Bioinformatic Analysis of the Significance of the KIR2DL4 Gene in Recurrent Implantation Failure.

Related studies have pointed out that Killer immunoglobulin-like receptor 2DL4 (KIR2DL4) was associated with vascular remodeling in early pregnancy, and it might play an important role in immunity. In this study, recurrent implantation failure (RIF)-related GSE58144 dataset was extracted from the Gene Expression Omnibus (GEO) database. Firstly, the immune micro-environment analyses were conducted to analyze the pathogenesis of KIR2DL4 in RIF. Then, the gene set enrichment analysis (GSEA) was performed to investigate the function of KIR2DL4. Moreover, the TF-mRNA-miRNA and the co-expression networks were constructed to reveal the potential regulation of KIR2DL4. Furthermore, the genes that were associated with KIR2DL4 and differentially expressed in RIF were obtained and defined as key genes, and the functions of these genes were further explored. KIR2DL4 could be used for clinical diagnosis of RIF, and it was correlated with the changes in the immune micro-environment in RIF. From the perspective of function, KIR2DL4 was associated with complement and coagulation cascades, natural killer cell-mediated cytotoxicity, etc. Moreover, the TF-mRNA-miRNA regulatory network was constructed with KIR2DL4, 9 TFs, and 29 miRNAs. Furthermore, KIR2DL4, ACSM1, IL2RB, and PTPN11 were screened as key genes, which were associated with immune-related functions. This study deeply analyzed the function of KIR2DL4 and its role in RIF, and we found that STAT1 might up-regulate KIR2DL4 by INF-γ/JAK2/STAT1 signaling pathway. Besides, over-expressed KIR2DL4 in the mid-luteal endometrium might influence embryo implantation by affecting the embryo implantation microenvironment, which might help deepen the understanding of the molecular mechanism of RIF.

Evaluation of alanine aminotransferase/aspartate aminotransferase ratio and high-density lipoprotein for predicting neonatal adverse outcomes associated with intrahepatic cholestasis of pregnancy.

Background: To determine the association between lipid metabolism and intrahepatic cholestasis of pregnancy (ICP), and explore the value of maternal alanine aminotransferase/aspartate aminotransferase (ALT/AST) and high-density lipoprotein (HDL) in predicting adverse neonatal outcomes in women with ICP. Methods: A total of 147 pregnant women with ICP admitted to The Fourth Hospital of Shijiazhuang and 120 normal pregnant women in the same period were selected in this study. The Mann-Whitney U test and Chi-square tests were used to compare the differences in clinical data. Multivariate logistic regression was used to analyze the relationship between ALT/AST and the occurrence of adverse pregnancy outcomes in patients with ICP. The combined predictive value of ALT/AST and HDL was determined by receiver operating characteristic (ROC) curve analysis. Results: Among 147 women with ICP, 122 women had total bile acid (TBA) levels of 10-39.9 µmol/L, and 25 had TBA ≥ 40 µmol/L. There was significantly lower gestational age in patients with severe ICP than in those with mild and control groups (all p < 0.05), and the weight of newborns in the maternal ICP group was significantly lower than in the control group (p < 0.05). Increasing TBA levels was associated with higher AST, ALT, ALT/AST, and lower HDL level (all p < 0.05). Meanwhile, higher levels of ALT/AST was positively associated with neonatal hyperbilirubinemia [adjusted odds ratio (AOR) = 4.019, 95% CI [1.757-9.194, p = 0.001] and cardiac injury [AOR = 3.500, 95% CI [1.535-7.987], p = 0.003]. HDL was a significant protective factor for neonatal hyperbilirubinemia and cardiac injury [AOR = 0.315, 95% CI [0.126-0.788], p = 0.014; AOR = 0.134 (0.039-0.461), p = 0.001]. The area under the ROC curve (AUC) for prediction of neonatal hyperbilirubinemia by ALT/AST combined with HDL was 0.668 [95% CI [56.3-77.3%], p = 0.002], and the sensitivity and specificity were 47.1% and 84.0%, respectively. To predict neonatal cardiac injury, the AUC value was 0.668 [95% CI [56.4-77.1%], p = 0.002], with sensitivity and specificity were 41.2% and 87.1%, respectively. Conclusions: The levels of higher ALT/AST and lower HDL were significantly associated with the risk of ICP-related adverse neonatal outcomes. Moreover, ALT/AST combined with HDL has moderate clinical value in predicting the adverse outcomes of neonatal hyperbilirubinemia and cardiac injury.

