Search Results (104)

Background/Objectives: Human identical twins are born at a rate of 3–4 per 1000 live births. Many other mammals also occasionally produce monozygotic twins, referred to as sporadic polyembryony. The underlying mechanisms are unknown. Through epigenome-wide association studies (EWAS), we identified a robust DNA methylation signature in somatic tissues from human monozygotic (MZ) twins, comprising 834 differentially methylated positions (MZ-DMPs). The results point to a connection between monozygotic twinning and early genome programming and enable new angles to study monozygotic twinning. Methods: The mammalian methylation array (MMA) measures 38,608 CpGs focusing on regions that are well-conserved across many mammalian species, allowing for pan-mammalian comparative epigenomic studies. Here, we successfully map human MZ-DMPs to probes of the mammalian methylation array across 157 mammalian genomes. Results: As expected, based on the modest probe overlap between Illumina 450k/EPIC and mammalian methylation array probes, only a subset of MZ-DMPs reside in conserved regions covered by the mammalian methylation array. These include probes mapping to NPAS3, KLHL35, CASZ1, and ATP2B2. Re-analysis restricting the original EWAS in humans to conserved MMA regions yielded additional MZ-DMPs, suggesting that more loci may be detected by application of the mammalian array to monozygotic twins. Conclusion: In conclusion, the mammalian methylation array may prove to be a promising platform to study whether a shared DNA methylation signature of sporadic polyembryony exists across diverse mammalian species. This may potentially point to shared underlying mechanisms. Full article

Thyroid gland carcinoma (TGC), though only 1% of all carcinomas, is the most common endocrine neoplasm with an increasing incidence since the 1990s. Of the TGC types, papillary thyroid carcinoma (PTC) is the most common and has the best overall prognosis. Although primarily studied in various neural spectrum disorders, monoamine oxidase A (MAOA) may also contribute to cancer occurrence. This case control study assessed the prevalence of MAOA uVNTR polymorphism in PTC patients, compared its frequency with a healthy control, and assessed the variant’s impact on clinical features. The research participants consisted of 30 PTC patients (20 female, 10 male) over 18 years old who underwent thyroidectomy and radioiodine therapy at a Federal District private clinic and 30 paired and unrelated healthy volunteers (18 female, 12 male). The most frequent MAOA uVNTR alleles were 3R and 4R. Although no significant difference was detected in the genotypic distribution nor the PTC patients’ thyroglobulin, thyroid-stimulating hormone, and antithyroglobulin levels; body mass indexes; administered radiopharmaceutical (131I) doses; or biological sex, the presence of at least one 3R allele was associated with a larger tumor size (T3 + T4 staging). Thus, the 3R allele seems to be associated with PTC pathogenesis severity. Full article

(1) The main aim of this study was to analyze the relationship of the Mediterranean diet (MD) with vascular function in participants with and without increased insulin resistance (IR) in the Spanish population. A secondary aim was to study differences by gender. (2) Methods: Data were analyzed from 3401 subjects in the EVA, MARK, and EVIDENT studies (mean age = 60 years and 57% men). IR was evaluated with the triglyceride and glucose index (TyG index). TyG index = Ln [(fasting triglyceride mg/dL × fasting glucose mg/dL)/2]. The MD was measured against the MEDAS questionnaire, with the 14 items used in the PREDIMED study. Vascular stiffness was estimated with the brachial–ankle pulse wave velocity (baPWV) and the cardio ankle vascular index (CAVI) using the Vasera VS-1500^®. (3) Results: The mean MEDAS value was 5.82 ± 2.03; (men: 5.66 ± 2.06; women: 6.04 ± 1.99; p < 0.001). MD adherence was 36.8% (men: 34.2%; women: 40.3%; p < 0.001). The mean baPWV value was 14.39 ± 2.78; (men: 14.50 ± 2.65; women: 14.25 ± 2.93; p = 0.005). A baPWV value ≥ 14.5 m/s was found in 43.4% (men: 43.6%; women: 40.0%; p = 0.727). The mean CAVI value was 8.59 ± 1.28; (men: 8.75 ± 1.28; women: 8.37 ± 1.26; p < 0.001). CAVI values ≥ 9 were present in 39.0% (men: 44.4%; women: 31.7%; p < 0.001). The mean value of the TGC/G index was 10.93 ± 1.39; (men: 11.08 ± 1.33; women: 10.73 ± 1.43; p < 0.001). IR was found in 49.9%. The average value of the MD score value was negatively associated with baPWV and CAVI in all groups analyzed (<0.05), except in the group of women with insulin resistance. (4) Conclusions: The results suggest that MD adherence is negatively associated with the vascular stiffness parameters analyzed in all the groups studied except the group of women with insulin resistance. Full article

