Search Results (31)

The incorporation of nucleoside analogs into DNA by polymerases, followed by their removal through base excision repair (BER), represents a promising strategy for cancer chemotherapy. In this study, we investigated the incorporation and cytotoxic effects of several nucleoside analogs—some of which are epigenetic reprogramming intermediates—in the U87 glioblastoma cell line. We found that two analogs, 5-hydroxymethyl-2′-deoxyuridine (5HmdU) and trifluorothymidine (TFT), are both cytotoxic and are efficiently incorporated into genomic DNA. In contrast, the 5-carboxy analogs—5-carboxy-2′-deoxyuridine (5CadU) and 5-carboxycytidine (5CadC)—showed no cytotoxicity and were not incorporated into DNA. Interestingly, 5-hydroxymethyl-2′-deoxycytidine (5HmdC) was cytotoxic but was not directly incorporated into DNA. Instead, it was deaminated into 5HmdU, which was then incorporated and likely responsible for the observed toxicity. 5HmdU is actively removed from DNA through the BER pathways. In contrast, TFT remains stably incorporated and is neither excised by BER nor does it hydrolyze into 5CadU—a known substrate for the DNA glycosylase SMUG1. We also found that N⁶-benzyladenosine (BzAdo), an inhibitor of the enzyme 2′-deoxynucleoside 5′-phosphate N-hydrolase (DNPH1), enhances the cytotoxicity of 5HmdU. However, the thymidine phosphorylase inhibitor tipiracil hydrochloride (TPI) does not increase the cytotoxic effect of TFT in U87 cells. Together, these findings highlight 5HmdU and TFT as promising chemotherapeutic agents for glioblastoma, each with distinct mechanisms of action and cellular processing. Full article

Background: There is growing interest in the potential role of manganese (Mn) in the development of Alzheimer’s Disease and related dementias (ADRD). Methods: In this nested pilot study of a ferroalloy worker cohort, we investigated the impact of chronic occupational Mn exposure on cognitive function through β-amyloid (Aβ) deposition and multi-omics profiling. We evaluated six male Mn-exposed workers (median age 63, exposure duration 31 years) and five historical controls (median age: 60 years), all of whom had undergone brain PET scans. Exposed individuals showed significantly higher Aβ deposition in exposed individuals (p < 0.05). The average annual cumulative respirable Mn was 329.23 ± 516.39 µg/m³ (geometric mean 118.59), and plasma Mn levels were significantly elevated in the exposed group (0.704 ± 0.2 ng/mL) compared to controls (0.397 ± 0.18 in controls). Results: LC-MS/MS-based pathway analyses revealed disruptions in olfactory signaling, mitochondrial fatty acid β-oxidation, biogenic amine synthesis, transmembrane transport, and choline metabolism. Simoa analysis showed notable alterations in ADRD-related plasma biomarkers. Protein microarray revealed significant differences (p < 0.05) in antibodies targeting neuronal and autoimmune proteins, including Aβ (25–35), GFAP, serotonin, NOVA1, and Siglec-1/CD169. Conclusion: These findings suggest Mn exposure is associated with neurodegenerative biomarker alterations and disrupted biological pathways relevant to cognitive decline. Full article

Background/Objectives: Monoclonal antibodies have successfully been used for a variety of indications. Many therapeutic antibodies are IgG1 and elicit effector functions as part of their mechanism of action. It is well known that aggregate levels should be controlled for therapeutic antibodies. Although there are several reports describing the impact of antibody aggregates on FcγR binding, most of these have been performed with surface plasmon resonance in an avidity-based format. What is less well known is which Fcγ receptor is most impacted by antibody aggregation and how antibody aggregates impact binding to Fcγ receptors in solution-based formats and in cell-based assays. Methods: An effector-competent IgG1 (mAb1) was forcibly degraded and fractionated by size exclusion chromatography to enrich for aggregates. The fractions were examined for FcγR binding by SPR with different formats and in solution. The fractions were also analyzed with cell-based FcγR reporter assays. Results: All Fcγ receptors displayed increased binding to enriched mAb1 aggregates in the avidity-based SPR methods and in solution, with FcγRIIa impacted the most. When examined with an antibody-down SPR format that is not usually susceptible to avidity, FcγRIIa did not show increased binding with mAb1 aggregation. Although activity for mAb1 aggregates increased slightly in an FcγRIIa cell-based reporter assay, it decreased in the FcγRIIIa reporter assay (most likely due to differences in fucosylation from the reference standard). Conclusions: Monoclonal antibody aggregation can impact FcγR binding for avidity-based binding formats. Even at low levels of antibody aggregation, FcγRII binding increases substantially. Full article

