Multicycle terahertz pulse generation by optical rectification in LiNbO3, LiTaO3, and BBO crystals.

We report multicycle, narrowband, terahertz radiation at 14.8 THz produced by phase-matched optical rectification of femtosecond laser pulses in bulk lithium niobate (LiNbO3) crystals. Our experiment and simulation show that the output terahertz energy greatly enhances when the input laser pulse is highly chirped, contrary to a common optical rectification process. We find this abnormal behavior is attributed to a linear electro-optic (EO) effect, in which the laser pulse propagating in LiNbO3 is modulated by the terahertz field it produces, and this in turn drives optical rectification more effectively to produce the terahertz field. This resonant cascading effect can greatly increase terahertz conversion efficiencies when the input laser pulse is properly pre-chirped with additional third order dispersion. We also observe similar multicycle terahertz emission from lithium tantalate (LiTaO3) at 14 THz and barium borate (BBO) at 7 THz, 10.6 THz, and 14.6 THz, all produced by narrowband phase-matched optical rectification.

Simplified single-shot supercontinuum spectral interferometry.

We have experimentally demonstrated a simplified method for performing single-shot supercontinuum spectral interferometry (SSSI) that does not require pre-characterization of the probe pulse. The method, originally proposed by D. T. Vu, D. Jang, and K. Y. Kim, uses a genetic algorithm (GA) and as few as two time-delayed pump-probe shots to retrieve the pump-induced phase shift on the probe [Opt. Express26, 20572 (2018)]. We show that the GA is able to successfully retrieve the transient modulations on the probe, and that the error in the retrieved modulation decreases dramatically with the number of shots used. In addition, we propose and demonstrate a practical method that allows SSSI to be done with a single pump-probe shot (again, without the need for pre-characterization of the probe). This simplified method can prove to be immensely useful when performing SSSI with a low-repetition-rate laser source.

Generation of 0.7 mJ multicycle 15 THz radiation by phase-matched optical rectification in lithium niobate.

We demonstrate efficient multicycle terahertz pulse generation at 14.6 THz from large-area lithium niobate crystals by using high-energy (up to 2 J) femtosecond Ti:sapphire laser pulses. Such terahertz radiation is produced by phase-matched optical rectification in lithium niobate. Experimentally, we achieve maximal terahertz energy of 0.71 mJ with conversion efficiency of ∼0.04%. Our experimental setup is simple and easily upscalable to produce multi-millijoule, multicycle terahertz radiation with proper lithium niobate crystals.

Highly enhanced terahertz conversion by two-color laser filamentation at low gas pressures.

We present an experimental study on pressure-dependent terahertz generation from two-color femtosecond laser filamentation in various gases. Contrary to short-focusing geometry, we find that long filamentation yields higher terahertz energy at lower gas pressures in most gases. This counter-intuitive phenomenon occurs due to multiple peculiar properties associated with filamentation. In practice, filamentation in low-pressure argon provides a maximum laser-to-terahertz conversion efficiency of 0.1%, about 10 times higher than in atmospheric air. In addition, our pressure-dependent study reveals an anticorrelation between terahertz output energy and local plasma fluorescence brightness. This determines the absolute phase difference between two-color laser fields for maximal terahertz generation, as well as verifies the microscopic mechanism of terahertz generation in two-color laser mixing.

Scalable terahertz generation by large-area optical rectification at 80 TW laser power.

We demonstrate high-energy terahertz generation from a large-aperture (75-mm diameter) lithium niobate wafer by using a femtosecond laser with energy up to 2 J. This scheme utilizes optical rectification in a bulk lithium niobate crystal, where most terahertz energy is emitted from a thin layer of the rear surface. Despite its simple setup, this scheme can yield 0.19 mJ of terahertz energy with laser-to-terahertz conversion efficiencies of ∼10-4, about 3 times better than ZnTe when pumped at 800 nm. The experimental setup is upscalable for multimillijoule terahertz generation with petawatt laser pumping.

Simplified chirp characterization in single-shot supercontinuum spectral interferometry.

