Transformation of Diffusion and Local Structure of CH4 , CO2 , SO2 and H2 O Mixtures in Graphene Under Wide Temperature and Pressure Range: A Molecular Dynamics Simulation Study.

As a material with high specific surface area and excellent chemical stability, graphene exhibited remarkable adsorption and separation performance as well as a wide range of potential applications. The graphene layer played a significant role in influencing gas transmission. In this study, we employed molecular dynamics simulation to investigate the diffusion characteristics and local structures of a mixed system consisting of CH4 , CO2 , SO2 and H2 O. Additionally, we further examined the transformation of the behavior of these mixtures within graphene layers. The order of diffusion coefficients of the four molecules without graphene was H2 O>SO2 >CO2 ≫CH4 . However, in the double-layer graphene, the order changed to CH4 >CO2 ≫H2 O>SO2 . Higher temperatures and lower pressures were found to facilitate gas diffusion. Temperature and pressure had great effects on the local structures of CH4 , CO2 and SO2 , while their impact on H2 O was limited due to the extensive network of hydrogen bonds formed by H2 O molecules. The statistical results of average coordination number revealed that CH4 tended to aggregate with itself, whereas CO2 and SO2 exhibited a tendency to aggregate with H2 O. The graphene structure enhanced the separation and transportation of CH4 from mixed systems.

Extraordinary-log Universality of Critical Phenomena in Plane Defects.

The recent discovery of the extraordinary-log (E-Log) criticality is a celebrated achievement in modern critical theory and calls for generalization. Using large-scale Monte Carlo simulations, we study the critical phenomena of plane defects in three- and four-dimensional O(n) critical systems. In three dimensions, we provide the first numerical proof for the E-Log criticality of plane defects. In particular, for n=2, the critical exponent q[over ^] of two-point correlation and the renormalization-group parameter α of helicity modulus conform to the scaling relation q[over ^]=(n-1)/(2πα), whereas the results for n≥3 violate this scaling relation. In four dimensions, it is strikingly found that the E-Log criticality also emerges in the plane defect. These findings have numerous potential realizations and would boost the ongoing advancement of conformal field theory.

Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: The ADAM challenge.

Accurate detection and quantification of unruptured intracranial aneurysms (UIAs) is important for rupture risk assessment and to allow an informed treatment decision to be made. Currently, 2D manual measures used to assess UIAs on Time-of-Flight magnetic resonance angiographies (TOF-MRAs) lack 3D information and there is substantial inter-observer variability for both aneurysm detection and assessment of aneurysm size and growth. 3D measures could be helpful to improve aneurysm detection and quantification but are time-consuming and would therefore benefit from a reliable automatic UIA detection and segmentation method. The Aneurysm Detection and segMentation (ADAM) challenge was organised in which methods for automatic UIA detection and segmentation were developed and submitted to be evaluated on a diverse clinical TOF-MRA dataset. A training set (113 cases with a total of 129 UIAs) was released, each case including a TOF-MRA, a structural MR image (T1, T2 or FLAIR), annotation of any present UIA(s) and the centre voxel of the UIA(s). A test set of 141 cases (with 153 UIAs) was used for evaluation. Two tasks were proposed: (1) detection and (2) segmentation of UIAs on TOF-MRAs. Teams developed and submitted containerised methods to be evaluated on the test set. Task 1 was evaluated using metrics of sensitivity and false positive count. Task 2 was evaluated using dice similarity coefficient, modified hausdorff distance (95th percentile) and volumetric similarity. For each task, a ranking was made based on the average of the metrics. In total, eleven teams participated in task 1 and nine of those teams participated in task 2. Task 1 was won by a method specifically designed for the detection task (i.e. not participating in task 2). Based on segmentation metrics, the top two methods for task 2 performed statistically significantly better than all other methods. The detection performance of the top-ranking methods was comparable to visual inspection for larger aneurysms. Segmentation performance of the top ranking method, after selection of true UIAs, was similar to interobserver performance. The ADAM challenge remains open for future submissions and improved submissions, with a live leaderboard to provide benchmarking for method developments at https://adam.isi.uu.nl/.

Platelet transcriptome profiles provide potential therapeutic targets for elderly acute myelocytic leukemia patients.

