Investigating the gene expression profiles of cells in seven embryonic stages with machine learning algorithms.

The development of embryonic cells involves several continuous stages, and some genes are related to embryogenesis. To date, few studies have systematically investigated changes in gene expression profiles during mammalian embryogenesis. In this study, a computational analysis using machine learning algorithms was performed on the gene expression profiles of mouse embryonic cells at seven stages. First, the profiles were analyzed through a powerful Monte Carlo feature selection method for the generation of a feature list. Second, increment feature selection was applied on the list by incorporating two classification algorithms: support vector machine (SVM) and repeated incremental pruning to produce error reduction (RIPPER). Through SVM, we extracted several latent gene biomarkers, indicating the stages of embryonic cells, and constructed an optimal SVM classifier that produced a nearly perfect classification of embryonic cells. Furthermore, some interesting rules were accessed by the RIPPER algorithm, suggesting different expression patterns for different stages.

Preparation of multi-temperature responsive elastomers by generating ionic networks in 1,2-polybutadiene using an anionic melting method.

The development of reversible networks in elastomers provided unique inspiration for the design of advanced polymers with excellent properties. In this paper, we adopted an anionic melting method to introduce carboxylate groups into 1,2-polybutadiene (1,2-PB), using maleic anhydride as a modifier, and sodium hydride (NaH), calcium hydride (CaH2), and lithium aluminum hydride (LiAlH4) as metallization reagents. Na-Based, Ca-based, and Li/Al-based ionic bond networks were constructed in the covalently crosslinked 1,2-PB. The effects of the electronegativity and valence of the metal ions on the strength and reversible temperature of the ionic network were studied. Payne effect was shown by rheological tests, demonstrating the interactions between the ionic networks and rubber chains. The reforming temperature for these ionic networks was studied by stress-relaxation analysis, and shape memory experiments were performed based on these temperatures. This concept provides novel inspiration for the design of high-performance and temperature-adaptive elastomers.

A novel morphometry system automatically assessing the growth and regeneration of intestinal organoids.

As compared with 2D cell line cultures, 3D intestinal organoids are better at maximally recapitulating the physiological features of stem cells in vivo. However, the complex 3D structure is an obstacle which must be objectively and automatically evaluated to assess colony growth and regeneration. Meanwhile, no internal standard currently exists for evaluating the size of heterogeneities in organoids or defining those regenerating colonies. Herein, we developed a simple morphometry system to image MTT-stained organoids. The growth curve of organoids can be automatically generated based upon analyzing the integrated optical density using software. Referencing the definition standards of in vivo regenerating crypts, the perimeters of crypts cultured 24 h after seeding were selected as an "Organoid Unit" to further evaluate colony survival rate and colony size heterogeneities after exposure to varying doses of irradiation. Moreover, the morphometry-based quantification data collected confirmed other findings associated with radiation sensitizing effects of ataxia telangiectasia mutated (ATM) and ataxia telangiectasia and Rad3-related protein (ATR) inhibitor and the radiation protective effect of IL-22. In summary, the novel organoid morphometry system combined with a new internal reference is a practical means for standardizing assessment of growth, survival and regeneration of intestinal organoid colonies. This method has promise to facilitate drug screens in intestinal and other organoid systems.

Understanding epidemic spread patterns: a visual analysis approach.

Epidemics present significant challenges for public health policy globally, but current tools for visualizing and analyzing epidemic spread are limited, especially at a large scale. This paper presents a novel visual analysis approach for exploring and comparing pandemic patterns in spatial and temporal dimensions across various regions. The method incorporates a potential flow technique to model the spatiotemporal dynamics of epidemics and a visual exploration tool, EPViz, for interactive data analysis. Utilizing COVID-19 data from Illinois and Pennsylvania in the United States, the paper evaluates the method and tool's effectiveness. These states were chosen for their differing epidemic scenarios and policies. Additionally, interviews with public health policy experts were conducted to gather feedback on the approach and EPViz's effectiveness, design, and usability. The findings indicate that this new approach and tool enhance expert understanding, support decision-making, and can inform effective strategies for epidemic prevention and control.

Automated graptolite identification at high taxonomic resolution using residual networks.

