentially offering protection against seizure-induced hippocampal neuronal death. We tested this by establishing a rat epilepsy model with pilocarpine and administering AML (10 mg/kg, orally, daily for 7 days) post-epilepsy onset. We assessed cognitive function through behavioral tests and conducted histological analyses for Zn2+ accumulation, oxidative stress, and neuronal death. Our findings show that AML's LTCC inhibition decreased excessive Zn2+ accumulation, reactive oxygen species (ROS) production, and hippocampal neuronal death following seizures. These results suggest amlodipine's potential as a therapeutic agent in seizure management and mitigating seizures' detrimental effects.

Rational design of conductive metal-organic frameworks and aligned carbon nanofibers for enhancing the performance of flexible supercapacitors.

Carbonaceous materials are attractive active materials for the manufacture of flexible electrochemical double-layer capacitors (EDLCs) because of their high electrical conductivity, large surface area, and inherent resilience against deformation. However, compared to pseudocapacitors, which store electrochemical energy via faradaic redox reactions, EDLCs generally exhibit inferior energy density. One potential approach to addressing this issue is to incorporate highly porous and electrically conductive materials into carbonaceous material-based EDLCs. In this paper, we present a hybrid electrode consisting of a conductive metal-organic framework (c-MOF) with high electrical conductivity and unique porous structure combined with a mat of aligned carbon nanofibers (ACNFs). Its highly ordered structure facilitates electronic/ionic transport, increasing the areal capacitance by up to 3.9 times compared to randomly-oriented carbon nanofibers (RCNFs). An additional increase in areal capacitance (+64%) is achieved by introducing c-MOF (RCNFs: 25.4 mF cm-2; ACNFs: 98.7 mF cm-2; c-MOF/ACNF: 161.8 mF cm-2). Additionally, an ACNF mat exhibits excellent mechanical flexibility and electrochemical reliability, making it highly suitable for the assembly of freestanding flexible supercapacitors. By optimizing the electrochemical performance of c-MOF/ACNF and its suitability for utilization in flexible energy storage systems, this study presents a promising avenue for the practical implementation of c-MOF-based supercapacitors.

Elevated white blood cell count and long-term clinical outcomes of patients with vasospastic angina.

OBJECTIVES: Inflammation is known as one of key pathophysiologic mechanisms of coronary artery disease. We aimed to investigate the relationship between white blood cell (WBC) count and long-term clinical outcomes of patients with vasospastic angina (VA). METHODS: A total of 823 patients who were diagnosed as VA without significant coronary lesion by coronary angiography with ergonovine provocation test were enrolled for analysis. Patients were divided according to WBC count tertile at the time of diagnosis: group I, tertile 1 and 2 (n = 546, <7490/ml); group II, tertile 3 (n = 277, ≥7490/ml). Primary outcome was defined as major adverse cardiovascular events (MACE), a composite outcome of all-cause death, cardiac death, myocardial infarction (MI), readmission due to cardiac symptoms, and revascularization. RESULTS: Median follow-up duration was 4.3 years. No significant difference of primary outcome was observed between group I and group II (14.7% vs. 20.2%, hazard ratio (HR) 1.29, confidence interval (CI) 0.90-1.83, P  = 0.162), while incidence of cardiac death and MI was significantly higher in group II (1.5% vs. 4.3%, HR 2.86, CI 1.14-7.17), P  = 0.025). In multivariate Cox regression model, elevated WBC count at the time of diagnosis of VA was an independent predictor of MI (HR 3.43, CI 1.02-11.59, P  = 0.047). CONCLUSION: Elevated WBC count at the time of diagnosis was associated with a significantly increased risk of cardiac death and MI during long-term follow-up in VA patients.

Water Extract of Desalted Salicornia europaea Inhibits RANKL-Induced Osteoclast Differentiation and Prevents Bone Loss in Ovariectomized Mice.

