Mott neurons with dual thermal dynamics for spatiotemporal computing.

Heat dissipation is a natural consequence of operating any electronic system. In nearly all computing systems, such heat is usually minimized by design and cooling. Here, we show that the temporal dynamics of internally produced heat in electronic devices can be engineered to both encode information within a single device and process information across multiple devices. In our demonstration, electronic NbOx Mott neurons, integrated on a flexible organic substrate, exhibit 18 biomimetic neuronal behaviours and frequency-based nociception within a single component by exploiting both the thermal dynamics of the Mott transition and the dynamical thermal interactions with the organic substrate. Further, multiple interconnected Mott neurons spatiotemporally communicate purely via heat, which we use for graph optimization by consuming over 106 times less energy when compared with the best digital processors. Thus, exploiting natural thermal processes in computing can lead to functionally dense, energy-efficient and radically novel mixed-physics computing primitives.

The crosstalk between PTEN-induced kinase 1-mediated mitophagy and the inflammasome in the pathogenesis of alopecia areata.

Alopecia areata (AA) is a T-cell-mediated autoimmune disease that causes chronic, relapsing hair loss; however, its precise pathogenesis remains to be elucidated. Recent studies have provided compelling evidence of crosstalk between inflammasomes and mitophagy-a process that contributes to the removal of damaged mitochondria. Our previous studies showed that the NLR family pyrin domain containing 3 (NLRP3) inflammasome is important for eliciting and progressing inflammation in AA. In this study, we detected mitochondrial DNA damage in AA-affected scalp tissues and IFNγ and poly(I:C) treated outer root sheath (ORS) cells. In addition, IFNγ and poly(I:C) treatment increased mitochondrial reactive oxygen species (ROS) levels in ORS cells. Moreover, we showed that mitophagy induction alleviates IFNγ and poly(I:C)-induced NLRP3 inflammasome activation in ORS cells. Lastly, PTEN-induced kinase 1 (PINK1) knockdown increased NLRP3 inflammasome activation, indicating that PINK1-mediated mitophagy plays a critical role in NLRP3 inflammasome activation in ORS cells. This study supports previous studies showing that oxidative stress disrupts immune privilege status and promotes autoimmunity in AA. The results emphasize the significance of crosstalk between mitophagy and inflammasomes in the pathogenesis of AA. Finally, mitophagy factors regulating mitochondrial dysfunction and inhibiting inflammasome activation could be novel therapeutic targets for AA.

Risk Factors and Temporal Patterns of Poststroke Epilepsy across Stroke Subtypes: Insights from a Nationwide Cohort Study in Korea.

INTRODUCTION: We aimed to investigate the risk factors associated with poststroke epilepsy (PSE) among patients with different subtypes of stroke, focusing on age-related risk and time-varying effects of stroke subtypes on PSE development. METHODS: A retrospective, nationwide, population-based cohort study was conducted using Korean National Health Insurance Service-National Sample Cohort data. Patients hospitalized with newly diagnosed stroke from 2005 to 2015 were included and followed up for up to 10 years. The primary outcome was the development of PSE, defined as having a diagnostic code and a prescription for anti-seizure medication. Multivariable Cox proportional hazard models were used to estimate PSE hazard ratios (HRs), and time-varying effects were also assessed. RESULTS: A total of 8,305 patients with ischemic stroke, 1,563 with intracerebral hemorrhage (ICH), and 931 with subarachnoid hemorrhage (SAH) were included. During 10 years of follow-up, 4.6% of patients developed PSE. Among patients with ischemic stroke, significant risk factors for PSE were younger age (HR = 1.47), living in rural areas (HR = 1.35), admission through the emergency room (HR = 1.33), and longer duration of hospital stay (HR = 1.45). Time-varying analysis revealed elevated HRs for ICH and SAH, particularly in the first 2 years following the stroke. The age-specific HRs also showed an increased risk for those under the age of 65, with a noticeable decrease in risk beyond that age. CONCLUSION: The risk of developing PSE varies according to stroke subtype, age, and other demographic factors. These findings underscore the importance of tailored poststroke monitoring and management strategies to mitigate the risk of PSE.

