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Targeting dysregulated molecular pathways in cancer cell lines using small molecule inhibitors as a promising therapeutic strategy
An in vitro model to study molecular pathogenesis of sarcopenia established by a SASP-dependent human myotube culture
Sarcopenia is a condition that affects one’s activities of daily livingand is rapidly increasing with the ages of the global population. However, the basic molecular mechanisms for prevention and treatment are not fully understood. Although rodent model animals have many valuable aspects for studying sarcopenia, some aspects and mechanisms differ from humans, such as immune response, metabolism, stress response, and myofiber composition. This study established a human cell-based in vitro model to elucidate the molecular mechanism by which SASP from senescence-induced human mesenchymal stem cells led to the narrowing of human myotube diameter, suggesting that this model is useful for studying sarcopenia. Gene expression profiling was performed the molecular mechanisms and devel on the model by RNA sequencing to identify genes whose expression was affected by SASP. Among these, the exposure to SASP upregulated PDK4 expression, and a PDK4 inhibitor, DCA, could increase myotube diameter and reverse SASP-mediated narrowing of the diameter. Pathway analyses suggested that SASP affected energy metabolism by activating OXPHOS and promoting the expression of mitochondrial function-related genes and mitochondrial biosynthesis factors. These results provide insights that contribute to developing new treatments for sarcopenia.
A semi supervised framework for human and machine collaboration in computer assisted text refinement
Abstract Human writing often exhibits a range of styles and levels of sophistication. However, automated text generation systems typically lack the nuanced understanding required to produce refined and elegant prose. Due to the inherent one-to-many relationship between inputs and outputs in natural language generation tasks, achieving annotator consistency is challenging. This complexity makes the annotation process considerably more difficult compared to tasks focused on natural language understanding. Our study focuses on the typical task of text refinement, which faces annotation difficulties, aiming to generate sentences with more elegant expressions while preserving the original semantics of the input sentence. This paper proposes a semi-automatic data construction method that combines auto-generation with human judgment. Initially, this method translates collected sentences containing elegant expressions into ordinary expressions through back translation. Subsequently, in an iterative quality control process, data filtering and human judgment are introduced to screen the auto-generated data based on quality standards, resulting in a large-scale text refinement dataset. By replacing manual annotation with human judgment and involving only a small amount of data for human judgment in each iteration, this method significantly reduces annotation difficulty and workload. With minimal human effort, it acquires a substantial amount of labeled data for text refinement, laying a foundation for further research in the field.
Calibration of parameters in microscopic traffic flow simulation models considering micro-meteorological information
Different micro-meteorological conditions can affect a driver’s judgment of road conditions, leading to changes in following behavior. On rainy days, water films on the road reduce traction, increasing the likelihood of hydroplaning and traffic accidents. While there are existing following models under various weather conditions, research on the specific impact of micro-meteorological factors is insufficient. To achieve fine management in intelligent transportation and real-time monitoring of vehicle states, it’s essential to study following behavior under different micro-meteorological conditions and establish corresponding models. This paper focuses on the Intelligent Driver Model (IDM) and the Wiedemann99 model, considering the impact of micro-meteorological conditions. By incorporating a driver’s judgment factor, λ, the IDM and Wiedemann99 models are improved, leading to the development of new models: I-IDM and I-Wiedemann99. Simulation validation is used to choose speed and following distance as performance indicators for parameter calibration of the I-IDM and I-Wiedemann99 models, with the sum of Root Mean Square Percentage Error (RMSPE) as the goodness-of-fit function. Comparisons are made between the driving paths, speeds, and accelerations of following vehicles before and after calibration, verified through simulations. The conclusions are as follows: the average error and standard deviation of the improved I-IDM model are smaller than those of the I-Wiedemann99 model, with the maximum Root Mean Square Percentage Error (RMSPE) for I-IDM model parameter calibration being 0.4568 and the minimum being 0.1324. For the I-Wiedemann99 model, the maximum RMSPE is 0.4613 and the minimum is 0.1376. The parameter calibration results of the I-Wiedemann99 model are more dispersed compared to those of the I-IDM model, indicating that the I-IDM model simulates following behavior more effectively than the I-Wiedemann99 model. The findings of this study can provide a reference for further improving the theory of following behavior, and offer a theoretical basis and IoT technology support for refined traffic management under rainy conditions.
Generation of a 28 GHz annular power distribution with high power gyrotron and its application to microwave driven in tube accelerator
Abstract The microwave-driven in-tube accelerator (MITA) concept, which installs the center body of the thruster inside the waveguide and generates thrust via millimeter-wave beam irradiation from the front side of the center body, was experimentally demonstrated using 210-kW and 28-GHz gyrotron device. For the 28-GHz beams, a vortex phase plate was newly designed to change the incident beam profile from a Gaussian to a donut-shaped pattern, which was installed in front of the thruster’s center body. Without the vortex phase plate, gas breakdown occurred at the center-body head, providing a negative impulse. However, as the electric field concentration at the center-body head was avoided using the vortex phase plate, plasma and strong shock wave generation were obtained at the rear side of the vehicle, inducing a positive impulse to accelerate the thruster toward the beam source direction. The MITA thrust performance increased as the incident beam pulse width increased because gas heating was enhanced at the rear side of the center body.
