Search Results (31)

The aim of this study was to investigate the accuracy and stability of both Perception of Velocity (PV) and Perception of Velocity Loss (PVL) over four weeks, without any feedback regarding velocity during training sessions. Fifteen subjects performed six training sessions: four sessions familiarized the athletes with PV and PVL and the final two sessions assessed the accuracy and stability of PV and PVL, with one conducted 48 h after the familiarization and the other after 4 weeks. To assess PV and PVL, two loads (60% 1RM and 80% 1RM) and two velocity losses (20% VL and 40% VL) were employed. PV accuracy was measured by the DeltaScore, the difference between perceived velocity (Vp) and the velocity provided by the encoder (Vr): DetlaScore = Vp − Vr. PVL was measured by the Vscore, the difference between repetitions where the subject perceived the target %VL (Np) and repetitions that actually met it (Nr): Vscore = Np − Nr. The analysis performed revealed no differences in DeltaScore nor in Vscore between the two test sessions performed 4 weeks apart (p > 0.05). On the other hand, the effect of load on both DeltaScore and Vscore was significant in both sessions (p < 0.05). PVL and PV accuracy are stable throughout time. PVL may be used to prescribe and monitor velocity-based training. Conversely, when prescribing training sessions based on PV, it is essential to pair PV with a perception scale and incorporate an encoder when possible. Full article

Cadmium and petroleum are the main pollutants in coastal wetland ecosystems that affect plant nutrient balance and growth. Scholars have discovered how saline plants adapt to single stresses. How plant ecology and physiology correspond to complex cadmium and petroleum pollution, especially regarding the pollution impacts on carbon (C), nitrogen (N), and phosphorus (P) stoichiometry and biomass allocation in coastal wetland plants, remains unclear, limiting their application in regard to pollution remediation. This study focuses on Suaeda salsa, a popular species used in vegetation restoration in the Yellow River Delta’s coastal wetlands. Through the use of pot experiments, the dynamic changes in plant–soil ecological stoichiometry and biomass allocation were systematically investigated in response to individual and combined cadmium (0, 5, and 10 mg kg⁻¹) and petroleum (0, 6, and 12 g kg⁻¹) treatments. Compared with the control (CK), petroleum stress significantly increased the total nitrogen (TN) and plant total phosphorus (TP) contents, but did not substantially impact the total carbon (TC) content, resulting in 19.7% and 26.6% decreases in the plant C/N and C/P ratios, respectively. The soil organic carbon (SOC) content increased significantly under petroleum stress, whereas the TN and TP contents did not notably change, considerably increasing the soil C/N and C/P ratios, which were 1.5 times and 1.3 times greater than those of the CK, respectively. Cadmium stress alone or with petroleum stress did not significantly affect the C, N, or P stoichiometry or biomass allocation in S. salsa. The soil C/N/P stoichiometry redundancy analysis revealed that the contribution rates (especially the soil C/P and C/N ratios) to the total biomass and its allocation in S. salsa (64.5%) were greater than those of the control group plants (35.5%). The correlation analysis revealed that the total growth biomass of S. salsa was negatively correlated with the soil carbon content, C/N ratio, and C/P ratio, but positively correlated with the plant C/N and C/P ratios. The aboveground biomass proportion in S. salsa was significantly negatively correlated with the soil N/P ratio. The belowground biomass proportion exhibited the opposite trend. Petroleum pollution was the main factor driving S. salsa stoichiometry and growth changes, increasing the soil C/N and C/P ratios, reducing the nitrogen and phosphorus nutrient absorption capacities in plant roots, limiting plant nitrogen and phosphorus nutrients, and inhibiting biomass accumulation. Appropriate N and P supplementation alleviated plant growth inhibition due to petroleum pollution stress, which was conducive to improving vegetation ecological restoration in the Yellow River Delta. Full article