The tradable green certificate (TGC) scheme is an important approach for mitigating carbon emissions within the context of a renewable energy development strategy and regional sustainable development. However, studies investigating the role of TGCs in encouraging carbon emissions reduction in China are limited and inconclusive due to ignoring the interference of other renewable energy policies and little distinguishing the impact of different green certificates. Using Chinese provincial data from 2013 to 2023, this study employs a difference-in-differences strategy to estimate the effect of the TGC policy on regional carbon emissions. The results reveal that the TGC policy significantly reduces provincial carbon emissions, and this reduction is predominantly contributed by certificate-electricity integration green certificates rather than certificate-electricity separation certificates. A 1% increase in the provincial trade volume of certificate-electricity integration green certificates can reduce total provincial carbon emissions by 0.8–1.3%. These findings hold across a series of rigorous robustness tests. This study also explains the different effects between certificate-electricity integration and certificate-electricity separation green certificates by the concept of additionality. To effectively reduce carbon emissions in the future, the TGC system must meet the requirement of additionality. These insights can provide reference for the improvement of TGC policy to better achieve the carbon reduction objective and sustainable development. Full article

The High-Luminosity Large Hadron Collider (HL-LHC) project aims to improve the performance of the LHC by increasing the proton–proton collision luminosity. New physics discoveries will be possible starting in 2027. The HL-LHC aims to improve the integrated luminosity by a factor of 10 concerning the current running LHC’s design value. The HL-LHC project foresees delivering proton–proton collisions at 14 TeV CM (Center of Mass) energy providing the integrated luminosity to a value of 3 ab⁻¹ for the ATLAS and CMS experiments, 50 fb⁻¹ for LHCb, and 5 fb⁻¹ for ALICE. The increased integrated luminosity for the above LHC experiments will provide the potential to discover rare processes while improving these measurements’ signal-to-noise (S/N) ratio statistics. The ATLAS muon spectrometer has been upgraded to face the challenges of the luminosity at the HL-LHC run. The new sub-detectors are as follows: The New Small Wheel (NSW) has replaced the Cathode Strip Chambers (CSC) discs at the internal part of the ATLAS end cups. The new integrated small Monitored Drift Chambers (sMDT) with the Resistive Plate Chambers (RPC) are installed at the outer end of the ATLAS BI (Barrel Inner) layer, in the barrel–endcap transition region, at 1.0 < |η| < 1.3, where η is the pseudo-rapidity (pseudo-rapidity η is a commonly used spatial coordinate describing the angle of a particle relative to the beam axis, defined as η=−lntanθ2, where θ is the angle between the vector momentum p→ and the positive direction of the beam axis). The NSW is an innovative technological achievement, including the MicroMegas (MM) gas detectors in large areas and small-strip Thin Gap Chambers (sTGC), enabling high p_T (high p_T is the high value of the particles’ transverse momentum versus the beam collision axis) trigger and muon detection. The muon reconstruction, the background rate, other spectrometer parameters, and the NSW performance are also presented. Full article

Improving China’s high-quality development efficiency represents a key lever for the development of new productivity and successfully achieving the “dual carbon” goal. Starting from the nonparametric production theory, this paper addresses the issues of infeasible solutions and technical heterogeneity by employing the total-factor non-radial directional distance function and a metafrontier non-radial Malmquist model. The static total-factor high-quality development efficiency index (THEI) and its dynamic metafrontier non-radial Malmquist high-quality development efficiency index (MNMHEI) are measured for 31 provinces in China from 2008 to 2021. Given that high-quality development efficiency is led and driven by talent, we use labor of different ages and levels of education as four inputs instead of single labor for the study of THEI. The MNMHEI is divided into three indices for measuring efficiency change (EC), best-practice gap change (BPC), and technology gap change (TGC). The empirical results demonstrate that labor with higher education is the main lever of static high-quality development efficiency; there is a 5.3% decrease in China’s dynamic high-quality development efficiency as a whole, and a lack of technological innovation remains a significant constraint on its improvement. The results of the heterogeneity analysis, which classified all provincial areas into low-carbon and high-carbon regions, indicate that the former exhibits a higher dynamic high-quality development efficiency than the latter, which still lacks innovation and technology leadership. It is recommended that the Chinese government consider the talent management system, investments in upgrading technologies, energy conservation, and emission reduction for high-carbon regions to improve their high-quality development efficiency. Full article