Synthetic temporal bone CT generation from UTE-MRI using a cycleGAN-based deep learning model: advancing beyond CT-MR imaging fusion.

OBJECTIVES: The aim of this study is to develop a deep-learning model to create synthetic temporal bone computed tomography (CT) images from ultrashort echo-time magnetic resonance imaging (MRI) scans, thereby addressing the intrinsic limitations of MRI in localizing anatomic landmarks in temporal bone CT. MATERIALS AND METHODS: This retrospective study included patients who underwent temporal MRI and temporal bone CT within one month between April 2020 and March 2023. These patients were randomly divided into training and validation datasets. A CycleGAN model for generating synthetic temporal bone CT images was developed using temporal bone CT and pointwise encoding-time reduction with radial acquisition (PETRA). To assess the model's performance, the pixel count in mastoid air cells was measured. Two neuroradiologists evaluated the successful generation rates of 11 anatomical landmarks. RESULTS: A total of 102 patients were included in this study (training dataset, n = 54, mean age 58 ± 14, 34 females (63%); validation dataset, n = 48, mean age 61 ± 13, 29 females (60%)). In the pixel count of mastoid air cells, no difference was observed between synthetic and real images (679 ± 342 vs 738 ± 342, p = 0.13). For the six major anatomical sites, the positive generation rates were 97-100%, whereas those of the five major anatomical structures ranged from 24% to 83%. CONCLUSION: We developed a model to generate synthetic temporal bone CT images using PETRA MRI. This model can provide information regarding the major anatomic sites of the temporal bone using MRI. CLINICAL RELEVANCE STATEMENT: The proposed algorithm addresses the primary limitations of MRI in localizing anatomic sites within the temporal bone. KEY POINTS: CT is preferred for imaging the temporal bone, but has limitations in differentiating pathology there. The model achieved a high success rate in generating synthetic images of six anatomic sites. This can overcome the limitations of MRI in visualizing key anatomic sites in the temporal skull.

Analysis of Rice Blast Fungus Genetic Diversity and Identification of a Novel Blast Resistance OsDRq12 Gene.

The rice blast fungus Magnaporthe oryzae poses a significant challenge to maintaining rice production. Developing rice varieties with resistance to this disease is crucial for its effective control. To understand the genetic variability of blast isolates collected between 2015 and 2017, the 27 monogenic rice lines that carry specific resistance genes were used to evaluate blast disease reactions. Based on criteria such as viability, virulence, and reactions to resistance genes, 20 blast isolates were selected as representative strains. To identify novel resistance genes, a quantitative trait locus analysis was carried out utilizing a mixture of the 20 representative rice blast isolates and a rice population derived from crossing the blast-resistant cultivar 'Cheongcheong' with the blast-susceptible cultivar 'Nagdong'. This analysis revealed a significant locus, RM1227-RM1261 on chromosome 12, that is associated with rice blast resistance. Within this locus, 12 disease resistance-associated protein genes were identified. Among them, OsDRq12, a member of the nucleotide-binding, leucine-rich repeat disease resistance family, was chosen as the target gene for additional computational investigation. The findings of this study have significant implications for enhancing rice production and ensuring food security by controlling rice blast and developing resistant rice cultivars.

Validity and Reliability of the Korean Version of Reduced Morningness-Eveningness Questionnaire: Results From a General Population-Based Sample.

