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Abstract Background The association between remnant cholesterol (RC) and diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM) remains unclear. Morphological changes in retinal vessels have been reported to predict vascular complications of diabetes, including DR. Methods This cross-sectional study included 6535 individuals with T2DM. The RC value was calculated using the recognized formula. The retinal vascular parameters were measured using fundus photography. The independent relationship between RC and DR was analyzed using binary logistic regression models. Multiple linear regression and subgroup analyses were employed to investigate the link between RC and vascular parameters, including the retinal arteriolar diameter (CRAE), venular diameter (CRVE), and fractal dimension (Df). Mediation analysis was performed to assess whether the vascular morphology could explain the association between RC and DR. Results RC was independently associated with DR in patients with a longer duration of T2DM (> 7 years). Patients with the highest quartile RC levels had larger CRAE (5.559 [4.093, 7.025] μm), CRVE (7.620 [5.298, 9.941] μm) and Df (0.013 [0.009, 0.017]) compared with patients with the lowest quartile RC levels. Results were robust across different subgroups. The association between RC and DR was mediated by CRVE (0.020 ± 0.005; 95% confidence interval: 0.012–0.032). Conclusions RC may be a risk factor for DR among those who have had T2DM for a longer period of time. Higher RC levels were correlated with wider retinal arterioles and venules as well as higher Df, and it may contribute to DR through the dilation of retinal venules.

BackgroundMandibuloacral dysplasia (MAD) syndrome is a rare genetic disease. Several progeroid syndromes including mandibuloacral dysplasia type A (MADA), mandibuloacral dysplasia type B(MADB), Hutchinson-Gilford progeria (HGPS) and mandibular hypoplasia, deafness, and lipodystrophy syndrome (MDPL) have been reported previously. A novel MAD progeroid syndrome (MADaM) has recently been reported. So far, 7 cases of MADaM diagnosed with molecular diagnostics have been reported in worldwide. In the Chinese population, cases of MAD associated with the MTX2 variant have never been reported.MethodsThe clinical symptoms and the genetic analysis were identified and investigated in patients presented with the disease. In addition, we analyzed and compared 7 MADaM cases reported worldwide and summarized the progeroid syndromes reported in the Chinese population to date.ResultsThe present study reports a case of a novel homozygous mutation c.378 + 1G > A in the MTX2 gene, which has not been previously reported in the literature. Patients present with early onset and severe symptoms and soon after birth are found to have growth retardation. In addition to the progeroid features, skeletal deformities, generalized lipodystrophy reported previously, and other multisystem involvement, e.g. hepatosplenic, renal, and cardiovascular system, this case was also reported to have combined hypogammaglobulinemia. She has since been admitted to the hospital several times for infections. Among 22 previously reported progeroid syndromes, 16/22 were MADA or HGPS caused by LMNA gene mutations, and the homozygous c.1579C > T (p.R527C) mutation may be a hot spot mutation for MAD in the Chinese population. MAD and HGPS mostly present in infancy with skin abnormalities or alopecia, MDPL mostly presents in school age with growth retardation as the first manifestation, and is often combined with an endocrine metabolism disorder after several decades.ConclusionThis is the first case of MAD syndrome caused by mutations in MTX2 gene reported in the Chinese population. MTX2 gene c.378 + 1G > A homozygous mutation has not been previously reported and the report of this patient expands the spectrum of MTX2 mutations. In addition, we summarized the genotypes and clinical characteristics of patients with progeroid syndromes in China.

Abstract The Arctic is warming at a rate four times the global average, while also being exposed to other global environmental changes, resulting in widespread vegetation and ecosystem change. Integrating functional trait-based approaches with multi-level vegetation, ecosystem, and landscape data enables a holistic understanding of the drivers and consequences of these changes. In two High Arctic study systems near Longyearbyen, Svalbard, a 20-year ITEX warming experiment and elevational gradients with and without nutrient input from nesting seabirds, we collected data on vegetation composition and structure, plant functional traits, ecosystem fluxes, multispectral remote sensing, and microclimate. The dataset contains 1,962 plant records and 16,160 trait measurements from 34 vascular plant taxa, for 9 of which these are the first published trait data. By integrating these comprehensive data, we bridge knowledge gaps and expand trait data coverage, including on intraspecific trait variation. These data can offer insights into ecosystem functioning and provide baselines to assess climate and environmental change impacts. Such knowledge is crucial for effective conservation and management in these vulnerable regions.

