163559 research outputs found
Sort by
Novel FRET-based Immunological Synapse Biosensor for the Prediction of Chimeric Antigen Receptor-T Cell Function
No full textChimeric antigen receptor (CAR)-T cell therapy has revolutionized cancer treatment. CARs are activated at the immunological synapse (IS) when their single-chain variable fragment (scFv) domain engages with an antigen, allowing them to directly eliminate cancer cells. Here, an innovative IS biosensor based on fluorescence resonance energy transfer (FRET) for the real-time assessment of CAR-IS architecture and signaling competence is presented. Using this biosensor, scFv variants for mesothelin-targeting CARs and identified as a novel scFv with enhanced CAR-T cell functionality despite its lower affinity than the original screened. The original CAR promoted internalization and trogocytosis, disrupting stable IS formation and impairing functionality are further observed. These findings emphasize the importance of enhancing IS quality rather than maximizing scFv affinity for superior CAR-T cell responses. Therefore, the FRET-based IS biosensor is a powerful tool for predicting CAR-T cell function, enabling the efficient engineering of next-generation CARs with enhanced antitumor potency.Y
Analysis of the effect of fentanyl dosage used in patient-controlled analgesia for pain management after oral cancer surgery: a retrospective observational study
No full textBackground: Postoperative pain management is challenging in patients with oral cancer, especially those undergoing reconstructive surgery. Patient-controlled analgesia (PCA) is widely used, and fentanyl (FTN) concentration adjustments may improve pain control. This study aimed to evaluate the effects of FTN PCA concentration and reconstructive surgery on postoperative pain in patients with oral cancer. Methods: This retrospective observational study analyzed 140 patients with oral cancer who underwent surgery under general anesthesia. Patients were categorized based on FTN PCA dosage (FTN 700 mcg and ketorolac 150 mg vs. FTN 1400 mcg and ketorolac 150 mg). Pain was assessed using the visual analog scale (VAS) at multiple time points postoperatively (0, 12, 24, 36, 48, 60, and 72 h). PCA usage patterns, including demand count, delivery count, and delivery/demand ratios, were compared across subgroups. Missing data were imputed using linear interpolation. Results: PCA usage and pain control were evaluated between the FTN 700 mcg (N = 40) and 1400 mcg (N = 100) groups, stratified by reconstruction status. Demographic characteristics showed no significant difference. In the reconstructive surgery subgroup, patients in the FTN 1400 mcg group showed lower PCA refill counts (1.45 +/- 0.69 vs. 1.61 +/- 0.58) and fewer delivery counts (17.1 +/- 21.3 vs. 25.1 +/- 28.5) compared to those in the FTN 700 mcg group, achieving similar or superior pain control with fewer interventions. Similarly, patients without reconstructive surgery in the FTN 1400 mcg group demonstrated lower PCA refill counts, shorter PCA usage times, and fewer delivery counts. VAS scores decreased consistently over time across all groups but remained higher in the reconstruction groups. Logistic regression analysis revealed that patients with reconstructive surgery in the FTN 1400 mcg group were more likely to achieve a VAS score of <= 3.0 at 72 h postoperatively (P = 0.022). These findings indicate FTN 1400 mcg's superiority in managing postoperative pain. Conclusion: Comparing FTN PCA dosages, 1400 mcg demonstrated superior pain control to 700 mcg in patients undergoing oral cancer surgery, particularly those who underwent reconstructive surgery. This finding underscores the importance of optimizing FTN dosages to enhance postoperative pain management, reduce PCA-related demands, and achieve better patient outcomes.N
Graphene Quantum Dots Attenuate TDP-43 Proteinopathy in Amyotrophic Lateral Sclerosis
No full textAberrant phase separation- and stress granule (SG)-mediated cytosolic aggregation of TDP-43 in motor neurons is the hallmark of amyotrophic lateral sclerosis (ALS). In this study, we found that graphene quantum dots (GQDs) potentially modulate TDP-43 aggregation during SG dynamics and phase separation. The intrinsically disordered region in the C-terminus of TDP-43 exhibited amyloid fibril formation; however, GQDs inhibited the formation of amyloid fibrils through direct intermolecular interactions with TDP-43. These effects were accompanied by attenuation of the ALS phenotype in animal models. Additionally, GQDs delayed the onset and survival of TDP-43 transgenic mouse models by enhancing motor neuron survival, reducing glial activation, and reducing the cytosolic aggregation of TDP-43 in motor neurons. In this research, we demonstrated the efficacy of GQDs on the SG-mediated aggregation of TDP-43 and the binding property of GQDs with TDP-43. Additionally, we demonstrated the clinical feasibility of GQDs using several animal models and other types of ALS caused by FUS and C9orf72. Therefore, GQDs could offer a new therapeutic approach for proteinopathy-associated ALS.Y
Hypotaxy of wafer-scale single-crystal transition metal dichalcogenides
