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Abstract Background Closing gaps in draft genomes leads to more complete and continuous genome assemblies. The ubiquitous genomic repeats are challenges to the existing gap-closing methods, based on either the k-mer representation by the de Bruijn graph or the overlap-layout-consensus paradigm. Besides, chimeric reads will cause erroneous k-mers in the former and false overlaps of reads in the latter. Results We propose a novel local assembly approach to gap closing, called RegCloser. It represents read coordinates and their overlaps respectively by parameters and observations in a linear regression model. The optimal overlap is searched only in the restricted range consistent with insert sizes. Under this linear regression framework, the local DNA assembly becomes a robust parameter estimation problem. We solved the problem by a customized robust regression procedure that resists the influence of false overlaps by optimizing a convex global Huber loss function. The global optimum is obtained by iteratively solving the sparse system of linear equations. On both simulated and real datasets, RegCloser outperformed other popular methods in accurately resolving the copy number of tandem repeats, and achieved superior completeness and contiguity. Applying RegCloser to a plateau zokor draft genome that had been improved by long reads further increased contig N50 to 3-fold long. We also tested the robust regression approach on layout generation of long reads. Conclusions RegCloser is a competitive gap-closing tool. The software is available at https://github.com/csh3/RegCloser . The robust regression approach has a prospect to be incorporated into the layout module of long read assemblers.

Abstract Background Normalization of RNA-seq data aims at identifying biological expression differentiation between samples by removing the effects of unwanted confounding factors. Explicitly or implicitly, the justification of normalization requires a set of housekeeping genes. However, the existence of housekeeping genes common for a very large collection of samples, especially under a wide range of conditions, is questionable. Results We propose to carry out pairwise normalization with respect to multiple references, selected from representative samples. Then the pairwise intermediates are integrated based on a linear model that adjusts the reference effects. Motivated by the notion of housekeeping genes and their statistical counterparts, we adopt the robust least trimmed squares regression in pairwise normalization. The proposed method (MUREN) is compared with other existing tools on some standard data sets. The goodness of normalization emphasizes on preserving possible asymmetric differentiation, whose biological significance is exemplified by a single cell data of cell cycle. MUREN is implemented as an R package. The code under license GPL-3 is available on the github platform: github.com/hippo-yf/MUREN and on the conda platform: anaconda.org/hippo-yf/r-muren. Conclusions MUREN performs the RNA-seq normalization using a two-step statistical regression induced from a general principle. We propose that the densities of pairwise differentiations are used to evaluate the goodness of normalization. MUREN adjusts the mode of differentiation toward zero while preserving the skewness due to biological asymmetric differentiation. Moreover, by robustly integrating pre-normalized counts with respect to multiple references, MUREN is immune to individual outlier samples.

Abstract Background A key problem in systems biology is the determination of the regulatory mechanism corresponding to a phenotype. An empirical approach in this regard is to compare the expression profiles of cells under two conditions or tissues from two phenotypes and to unravel the underlying transcriptional regulation. We have proposed the method BASE to statistically infer the effective regulatory factors that are responsible for the gene expression differentiation with the help from the binding data between factors and genes. Usually the protein-DNA binding data are obtained by ChIP-seq experiments, which could be costly and are condition-specific. Results Here we report a definition of binding strength based on a probability model. Using this condition-free definition, the BASE method needs only the frequencies of cis-motifs in regulatory regions, thereby the inferences can be carried out in silico. The directional regulation can be inferred by considering down- and up-regulation separately. We showed the effectiveness of the approach by one case study. In the study of the effects of polyunsaturated fatty acids (PUFA), namely, docosahexaenoic (DHA) and eicosapentaenoic (EPA) diets on mouse small intestine cells, the inferences of regulations are consistent with those reported in the literature, including PPARα and NFκB, respectively corresponding to enhanced adipogenesis and reduced inflammation. Moreover, we discovered enhanced RORA regulation of circadian rhythm, and reduced ETS1 regulation of angiogenesis. Conclusions With the probabilistic definition of cis-trans binding affinity, the BASE method could obtain the significances of TF regulation changes corresponding to a gene expression differentiation profile between treatment and control samples. The landscape of the inferred cis-trans regulations is helpful for revealing the underlying molecular mechanisms. Particularly we reported a more comprehensive regulation induced by EPA&DHA diet.

Abstract Background Phred quality scores are essential for downstream DNA analysis such as SNP detection and DNA assembly. Thus a valid model to define them is indispensable for any base-calling software. Recently, we developed the base-caller 3Dec for Illumina sequencing platforms, which reduces base-calling errors by 44-69% compared to the existing ones. However, the model to predict its quality scores has not been fully investigated yet. Results In this study, we used logistic regression models to evaluate quality scores from predictive features, which include different aspects of the sequencing signals as well as local DNA contents. Sparse models were further obtained by three methods: the backward deletion with either AIC or BIC and the L 1 regularization learning method. The L 1-regularized one was then compared with the Illumina scoring method. Conclusions The L 1-regularized logistic regression improves the empirical discrimination power by as large as 14 and 25% respectively for two kinds of preprocessed sequencing signals, compared to the Illumina scoring method. Namely, the L 1 method identifies more base calls of high fidelity. Computationally, the L 1 method can handle large dataset and is efficient enough for daily sequencing. Meanwhile, the logistic model resulted from BIC is more interpretable. The modeling suggested that the most prominent quenching pattern in the current chemistry of Illumina occurred at the dinucleotide “GT”. Besides, nucleotides were more likely to be miscalled as the previous bases if the preceding ones were not “G”. It suggested that the phasing effect of bases after “G” was somewhat different from those after other nucleotide types.