Nonlinear loads, crucial components of power system grids, pose a challenge due to harmonics injection. This work tackles this issue with a novel modified green plug–switched filter compensation scheme using fuzzy logic controllers. This innovative scheme presented in this paper utilizes dual action pulse width modulation to ensure switching functions from harmonics reduction and capacitive compensation for inrush nonlinear-type AC loads. The scheme’s multi-loop regulations and online switching effectively handle dynamic-type slow-acting inrush, motorized- and other rectifier-type nonlinear loads, enhancing the power factor, power quality at source and load buses, and reducing the total harmonics distortion at the key source and sensitive nonlinear load buses. A simulation model in the MATLAB/SIMULINK-2023b software environment demonstrates the efficiency of the proposed FACTS technique. The modulated dual mode switched filter-capacitive compensation scheme controlled by a fuzzy logic controller ensures less harmonics distortion and improved voltage stabilization. The results show that voltage, current, active power, reactive power, power factor regulation, and effective energy utilization are achievable with the designed Flexible AC Transmission System-Modulated Filter Capacitor Compensation–Switched Filter Compensator (FACTS-MFCC-SFC). The switched modulated AC green plug filter significantly improves power quality and enhances power factor in cases of inrush and nonlinear loads. Full article

Sandwich structures are engineered with continuous layers surrounding the inner lattices, which combines the advantages of the high strength of the continuous layer and the light weight of the lattice layer. They are widely employed in weight-critical energy-absorbing engineering fields such as aerospace, automobile, and robotics. However, the application of sandwich structures made of polymer matrix composites is still limited due to lack of essential performance investigation and adequate reference data. The following innovative works are accomplished in this paper: (i) Continuous long glass fiber (CGF) is employed within the continuous layer of the sandwich structure, with composite short carbon fiber/polyamide (SCF/N) applied within the lattice layer. (ii) Sandwich structures with different cell types and orientations of the lattice infills are designed and prepared by additive manufacturing. (iii) The basic mechanical properties of the sandwich structures, i.e., the bi-directional tension/compression compound performance, failure modes and mechanisms in characteristic directions, are analyzed systematically. (iv) The effects of geometric features on the three-point bending properties of L-shaped sandwich structures are investigated and compared with those of pure SCF/N structures. The results show that the bending resistance per unit weight was up to 54.3% larger than that of pure SCF/N, while the weight could be decreased by 49%, and the bending flexibility before fracture could be increased by 44%. These studies contribute fundamental research data to the application of sandwich structures prepared by fiber reinforced polymer matrix composites. Full article