No full textTwo-dimensional (2D) semiconductors, particularly transition metal dichalcogenides (TMDs), are promising for advanced electronics beyond silicon1, 2-3. Traditionally, TMDs are epitaxially grown on crystalline substrates by chemical vapour deposition. However, this approach requires post-growth transfer to target substrates, which makes controlling thickness and scalability difficult. Here we introduce a method called hypotaxy ('hypo' meaning downward and 'taxy' meaning arrangement), which enables wafer-scale single-crystal TMD growth directly on various substrates, including amorphous and lattice-mismatched substrates, while preserving crystalline alignment with an overlying 2D template. By sulfurizing or selenizing a pre-deposited metal film under graphene, aligned TMD nuclei form, coalescing into a single-crystal film as graphene is removed. This method achieves precise MoS2 thickness control from monolayer to hundreds of layers on diverse substrates, producing 4-inch single-crystal MoS2 with high thermal conductivity (about 120 W m-1 K-1) and mobility (around 87 cm2 V-1 s-1). Furthermore, nanopores created in graphene using oxygen plasma treatment allow MoS2 growth at a lower temperature of 400 degrees C, compatible with back-end-of-line processes. This hypotaxy approach extends to other TMDs, such as MoSe2, WS2 and WSe2, offering a solution to substrate limitations in conventional epitaxy and enabling wafer-scale TMDs for monolithic three-dimensional integration.N
An explainable and accurate transformer-based deep learning model for wheeze classification utilizing real-world pediatric data
No full textAuscultation is a method that involves listening to sounds from the patient's body, mainly using a stethoscope, to diagnose diseases. The stethoscope allows for non-invasive, real-time diagnosis, and it is ideal for diagnosing respiratory diseases and first aid. However, accurate interpretation of respiratory sounds using a stethoscope is a subjective process that requires considerable expertise from clinicians. To overcome the shortcomings of existing stethoscopes, research is actively being conducted to develop an artificial intelligence deep learning model that can interpret breathing sounds recorded through electronic stethoscopes. Most recent studies in this area have focused on CNN-based respiratory sound classification models. However, such CNN models are limited in their ability to accurately interpret conditions that require longer overall length and more detailed context. Therefore, in the present work, we apply the Transformer model-based Audio Spectrogram Transformer (AST) model to our actual clinical practice data. This prospective study targeted children who visited the pediatric departments of two university hospitals in South Korea from 2019 to 2020. A pediatric pulmonologist recorded breath sounds, and a pediatric breath sound dataset was constructed through double-blind verification. We then developed a deep learning model that applied the pre-trained weights of the AST model to our data with a total of 194 wheezes and 531 other respiratory sounds. We compared the performance of the proposed model with that of a previously published CNN-based model and also conducted performance tests using previous datasets. To ensure the reliability of the proposed model, we visualized the classification process using Score-Class Activation Mapping (Score-CAM). Our model had an accuracy of 91.1%, area under the curve (AUC) of 86.6%, precision of 88.2%, recall of 76.9%, and F1-score of 82.2%. Ultimately, the proposed transformer-based model showed high accuracy in wheezing detection, and the decision-making process of the model was also verified to be reliable. The artificial intelligence deep learning model we have developed and described in this study is expected to help accurately diagnose pediatric respiratory diseases in real-world clinical practice.Y
Improving NMT Models by Retrofitting Quality Estimators into Trainable Energy Loss
No full textReinforcement learning has shown great promise in aligning language models with human preferences in a variety of text generation tasks, including machine translation. For translation tasks, rewards can easily be obtained from quality estimation (QE) models which can generate rewards for unlabeled data. Despite its usefulness, reinforcement learning cannot exploit the gradients with respect to the QE score. We propose QE-EBM, a method of employing quality estimators as trainable loss networks that can directly backpropagate to the NMT model. We examine our method on several low and high resource target languages with English as the source language. QE-EBM outperforms strong baselines such as REINFORCE and proximal policy optimization (PPO) as well as supervised fine-tuning for all target languages, especially low-resource target languages. Most notably, for English-to-Mongolian translation, our method achieves improvements of 2.5 BLEU, 7.1 COMET-KIWI, 5.3 COMET, and 6.4 XCOMET relative to the supervised baseline.N
Wealth Effects When the Cost of Effort is Money
No full textWe study the effects of the agents wealth on the agency cost
and the principals profit in the principal-agent model in which the
agents effort entails a monetary cost. We show that if the inverse of
the marginal utility function is concave in the utility function, then
an increase in the agents wealth lowers the agency cost for any
effort level, directly implying that the principal clearly benefits from
such a decrease in the agency cost. However, even if the convexity
of the marginal utility function with respect to the utility function
is assumed, as in most of the previous results, the effects of the
agent's wealth on the agency cost remain unclear in our model.