As a typical desert oasis ecosystem in the arid region of Northwest China, the Ejina Delta plays a crucial role in regional ecological security through its vegetation dynamics and landscape pattern changes. Based on Landsat remote sensing images (1990–2020), runoff data, and vegetation landscape surveys, this study investigated the evolutionary patterns and driving mechanisms of vegetation degradation and restoration processes using Normalized Difference Vegetation Index (NDVI), landscape metrics, and Land Use Transition Matrix (LUTM) methods. The following key findings were obtained: (1) Since the implementation of the Ecological Water Diversion Project (EWDP) in the Heihe River Basin (HRB) in 2000, a significant recovery in vegetation coverage has been observed, with an NDVI growth rate of 0.0187/10 yr, which is five times faster than that in the pre-diversion period. The areas of arbor vegetation, shrubland, and grassland increased to 356.8, 689.5, and 2192.6 km², respectively. However, there is a lag of about five years for the recovery of arbor and shrub compared to grass. (2) The implementation of EWDP has effectively reversed the trend of vegetation degradation, transforming the previously herb-dominated fragmented landscape into a more integrated pattern comprising multiple vegetation types. During the degradation period (1990–2005), the landscape exhibited a high degree of fragmentation, with an average number of patches (NP) reaching 45,875. In the subsequent recovery phase (2005–2010), fragmentation was significantly reduced, with the average NP dropping to 30,628. (3) Stronger vegetation growth and higher NDVI values were observed along the riparian zone, with the West River demonstrating greater restoration effectiveness compared to the East River. This study revealed that EWDP serves as the key factor driving vegetation recovery. To enhance oasis stability, future ecological management strategies should optimize spatiotemporal water allocation while considering differential vegetation responses. Full article

The characterization of the lunar surface and subsurface through the utilization of synthetic aperture radar data has assumed a pivotal role in the domain of lunar exploration science. This investigation concentrated on the polarimetric analysis aimed at identifying water ice within a specific crater, designated Erlanger, located at the lunar north pole, which is fundamentally a region that is perpetually shaded from solar illumination. The area that is perpetually shaded on the moon is defined as that region that is never exposed to sunlight due to the moon’s slightly tilted rotational axis. These permanently shaded regions serve as cold traps for water molecules. To ascertain the presence of water ice within the designated study area, we conducted an analysis of two datasets from the Chandrayaan mission: Mini-SAR data from Chandrayaan-1 and Dual-Frequency Synthetic Aperture Radar (DFSAR) data from Chandrayaan-2. The polarimetric analysis of the Erlanger Crater, located in a permanently shadowed region of the lunar north pole, utilizes data from the Dual-Frequency Synthetic Aperture Radar (DFSAR) and the Mini-SAR. This study focuses exclusively on the L-band DFSAR data due to the unavailability of S-band data for the Erlanger Crater. The crater, identified by the PSR ID NP_869610_0287570, is of particular interest for its potential water ice deposits. The analysis employs three decomposition models—m-delta, m-chi, and m-alpha—derived from the Mini-SAR data, along with the H-A-Alpha model known as an Eigenvector and Eigenvalue model, applied to the DFSAR data. The H-A-Alpha helps in assessing the entropy and anisotropy of the lunar surface. The results reveal a correlation between the hybrid polarimetric models (m-delta, m-chi, and m-alpha) and fully polarimetric parameters (entropy, anisotropy, and alpha), suggesting that volume scattering predominates inside the crater walls, while surface and double bounce scattering are more prevalent in the right side of the crater wall and surrounding areas. Additionally, the analysis of the circular polarization ratio (CPR) from both datasets suggests the presence of water ice within and around the crater, as values greater than 1 were observed. This finding aligns with other studies indicating that the high CPR values are indicative of ice deposits in the lunar polar regions. The polarimetric analysis of the Erlanger Crater contributes to the understanding of lunar polar regions and highlights the potential for future exploration and resource utilization on the Moon. Full article