BACKGROUND: Chronotype refers to individual variations in diurnal preferences that manifest as everyday behaviors, including sleep patterns. Traditionally, the Horne & Östberg Morningness-Eveningness Questionnaire (MEQ), which comprises of 19 items, has been the standard for determining chronotype. However, its length makes it cumbersome for widespread application. To address this issue, the reduced MEQ (rMEQ), a concise version containing only five items from the MEQ, was developed for a more practical approach to chronotype assessment. This study aimed to evaluate the validity and reliability of Korean version of rMEQ in a sample from the general Korean population. METHODS: The Korean version of the rMEQ comprises of items 1, 7, 10, 18, and 19 of the original MEQ. The validity of the rMEQ was assessed by correlating its scores with those of the MEQ and Munich Chronotype Questionnaire (MCTQ). Its reliability was determined by calculating internal consistency. RESULTS: A total of 3,030 individuals participated in the study, yielding an average rMEQ score of 14.0 ± 3.4. There was a substantial positive correlation between the rMEQ and MEQ scores (r = 0.859, P < 0.001). Furthermore, the rMEQ scores were significantly negatively correlated with the midpoint of sleep on free days corrected for sleep debt as measured by the MCTQ (r = -0.388, P < 0.001), indicating a robust association with chronotype. The internal consistency of rMEQ, measured using Cronbach's alpha, was 0.609. CONCLUSION: This study finds the Korean version of the rMEQ to be a valid and reliable instrument for assessing chronotype in the general population.

PVS-GEN: Systematic Approach for Universal Synthetic Data Generation Involving Parameterization, Verification, and Segmentation.

Synthetic data generation addresses the challenges of obtaining extensive empirical datasets, offering benefits such as cost-effectiveness, time efficiency, and robust model development. Nonetheless, synthetic data-generation methodologies still encounter significant difficulties, including a lack of standardized metrics for modeling different data types and comparing generated results. This study introduces PVS-GEN, an automated, general-purpose process for synthetic data generation and verification. The PVS-GEN method parameterizes time-series data with minimal human intervention and verifies model construction using a specific metric derived from extracted parameters. For complex data, the process iteratively segments the empirical dataset until an extracted parameter can reproduce synthetic data that reflects the empirical characteristics, irrespective of the sensor data type. Moreover, we introduce the PoR metric to quantify the quality of the generated data by evaluating its time-series characteristics. Consequently, the proposed method can automatically generate diverse time-series data that covers a wide range of sensor types. We compared PVS-GEN with existing synthetic data-generation methodologies, and PVS-GEN demonstrated a superior performance. It generated data with a similarity of up to 37.1% across multiple data types and by 19.6% on average using the proposed metric, irrespective of the data type.

High Amplitude Spike Generator in Au Nanodot-Incorporated NbOx Mott Memristor.

NbOx-based Mott memristors exhibit fast threshold switching behaviors, making them suitable for spike generators in neuromorphic computing and stochastic clock generators in security devices. In these applications, a high output spike amplitude is necessary for threshold level control and accurate signal detection. Here, we propose a materialwise solution to obtain the high amplitude spikes by inserting Au nanodots into the NbOx device. The Au nanodots enable increasing the threshold voltage by modulating the oxygen contents at the electrode-oxide interface, providing a higher ON current compared to nanodot-free NbOx devices. Also, the reduction of the local switching region volume decreases the thermal capacitance of the system, allowing the maximum spike amplitude generation. Consequently, the Au nanodot incorporation increases the spike amplitude of the NbOx device by 6 times, without any additional external circuit elements. The results are systematically supported by both a numerical model and a finite-element-method-based multiphysics model.

Inter-Species Pharmacokinetic Modeling and Scaling for Drug Repurposing of Pyronaridine and Artesunate.

Even though several new targets (mostly viral infection) for drug repurposing of pyronaridine and artesunate have recently emerged in vitro and in vivo, inter-species pharmacokinetic (PK) data that can extend nonclinical efficacy to humans has not been reported over 30 years of usage. Since extrapolation of animal PK data to those of humans is essential to predict clinical outcomes for drug repurposing, this study aimed to investigate inter-species PK differences in three animal species (hamster, rat, and dog) and to support clinical translation of a fixed-dose combination of pyronaridine and artesunate. PK parameters (e.g., steady-state volume of distribution (Vss), clearance (CL), area under the concentration-time curve (AUC), mean residence time (MRT), etc.) of pyronaridine, artesunate, and dihydroartemisinin (an active metabolite of artesunate) were determined by non-compartmental analysis. In addition, one- or two-compartment PK modeling was performed to support inter-species scaling. The PK models appropriately described the blood concentrations of pyronaridine, artesunate, and dihydroartemisinin in all animal species, and the estimated PK parameters in three species were integrated for inter-species allometric scaling to predict human PKs. The simple allometric equation (Y = a × Wb) well explained the relationship between PK parameters and the actual body weight of animal species. The results from the study could be used as a basis for drug repurposing and support determining the effective dosage regimen for new indications based on in vitro/in vivo efficacy data and predicted human PKs in initial clinical trials.