Abstract Several brain neuronal populations transmit both the excitatory and inhibitory neurotransmitters, glutamate, and GABA. However, it remains largely unknown whether these opposing neurotransmitters are co-released simultaneously or are independently transmitted at different times and locations. By recording from acute mouse brain slices, we observed biphasic miniature postsynaptic currents, i.e., minis with time-locked excitatory and inhibitory currents, in striatal spiny projection neurons. This observation cannot be explained by accidental coincidence of monophasic excitatory and inhibitory minis. Interestingly, these biphasic minis could either be an excitatory current leading an inhibitory current or vice versa. Deletion of dopaminergic neurons did not eliminate biphasic minis, indicating that they originate from another source. Importantly, we found that both types of biphasic minis were present in multiple striatal neuronal types and in nine out of ten other brain regions. Overall, co-release of glutamate and GABA appears to be a widespread mode of neurotransmission in the brain.

Abstract Despite the successful application of immune checkpoint therapy, no response or recurrence is typical in lung cancer. Cancer stem cells (CSCs) have been identified as a crucial player in immunotherapy-related resistance. Ferroptosis, a form of cell death driven by iron-dependent lipid peroxidation, is highly regulated by cellular metabolism remolding and has been shown to have synergistic effects when combined with immunotherapy. Metabolic adaption of CSCs drives tumor resistance, yet the mechanisms of their ferroptosis defense in tumor immune evasion remain elusive. Here, through metabolomics, transcriptomics, a lung epithelial-specific Cpt1a-knockout mouse model, and clinical analysis, we demonstrate that CPT1A, a key rate-limiting enzyme of fatty acid oxidation, acts with L-carnitine, derived from tumor-associated macrophages to drive ferroptosis-resistance and CD8+ T cells inactivation in lung cancer. Mechanistically, CPT1A restrains ubiquitination and degradation of c-Myc, while c-Myc transcriptionally activates CPT1A expression. The CPT1A/c-Myc positive feedback loop further enhances the cellular antioxidant capacity by activating the NRF2/GPX4 system and reduces the amount of phospholipid polyunsaturated fatty acids through ACSL4 downregulating, thereby suppressing ferroptosis in CSCs. Significantly, targeting CPT1A enhances immune checkpoint blockade-induced anti-tumor immunity and tumoral ferroptosis in tumor-bearing mice. The results illustrate the potential of a mechanism-guided therapeutic strategy by targeting a metabolic vulnerability in the ferroptosis of CSCs to improve the efficacy of lung cancer immunotherapy.

Oxidative stress and iron accumulation-induced ferroptosis occurs in injured vascular cells and can promote thrombogenesis. Transferrin receptor 1 (encoded by the TFRC gene) is an initial element involved in iron transport and ferroptosis and is highly expressed in injured vascular tissues, but its role in thrombosis has not been determined. To explore the potential mechanism and therapeutic effect of TFRC on thrombogenesis, a DVT model of femoral veins (FVs) was established in rats, and weighted correlation network analysis (WGCNA) was used to identify TFRC as a hub protein that is associated with thrombus formation. TFRC was knocked down by adeno-associated virus (AAV) or lentivirus transduction in FVs or human umbilical vein endothelial cells (HUVECs), respectively. Thrombus characteristics and ferroptosis biomarkers were evaluated. Colocalization analysis, molecular docking and coimmunoprecipitation (co-IP) were used to evaluate protein interactions. Tissue-specific TFRC knockdown alleviated iron overload and redox stress, thereby preventing ferroptosis in injured FVs. Loss of TFRC in injured veins could alleviate thrombogenesis, reduce thrombus size and attenuate hypercoagulability. The protein level of thrombospondin-1 (THBS1) was increased in DVT tissues, and silencing TFRC decreased the protein level of THBS1. In vitro experiments further showed that TFRC and THBS1 were sensitive to erastin-induced ferroptosis and that TFRC knockdown reversed this effect. TFRC can interact with THBS1 in the domain spanning from TSR1-2 to TSR1-3 of THBS1. Amino acid sites, including GLN320 of TFRC and ASP502 of THBS1, could be potential pharmacological targets. Erastin induced ferroptosis affected extracellular THBS1 levels and weakened the interaction between TFRC and THBS1 both in vivo and in vitro, and promoted the interaction between THBS1 and CD47. This study revealed a linked relationship between venous ferroptosis and coagulation cascades. Controlling TFRC and ferroptosis in endothelial cells can be an efficient approach for preventing and treating thrombogenesis.

