Search Results (10)

This study examines improvements in local air quality and noise (LAQ&N) of the Landing and Take-Off cycle (LTO cycle) with the introduction of a hybrid electric/sustainable mid-range aircraft. Using Dortmund Airport as a case study, the results highlight significant environmental benefits. Future traffic scenarios estimate potential gains: INDIGO flights improve LAQ by up to 74% and noise impacts by 36%. When replacing 15% of the future traffic demand with INDIGO aircraft, up to a 3% benefit in LAQ&N can be expected. Full traffic replacement scenarios promise substantial environmental advantages, affirming the INDIGO aircrafts’ role in greener aviation. Full article

Landscape aesthetic quality (LAQ) evaluation is vital in territorial spatial planning. It helps to achieve the rational development and protection of territorial space and ensures the harmonious coexistence of developments and the ecological environment. Based on mapping and quantification, this paper took LAQ evaluation as the object, established a methodological framework for large-scale natural LAQ evaluation, excavated and identified key areas with outstanding landscape aesthetics service supply capabilities, and supported regional landscape planning and protection management. This paper took the Hengduan Mountains in China as an example to evaluate and identify the spatial distribution of the LAQ in mountainous areas. The results showed that the high-value LAQ areas are located east and south of the Hengduan Mountains, where high-quality natural landscapes are concentrated and have significant potential for establishing national parks. The evaluation results of the LAQ can provide a good reference for the spatial identification of future national parks in the Hengduan Mountains. Moreover, our research can provide a scientific basis for large-scale landscape spatial planning and decision-making for the classified protection and rational utilization of landscape resources and other mountain ecosystems. Full article

Imaging disdrometers are widely used in field campaigns to provide information on the shape of hydrometeors, together with the diameter and the fall velocity, which can be used to derive information on the shape–size relations of hydrometeors. However, due to their higher price compared to laser disdrometers, their use is limited to scientific research purposes. The 3D stereo (3DS) is a commercial imaging disdrometer recently made available by Thies Clima and on which there are currently no scientific studies in the literature. The most innovative feature of the 3DS is its ability in capturing images of the particles passing through the measurement volume, crucial to provide an accurate classification of hydrometeors based on information about their shape, especially in the case of solid precipitation. In this paper. the performance of the new device is analyzed by comparing 3DS with the Laser Precipitation Monitor (LPM) from the same manufacturer, which is a known laser disdrometer used in many research works. The data used in this paper were obtained from measurements of the two instruments carried out at the Casale Calore site in L’Aquila during the CORE-LAQ (Combined Observations of Radar Experiments in L’Aquila) campaign. The objective of the comparison analysis is to analyze the differences between the two disdrometers in terms of hydrometeor classification, number and falling speed of particles, precipitation intensity, and total cumulative precipitation on an event basis. As regards the classification of precipitation, the two instruments are in excellent agreement in identifying rain and snow; greater differences are observed in the case of particles in mixed phase (rain and snow) or frozen phase (hail). Due to the different measurement area of the two disdrometers, the 3DS generally detects more particles than the LPM. The performance differences also depend on the size of the hydrometeors and are more significant in the case of small particles, i.e., D < 1 mm. In the case of rain events, the two instruments are in agreement with respect to the terminal velocity in still air predicted by the Gunn and Kinzer model for drops with a diameter of less than 3 mm, while, for larger particles, terminal velocity is underestimated by both the disdrometers. The agreement between the two instruments in terms of total cumulative precipitation per event is very good. Regarding the 3DS ability to capture images of hydrometeors, the raw data provide, each minute, from one to four images of single particles and information on their size and type. Their number and coarse resolution make them suitable to support only qualitative analysis of the shape of precipitating particles. Full article

Purpose: The COVID-19 pandemic, with its multidimensional consequences, is the most serious threat of the 21st century affecting the mental health of women in the perinatal period around the world. Resilience, which assumes the flexible use of an individual’s resources in facing adversity, is an important, protective factor influencing mental well-being. The presented study aimed to determine to what extent psychological resilience, mitigates the relationship between adverse consequences of the COVID-19 pandemic and symptoms of depression and anxiety in women in the perinatal period. Methods: We recruited pregnant women from 17 February to 13 October 2021, using social media, the parenting portal, and the snowball method. To assess mental well-being, we used: The Edinburgh Postnatal Depression Scale (EPDS), The Beck Depression Inventory (BDI-2), Self-report Labour Anxiety Questionnaire—LAQ and the self-developed COVID-19 Pandemic Anxiety Questionnaire (CRAQ). Resilience was measured usingthe Resilience Measure Questionnaire (KOP26). Multiple Correspondence Analysis (MCA), an independent t-test, and a Pearson correlation analysis were performed. Results: Low resilience was significantly associated with depressive symptoms (r = −0.46; p < 0.05) and anxiety related to childbirth (r = −0.21; p < 0.05). No associations were found for resilience and pandemic-related stress. Very high and high perinatal anxiety along with the lowest level of resilience clustered with EPDS and BDI-2 scores indicating depression. Conclusions: Our study provides evidence that lower levels of resilience during pregnancy may be a significant predictor of increased severity of depressive symptoms and higher levels of anxiety related to childbirth among the perinatal population. Full article