Osteoporosis, which is often associated with increased osteoclast activity due to menopause or aging, was the main focus of this study. We investigated the inhibitory effects of water extract of desalted Salicornia europaea L. (WSE) on osteoclast differentiation and bone loss in ovariectomized mice. Our findings revealed that WSE effectively inhibited RANKL-induced osteoclast differentiation, as demonstrated by TRAP staining, and also suppressed bone resorption and F-actin ring formation in a dose-dependent manner. The expression levels of genes related to osteoclast differentiation, including NFATc1, ACP5, Ctsk, and DCSTAMP, were downregulated by WSE. Oral administration of WSE improved bone density and structural parameters in ovariectomized mice. Dicaffeoylquinic acids (DCQAs) and saponins were detected in WSE, with 3,4-DCQA, 3,5-DCQA, and 4,5-DCQA being isolated and identified. All tested DCQAs, including the aforementioned types, inhibited osteoclast differentiation, bone resorption, and the expression of osteoclast-related genes. Furthermore, WSE and DCQAs reduced ROS production mediated by RANKL. These results indicate the potential of WSE and its components, DCQAs, as preventive or therapeutic agents against osteoporosis and related conditions.

Hotspots-based patrol route optimization algorithm for smart policing.

Smart policing based on the analysis of big data ensures the development and sustainability of police policy. However, it is difficult to find instances in which the results of data analysis have been applied to actual policy in the field of crime prevention. The South Korean police force recognizes the need for smart policing and is engaged in various research and field support activities. Some examples that are especially relevant for crime investigation include analyzing the connections between cases and predicting the location of the next crime in a series of crimes and the location of suspects. However, it is difficult to find examples of police policy that use big data. Therefore, this study aims to suggest a model that uses big data to respond to emergency calls efficiently. First, we extract hotspots that are predicted to be locations of criminal activity based on an analysis of the association between community environment data and crime data. Second, we create a route having the shortest travel time to the crime location by developing a route optimization algorithm. Lastly, we assess the performance of the patrol routes in reflecting real-time traffic information. If the data application model suggested in this study could be adjusted and applied to the current police patrol system, the model could be used by each police department effectively.

Synthesis and evaluation of 18F-labeled procainamide as a PET imaging agent for malignant melanoma.

Malignant melanoma has an aggressive nature and a high metastatic propensity resulting in the highest mortality rate of any skin cancer. In this study, we synthesized 18F-labeled procainamide (PCA) for detection of melanoma using positron emission tomography (PET), and evaluated its biological characteristics. The non-decay-corrected radiochemical yield of 18F-PCA was 10-15% and its in vitro stability was over 98% for 2 h. At 1 h, cellular uptake of 18F-PCA was 3.8-fold higher in a group with the presence of l-tyrosine than in a non-l-tyrosine-treated group. Furthermore, 18F-PCA permitted visualization of B16F10 (mouse melanoma) xenografts on microPET after intravenous injection, and was retained in the tumor for 60 min, with a high tumor-to-liver uptake ratio. 18F-PCA showed specific melanoma uptake in primary lesions with a high melanin targeting ability in small animal models. 18F-PCA may have potential as a PET imaging agent for direct melanoma detection.

Electrochemically-mediated reactive separation of nitric oxide into nitrate using iron chelate.

Valorization of nitric oxide is a promising solution for addressing the environmental and resource issues related to the nitrogen cycle. However, low concentrations of nitric oxide combined with impurities in exhaust streams limit its potential, and it requires extensive energy to produce high-purity nitric oxide. Here, we propose a synergistic reactive separation system that combines iron-chelate selective absorption with an electrochemical reaction to convert nitric oxide to nitrate. Among the iron-based chelates tested, EDTA was found to be the most effective in capturing gas-phase nitric oxide. Direct electrochemical oxidation of Fe-EDTA-NO solution exhibited Faradaic efficiency and a partial current density toward nitrate of 70% and 30.1 mA cm-2 at 2.2 V vs RHE and pH 7, resulting in a 43-fold enhancement of nitrate partial current density and a 2-fold improvement in Faradaic efficiency compared to simple purging without selective absorbent. Nitrate was then selectively recovered from the Fe-EDTA system using simple polarity reversal following electrooxidation with a separation factor of 13 over background sulfate. This study offers a new approach to gas-phase NO remediation and valorization using an electrified means.

Oral Administration of Lactobacillus sakei CVL-001 Improves Recovery from Dextran Sulfate Sodium-Induced Colitis in Mice by Microbiota Modulation.