A 56-day feeding trial was conducted to evaluate the quantitative methionine requirements in the diets of Florida pompano (Trachinotus carolinus). Eight practical diets using soybean meal, poultry meal, and red lentil meal as the primary protein sources were formulated using graded levels of methionine supplement (0 to 0.70 g/100 g diet). Groups of 15 juvenile Florida pompano (4.04 ± 0.05 g) were size-sorted and placed into one of 40 glass aquaria (132 L) with five replicates per diet. Significant differences (p ≤ 0.05) were observed in overall biomass, mean weight, weight gain, thermal growth coefficient (TGC), and feed conversion ratio (FCR). To estimate the dietary methionine requirement, a series of statistical models, including the one-slope broken line model (BLM1), two-slope broken line model (BLM2), broken quadratic model (BQM), and four-parameter saturation kinetic model (SKM-4) were used to assess mean weight, weight gain, TGC, apparent net protein retention (ANPR), and methionine retention (MR). The model selection showed that BLM1 fit the data best for MW and TGC, SKM-4 for PWG and ANPR, and BQM for MR. Based on these results, a minimum dietary methionine requirement of 0.68% of the diet or 1.70 g/100 g protein is recommended. Full article

Mitigating air pollutants such as SO_x and PM emitted from ships is an important task for marine environmental protection and improving air quality. To address this, exhaust gas after-treatment devices have been introduced, but treating pollutants like SO_x and PM individually poses challenges due to spatial constraints on ships. Consequently, a Total Gas Cleaning System (TGCS) capable of simultaneously reducing sulfur oxides and particulate matter has been developed. The TGCS combines a cyclone dust collector and a wet scrubber system. The cyclone dust collector is designed to maintain a certain distance from the bottom of the wet scrubber, allowing exhaust gases entering from the bottom to rise as sulfur oxides are adsorbed. Additionally, the exhaust gases descending through the space between the cyclone dust collector and the wet scrubber collide with the scrubbing solution before entering the bottom of the wet scrubber, facilitating the absorption of SO_x. In this study, the efficiency of the developed TGCS was evaluated, and the reduction effects based on design parameters were investigated. Furthermore, the impact of this device on ship engines was analyzed to assess its practical applicability. Experimental results showed that increasing the volume flow rate of the cleaning solution enhanced the PM reduction effect. Particularly, when the height of the Pall ring was 1000 mm and the volume flow rate was 35 L/min, the sulfur oxide reduction effect met the standards for Sulfur Emission Control Areas (SECA). Based on these findings, suggestions for effectively controlling atmospheric pollutants from ships were made, with the expectation of contributing to the development of systems combining various after-treatment devices. Full article

Track geometry measurements (TGMs) are a critical methodology for assessing the quality of track regularities and, thus, are essential for ensuring the safety and comfort of high-speed railway (HSR) operations. TGMs also serve as foundational datasets for engineering departments to devise daily maintenance and repair strategies. During routine maintenance, S-shaped long-wave irregularities (SLIs) were found to be present in the vertical direction from track geometry cars (TGCs) at the beginning and end of a vertical curve (VC). In this paper, we conduct a comprehensive analysis and comparison of the characteristics of these SLIs and design a long-wave filter for simulating inertial measurement systems (IMSs). This simulation experiment conclusively demonstrates that SLIs are not attributed to track geometric deformation from the design reference. Instead, imperfections in the longitudinal profile’s design are what cause abrupt changes in the vehicle’s acceleration, resulting in the measurement output of SLIs. Expanding upon this foundation, an additional investigation concerning the quantitative relationship between SLIs and longitudinal profiles is pursued. Finally, a method that involves the addition of a third-degree parabolic transition curve (TDPTC) or a full-wave sinusoidal transition curve (FSTC) is proposed for a smooth transition between the slope and the circular curve, designed to eliminate the abrupt changes in vertical acceleration and to mitigate SLIs. The correctness and effectiveness of this method are validated through filtering simulation experiments. These experiments indicate that the proposed method not only eliminates abrupt changes in vertical acceleration, but also significantly mitigates SLIs. Full article