Traditional camera sensors rely on human eyes for observation. However, human eyes are prone to fatigue when observing objects of different sizes for a long time in complex scenes, and human cognition is limited, which often leads to judgment errors and greatly reduces efficiency. Object recognition technology is an important technology used to judge the object’s category on a camera sensor. In order to solve this problem, a small-size object detection algorithm for special scenarios was proposed in this paper. The advantage of this algorithm is that it not only has higher precision for small-size object detection but also can ensure that the detection accuracy for each size is not lower than that of the existing algorithm. There are three main innovations in this paper, as follows: (1) A new downsampling method which could better preserve the context feature information is proposed. (2) The feature fusion network is improved to effectively combine shallow information and deep information. (3) A new network structure is proposed to effectively improve the detection accuracy of the model. From the point of view of detection accuracy, it is better than YOLOX, YOLOR, YOLOv3, scaled YOLOv5, YOLOv7-Tiny, and YOLOv8. Three authoritative public datasets are used in these experiments: (a) In the Visdron dataset (small-size objects), the map, precision, and recall ratios of DC-YOLOv8 are 2.5%, 1.9%, and 2.1% higher than those of YOLOv8s, respectively. (b) On the Tinyperson dataset (minimal-size objects), the map, precision, and recall ratios of DC-YOLOv8 are 1%, 0.2%, and 1.2% higher than those of YOLOv8s, respectively. (c) On the PASCAL VOC2007 dataset (normal-size objects), the map, precision, and recall ratios of DC-YOLOv8 are 0.5%, 0.3%, and 0.4% higher than those of YOLOv8s, respectively. Full article

A swarm of unmanned aerial vehicles (UAVs) can be used for many applications, including disaster relief, search and rescue, and establishing communication networks, due to its mobility, scalability, and robustness to failure. However, a UAV swarm’s performance is typically limited by each agent’s stored energy. Recent works have considered the usage of thermals, or vertical updrafts of warm air, to address this issue. One challenge lies in a swarm of UAVs detecting and taking advantage of these thermals. Inspired by hawks, a swarm could take advantage of thermals better than individuals due to the swarm’s distributed sensing abilities. To determine which emergent behaviors increase survival time, simulation software was created to test the behavioral models of UAV gliders around thermals. For simplicity and robustness, agents operate with limited information about other agents. The UAVs’ motion was implemented as a Boids model, replicating the behavior of flocking birds through cohesion, separation, and alignment forces. Agents equipped with a modified behavioral model exhibit dynamic flocking behavior, including relative ascension-based cohesion and relative height-based separation and alignment. The simulation results show the agents flocking to thermals and improving swarm survival. These findings present a promising method to extend the flight time of autonomous UAV swarms. Full article

Major Depression disorder (MDD) is a potentially life-threatening mental illness, however, many patients have a poor response to current treatments. Recent studies have suggested that stress- or trauma-induced oxidative stress and inflammation could be important factors involved in the development of MDD, but the mechanisms remain unclear. We showed that the glymphatic system is a recently discovered structure in the brain that may be involved in the clearance of large molecular and cell debris in extracellular space. In addition, the glymphatic system can help with the removal of reactive oxygen species (ROS) and cytokines such as IL-1β and HIF-1α. Glymphatic impairment can lead to ROS accumulation in the microenvironment, inducing cellular injury signaling and activating NLRP3 in microglia to induce inflammation and, thus, many brain diseases, including psychiatric disorders. Therefore, trauma-induced glymphatic impairment could induce oxidative stress and inflammation, and thus MDD. This paper will review recent advances with regard to stress-induced glymphatic system impairment and ROS-mediated inflammation in MDD. Full article

High-throughput mass-spectrometry-based quantitative proteomic analysis was performed using formalin-fixed, paraffin-embedded (FFPE) biopsy samples obtained before treatment from 13 patients with locally advanced rectal cancer (LARC), who were treated with concurrent chemoradiation therapy (CCRT) followed by surgery. Patients were divided into complete responder (CR) and non-complete responder (nCR) groups. Immunohistochemical (IHC) staining of 79 independent FFPE tissue samples was performed to validate the predictive ability of proteomic biomarker candidates. A total of 3637 proteins were identified, and the expression of 498 proteins was confirmed at significantly different levels (differentially expressed proteins—DEPs) between two groups. In Gene Ontology enrichment analyses, DEPs enriched in biological processes in the CR group included proteins linked to cytoskeletal organization, immune response processes, and vesicle-associated protein transport processes, whereas DEPs in the nCR group were associated with biosynthesis, transcription, and translation processes. Dual oxidase 2 (DUOX2) was selected as the most predictive biomarker in machine learning algorithm analysis. Further IHC validation ultimately confirmed DUOX2 as a potential biomarker for predicting the response of nCR to CCRT. In conclusion, this study suggests that the treatment response to RT may be affected by the pre-treatment tumor microenvironment. DUOX2 is a potential biomarker for the early prediction of nCR after CCRT. Full article

