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Abstract The exploitation of sharks and the degradation of their habitats elevate the urgency to understand the factors that influence offspring survival and ultimately shark reproductive success. We monitored and sampled blacktip reef sharks (Carcharhinus melanopterus) in nursery habitats of Moorea Island (French Polynesia), to improve knowledge on shark reproductive behavior and biology. We sampled fin clips and morphometrics from 230 young-of-the-year sharks and used microsatellite DNA markers to process parentage analysis to study the reproductive philopatric behavior in female sharks and the matrotrophy within litters. These traits are driving the success of the local replenishment influencing selection through birth site and maternal reserves transmitted to pups. Parentage analysis revealed that some female sharks changed their parturition areas (inter-seasonally) while other female sharks came back to the same site for parturition, providing evidence for a plastic philopatric behavior. Morphometrics showed that there was no significant relationship between body condition indices and nursery locations. However, similarities and differences in body condition were observed between individuals sharing the same mother, indicating that resource allocation within some shark litters might be unbalanced. Our findings further our understanding of the reproductive biology and behavior that shape shark populations with the aim to introduce these parameters into future conservation strategies.

Abstract In this work, a coupled Monte Carlo Genetic Algorithm (MCGA) approach is used to optimize a gas phase uranium oxide reaction mechanism based on plasma flow reactor (PFR) measurements. The PFR produces a steady Ar plasma containing U, O, H, and N species with high temperature regions (3000–5000 K) relevant to observing UO formation via optical emission spectroscopy. A global kinetic treatment is used to model the chemical evolution in the PFR and to produce synthetic emission signals for direct comparison with experiments. The parameter space of a uranium oxide reaction mechanism is then explored via Monte Carlo sampling using objective functions to quantify the model-experiment agreement. The Monte Carlo results are subsequently refined using a genetic algorithm to obtain an experimentally corroborated set of reaction pathways and rate coefficients. Out of 12 reaction channels targeted for optimization, four channels are found to be well constrained across all optimization runs while another three channels are constrained in select cases. The optimized channels highlight the importance of the OH radical in oxidizing uranium in the PFR. This study comprises a first step toward producing a comprehensive experimentally validated reaction mechanism for gas phase uranium molecular species formation.

Abstract In order to model the fate and transport of particles following a nuclear explosion, there must first be an understanding of individual physical and chemical processes that affect particle formation. One interaction pertinent to fireball chemistry and resultant debris formation is that between uranium and oxygen. In this study, we use laser ablation of uranium metal in different concentrations of oxygen gas, either 16O2 or 18O2, to determine the influence of oxygen on rapidly cooling uranium. Analysis of recovered particulates using infrared absorption and Raman spectroscopies indicate that the micrometer-sized particulates are predominantly amorphous UOx (am-UOx, where 3 ≤ x ≤ 4) and UO2 after ablation in 1 atm of pure O2 and a 1% O2/Ar mixture, respectively. Energy dispersive X-ray spectroscopy (EDS) of particulates formed in pure O2 suggest an O/U ratio of ~ 3.7, consistent with the vibrational spectroscopy analysis. Both am-UOx and UO2 particulates convert to α-U3O8 when heated. Lastly, experiments performed in 18O2 environments show the formation of 18O-substituted uranium oxides; vibrational frequencies for am-U18Ox are reported for the first time. When compared to literature, this work shows that cooling timescales can affect the structural composition of uranium oxides (i.e., crystalline vs. amorphous). This indicator can be used in current models of nuclear explosions to improve our predicative capabilities of chemical speciation.

We use a machine learning-based tomography method to obtain high-resolution subsurface geophysical structure in Long Beach, CA, from seismic noise recorded on a "large-N" array with 5204 geophones (~13.5 million travel times). This method, called locally sparse travel time tomography (LST) uses unsupervised machine learning to exploit the dense sampling obtained by ambient noise processing on large arrays. Dense sampling permits the LST method to learn directly from the data a dictionary of local, or small-scale, geophysical features. The features are the small scale patterns of Earth structure most relevant to the given tomographic imaging scenario. Using LST, we obtain a high-resolution 1 Hz Rayleigh wave phase speed map of Long Beach. Among the geophysical features shown in the map, the important Silverado aquifer is well isolated relative to previous surface wave tomography studies. Our results show promise for LST in obtaining detailed geophysical structure in travel time tomography studies.