Single-shot supercontinuum spectral interferometry (SSSI) is an optical technique that can measure ultrafast transients in the complex index of refraction. This method uses chirped supercontinuum reference/probe pulses that need to be pre-characterized prior to use. Conventionally, the spectral phase (or chirp) of those pulses can be determined from a series of phase or spectral measurements taken at various time delays with respect to a pump-induced modulation. Here we propose a novel method to simplify this process and characterize reference/probe pulses up to the third order dispersion from a minimum of 2 snapshots taken at different pump-probe delays. Alternatively, without any pre-characterization, our method can retrieve both unperturbed and perturbed reference/probe phases, including the pump-induced modulation, from 2 time-delayed snapshots. From numerical simulations, we show that our retrieval algorithm is robust and can achieve high accuracy even with 2 snapshots. Without any apparatus modification, our method can be easily applied to any experiment that uses SSSI.

Identification and functional characterization of Siberian wild rye (Elymus sibiricus L.) small heat shock protein 16.9 gene (EsHsp16.9) conferring diverse stress tolerance in prokaryotic cells.

Small heat shock proteins (Hsps) protect against stress-inducible denaturation of substrates. Our objectives were to clone and examine the mRNA expression of the Hsp16.9 gene from Siberian wild rye grown under diverse stress treatments. We characterized EsHsp16.9 from Elymus sibiricus L. EsHsp16.9 has a 456-bp open reading frame that encodes a 151-amino acid protein with a conserved α-crystallin domain. Northern blot analysis showed that EsHsp16.9 transcripts were enhanced by heat, drought, arsenate, methyl viologen, and H2O2 treatment. In addition, recombinant EsHsp16.9 protein acts as a molecular chaperone to prevent the denaturation of malate dehydrogenase. Growth of cells overexpressing EsHsp16.9 was up to 200% more rapid in the presence of NaCl, arsenate, and polyethylene glycol than that of cells harboring an empty vector. These data suggest that EsHsp16.9 acts as a molecular chaperone that enhances stress tolerance in living organisms.

Effects of Virtual Reality (VR)-Based Meditation on Sleep Quality, Stress, and Autonomic Nervous System Balance in Nursing Students.

This study aimed to determine the effects of virtual reality (VR)-based meditation on the sleep quality, stress, and autonomic nervous system balance of nursing students. Nursing students were categorized into experimental groups I (VR-based meditation) and II (concentration meditation) and a control group. Before the study's initiation, we measured the participants' general characteristics, and a sleep measurement device was used to measure sleep quality. Stress levels and heart rate variability were measured before and after study completion. On the first day, all three groups slept without any intervention. On days 2-6, only experimental groups I and II implemented the intervention before sleeping. We found that the subjective sleep quality, wakefulness after sleep onset, sleep efficiency, deep sleep quality, subjective stress, objective stress, and autonomic nervous system balance of the VR meditation group were significantly better than those of the other groups. Our results reveal that the participants who underwent VR-based meditation experienced better sleep quality, lower stress levels, and improved autonomic nervous system balance compared with those in the concentration meditation and control groups. Thus, VR-based meditation effectively enhances sleep quality, lowers stress levels, and improves autonomic nervous system balance in nursing students.

Percolative Metal Microweb-Based Flexible Lithium-Ion Battery with Fast Charging and High Energy Density.

Flexible and high-performance lithium-ion batteries (LIBs) encounter challenges due to the inherent trade-offs in conventional electrode designs, particularly concerning mechanical flexibility and high energy density. Here, a novel percolative metal microweb-based electrode, fabricated via electrohydrodynamic processes, yielding a three-dimensional (3D) network structure with exceptional electrical properties and mechanical durability is introduced. This lightweight electrode design addresses the need for improved energy density by reducing the weight of the current collector, which typically accounts for more than 10% of the battery's weight. The 3D architecture of the electrode enhances the contact area with the electrolyte, thereby minimizing polarization voltage and improving lithium-ion diffusion. Furthermore, the low coating thickness-to-weight ratio promotes electron transfer and mitigates capacity fade at high current densities. The microweb-based full cell exhibits energy and power densities of 110 and 1,048 W kg⁻¹ at 10 C, respectively, which are the highest reported values among LIBs utilizing similar materials. The design of the electrode proposed in this study is expected to significantly contribute to the development of wearable and flexible electronics.

Ionizing terahertz waves with 260 MV/cm from scalable optical rectification.

Terahertz (THz) waves, known as non-ionizing radiation owing to their low photon energies, can actually ionize atoms and molecules when a sufficiently large number of THz photons are concentrated in time and space. Here, we demonstrate the generation of ionizing, multicycle, 15-THz waves emitted from large-area lithium niobate crystals via phase-matched optical rectification of 150-terawatt laser pulses. A complete characterization of the generated THz waves in energy, pulse duration, and focal spot size shows that the field strength can reach up to 260 megavolts per centimeter. In particular, a single-shot THz interferometer is employed to measure the THz pulse duration and spectrum with complementary numerical simulations. Such intense THz pulses are irradiated onto various solid targets to demonstrate THz-induced tunneling ionization and plasma formation. This study also discusses the potential of nonperturbative THz-driven ionization in gases, which will open up new opportunities, including nonlinear and relativistic THz physics in plasma.