BACKGROUND: Acute myeloid leukemia (AML) is the most common acute leukemia in adults, with a median age of 68 in clinical diagnosis. About 60% patients are over 60 years old. There are various treatment options for AML patients. But for elderly patients, the complete remission rates are disappointing due to genetic, molecular, and age-related factors. Development of next-generation sequencing technologies makes it possible to seek individual strategies for patients in different ages. This study analyzed transcriptome profiles in platelets of AML patients in different ages for the first time. METHODS: Platelet RNA sequencing in AML of ten elderly and seven young patients were performed with Illumina TruSeq Stranded mRNA library Prep Kit and Illumina HiSeq4000 sequencing instrument. With the FASTQ sequencing data obtained, statistical analyses between elderly with young AML patients were analyzed by R program. GO and KEGG enrichment analyses were performed via R package clusterProfiler. TOP 10 down-regulated/up-regulated genes in elderly patients compared to young patients were selected with the threshold of |L2FC| > 2 and padj ≤ 0.0001. The down-regulated gene ATF4 was chosen by GSEA analysis and ROC analysis with AUC > 0.95. RESULTS: We found 3059 genes with differential transcript levels (GDTLs) in AML patients of different age. Among them, 2048 genes are down-regulated and 651 genes are up-regulated in elderly patients. We found that gene transcript profiles in elderly patients is obviously different from those in young patients, including a collection of down-regulated genes related to proteins processing in endoplasmic reticulum and immunity. We further identified that genes of pathway in cancer and mitogen activated protein kinase (MAPK) pathway, involved in natural immunity and metabolism, are significantly down-regulated in elderly patients. Among all screened genes with decreased transcript levels, we believe that activating transcription factor 4 (ATF4) is a biomarker indicating different chemotherapy strategies for elderly patients. CONCLUSIONS: In summary, gene transcript profiles are different in platelets of elderly and young AML patients. And ATF4 can be a useful biomarker indicating different chemotherapy strategies for AML patients with different ages.

Extraordinary-Log Surface Phase Transition in the Three-Dimensional XY Model.

Universality is a pillar of modern critical phenomena. The standard scenario is that the two-point correlation algebraically decreases with the distance r as g(r)∼r^{2-d-η}, with d the spatial dimension and η the anomalous dimension. Very recently, a logarithmic universality was proposed to describe the extraordinary surface transition of the O(N) system. In this logarithmic universality, g(r) decays in a power of logarithmic distance as g(r)∼(lnr)^{-η[over ^]}, dramatically different from the standard scenario. We explore the three-dimensional XY model by Monte Carlo simulations, and provide strong evidence for the emergence of logarithmic universality. Moreover, we propose that the finite-size scaling of g(r,L) has a two-distance behavior: simultaneously containing a large-distance plateau whose height decays logarithmically with L as g(L)∼(lnL)^{-η[over ^]^{'}} as well as the r-dependent term g(r)∼(lnr)^{-η[over ^]}, with η[over ^]^{'}≈η[over ^]-1. The critical exponent η[over ^]^{'}, characterizing the height of the plateau, obeys the scaling relation η[over ^]^{'}=(N-1)/(2πα) with the RG parameter α of helicity modulus. Our picture can also explain the recent numerical results of a Heisenberg system. The advances on logarithmic universality significantly expand our understanding of critical universality.

A Review on Map-Merging Methods for Typical Map Types in Multiple-Ground-Robot SLAM Solutions.

When multiple robots are involved in the process of simultaneous localization and mapping (SLAM), a global map should be constructed by merging the local maps built by individual robots, so as to provide a better representation of the environment. Hence, the map-merging methods play a crucial rule in multi-robot systems and determine the performance of multi-robot SLAM. This paper looks into the key problem of map merging for multiple-ground-robot SLAM and reviews the typical map-merging methods for several important types of maps in SLAM applications: occupancy grid maps, feature-based maps, and topological maps. These map-merging approaches are classified based on their working mechanism or the type of features they deal with. The concepts and characteristics of these map-merging methods are elaborated in this review. The contents summarized in this paper provide insights and guidance for future multiple-ground-robot SLAM solutions.

Apoptosis in human myelodysplastic syndrome CD34+ cells is modulated by the upregulation of TLRs and histone H4 acetylation via a ß-arrestin 1 dependent mechanism.