Increasing levels of pCO2 within the oceans will select for resistant organisms such as anemones, which may thrive under ocean acidification conditions. However, increasing pCO2 may alter the bacterial community of marine organisms, significantly affecting the health status of the host. A pH gradient associated with a natural volcanic vent system within Levante Bay, Vulcano Island, Italy, was used to test the effects of ocean acidification on the bacterial community of two anemone species in situ, Anemonia viridis and Actinia equina using 16 S rDNA pyrosequencing. Results showed the bacterial community of the two anemone species differed significantly from each other primarily because of differences in the Gammaproteobacteria and Epsilonproteobacteria abundances. The bacterial communities did not differ within species among sites with decreasing pH except for A. viridis at the vent site (pH = 6.05). In addition to low pH, the vent site contains trace metals and sulfide that may have influenced the bacteria community of A. viridis. The stability of the bacterial community from pH 8.1 to pH 7.4, coupled with previous experiments showing the lack of, or beneficial changes within anemones living under low pH conditions indicates that A. viridis and A. equina will be winners under future ocean acidification scenarios. [ABSTRACT FROM AUTHOR]

Increasing levels of pCO2 within the oceans will select for resistant organisms such as anemones, which may thrive under ocean acidification conditions. However, increasing pCO2 may alter the bacterial community of marine organisms, significantly affecting the health status of the host. A pH gradient associated with a natural volcanic vent system within Levante Bay, Vulcano Island, Italy, was used to test the effects of ocean acidification on the bacterial community of two anemone species in situ, Anemonia viridis and Actinia equina using 16 S rDNA pyrosequencing. Results showed the bacterial community of the two anemone species differed significantly from each other primarily because of differences in the Gammaproteobacteria and Epsilonproteobacteria abundances. The bacterial communities did not differ within species among sites with decreasing pH except for A. viridis at the vent site (pH = 6.05). In addition to low pH, the vent site contains trace metals and sulfide that may have influenced the bacteria community of A. viridis. The stability of the bacterial community from pH 8.1 to pH 7.4, coupled with previous experiments showing the lack of, or beneficial changes within anemones living under low pH conditions indicates that A. viridis and A. equina will be winners under future ocean acidification scenarios. [ABSTRACT FROM AUTHOR]

The purpose of this study is to provide data for the best possible circuit breaker allocation in power grids with HVDC transmission while taking circuit breaker failure into account. The lack of a suitable selection of HVDC circuit breakers is one of the primary obstacles to establishing an appropriate protection system for HVDC transmission. This research focuses on finding the optimal circuit breaker allocation strategy with respect to the transient response of the system, especially when the grid operator is using existing circuit breakers, rather than on the necessary steps to improve the technology of circuit breakers. Case studies are simulated using PSCAD/EMTDC in order to verify the transient response of the transmission system corresponding to the allocation of circuit breakers and the circumstance of circuit breaker failure. It is crucial to remember that there isn't a strategy that is always the best. Consequently, a detailed analysis of the suggested approach is required, taking into account the benefits and drawbacks from the standpoints of fault clearing, power system planning, and operational factors. In the context of HVDC transmission, the authors hope that their research will spark and start conversations about circuit breaker allocation strategies., (© 2024. The Author(s).)

Drug-coated balloons (DCB) are increasingly utilized in percutaneous coronary intervention (PCI), but their effectiveness in coronary artery disease (CAD) needs further exploration. This study investigates the efficacy and safety of a DCB-based strategy for de novo left anterior descending artery (LAD) disease. Patients with de novo LAD lesions treated with DCB alone or combined with drug-eluting stents (DES) and were retrospectively enrolled from 2010 to 2023 (n = 268). The comparator group consisted of patients treated with second-generation DES from a Korean multicenter registry (n = 4,147). The primary endpoint was three-year major adverse cardiovascular events (MACE), including cardiac death, myocardial infarction, target vessel revascularization, target lesion thrombosis, and major bleeding. In the DCB-based group (n = 268), 218 (81.3%) received DCB-only, while 50 (18.7%) underwent a hybrid approach. After propensity score-matching of 243 paired subjects, baseline characteristics were balanced. The DCB-based PCI reduced overall stent burden by 86.7% and significantly lowered the risk of MACE at three years compared to DES-only PCI (4.5% vs. 7.6%, HR 0.50, 95% CI 0.28-0.90; p = 0.020). The most significant reduction was in major bleeding. The DCB-based approach offers an alternative to DES-only strategy for LAD PCI by reducing three-year MACE risk, supporting its use in treating de novo CAD., (© 2024. The Author(s).)

Predicting major adverse cardiovascular events (MACE) is crucial due to its high readmission rate and severe sequelae. Current risk scoring model of MACE are based on a few features of a patient status at a single time point. We developed a self-attention-based model to predict MACE within 3 years from time series data utilizing numerous features in electronic medical records (EMRs). In addition, we demonstrated transfer learning for hospitals with insufficient data through code mapping and feature selection by the calculated importance using Xgboost. We established operational definitions and categories for diagnoses, medications, and laboratory tests to streamline scattered codes, enhancing clinical interpretability across hospitals. This resulted in reduced feature size and improved data quality for transfer learning. The pre-trained model demonstrated an increase in AUROC after transfer learning, from 0.564 to 0.821. Furthermore, to validate the effectiveness of the predicted scores, we analyzed the data using traditional survival analysis, which confirmed an elevated hazard ratio for a group with high scores., (© 2024. The Author(s).)