Halotolerant endophytic bacteria alleviate salinity stress in rice (oryza sativa L.) by modulating ion content, endogenous hormones, the antioxidant system and gene expression.

Excessive salinity reduces crop production and negatively impacts agriculture worldwide. We previously isolated endophytic bacterial strains from two halophytic species: Artemisia princeps and Chenopodium ficifolium. We used three bacterial isolates: ART-1 (Lysinibacillus fusiformis), ART-10 (Lysinibacillus sphaericus), and CAL-8 (Brevibacterium pityocampae) to alleviate the impact of salinity stress on rice. The impact of 160 mM NaCl salinity on rice was significantly mitigated following inoculation with these bacterial strains, resulting in increased growth and chlorophyll content. Furthermore, OsNHX1, OsAPX1, OsPIN1 and OsCATA expression was increased, but OsSOS expression was decreased. Inductively coupled plasma mass spectrometry (ICP-MS) revealed reduced K+ and Na+ levels in shoots of bacteria-inoculated plants, whereas that of Mg2+ was increased. Bacterial inoculation reduced the content of total flavonoids in rice leaves. Salinized plants inoculated with bacteria showed reduced levels of endogenous salicylic acid (SA) and abscisic acid (ABA) but increased levels of jasmonic acid (JA). In conclusion, the bacterial isolates ART-1, ART-10, and CAL-8 alleviated the adverse effect of salinity on rice growth, which justifies their use as an eco-friendly agricultural practice.

MRI-Based Radiomics Approach for Differentiating Juvenile Myoclonic Epilepsy from Epilepsy with Generalized Tonic-Clonic Seizures Alone.

BACKGROUND: The clinical presentation of juvenile myoclonic epilepsy (JME) and epilepsy with generalized tonic-clonic seizures alone (GTCA) is similar, and MRI scans are often perceptually normal in both conditions making them challenging to differentiate. PURPOSE: To develop and validate an MRI-based radiomics model to accurately diagnose JME and GTCA, as well as to classify prognostic groups. STUDY TYPE: Retrospective. POPULATION: 164 patients (127 with JME and 37 with GTCA) patients (age 24.0 ± 9.6; 50% male), divided into training (n = 114) and test (n = 50) sets in a 7:3 ratio with the same proportion of JME and GTCA patients kept in both sets. FIELD STRENGTH/SEQUENCE: 3T; 3D T1-weighted spoiled gradient-echo. ASSESSMENT: A total of 17 region-of-interest in the brain were identified as having clinical evidence of association with JME and GTCA, from where 1581 radiomics features were extracted for each subject. Forty-eight machine-learning combinations of oversampling, feature selection, and classification algorithms were explored to develop an optimal radiomics model. The performance of the best radiomics models for diagnosis and for classification of the favorable outcome group were evaluated in the test set. STATISTICAL TESTS: Model performance measured using area under the curve (AUC) of receiver operating characteristic (ROC) curve. Shapley additive explanations (SHAP) analysis to estimate the contribution of each radiomics feature. RESULTS: The AUC (95% confidence interval) of the best radiomics models for diagnosis and for classification of favorable outcome group were 0.767 (0.591-0.943) and 0.717 (0.563-0.871), respectively. SHAP analysis revealed that the first-order and textural features of the caudate, cerebral white matter, thalamus proper, and putamen had the highest importance in the best radiomics model. CONCLUSION: The proposed MRI-based radiomics model demonstrated the potential to diagnose JME and GTCA, as well as to classify prognostic groups. MRI regions associated with JME, such as the basal ganglia, thalamus, and cerebral white matter, appeared to be important for constructing radiomics models. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning.