Excessive apoptosis of hematopoietic precursors in the bone marrow underlies the ineffective hematopoiesis characteristic of myelodysplastic syndrome (MDS). Toll-like receptor (TLR) signaling is abnormally activated in MDS and may be involved in excessive programmed cell death in the pathogenesis of MDS. TLRs expression and global histone H3/H4 acetylation were analyzed in bone marrow (BM) CD34+ cells from 20 lower-risk and 20 higher-risk MDS patients and 10 healthy controls. Apoptosis of BM CD34+ cells was examined by flow cytometry, and its correlation to histone acetylation and the expression of TLR2 and ß-arrestin1 (ß-arr1), measured by enzyme-linked immunosorbent assay and qRT-PCR, was assessed. TLR1, TLR2 and TLR6 expression and H4 acetylation levels were higher in lower-risk MDS patients than in higher-risk MDS patients or controls, and TLR2 expression and H4 acetylation levels were positively correlated with an increased rate of apoptosis. Lower-risk MDS was associated with increased ß-arr1 expression and histone acetyltransferase p300 activity. In in vitro-cultured primary normal and lower-risk MDS CD34+ cells, TLR2 activation-induced apoptosis was mediated by the upregulation of ß-arr1 leading to the recruitment of p300 and increased histone H4 acetylation. The nuclear accumulation of ßarr1 following TLR2 activation promote H4 acetylation at specific target gene promoters and may thus affect transcription of target genes in BM CD34+ cells. The mechanisms underlying the deregulation of TLR2 and increased apoptosis in MDS may involve the ß-arr1 mediated recruitment of p300 leading to increased levels of histone H4 acetylation.

Inward-facing conformation of the zinc transporter YiiP revealed by cryoelectron microscopy.

YiiP is a dimeric Zn(2+)/H(+) antiporter from Escherichia coli belonging to the cation diffusion facilitator family. We used cryoelectron microscopy to determine a 13-Å resolution structure of a YiiP homolog from Shewanella oneidensis within a lipid bilayer in the absence of Zn(2+). Starting from the X-ray structure in the presence of Zn(2+), we used molecular dynamics flexible fitting to build a model consistent with our map. Comparison of the structures suggests a conformational change that involves pivoting of a transmembrane, four-helix bundle (M1, M2, M4, and M5) relative to the M3-M6 helix pair. Although accessibility of transport sites in the X-ray model indicates that it represents an outward-facing state, our model is consistent with an inward-facing state, suggesting that the conformational change is relevant to the alternating access mechanism for transport. Molecular dynamics simulation of YiiP in a lipid environment was used to address the feasibility of this conformational change. Association of the C-terminal domains is the same in both states, and we speculate that this association is responsible for stabilizing the dimer that, in turn, may coordinate the rearrangement of the transmembrane helices.

Biogeography and diversity patterns of abundant and rare bacterial communities in paddy soils along middle and lower Yangtze River.

The middle and lower reaches of the Yangtze River serve as principal rice production bases in China, yet the biodiversity and ecological processes of bacterial communities in paddy soils are not well understood. This study explores the diversity, composition, ecological function, and assembly processes of abundant and rare bacterial communities in paddy soils. A total of 129 paddy soil samples from 43 sites along the middle and lower reaches of the Yangtze River were collected and analyzed using NovaSeq sequencing. The results showed that the dominant phylum for both abundant and rare taxa was Proteobacteria, with a greater relative abundance of the abundant taxa. The diversity of the abundant community was lower than that of the rare community. Soil properties and geographic variables explained more of the variation in the abundant community than in the rare community. The rare community exhibited a significant distance-decay relationship. The assembly of the abundant community was more influenced by stochastic processes, although both the abundant and rare communities were governed by stochastic processes. It is concluded that both abundant and rare bacterial communities exhibit differing biogeographic patterns, yet they undergo similar ecological processes in the paddy soils along the middle and lower reaches of the Yangtze River. These observations offer a theoretical framework for a deeper comprehension of the function of both abundant and rare bacteria, as well as the development and preservation of soil bacterial diversity within agricultural ecosystems.