Quantitative attribution of spatio-temporal pattern of pm2.5 concentration based on geodetector and GWR model: Evidence from China’s three major urban agglomerations
Clarifying the spatio-temporal evolution of PM2.5 concentration law and its driving mechanism is crucial for the prevention and control of air pollution in urban agglomerations, also helping promote their high-quality development. Based on remote sensing and statistics of urban agglomerations in China’s Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) from 2005 to 2020, the paper analyses the evolution characteristics of the pollution concentration pattern and identifies the influencing factors through spatial analysis method combining the geodetector and geographically weighted regression (GWR) model. As the results show, during the study period: (1) Temporal Trends: annual PM2.5 concentrations exhibited significant declines, with BTH decreasing from 1004.71 μg/m3 (2006) to 528 μg/m3 (2020), YRD from 1434.81 μg/m3 (2008) to 621 μg/m3, and PRD from 405.02 μg/m3 (2007) to 292 μg/m3. The ranking remained YRD > BTH > PRD throughout the study period. (2) Spatial Heterogeneity: Spatial clustering (Moran’s I: 0.286–0.729, p < 0.05) dominated all regions. BTH showed a “high-south” pattern (e.g., Xingtai: 78.3 μg/m3 vs. Qinhuangdao: 34.2 μg/m3), YRD displayed “high-northwest” characteristics (Hefei: 68.5 μg/m3 vs. Ningbo: 42.1 μg/m3), while PRD exhibited a west-east gradient (Foshan: 49.8 μg/m3 vs. Shenzhen: 25.6 μg/m3). (3) The evolution of PM2.5 concentration in three urban agglomerations is generally positive autocorrelative aggregative distribution, and aggregation types include “high-high”, “low-low” and “high-low”. (4) The measurement of geographical detector indicates the differentiation of PM2.5 concentration is affected by both natural geography and socio-economic factors, and the former ones have stronger driving forces. (5) The measurement of GWR model indicates temperature, precipitation, vegetation coverage, urban expansion, industrial structure, and energy efficiency are main influencing factors of PM2.5 concentration pattern, and the degree of influence of these factors is different.
Orbital eccentricity and internal feedbacks drove the Triassic megamonsoon variability
Abstract The evolution of the Triassic megamonsoon was closely linked to Earth’s orbital variations. Despite recognizing secular orbital cycles as a fundamental pacemaker of the megamonsoon, the driving mechanisms remain unclear. Here, we use data-model synthesis to study orbital-scale megamonsoon variability during the Middle Triassic (~ 246–239 Ma). By integrating high-resolution reconstructions of hydrologic fluctuations, obtained from lithological and magnetic susceptibility data series in the lacustrine sediments of the Ordos Basin (Northeast Tethys), with the climate simulations, we identify monsoon cycles in the ~ 20, 100, and 405 kyr Milankovitch bands. Comparisons with other records further reveal an additional eccentricity-related ~ 3.3 Myr orbital cycle in monsoon variabilities, temperature oscillations, carbon cycles, and sea-level changes. Earth system models show the effects of orbital configurations and atmospheric CO₂ concentrations on megamonsoon dynamics, implying threshold responses to solar radiation and the impacts of temperature and sea-level fluctuations on long-term megamonsoon variability. These findings improve our understanding of the interplay between astronomical forcing and feedbacks in shaping orbital-scale monsoon dynamics.
Changes in heart rate variability and hemodynamics of adolescents within the frontal cortex in response to face emotional stimulation
Background Functional near-infrared spectroscopy (fNIRS) and heart rate variability (HRV) are commonly utilized biomarkers for assessing emotional states. This study hypothesizes that emotional perception—particularly the experience and variability of unpleasant emotions in adolescents—may be characterized by reduced HRV and increased or dysregulated frontal lobe activity, indicative of impaired emotional and autonomic regulation. Materials and Methods A total of 55 adolescents were enrolled in this study. After completing clinical questionnaires, resting-state HRV and fNIRS data were collected from all participants over a 200-second period. Following a 10-second intermission, HRV and fNIRS were simultaneously recorded during a 192-second positive emotional perception task. After a subsequent 30-second rest, the same procedures were repeated during a negative emotional perception task. Results A higher correction rate of unpleasant facial emotional perception—defined as the proportion of emotional stimuli (positive, negative, and neutral expressions) interpreted as unpleasant—was significantly associated with reduced HRV, as evidenced by lower high-frequency (HF) power and decreased standard deviation of normal-to-normal intervals (SDNN). Moreover, this correction rate positively correlated with the differential accumulation of oxygenated hemoglobin (ΔaccHbO₂) in the left dorsolateral prefrontal cortex (DLPFC), suggesting increased cortical engagement during the processing of negatively perceived stimuli. In contrast, the correction rate of pleasant facial emotional perception showed a negative correlation with ΔaccHbO₂ in the same region. Additionally, both unpleasant-SDNN and unpleasant-HF values were negatively correlated with ΔaccHbO₂ in the left DLPFC. Conclusions In adolescents, the perception of negative emotions is associated with individual differences in depression and anxiety levels. Furthermore, the perception of negative emotions demonstrates significant associations with alterations in HRV and neural activity within the left DLPFC. These findings also support a potential relationship between autonomic function and frontal lobe activation during the processing of unpleasant emotional stimuli.