Abstract Background Great variation has been observed in the composition of the normal microbiota of the ocular surface, and therefore, in addition to differences in detection techniques, the method of collecting ocular surface specimens has a significant impact on the test results.The goal of this study is to ascertain whether the eye surface microbial communities detected by two different sampling methods are consistent and hence explore the feasibility of using tear test paper instead of conjunctival swabs to collect eye surface samples for microbial investigation. Materials and methods From July 15, 2021, to July 30, 2021, nonirritating tear test strips and conjunctival swabs of both eyes were used in 158 elderly people (> 60 years old) (79 diabetic and 79 nondiabetic adults) in Xinjing Community for high-throughput sequencing of the V3-V4 region of the 16S rRNA gene. The composition of the microbial communities in tear test paper and conjunctival swab samples was analyzed. Results There was no statistically significant difference in Alpha diversity of ocular surface microorganisms represented by tear strip and conjunctival swab in diabetic group (P > 0.05), but there was statistically significant difference in Alpha diversity of ocular surface microorganisms detected by tear strip and conjunctival swab in nondiabetic group (P 0.05). Conclusions Tear test paper and conjunctival swabs detect different compositions of microbes through two different techniques of eye surface microbe sampling. Tear test paper cannot completely replace conjunctival swab specimens for the study of microbes related to eye surface diseases.

Lithium-ion batteries (LIBs) have recently become popular for energy storage due to their high energy density, storage capacity, and long-term cycle life. Although binders make up only a small proportion of LIBs, they have become the key to promoting the transformation of the battery preparation process. Along with the development of binders, the battery manufacturing process has evolved from the conventional slurry-casting (SC) process to a more attractive solvent-free (SF) method. Compared with traditional LIBs manufacturing method, the SF method could dramatically reduce and increase the energy density due to the reduced preparation steps and enhanced electrode loading. Polytetrafluoroethylene (PTFE), as a typical binder, has played an important role in fabricating high-performance LIBs, particularly in regards to the SF technique. In this paper, the development history and application status of PTFE binder was introduced, and then its contributions and the inherent problems involved in the SF process were described and analyzed. Finally, the viewpoints concerning the future trends for PTFE-based SF manufacturing methods were also discussed. We hope this work can inspire future research concerning high-quality SF binders and assist in promoting the evolution of the SF manufacturing technology in regards to LIBs.

Synthetic cannabinoid receptor agonists (SCRAs) continue to make up a significant portion new psychoactive substances (NPS) detected and seized worldwide. Due to their often potent activation of central cannabinoid receptors in vivo, use of SCRAs can result in severe intoxication, in addition to other adverse health effects. Recent detections of AB-4CN-BUTICA, MMB-4CN-BUTINACA, MDMB-4F-BUTICA and MDMB-4F-BUTINACA mark a continuation in the appearance of SCRAs bearing novel tail substituents. The proactive characterization campaign described here has facilitated the detection of several new SCRAs in toxicological case work. Here we detail the synthesis, characterization, and pharmacological evaluation of recently detected SCRAs, as well as a systematic library of 32 compounds bearing head, tail, and core group combinations likely to appear in future. In vitro radioligand binding assays revealed most compounds showed moderate to high affinity at both CB1 (pKi = < 5 to 8.89 ± 0.09 M) and CB2 (pKi = 5.49 ± 0.03 to 9.92 ± 0.09 M) receptors. In vitro functional evaluation using a fluorescence-based membrane potential assay showed that most compounds were sub-micromolar to sub-nanomolar agonists at CB1 (pEC50 = < 5 to 9.48 ± 0.14 M) and CB2 (pEC50 = 5.92 ± 0.16 to 8.64 ± 0.15 M) receptors. An in silico receptor-ligand docking approach was utilized to rationalize binding trends for CB2 with respect to the tail substituent, and indicated that rigidity in this region (i.e., 4-cyanobutyl) was detrimental to affinity.