The heterogeneity of Parkinson's disease (PD) presents considerable challenges for accurate diagnosis, particularly during early-stage disease, when the symptoms may be extremely subtle. This study aimed to assess the accuracy of a convolutional neural network (CNN) technique based on the 6-min walk test (6MWT) measured using wearable sensors to distinguish patients with early-stage PD (n = 78) from healthy controls (n = 50). The participants wore six sensors, and performed the 6MWT. The time-series data were converted into new images. The results revealed that the gyroscopic vertical component of the lumbar spine displayed the highest classification accuracy of 83.5%, followed by those of the thoracic spine (83.1%) and right thigh (79.5%) segment. These findings suggest that the 6MWT and CNN models may facilitate earlier diagnosis and monitoring of PD symptoms, enabling clinicians to provide timely treatment during the critical transition from normal to pathologic gait patterns., (© 2024. The Author(s).)

Pure laparoscopic donor hepatectomy (PLDH) has become a standard practice for living donor liver transplantation in expert centers. Accurate understanding of biliary structures is crucial during PLDH to minimize the risk of complications. This study aims to develop a deep learning-based segmentation model for real-time identification of biliary structures, assisting surgeons in determining the optimal transection site during PLDH. A single-institution retrospective feasibility analysis was conducted on 30 intraoperative videos of PLDH. All videos were selected for their use of the indocyanine green near-infrared fluorescence technique to identify biliary structure. From the analysis, 10 representative frames were extracted from each video specifically during the bile duct division phase, resulting in 300 frames. These frames underwent pixel-wise annotation to identify biliary structures and the transection site. A segmentation task was then performed using a DeepLabV3+ algorithm, equipped with a ResNet50 encoder, focusing on the bile duct (BD) and anterior wall (AW) for transection. The model's performance was evaluated using the dice similarity coefficient (DSC). The model predicted biliary structures with a mean DSC of 0.728 ± 0.01 for BD and 0.429 ± 0.06 for AW. Inference was performed at a speed of 15.3 frames per second, demonstrating the feasibility of real-time recognition of anatomical structures during surgery. The deep learning-based semantic segmentation model exhibited promising performance in identifying biliary structures during PLDH. Future studies should focus on validating the clinical utility and generalizability of the model and comparing its efficacy with current gold standard practices to better evaluate its potential clinical applications., (© 2024. The Author(s).)

Following an injury, the liver embarks on a process that drives the accumulation and reformation of the extracellular matrix, leading to hepatic fibrosis. Type I interferons (IFNs), including IFN-α and IFN-β, play a crucial role in averting chronic liver injury through the activation of IFN-stimulated genes (ISGs), which are instrumental in sculpting adaptive immunity. The role of 2'-5'-oligoadenylate synthase-like protein 1 (OASL1), an antiviral ISG, in the context of liver fibrosis remains to be elucidated. To elicit liver fibrosis, a diet containing 0.1% diethoxycarbonyl-1,4-dihydrocollidine (DDC) and carbon tetrachloride (CCl 4 ) were employed to induce cholestatic- and hepatotoxin-mediated liver fibrosis, respectively. Histological analyses of both models revealed that OASL1 -/- mice exhibited reduced liver damage and, consequently, expressed lower levels of fibrotic mediators, notably α-smooth muscle actin. OASL1 -/- mice demonstrated significantly elevated IFN-α and IFN-β mRNA levels, regulated by the IFN regulatory factor 7 (IRF7). Additionally, OASL1 -/- ameliorated chronic liver fibrosis through the modulation of nuclear factor-κB (NF-κB) signaling. The effect of OASL1 on type I IFN production in acute liver damage was further explored and OASL1 -/- mice consistently showed lower alanine transaminase levels and pro-inflammatory cytokines, but IFN-α and IFN-β mRNA levels were upregulated, leading to amelioration of acute liver injury. Additionally, the study discovered that F4/80-positive cells were observed more frequently in OASL1 -/- CCl 4 acutely treated mice. This implies that there is a significant synergy in the function of macrophages and OASL1 deficiency. These results demonstrate that in instances of liver injury, OASL1 inhibits the production of type I IFN by modulating the NF-κB signaling pathway, thereby worsening disease., (© 2024. The Author(s).)