This paper presents a system, namely, the abnormal-weather monitoring and curation service (AWMC), which provides people with a better understanding of abnormal weather conditions. The service can analyze a set of multivariate weather datasets (i.e., 7 meteorological datasets from 18 cities in Korea) and show (i) which dates are mostly abnormal in a certain city, and (ii) which cities are mostly abnormal on a certain date. In particular, the dynamic graph-embedding-based anomaly detection method was employed to measure anomaly scores. We implemented the service and conducted evaluations. Regarding the results of monitoring abnormal weather, AWMC shows that the average precision was approximately 90.9%, recall was 93.2%, and F1 score was 92.1% for all the cities. Full article

Major depressive disorder (MDD) is a common and complex mental disorder, that adversely impacts an individual’s quality of life, but its diagnosis and treatment are not accurately executed and a symptom-based approach is utilized in most cases, due to the lack of precise knowledge regarding the pathophysiology. So far, the first-line treatments are still based on monoamine neurotransmitters. Even though there is a lot of progress in this field, the mechanisms seem to get more and more confusing, and the treatment is also getting more and more controversial. In this study, we try to review the broad advances of monoamine neurotransmitters in the field of MDD, and update its effects in many advanced neuroscience studies. We still propose the monoamine hypothesis but paid special attention to their effects on the new pathways for MDD, such as inflammation, oxidative stress, neurotrophins, and neurogenesis, especially in the glial cells, which have recently been found to play an important role in many neurodegenerative disorders, including MDD. In addition, we will extend the monoamine hypothesis to basic emotions; as suggested in our previous reports, the three monoamine neurotransmitters play different roles in emotions: dopamine—joy, norepinephrine—fear (anger), serotonins—disgust (sadness). Above all, this paper tries to give a full picture of the relationship between the MDD and the monoamine neurotransmitters such as DA, NE, and 5-HT, as well as their contributions to the Three Primary Color Model of Basic Emotions (joy, fear, and disgust). This is done by explaining the contribution of the monoamine from many sides for MDD, such the digestive tract, astrocytes, microglial, and others, and very briefly addressing the potential of monoamine neurotransmitters as a therapeutic approach for MDD patients and also the reasons for its limited clinical efficacy, side effects, and delayed onset of action. We hope this review might offer new pharmacological management of MDD. Full article

Objective: Recently, many emotional diseases, such as anxiety and depression, have prevailed, and it is expected that emotional disease will be the leading cause of social and economic burden in 2030. These emotional diseases may be due to certain personality traits, which could be the reasons for the development of mental illness. Personality theories have been constantly developed over the past hundreds of years, and different dimensions of personality traits corresponding to different physiological bases and emotional feelings have been proposed. However, personality may be the least studied area in psychology. Methods: In this paper, we will give a short review on the development of personality theories as well as dimensional emotional theory. Then, we will compare the similarities between the emotional dimension and personality dimension. Furthermore, we will also investigate the neural mechanisms of personality and emotions, focusing on neuromodulators for anxiety-related personality traits, in order to provide a clear relationship between different neurotransmitters and anxiety-related personality traits. Results: The results of our study suggest that the emotional dimension and personality dimension may be somewhat related, for example, the extrovert/introvert dimension of personality might be related to the hedonic dimension, which includes happiness/sadness, and the neurotic dimensions might be related to emotional arousal. In addition, our study found that personality traits are also related to basic emotions, for instance, people who are too self-centered are prone to feeling a mood of disgust or depression, while anger and fear correspond to unstable personality traits. The analysis suggested that the neural substrates of both personality and emotions might be described as follows: extroverted–joy–dopamine (DA); introverted–disgust–5-hydroxytryptamine (5-HT); unstable (neuroticism)–anger/fear–noradrenaline (NE); stable–calmness. Conclusions: The results of this study suggest that there is a correlation between personality traits and emotions, and both depend on monoamine neurotransmitters (dopamine, norepinephrine and serotonin). In addition, personality disorders can be interfered via the regulation of emotions and neurotransmitters. This paper opens up a whole new perspective for future research on personality traits and emotional diseases and has great clinical value and practical significance. Full article