Soil thickness determines the soil productivity in the black soil region of northeast China, which is important for national food security. Existing information on the spatial variation of black soil thickness is inadequate. In this paper, we propose a model framework for spatial estimation of the black soil thickness at the watershed scale by integrating field observations, unmanned aerial vehicle variations of topography, and satellite variations of vegetation with the aid of random forest. We sampled 141 sample profiles over a watershed and identified the black soil thickness based on indices of the mollic epipedon. Topographic variables were derived from a digital elevation model and vegetation variables were derived from Landsat 8 imagery. Random forest was used to determine the relationship between black soil thickness and environmental variables. The resulting model explained 61% of the black soil thickness spatial variation, which was more than twice that of traditional interpolation methods (ordinary kriging, universal kriging and inverse distance weighting). Topographic variables contributed the most toward explaining the thickness, followed by vegetation indices. The black soil thickness over the watershed had a clear catenary soil pattern, with thickest black soil in the low depositional areas and thinnest at the higher elevations that drain into the low areas. The proposed model framework will improve estimates of soil thickness in the region of our study.

A novel prefabricated strengthening structure (NPSS) is proposed to improve the vertical stiffness and load-bearing capacity of existing short-span bridges for heavier axle-load trains passing through. The strengthening principle of the NPSS is revealed through theoretical derivation. A refined calculation model is prepared to investigate the effects of two important parameters on the structural behavior of the bridge, including the support stiffness and the installation location of the NPSS. The calculation model is also verified with four-point bending test of a bridge removed from a heavy-haul railway. With the calculation model and the response surface methodology (RSM), the functional relationships among the crucial mechanical indexes of the bridge and the two parameters of the NPSS are methodically established. Thus, the optimal values of the parameters are determined via a multi-objective optimization model and the analysis hierarchy process-fuzzy comprehensive evaluation method. Furthermore, the feasibility of the optimal parameters is appropriately verified based on simulations of the vehicle–track–bridge dynamics. The existence of the NPSS with optimal parameters could enhance the vertical stiffness of the bridge by 21.0% and bearing capacity by 19.5%. In addition, it could reduce the midspan dynamic deflection amplitude by 23.4% and vertical vibration acceleration amplitude of the bridge by 25.2%. The results of the study are expected to contribute to the capacity development and rehabilitation of existing heavy-haul railways with low cost and convenient construction without railway outage.

Abstract Neutral antagonists of GPCRs remain relatively rare—indeed, a large majority of GPCR antagonists are actually inverse agonists. The synthetic cannabinoid receptor agonist (SCRA) EG‐018 was recently reported as a low efficacy cannabinoid receptor agonist. Here we report a comparative characterization of EG‐018 and 13 analogues along with extant putative neutral antagonists of CB1. In HEK cells stably expressing human CB1, assays for inhibition of cAMP were performed by real‐time BRET biosensor (CAMYEL), G protein cycling was quantified by [35S]GTPγS binding, and stimulation of pERK was characterized by AlphaLISA (PerkinElmer). Signaling outcomes for the EG‐018 analogues were highly variable, ranging from moderate efficacy agonism with high potency, to marginal agonism at lower potency. As predicted by differing pathway sensitivities to differences in ligand efficacy, most EG‐018‐based compounds were completely inactive in pERK alone. The lowest efficacy analogue in cAMP assays, 157, had utility in antagonism assay paradigms. Developing neutral antagonists of the CB1 receptor has been a long‐standing research goal, and such compounds would have utility both as research tools and in therapeutics. Although these results emphasize again the importance of system factors in determining signaling outcomes, some compounds characterized in this study appear among the lowest efficacy agonists described to date and therefore suggest that development of neutral antagonists is an achievable goal for CB1.