Academic achievement is a critical measure of intellectual ability, prompting extensive research into cognitive tasks as potential predictors. Neuroimaging technologies, such as functional near-infrared spectroscopy (fNIRS), offer insights into brain hemodynamics, allowing understanding of the link between cognitive performance and academic achievement. Herein, we explored the association between cognitive tasks and academic achievement by analyzing prefrontal fNIRS signals. A novel quantum annealer (QA) feature selection algorithm was applied to fNIRS data to identify cognitive tasks correlated with CSAT scores. Twelve features (signal mean, median, variance, peak, number of peaks, sum of peaks, range, minimum, kurtosis, skewness, standard deviation, and root mean square) were extracted from fNIRS signals at two time windows (10- and 60-s) to compare results from various feature variable conditions. The feature selection results from the QA-based and XGBoost regressor algorithms were compared to validate the former's performance. In a two-step validation process using multiple linear regression models, model fitness (adjusted R 2 ) and model prediction error (RMSE) values were calculated. The quantum annealer demonstrated comparable performance to classical machine learning models, and specific cognitive tasks, including verbal fluency, recognition, and the Corsi block tapping task, were correlated with academic achievement. Group analyses revealed stronger associations between Tower of London and N-back tasks with higher CSAT scores. Quantum annealing algorithms have significant potential in feature selection using fNIRS data, and represents a novel research approach. Future studies should explore predictors of academic achievement and cognitive ability., (© 2024. The Author(s).)

Loop diuretics are prevailing drugs to manage fluid overload in heart failure. However, adjusting to loop diuretic doses is strenuous due to the lack of a diuretic guideline. Accordingly, we developed a novel clinician decision support system for adjusting loop diuretics dosage with a Long Short-Term Memory (LSTM) algorithm using time-series EMRs. Weight measurements were used as the target to estimate fluid loss during diuretic therapy. We designed the TSFD-LSTM, a bi-directional LSTM model with an attention mechanism, to forecast weight change 48 h after heart failure patients were injected with loop diuretics. The model utilized 65 variables, including disease conditions, concurrent medications, laboratory results, vital signs, and physical measurements from EMRs. The framework processed four sequences simultaneously as inputs. An ablation study on attention mechanisms and a comparison with the transformer model as a baseline were conducted. The TSFD-LSTM outperformed the other models, achieving 85% predictive accuracy with MAE and MSE values of 0.56 and 1.45, respectively. Thus, the TSFD-LSTM model can aid in personalized loop diuretic treatment and prevent adverse drug events, contributing to improved healthcare efficacy for heart failure patients., (© 2024. The Author(s).)

The Ferromagnetic Resonance (FMR) phenomenon, marked by the selective absorption of microwave radiation by magnetic materials in the presence of a magnetic field, plays a pivotal role in the development of radar absorbing materials, high speed magnetic storage, and magnetic sensors. This process is integral for technologies requiring precise control over microwave absorption frequencies. We explored how variations in resonance fields can be effectively modulated by adjusting both the shape and stress anisotropies of magnetic materials on a flexible substrate. Utilizing polyethylene-naphthalate (PEN) as the substrate and Permalloy (Ni 79 Fe 21 , noted for its positive magnetostriction coefficient) as the magnetic component, we demonstrated that modifications in the aspect ratio and bending repetitions can significantly alter the resonance field. The results, consistent with Kittel's equation and the predictions of a uniaxial magnetic anisotropy model, underscore the potential for flexible substrates in enhancing the sensitivity and versatility of RF-based magnetic devices., (© 2024. The Author(s).)

We explored the distinctive behavior of coherent and dissipative photon-magnon coupling (PMC) in dual hybrid resonators, each incorporating an Inverted Split-Ring Resonator (ISRR) paired with a Yttrium Iron Garnet (YIG) film, positioned in close proximity but with varying relative split-gap orientations. These orientations led to notable shifts in the dispersion spectra, characterized by level repulsion and attraction, signaling coherent and dissipative coupling, respectively, in single ISRR/YIG hybrids at certain orientations. Through analytical modeling, we determined that the observed shifts in coupling types are primarily due to the effect of photon-photon (ISRR-ISRR) interactions altering the phase difference between the coupled ISRR and magnon modes. Our findings highlight that precise manipulation of the relative split-gap orientations in the ISRR resonators enables controlled coherent and dissipative coupling within planar PMC systems. This capability opens new avenues for applications in quantum information technologies and quantum materials., (© 2024. The Author(s).)

Speckle contrast optical spectroscopy (SCOS) is an emerging camera-based technique that can measure human cerebral blood flow (CBF) with high signal-to-noise ratio (SNR). At low photon flux levels typically encountered in human CBF measurements, camera noise and nonidealities could significantly impact SCOS measurement SNR and accuracy. Thus, a guide for characterizing, selecting, and optimizing a camera for SCOS measurements is crucial for the development of next-generation optical devices for monitoring human CBF and brain function. Here, we provide such a guide and illustrate it by evaluating three commercially available complementary metal-oxide-semiconductor cameras, considering a variety of factors including linearity, read noise, and quantization distortion. We show that some cameras that are well-suited for general intensity imaging could be challenged in accurately quantifying spatial contrast for SCOS. We then determine the optimal operating parameters for the preferred camera among the three and demonstrate measurement of human CBF with this selected low-cost camera. This work establishes a guideline for characterizing and selecting cameras as well as for determining optimal parameters for SCOS systems., (© 2024. The Author(s).)