As a novel histone deacetylase inhibitor (HDACi), LAQ824 (LAQ) effectively inhibits the proliferation of hematological malignancies and solid tumors. However, phase II trials of LAQ in solid tumors were terminated due to dose-dependent toxicity. Furthermore, LAQ has been shown to induce the activation of the Notch signaling pathway in hematopoietic stem cells, which is associated with tumor progression and drug resistance in colon and breast cancers. Therefore, in this study, we investigated the strategy of LAQ combined with a Notch signaling pathway inhibitor to treat solid tumors. We used RT-PCR and Western blot methods to demonstrate that LAQ upregulated the Notch signaling pathway in solid tumor cell lines at the molecular level. The combination of LAQ and a Notch signaling pathway inhibitor was shown by a Chou–Talalay assay to have a synergistic effect in inhibiting solid tumor cell line proliferation in vitro. We also demonstrated that the combination of LAQ and a Notch signaling pathway inhibitor significantly inhibited the growth of tumor cells in vivo using an allograft tumor model. This study indicates that inhibition of the Notch signaling pathway provides a valuable strategy for enhancing solid tumor sensitivity to LAQ. Full article

Globally, the COVID-19 pandemic has had both positive and negative impacts on humans and the environment. In general, a positive impact can be seen on the environment, especially in regard to air quality. This positive impact on air quality around the world is a result of movement control orders (MCO) or lockdowns, which were carried out to reduce the cases of COVID-19 around the world. Nevertheless, data on the effects on air quality both during and post lockdown at local scales are still sparse. Here, we investigate changes in air quality during normal days, the MCOs (MCO 1, 2 and 3) and post MCOs, namely the Conditional Movement Control Order (CMCO) and the Recovery Movement Control Order (RMCO) in the Klang Valley region. In this study, we used the air sensor network AiRBOXSense that measures carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and particulate matter (PM_2.5 and PM₁₀) at Petaling Jaya South (PJS), Kelana Jaya (KJ) and Kota Damansara (KD). The results showed that the daily average concentrations of CO and NO₂ mostly decreased in the order of normal days > MCO (MCO 1, 2 and 3) > CMCO > RMCO. PM₁₀, PM_2.5, SO₂ and O₃ showed a decrease from the MCO to RMCO. PJS showed that air pollutant concentrations decreased from normal days to the lockdown phases. This clearly shows the effects of ‘work from home’ orders at all places in the PJS city. The greatest percentage reductions in air pollutants were observed during the change from normal days to MCO 1 (24% to 64%), while during MCO 1 to MCO 2, the concentrations were slightly increased during the changes of the lockdown phase, except for SO₂ and NO₂ over PJS. In KJ, most of the air pollutants decreased from MCO 1 to MCO 3 except for CO. However, the percentage reduction and increments of the gas pollutants were not consistent during the different phases of lockdown, and this effect was due to the sensor location—only 20 m from the main highway (vehicle emissions). The patterns of air pollutant concentrations over the KD site were similar to the PJS site; however, the percentage reduction and increases of PM_2.5, O₃, SO₂ and CO were not consistent. We believe that local burning was the main contribution to these unstable patterns during the lockdown period. The cause of these different changes in concentrations may be due to the relaxation phases during the lockdown at each station, where most of the common activities, such as commuting and industrial activities changed in frequency from the MCO, CMCO and RMCO. Wind direction also affected the concentrations, for example, during the CMCO and RMCO, most of the pollutants were blowing in from the Southeast region, which mostly consists of a city center and industrial areas. There was a weak correlation between air pollutants and the temperature and relative humidity at all stations. Health risk assessment analysis showed that non-carcinogenic risk health quotient (HQ) values for the pollutants at all stations were less than 1, suggesting unlikely non-carcinogenic effects, except for SO₂ (HQ > 1) in KJ. The air quality information showed that reductions in air pollutants can be achieved if traffic and industry emissions are strictly controlled. Full article

Background: Meningiomas are the most common primary central nervous system tumors. 20–30% of these tumors are considered high-grade and associated with poor prognosis and high recurrence rates. Despite the high occurrence of meningiomas, there are no FDA-approved compounds for the treatment of these tumors. Methods: In this study, we screened patient-cultured meningiomas with an epigenetic compound library to identify targetable mechanisms for the potential treatment of these tumors. Meningioma cell cultures were generated directly from surgically resected patient tumors and were cultured on a neural matrix. Cells were treated with a library of compounds meant to target epigenetic functions. Results: Although each tumor displayed a unique compound sensitivity profile, Panobinostat, LAQ824, and HC toxin were broadly effective across most tumors. These three compounds are broad-spectrum Histone Deacetylase (HDAC) inhibitors which target class I, IIa, and IIb HDACs. Panobinostat was identified as the most broadly effective compound, capable of significantly decreasing the average cell viability of the sample cohort, regardless of tumor grade, recurrence, radiation, and patient gender. Conclusions: These findings strongly suggest an important role of HDACs in meningioma biology and as a targetable mechanism. Additional validation studies are necessary to confirm these promising findings, as well to identify an ideal HDAC inhibitor candidate to develop for clinical use. Full article