Patients with multiple sclerosis (MS) and spinal cord injury (SCI) commonly sustain central neuropathic pain (NP) and spasticity. Despite a lack of consistent evidence, cannabis-based medicine (CBM) has been suggested as a supplement treatment. We aimed to investigate the effect of CBM on NP and spasticity in patients with MS or SCI. We performed a randomized, double-blinded, placebo-controlled trial in Denmark. Patients aged ≥18 years with NP (intensity >3, ≤9 on a numerical rating scale (NRS0-10) and/or spasticity (>3 on NRS0-10) were randomized to treatment consisting of either delta-9-tetrahydrocannabinol (THC), cannabidiol (CBD), a combination of THC&CBD in maximum doses of 22.5 mg, 45 mg and 22.5/45 mg per day, respectively, or placebo. A baseline registration was performed before randomization. Treatment duration was six weeks followed by a one-week phaseout. Primary endpoints were the intensity of patient-reported NP and/or spasticity. Between February 2019 and December 2021, 134 patients were randomized (MS n = 119, SCI n = 15), where 32 were assigned to THC, 31 to CBD, 31 to THC&CBD, and 40 to placebo. No significant difference was found for: mean pain intensity (THC 0.42 (−0.54–1.38), CBD 0.45 (−0.47–1.38) and THC&CBD 0.16 (−0.75–1.08)), mean spasticity intensity (THC 0.24 (−0.67–1.45), CBD 0.46 (−0.74–1.65), and THC&CBD 0.10 (−1.18–1.39), secondary outcomes (patient global impression of change and quality of life), or any tertiary outcomes. We aimed to include 448 patients in the trial; however, due to COVID-19 and recruitment challenges, fewer were included. Nevertheless, in this four-arm parallel trial, no effect was found between placebo and active treatment with THC or CBD alone or in combination on NP or spasticity in patients with either MS or SCI. The trial was registered with the EU Clinical Trials Register EudraCT (2018-002315-98). Full article

As an economically developed region, the Yangtze River Delta region has undergone earth-shaking changes in its rural settlements due to rapid urbanization. For the optimization and adjustment of rural settlements, it is crucial to disclose their distinguishing spatial features and impelling factors. Taking 307 county-level administrative regions in the Yangtze River Delta region as the research object, this study comprehensively uses the landscape index, nearest neighbor index, Moran index, and spatial hot spot detection system to analyze the spatial differentiation characteristics of rural residential location-scale morphology and reveals its driving factors using the optimal parameters-based geographical detector model. According to the findings, rural settlements in the Yangtze River Delta region exhibit an average nearest neighbor index of 0.7417, a Moran’s I of 1.2993 for the number of patches (NP), and a maximum patch density (PD) of 17.25 villages per square kilometer. It has significant characteristics of large-scale village cluster distribution, and the morphology of rural settlements in the southern and northern regions shows apparent differences. The natural environment and social economies, such as elevation, slope, precipitation, and population density, mainly drive the location-scale morphological spatial distribution of rural settlements. At the same time, the interaction between the natural environment, social economy, and location condition factors has a synergistic enhancement effect on the spatial distribution of location-scale morphology of rural settlements. Full article

Compound-specific stable isotope analysis (CSIA) is an efficient method for source apportionment and the identification of the transformation process in organic compounds. However, most studies of CSIA are still limited to laboratory experiments. Few studies used have CSIA in an in situ environment due to the complexity of environmental samples. Therefore, a purification method for analyzing the carbon isotope ratios of three phenolic endocrine disrupting compounds (EDCs) (nonylphenols (NPs), octylphenol (OP), and bisphenol A(BPA)) in sediment and water samples was developed in this study. The silica gel column was used to isolate EDCs from complex matrices with multiple organic solvents. Gas chromatography/mass spectrometry was used to quantify the targeted EDCs and analyze the purity of the extracts in full-scan mode. The interfering peaks disappeared, the baseline was sharply reduced, and all the target compounds appeared as single peaks in the chromatogram after purification. Analyzing the standard samples with known isotope ratios showed that the purification treatment did not cause isotope fractionation. The isotopic difference before and after purification was less than 0.04. The method was successfully used to analyze the isotope composition of BPA, OP, and NPs in river water and sediments in the Guangzhou River, Pearl River Delta, South China. Sewage discharge significantly affected the carbon isotope values of BPA, OP and NPs in Guangzhou rivers, suggesting that sewage discharge is the main source of EDCs in the Guangzhou rivers. There is a significant correlation between the isotopic values and concentrations of OP and NPs in sediments, indicating that they may undergo chemical transformation. Full article

