GDF-15 as a biomarker for diagnosis and prognosis of lung cancer: a meta-analysis

IntroductionDue to the tendency of lung cancer to be diagnosed at advanced stages, many patients are not eligible for curative surgery. Identifying early detection and prognosis biomarkers is crucial for improving outcomes. This study explores the potential of Growth Differentiation Factor 15 (GDF-15) as a biomarker for these purposes.MethodsA thorough review and meta-analysis of literature from PubMed, Embase, the CENTRAL, and the CNKI was performed. We analyzed the diagnostic accuracy of GDF-15, focusing on its sensitivity, specificity, and AUC. Additionally, we investigated the association between three-year overall survival and GDF-15 levels in lung cancer patients. Our analysis included nine studies, encompassing 1296 patients with lung cancer and 1182 healthy controls.ResultsGDF-15 showed high diagnostic performance with a sensitivity of 0.80 (95% Confidence Interval (CI): 0.71-0.87), specificity of 0.92 (95% CI: 0.85-0.96), diagnostic odds ratio of 45 (95% CI: 25-79), and an AUC of 0.93 (95% CI: 0.90-0.95). Moreover, the prognosis analysis revealed that the plasma GDF-15 levels were significantly higher in patients than controls (standardized mean difference: 2.91, CI 2.79-3.04 and P < 0.00001), and the odds ratio of 3-year overall survival rate was 4.05 (95% CI: 1.92-8.51 and P = 0.0002).DiscussionGDF-15 exhibits strong potential as both a diagnostic and prognostic biomarker in lung cancer, distinguishing effectively between patients and healthy individuals. These findings support its further exploration and potential integration into clinical practice.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024519807

Targeting Anion Exchange of Osteoclast, a New Strategy for Preventing Wear Particles Induced- Osteolysis

Joint replacement is essential for the treatment of serious joint disease. However, prosthetic failure remains an important clinical issue, with periprosthesis osteolysis (PO), caused by osteoclastic bone resorption induced by wear particles, being the leading cause of failure. Nuclear factor of activated T cells c1 (NFATc1) appears to play an important role in wear particle-induced osteoclastogenesis, with bicarbonate/chloride exchanger, solute carrier family 4, anion exchanger, member 2, (SLC4A2) being upregulated during osteoclastogenesis in an NFATc1-dependent manner. Anion exchange mediated by SLC4A2 in osteoclasts could affect the bone resorption activity by regulating pHi. This study investigated the role and mechanism of SLC4A2 in wear particle-induced osteoclast differentiation and function in vitro. The use of 4, 4′-diisothiocyano-2,2′-stilbenedisulfonic acid (DIDS), an anion exchange inhibitor, suppressed wear particle-induced PO in vivo. Furthermore, controlled release of DIDS from chitosan microspheres can strengthen the PO therapy effect. Therefore, anion exchange mediated by osteoclastic SLC4A2 may be a potential therapeutic target for the treatment of aseptic loosening of artificial joints

Incorporating Wavelet Decomposition Technique to Compress TransGuide Intelligent Transportation System Data

With the improvement and application of various data collection techniques, intelligent transportation system (ITS) data have created obstacles for the effective storage, transmission, and retrieval of data. Some traffic management centers (TMCs) collect ITS information and maintain the “recent” data until it can be transferred to users for ultimate long-term storage, management, or both. Others archive data in convenient storage formats (usually compressed text) without action on data usage and analyses. In currently compressed ITS data (e.g., TransGuide zipped data), many redundant and empty spaces can be eliminated and compressed. Sophisticated approaches must be developed to compress ITS data in TMCs effectively. The wavelet-incorporated ITS data compression method not only makes use of conventional data-compression techniques but also incorporates the advanced one-dimensional discrete wavelet-compression approach. Three compression indices are constructed, and one threshold selection algorithm is proposed. The identified threshold can balance both compression ratio and signal distortion. Results of a case study in San Antonio, Texas, indicate that the proposed method and algorithm can achieve a compression ratio that is about 8.12% of what TransGuide currently provides. The entire compression ratio is &lt;1% for a typical day's data. Results of impact analyses indicate that the selection of wavelet forms does not significantly affect the final compression ratio, whereas higher decomposition levels yield smaller decomposition ratios. </jats:p