Indirect co-culture of osteoblasts and endothelial cells in vitro based on a biomimetic 3D composite hydrogel scaffold to promote the proliferation and differentiation of osteoblasts.

The field of orthopedics has long struggled with the challenge of repairing and regenerating bone defects, which involves a complex process of osteogenesis requiring coordinated interactions among different types of cells. The crucial role of endothelial cells and osteoblasts in bone vascularization and osteogenesis underscores the importance of their intimate interaction. However, efforts to bioengineer bone tissue have been impeded by the difficulty in establishing proper angiogenesis and osteogenesis in tissue structures. This study presents a novel approach to bone tissue engineering, involving a three-dimensional composite hydrogel scaffold composed of sodium alginate microspheres encapsulated in type I collagen. Using this scaffold, a three-dimensional indirect co-culture system was established for osteoblasts and endothelial cells to evaluate the osteogenic differentiation potential of osteoblasts. Results demonstrate that the non-contact co-culture system of endothelial cells and osteoblasts constructed by the composite hydrogel scaffold loaded with microspheres holds promise for bone tissue engineering. The innovative concept of an indirect co-culture system presents exciting prospects for conducting intercellular communication studies and offers a valuable in vitro tissue platform to investigate tissue regeneration.

The impact of serum uric acid on psoriasis: NHANES 2005-2014 and Mendelian randomization.

Background: Psoriasis is a chronic systemic inflammatory disease, and hyperuricemia is a common comorbidity in patients with psoriasis. However, the exact relationship between uric acid levels and psoriasis remains unclear. This study aimed to explore the association between uric acid levels and psoriasis. Methods: Observational study participant data (≥16 years, n = 23,489) from NHANES 2003-2014. We conducted analyses using a weighted multiple logistic regression model. Genetic data sets for uric acid levels and psoriasis were obtained from the IEU database. We selected genetically independent loci closely associated with serum uric acid levels as instrumental variables and performed Mendelian randomization analyses using five complementary methods: inverse variance weighting (IVW), MR-Egger, weighted median, simple mode, and weighted mode. Results: After adjusting for other covariates, the results revealed no significant association between serum uric acid levels and psoriasis (b = 0.999, 95% CI: 0.998, 1.001, p = 0.275). Subgroup analyses stratified by gender and ethnicity showed no significant association between sUA and psoriasis in any of the subgroups. Furthermore, the MR analysis involved the selection of 227 SNPs that were associated with both sUA and psoriasis. IVW results demonstrated no causal relationship between sUA and psoriasis (OR = 0.282, 95% CI: -0.094-0.657, p = 0.142). Conclusion: Our study suggests that uric acid levels are not significantly causally related to psoriasis. This finding provides valuable insights for the treatment and prevention of psoriasis, indicating that merely reducing uric acid levels may not be an effective strategy to reduce the risk of psoriasis onset.

CTH-Net: A CNN and Transformer hybrid network for skin lesion segmentation.

Automatically and accurately segmenting skin lesions can be challenging, due to factors such as low contrast and fuzzy boundaries. This paper proposes a hybrid encoder-decoder model (CTH-Net) based on convolutional neural network (CNN) and Transformer, capitalizing on the advantages of these approaches. We propose three modules for skin lesion segmentation and seamlessly connect them with carefully designed model architecture. Better segmentation performance is achieved by introducing SoftPool in the CNN branch and sandglass block in the bottleneck layer. Extensive experiments were conducted on four publicly accessible skin lesion datasets, ISIC 2016, ISIC 2017, ISIC 2018, and PH2 to confirm the efficacy and benefits of the proposed strategy. Experimental results show that the proposed CTH-Net provides better skin lesion segmentation performance in both quantitative and qualitative testing when compared with state-of-the-art approaches. We believe the CTH-Net design is inspiring and can be extended to other applications/frameworks.

Functionalizing tetrahedral framework nucleic acids-based nanostructures for tumor in situ imaging and treatment.