This study developed a new convolutional neural network model to detect and classify gastric lesions as malignant, premalignant, and benign. We used 10,181 white-light endoscopy images from 2606 patients in an 8:1:1 ratio. Lesions were categorized as early gastric cancer (EGC), advanced gastric cancer (AGC), gastric dysplasia, benign gastric ulcer (BGU), benign polyp, and benign erosion. We assessed the lesion detection and classification model using six-class, cancer versus non-cancer, and neoplasm versus non-neoplasm categories, as well as T-stage estimation in cancer lesions (T1, T2-T4). The lesion detection rate was 95.22% (219/230 patients) on a per-patient basis: 100% for EGC, 97.22% for AGC, 96.49% for dysplasia, 75.00% for BGU, 97.22% for benign polyps, and 80.49% for benign erosion. The six-class category exhibited an accuracy of 73.43%, sensitivity of 80.90%, specificity of 83.32%, positive predictive value (PPV) of 73.68%, and negative predictive value (NPV) of 88.53%. The sensitivity and NPV were 78.62% and 88.57% for the cancer versus non-cancer category, and 83.26% and 89.80% for the neoplasm versus non-neoplasm category, respectively. The T stage estimation model achieved an accuracy of 85.17%, sensitivity of 88.68%, specificity of 79.81%, PPV of 87.04%, and NPV of 82.18%. The novel CNN-based model remarkably detected and classified malignant, premalignant, and benign gastric lesions and accurately estimated gastric cancer T-stages., (© 2024. The Author(s).)

Full-scale drilling for shale gas has been deepening, and the horizontal definitions have been increasing for drilling efficiency. Pressures and bending stresses are generated in the joints of gas-cored pipes, which seriously affect their durability. Premium casing connections are primarily forced at the interfaces of two parts, so the design of the threads is crucial, and the choice of optimal parameters is precisely related to their resistance to stresses. This article proposes a novel premium connection design, and its performance is validated through simulations to demonstrate good noise, vibration, and harshness (NVH) and durability performance. A parametric study is especially performed with the change of lower corner radius to observe maximum stress changes of the system and it is advised that a parameter be optimized. This study demonstrates that it is possible to design a premium connection capable of reducing the stress concentrated on the stab flank contact portion when drilling deep gas wells in response to parameter changes., (© 2024. The Author(s).)

There have been over 769 million cases of COVID-19, and up to 50% of infected individuals are asymptomatic. The purpose of this study aimed to assess the use of a clinical-grade physiological wearable monitoring system, ANNE One, to develop an artificial intelligence algorithm for (1) cough detection and (2) early detection of COVID-19, through the retrospective analysis of prospectively collected physiological data from longitudinal wear of ANNE sensors in a multicenter single arm study of subjects at high risk for COVID-19 due to occupational or home exposures. The study employed a two-fold approach: cough detection algorithm development and COVID-19 detection algorithm development. For cough detection, healthy individuals wore an ANNE One chest sensor during scripted activity. The final performance of the algorithm achieved an F-1 score of 83.3% in twenty-seven healthy subjects during biomarker validation. In the COVID-19 detection algorithm, individuals at high-risk for developing COVID-19 because of recent exposures received ANNE One sensors and completed daily symptom surveys. An algorithm analyzing vital parameters (heart rate, respiratory rate, cough count, etc.) for early COVID-19 detection was developed. The COVID-19 detection algorithm exhibited a sensitivity of 0.47 and specificity of 0.72 for detecting COVID-19 in 325 individuals with recent exposures. Participants demonstrated high adherence (≥ 4 days of wear per week). ANNE One shows promise for detection of COVID-19. Inclusion of respiratory biomarkers (e.g., cough count) enhanced the algorithm's predictive ability. These findings highlight the potential value of wearable devices in early disease detection and monitoring., (© 2024. The Author(s).)

The aim of our study was to assess the performance of content-based image retrieval (CBIR) for similar chest computed tomography (CT) in obstructive lung disease. This retrospective study included patients with obstructive lung disease who underwent volumetric chest CT scans. The CBIR database included 600 chest CT scans from 541 patients. To assess the system performance, follow-up chest CT scans of 50 patients were evaluated as query cases, which showed the stability of the CT findings between baseline and follow-up chest CT, as confirmed by thoracic radiologists. The CBIR system retrieved the top five similar CT scans for each query case from the database by quantifying and comparing emphysema extent and size, airway wall thickness, and peripheral pulmonary vasculatures in descending order from the database. The rates of retrieval of the same pairs of query CT scans in the top 1-5 retrievals were assessed. Two expert chest radiologists evaluated the visual similarities between the query and retrieved CT scans using a five-point scale grading system. The rates of retrieving the same pairs of query CTs were 60.0% (30/50) and 68.0% (34/50) for top-three and top-five retrievals. Radiologists rated 64.8% (95% confidence interval 58.8-70.4) of the retrieved CT scans with a visual similarity score of four or five and at least one case scored five points in 74% (74/100) of all query cases. The proposed CBIR system for obstructive lung disease integrating quantitative CT measures demonstrated potential for retrieving chest CT scans with similar imaging phenotypes. Further refinement and validation in this field would be valuable., (© 2024. The Author(s).)