Physiological and transcriptomic responses of silkworms to graphene oxide exposure.

The growing use of nanomaterials has sparked significant interest in assessing the insect toxicities of nanoparticles. The silkworm, as an economically important insect, serves as a promising model for studying how insects respond to harmful substances. Here, we conducted a comprehensive investigation on the impact of graphene oxide (GO) on silkworms using a combination of physiological and transcriptome analyses. GO can enter the midguts and posterior silk glands of silkworms. High GO concentrations (> 25 mg/L) significantly (P < 0.01) inhibited larval growth. Additionally, GO (> 5 mg/L) significantly reduced the cocooning rate, and GO (> 15 mg/L) hindered oviduct development and egg laying in silkworms. GO increased the reactive oxygen species content and regulated catalase activity, suggesting that it may affect insect growth by regulating reactive oxygen detoxification. The transcriptome data analysis showed that 35 metabolism-related genes and 20 ribosome biogenesis-related genes were differentially expressed in response to GO, and their expression levels were highly correlated. Finally, we propose that a Ribosome biogenesis-Metabolic signaling network is involved in responses to GO. The research provides a new perspective on the molecular responses of insects to GO.

A Study on Dimensionality Reduction and Parameters for Hyperspectral Imagery Based on Manifold Learning.

With the rapid advancement of remote-sensing technology, the spectral information obtained from hyperspectral remote-sensing imagery has become increasingly rich, facilitating detailed spectral analysis of Earth's surface objects. However, the abundance of spectral information presents certain challenges for data processing, such as the "curse of dimensionality" leading to the "Hughes phenomenon", "strong correlation" due to high resolution, and "nonlinear characteristics" caused by varying surface reflectances. Consequently, dimensionality reduction of hyperspectral data emerges as a critical task. This paper begins by elucidating the principles and processes of hyperspectral image dimensionality reduction based on manifold theory and learning methods, in light of the nonlinear structures and features present in hyperspectral remote-sensing data, and formulates a dimensionality reduction process based on manifold learning. Subsequently, this study explores the capabilities of feature extraction and low-dimensional embedding for hyperspectral imagery using manifold learning approaches, including principal components analysis (PCA), multidimensional scaling (MDS), and linear discriminant analysis (LDA) for linear methods; and isometric mapping (Isomap), locally linear embedding (LLE), Laplacian eigenmaps (LE), Hessian locally linear embedding (HLLE), local tangent space alignment (LTSA), and maximum variance unfolding (MVU) for nonlinear methods, based on the Indian Pines hyperspectral dataset and Pavia University dataset. Furthermore, the paper investigates the optimal neighborhood computation time and overall algorithm runtime for feature extraction in hyperspectral imagery, varying by the choice of neighborhood k and intrinsic dimensionality d values across different manifold learning methods. Based on the outcomes of feature extraction, the study examines the classification experiments of various manifold learning methods, comparing and analyzing the variations in classification accuracy and Kappa coefficient with different selections of neighborhood k and intrinsic dimensionality d values. Building on this, the impact of selecting different bandwidths t for the Gaussian kernel in the LE method and different Lagrange multipliers λ for the MVU method on classification accuracy, given varying choices of neighborhood k and intrinsic dimensionality d, is explored. Through these experiments, the paper investigates the capability and effectiveness of different manifold learning methods in feature extraction and dimensionality reduction within hyperspectral imagery, as influenced by the selection of neighborhood k and intrinsic dimensionality d values, identifying the optimal neighborhood k and intrinsic dimensionality d value for each method. A comparison of classification accuracies reveals that the LTSA method yields superior classification results compared to other manifold learning approaches. The study demonstrates the advantages of manifold learning methods in processing hyperspectral image data, providing an experimental reference for subsequent research on hyperspectral image dimensionality reduction using manifold learning methods.

Tunable Light-Responsive Polyurethane-urea Elastomer Driven by Photochemical and Photothermal Coupling Mechanism.