Graptolites, fossils significant for evolutionary studies and shale gas exploration, are traditionally identified visually by taxonomists due to their intricate morphologies and preservation challenges. Artificial intelligence (AI) holds great promise for transforming such meticulous tasks. In this paper, we demonstrate that graptolites can be identified with taxonomist accuracy using a deep learning model. We construct the most sophisticated and largest professional single organisms image dataset to date, which is composed of >34,000 images of 113 graptolite species annotated at pixel-level resolution to train the model, develop, and evaluate deep learning networks to classify graptolites. The model's performance surpassed taxonomists in accuracy, time, and generalization, achieving 86% and 81% accuracy in identifying graptolite genus and species, respectively. This AI-based method, capable of recognizing minute morphological details better than taxonomists, can be integrated into web and mobile apps, extending graptolite identification beyond research institutes and enhancing shale gas exploration efficiency.

Delinquent Events Prediction in Temporal Networked-Guarantee Loans.

Under debt obligation promises, small- and medium-sized enterprises (SMEs) can guarantee each other to enhance their financial security to get loans from commercial banks. When the economy rises, the banks may reduce the threshold to some extent, which may introduce default risk during the economy down period, especially when many SMEs bind together and form complex networks. The risk may diffuse across the guarantee network and may result in a financial crisis. Macroprudential oversight of the guarantee network to eliminate any potential systematics financial risk is the central task of the regulatory commission and the commercial banks. Based on our observation, the delinquent probability of an SME depends not only on self-financial status but also highly related to its temporal behaviors and structural position in networks. The classic approach for loan assessment criteria face challenges in extracting temporal and structural patterns from dynamic networks. To address these issues, we propose a temporal delinquent event prediction (TDEP) framework that preserves temporal network structures and credit behavior sequences in an end-to-end model. In particular, we first employ a graph attention layer to learn the representation of nodes in temporal guarantee networks. We then design a recursive and self-attention mechanism to integrate both credit behavior and network structure information. The learned attentional weights are leveraged to uncover high-risk guarantee patterns that effectively accelerate the risk assessment process. Afterward, we conduct extensive experiments in a real-world guaranteed-loan data set to evaluate its performance. The results show the effectiveness of our proposed approach compared with the state-of-the-art baselines. Finally, we integrate the proposed model in a real-world loan risk management system. We present the implementation details of each subcomponent of the system and report out the performance after online deployment.

Identifying Protein Subcellular Locations With Embeddings-Based node2loc.

Identifying protein subcellular locations is an important topic in protein function prediction. Interacting proteins may share similar locations. Thus, it is imperative to infer protein subcellular locations by taking protein-protein interactions (PPIs)into account. In this study, we present a network embedding-based method, node2loc, to identify protein subcellular locations. node2loc first learns distributed embeddings of proteins in a protein-protein interaction (PPI)network using node2vec. Then the learned embeddings are further fed into a recurrent neural network (RNN). To resolve the severe class imbalance of different subcellular locations, Synthetic Minority Over-sampling Technique (SMOTE)is applied to artificially synthesize proteins for minority classes. node2loc is evaluated on our constructed human benchmark dataset with 16 subcellular locations and yields a Matthews correlation coefficient (MCC)value of 0.800, which is superior to baseline methods. In addition, node2loc yields a better performance on a Yeast benchmark dataset with 17 locations. The results demonstrate that the learned representations from a PPI network have certain discriminative ability for classifying protein subcellular locations. However, node2loc is a transductive method, it only works for proteins connected in a PPI network, and it needs to be retrained for new proteins. In addition, the PPI network needs be annotated to some extent with location information. node2loc is freely available at https://github.com/xypan1232/node2loc.

The preparation of multifunction chitosan adhesive hydrogel by "one- step" method.

Chitosan adhesive hydrogels have attracted interest because of their unique properties. However, it is still a challenge to use simple and unmodified chitosan to synthesize multifunctional hydrogels with adhesive, self-healing and strain sensing properties. Here, a multifunctional hydrogel of Ca2+-chitosan/polyacrylamide（Ca2+- CS/PAAm）with adhesive self-healing and strain sensing properties was carried out by one-step preparation method. The hydrogel has the ability to adhere to a variety of materials, wherein the adhesion strength to rubber surface is 48.4 kPa. The hydrogel has excellent strain sensing capability on finger bending or cyclic stretching, the sensitivity factor is 0.41 ± 0.015. The cut hydrogel healed completely at room temperature within 4 h, and the healing hydrogel can be stretched to 5 times of its original length. This makes Ca2+-CS/PAAm hydrogel to be great potential in the application of strain sensors, wound dressing and skin adhesives.

Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules.