Inflammatory bowel disease (IBD) is an intestinal chronic inflammatory disease, and its incidence is steadily increasing. IBD is closely related to the intestinal microbiota, and probiotics are known to be a potential therapeutic agent for IBD. In our study, we evaluated the protective effect of Lactobacillus sakei CVL-001, isolated from Baechu kimchi, on dextran sulfated sodium (DSS)-induced colitis in mice. The oral administration of L. sakei CVL-001 according to the experimental schedule alleviated weight loss and disease activity in the mice with colitis. Furthermore, the length and histopathology of the colon improved. The expression of tumor necrosis factor (TNF)-α and interleukin (IL)-1ß genes decreased in the colons of mice that were administered L. sakei CVL-001, whereas that of IL-10 increased. The expressions of genes coding for E-cadherin, claudin3, occludin, and mucin were also restored. In co-housed conditions, L. sakei CVL-001 administration did not improve disease activity, colon length, and histopathology. Microbiota analysis revealed that L. sakei CVL-001 administration increased the abundance of microbiota and altered Firmicutes/Bacteroidetes ratio, and decreased Proteobacteria. In conclusion, L. sakei CVL-001 administration protects mice from DSS-induced colitis by regulating immune response and intestinal integrity via gut microbiota modulation.

Effects of air blower and pump failures on the performance of A2O processes for wastewater treatment.

The unexpected failure of equipment such as pumps and fans in wastewater treatment plants can reduce wastewater treatment efficiency, leading to direct leakage of untreated wastewater into the environment. It is hence important to predict the possible consequences of equipment failure to minimize the leakage of harmful substances. This study examines the impacts of equipment shutdown on the performance and recovery time of a laboratory-scale anaerobic/anoxic/aerobic system with regard to reactor conditions and water quality. Two days after the air blowers are stopped, the concentrations of the soluble chemical oxygen demand, NH4-N, and PO4-P in the effluent of the settling tank increase to 122 mg/L, 23.8 mg/L, and 46.6 mg/L, respectively. These concentrations return to their initial values after 12, 24, and 48 h of restarting the air blowers. The concentrations of PO4-P and NO3-N in the effluent increase to 58 mg/L and 20 mg/L, respectively, about 24 h after stopping the return activated sludge and mixed liquor recirculation pumps, owing to the release of phosphates in the settling tank and inhibition of denitrification.

Effects of Pyruvate Kinase M2 (PKM2) Gene Deletion on Astrocyte-Specific Glycolysis and Global Cerebral Ischemia-Induced Neuronal Death.

Ischemic stroke is caused by insufficient blood flow to the brain. Astrocytes have a role in bidirectionally converting pyruvate, generated via glycolysis, into lactate and then supplying it to neurons through astrocyte-neuron lactate shuttle (ANLS). Pyruvate kinase M2 (PKM2) is an enzyme that dephosphorylates phosphoenolpyruvate to pyruvate during glycolysis in astrocytes. We hypothesized that a reduction in lactate supply in astrocyte PKM2 gene deletion exacerbates neuronal death. Mice harboring a PKM2 gene deletion were established by administering tamoxifen to Aldh1l1-CreERT2; PKM2f/f mice. Upon development of global cerebral ischemia, mice were immediately injected with sodium l-lactate (250 mg/kg, i.p.). To verify our hypothesis, we compared oxidative damage, microtubule disruption, ANLS disruption, and neuronal death between the gene deletion and control subjects. We observed that PKM2 gene deletion increases the degree of neuronal damage and impairment of lactate metabolism in the hippocampal region after GCI. The lactate administration groups showed significantly reduced neuronal death and increases in neuron survival and cognitive function. We found that lactate supply via the ANLS in astrocytes plays a crucial role in maintaining energy metabolism in neurons. Lactate administration may have potential as a therapeutic tool to prevent neuronal damage following ischemic stroke.

GPS Spoofing Detection Method for Small UAVs Using 1D Convolution Neural Network.

The navigation of small unmanned aerial vehicles (UAVs), such as quadcopters, significantly relies on the global positioning system (GPS); however, UAVs are vulnerable to GPS spoofing attacks. GPS spoofing is an attempt to manipulate a GPS receiver by broadcasting manipulated signals. A commercial GPS simulator can cause a GPS-guided drone to deviate from its intended course by transmitting counterfeit GPS signals. Therefore, an anti-spoofing technique is essential to ensure the operational safety of UAVs. Various methods have been introduced to detect GPS spoofing; however, most methods require additional hardware. This may not be appropriate for small UAVs with limited capacity. This study proposes a deep learning-based anti-spoofing method equipped with 1D convolutional neural network. The proposed method is lightweight and power-efficient, enabling real-time detection on mobile platforms. Furthermore, the performance of our approach can be enhanced by increasing training data and adjusting the network architecture. We evaluated our algorithm on the embedded board of a drone in terms of power consumption and inference time. Compared to the support vector machine, the proposed method showed better performance in terms of precision, recall, and F-1 score. Flight test demonstrated our algorithm could successfully detect GPS spoofing attacks.

cPlot: Contig-Plotting Visualization for the Analysis of Short-Read Nucleotide Sequence Alignments.