Light-driven soft actuators based on photoresponsive materials can be used to mimic biological motion, such as hand movements, without involving rigid or bulky electromechanical actuations. However, to our knowledge, no robust photoresponsive material with desireable mechanical and biological properties and relatively simple manufacture exists for robotics and biomedical applications. Herein, we report a new visible-light-responsive thermoplastic elastomer synthesized by introducing photoswitchable moieties (i.e., azobenzene derivatives) into the main chain of poly(ε-caprolactone) based polyurethane urea (PAzo). A PAzo elastomer exhibits controllable light-driven stiffness softening due to its unique nanophase structure in response to light, while possessing excellent hyperelasticity (stretchability of 575.2%, elastic modulus of 17.6 MPa, and strength of 44.0 MPa). A bilayer actuator consisting of PAzo and polyimide films is developed, demonstrating tunable bending modes by varying incident light intensities. Actuation mechanism via photothermal and photochemical coupling effects of a soft-hard nanophase is demonstrated through both experimental and theoretical analyses. We demonstrate an exemplar application of visible-light-controlled soft "fingers" playing a piano on a smartphone. The robustness of the PAzo elastomer and its scalability, in addition to its excellent biocompatibility, opens the door to the development of reproducible light-driven wearable/implantable actuators and lightweight soft robots for clinical applications.

New-onset atrial fibrillation following arteriovenous fistula increases adverse clinical events in dialysis patients with end-stage renal disease.

Background: End-stage renal disease (ESRD) patients have a high potential cardiovascular burden, and cardiovascular disease (CVD) is the leading cause of death in maintenance haemodialysis (MHD) patients. Arteriovenous fistula (AVF) is the preferred vascular access for MHD patients, but AVF significantly affects the haemodynamics of the cardiovascular system, leading to or exacerbating CVD, including atrial fibrillation (AF). This study aimed to evaluate the impact of AVF on cardiac function, especially of the left atrium (LA), in patients with ESRD and to further explore the relationship between AVF establishment and the occurrence of AF. Methods: We selected 1,107 ESRD patients on haemodialysis using AVF and 550 patients with tunneled-cuffed catheters (TCC) admitted between January 2016 and December 2022 for follow-up to compare the rate of AF between the two groups. A total of 153 patients in the AVF group with complete information (clinical data, echocardiographic and biochemical indices, and other data) were enrolled and retrospectively analysed for risk factors for the development of AF and were followed up for adverse clinical outcomes (including all-cause death, cardiac death, readmission due to heart failure, and stroke). Results: The incidence of new-onset AF was higher in the AVF group than the TCC group after dialysis access was established (16.30% vs. 5.08%, P < 0.001). Echocardiography showed that the LA anteroposterior diameter increased (P < 0.001) and the incidence of AF increased from 11.76% to 26.14% (P = 0.001) after AVF establishment. Multivariate logistic regression analysis showed that age and LA enlargement were independent risk factors for new-onset AF after AVF establishment (P < 0.05). Adverse clinical outcomes were more common in patients with AF than in patients without AF (P < 0.001). Multivariate Cox risk regression analysis suggested that new-onset AF (HR = 4.08, 95% CI: 2.00-8.34, P < 0.001) and left ventricular systolic dysfunction (HR = 2.42, 95% CI: 1.20-4.88, P = 0.01) after AVF establishment were independent risk factors for adverse clinical outcomes. Conclusion: LA enlargement after AVF establishment is associated with a significant increase in the incidence of AF, in addition, AF which is as an important influential factor in patients with MHD combined other systemic diseases might increase adverse clinical events. Clinical Trial Registration: (NCT06199609).

Unraveling the role of PlARF2 in regulating deed formancy in Paeonia lactiflora.

MAIN CONCLUSION: PlARF2 can positively regulate the seed dormancy in Paeonia lactiflora Pall. and bind the RY cis-element. Auxin, a significant phytohormone influencing seed dormancy, has been demonstrated to be regulated by auxin response factors (ARFs), key transcriptional modulators in the auxin signaling pathway. However, the role of this class of transcription factors (TFs) in perennials with complex seed dormancy mechanisms remains largely unexplored. Here, we cloned and characterized an ARF gene from Paeonia lactiflora, named PlARF2, which exhibited differential expression levels in the seeds during the process of seed dormancy release. The deduced amino acid sequence of PlARF2 had high homology with those of other plants and contained typical conserved Auxin_resp domain of the ARF family. Phylogenetic analysis revealed that PlARF2 was closely related to VvARF3 in Vitis vinifera. The subcellular localization and transcriptional activation assay showed that PlARF2 is a nuclear protein possessing transcriptional activation activity. The expression levels of dormancy-related genes in transgenic callus indicated that PlARF2 was positively correlated with the contents of PlABI3 and PlDOG1. The germination assay showed that PlARF2 promoted seed dormancy. Moreover, TF Centered Yeast one-hybrid assay (TF-Centered Y1H), electrophoretic mobility shift assay (EMSA) and dual-luciferase reporter assay analysis (Dual-Luciferase) provided evidence that PlARF2 can bind to the 'CATGCATG' motif. Collectively, our findings suggest that PlARF2, as TF, could be involved in the regulation of seed dormancy and may act as a repressor of germination.