Comparing Montreal Cognitive Assessment Performance in Parkinson's Disease Patients: Age- and Education-Adjusted Cutoffs vs. Machine Learning.

OBJECTIVE: The Montreal Cognitive Assessment (MoCA) is recommended for general cognitive evaluation in Parkinson's disease (PD) patients. However, age- and education-adjusted cutoffs specifically for PD have not been developed or systematically validated across PD cohorts with diverse education levels. METHODS: In this retrospective analysis, we utilized data from 1,293 Korean patients with PD whose cognitive diagnoses were determined through comprehensive neuropsychological assessments. Age- and education-adjusted cutoffs were formulated based on 1,202 patients with PD. To identify the optimal machine learning model, clinical parameters and MoCA domain scores from 416 patients with PD were used. Comparative analyses between machine learning. METHODS: and different cutoff criteria were conducted on an additional 91 consecutive patients with PD. RESULTS: The cutoffs for cognitive impairment decrease with increasing age within the same education level. Similarly, lower education levels within the same age group correspond to lower cutoffs. For individuals aged 60-80 years, cutoffs were set as follows: 25 or 24 years for those with more than 12 years of education, 23 or 22 years for 10-12 years, and 21 or 20 years for 7-9 years. Comparisons between age- and education-adjusted cutoffs and the machine learning method showed comparable accuracies. The cutoff method resulted in a higher sensitivity (0.8627), whereas machine learning yielded higher specificity (0.8250). CONCLUSION: Both the age- and education-adjusted cutoff. METHODS: and machine learning. METHODS: demonstrated high effectiveness in detecting cognitive impairment in PD patients. This study highlights the necessity of tailored cutoffs and suggests the potential of machine learning to improve cognitive assessment in PD patients.

Mechanism of elliptically polarized terahertz generation in two-color laser filamentation.

We investigate the mechanism of elliptically polarized terahertz (THz) pulse generation in femtosecond two-color laser-produced plasma. In the case of in-line laser focusing, we observe the THz polarization evolves from linear to elliptical with increasing plasma length. This ellipticity arises from two combined effects--successive polarization rotation of local THz plasma sources, caused by laser phase and polarization modulations, and the velocity mismatch between laser and THz, which produces an elliptical THz pulse from a series of time-delayed, polarization-rotating local THz fields.

RelCurator: a text mining-based curation system for extracting gene-phenotype relationships specific to neurodegenerative disorders.

BACKGROUND: The identification of gene-phenotype relationships is important in medical genetics as it serves as a basis for precision medicine. However, most of the gene-phenotype relationship data are buried in the biomedical literature in textual form. OBJECTIVE: We propose RelCurator, a curation system that extracts sentences including both gene and phenotype entities related to specific disease categories from PubMed articles, provides rich additional information such as entity taggings, and predictions of gene-phenotype relationships. METHODS: We targeted neurodegenerative disorders and developed a deep learning model using Bidirectional Gated Recurrent Unit (BiGRU) networks and BioWordVec word embeddings for predicting gene-phenotype relationships from biomedical texts. The prediction model is trained with more than 130,000 labeled PubMed sentences including gene and phenotype entities, which are related to or unrelated to neurodegenerative disorders. RESULTS: We compared the performance of our deep learning model with those of Bidirectional Encoder Representations from Transformers (BERT), Support Vector Machine (SVM), and simple Recurrent Neural Network (simple RNN) models. Our model performed better with an F1-score of 0.96. Furthermore, the evaluation done using a few curation cases in the real scenario showed the effectiveness of our work. Therefore, we conclude that RelCurator can identify not only new causative genes, but also new genes associated with neurodegenerative disorders' phenotype. CONCLUSION: RelCurator is a user-friendly method for accessing deep learning-based supporting information and a concise web interface to assist curators while browsing the PubMed articles. Our curation process represents an important and broadly applicable improvement to the state of the art for the curation of gene-phenotype relationships.

Multi-millijoule terahertz emission from laser-wakefield-accelerated electrons.