The transcription factor Bach2 which is predominantly expressed in B and T lymphocytes represses the expression of genes by forming heterodimers with small Maf and Batf proteins and binding to the corresponding sequence on the DNA. In this way, Bach2 serves as a highly conserved repressor which controls the terminal differentiation and maturation of both B and T lymphocytes. It is required for class switch recombination (CSR) and somatic hypermutation (SHM) of immunoglobulin genes in activated B cells, and its function in B cell differentiation has been well-described. Furthermore, emerging data show that Bach2 regulates transcriptional activity in T cells at super enhancers or regions of high transcriptional activity, thus stabilizing immunoregulatory capacity and maintaining T cell homeostasis. Bach2 is also critical for the formation and function of CD4+ T cell lineages (Th1, Th2, Th9, Th17, T follicular helper (Tfh), and regulatory T (Treg) cells). Genetic variations within Bach2 locus are associated with numerous immune-mediated diseases including multiple sclerosis (MS), rheumatoid arthritis (RA), chronic pancreatitis (CP), type 2 chronic airway inflammation, inflammatory bowel disease (IBD), and type 1 diabetes. Here, we reveal a critical role of Bach2 in regulating T cell biology and the correlation with these immune-mediated diseases.

The Arctic is warming twice as fast as the rest of the planet, leading to rapid changes in species composition and plant functional trait variation. Landscape-level maps of vegetation composition and trait distributions are required to expand spatially-limited plot studies, overcome sampling biases associated with the most accessible research areas, and create baselines from which to monitor environmental change. Unmanned aerial vehicles (UAVs) have emerged as a low-cost method to generate high-resolution imagery and bridge the gap between fine-scale field studies and lower resolution satellite analyses. Here we used field spectroscopy data (400–2500 nm) and UAV multispectral imagery to test spectral methods of species identification and plant water and chemistry retrieval near Longyearbyen, Svalbard. Using the field spectroscopy data and Random Forest analysis, we were able to distinguish eight common High Arctic plant tundra species with 74% accuracy. Using partial least squares regression (PLSR), we were able to predict corresponding water, nitrogen, phosphorus and C:N values ( r ^2 = 0.61–0.88, RMSEmean = 12%–64%). We developed analogous models using UAV imagery (five bands: Blue, Green, Red, Red Edge and Near-Infrared) and scaled up the results across a 450 m long nutrient gradient located underneath a seabird colony. At the UAV level, we were able to map three plant functional groups (mosses, graminoids and dwarf shrubs) at 72% accuracy and generate maps of plant chemistry. Our maps show a clear marine-derived fertility gradient, mediated by geomorphology. We used the UAV results to explore two methods of upscaling plant water content to the wider landscape using Sentinel-2A imagery. Our results are pertinent for high resolution, low-cost mapping of the Arctic.

Detecting moving objects in a video sequence is an important problem in many vision-based applications. In particular, detecting moving objects when the camera is moving is a difficult problem. In this study, we propose a symmetric method for detecting moving objects in the presence of a dynamic background. First, a background compensation method is used to detect the proposed region of motion. Next, in order to accurately locate the moving objects, we propose a convolutional neural network-based method called YOLOv3-SOD for detecting all objects in the image, which is lightweight and specifically designed for small objects. Finally, the moving objects are determined by fusing the results obtained by motion detection and object detection. Missed detections are recalled according to the temporal and spatial information in adjacent frames. A dataset is not currently available specifically for moving object detection and recognition, and thus, we have released the MDR105 dataset comprising three classes with 105 videos. Our experiments demonstrated that the proposed algorithm can accurately detect moving objects in various scenarios with good overall performance.