Point Cloud Denoising and Feature Preservation: An Adaptive Kernel Approach Based on Local Density and Global Statistics.

Noise removal is a critical stage in the preprocessing of point clouds, exerting a significant impact on subsequent processes such as point cloud classification, segmentation, feature extraction, and 3D reconstruction. The exploration of methods capable of adapting to and effectively handling the noise in point clouds from real-world outdoor scenes remains an open and practically significant issue. Addressing this issue, this study proposes an adaptive kernel approach based on local density and global statistics (AKA-LDGS). This method constructs the overall framework for point cloud denoising using Bayesian estimation theory. It dynamically sets the prior probabilities of real and noise points according to the spatial function relationship, which varies with the distance from the points to the center of the LiDAR. The probability density function (PDF) for real points is constructed using a multivariate Gaussian distribution, while the PDF for noise points is established using a data-driven, non-parametric adaptive kernel density estimation (KDE) approach. Experimental results demonstrate that this method can effectively remove noise from point clouds in real-world outdoor scenes while maintaining the overall structural features of the point cloud.

Knowledge atlas of white matter microstructure: a bibliometric analysis.

Background: White matter microstructure is valued for being an indicator of neural network integrity, which plays an indispensable role in the execution of advanced brain functions. Although the number of publications has increased in the past 10 years, no comprehensive analysis has yet been conducted of this field. Therefore, this study aimed to identify the research hotspots and trends in research on white matter microstructure using a bibliometric analysis of the related literature published from 2013 to 2022. Methods: VOSviewer and CiteSpace were used to objectively analyze the research articles concerning white matter microstructure, which were retrieved from the Web of Science Core Collection (WoSCC). Results: A total of 5,806 publications were obtained, with the number of published articles increasing annually over the past decade. The United States, China, the United Kingdom, and Canada maintained the top positions worldwide and had strong cooperative relationships. The top institution and journal were Harvard Medical School and Neuroimage, respectively. Alexander Leemans, Marek Kubicki, and Martha E Shenton were the most productive authors. Thematic keywords mainly included "diffusion tensor imaging" (DTI), "white matter integrity", and "connectivity". The keyword analysis revealed that DTI has a critical role in detecting white matter microstructure integrity and that fractional anisotropy is the main parameter in the assessment process. Keyword burst detection identified four research hotspots: movement, distortion correction, voxelwise analysis, and fixel-based analysis. Conclusions: This bibliometric analysis provided a systematic understanding of the research on white matter microstructure and identified the current frontiers. This may help clinicians and researchers comprehensively identify hotspots and trends in this field.

[Research Process on the Combined Pollution of Microplastics and Typical Pollutants in Agricultural Soils].

As a new type of environmental persistent pollutant， microplastics can not only have adverse effects on the ecosystem but also form complex pollution with co-existing pollutants in the surrounding environment， resulting in higher ecological and health risks. Based on the perspective of agroecosystems， this study focused on the combined pollution of heavy metals， pesticides， and antibiotics， which are three typical pollutants of farmland soil， as well as microplastics and discussed the adsorption-desorption behavior of heavy metals， pesticides， and antibiotics on microplastics. The influence of the structure and properties of microplastics， the physicochemical properties of pollutants， and environmental conditions on the adsorption and desorption behavior of heavy metals， pesticides， and antibiotics on microplastics was discussed. The influence of microplastics on the bioavailability of heavy metals， pesticides， and antibiotics in farmland soil and the internal mechanism were expounded. The existing problems and shortcomings of current research were pointed out， and the future research direction was proposed. This study can provide a scientific reference for ecological risk assessment of the combined pollution of microplastics and typical pollutants in farmland soil.

FGR-associated placental insufficiency and capillary angiogenesis involves disruptions in human placental miRNAs and mRNAs.

