Search Results (150)

Background: Tic spectrum disorder (TSD), encompassing Tourette syndrome and chronic tic disorder, is a childhood-onset neurodevelopmental condition with complex genetic and environmental contributions. Heritable components have been implicated in TSD, but no clear genetic mechanisms have been identified. Significant aspects of TSD etiology remain unclear, with key uncertainties concerning the role of environmental influences in its development. In this study, we aimed to identify environmentally induced epigenomic and transcriptomic changes contributing to TSD pathology by investigating genetically similar monozygotic twins discordant for TSD. Methods: To investigate environmentally driven mechanisms, we analyzed peripheral blood from eleven monozygotic twin pairs, either discordant or concordant for TSD, using RNA sequencing and DNA methylation analysis. Results: Differential expression analysis identified a dozen differentially expressed genes between TSD and non-TSD individuals, most of which were long non-coding RNAs or pseudogenes. Expression of the small RNA gene RNY1 was significantly associated with tic severity, suggesting involvement of immune-related processes. DNA methylation (DNAm) analysis revealed ~30,000 probes with a nominal p < 0.05, however none of these were significant after multiple testing correction. Expression quantitative trait methylation (eQTM) analysis identified 236 methylation-associated genes. Gene set enrichment analysis demonstrated broad downregulation in TSD individuals for pathways related to translation, RNA processing, and neurobiological functions, with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways including ribosome, nucleocytoplasmic transport, pluripotency signaling, and nicotine addiction. Conclusions: These results suggest that environmentally influenced gene expression may contribute to TSD pathogenesis through dysregulation of immune and neuronal pathways. Despite a small sample size, the monozygotic twin design provides strong control for genetic background and identifies significant differences that contribute to the understanding of the underlying molecular mechanisms of TSD. Full article

Traffic sign detection under adverse weather conditions remains challenging due to severe feature degradation caused by rain, fog, and snow, which significantly impairs the performance of existing detection systems. This study presents the CW-DETR (Complex Weather Detection Transformer), an end-to-end detection framework designed to address weather-induced feature deterioration in real-time applications. Building upon the RT-DETR, our approach integrates four key innovations: a multipath feature enhancement network (FPFENet) for preserving fine-grained textures, a Multiscale Edge Enhancement Module (MEEM) for combating boundary degradation, an adaptive dual-stream bidirectional feature pyramid network (ADBF-FPN) for cross-scale feature compensation, and a multiscale convolutional gating module (MCGM) for suppressing semantic–spatial confusion. Extensive experiments on the CCTSDB2021 dataset demonstrate that the CW-DETR achieves 69.0% $AP$ and 94.4% $A{P}_{50}$, outperforming state-of-the-art real-time detectors by 2.3–5.7 percentage points while maintaining computational efficiency (56.8 GFLOPs). A cross-dataset evaluation on TT100K, the TSRD, CNTSSS, and real-world snow conditions (LNTU-TSD) confirms the robust generalization capabilities of the proposed model. These results establish CW-DETR as an effective solution for all-weather traffic sign detection in intelligent transportation systems. Full article

Examining the long-term spatiotemporal distribution of grassland types and their transitions is crucial for better understanding regional and global changes. Most research in this field has examined the spatial distribution, temporal dynamics of grasslands, and their causes as a unified entity. This study predicted the distribution of nine major grassland types in Xinjiang under three climate change scenarios from 2041 to 2100 based on 1980s grassland maps, field data in 2023, and 28 factors. The total area of the nine grassland types showed a decreasing trend from 2041 to 2100. The lowland meadow (LM), temperate meadow steppe (TMS), temperate steppe desert (TSD), temperate desert steppe (TDS), and mountain meadow (MM) expanded, while significant declines occurred in alpine meadow (AM), alpine steppe (AS), temperate desert (TD), and temperate steppe (TS). Among cumulative contribution rate of the 28 factors examined in this study, NDVI, vegetation type, slope, elevation, soil_symbol, soil_ph, Bio1, Bio5, Bio8, Bio9, Bio10, Bio12, Bio13, Bio15, and Bio18 played important roles in most grassland types. LM, TD, and AS grassland were found to be more sensitive to E (environment), while AM, TDS, and TSD were more influenced by T (temperature). The distributions of MM and TMS are significantly influenced by the combined effects of all three categories of factors. For TS, the impacts of both temperature and environmental factors are substantial. These findings provided a robust foundation for conservation planning and the sustainable management of grassland ecosystems in temperate and alpine regions. Full article