BACKGROUND: Accurate and rapid measurement of the MRI volume of meningiomas is essential in clinical practice to determine the growth rate of the tumor. Imperfect automation and disappointing performance for small meningiomas of previous automated volumetric tools limit their use in routine clinical practice. PURPOSE: To develop and validate a computational model for fully automated meningioma segmentation and volume measurement on contrast-enhanced MRI scans using deep learning. STUDY TYPE: Retrospective. POPULATION: A total of 659 intracranial meningioma patients (median age, 59.0 years; interquartile range: 53.0-66.0 years) including 554 women and 105 men. FIELD STRENGTH/SEQUENCE: The 1.0 T, 1.5 T, and 3.0 T; three-dimensional, T1 -weighted gradient-echo imaging with contrast enhancement. ASSESSMENT: The tumors were manually segmented by two neurosurgeons, H.K. and C.-K.P., with 10 and 26 years of clinical experience, respectively, for use as the ground truth. Deep learning models based on U-Net and nnU-Net were trained using 459 subjects and tested for 100 patients from a single institution (internal validation set [IVS]) and 100 patients from other 24 institutions (external validation set [EVS]), respectively. The performance of each model was evaluated with the Sørensen-Dice similarity coefficient (DSC) compared with the ground truth. STATISTICAL TESTS: According to the normality of the data distribution verified by the Shapiro-Wilk test, variables with three or more categories were compared by the Kruskal-Wallis test with Dunn's post hoc analysis. RESULTS: A two-dimensional (2D) nnU-Net showed the highest median DSCs of 0.922 and 0.893 for the IVS and EVS, respectively. The nnU-Nets achieved superior performance in meningioma segmentation than the U-Nets. The DSCs of the 2D nnU-Net for small meningiomas less than 1 cm3 were 0.769 and 0.780 with the IVS and EVS, respectively. DATA CONCLUSION: A fully automated and accurate volumetric measurement tool for meningioma with clinically applicable performance for small meningioma using nnU-Net was developed. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Efficient identification of palatability-related genes using QTL mapping in rice breeding.

The gelatinization temperature of rice is an important factor in determining the eating and cooking quality, and it affects consumer preference. The alkali digestion value (ADV) is one of the main methods used to test the quality of rice and has a high correlation with the gelatinization temperature. For the development of high-quality rice, it is important to understand the genetic basis of palatability-related traits, and QTL analysis is a statistical method linking phenotypic data and genotype data and is an effective method to explain the genetic basis of variation in complex traits. QTL mapping related to the ADV of brown and milled rice was performed using the 120 Cheongcheong/Nagdong double haploid (CNDH) line. As a result, 12 QTLs related to ADV were detected, and 20 candidate genes were selected from the RM588-RM1163 region of chromosome 6 through screening by gene function analysis. The comparison of the relative expression level of candidate genes showed that OsSS1q6 is highly expressed in CNDH lines with high ADV in both brown rice and milled rice. In addition, OsSS1q6 has high homology with the starch synthase 1 protein and interacts with various starch biosynthesis-related proteins, such as GBSSII, SBE, and APL. Therefore, we suggest that OsSS1q6 identified through QTL mapping could be one of the various genes involved in the gelatinization temperature of rice by regulating starch biosynthesis. This study can be used as basic data for breeding high-quality rice and provides a new genetic resource that can increase the palatability of rice. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01392-2.

Photosensitizing deep-seated cancer cells with photoprotein-conjugated upconversion nanoparticles.