DNA methylation is an essential epigenetic modification for multiple biological processes. DNA methylation in mammals acts as an epigenetic mark of transcriptional repression. Aberrant levels of DNA methylation can be observed in various types of tumor cells. Thus, DNA methylation has attracted considerable attention among researchers to provide new and feasible tumor therapies. Conventional studies considered single-gene methylation or specific loci as biomarkers for tumorigenesis. However, genome-scale methylated modification has not been completely investigated. Thus, we proposed and compared two novel computational approaches based on multiple machine learning algorithms for the qualitative and quantitative analyses of methylation-associated genes and their dys-methylated patterns. This study contributes to the identification of novel effective genes and the establishment of optimal quantitative rules for aberrant methylation distinguishing tumor cells with different origin tissues.

Identification of G2/M phase transition by sequential nuclear and cytoplasmic changes and molecular markers in mice intestinal epithelial cells.

Although the regulatory network of G2/M phase transition has been intensively studied in mammalian cell lines, the identification of morphological and molecular markers to identify G2/M phase transition in vivo remains elusive. In this study, we found no obvious morphological changes between the S phase and G2 phase in mice intestinal epithelial cells. The G2 phase could be identified by Brdu incorporation resistance, marginal and scattered foci of histone H3 phosphorylated at Ser10 (pHH3), and relatively intact Golgi ribbon. Prophase starts with nuclear transformation in situ, which was identified by a series of prophase markers including nuclear translocation of cyclinB1, fragmentation of the Golgi complex, and a significant increase in pHH3. The nucleus started to move upwards in the late prophase and finally rounded up at the apical surface. Then, metaphase was initiated as the level of pHH3 peaked. During anaphase and telophase, pHH3 sharply decreased, while Ki67 was obviously bound to chromosomes, and PCNA was distributed throughout the whole cell. Based on the aforementioned markers and Brdu pulse labeling, it was estimated to take about one hour for most crypt cells to go through the G2 phase and about two hours to go through the G2-M phase. It took much longer for crypt base columnar (CBC) stem cells to undergo G2-prophase than rapid transit amplifying cells. In summary, a series of sequentially presenting markers could be used to indicate the progress of G2/M events in intestinal epithelial cells and other epithelial systems in vivo.

[Expression of Stat3, HIF-1alpha and VEGF in Wilms' tumor].

OBJECTIVE: To study the expression of signal transducer and activator of transcription 3 (Stat3), hypoxia-inducible factor-1alpha (HIF-1alpha) and vascular endothelial growth factor (VEGF) in Wilms' tumor and their roles in the development of Wilms' tumor. METHODS: The expression of Stat3, HIF-1alpha and VEGF were detected by the immunohistochemical staining in 52 specimens from Wilms' tumor tissues, 47 from adjacent kidney tissues and 8 from normal kidney tissues. The expression intensity was analyzed by computer image processing. RESULTS: The expression of Stat3, HIF-1 and VEGF were significantly up-regulated in Wilms' tumor tissues compared to those in adjacent tissues and normal kidney tissues (P < 0.05). Stat3 and VEGF proteins in Wilms' tumor tissues of stage III-IV and high risk histopathology were significantly higher than those of stage I-II and low risk histopathology. The higher expression of HIF-1 in Wilms' tumor tissues was shown in tumors with high risk histopathology and tumor size > or = 6 cm. CONCLUSIONS: Increased expression of Stat3, HIF-1 and VEGF were found in Wilms' tumor tissues, and may be related to the development and angiogenesis of Wilms' tumor. Stat3 may regulate the expression of HIF-1 and VEGF, so it could be an effective target for inhibiting VEGF expression and angiogenesis of Wilms' tumor.

Chromosome 13q deletion syndrome involving 13q31­qter: A case report.

Partial deletions on the long arm of chromosome 13 lead to a number of different phenotypes depending on the size and position of the deleted region. The present study investigated 2 patients with 13q terminal (13qter) deletion syndrome, which manifested as anal atresia with rectoperineal fistula, complex type congenital heart disease, esophageal hiatus hernia with gastroesophageal reflux, facial anomalies and developmental and mental retardation. Array comparative genomic hybridization identified 2 regions of deletion on chromosome 13q31­qter; 20.38 Mb in 13q31.3­qter and 12.99 Mb in 13q33.1­qter in patients 1 and 2, respectively. Comparisons between the results observed in the present study and those obtained from patients in previous studies indicate that the gene encoding ephrin B2 (EFNB2) located in the 13q33.3­q34 region, and the gene coding for endothelin receptor type B, in the 13q22.1­31.3 region, may be suitable candidate genes for the observed urogenital/anorectal anomalies. In addition, the microRNA­17­92a­1 cluster host gene and the glypican 6 gene in the 13q31.3 region, as well as EFNB2 and the collagen type IV a1 chain (COL4A1) and COL4A2 genes in the 13q33.1­q34 region may together contribute to cardiovascular disease development. It is therefore possible that these genes may be involved in the pathogenesis of complex type congenital heart disease in patients with 13q deletion syndrome.