Contemporary climate change, driven by anthropogenic greenhouse gas (GHG) emissions, has raised global temperatures by over 1 °C above pre-industrial levels, profoundly altering Earth’s energy balance. In marine turtles, which exhibit temperature-dependent sex determination (TSD), embryonic sex ratios are highly sensitive to nest temperature. Most studies predicting the effects of climate change on turtle sex ratios have used air temperature or sea surface temperature (SST) as proxies for nest temperature, despite limited empirical validation of this assumption. I question the validity of this approach by examining the physical mechanisms of heat transfer within beach soils, including conduction, convection, and radiation, and how they are modulated by factors such as soil texture, moisture, and solar radiation. The analysis highlights that while GHGs increase air temperature through the greenhouse effect, they do not directly alter incoming solar radiation, the principal driver of subsurface temperature. Furthermore, increased air temperature enhances evaporation and soil drying, reducing thermal conductivity and potentially lowering heat penetration into nesting depths. Consequently, air or SST proxies can misrepresent the actual thermal environment of marine turtle nests, leading to inaccurate or even reverse projections of sex ratios under climate change. A mechanistic approach integrating soil heat dynamics and solar radiation is therefore essential for realistic assessments of TSD responses and conservation planning in a warming world. Full article

Background: Chionanthus retusus Lindl. et Paxt., a deciduous tree of the genus Chionanthus (Oleaceae), represents a significant native species and a widely cultivated ornamental. Its tender leaves can be processed into tea, traditionally consumed in southern China under the common name “Nuomi Cha”. Methods: Our team quantified the tea polyphenol content across 150 individual trees of C. retusus and selected three low-polyphenol (ZB_D_14, AQ_2, AQ_1) and three high-polyphenol (SX_3, SXG_D_8, TS_D_13) lines for transcriptome sequencing of their young leaves. The resulting data were analyzed to screen for candidate genes. Subsequently, transgenic plants were constructed, and their tea polyphenol content was determined. Results: A significant difference in tea polyphenol content was confirmed between the high- and low-polyphenol lines. Weighted Gene Co-expression Network Analysis (WGCNA) pinpointed a key module strongly associated with tea polyphenol synthesis, encompassing 432 DEGs, which were predominantly enriched in pathways like phenylpropanoid biosynthesis. A comparative transcriptomic analysis further yielded 84 DEGs (40 up- and 44 down-regulated). Enrichment analysis showed these were primarily involved in flavonoid and phenylpropanoid biosynthesis pathways. Expression profiling of genes in the tea polyphenol biosynthetic pathway indicated that several key genes (e.g., 4CL, CHS, DFR) were highly expressed in the high-content lines. A gene interaction network related to this synthesis identified 20 hub genes (e.g., CrHSP70-14, CrMYB44, CrbHLH92). Functional validation of four hubs (CrMYB44, CrHSP70-14, CrCDC6B, CrRAE1) via tobacco transient transformation assays demonstrated that all four significantly elevated tea polyphenol levels, with CrHSP70-14 overexpression yielding the highest content. Furthermore, stable CrHSP70-14 overexpression transgenic tobacco lines were generated, exhibiting significantly higher leaf tea polyphenol content versus controls. Conclusions: This study identifies multiple regulatory genes involved in C. retusus tea polyphenol biosynthesis, provides initial mechanistic insights, and establishes a molecular foundation for breeding specialized tea cultivars of this species. Full article

Traffic Speed Deflectometer (TSD) measures deflection velocities, normalised by travel speed to obtain deflection slopes. Pavement temperature and travel speed can significantly affect deflection slopes. Therefore, correcting deflection slopes for temperature and speed effects is essential. This study employs three-dimensional (3D) finite element simulations of a three-layer flexible pavement system subjected to moving load at travel speeds from 40 km/h to 80 km/h, while varying the Asphalt Concrete (AC) layers’ thickness from 100 mm to 300 mm and the temperature from 5 °C to 45 °C. The results showed that deflection slopes at 100 mm offset distance could be corrected for the effects of temperature and speed using a correction factor comprising the sum of a parabolic function of temperature and a linear function of speed. At 600 mm and 1500 mm offset distances, simpler correction factors could be established using the sum of linear functions of temperature and speed. The Mean Absolute Percentage Error (MAPE) for all predictions was below 3%, indicating high accuracy. Accurate regression-based equations were also proposed to incorporate AC thickness in predicting the correction factors. The results highlight the potential to correct deflection slopes to a reference temperature and speed by evaluating a range of pavement systems. Full article