To resolve the problem of target specificity and light transmission to deep-seated tissues in photodynamic therapy (PDT), we report a cancer cell-targeted photosensitizer using photoprotein-conjugated upconversion nanoparticles (UCNPs) with high target specificity and efficient light transmission to deep tissues. Core-shell UCNPs with low internal energy back transfer were conjugated with recombinant proteins that consists of a photosensitizer (KillerRed; KR) and a cancer cell-targeted lead peptide (LP). Under near infrared (NIR)-irradiating condition, the UCNP-KR-LP generated superoxide anion radicals as reactive oxygen species via NIR-to-green light conversion and exhibited excellent specificity to target cancer cells through receptor-mediated cell adhesion. Consequently, this photosensitizing process facilitated rapid cell death in cancer cell lines (MCF-7, MDA-MB-231, and U-87MG) overexpressing integrin beta 1 (ITGB1) receptors but not in a cell line (SK-BR-3) with reduced ITGB1 expression and a non-invasive normal breast cell line (MCF-10A). In contrast to green light irradiation, NIR light irradiation exhibited significant PDT efficacy in cancer cells located beneath porcine skin tissues up to a depth of 10 mm, as well as in vivo tumor xenograft mouse models. This finding suggests that the designed nanocomposite is useful for sensing and targeting various deep-seated tumors.

Hormones and the antioxidant transduction pathway and gene expression, mediated by Serratia marcescens DB1, lessen the lethality of heavy metals (As, Ni, and Cr) in Oryza sativa L.

Microorganisms have recently gained recognition as efficient biological tool for reducing heavy metal toxicity in crops. In this experiment, we isolated a potent heavy metal (As, Ni, and Cr) resistant rhizobacterium Serratia marcescens DB1 and detected its plant growth promoting traits such as phosphate solubilization, gibberellin synthesis, organic acid production and amino acid regulation. Based on these findings, DB1 was further investigated for application in a rice var. Hwayeongbyeo subjected to 1 mM As, 4 mM Ni, and 4 mM Cr stress. The rice plants treated with Cr and Ni appeared healthy but were lethal, indicating unfitness for consumption due to toxic metal deposition, whereas the plants treated with > 1 mM As instantaneously died. Our results showed that DB1 inoculation significantly decreased metal accumulation in the rice shoots. Particularly, Cr uptake dropped by 16.55% and 22.12% in (Cr + DB1) and (Cr + As + Ni + DB1), respectively, As dropped by 48.90% and 35.82% in (As + DB1) and (Cr + As + Ni + DB1), respectively, and Ni dropped by 7.95% and 19.56% in (Ni + DB1) and (Cr + As + Ni + DB1), respectively. These findings were further validated by gene expression analysis results, which showed that DB1 inoculation significantly decreased the expression of OsPCS1 (a phytochelatin synthase gene), OsMTP1 (a metal transporting gene), and OsMTP5 (a gene for the expulsion of excess metal). Moreover, DB1 inoculation considerably enhanced the morphological growth of rice through modulation of endogenous phytohormones (abscisic acid, salicylic acid, and jasmonic acid) and uptake of essential elements such as K and P. These findings indicate that DB1 is an effective biofertilizer that can mitigate heavy metal toxicity in rice crops.

A Measles Outbreak in a Local Children's Hospital in Korea, 2019.

A measles outbreak with 20 confirmed cases occurred at a local children's hospital in Daejeon from March 28 to April 21, 2019. The index patient was a 7-month-old girl with a recent history of travel to Vietnam. Contact tracing, active surveillance, and post-exposure prophylaxis were conducted by health authorities. Among the 20 patients, 11 (55%) were infants (0-11 months of age), three (15%) were aged 1-3 years, one (5%) was aged 4 years, and five (25%) were adults. Fifteen (75%) patients did not have a history of measles vaccination, and five (25%) had received only one vaccine dose. This study described the importance of prompt application of infection control measures in susceptible environments, including hospitals. Age-appropriate vaccination and providing information on infectious diseases to international travelers and multicultural families in Korea is vital.

Visual Aura in Non-Migraine Headaches: A Population Study.