Fetal growth restriction (FGR) is one of the most common pregnancy complications culminating in adverse fetal outcome, including preterm birth, neonatal mortality and stillbirth. Compromised placental development and function, especially disruption in angiogenesis and inadequate nutrient supply are contributing factors. Fetal sex also influences placental function. Knowledge of gene expression changes and epigenetic factors contributing to placental dysfunction in FGR pregnancies will help identify biomarkers and help target interventions. This study tested the hypothesis that FGR pregnancies are associated with disruptions in miRNA - an epigenetic factor and mRNAs involving key mediators of angiogenesis and microvessel development. Changes in expression of key genes/proteins involved in placental dysfunction by RT-PCR and immunohistochemistry and miRNA changes by RNA sequencing were undertaken with term placenta from 12 control and 20 FGR pregnancies. Findings showed changes in expression of genes involved in steroidogenesis, steroid action, IGF family members, inflammatory cytokines and angiogenic factors in FGR pregnancies. In addition, upregulation of MIR451A and downregulation of MIR543 in placentas from FGR group with female newborns and upregulation of MIR520G in placentas from FGR group with male newborns were also noted. MIR451A and MIR543 have been implicated in angiogenesis. Consistent with gene changes, CD34, the microvessel angiogenesis marker, also showed reduced staining only in female FGR group. These findings provide evidence that epigentically regulated gene expression changes in angiogenesis and capillary development influence placental impairment in FGR pregnancies. Our preliminary observations also support for these changes to be driven in a sex-specific manner.

The discrepancy distribution of macrophage subsets in preeclampsia placenta with or without fetal growth restriction from a small cohort.

OBJECTIVES: To identify the effect of distribution characteristic of macrophages on placental function and angiogenesis in pregnancies with preeclampsia (PE) in presence of fetal growth restriction (FGR) or preeclampsia without FGR. MATERIAL AND METHODS: The study tested the hypothesis that there was association between distribution characteristic of macrophage subsets (marked by CD68, CD163, respectively) and placental capillary development, leading to placental dysfunction in PE pregnancies with FGR (n = 36). Changes in placental parameters related with efficiency and angiogenesis and macrophage phenotypes (CD68 and CD163) were evaluated by immunohistochemistry. Pearson correlation analysis was performed to analysis the association between macrophage phenotype and placental function as well the CD34 staining, respectively. Additionally, the localization of CD68 and CD163 was assessed by using immunoflurorescence staining. RESULTS: Pearson correlation analysis had shown the positive association between CD68 expression and microvessel formation and the reverse linear relationship between CD163 staining and placental sufficiency in PE + FGR placenta. The co-localization of CD163 and CD34 may pointed to the compensatory role of CD163 distribution involved in prompting neovascularization. CONCLUSIONS: The association between disturbed distribution of macrophages and placental efficiency and angiogenesis were only found in PE with FGR not in PE pregnancies without FGR, underlying the discrepancy role of macrophage subsets depending on the clinical phenotype of PE pregnancies.

Risk factors for high-stage histological chorioamnionitis among pregnancies with cervical incompetence.

AIM: The study aimed to identify predictive risk factor to identify high-stage histological chorioamnionitis (HCA) in pregnancies with cervical incompetence (CIC). METHODS: A retrospective cohort study was conducted by including 116 pregnant women with cervical incompetence that required prophylactical and therapeutical cerclage. The histopathology examination on placenta was conducted with informed patient consent. All the cases included in this study were divided based on the severity degree of HCA. The demographic characteristic and the parameters related to maternal and fetal outcome were all analyzed. Besides, perioperative parameters of cerclage, including cervical length, cervical morphology, and laboratory indexes were also compared between two groups. Univariate and multivariate logistic regression analysis were used to determine the risk factor of severe chorioamnionitis. RESULTS: Severe HCA was significantly associated with cervical morphology, cerclage indication, cerclage type, and cervical length measured via ultrasound and vaginal examination. After adjusted for confounders, V-type funneling and short cervix was indicated as independent risk factors of severe HCA by multivariate logistic regression analysis, respectively. CONCLUSIONS: V-type funneling and short cervix may indicate the elevated risk of high-stage HCA. Due to the negative outcomes related with high-stage HCA, appropriate prenatal treatment would improve the pregnancy outcomes in cerclaged population. To facilitate postpartum treatment, placental histological examination should be routinely recommended to identify the high-stage HCA, especially in high risk pregnancies.

The correlation between serum total bile acid and alanine aminotransferase of pregnant women and the disorders of neonatal hyperbilirubinemia-related amino acid metabolism.