Timely in situ imaging and effective treatment are efficient strategies in improving the therapeutic effect and survival rate of tumor patients. In recent years, there has been rapid progress in the development of DNA nanomaterials for tumor in situ imaging and treatment, due to their unsurpassed structural stability, excellent material editability, excellent biocompatibility and individual endocytic pathway. Tetrahedral framework nucleic acids (tFNAs), are a typical example of DNA nanostructures demonstrating superior stability, biocompatibility, cell-entry performance, and flexible drug-loading ability. tFNAs have been shown to be effective in achieving timely tumor in situ imaging and precise treatment. Therefore, the progress in the fabrication, characterization, modification and cellular internalization pathway of tFNAs-based functional systems and their potential in tumor in situ imaging and treatment applications were systematically reviewed in this article. In addition, challenges and future prospects of tFNAs in tumor in situ imaging and treatment as well as potential clinical applications were discussed.

Accelerating 3D genomics data analysis with Microcket.

The three-dimensional (3D) organization of genome is fundamental to cell biology. To explore 3D genome, emerging high-throughput approaches have produced billions of sequencing reads, which is challenging and time-consuming to analyze. Here we present Microcket, a package for mapping and extracting interacting pairs from 3D genomics data, including Hi-C, Micro-C, and derivant protocols. Microcket utilizes a unique read-stitch strategy that takes advantage of the long read cycles in modern DNA sequencers; benchmark evaluations reveal that Microcket runs much faster than the current tools along with improved mapping efficiency, and thus shows high potential in accelerating and enhancing the biological investigations into 3D genome. Microcket is freely available at https://github.com/hellosunking/Microcket .

ShuYu capsule alleviates emotional and physical symptoms of premenstrual dysphoric disorder: Impact on ALLO decline and GABAA receptor δ subunit in the PAG area.

Premenstrual dysphoric disorder (PMDD) is a severe subtype of premenstrual syndrome in women of reproductive age, with its pathogenesis linked to the heightened sensitivity of type A γ -aminobutyric acid receptors (GABAAR) to neuroactive steroid hormone changes, particularly allopregnanolone (ALLO). While a low dose of fluoxetine, a classic selective serotonin reuptake inhibitor, is commonly used as a first-line drug to alleviate emotional disorders in PMDD in clinical settings, its mechanism of action is related to ALLO-GABAA receptor function. However, treating PMDD requires attention to both emotional and physical symptoms, such as pain sensitivity. This study aims to investigate the efficacy of ShuYu capsules, a traditional Chinese medicine, in simultaneously treating emotional and physical symptoms in a rat model of PMDD. Specifically, our focus centres on the midbrain periaqueductal grey (PAG), a region associated with emotion regulation and susceptibility to hyperalgesia. Considering the underlying mechanisms of ALLO-GABAA receptor function in the PAG region, we conducted a series of experiments to evaluate and define the effects of ShuYu capsules and uncover the relationship between the drug's efficacy and ALLO concentration fluctuations on GABAA receptor function in the PAG region. Our findings demonstrate that ShuYu capsules significantly improved oestrous cycle-dependant depression-like behaviour and reduced stress-induced hyperalgesia in rats with PMDD. Similar to the low dose of fluoxetine, ShuYu capsules targeted and mitigated the sharp decline in ALLO, rescued the upregulation of GABAAR subunit function, and activated PAG neurons in PMDD rats. The observed effects of ShuYu capsules suggest a central mechanism underlying PMDD symptoms, involving ALLO_GABAA receptor function in the PAG region. This study highlights the potential of traditional Chinese medicine in addressing both emotional and physical symptoms associated with PMDD, shedding light on novel therapeutic approaches for this condition.

Association of the IRF5 rs2004640 polymorphism with rheumatoid arthritis: a meta-analysis.

Several molecular epidemiological studies have been conducted in recent years to evaluate a possible association between the interferon regulatory factor 5 (IRF5) rs2004640 polymorphism and rheumatoid arthritis risk in diverse populations. However, the results remain conflicting rather than conclusive. Our aim was to assess associations of IRF5 gene polymorphisms with rheumatoid arthritis risk. Meta-analysis was performed on six published case-control studies (from eight countries) that included 4,818 cases of rheumatoid arthritis and 4,316 controls. The rs2004640-T allele was associated with a significantly increased risk of rheumatoid arthritis when the dominant genetic model was applied (T/T + T/G versus G/G: P = 0.003, OR = 1.14, 95% CI 1.05-1.25). Upon stratified analysis by ethnicity, the rs2004640 polymorphism was associated with an increased rheumatoid arthritis risk in Caucasians when the homozygotic contrast model was employed(T/T versus G/G: P = 0.03, OR = 1.25, 95% CI 1.02-1.53) and this was also the case when the dominant genetic model was used (T/T + T/G versus G/G: P = 0.04, OR = 1.20, 95% CI 1.01-1.42), whereas, in Asian populations, only the dominant genetic model was associated with an increased rheumatoid arthritis risk (T/T + T/G versus G/G: P = 0.02, OR = 1.14, 95% CI 1.02-1.26). The results suggest that the IRF5 rs2004640 polymorphism is associated with rheumatoid arthritis especially when the dominant genetic model is applied.

