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As the turnaround time of diagnosis becomes important, there is an increasing demand for rapid, point-of-care testing (POCT) based on polymerase chain reaction (PCR), the most reliable diagnostic tool. Although optical components in real-time PCR (qPCR) have quickly become compact and economical, conventional PCR instruments still require bulky thermal systems, making it difficult to meet emerging needs. Photonic PCR, which utilizes photothermal nanomaterials as heating elements, is a promising platform for POCT as it reduces power consumption and process time. Here, we develop a photonic qPCR platform using hydrogel microparticles. Microparticles consisting of hydrogel matrixes containing photothermal nanomaterials and primers are dubbed photothermal primer-immobilized networks (pPINs). Reduced graphene oxide is selected as the most suitable photothermal nanomaterial to generate heat in pPIN due to its superior light-to-heat conversion efficiency. The photothermal reaction volume of 100 nL (predefined by the pPIN dimensions) provides fast heating and cooling rates of 22.0 ± 3.0 and 23.5 ± 2.6 °C s

In recent decades "saliva" has emerged as an important non-invasive biofluid for diagnostic purposes in both human and animal health sectors. However, with the rapid evolution of molecular detection technologies, the limitation has been the lack of an efficient method for the facile amplification of target RNA from such a complex matrix. Herein, we demonstrate the novel application of hydrogel microparticles of primer-immobilized networks (PIN) for direct quantitative reverse transcription PCR (dirRT-qPCR) of viral RNA from saliva samples without prior RNA purification. Each of these highly porous PIN particles operates as an independent reactor. They filter in micro-volumes of the analyte solution. Viral RNA is captured and converted to complementary DNA (cDNA) through the RT step using covalently incorporated RT primers. The PIN with cDNA of the viral target will be ready for subsequent highly specific qPCR. Preceded by heat-treatment for viral lysis, we were able to conduct PIN dirRT-qPCR with 95% efficiency of the matrix (M) gene for influenza A virus (IAV) and 5' untranslated region (5' UTR) for chicken coronavirus spiked into saliva samples. The addition of reverse transcriptase enzyme (RTase) and 10% dilution of the matrix improved the assay sensitivity considerably. PIN particles' compatibility with microfluidic PCR chip technology has significantly reduced total sample processing time to 50 min, instead of an average of 120 min that are normally used by other assays. We anticipate this technology will be useful for other viral RNA targets by changing the incorporated RT primer sequences and can be adapted for onsite diagnostics.The online version contains supplementary material available at 10.1007/s13206-022-00065-0.

Temperature forecasting is an area of ongoing research because of its importance in all life aspects. However, because a variety of climate factors controls the temperature, it is a never-ending challenge. The numerical weather prediction (NWP) model has been frequently used to forecast air temperature. However, because of its deprived grid resolution and lack of parameterizations, it has systematic distortions. In this study, a gray wolf optimizer (GWO) and a support vector machine (SVM) are used to ensure accuracy and stability of the next day forecasting for minimum and maximum air temperatures in Seoul, South Korea, depending on local data assimilation and prediction system (LDAPS; a model of local NWP over Korea). A total of 14 LDAPS models forecast data, the daily maximum and minimum air temperatures of in situ observations, and five auxiliary data were used as input variables. The LDAPS model, the multimodal array (MME), the particle swarm optimizer with support vector machine (SVM-PSO), and the conventional SVM were selected as comparison models in this study to illustrate the advantages of the proposed model. When compared to the particle swarm optimizer and traditional SVM, the Gray Wolf Optimizer produced more accurate results, with the average RMSE value of SVM for T max and T min Forecast prediction reduced by roughly 51 percent when combined with GWO and 31 percent when combined with PSO. In addition, the hybrid model (SVM-GWO) improved the performance of the LDAPS model by lowering the RMSE values for T max Forecast and T min Forecast forecasting from 2.09 to 0.95 and 1.43 to 0.82, respectively. The results show that the proposed hybrid (GWO-SVM) models outperform benchmark models in terms of prediction accuracy and stability and that the suggested model has a lot of application potentials.