High-power terahertz radiation was observed to be emitted from a gas jet irradiated by 100-terawatt-class laser pulses in the laser-wakefield acceleration of electrons. The emitted terahertz radiation was characterized in terms of its spectrum, polarization, and energy dependence on the accompanying electron bunch energy and charge under various gas target conditions. With a nitrogen target, more than 4 mJ of energy was produced at <10 THz with a laser-to-terahertz conversion efficiency of ~0.15%. Such strong terahertz radiation is hypothesized to be produced from plasma electrons accelerated by the ponderomotive force of the laser and the plasma wakefields on the time scale of the laser pulse duration and plasma period. This model is examined with analytic calculations and particle-in-cell simulations to better understand the generation mechanism of high-energy terahertz radiation in laser-wakefield acceleration.

Transgenic Expression of MsHsp23 Confers Enhanced Tolerance to Abiotic Stresses in Tall Fescue.

Tall fescue (Festuca arundinacea Schreb.) is an important cool season forage plant that is not well suited to extreme heat, salts, or heavy metals. To develop transgenic tall fescue plants with enhanced tolerance to abiotic stress, we introduced an alfalfa Hsp23 gene expression vector construct through Agrobacterium-mediated transformation. Integration and expression of the transgene were confirmed by polymerase chain reaction, northern blot, and western blot analyses. Under normal growth conditions, there was no significant difference in the growth of the transgenic plants and the non-transgenic controls. However, when exposed to various stresses such as salt or arsenic, transgenic plants showed a significantly lower accumulation of hydrogen peroxide and thiobarbituric acid reactive substances than control plants. The reduced accumulation of thiobarbituric acid reactive substances indicates that the transgenic plants possessed a more efficient reactive oxygen species-scavenging system. We speculate that the high levels of MsHsp23 proteins in the transgenic plants protect leaves from oxidative damage through chaperon and antioxidant activities. These results suggest that MsHsp23 confers abiotic stress tolerance in transgenic tall fescue and may be useful in developing stress tolerance in other crops.

Accuracy of Machine Learning Using the Montreal Cognitive Assessment for the Diagnosis of Cognitive Impairment in Parkinson's Disease.

OBJECTIVE: The Montreal Cognitive Assessment (MoCA) is recommended for assessing general cognition in Parkinson's disease (PD). Several cutoffs of MoCA scores for diagnosing PD with cognitive impairment (PD-CI) have been proposed, with varying sensitivity and specificity. This study investigated the utility of machine learning algorithms using MoCA cognitive domain scores for improving diagnostic performance for PD-CI. METHODS: In total, 2,069 MoCA results were obtained from 397 patients with PD enrolled in the Parkinson's Progression Markers Initiative database with a diagnosis of cognitive status based on comprehensive neuropsychological assessments. Using the same number of MoCA results randomly sampled from patients with PD with normal cognition or PD-CI, discriminant validity was compared between machine learning (logistic regression, support vector machine, or random forest) with domain scores and a cutoff method. RESULTS: Based on cognitive status classification using a dataset that permitted sampling of MoCA results from the same individual (n = 221 per group), no difference was observed in accuracy between the cutoff value method (0.74 ± 0.03) and machine learning (0.78 ± 0.03). Using a more stringent dataset that excluded MoCA results (n = 101 per group) from the same patients, the accuracy of the cutoff method (0.66 ± 0.05), but not that of machine learning (0.74 ± 0.07), was significantly reduced. Inclusion of cognitive complaints as an additional variable improved the accuracy of classification using the machine learning method (0.87-0.89). CONCLUSION: Machine learning analysis using MoCA domain scores is a valid method for screening cognitive impairment in PD.

The Protein-Protein Interaction Network of Hereditary Parkinsonism Genes Is a Hierarchical Scale-Free Network.

PURPOSE: Hereditary parkinsonism genes consist of causative genes of familial Parkinson's disease (PD) with a locus symbol prefix (PARK genes) and hereditary atypical parkinsonian disorders that present atypical features and limited responsiveness to levodopa (non-PARK genes). Although studies have shown that hereditary parkinsonism genes are related to idiopathic PD at the phenotypic, gene expression, and genomic levels, no study has systematically investigated connectivity among the proteins encoded by these genes at the protein-protein interaction (PPI) level. MATERIALS AND METHODS: Topological measurements and physical interaction enrichment were performed to assess PPI networks constructed using some or all the proteins encoded by hereditary parkinsonism genes (n=96), which were curated using the Online Mendelian Inheritance in Man database and literature. RESULTS: Non-PARK and PARK genes were involved in common functional modules related to autophagy, mitochondrial or lysosomal organization, catecholamine metabolic process, chemical synapse transmission, response to oxidative stress, neuronal apoptosis, regulation of cellular protein catabolic process, and vesicle-mediated transport in synapse. The hereditary parkinsonism proteins formed a single large network comprising 51 nodes, 83 edges, and three PPI pairs. The probability of degree distribution followed a power-law scaling behavior, with a degree exponent of 1.24 and a correlation coefficient of 0.92. LRRK2 was identified as a hub gene with the highest degree of betweenness centrality; its physical interaction enrichment score was 1.28, which was highly significant. CONCLUSION: Both PARK and non-PARK genes show high connectivity at the PPI and biological functional levels.

PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine.

Precision medicine has been revolutionized by the advent of high-throughput next-generation sequencing (NGS) technology and development of various bioinformatic analysis tools for large-scale NGS big data. At the population level, biomedical studies have identified human diseases and phenotype-associated genetic variations using NGS technology, such as whole-genome sequencing, exome sequencing, and gene panel sequencing. Furthermore, patients' genetic variations related to a specific phenotype can also be identified by analyzing their genomic information. These breakthroughs paved the way for the clinical diagnosis and precise treatment of patients' diseases. Although many bioinformatics tools have been developed to analyze the genetic variations from the individual patient's NGS data, it is still challenging to develop user-friendly programs for clinical physicians who do not have bioinformatics programing skills to diagnose a patient's disease using the genomic data. In response to this demand, we developed a Phenotype to Genotype Variation program (PhenGenVar), which is a user-friendly interface for monitoring the variations in a gene of interest for molecular diagnosis. This allows for flexible filtering and browsing of variants of the disease and phenotype-associated genes. To test this program, we analyzed the whole-genome sequencing data of an anonymous person from the 1000 human genome project data. As a result, we were able to identify several genomic variations, including single-nucleotide polymorphism, insertions, and deletions in specific gene regions. Therefore, PhenGenVar can be used to diagnose a patient's disease. PhenGenVar is freely accessible and is available at our website.

Efficacy of Adductor Canal Block on Medial Knee Pain in Patients with Knee Osteoarthritis: A Randomized Single-Blind Placebo-Controlled Study.

BACKGROUND: This study aimed to confirm the efficacy of ultrasound-guided adductor canal block (ACB) as a treatment option for medial knee pain caused by knee osteoarthritis (KOA). METHODS: In total, 31 participants with medial knee pain due to KOA were randomized to either the ACB (ultrasound-guided ACB, n = 15) or placebo group (1 mL of 1% lidocaine, n = 16). The primary outcome was a numerical rating scale (NRS) for knee pain intensity comparing before and 4 weeks after injection. The secondary outcomes were the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), average daily number of analgesics consumed, average daily opioid consumption, and Timed Up and Go (TUG) test results before and 4 weeks after injection. RESULTS: Participants' baseline characteristics were not significantly different between the groups, except for age. At 4 weeks post-injection, the NRS score in the ACB group significantly improved compared to that in the placebo group (p = 0.009). However, the WOMAC, average daily number of analgesics consumed, average daily opioid consumption, and TUG test results did not show significant differences. CONCLUSION: ACB can be an effective treatment for reducing medial knee pain in patients with KOA.

Development of antibiotic marker-free creeping bentgrass resistance against herbicides.

Herbicide-resistant creeping bentgrass plants (Agrostis stolonifera L.) without antibiotic-resistant markers were produced by Agrobacterium-mediated transformation. Embryogenic callus tissues were infected with Agrobacterium tumefaciens EHA105, harboring the bar and the CP4-EPSPS genes for bialaphos and glyphosate resistance. Phosphinothricin-resistant calli and plants were selected. Soil-grown plants were obtained at 14-16 weeks after transformation. Genetic transformation of the selected, regenerated plants was validated by PCR. Southern blot analysis revealed that at least one copy of the transgene was integrated into the genome of the transgenic plants. Transgene expression was confirmed by Northern blot. CP4-EPSPS protein was detected by ELISA. Transgenic plants remained green and healthy when sprayed with Basta, containing 0.5% glufosinate ammonium or glyphosate. The optimized Agrobacterium-mediated transformation method resulted in an average of 9.4% transgenic plants. The results of the present study suggest that the optimized marker-free technique could be used as an effective and reliable method for routine transformation, which may facilitate the development of varieties of new antibiotic-free grass species.