[Identifying the origin of chromophoric dissolved organic matter in Xiamen Bay using fluorescence spectroscopy and chemometrics].

The fluorescent components of chromophoric dissolved matter (CDOM) in water samples collected from Xiamen Bay in spring and autumn, 2009 were examined using excitation-emission matrix fluorescence spectroscopy combined with parallel factor analysis (EEMs-PARAFAC). PARAFAC decomposed the fluorescence matrices of CDOM into three humic-like (C1: 250, 345/454 nm; C2: 230, 310/374 nm; C5: 265, 424/478 nm) and two protein-like (C3: 230/342 nm; C4: 230, 275/322 nm) components. Good linear correlation occurred among three humic-like components and between two protein-like components, respectively. This demonstrated that the same types of components (humic-like or protein-like) have similar origin and geochemical behaviors. High abundances of humic-like components were found at the upstream zone of the Jiulong Estuary, while the high abundance of protein-like components occurred at the northern part of semi-enclosed Western Xiamen Harbor. The significant negative correlations were found between the abundances of all fluorescence components and salinity in the estuary area. However, the high contents of chlorophyll a were in line with the high abundances of C3 and C4 in non-estuarine area, which implies that phytoplankton activity could be another important source of protein-like components besides the river runoff. A principal component analysis(PCA) of fluorescent components revealed that terrestrial runoff was the dominant sources of CDOM fluorescence components in Xiamen Bay, while the contribution of the in situ biological processes was relatively lower. This study demonstrates that the combination use of PARAFAC modeling and chemometrics (i. e. PCA) is very useful in identifying the origin of CDOM and quantifying the primary factors influencing their distributions.

Self-Distillation for Randomized Neural Networks.

Knowledge distillation (KD) is a conventional method in the field of deep learning that enables the transfer of dark knowledge from a teacher model to a student model, consequently improving the performance of the student model. In randomized neural networks, due to the simple topology of network architecture and the insignificant relationship between model performance and model size, KD is not able to improve model performance. In this work, we propose a self-distillation pipeline for randomized neural networks: the predictions of the network itself are regarded as the additional target, which are mixed with the weighted original target as a distillation target containing dark knowledge to supervise the training of the model. All the predictions during multi-generation self-distillation process can be integrated by a multi-teacher method. By induction, we have additionally arrived at the methods for infinite self-distillation (ISD) of randomized neural networks. We then provide relevant theoretical analysis about the self-distillation method for randomized neural networks. Furthermore, we demonstrated the effectiveness of the proposed method in practical applications on several benchmark datasets.

Online dynamic ensemble deep random vector functional link neural network for forecasting.

This paper proposes a three-stage online deep learning model for time series based on the ensemble deep random vector functional link (edRVFL). The edRVFL stacks multiple randomized layers to enhance the single-layer RVFL's representation ability. Each hidden layer's representation is utilized for training an output layer, and the ensemble of all output layers forms the edRVFL's output. However, the original edRVFL is not designed for online learning, and the randomized nature of the features is harmful to extracting meaningful temporal features. In order to address the limitations and extend the edRVFL to an online learning mode, this paper proposes a dynamic edRVFL consisting of three online components, the online decomposition, the online training, and the online dynamic ensemble. First, an online decomposition is utilized as a feature engineering block for the edRVFL. Then, an online learning algorithm is designed to learn the edRVFL. Finally, an online dynamic ensemble method, which can measure the change in the distribution, is proposed for aggregating all layers' outputs. This paper evaluates and compares the proposed model with state-of-the-art methods on sixteen time series.