BACKGROUND: To explore the association between liver metabolism-related indicators in maternal serum and neonatal hyperbilirubinemia (NHB), and further investigate the predictive value of these indicators in NHB-related amino acid metabolism disorders. METHODS: 51 NHB and 182 No-NHB newborns and their mothers who treated in the Fourth Hospital of Shijiazhuang from 2018 to 2022 were participated in the study. The differences in clinical data were compared by the Mann-Whitney U test and Chi-square test. Multivariate logistic regression was used to analyze the relationship between maternal serum indicators and the occurrence of NHB. The correlation analysis and risk factor assessment of maternal serum indicators with NHB-related amino acid metabolic disorders were performed using Spearman correlation analysis and multivariate logistic regression. RESULTS: Compared to the non NHB group, the NHB group had higher maternal serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), ALT/AST, and total bile acid (TBA), while lower levels of serum albumin (ALB), total cholesterol (TC) and high-density lipoprotein (HDL). The levels of alanine (ALA), valine (VAL), ornithine (ORN), and proline (PRO) in the newborns were reduced in NHB group, while arginine (ARG) showed a tendency to be elevated. Multiple logistic regression analysis showed that maternal ALT, AST, ALT/AST, and TBA levels were all at higher risk with the development of NHB, whereas ALB, TC, and HDL levels were negatively associated with NHB development. Increasing maternal TBA level was associated with lower ALA (r=-0.167, p = 0.011), VAL (r=-0.214, p = 0.001), ORN (r=-0.196, p = 0.003), and PRO in the newborns (r=-0.131, p = 0.045). Maternal ALT level was negatively associated with ALA (r=-0.135, p = 0.039), VAL (r=-0.177, p = 0.007), ORN (r=-0.257, p < 0.001), while ALT/AST was positively correlated with ARG (r = 0.133, p = 0.013). After adjustment for confounding factors, maternal serum TBA and ALT were the independent risk factor for neonatal ORN metabolic disorders [(adjusted odds ratio (AOR) = 0.379, 95%CI = 0.188-0.762, p = 0.006), (AOR = 0.441, 95%CI = 0.211-0.922, p = 0.030)]. Maternal ALT level was an independent risk factor for neonatal VAL metabolic disorders (AOR = 0.454, 95%CI = 0.218-0.949, p = 0.036). CONCLUSIONS: The levels of high TBA, ALT, AST, and low HDL, TC of maternal were associated with the risk of NHB. Maternal TBA and ALT levels were independent risk factors for NHB-related amino acid disturbances which have value as predictive makers.

Parkinson's severity diagnosis explainable model based on 3D multi-head attention residual network.

The severity evaluation of Parkinson's disease (PD) is of great significance for the treatment of PD. However, existing methods either have limitations based on prior knowledge or are invasive methods. To propose a more generalized severity evaluation model, this paper proposes an explainable 3D multi-head attention residual convolution network. First, we introduce the 3D attention-based convolution layer to extract video features. Second, features will be fed into LSTM and residual backbone networks, which can be used to capture the contextual information of the video. Finally, we design a feature compression module to condense the learned contextual features. We develop some interpretable experiments to better explain this black-box model so that it can be better generalized. Experiments show that our model can achieve state-of-the-art diagnosis performance. The proposed lightweight but effective model is expected to serve as a suitable end-to-end deep learning baseline in future research on PD video-based severity evaluation and has the potential for large-scale application in PD telemedicine. The source code is available at https://github.com/JackAILab/MARNet.

Improvement of Culture Conditions and Plant Growth Regulators for In Vitro Callus Induction and Plant Regeneration in Paeonia lactiflora Pall.

Owing to its high ornamental, medicinal and horticultural values, herbaceous peony (Paeonia lactiflora Pall.) has been widely used as a landscaping and economical plant around the world. However, the lack of an efficient and stable regeneration system in P. lactiflora restricts its rapid propagation and large-scale production. By testing the key factors affecting callus formation, proliferation, adventitious bud induction and rooting, here, we developed an in vitro system for callus induction and regeneration in P. lactiflora. Our results show that callus formation was affected by explant types, culture environment, basal medium and plant growth regulators. Using cotyledons as explants, we established good conditions for P. lactiflora callus induction and callus proliferation. We effectively obtained adventitious buds differentiated from callus in Murashige and Skoog (MS) medium containing kinetin (KT) and thidiazuron (TDZ). Adventitious bud growth can be further promoted by adding gibberellin 3 (GA3), 1-naphthaleneacetic acid (NAA) and 6-benzyleaminopurine (6-BA) into the MS medium. A high percentage of rooting can be achieved by adding indolebutyric acid (IBA) and activated carbon (AC) to ½ MS medium. Overall, our system promotes callus induction and adventitious bud regeneration for P. lactiflora through improved culture conditions and plant growth regulators in the culture media, and lays a foundation for subsequent genetic engineering research.