In various domains, including everyday activities, agricultural practices, and medical treatments, the escalating challenge of antibiotic resistance poses a significant concern. Traditional approaches to studying antibiotic resistance genes (ARGs) often require substantial time and effort and are limited in accuracy. Moreover, the decentralized nature of existing data repositories complicates comprehensive analysis of antibiotic resistance gene sequences. In this study, we introduce a novel computational framework named TGC-ARG designed to predict potential ARGs. This framework takes protein sequences as input, utilizes SCRATCH-1D for protein secondary structure prediction, and employs feature extraction techniques to derive distinctive features from both sequence and structural data. Subsequently, a Siamese network is employed to foster a contrastive learning environment, enhancing the model’s ability to effectively represent the data. Finally, a multi-layer perceptron (MLP) integrates and processes sequence embeddings alongside predicted secondary structure embeddings to forecast ARG presence. To evaluate our approach, we curated a pioneering open dataset termed ARSS (Antibiotic Resistance Sequence Statistics). Comprehensive comparative experiments demonstrate that our method surpasses current state-of-the-art methodologies. Additionally, through detailed case studies, we illustrate the efficacy of our approach in predicting potential ARGs. Full article

Hemolysis is a common cause of errors in laboratory tests as it affects blood parameters and leads to a positive or negative bias. This study aims to examine the relationship between the level of hemolysis (expressed as cell-free hemoglobin concentration, g/L) and the variability of metabolic and endocrine parameters and to determine the threshold level of hemolysis that causes an analytically and clinically significant bias for the twenty most frequently examined blood parameters in cows. Paired blood samples of 10 mL each were obtained from 30 cows. One was subjected to mechanical trauma and plasma was extracted directly from the other. Hemolyzed and non-hemolyzed samples from the same animal were mixed to obtain final samples with cell-free hemoglobin concentrations of 0, 1, 2, 4, 6, 8, and 10 g/L. Metabolic and endocrine parameters were measured in the samples and their deviation and the linear equation between the level of hemolysis and the deviation were determined. The following threshold values of hemolysis were determined, which correspond to the acceptable analytical (lower value) and clinical (upper value) levels of parameter variability: BHB 0.96 and 4.81; NEFA 0.39 and 3.31; GLU 0.38 and 3.90; ALB 1.12 and 6.11; TPROT 1.40 and 6.80; UREA 6.62 and 20.1; TBIL 0.75 and 5.65; AST 0.11 and 2.18; GGT 1.71 and 8.90, LDH 0.01 and 0.11, ALP 0.97 and 2.95; TGC 1.56 and 15.5; CHOL 1.29 and 8.56; Ca 5.68 and 25.7; P 0.57 and 8.43; Mg 1.10 and 8.47; INS 1.15 and 3.89; T3 8.19 and 15.6; T4 8.97 and 18.5; and CORT 2.78 and 11.22 g/L cell-free hemoglobin. Three decision levels are available for each metabolic and endocrine parameter: if hemolysis is below the lower (analytical) threshold value, results can be reported without restriction; if hemolysis is between the lower and upper thresholds, the results can be issued with guidance in the form of corrective linear equations; and if hemolysis is above the upper (clinical) threshold, the results and sample must be discarded. This method contributes to an optimal approach to hemolysis interference with metabolic profile parameters in blood samples from cows. Full article

Lithium plating can cause capacity fade and thermal runaway safety issues in lithium-ion batteries. Therefore, accurately detecting the amount of lithium plating on the surface of the battery’s negative electrode is crucial for battery safety. This is especially crucial in high-energy-density applications such as battery energy storage systems or in electric vehicles (EVs). Early detection of lithium plating is crucial for evaluation of reliability and longevity. It also serves as a method for early diagnostics in practical industrial applications or infrastructure, such as EV transportation. This can enhance its impact on customers. This study validates the effectiveness of titration gas chromatography (TGC) technology in quantitatively detecting lithium plating on graphite negative electrodes in lithium-ion batteries. The results show that it can detect a minimum of 2.4 μmol of metallic lithium. Compared with the heating direct current resistance and reference electrode methods, which can be used to perform only qualitative dendrite detection, TGC has a wider range of detection. Compared with the nuclear magnetic resonance (NMR) method with higher quantitative detection accuracy, the maximum difference between the detection results of the two methods was only 7.2%, but the TGC method had lower cost and higher implementation convenience. In summary, among various dendrite detection methods, the TGC method can not only realize the effective quantitative detection of lithium plating, but also comprehensively consider its detection range, implementation convenience, cost, and detection accuracy, indicating that it is suitable for engineering applications and has the prospect of realizing large-scale quantitative detection of lithium plating in lithium-ion batteries. Full article