Deflection slopes measured by the traffic speed deflectometer (TSD) are being used to backcalculate the moduli of pavement layers. Pavement surface roughness causes variations in tyre load magnitude due to excitation, which affects TSD measurements. In this study, three rough pavement surface profiles over 150 m longitudinal distances were extracted from the Long-Term Pavement Performance (LTPP) programme database. Utilising finite element method (FEM) simulation of the TSD pass at a travel speed of 80 km/h over a three-layer flexible pavement system containing the rough surface profiles and employing the Greenwood Engineering TSD backcalculation tool, it was found that tyre load excitation can lead to backcalculation errors of up to 48%. By obtaining deflection slopes at equal distance intervals along the 150 m pavement profiles, it was found that averaging the deflection slopes across 9 measurement points reduced backcalculation errors to 10%, while increasing the number of measurement points to 28 further lowered the backcalculation errors to 5%. These findings highlight the potential to mitigate the effects of tyre load excitation on TSD backcalculation outputs without relying on strain gauges, which are mounted on modern TSDs to measure instantaneous tyre load magnitudes but are sensitive to environmental conditions and require calibration. Full article

Animal cruelty investigations can be hampered by not knowing when a biological sample was deposited at a crime scene, i.e., the sample’s time-since-deposition (TSD). The goal of this study was to characterize a new signature system for estimating the TSD of canine blood samples based on changes in the autofluorescence spectra of cell populations that occur over time. The results showed that the intensity of cellular autofluorescence measured in two detector channels (523/30 nm and 695/50 nm; 488 nm excitation) could clearly differentiate older blood deposits (i.e., samples with a TSD of either 6 months or 1 year) from younger samples that had a TSD of less than three months. Further, cellular autofluorescence was strongly correlated with time when the sample TSD was between one day and three months, with correlation coefficients ranging between 0.83 and 0.91. A multiple linear regression model based on autofluorescence variation was tested on mock casework samples and yielded residual errors between 2 days and 35 days, with the lowest residuals observed in samples that have a TSD less than 6 days. This information can provide probative leads during an investigation of an illicit canine fighting event or an individual injury and also allow animal cruelty agencies to triage blood samples based on their TSD for downstream analyses. Full article

Urban land-use optimization plays a vital role in mitigating the escalating carbon emissions of rapidly growing cities. This study employs advanced computational intelligence to address urban carbon reduction through optimized spatial configurations. A Deep Reinforcement Learning (DRL) framework is proposed that integrates Points of Interest (POI), Areas of Interest (AOI), and Transportation System Data (TSD) to generate fine-grained carbon emission maps guiding land-use adjustments. In the case study of Hangzhou, China, results show that a carefully designed reward function enables the DRL agent to selectively optimize land-use structures, prioritizing the centralization of residential, dining, and commercial areas to form high-density, mixed-use urban clusters. This spatial reorganization leads to notable reductions in carbon emissions and improvements in resource-use efficiency. The proposed DRL-based framework provides a scientific basis for policy development toward sustainable land-use and urban density optimization. By merging advanced AI techniques with urban planning, this research contributes to the creation of low-carbon, resilient, and environmentally sustainable cities capable of addressing global climate challenges. The optimized DRL agent achieved carbon emission reductions of up to 15% compared to baseline configurations in the Hangzhou case study. Spatial concentration analysis revealed a 23% increase in residential area clustering and 31% increase in commercial zone centralization over 400 training episodes. The PPO-based model demonstrated superior performance compared to genetic algorithm and linear regression baselines, with lower policy loss (converging to <0.01) and critic loss (converging to <0.005) after early stopping at 400 episodes. However, this study is limited by its deterministic environment model, geographic specificity to Hangzhou, and exclusive focus on carbon reduction without incorporating socioeconomic constraints. Full article