Compliant bipedal robots demonstrate a potential for impact resistance and high energy efficiency through the introduction of compliant elements. However, it also adds to the difficulty of stable control of the robot. To motivate the control strategies of compliant bipedal robots, this work presents an improved control strategy for the stable and fast planar jumping of a compliant one-legged robot designed by the authors, which utilizes the concept of the virtual pendulum. The robot was modeled as an extended spring-loaded inverted pendulum (SLIP) model with non-negligible torso inertia, leg inertia, and leg damping. To enable the robot to jump forward stably, a foot placement method was adopted, where due to the asymmetric feature of the extended SLIP model, a variable time coefficient and an integral term with respect to the forward speed tracking error were introduced to the method to accurately track a given forward speed. An energy-based leg rest length regulation method was used to compensate for the energy dissipation due to leg damping, where an integral term, regarding jumping height tracking error, was introduced to accurately track a given jumping height. Numerical simulations were conducted to validate the effectiveness of the proposed control strategy. Results show that stable and fast jumping of compliant one-legged robots could be achieved, and the desired forward speed and jumping height could also be accurately tracked. In addition to that, using the proposed control strategy, the robust jumping performance of the robot could be observed in the presence of disturbances from state variables or uneven terrain. Full article

In the research of computer vision, a very challenging problem is the detection of small objects. The existing detection algorithms often focus on detecting full-scale objects, without making proprietary optimization for detecting small-size objects. For small objects dense scenes, not only the accuracy is low, but also there is a certain waste of computing resources. An improved detection algorithm was proposed for small objects based on YOLOv5. By reasonably clipping the feature map output of the large object detection layer, the computing resources required by the model were significantly reduced and the model becomes more lightweight. An improved feature fusion method (PB-FPN) for small object detection based on PANet and BiFPN was proposed, which effectively increased the detection ability for small object of the algorithm. By introducing the spatial pyramid pooling (SPP) in the backbone network into the feature fusion network and connecting with the model prediction head, the performance of the algorithm was effectively enhanced. The experiments demonstrated that the improved algorithm has very good results in detection accuracy and real-time ability. Compared with the classical YOLOv5, the mAP@0.5 and mAP@0.5:0.95 of SF-YOLOv5 were increased by 1.6% and 0.8%, respectively, the number of parameters of the network were reduced by 68.2%, computational resources (FLOPs) were reduced by 12.7%, and the inferring time of the mode was reduced by 6.9%. Full article

As one of the fastest running animals on land, the ostrich’s excellent athletic ability benefits from its unique leg structure. Based on the idea of bionics, this paper intends to obtain a kind of robotic leg structure with a similar buffering capacity to that of the ostrich. For this purpose, the structural characteristics of a seven-link parallel mechanism are analyzed firstly, having some specific features similar to ostrich legs, such as the center of mass (COM) located at the root of the leg, a large folding/unfolding ratio, and so on. Then, the kinematic model of the bionic leg is established, and the energy storage of the flexible parts of the leg is investigated. Finally, an impact experiment of the structure onto the ground is carried out to verify the accuracy of the established kinematic model. This paper systematically reveals the nonlinear law of the elasticity of an ostrich-like leg and provides the buffering performance characteristics of the leg in the process of hitting the ground, based on its elastic properties by the kinematic model and the experiment. Full article