Task conditions significantly impact human motor control. We investigated how task type, difficulty, and constraints influence the kinematics of goal-directed arm reaching. Non-disabled young adults performed two distinct goal-directed arm reaching tasks: pointing and picking up an object with chopsticks. These tasks were carried out under various conditions, including constrained and unconstrained elbow extension and two different task difficulties. We collected kinematic data using a 3-D motion capture system and analyzed the effects of different task conditions on kinematic variables using linear mixed-effects regression analysis. Our findings revealed statistically significant differences in kinematics between the two tasks. Arm reaching during the picking-up task was slower and exhibited jerkier movements compared to the pointing task. Additionally, when arm reaching was performed with constrained elbow extension, it led to slower and jerkier movements, with an increased involvement of trunk movements compared to the unconstrained condition. These findings show that complex manipulative motor tasks requiring higher hand dexterity necessitate feedback-based control of arm reaching, but simple pointing tasks requiring less hand dexterity do not. In conclusion, our study sheds light on the influence of task conditions on goal-directed arm reaching kinematics and provides valuable insights into the motor control strategies involved in different tasks., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Many polar organisms produce antifreeze proteins (AFPs) and ice-binding proteins (IBPs) to protect themselves from ice formation. As IBPs protect cells and organisms, the potential of IBPs as natural or biological cryoprotective agents (CPAs) for the cryopreservation of animal cells, such as oocytes and sperm, has been explored to increase the recovery rate after freezing-thawing. However, only a few IBPs have shown success in cryopreservation, possibly because of the presence of protein denaturants, such as dimethyl sulfoxide, alcohols, or ethylene glycol, in freezing buffer conditions, rendering the IBPs inactive. Therefore, we investigated the thermal and chemical stability of FfIBP isolated from Antarctic bacteria to assess its suitability as a protein-based impermeable cryoprotectant. A molecular dynamics (MD) simulation identified and generated stability-enhanced mutants (FfIBP_CC1). The results indicated that FfIBP_CC1 displayed enhanced resistance to denaturation at elevated temperatures and chemical concentrations, compared to wildtype FfIBP, and was functional in known CPAs while retaining ice-binding properties. Given that FfIBP shares an overall structure similar to DUF3494 IBPs, which are recognized as the most widespread IBP family, these findings provide important structural information on thermal and chemical stability, which could potentially be applied to other DUF3494 IBPs for future protein engineering., (© 2024. The Author(s).)

Amlexanox is an anti-inflammatory and anti-allergic agent used clinically for the treatment of aphthous ulcers, allergic rhinitis, and asthma. Recent studies have demonstrated that amlexanox, a selective inhibitor of IkB kinase epsilon (IKKε) and TANK-binding kinase 1 (TBK1), suppresses a range of diseases or inflammatory conditions, such as obesity-related metabolic dysfunction and type 2 diabetes. However, the effects of amlexanox on neuroinflammatory responses to amlexanox have not yet been comprehensively studied. In this study, we investigated the novel therapeutic effect of amlexanox on LPS-induced neuroinflammation in vivo, and intraperitoneal injection of amlexanox markedly reduced LPS-induced IKKε levels, proinflammatory cytokines, and microglial activation, as evidenced by ionized calcium-binding adapter molecule 1 (Iba1) immunostaining. Furthermore, amlexanox significantly reduced proinflammatory cytokines and chemokines in LPS-induced bone marrow-derived macrophages (BMDM), murine BV2, and human HMC3 microglial cells. This data provided considerable evidence that amlexanox can be used as a preventive and curative therapy for neuroinflammatory and neurodegenerative diseases. In terms of mechanism aspects, our results demonstrated that the anti-inflammatory action of amlexanox in BV2 microglial cells was through the downregulation of NF-κB and STAT3 signaling pathways. In addition, the combination of amlexanox and SPI (a STAT3 selective inhibitor) showed high efficiency in inhibiting the production of neurotoxic and pro-inflammatory mediators. Overall, our data provide rational insights into the mechanisms of amlexanox as a potential therapeutic strategy for neuroinflammation-related diseases., (© 2024. The Author(s).)