As viruses have been threatening global public health, fast diagnosis has been critical to effective disease management and control. Reverse-transcription quantitative polymerase chain reaction (RT-qPCR) is now widely used as the gold standard for detecting viruses. Although a multiplex assay is essential for identifying virus types and subtypes, the poor multiplicity of RT-qPCR makes it laborious and time-consuming. In this paper, we describe the development of a multiplex RT-qPCR platform with hydrogel microparticles acting as independent reactors in a single reaction. To build target-specific particles, target-specific primers and probes are integrated into the particles in the form of noncovalent composites with boron nitride nanotubes (BNNTs) and carbon nanotubes (CNTs). The thermal release characteristics of DNA, primer, and probe from the composites of primer-BNNT and probe-CNT allow primer and probe to be stored in particles during particle production and to be delivered into the reaction. In addition, BNNT did not absorb but preserved the fluorescent signal, while CNT protected the fluorophore of the probe from the free radicals present during particle production. Bicompartmental primer-incorporated network (bcPIN) particles were designed to harness the distinctive properties of two nanomaterials. The bcPIN particles showed a high RT-qPCR efficiency of over 90% and effective suppression of non-specific reactions. 16-plex RT-qPCR has been achieved simply by recruiting differently coded bcPIN particles for each target. As a proof of concept, multiplex one-step RT-qPCR was successfully demonstrated with a simple reaction protocol.

The typical metamaterial absorber includes a single absorption band, based on a single resonator. We note that four or more absorption peaks are formed by only a single meta-atom, that is, a widely used cut-wire (CW) structure. Through a differential equivalent-circuit approach, the absorption mechanism of odd-order magnetic resonance and electric resonance in CW was elucidated by one unique circuit. With electrical interaction between adjacent meta-atoms taken into consideration, the absorption properties of a CW structure are proved as a function of the geometric parameters, and are verified through numerical and experimental results. By obtaining the experimental results of disk-structured meta-atoms showing higher than third-order magnetic resonance absorption bands, the existence and absorption properties of higher-order magnetic resonances for meta-atoms in a non-CW metamaterial are shown to be coherent with those of a CW structure. This presence of multiple absorption peaks opens the possibility for multiband metamaterial absorbers not only in the GHz but also in the visible range.

Considerable evidence suggests breast cancer metastasis arises from cells undergoing epithelial-to-mesenchymal-transition (EMT) and cancer stem-like cells (CSCs). Using a microfluidic device that enriches migratory breast cancer cells with enhanced capacity for tumor formation and metastasis, we identified genes differentially expressed in migratory cells by high-throughput single-cell RNA-sequencing. Migratory cells exhibited overall signatures of EMT and CSCs with variable expression of marker genes, and they retained expression profiles of EMT over time. With single-cell resolution, we discovered intermediate EMT states and distinct epithelial and mesenchymal sub-populations of migratory cells, indicating breast cancer cells can migrate rapidly while retaining an epithelial state. Migratory cells showed differential profiles for regulators of oxidative stress, mitochondrial morphology, and the proteasome, revealing potential vulnerabilities and unexpected consequences of drugs. We also identified novel genes correlated with cell migration and outcomes in breast cancer as potential prognostic biomarkers and therapeutic targets to block migratory cells in metastasis.

The novel electrode design, which is a diffusion-dependent electrode structure composed only of active materials, can theoretically realize high energy density. The diffusion-dependent electrode structure can transport lithium ions in the entire electrode through lithium-ion diffusion between the active material particles unless the connectivity between the active material particles is cut off. However, since the electrode structure transfers ions through diffusion, if the thickness of the electrode is too thick, there is a possibility that the performance may have deteriorated. For this purpose, by using not only graphite but also silicon particles, it is possible to have a thin electrode structure compared to the same capacity. In this study, graphite-silicon diffusion-dependent electrode according to the silicon particle size is formed into a digital three-dimensional electrode structure and based on this, electrochemical simulation and analysis of an all-solid-state battery having a diffusion-dependent electrode are performed. The importance and cause of the size of silicon particles in the graphite-silicon diffusion-dependent electrode will be investigated. Reference Diffusion-dependent graphite electrode for all-solid-state batteries with extremely high energy density, ACS Energy Letters , 5(9) (2020) 2995-3004 Revisiting TiS2 as a diffusion-dependent cathode with promising energy density for all-solid-state lithium secondary batteries, Energy Storage Materials , 41 (2021) 289-296