Saliva is a biological fluid that can be found at various crime scenes and mainly presents two challenges for the forensic analysis: its identification and the estimation of the time since deposition (TSD). In this study, the performance of Partial Least Squares Regression (PLSR) and Principal Component Regression (PCR) models is compared for estimating the TSD of human saliva stains using Attenuated Total Reflectance Fourier-Transform Infrared Spectroscopy (ATR-FTIR). Saliva samples were obtained from eight donors and deposited on various surfaces, exposed to different environmental conditions (indoor and outdoor) and analyzed over a period ranging from 0 to 212 days. The results indicate that PLSR outperforms PCR in terms of Root Mean Squared Error (RMSE) in all cases. This improvement is particularly evident on paper surfaces, where PLSR reduces the RMSE by 10.45 days under indoor conditions and by 13.47 days under outdoor conditions compared to PCR. On woven surfaces, PLSR improves the RMSE by 3.19 days under indoor conditions and by 8.27 days under outdoor conditions compared to PCR. These results highlight the potential of vibrational spectroscopy combined with chemometric methods for the in situ forensic analysis of biological fluids at crime scenes. Full article

Background and Objectives: Diffuse idiopathic skeletal hyperostosis (DISH)-related spinal fractures with marked anterior distraction are highly unstable and pose substantial surgical challenges. The transdiscal screw for diffuse idiopathic skeletal hyperostosis (TSD) technique has been proposed to enhance fixation strength by penetrating adjacent vertebral endplates; however, its clinical utility in large-displacement cases remained unclear. Materials and Methods: In this retrospective study, we reviewed 21 patients with thoracolumbar DISH-related fractures and an anterior fracture gap ≥ 15 mm, who underwent posterior fixation between 2010 and 2024. 11 patients underwent TSD fixation (TSD group), and 10 underwent conventional fixation without bilateral TSD (control group). Results: The mean number of fused segments did not differ significantly between the groups (5.0 ± 1.4 vs. 5.0 ± 1.3, p = 0.43). Operative time was comparable (164 ± 57 vs. 168 ± 60 min, p = 0.90). Blood loss tended to be lower in the TSD group (306 ± 334 vs. 528 ± 658 mL, p = 0.33). For fracture-gap reduction, the TSD group improved from 17.4 ± 2.3 mm preoperatively to 13.8 ± 4.4 mm postoperatively and 2.0 ± 3.6 mm at final follow-up, while the control group showed less reduction (16.8 ± 2.2, 15.4 ± 1.4, and 7.0 ± 9.1 mm, respectively). Screw loosening occurred in three TSD patients and six controls (p = 0.13). All patients in the TSD group achieved bone union without reoperation, whereas four controls experienced implant backout, three required reoperation, and two failed to achieve bone union (p = 0.035). Conclusions: Posterior fixation using TSD provided reliable stability, maintained reduction, and reduced the risk of implant failure compared with conventional fixation in highly unstable DISH-related fractures with anterior distraction. Although larger prospective studies are needed, TSD may represent a valuable surgical option for this challenging patient population. Full article

Humans learn new tasks without forgetting, but neural networks suffer from catastrophic forgetting when trained sequentially. Dynamic expandable networks attempt to address this by assigning each task its own feature extractor and freezing previous ones to preserve past knowledge. While effective for retaining old tasks, this design leads to rapid parameter growth, and frozen extractors never adapt to future data, often producing irrelevant features that degrade later performance. To overcome these limitations, we propose Task-Sharing Distillation (TSD), which reduces the number of extractors by allowing multiple tasks to share one extractor and consolidating them through distillation. We study two strategies: (1) grouped rolling consolidation, which groups consecutive tasks and consolidates them into a shared extractor, and (2) a fixed-size pooling with similarity-based consolidation, where new tasks are merged into the most compatible extractor in a fixed pool according to prototype similarity. Experiments on the CIFAR-100 and ImageNet-100 datasets show that TSD maintains strong performance across tasks, demonstrating that careful feature sharing is more effective than simply adding more extractors. On ImageNet-100, our method achieves 2.5% higher average accuracy than DER while using fewer feature extractors. Full article