Advances in the next-generation sequencing technology have led to a dramatic decrease in read-generation cost and an increase in read output. Reconstruction of short DNA sequence reads generated by next-generation sequencing requires a read alignment method that reconstructs a reference genome. In addition, it is essential to analyze the results of read alignments for a biologically meaningful inference. However, read alignment from vast amounts of genomic data from various organisms is challenging in that it involves repeated automatic and manual analysis steps. We, here, devised cPlot software for read alignment of nucleotide sequences, with automated read alignment and position analysis, which allows visual assessment of the analysis results by the user. cPlot compares sequence similarity of reads by performing multiple read alignments, with FASTA format files as the input. This application provides a web-based interface for the user for facile implementation, without the need for a dedicated computing environment. cPlot identifies the location and order of the sequencing reads by comparing the sequence to a genetically close reference sequence in a way that is effective for visualizing the assembly of short reads generated by NGS and rapid gene map construction.

D-galactose Intake Alleviates Atopic Dermatitis in Mice by Modulating Intestinal Microbiota.

Atopic dermatitis (AD) is one of the most prevalent, chronic and persistent inflammatory skin diseases closely associated with intestinal microbiota. To evaluate the effect of D-galactose intake on AD, we orally administered D-galactose to BALB/c mice whose ears and skin were treated with 2,4-dinitrochlorobenzene (DNCB). D-galactose alleviated DNCB-induced AD-like phenotypes such as redness, scaling/dryness and excoriation. Ear thickness was also decreased by D-galactose administration. Histopathological analysis revealed decreased epidermal thickening, infiltration of immune cells, especially mast cells, in the dermis. Total levels of serum IgE representing the immunological response of AD were decreased by D-galactose administration. Microbiota analysis showed that D-galactose administration restored gut microbiota profiles, which were altered in AD mice, characterized by increased abundance of Bacteroidetes and decreased abundance of Firmicutes. The increased abundance of Bacteroides and the decreased abundance of Prevotella and Ruminococcus were reversed by D-galactose treatment, following improvement of AD. Our results suggest the possible use of D-galactose as a prebiotic to alleviate AD by altering gut microbiota.

Accelerating a spatially varying aberration correction of holographic displays with low-rank approximation.

Correction of spatially varying aberrations in holographic displays often requires intractable computational loads. In this Letter, we introduce a low-rank approximation method that decomposes sub-holograms into a small number of modes, thereby reformulating the computer-generated hologram calculation into a summation of a few convolutions. The low-rank approximation is carried out with two different algorithms: the Karhunen-Loeve transform as the optimum solution with respect to the mean-squared error criterion and a novel, to the best of our knowledge, optimization method to provide uniform image quality over the entire field of view. The proposed method is two orders of magnitude faster than the conventional point-wise integration method in our experimental setup, with comparable image quality.

KSNM60: The History of Radiopharmaceutical Sciences in Korea.

A number of researchers in Korea have tried to set-up the production of radionuclides and develop new radiopharmaceuticals for several decades. Thanks to their 60-year endeavor to advance the field of radiopharmaceutical sciences, now we have a lot of research units and facilities in Korea. Still, there are huge number of issues to be solved in radiopharmaceutical sciences; however, our efforts will be continued to develop new radiopharmaceuticals and to apply the new radiopharmaceuticals into nuclear medicine field.

Expanding energy envelope in holographic display via mutually coherent multi-directional illumination.

Holographic display is considered as the most promising three-dimensional (3D) display due to its unique feature of reconstructing arbitrary wavefronts. However, the limited étendue, which hinders the immersive experience of observers, remains a major unresolved issue in holographic display technique. In this paper, we propose a novel approach to tweak the constraints of étendue by expanding the energy envelope in holographic display via mutually coherent multi-illumination. The proposed concept contains both a light source design for generating a mutually coherent multi-directional wave and a computer-generated hologram optimization framework for providing high-resolution 3D holograms. To verify the proposed approach, a benchtop prototype of a holographic near-eye display providing an intrinsic large exit-pupil is implemented. The experimental results clearly show that the exit-pupil is effectively expanded by four times and an appropriate viewpoint image is reconstructed according to the view position.