Evolving patient preferences from surgery to thermal ablation in solitary thyroid nodule treatment
Accuracy of anterior cranial base surfaces acquired from computed tomography imaging
Abstract Understanding computed tomography scan accuracy is crucial for reliable diagnoses and minimal radiation exposure. This study assessed the accuracy of 3D surface models of the anterior cranial base created using different imaging devices and settings. Ten human skulls were scanned with two cone beam computed tomography (CBCT) scanners, including a low-radiation protocol, a CT scanner, and an optical scanner that provided highly accurate reference models. Water-filled head shells were used to simulate soft tissue during imaging. Reproducibility of the 3D models was evaluated through repeated segmentations, while accuracy was assessed by comparing the segmented models to the reference scans. The primary metric used was the mean absolute distance (MAD) between the 3D surface-approximated models. Results demonstrated high consistency across repeated segmentations, with only minor differences observed (< 0.09 mm). The low-radiation CBCT scans produced 3D models with accuracy comparable to conventional CT scans (median: 0.12 mm, IQR: 0.07 mm). No considerable differences were found between the imaging devices or protocols. These findings confirm that low-radiation CBCT protocols can reliably produce 3D anterior cranial base models comparable to standard CT scans, offering a safer alternative. This supports lower-dose imaging for craniofacial morphology assessment in clinical and research settings, ensuring accuracy while prioritizing patient safety.
Matrix metalloproteinase-2 as a novel regulator of glucose utilization by adipocytes
Identification and validation of glucocorticoid receptor and programmed cell death-related genes in spinal cord injury using machine learning
A hybrid ARIMA-BP approach for superior accuracy in predicting traffic accident losses
Association between serum osmolality and chronic kidney disease prevalence: Evidence from NHANES 1999–2018
Reliability and validity of OpenPose for measuring HKA angle in dynamic walking videos in patients with knee osteoarthritis
Abstract The hip-knee-ankle (HKA) angle is essential to assess surgical evaluation and disease progression in patients with knee osteoarthritis (KOA). Rapid, radiation-free assessment methods are a key area of research. This study investigates the reliability and validity of OpenPose, video-based human pose estimation method, for determining the HKA angle in KOA patients. In this study, we analyzed 50 knees affected by osteoarthritis. The HKA angle was measured using the pose estimation method and X-ray imaging before total knee arthroplasty. The pose estimation method demonstrated excellent test-retest reliability (ICC 1,1 = 1.000) and good consistency with radiography (ICC 2,1 = 0.897), with linear regression analysis showing a good correlation (R2 = 0.814). Compared with radiography, the pose estimation method exhibited a fixed error of 0.131°. This is the first study to examine the feasibility of measuring the HKA angle from frontal-view videos of patients walking normally by using the pose estimation method. Using the pose estimation method to measure the HKA angle in knee osteoarthritis patients is reliable and valid. The pose estimation method provides a safe, cost-effective, and user-friendly solution for monitoring lower limb alignment, with promising applications in remote healthcare and rehabilitation management. It eliminates radiation exposure, avoiding the health risks associated with X-ray imaging, and it does not require specialized medical equipment, enabling fully automated analysis.
Static short-range laser circumferential detection using a transmissive-reflective optical architecture
Establishment of a clinical workflow for in vivo Raman spectroscopy during head and neck cancer surgery
Abstract As first part of an ongoing prospective feasibility trial (DRKS00028114) this work explored the integration of in vivo Raman spectroscopy (RS) into the routine setting workflow of head and neck cancer (HNC) surgery. In vivo RS was performed intraoperatively on 30 patients with HNC cell carcinoma and 10 patients with inflammatory diseases as a control group. A standardized process was established using a Raman system complied with stringent medical device regulatory standards. Spectra were collected in vivo from the tumor site, the tumor margins, and healthy tissue. The learning curve of the HNC team significantly improved measurement times from over 30 min initially to 2 min after 15 patients. Data from 35 patients were interpretable, demonstrating clear spectral differences between tumor and healthy tissues. The intraoperative in vivo RS workflow is now well established and is being used in the ongoing clinical trial.