Exploration of the Performance and Mechanism of Uranium Adsorption by a Covalent Organic Framework Possessing the Thiazole Structure.

This study prepared an active 2-D covalent organic skeleton (HDU-27) with a network structure, high crystallinity, considerable specific surface area, excellent pore structure, and excellent stability. Kinetic studies manifested that HDU-27 could effectively capture uranium as monolayer chemisorption within a very short kinetic equilibrium time (10 min). In particular, the temperature significantly and positively impacted the uranium adsorption performance of HDU-27. At 298, 313, and 328 K, the adsorption capacity reached 269.2, 488.8, and 576.2 mg g-1, respectively, suggesting the potential to treat high-temperature industrial wastewater containing uranium. HDU-27 had high stability and recoverability with an adsorption efficiency of 98.5% after five adsorption-desorption cycles. According to X-ray photoelectron spectroscopy, the mechanism of interaction between U(VI) and HDU-27 was mainly the chelation of UO22+ by the N atom in the thiazole structure and the strong coordination of the O atom in the keto structure with UO22+. More excitingly, HDU-27 could chemically reduce soluble U(VI) to insoluble U(IV) and release binding sites for the adsorption of additional U(VI). In conclusion, HDU-27 has outstanding potential for uranium adsorption from industrial wastewater containing uranium.

A scalable human iPSC-based neuromuscular disease model on suspended biobased elastomer nanofiber scaffolds.

Many devastating neuromuscular diseases currently lack effective treatments. This is in part due to a lack of drug discovery platforms capable of assessing complex human neuromuscular disease phenotypes in a scalable manner. A major obstacle has been generating scaffolds to stabilise mature contractile myofibers in a multi-well assay format amenable to high content image (HCI) analysis. This study describes the development of a scalable human induced pluripotent stem cell (iPSC)-neuromuscular disease model, whereby suspended elastomer nanofibers support long-term stability, alignment, maturation, and repeated contractions of iPSC-myofibers, innervated by iPSC-motor neurons in 96-well assay plates. In this platform, optogenetic stimulation of the motor neurons elicits robust myofiber-contractions, providing a functional readout of neuromuscular transmission. Additionally, HCI analysis provides rapid and automated quantification of axonal outgrowth, myofiber morphology, and neuromuscular synapse number and morphology. By incorporating amyotrophic lateral sclerosis (ALS)-related TDP-43G298Smutant motor neurons and CRISPR-corrected controls, key neuromuscular disease phenotypes are recapitulated, including weaker myofiber contractions, reduced axonal outgrowth, and reduced number of neuromuscular synapses. Treatment with a candidate ALS drug, the receptor-interacting protein kinase-1 (RIPK1)-inhibitor necrostatin-1, rescues these phenotypes in a dose-dependent manner, highlighting the potential of this platform to screen novel treatments for neuromuscular diseases.

Research hotspots and trends on neuromyelitis optica spectrum disorders: insights from bibliometric analysis.

Neuromyelitis optica spectrum disorders (NMOSD) are demyelinating diseases of the central nervous system, have drawn the attention of many researchers due to the relapsing courses and cumulative disability. A first bibliometric analysis of NMOSD was conducted to identify the research hotspots and emerging trends. Articles relevant to NMOSD published in the core collection of Web of Science were retrieved and analyzed through visualized analysis using CiteSpace and VOSviewer, focusing on annual publication trends, countries, institutions, authors, journals, and keywords. The analysis showed that over the past 30 years, publications related to NMOSD had shown steady growth with slight fluctuations. The United States played an important part in this field, with the highest outputs and the greatest number of citations. Research hotspots of NMOSD had gradually shifted from the definition, biomarkers, and diagnostic criteria to diagnosis and treatment, particularly immunotherapy. This bibliometric analysis provides researchers with a theoretical basis for studying NMOSD and offers guidance for future research directions.