Cloud removal is a prerequisite for the application of Landsat datasets, as such satellite images are invariably contaminated by clouds. Clouds affect the transmission of radiation signal to different degrees because of their different thicknesses, shapes, heights and distributions. Existing methods utilize pixel replacement to remove thick clouds and pixel correction techniques to rectify thin clouds in order to retain the land surface information in contaminated pixels. However, a major limitation of these methods refers to their deficiency in retrieving land surface reflectance when both thick clouds and thin clouds exist in the images, as the two types of clouds differ in the transmission of radiation signal. As most remotely sensed images show rather complex cloud contamination patterns, an efficient method to alleviate both thin and thick cloud effects is in need of development. To this end, the paper proposes a new method to rectify cloud contamination based on the cloud detection of iterative haze-optimized transformation (IHOT) and the cloud removal of cloud trajectory (IHOT-Trajectory). The cloud trajectory is able to take consideration of signal transmission for different levels of cloud contamination, which characterizes the spectral response of a certain type of land cover under increasing cloud thickness. Specifically, this method consists in four steps. First, the cloud thicknesses of contaminated pixels are estimated by the IHOT. Second, areas affected by cloud shadows are marked. Third, cloud trajectories are fitted with the aid of neighboring similar pixels under different cloud thickness. Last, contaminated areas are rectified according to the relationship between the land surface reflectance and the IHOT. The experimental results indicate that the proposed approach is able to effectively remove both the thin and thick clouds and erase the cloud shadows of Landsat images under different scenarios. In addition, the proposed method was compared with the dark object subtraction (DOS), the modified neighborhood similar pixel interpolator (MNSPI) and the multitemporal dictionary learning (MDL) methods. Quantitative assessments show that the IHOT-Trajectory method is superior to the other cloud removal methods overall. For specific spectral bands, the proposed method performs better than other methods in visible bands, whereas it does not necessarily perform better in infrared bands.

Diabetic gastroparesis, a common complication of type 2 diabetes (T2DM), presents a significant treatment challenge. FoxiangSan is emerging as a potential therapy. FoxiangSan is a traditional Chinese medicine formula with the potential for treating diabetic gastroparesis by modulating gut microbiota and cAMP/PKA signaling pathways. This study explores the mechanisms behind FoxiangSan's effects on T2DM-induced gastroparesis, focusing on its impact on gut microbiota and the cAMP/PKA pathway. A rat model of type 2 diabetic gastroparesis was established through a high-fat diet and streptozotocin (STZ) injection, and the effects of FoxiangSan were assessed. Additionally, protein expression related to the cAMP/PKA pathway was examined, and FoxiangSan's influence on gut microbiota was studied using 16S rRNA sequencing. FoxiangSan significantly alleviated hyperglycemia, improved gastric pathology in rats with gastroparesis, enhanced the expression of 5-HT4, cAMP, PKA, and pPKA in the gastric antrum, and rebalanced gut microbiota. FoxiangSan demonstrates the therapeutic potential for T2DM-associated gastroparesis by modulating the cAMP/PKA pathway and gut microbiota.

Abstract Introduction There is a high morbidity and mortality rate in mechanical trauma (MT)-induced hepatic injury. Currently, the molecular mechanisms underlying liver MT are largely unclear. Exploring the underlying mechanisms and developing safe and effective medicines to alleviate MT-induced hepatic injury is an urgent requirement. The aim of this study was to reveal the role of mitochondria-associated ER membranes (MAMs) in post-traumatic liver injury, and ascertain whether melatonin protects against MT-induced hepatic injury by regulating MAMs. Methods Hepatic mechanical injury was established in Sprague–Dawley rats and primary hepatocytes. A variety of experimental methods were employed to assess the effects of melatonin on hepatic injury, apoptosis, MAMs formation, mitochondrial function and signaling pathways. Results Significant increase of IP3R1 expression and MAMs formation were observed in MT-induced hepatic injury. Melatonin treatment at the dose of 30 mg/kg inhibited IP3R1-mediated MAMs and attenuated MT-induced liver injury in vivo. In vitro, primary hepatocytes cultured in 20% trauma serum (TS) for 12 h showed upregulated IP3R1 expression, increased MAMs formation and cell injury, which were suppressed by melatonin (100 μmol/L) treatment. Consequently, melatonin suppressed mitochondrial calcium overload, increased mitochondrial membrane potential and improved mitochondrial function under traumatic condition. Melatonin’s inhibitory effects on MAMs formation and mitochondrial calcium overload were blunted when IP3R1 was overexpressed. Mechanistically, melatonin bound to its receptor (MR) and increased the expression of phosphorylated ERK1/2, which interacted with FoxO1 and inhibited the activation of FoxO1 that bound to the IP3R1 promoter to inhibit MAMs formation. Conclusion Melatonin prevents the formation of MAMs via the MR-ERK1/2-FoxO1-IP3R1 pathway, thereby alleviating the development of MT-induced liver injury. Melatonin-modulated MAMs may be a promising therapeutic therapy for traumatic hepatic injury. Graphical Abstract