An internal short circuit (ISC) is known to be the main cause of fatal accidents in Li-ion batteries (LIBs). If two electrodes come into contact with each other because of any event, the inner temperature of LIBs increases rapidly within the very short time. If the temperature can increase over the threshold temperature, fire or explosion accidents can occur in the LIB, which is called thermal runaway (TR). Because the fire in the LIBs is not easily extinguished and can cause significant damage of life and property, we should understand the fundamental electrochemical and thermal behavior of ISC-TR in order to prevent or delay these severe accidents. For this purpose, there have been tremendous attempts to analyze different ISC cases with a variety of LIB cells experimentally through penetrating nails, pucks, shape memory alloys, etc. However, experimental methods have limitations in measuring internal temperatures and estimating current density and lithium-ion concentration within LIB cells. Also it is still challenging to control the types and locations of ISCs practically. To compensate these experimental limitations, many simulation studies have also been conducted. However, many simulation research have been considering a two-dimensional-based microscale domain, which may have relatively inaccurate simulation results or cannot consider three-dimensional placement, or a three-dimensional-based large domain, which calculates ISC only in mm units or more. In this work, we developed an advanced thermo-electrical model to simulate the responses of LIB cells depending on the sizes, numbers, and locations of lithium dendrites or impurities. This model can calculate the current density, which causes joule heat flux, and simulate heat transfer. Thus, this model can provide us with information on what kinds or how many of lithium dendrites will lead to thermal runaway. Also, it is possible to analyze the thermal behavior of LIBs according to the various physical and temperature conditions of the lithium dendrites.

Physical memory acquisition is a prerequisite when performing memory forensics, referring to a set of techniques for acquiring and analyzing traces associated with user activity information, malware analysis, cyber incident response, and similar areas when the traces remain in the physical RAM. However, certain types of malware have applied anti-memory forensics techniques to evade memory analysis strategies or to make the acquisition process impossible. To disturb the acquisition process of physical memory, an attacker hooks the kernel API, which returns a map of the physical memory spaces, and modifies the return value of the API, specifically that typically used by memory acquisition tools. Moreover, an attacker modifies the kernel object referenced by the kernel API. This causes the system to crash during the memory acquisition process or causes the memory acquisition tools to incorrectly proceed with the acquisition. Even with a modification of one byte, called a one-byte modification attack, some tools fail to acquire memory. Therefore, specialized countermeasure techniques are needed for these anti-memory forensics techniques. In this paper, we propose a memory layout acquisition method which is robust to kernel API hooking and the one-byte modification attack on NumberOfRuns, the kernel object used to construct the memory layout in Windows. The proposed acquisition method directly accesses the memory, extracts the byte array, and parses it in the form of a memory layout. When we access the memory, we extract the _PHYSICAL_MEMORY_DESCRIPTOR structure, which is the basis of the memory layout without using the existing memory layout acquisition API. Furthermore, we propose a verification method that selects a reliable memory layout. We realize the verification method by comparing NumberOfRuns and the memory layout acquired via the kernel API, the registry, and the proposed method. The proposed verification method guarantees the reliability of the memory layout and helps secure memory image acquisition through a comparative verification with existing memory layout acquisition methods. We also conduct experiments to prove that the proposed method is resistant to anti-memory forensics techniques, confirming that there are no significant differences in time compared to the existing tools.

Since the 2000s, two lineages of the influenza B virus (influenza B/Victoria and influenza B/Yamagata) have been co-circulating. Information on the age distribution of patients infected by each influenza B virus lineage may be helpful for establishing differentiated influenza prevention and control strategies for each age group. Age distributions were compared between patients infected by influenza A and B viruses and between those infected by the influenza B virus when B/Victoria and B/Yamagata lineages circulated dominantly. Between the 2014–2015 and 2018–2019 influenza seasons, 2,718 and 1,397 patients were diagnosed with influenza A and B virus infections, respectively. The median age of patients infected by the influenza B virus was lower than that of patients infected by the influenza A virus (8 vs 12 years, p p = 0.732); however, in the Victoria season, the median age of patients infected by the influenza B virus was lower than that of patients infected by the influenza A virus (6 vs 10 years, p p The age distribution of patients infected by the influenza virus was different between the Yamagata and Victoria seasons. Different influenza prevention and control strategies should be considered on the basis of the predominantly circulating virus and the affected age group.

Given the growing interest in molecular diagnosis, highly extensive and selective detection of genetic targets from a very limited amount of samples is in high demand. We demonstrated the highly sensitive and multiplexed one-step RT-qPCR platform for RNA analysis using microparticles as individual reactors. Those particles are equipped with a controlled release system of thermo-responsive materials, and are able to capture RNA targets inside. The particle-based assay can successfully quantify multiple target RNAs from only 200 pg of total RNA. The assay can also quantify target RNAs from a single cell with the aid of a pre-concentration process. We carried out 8-plex one-step RT-qPCR using tens of microparticles, which allowed extensive mRNA profiling. The circadian cycles were shown by the multiplex one-step RT-qPCR in human cell and human hair follicles. Reliable 24-plex one-step RT-qPCR was developed using a single operation in a PCR chip without any loss of performance (i.e., selectivity and sensitivity), even from a single hair. Many other disease-related transcripts can be monitored using this versatile platform. It can also be used non–invasively for samples obtained in clinics.