Few cross-sectional studies have investigated the correlation between neurochemical changes and multiple sclerosis (MS) fatigue, but little is known on the fatigue-related white matter differences between time points. We aim to investigate the longitudinal neurometabolite profile of white matter in MS fatigue. Forty-eight relapsing remitting multiple sclerosis (RRMS) patients with an expanded disability status scale (EDSS) ≤ 4 underwent high field ¹H-multivoxel magnetic resonance spectroscopy (MRS) at baseline and year 1. Fatigue severity was evaluated by the fatigue severity scale (FSS). Patients were divided into low (LF, FSS ≤ 3), moderate (MF, FSS = 3.1–5), and high fatigue (HF, FSS ≥ 5.1) groups. In a two-way analysis of variance (ANOVA), we observed a decline in the ratio of the sum of N-acetylaspartate (NAA) and N-acetylaspartylglutamate (NAAG) to the sum of creatine (Cr) and phosphocreatine (PCr) in the right anterior quadrant (RAQ) and left anterior quadrant (LAQ) of the MRS grid in the HF group at baseline and year 1. This decline was significant when compared with the LF group (p = 0.018 and 0.020). In a one-way ANOVA, the fatigue group effect was significant and the ratio difference in the right posterior quadrant (RPQ) and left posterior quadrant (LPQ) of the HF group was also significant (p = 0.012 and 0.04). Neurochemical changes in the bilateral frontal white matter and possibly parietooccipital areas were noted in the HF group at two different time points. Our findings may shed some light on the pathology of MS fatigue. Full article

IMA-08401 (C2) is a novel aryl hydrocarbon receptor (AHR) agonist and selective AHR modulator (SAHRM) that is structurally similar to laquinimod (LAQ). Both compounds are converted to the AHR-active metabolite DELAQ (IMA-06201) in vivo. SAHRMs have been proposed as therapeutic options for various autoimmune disorders. Clinical trials on LAQ have not reported any significant toxic outcomes and C2 has shown low toxicity in rats; however, their functional resemblance to the highly toxic AHR agonist 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) raises questions. Here, we characterize the hepatic transcriptomic changes induced by acute (single-dose) and subacute exposure (repeated dosing for 5 days followed by a 5-day recovery period) to C2 in Sprague-Dawley rats. Exposure to C2 leads to activation of the AHR, as shown by altered transcription of Cyp1a1. We identify a heightened response early after exposure that drops off by day 10. Acute exposure to C2 leads to changes to transcription of genes involved in antiviral and antibacterial responses, which highlights the immunomodulator effects of this AHR agonist. Subacute exposure causes an oxidative stress response in the liver, the consequences of which require further study on target tissues such as the CNS and immune system, both of which may be compromised in this patient population. Full article

Conventional air quality monitoring systems, such as gas analysers, are commonly used in many developed and developing countries to monitor air quality. However, these techniques have high costs associated with both installation and maintenance. One possible solution to complement these techniques is the application of low-cost air quality sensors (LAQSs), which have the potential to give higher spatial and temporal data of gas pollutants with high precision and accuracy. In this paper, we present DiracSense, a custom-made LAQS that monitors the gas pollutants ozone (O₃), nitrogen dioxide (NO₂), and carbon monoxide (CO). The aim of this study is to investigate its performance based on laboratory calibration and field experiments. Several model calibrations were developed to improve the accuracy and performance of the LAQS. Laboratory calibrations were carried out to determine the zero offset and sensitivities of each sensor. The results showed that the sensor performed with a highly linear correlation with the reference instrument with a response-time range from 0.5 to 1.7 min. The performance of several calibration models including a calibrated simple equation and supervised learning algorithms (adaptive neuro-fuzzy inference system or ANFIS and the multilayer feed-forward perceptron or MLP) were compared. The field calibration focused on O₃ measurements due to the lack of a reference instrument for CO and NO₂. Combinations of inputs were evaluated during the development of the supervised learning algorithm. The validation results demonstrated that the ANFIS model with four inputs (WE OX, AE OX, T, and NO₂) had the lowest error in terms of statistical performance and the highest correlation coefficients with respect to the reference instrument (0.8 < r < 0.95). These results suggest that the ANFIS model is promising as a calibration tool since it has the capability to improve the accuracy and performance of the low-cost electrochemical sensor. Full article