The main reason is because a rise in wealth inevitably makes the
incentive problem easier by lowering the marginal cost of effort,
reducing the agency cost whereas that convexity raises the agency
cost
Optimization of co-sputtered zinc indium tin oxide-based MOSFET-type sensor for effective NO2 gas detection
No full textThe growing demand for high-sensitivity and low-power gas sensors has driven the exploration of advanced sensing materials. In this study, we fabricated MOSFET-type gas sensors using co-sputtered zinc indium tin oxide (ZITO) films as sensing layers, with five different films containing varying ratios of indium tin oxide (ITO) and ZnO mixtures. As the Zn content increased, the agglomeration sizes within the films decreased, exhibiting amorphous-like morphology. X-ray photoelectron spectroscopy (XPS) revealed that scarce Zn content induced oxygen vacancies, while the number of hydroxy groups increased with higher Zn content. These material properties of the sensing layers significantly influenced the gas sensing characteristics. At high temperatures (∼210 ℃), the oxygen vacancy-rich sensor showed the highest gas response, whereas the hydroxy-rich sensor exhibited enhanced performance at low temperatures (∼150 ℃). The adjustment of the co-sputtering ratio influences gas response, power consumption, and response time, allowing for the fabrication of sensors optimized for specific applications by comprehensively considering various performance factors. We believe that this method can be applied to the formation of a wide range of sensing materials.N
Advancements in simulation-based nursing education: Insights from a bibliometric analysis of temporal trends
No full textBackground: Simulations are used in nursing education to create realistic clinical practice environments. With rapid changes in educational demands and the growing importance of simulation in nursing, understanding the evolution of its application will provide critical insights into how educational strategies have undergone adaptive changes over time to meet the needs of nursing students and healthcare settings. Aims: This study aimed to identify temporal trends in simulation-based nursing education, map key research themes, and examine changes in the educational landscape over time. Design: This is a bibliometric study of simulation-based nursing education. Methods: The analysis was conducted using VOSviewer. A total of 12,083 publications retrieved from PubMed, the Excerpta Medica Database, and the Cumulative Index to Nursing and Allied Health Literature were analyzed. To identify temporal shifts in simulation-based nursing education, articles were categorized into four periods based on the progression of simulation usage and technological advancements. Co-occurrence analysis was performed for each period. Results: Our analysis revealed a substantial increase in research on simulation-based nursing education after 2014, with a surge following the COVID-19 pandemic. The results show an increasing adoption of advanced techniques, such as standardized patients, in-situ simulations, and virtual reality. Core keywords, such as CPR, critical thinking, and team training, highlight the diverse applications of simulations in technical and psychological training. Temporal trends highlight significant shifts in keywords driven by technological advancements and evolving pedagogical approaches. Integrating advanced technology and realistic scenarios provides learners with immersive experiences that can substantially enhance their nursing competencies. Conclusions: This study revealed that simulation-based nursing education has evolved substantially, reflecting technological progress and changes in educational priorities. This underscores the need to integrate advanced technology with innovative simulation methods to prepare nursing students for real-world clinical challenges.N
Quality of Life in Women With Gestational Diabetes Mellitus and Treatment Satisfaction Upon Intermittently Scanned Continuous Glucose Monitoring
No full textBackground: To assess the quality of life (QoL) and treatment satisfaction with intermittently-scanned continuous glucose monitoring (isCGM) in women with gestational diabetes mellitus (GDM). Methods: This prospective observational study included 189 women with GDM who completed the Korean version of the Audit of Diabetes-Dependent Quality of Life Questionnaire (K-ADDQoL). Among them, 25 women who utilized isCGM between gestational weeks 30 and 34 completed the Korean version of the Diabetes Treatment Satisfaction Questionnaire change version (K-DTSQc) to evaluate their satisfaction with isCGM during pregnancy. Results: GDM had a negative impact on the perceived QoL in 89.4% of the women. All 19 domains of the K-ADDQoL were adversely influenced by GDM, with the most significant impact on the freedom to eat (weighted impact score, −6.98 ± 2.49, P < 0.001) and the least impact on the sex life (−0.25 ± 0.80, P = 0.008). Younger women and those treated with insulin perceived themselves as being more affected in their QoL due to GDM. Women perceived to have less effect on their QoL attributed to GDM exhibited higher ΔHbA1c one year after delivery (ΔHbA1c, 0.3 ± 0.4% vs. 0.0 ± 0.4% in less affected vs. more affected women). The utilization of isCGM improved treatment satisfaction (overall satisfaction score, 10.36 ± 9.21, P < 0.001), independent of glycemic control during pregnancy. Conclusion: Although GDM negatively affects the perceived QoL during pregnancy, attentiveness to GDM management may have a positive impact on long-term glycemic control. Moreover, employing isCGM can enhance treatment satisfaction in women with GDM.N