Extreme drought events may become more frequent with climate change. Understanding the impact of extreme drought on grassland ecosystems is therefore crucial for the long-term sustainability of ecosystems. Here, we identified extreme drought events in the Inner Mongolia grasslands of China using long-term standardized precipitation evapotranspiration index (SPEI) data and evaluated drought resistance of the vegetation under extreme drought based on net primary production (NPP). The impact of consecutive extreme drought events and multiple discontinuous one-year extreme drought events on grasslands were further analyzed to investigate the response strategies of different grassland types to different drought conditions. We found that the frequency and area of extreme drought in 2000–2011 were significantly higher than those in 2012–2020, and the Xilingol League region showed the highest frequency of extreme drought events. Under extreme drought, vegetation resistance was positively correlated, where annual precipitation > 300 mm. The mean resistance of different grassland types followed the order: upland meadow (UM) > lowland meadow (LM) > temperate meadow steppe (TMS) > temperate desert (TD) > temperate steppe (TS) > temperate steppe desert (TSD) > temperate desert steppe (TDS). In the analysis of two cases of consecutive two-year extreme drought, all grassland types except TSD and TD showed obvious decreased resistance in the final drought year, with the highest reduction (0.16) in LM during 2010–2011, implying the widespread and significant inhibition of grassland growth by continuous drought. However, under the multiple discontinuous extreme drought events, the resistance of all grassland types showed a fluctuating but an overall increasing trend, suggesting the adaptability of grassland to drought. The results emphasize that management departments should pay more attention to regions with low resistance and enhance the stability of grassland production by increasing the proportion of drought-resistant plants in reaction to future extreme drought scenarios. Full article

Gangliosides are essential for membrane functions, cell recognition, and maintenance of the nervous system. GM2 gangliosidosis is a group of rare genetic lysosomal storage diseases that includes Tay-Sachs disease (TSD), Sandhoff disease (SD), and AB variant. TSD and SD are characterized by deficient β-N-acetyl-hexosaminidase activity. This leads to decreased catabolism of β-N-acetyl-hexosamine-containing ganglioside GM2 in the lysosomes, damage to cells and tissues, and severe neurological symptoms. GM2 is a major ganglioside accumulating in TSD and SD, and is synthesized from GM3 by β1,4-N-acetylgalactosaminyltransferase 1 (B4GALNT1, GM2 synthase). Therapies under development for GM2 gangliosidosis include adeno-associated virus gene therapy, enzyme replacement, and substrate reduction therapy (SRT). The goal of this work was to express and purify human B4GALNT1, characterize its activity, and explore its structural features by protein modeling and substrate docking. We used a panel of synthetic compounds to study their potential inhibition of B4GALNT1 activity. This work can serve to develop SRT for GM2 gangliosidosis. Full article

Objective: To investigate the survival prediction probability of the nomogram from retro-EMBRACE and the T-score in patients with locally advanced cervical cancer (LACC). Materials and Methods: A total of 204 patients with LACC who underwent curative chemoradiotherapy and brachytherapy (BT) between 2010 and 2021 were included in our single-center retrospective study. Clinical records, examinations, and magnetic resonance images (MRI) before and after external beam radiotherapy (EBRT) were retrospectively reviewed to obtain information on age, tumor size, parametrial involvement, ureteral involvement, bladder invasion, uterine involvement, high-risk clinical target volume at the first brachytherapy application, lymph node involvement, vaginal involvement, recurrence, metastasis, and last follow-up. The 5-year overall survival probabilities of the patients were determined by nomogram. T-score was calculated separately at diagnosis (TS_D) and brachytherapy (TS_BT), and their effects on local recurrence-free survival, disease-free survival, and overall survival were analyzed. Results: The median age was 52 (29–89). The 5-year survival rate of the patients was calculated to be 90.18%. The median nomogram’s survival estimate for 60 months was 70.35% (20.9–87.1). The median TS_D and TS_BT were 5.5 (1–16) and 1 (0–6), respectively. According to the multivariate Cox regression models, TS_D (HR = 1.203, 95% CI 1.021–1.417, p = 0.024) was significantly associated with local recurrence-free survival. Conclusions: This study demonstrated that the nomogram’s predictions for 60-month overall survival are underestimates. Prognosis can be estimated using the TS_D, which can be easily obtained with a clinical examination and detailed MRI examination. Full article