Screening and identification of the differentially expressed proteins in neonatal rat kidney after partial unilateral ureteral obstruction.

Renal fibrosis, considered to be a common consequence of progressive renal disease, involves glomerulosclerosis and/or tubulointerstitial fibrosis. Currently, research is focused on investigating potential mechanisms to prevent or reverse the damage caused by fibrosis. Under the influence of cytokines, chemokines and other signaling molecules, the cellular interactions that regulate the development of interstitial fibrosis are complex. Epithelial­mesenchymal transition (EMT) has emerged as an important pathway leading to the generation of matrix­producing fibroblasts and myofibroblasts in diseased kidneys. The proteomics study compared the protein profiles between the time points of podocyte EMT and tubular cell EMT in a partial unilateral ureteral obstruction (PUUO) model in rats. Proteins isolated from the PUUO group and corresponding sham rat kidney tissues were subjected to 2­D gel electrophoresis and were then identified by mass spectrometry. In total, 43 proteins with differential expression were identified, which were reported to be involved in the regulation of the cytoskeleton and actin, glucose metabolism, cell apoptosis, mitochondrial energy metabolism, oxidative stress and endoplasmic reticulum stress. Electron transfer flavoprotein, ß polypeptide was detected by immunoblot analysis and its mRNA levels were determined in renal tissues. The results demonstrate protein alterations that reflect the pathology of the obstructed kidneys, and thus may aid in understanding the pathogenesis of obstructive nephropathy.

Postoperative intussusception in children: a review of 14 cases.

OBJECTIVE: To search the etiologic factor, clinical diagnosis points and treatment of postoperative intussusception (PI). METHODS: To retrospectively review the clinical materials of 14 cases with PI including the cause of disease and treatment. RESULTS: PI occurred within 10 days (average 4 days) after the primary operation. Bowel obstructive symptoms gradually emerged. One case was diagnosed with intussusception by sonography and received enema reduction of intussusception by hydrostatic pressure. Thirteen cases were performed secondary operation. Small intestine was main site of intussusception. Manual reduction of the lesion was performed in 12 cases and bowel resection and anastomosis was done in 1 case with bowel necrosis. CONCLUSION: PI should be suspected if child presents with the symptoms of ileus in early postoperative period. Abdominal sonography may have some value on diagnosis of PI. Operation is the first choice for the treatment of PI.

Increased Tbx1 expression may play a role via TGFß-Smad2/3 signaling pathway in acute kidney injury induced by gentamicin.

T-box 1 (Tbx1) gene is closely involved in embryonic kidney development. To explore the role of Tbx1 in acute kidney injury (AKI) and the underlying mechanism, we detected the expression of Tbx1 and components of transforming growth factor-beta (TGF-ß) signaling pathways including TGF-ß, phosphorylated Smad2/3 (p-Smad2/3) and phosphorylated Smad1/5/8 (p-Smad1/5/8) in kidney tissues derived from a rat model for AKI induced by gentamicin (GM). Apoptosis of renal cells was assessed by terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling (TUNEL), along with the expression of two essential genes involved in apoptosis, caspase-3 and Bcl-2. Correlation between Tbx1 expression and the number of TUNEL-positive cells was analyzed by a Spearman test. Expression of TGF-ß, p-Smad2/3 and p-Smad1/5/8 in Tbx1-knockdown NRK cells was also analyzed by real-time RT-PCR and Western blotting. Markedly increased Tbx1 expression was found in the injured kidney tissues, which has activated the TGFß-Smad2/3 pathway whilst suppressed Smad1/5/8 expression. Conversely, decreased TGF-ß and p-Smad2/3 levels, and elevated p-Smad1/5/8 levels were detected in Tbx1-knockdown NRK cells. More apoptotic cells were detected in the injured kidneys, which has well correlated with the expression of Tbx1. Expression of caspase-3 was markedly increased, while Bcl-2 was decreased in the injured kidney tissues. Above findings suggested that activation of Tbx1 is involved in AKI through the TGFß-Smad2/3 pathway. Tbx1 expression may therefore serve as a marker for AKI, and Tbx1-blocking therapies may provide an option for treating GM-induced nephropathy.