Impacts of pavement types on in-vehicle noise and human health

Noise is a major source of pollution that can affect the human physiology and living environment. According to the World Health Organization (WHO), an exposure for longer than 24 hours to noise levels above 70 dB(A) may damage human hearing sensitivity, induce adverse health effects, and cause anxiety to residents nearby roadways. Pavement type with different roughness is one of the associated sources that may contribute to in-vehicle noise. Most previous studies have focused on the impact of pavement type on the surrounding acoustic environment of roadways, and given little attention to in-vehicle noise levels. This paper explores the impacts of different pavement types on in-vehicle noise levels and the associated adverse health effects. An old concrete pavement and a pavement with a thin asphalt overlay were chosen as the test beds. The in-vehicle noise caused by the asphalt and concrete pavements were measured, as well as the drivers’ corresponding heart rates and reported riding comfort. Results show that the overall in-vehicle sound levels are higher than 70 dB(A) even at midnight. The newly overlaid asphalt pavement reduced in-vehicle noise at a driving speed of 96.5 km/hr by approximately 6 dB(A). Further, on the concrete pavement with higher roughness, driver heart rates were significantly higher than on the asphalt pavement. Drivers reported feeling more comfortable when driving on asphalt than on concrete pavement. Further tests on more drivers with different demographic characteristics, along highways with complicated configurations, and an examination of more factors contributing to in-vehicle noise are recommended, in addition to measuring additional physical symptoms of both drivers and passengers.Implications: While there have been many previous noise-related studies, few have addressed in-vehicle noise. Most studies have focused on the noise that residents have complained about, such as neighborhood traffic noise. As yet, there have been no complaints by drivers that their own in-vehicle noise is too loud. Nevertheless, it is a fact that in-vehicle noise can also result in adverse health effects if it exceeds 85 dB(A). Results of this study show that in-vehicle noise was strongly associated with pavement type and roughness; also, driver heart rate patterns presented statistically significant differences on different types of pavement with different roughness

Vehicle emission implications of drivers’ smart advisory system for traffic operations in work zones

ABSTRACT: Wireless communication systems have been broadly applied in various complicated traffic operations to improve mobility and safety on roads, which may raise a concern about the implication of the new technology on vehicle emissions. This paper explores how the wireless communication systems improve drivers’ driving behaviors and its contributions to the emission reduction, in terms of Operating Mode (OpMode) IDs distribution used in emission estimation. A simulated work zone with completed traffic operation was selected as a test bed. Sixty subjects were recruited for the tests, whose demographic distribution was based on the Census data in Houston, Texas. A scene of a pedestrian’s crossing in the work zone was designed for the driving test. Meanwhile, a wireless communication system called Drivers Smart Advisory System (DSAS) was proposed and introduced in the driving simulation, which provided drivers with warning messages in the work zone. Two scenarios were designed for a leading vehicle as well as for a following vehicle driving through the work zone, which included a base test without any wireless communication systems, and a driving test with the trigger of the DSAS. Subjects’ driving behaviors in the simulation were recorded to evaluate safety and estimate the vehicle emission using the Environmental Protection Agency (EPA) released emission model MOVES. The correlation between drivers’ driving behavior and the distribution of the OpMode ID during each scenario was investigated. Results show that the DSAS was able to induce drivers to accelerate smoothly, keep longer headway distance and stop earlier for a hazardous situation in the work zone, which driving behaviors result in statistically significant reduction in vehicle emissions for almost all studied air pollutants (p-values range from 4.10E-51 to 2.18E-03). The emission reduction was achieved by the switching the distribution of the OpMode IDs from higher emission zones to lower emission zones. Implications: Transportation section is a significant source of greenhouse gas emissions. Many studies demonstrate that the wireless communication system dedicated for safety and mobility issues may contribute to the induction in vehicle emissions through changing driving behaviors. An insight into the correlation between the driving behaviors and the distribution of Operating Mode (OpMode) IDs is essential to enhance the emission reduction. The result of this study shows that with a Drivers Smart Advisory System (DSAS) drivers accelerated smoothly and stopped earlier for a hazardous situation, which induce the switch of the OpMode IDs from high emission zones to lower emission zones