Insomnia is a common sleep disorder around the world, which is harmful to people’s health, daily life, and work. The paraventricular thalamus (PVT) plays an essential role in the sleep–wake transition. However, high temporal-spatial resolution microdevice technology is lacking for accurate detection and regulation of deep brain nuclei. The means for analyzing sleep–wake mechanisms and treating sleep disorders are limited. To detect the relationship between the PVT and insomnia, we designed and fabricated a special microelectrode array (MEA) to record electrophysiological signals of the PVT for insomnia and control rats. Platinum nanoparticles (PtNPs) were modified onto an MEA, which caused the impedance to decrease and improved the signal-to-noise ratio. We established the model of insomnia in rats and analyzed and compared the neural signals in detail before and after insomnia. In insomnia, the spike firing rate was increased from 5.48 ± 0.28 spike/s to 7.39 ± 0.65 spike/s, and the power of local field potential (LFP) decreased in the delta frequency band and increased in the beta frequency band. Furthermore, the synchronicity between PVT neurons declined, and burst-like firing was observed. Our study found neurons of the PVT were more activated in the insomnia state than in the control state. It also provided an effective MEA to detect the deep brain signals at the cellular level, which conformed with macroscopical LFP and insomnia symptoms. These results laid the foundation for studying PVT and the sleep–wake mechanism and were also helpful for treating sleep disorders. Full article

The highly contagious SARS-CoV-2 virus is primarily transmitted through respiratory droplets, aerosols, and contaminated surfaces. In addition to antiviral drugs, the decontamination of surfaces and personal protective equipment (PPE) is crucial to mitigate the spread of infection. Conventional approaches, including ultraviolet radiation, vaporized hydrogen peroxide, heat and liquid chemicals, can damage materials or lack comprehensive, effective disinfection. Consequently, alternative material-compatible and sustainable methods, such as nanomaterial coatings, are needed. Therefore, the antiviral activity of two novel zinc-oxide nanoparticles (ZnO-NP) against SARS-CoV-2 was investigated in vitro. Each nanoparticle was produced by applying highly efficient “green” synthesis techniques, which are free of fossil derivatives and use nitrate, chlorate and sulfonate salts as starting materials and whey as chelating agents. The two “green” nanomaterials differ in size distribution, with ZnO-NP-45 consisting of particles ranging from 30 nm to 60 nm and ZnO-NP-76 from 60 nm to 92 nm. Human lung epithelial cells (Calu-3) were infected with SARS-CoV-2, pre-treated in suspensions with increasing ZnO-NP concentrations up to 20 mg/mL. Both “green” materials were compared to commercially available ZnO-NP as a reference. While all three materials were active against both virus variants at concentrations of 10–20 mg/mL, ZnO-NP-45 was found to be more active than ZnO-NP-76 and the reference material, resulting in the inactivation of the Delta and Omicron SARS-CoV-2 variants by a factor of more than 10⁶. This effect could be due to its greater total reactive surface, as evidenced by transmission electron microscopy and dynamic light scattering. Higher variations in virus inactivation were found for the latter two nanomaterials, ZnO-NP-76 and ZnO-NP-ref, which putatively may be due to secondary infections upon incomplete inactivation inside infected cells caused by insufficient NP loading of the virions. Taken together, inactivation with 20 mg/mL ZnO-NP-45 seems to have the greatest effect on both SARS-CoV-2 variants tested. Prospective ZnO-NP applications include an antiviral coating of filters or PPE to enhance user protection. Full article