Carbon sinks provided by land ecosystems play a crucial role in achieving carbon neutrality. However, the future potential of carbon sequestration remains highly uncertain. The impact of pollutant emission reduction (PER) introduced by the proposed synergistic approach to air pollution control and carbon neutrality on carbon sinks in China has not yet been fully evaluated. In this study, we analyzed the effects of regional carbon-neutral PER policies, global climate change, and their coupled effects on China’s terrestrial gross primary productivity (GPP) by conducting numerical experiments using the weather research and forecasting model coupled with chemistry (WRF-Chem) and the moderate resolution imaging spectroradiometer photosynthesis algorithm (MODIS-PSN). We found that carbon-neutral PER policies could promote GPP growth in most regions of China in 2060, particularly during April and October, resulting in a total increase of at least 21.84 TgC compared to that in 2016, which offset the adverse effects of global climate change up to fourfold. The aerosol radiative effects drive GPP growth under carbon-neutral PER policies, primarily through an increase in daily minimum temperature during winter and an increase in shortwave radiation during other seasons. Our research highlights that reducing pollutant emissions enhances future potential for carbon sequestration, revealing positive feedback towards achieving the target of carbon neutrality. Full article

Mangrove ecosystems are pivotal to the global carbon budget. However, there is still a dearth of research addressing the impact of regional mangrove land use and land cover change (LUCC) on carbon sequestration and its associated spatial distribution patterns. To investigate the impact of different development scenarios on the carbon storage capacity of mangrove ecosystems, we focused on Hainan Island. We used LUCC data from 2010 to 2020 from mangrove-inhabited regions. The Markov-PLUS model was applied to predict the spatiotemporal dynamics of mangrove coverage under the natural increase scenario (NIS) and the mangrove protection scenario (MPS) over the next 40 years. Carbon storage was estimated using the InVEST model based on field-measured carbon density data. The outcomes show the following: (1) The Markov-PLUS model, with an overall accuracy of 0.88 and a Kappa coefficient of 0.82, is suitable for predicting mangrove distribution patterns on Hainan Island. (2) Environmental factors were the main drivers of historical mangrove changes on Hainan Island, explaining 54% of the variance, with elevation, temperature, and precipitation each contributing over 13%. (3) From 2025 to 2065, the mangrove area on Hainan Island is projected to increase by approximately 12,505.68 ha, mainly through conversions from forest land (12.73% under NIS and 12.37% under MPS) and agricultural land (39.72% under NIS and 34.53% under MPS). (4) The carbon storage increment within Hainan Island’s mangroves is projected at 2.71 TgC over the whole island, with notable increases expected in the eastern, northern, and northwestern regions, and modest gains in other areas. In this study, we comprehensively investigated the spatiotemporal dynamics and future trends of carbon storage in the mangroves of Hainan Island, offering invaluable guidance for the long-term management of mangrove ecosystems and the realization of carbon neutrality goals by 2060. Full article

Mountainous forests are pivotal in the global carbon cycle, serving as substantial reservoirs and sinks of carbon. However, generating a reliable estimate remains a considerable challenge, primarily due to the lack of representative in situ measurements and proper methods capable of addressing their complex spatial variation. Here, we proposed a deep learning-based method that combines Residual convolutional neural networks (ResNet) with in situ measurements, microwave (Sentinel-1 and VOD), and optical data (Sentinel-2 and Landsat) to estimate forest biomass and track its change over the mountainous regions. Our approach, integrating in situ measurements across representative elevations with multi-source remote sensing images, significantly improves the accuracy of biomass estimation in Tibet’s complex mountainous forests (R² = 0.80, root mean squared error = 15.8 MgC ha⁻¹). Moreover, ResNet, which addresses the vanishing gradient problem in deep neural networks by introducing skip connections, enables the extraction of complex spatial patterns from limited datasets, outperforming traditional optical-based or pixel-based methods. The mean value of forest biomass was estimated as 162.8 ± 21.3 MgC ha⁻¹, notably higher than that of forests at comparable latitudes or flat regions in China. Additionally, our findings revealed a substantial forest biomass carbon sink of 3.35 TgC year⁻¹ during 2015–2020, which is largely underestimated by previous estimates, mainly due to the underestimation of mountainous carbon stock. The significant carbon density, combined with the underestimated carbon sink in mountainous regions, emphasizes the urgent need to reassess mountain forests to better approximate the global carbon budget. Full article