Synthetic cannabinoid receptor agonists (SCRAs) continue to make up a significant portion new psychoactive substances (NPS) detected and seized worldwide. Due to their often potent activation of central cannabinoid receptors in vivo, use of SCRAs can result in severe intoxication, in addition to other adverse health effects. Recent detections of AB-4CN-BUTICA, MMB-4CN-BUTINACA, MDMB-4F-BUTICA and MDMB-4F-BUTINACA mark a continuation in the appearance of SCRAs bearing novel tail substituents. The proactive characterization campaign described here has facilitated the detection of several new SCRAs in toxicological case work. Here we detail the synthesis, characterization, and pharmacological evaluation of recently detected SCRAs, as well as a systematic library of 32 compounds bearing head, tail, and core group combinations likely to appear in future. In vitro radioligand binding assays revealed most compounds showed moderate to high affnity at both CB1 (pKi = < 5 to 8.89 ± 0.09M) and CB2 (pKi = 5.49 ± 0.03 to 9.92 ± 0.09M) receptors. In vitro functional evaluation using a fluorescence-based membrane potential assay showed that most compounds were sub-micromolar to sub-nanomolar agonists at CB1 (pEC50 = < 5 to 9.48 ± 0.14M) and CB2 (pEC50 = 5.92 ± 0.16 to 8.64 ± 0.15M) receptors. An in silico receptor-ligand docking approach was utilized to rationalize binding trends for CB2 with respect to the tail substituent, and indicated that rigidity in this region (i.e., 4-cyanobutyl) was detrimental to affnity. [ABSTRACT FROM AUTHOR]

Semantic segmentation is currently a hot topic in remote sensing image processing. There are extensive applications in land planning and surveying. Many current studies combine Convolutional Neural Networks (CNNs), which extract local information, with Transformers, which capture global information, to obtain richer information. However, the fused feature information is not sufficiently enriched and it often lacks detailed refinement. To address this issue, we propose a novel method called the Multi-View Feature Fusion and Rich Information Refinement Network (MFRNet). Our model is equipped with the Multi-View Feature Fusion Block (MAFF) to merge various types of information, including local, non-local, channel, and positional information. Within MAFF, we introduce two innovative methods. The Sliding Heterogeneous Multi-Head Attention (SHMA) extracts local, non-local, and positional information using a sliding window, while the Multi-Scale Hierarchical Compressed Channel Attention (MSCA) leverages bar-shaped pooling kernels and stepwise compression to obtain reliable channel information. Additionally, we introduce the Efficient Feature Refinement Module (EFRM), which enhances segmentation accuracy by interacting the results of the Long-Range Information Perception Branch and the Local Semantic Information Perception Branch. We evaluate our model on the ISPRS Vaihingen and Potsdam datasets. We conducted extensive comparison experiments with state-of-the-art models and verified that MFRNet outperforms other models.

The preparation of a novel phosphapalladacycle derived from (di-tert-butyl)(diphenylmethyl)phosphine in the optically active form was observed to display a very strong tendency to remain in the ortho-palladated state with a palladacycle Pd-C bond which could not be permanently ruptured is presented.