Understanding the regulatory mechanisms underlying corneal epithelial cell (CEC) proliferation in vitro may provide the means to boost CEC production in cell therapy for ocular disorders. The transcription factor ΔNp63 plays a crucial role in the proliferation of CECs, but the underlying mechanisms is yet to be elucidated. TP63 and ΔNp63 are encoded by the TP63 gene via alternative promoters. We previously reported that both ΔNp63 and activating transcription factor (ATF3) are substantially expressed in cultured CECs, but the regulatory relationship between ΔNp63 and ATF3 is unknown. In the present study, we found that ΔNp63 increased ATF3 expression and ATF3 promoter activity in cultured CECs. The deletion of the p63 binding core site reduced ATF3 promoter activity. CECs overexpressing ATF3 exhibited significantly greater proliferation than control CECs. ATF3 knockdown suppressed the ΔNp63-induced increase in cell proliferation. Overexpression of ATF3 in CECs significantly elevated protein and mRNA levels of cyclin D. The protein levels of keratin 3/14, integrin β1, and involucrin did not differ between ATF3-overexpressing CECs, ATF3-downregulated CECs, and control cells. In conclusion, our results suggest that ΔNp63 increases CEC proliferation via the ΔNp63/ATF3/CDK pathway. Full article

The energy consumption of a multi-access edge computing (MEC) system must be reduced to save operational costs. Determining a set of active MEC servers (MECSs) that can minimize the energy consumption of the MEC system while satisfying the service delay requirements of the tasks is an NP-complete problem. To solve this problem, we take a bio-inspired approach. We note that the sleep control problem of the MECS differentiates the operational mode among neighboring MECSs. Therefore, by mimicking the cell differentiation process in a biological system, we designed a distributed sleep control method. Each MECS periodically gathers the utilization and delta levels of the neighboring MECSs. Subsequently, by using the gathered information and the Delta–Notch inter-cell signaling model, a MECS autonomously decides whether to sleep. We evaluated the performance of our method through extensive simulations. Compared with a conventional method, the proposed method reduces energy consumption in a MEC system by more than $13\%$ while providing a comparable service delay. In addition, our method reduces the variations in the service delay by more than $35\%$. Full article

Objectives. Since the outbreak of SARS-CoV-2 in late 2019, nearly 12.2 billion doses of the COVID-19 vaccine have been administered worldwide; however, the humoral immune responses induced by different types of vaccines are yet to be fully validated. Methods. We analyzed antibody levels in 100 serum samples after vaccination with different types of COVID-19 vaccines and their reactivity against the RBD antigen of Delta and Omicron variants using a bead-based microarray. Results. Elevated levels of anti-wild-type (WT)-RBD IgG and anti-WT-NP IgG were detected in participants who received two doses of the inactivated vaccines (CoronaVac or BBIBP-CorV) and three doses of the recombinant spike protein vaccine (ZF2001), indicating that antibody responses to SARS-CoV-2 were generated regardless of the vaccine administered. We found highly correlated levels of serum anti-RBD IgG and anti-NP IgG (r = 0.432, p < 0.001). We observed that the antibodies produced in vivo after COVID-19 vaccination still reacted with variants of SARS-CoV-2 (p < 0.0001). Conclusions. Our results show that high levels of specific antibodies can be produced after completion of COVID-19 vaccination (two doses of the inactivated vaccines or three doses of ZF2001), with some degree of cross-reactivity to the RBD antigen of Delta and Omicron variants, and provide an accessible and practical experimental method for post-vaccination antibody detection. Full article