The triglyceride glucose (TyG) index was suggested as a novel reliable surrogate marker for insulin resistance and related cardiovascular-metabolic diseases. We aimed to evaluate the association between the TyG index and environmental exposure to lead (Pb), mercury (Hg), and cadmium (Cd). A total of 9645 adults who enrolled in the Korea National Health and Nutrition Examination Survey in 2005, 2008-2013, and 2016 were included. Fasting plasma glucose and triglyceride levels were used to calculate the TyG index. Multivariate logistic regression model was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). We noted an increasing trend in the TyG index with increment of blood Pb and Cd concentrations. Participants in the highest quartile of blood Pb and Cd concentrations had higher TyG index values than those in the lowest quartile, with ORs (95% CIs) of 1.32 (1.07-1.63) and 1.29 (1.04-1.59) for Pb and Cd, respectively. Strong associations between blood Pb and Cd concentrations and the TyG index were found in men. Blood Hg concentrations did not show a significant association with the TyG index. Our study suggests that public health strategies for cardiovascular-metabolic disorder prevention should be directed toward individuals exposed to priority heavy metals., (© 2024. The Author(s).)

Linear gratings polarizers provide remarkable potential to customize the polarization properties and tailor device functionality via dimensional tuning of configurations. Here, we extensively investigate the polarization properties of single- and double-layer linear grating, mainly focusing on self-aligned bilayer linear grating (SABLG), serving as a wire grid polarizer in the mid-wavelength infrared (MWIR) region. Computational analyses revealed the polarization properties of SABLG, highlighting enhancement in TM transmission and reduction in TE transmission compared to single-layer linear gratings (SLG) due to optical cavity effects. As a result, the extinction ratio is enhanced by approximately 2724-fold in wavelength 3-6 μm. Furthermore, integrating the specially designed SABLG with an MWIR InAs/GaSb Type-II Superlattice (T2SL) photodetector yields a significantly enhanced spectral responsivity. The TM-spectral responsivity of SABLG is enhanced by around twofold than the bare device. The simulation methodology and analytical analysis presented herein provide a versatile route for designing optimized polarimetric structures integrated into infrared imaging devices, offering superior capabilities to resolve linear polarization signatures., (© 2024. The Author(s).)

In this paper, we propose a method for predicting epileptic seizures using a pre-trained model utilizing supervised contrastive learning and a hybrid model combining residual networks (ResNet) and long short-term memory (LSTM). The proposed training approach encompasses three key phases: pre-processing, pre-training as a pretext task, and training as a downstream task. In the pre-processing phase, the data is transformed into a spectrogram image using short time Fourier transform (STFT), which extracts both time and frequency information. This step compensates for the inherent complexity and irregularity of electroencephalography (EEG) data, which often hampers effective data analysis. During the pre-training phase, augmented data is generated from the original dataset using techniques such as band-stop filtering and temporal cutout. Subsequently, a ResNet model is pre-trained alongside a supervised contrastive loss model, learning the representation of the spectrogram image. In the training phase, a hybrid model is constructed by combining ResNet, initialized with weight values from the pre-trained model, and LSTM. This hybrid model extracts image features and time information to enhance prediction accuracy. The proposed method's effectiveness is validated using datasets from CHB-MIT and Seoul National University Hospital (SNUH). The method's generalization ability is confirmed through Leave-one-out cross-validation. From the experimental results measuring accuracy, sensitivity, and false positive rate (FPR), CHB-MIT was 91.90%, 89.64%, 0.058 and SNUH was 83.37%, 79.89%, and 0.131. The experimental results demonstrate that the proposed method outperforms the conventional methods., (© 2023. The Author(s).)

Neuromyelitis optica (NMO) is an autoimmune inflammatory disease that primarily affects the optic nerve and spinal cord within the central nervous system (CNS). Acute astrocyte injury caused by autoantibodies against aquaporin 4 (NMO-IgG) is a well-established key factor in the pathogenesis, ultimately leading to neuronal damage and patient disability. In addition to these humoral immune processes, numerous innate immune cells were found in the acute lesions of NMO patients. However, the origin and function of these innate immune cells remain unclear in NMO pathogenesis. Therefore, this study aims to analyze the origin and functions of these innate immune cells in an NMO-like mouse model and evaluate their role in the pathophysiology of NMO. The expression of Tmem119 on Iba1 + cells in brain tissue disappeared immediately after the injection of NMO-IgG + human complement mixture, while the expression of P2ry12 remained well-maintained at 1 day after injection. Based on these observations, it was demonstrated that monocytes infiltrate the brain during the early stages of the pathological process and are closely associated with the inflammatory response through the expression of the proinflammatory cytokine IL-1β. Understanding the variations in the expression patterns of P2ry12, Tmem119, and other markers could be helpful in distinguishing between these cell types and further analyzing their functions. Therefore, this research may contribute to a better understanding of the mechanisms and potential treatments for NMO., (© 2024. The Author(s).)