BACKGROUND: Visual aura (VA) occurs mostly in migraine with aura (MA), but some case studies have reported aura in non-migraine headaches. Thus, information of VA in non-migraine headaches is scarce. Aim of this study was to investigate the prevalence and impact of VA in non-migraine headache and compare it with that of migraine headache. METHODS: This study was a nationwide population-based study. We used an internet-based headache diagnosis questionnaire to diagnose headache, and various modules to evaluate clinical features and comorbidities of participants with headache. We defined migraine headache as migraine and probable migraine (PM), whereas non-migraine headache was defined as a headache but not migraine or PM. VA was defined as a self-reporting VA rating scale score ≥ 3. RESULTS: Of the 3,030 participants, 1,431 (47.2%) and 507 (16.7%) had non-migraine headache and migraine headache, respectively. VA prevalence was much lower in the non-migraine headache group than in the migraine headache group (14.5% [207/1,431] vs. 26.0% [132/507], P < 0.001). In subjects with non-migraine headache, those with VA had a markedly higher number of headache days per 30 days (median [25th-75th percentiles]: 2.0 [1.0-5.0] vs. 2.0 [1.0-3.0], P < 0.001), and headache-related disability (6.0 [3.0-16.0] vs. 2.0 [0.0-7.0], P < 0.001) than those without VA. VA prevalence did not differ significantly according to age and sex. CONCLUSION: Non-migraine headache with VA patients had more severe symptoms than those without VA. These findings may improve the understanding of VA and the management of individuals with non-migraine headache.

First report of leaf anthracnose caused by Colletotrichum camelliae on tea plants (Camellia sinensis) in South Korea.

The tea plant (Camellia sinensis (L.) O. Kuntze) is a popular non-alcoholic beverage crop worldwide. The tea market in South Korea is projected to increase annually by 4.59% (Statista, 2022). Boseong, Hadong, and Jeju Island are the main tea-growing regions in South Korea. Anthracnose is one of the major diseases of tea plants and is responsible for substantial yield loss and poor tea quality. In 2021, anthracnose of tea (disease incidence of 30%) was observed in a garden (33°28'45.5"N 126°42'02.2"E) at Jeju Island, where the Yabukita cultivar has been cultivated. The typical symptoms consisted of round or irregularly shaped lesions with gray-white centers and purple-brown borders. Twelve morphologically similar isolates were recovered from 12 infected leaves using the single spore isolation method on solid potato dextrose agar (PDA) (Cai et al. 2009). Four representative isolates (GT6, GT7, GT8, and GT11) were identified based on morphology, molecular analysis, and pathogenicity tests. The upper side of seven-day-old colonies on PDA (incubated at 25 °C in the dark) was off-white with white aerial mycelia and gray-white with black zonation on their reverse side. Conidia were hyaline, aseptate, cylindrical, with both obtuse ends, and measuring 12.3 - 25.8 µm × 4.4 - 9.3 µm (n = 50). Appressoria were dark brown, irregularly shaped with a smooth edge, and measuring 7.3 -18.8 µm × 6.9 - 11.3 µm (n = 50). According to morphological characteristics, the fungal isolates were tentatively identified as the Colletotrichum gloeosporioides complex, including C. caelliae (Wang et al. 2016; Weir et al. 2012). The genomic DNA was extracted, and the ribosomal internal transcribed spacer (ITS), ß-tubulin-2 (TUB2) gene, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene, actin (ACT), calmodulin (CAL), and the Apn2-Mat1-2 intergenic spacer and partial mating type (ApMat) genes were amplified and subsequently sequenced using primer sets ITS1/ITS4, BT2a/BT2b, GDF1/GDR1, ACT-512F/ACT-783R1, CL1C/CL2C, and AM-F/AM-R, respectively (Silva et al. 2012; Weir et al. 2012). The resulting sequences were deposited in GenBank accession numbers (LC738932-LC738959). All the representative isolates were identified as C. camelliae by constructing the 50% majority rule consensus and maximum likelihood phylogenetic treebased on the combined ITS, TUB2, GAPDH, ACT, CAL, and ApMat sequences using MrBayes v. 3.2.2 and Mega X, respectively (Kumar et al., 2018; Ronquist et al. 2012). The pathogenicity of these isolates was tested on healthy leaves of 2- years-old tea seedlings (the Yabukita cultivar). Onside of unwounded or wounded leaves of seedlings were inoculated with 20 µL of conidial suspension (1 × 106 conidia or spores/ml) per spot (3-4 wounded or unwounded spots per side per leaf). Another side of the leaves received sterile distilled water and served as a control. Each treatment was replicated three times (three seedlings/isolate and four leaves per seedling) and this experiment was repeated twice. All plants were covered with plastic bags, placed in a growth chamber, and incubated at 25 °C with a 12-h photoperiod and 90% relative humidity. Typical anthracnose symptoms appeared on wounded leaves after two days of inoculation. Unwounded and controlled leaves remain asymptotic. To confirm Koch's postulates, fungal isolates were re-isolated from inoculated leaf lesions and identified as C. camelliae based on morphology and ITS sequences. Colletotrichum camelliae is a very common pathogen associated with tea anthracnose worldwide, including China (Liu et al. 2015; Wang et al. 2016).To the best of our knowledge, this is the first report of anthracnose in tea trees caused by C. camelliae in South Korea. The results of this study could help come up with better ways to keep an eye on and deal with this devastating on tea plants. Key words: Tea anthracnose, Colletotrichum camelliae, pathogenicity References Cai, L., et al. 2009. Fungal Divers. 39:183. Kumar, S., et al. 2018. Mol. Biol. Evol. 35:1547. Liu, F. et al. 2015. Persoonia. 35: 63-86. Ronquist, F. et al. 2012. Syst. Biol. 61:539-542. Silva, D. N. et al. 2012. Mycologia. 104:396-409. Statista 2022. Statista Digital Market out Look. Available at www.statista.com. Wang, Y.-C. et al. 2016. Sci. Rep. 6: 35287. Weir, B. S., et al. 2012. Stud. Mycol. 73:115.