The association between nasopharyngeal (NP) SARS-CoV-2 viral loads and clinical outcomes remains debated. Here, we examined the factors that might predict the NP viral load and the role of the viral load as a predictor of clinical outcomes. A convenience sample of 955 positive remnant NP swab eluent samples collected during routine care between 18 November 2020 and 26 September 2021 was cataloged and a chart review was performed. For non-duplicate samples with available demographic and clinical data (i.e., non-employees), an aliquot of eluent was sent for a droplet digital PCR quantification of the SARS-CoV-2 viral load. Univariate and multivariate analyses were performed to identify the clinical predictors of NP viral loads and the predictors of COVID-19-related clinical outcomes. Samples and data from 698 individuals were included in the final analysis. The sample cohort had a mean age of 50 years (range: 19–91); 86.6% were male and 76.3% were unvaccinated. The NP viral load was higher in people with respiratory symptoms (p = 0.0004) and fevers (p = 0.0006). In the predictive models for the clinical outcomes, the NP viral load approached a significance as a predictor for in-hospital mortality. In conclusion, the NP viral load did not appear to be a strong predictor of moderate-to-severe disease in the pre-Delta and Delta phases of the pandemic, but was predictive of symptomatic diseases and approached a significance for in-hospital mortality, providing support to the thesis that early viral control prevents the progression of disease. Full article

Land subsidence affects many areas of the world, posing a serious threat to human structures and infrastructures. It can be effectively monitored using ground-based and remote sensing techniques, such as the Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). GNSS provides high precision measurements, but in a limited number of points, and is time-consuming, while InSAR allows one to obtain a very large number of measurement points, but only in areas characterized by a high and constant reflectivity of the signal. The aim of this work is to propose an approach to combine the two techniques, overcoming the limits of each of them. The approach was applied in the Po River Delta (PRD), an area located in Northern Italy and historically affected by land subsidence. Ground-based GNSS data from three continuous stations (CGNSS) and 46 non-permanent sites (NPS) measured in 2016, 2018, and 2020, and Sentinel-1 and COSMO-SkyMed SAR data acquired from 2016 to 2020, were considered. In the first phase of the method, InSAR processing was calibrated and verified through CGNSS measurements; subsequently, the calibrated interferometric data were used to validate the GNSS measurements of the NPS. In the second phase, the datasets were integrated to provide an efficient monitoring system, extracting high-resolution deformation maps. The results showed a good agreement between the different sources of data, a high correlation between the displacement rate and the age of the emerged surfaces composed of unconsolidated fine sediments, and high land subsidence rates along the coastal area (up to 16–18 mm/year), where the most recent deposits outcrop. The proposed approach makes it possible to overcome the disadvantages of each technique by providing more complete and detailed information for a better understanding of the ongoing phenomenon. Full article

The COVID-19 pandemic emerged in 2020 and has caused an unprecedented burden to all countries in the world. SARS-CoV-2 continues to circulate and antigenically evolve, enabling multiple reinfections. To address the issue of the virus antigenic variability, T cell-based vaccines are being developed, which are directed to more conserved viral epitopes. We used live attenuated influenza vaccine (LAIV) virus vector to generate recombinant influenza viruses expressing various T-cell epitopes of SARS-CoV-2 from either neuraminidase (NA) or non-structural (NS1) genes, via the P2A self-cleavage site. Intranasal immunization of human leukocyte antigen-A*0201 (HLA-A2.1) transgenic mice with these recombinant viruses did not result in significant SARS-CoV-2-specific T-cell responses, due to the immunodominance of NP₃₆₆ influenza T-cell epitope. However, side-by-side stimulation of peripheral blood mononuclear cells (PBMCs) of COVID-19 convalescents with recombinant viruses and LAIV vector demonstrated activation of memory T cells in samples stimulated with LAIV/SARS-CoV-2, but not LAIV alone. Hamsters immunized with a selected LAIV/SARS-CoV-2 prototype were protected against challenge with influenza virus and a high dose of SARS-CoV-2 of Wuhan and Delta lineages, which was confirmed by reduced weight loss, milder clinical symptoms and less pronounced histopathological signs of SARS-CoV-2 infection in the lungs, compared to LAIV- and mock-immunized animals. Overall, LAIV is a promising platform for the development of a bivalent vaccine against influenza and SARS-CoV-2. Full article