Properly handling animals and understanding their habits are crucial to establish a society where humans and animals coexist. Thus, identifying individual animals, including their possessions, and adequately managing each animal is necessary. Although several conventional identification methods exist, such as the use of ear punch, tattoos, and radio frequency (RF) chips, they require several processes and external apparatus. In this study, we proposed a new biotagging method using a microneedle array for animal identification. Our approach uses dissolvable microneedle arrays as a single patch to deliver dyes directly into the skin layer. Additionally, we developed a new fabrication method for customised female moulds to realise microneedle array patches (MAPs) with patterns of different characters and number. The characteristics and feasibility of the patterned MAPs were confirmed through basic evaluations and animal experiments. Moreover, we confirmed that patterns formed from biotagging using the developed patterned MAPs lasted over one month with clear readability. Finally, we confirmed that our patterned MAPs successfully realised biotagging on rat skin with the designated patterns including characters and number patterns. The proposed method is expected to enable minimally invasive tagging without external equipment or complex processes. In addition, the developed method could be used to embed various tags into the skin of animals and humans in the future., (© 2023. The Author(s).)

Natural products and herbal medicine have been widely used in drug discovery for treating infectious diseases. Recent outbreak of COVID-19 requires various therapeutic strategies. Here, we used YSK-A, a mixture of three herbal components Boswellia serrata, Commiphora myrrha, and propolis, to evaluate potential antiviral activity against SARS-CoV-2. We showed that YSK-A inhibited SARS-CoV-2 propagation with an IC 50 values of 12.5 µg/ml and 15.42 µg/ml in Vero E6 and Calu-3 cells, respectively. Using transcriptome analysis, we further demonstrated that YSK-A modulated various host gene expressions in Calu-3 cells. Among these, we selected 9 antiviral- or immune-related host genes for further study. By siRNA-mediated knockdown experiment, we verified that MUC5AC, LIF, CEACAM1, and GDF15 host genes were involved in antiviral activity of YSK-A. Therefore, silencing of these genes nullified YSK-A-mediated inhibition of SARS-CoV-2 propagation. These data indicate that YSK-A displays an anti-SARS-CoV-2 activity by targeting multiple antiviral genes. Although the exact antiviral mechanism of each constituent has not been verified yet, our data indicate that YSK-A has an immunomodulatory effect on SARS-CoV-2 and thus it may represent a novel natural product-derived therapeutic agent for treating COVID-19., (© 2023. The Author(s).)

To assess the prevalence and abundance of antibiotic resistance genes in human and livestock gut microbiomes, 87 humans (healthy individuals and patients with Clostridioides difficile infection (CDI)) and 108 livestock (swine, cattle, and chickens) were enrolled. Gut microbiomes and fluoroquinolone-resistant Escherichia coli isolates were sequenced, and mobile genetic elements adjacent to the β-lactamase (bla) and transferable quinolone resistance (qnr) genes were compared using metagenomic contigs. Each group of humans and livestock exhibited distinctive microbiota and resistome compositions in the gut. Concerning the resistome of bla and qnr, the prevalence rates between chickens and patients with CDI were the most similar (R 2  = 0.46); bla TEM , bla OXA , bla CTX-M , and qnrS were highly prevalent in both groups. According to genomic and phylogenetic analyses, bla CTX-M and bla OXA expressed lineage specificity to either humans or livestock, while qnrS and bla TEM displayed a shared lineage between humans and livestock. A qnrS1 mobilome comprising five genes, including two recombinases, a transposase, and a plasmid gene, is commonly found in human and chicken gut microbiomes. Humans and chickens showed the most similar gut resistomes to β-lactams and quinolones. QnrS and bla TEM displayed especially strong co-occurrence between the guts of humans and livestock., (© 2023. The Author(s).)

Birefringence, an inherent characteristic of optically anisotropic materials, is widely utilized in various imaging applications ranging from material characterizations to clinical diagnosis. Polarized light microscopy enables high-resolution, high-contrast imaging of optically anisotropic specimens, but it is associated with mechanical rotations of polarizer/analyzer and relatively complex optical designs. Here, we present a form of lens-less polarization-sensitive microscopy capable of complex and birefringence imaging of transparent objects without an optical lens and any moving parts. Our method exploits an optical mask-modulated polarization image sensor and single-input-state LED illumination design to obtain complex and birefringence images of the object via ptychographic phase retrieval. Using a camera with a pixel size of 3.45 μm, the method achieves birefringence imaging with a half-pitch resolution of 2.46 μm over a 59.74 mm 2  field-of-view, which corresponds to a space-bandwidth product of 9.9 megapixels. We demonstrate the high-resolution, large-area, phase and birefringence imaging capability of our method by presenting the phase and birefringence images of various anisotropic objects, including a monosodium urate crystal, and excised mouse eye and heart tissues., (© 2023. The Author(s).)