Molecular Characterization and Fungicide Sensitivity of Jujube Pathogens Colletotrichum gloeosporioides Sensu Stricto and Colletotrichum nymphaeae in South Korea.

Jujube (Ziziphus jujuba) is cultivated across South Korea because of its medicinal and economic value. It is used as a sweetener in jam, tea, and snacks and a garnish in many cuisines. Anthracnose caused by Colletotrichum spp. accounts for huge economic losses for jujube growers. In 2019 and 2020, severe anthracnose was observed in the jujube-growing areas of South Korea. The infected fruit displayed small, water-soaked, sunken, circular spots. Infected fruit were collected from different commercial orchards of Boeungun and Gyeongsan regions of South Korea, and putative causal agents were isolated on potato dextrose agar. Based on the morphological and molecular characteristics, the fungal isolates were identified as Colletotrichum gloeosporioides sensu stricto and C. nymphaeae. The pathogenicity of these isolates was confirmed by inoculating a conidial suspension (1 × 106 conidia ml-1) on healthy fruit. The in vitro sensitivity of the fungal isolates to tebuconazole, carbendazim, and azoxystrobin was also tested. All isolates showed high sensitivity to azoxystrobin in terms of mycelial growth inhibition (half maximal effective concentration value of 0.01 to 0.6 µg/ml). To the best of our knowledge, this is also the first report of jujube anthracnose caused by C. nymphaeae in South Korea.

Lossless Data Compression for Time-Series Sensor Data Based on Dynamic Bit Packing.

In this paper, we propose a bit depth compression (BDC) technique, which performs bit packing by dynamically determining the pack size based on the pattern of the bit depth level of the sensor data, thereby maximally reducing the space wastage that may occur during the bit packing process. The proposed technique can dynamically perform bit packing according to the data's characteristics, which may have many outliers or several multidimensional variations, and therefore has a high compression ratio. Furthermore, the proposed method is a lossless compression technique, which is especially useful as training data in the field of artificial intelligence or in the predictive analysis of data science. The proposed method effectively addresses the spatial inefficiency caused by unpredictable outliers during time-series data compression. Additionally, it offers high compression efficiency, allowing for storage space savings and optimizing network bandwidth utilization while transmitting large volumes of data. In the experiment, the BDC method demonstrated an improvement in the compression ratio of up to 247%, with 30% on average, compared with other compression algorithms. In terms of energy consumption, the proposed BDC also improves data transmission using Bluetooth up to 34%, with 18% on average, compared with other compression algorithms.