Sepsis is a clinical syndrome characterized by a dysregulated host response to infection, leading to life-threatening organ dysfunction. It is a high-fatality condition associated with a complex interplay of immune and inflammatory responses that can cause severe harm to vital organs. Sepsis-induced myocardial injury (SIMI), as a severe complication of sepsis, significantly affects the prognosis of septic patients and shortens their survival time. For the sake of better administrating hospitalized patients with sepsis, it is necessary to understand the specific mechanisms of SIMI. To date, multiple studies have shown that programmed cell death (PCD) may play an essential role in myocardial injury in sepsis, offering new strategies and insights for the therapeutic aspects of SIMI. This review aims to elucidate the role of cardiomyocyte’s programmed death in the pathophysiological mechanisms of SIMI, with a particular focus on the classical pathways, key molecules, and signaling transduction of PCD. It will explore the role of the cross-interaction between different patterns of PCD in SIMI, providing a new theoretical basis for multi-target treatments for SIMI.

Previous Chinese research revealed that diarsenic trioxide (As2O3) inhibits acute promyelocytic leukemia (PML) cell proliferation and initiates apoptosis through degradation of the PML-retinoic acid receptor protein. This study was to analyse whether As2O3 also had an effect on hepatocellular carcinoma (HCC) cells. As2O3 effects on various HCC cell lines and primary HCC cells were investigated in time and dose series, including measurements of cell growth, PML mRNA and protein expression, xenografted tumor formation, and the self-renewal Oct4 and hepatocyte marker expressions in mouse model xenografts or cells treated with PML siRNA. The results were analyzed by immunocytochemistry, quantitative reverse transcription PCR and western blotting as well as indocyanine green and Periodic Acid Schiff staining. As2O3 inhibited HCC cell and HCC cell-derived xenograft tumor formation in a time-dependent manner and reduced PML protein expression in HCC cells, but had limited effects on PML mRNA levels in cell nuclei. The HCC cell line HuH7 treated with As2O3 showed a decreased expression of alpha-fetoprotein and increased expression and transcription of mature hepatocyte markers, indicating differentiation of HCC cells into hepatocytes. Cytokeratin 18 protein and mRNA levels as well as tyrosine aminotransferase and apolipoprotein B mRNA transcriptions were enhanced by As2O3 as were the numbers of indocyanine green and Periodic Acid Schiff stained cells. In addition, As2O3 downregulated the expression of Oct4. In conclusion, since As2O3 inhibited HCC cell proliferation and HCC cell-derived xenograft tumor formation it is suggested that an appropriate concentration of As2O3 might be a promising therapy to treat HCC.

Knowledge mapping of medicinal plants enable ordinary people to differentiate between medicinal plants and learn their pharmacological effects, provide assistances and instructions to medical workers during the use of medicinal plants, and support intelligent queries of the properties of traditional medicinal plants. This paper innovatively introduces artificial neural network to the knowledge mapping of medicinal plants, and provides a practical and valuable reference for scientific development and reasonable use of medicinal plants. Firstly, the entity relationships were designed for medical knowledge map, and the definitions, scales, and examples were given for each type of data in the proposed knowledge map of medicinal plants. Next, the authors detailed the ideas of multi-source knowledge fusion, and the acquisition and storage strategies for entity information of medicinal plants. Then, the attention-based bidirectional gated recurrent network was combined with convolutional neural network to detect the genetic relationships between medicinal plants from the angles of semantics and texts. Finally, this paper explains the semantic retrieval algorithm for medicinal plants, and visualizes the knowledge map. The proposed model and semantic retrieval algorithm were proved effective and superior through experiments. It is concluded that: The smaller the batch size, the higher the recognition accuracy of plant entities, and the better the recognition effect. The research findings provide a reference for knowledge mapping in other fields.

Abstract Background Despite accumulating epidemiological studies support that diabetes increases the risk of Alzheimer’s disease (AD), the causal associations between diabetes and AD remain inconclusive. The present study aimed to explore: i) whether diabetes is causally related to the increased risk of AD; ii) and if so, which diabetes-related physiological parameter is associated with AD; iii) why diabetes drugs can be used as candidates for the treatment of AD. Two-sample Mendelian randomization (2SMR) was employed to perform the analysis. Results Firstly, the 2SMR analysis provided a suggestive association between genetically predicted type 1 diabetes (T1D) and a slightly increased AD risk (OR = 1.04, 95% CI = [1.01, 1.06]), and type 2 diabetes (T2D) showed a much stronger association with AD risk (OR = 1.34, 95% CI = [1.05, 1.70]). Secondly, further 2SMR analysis revealed that diabetes-related physiological parameters like fasting blood glucose and total cholesterol levels might have a detrimental role in the development of AD. Thirdly, we obtained 74 antidiabetic drugs and identified SNPs to proxy the targets of antidiabetic drugs. 2SMR analysis indicated the expression of three target genes, ETFDH, GANC, and MGAM, were associated with the increased risk of AD, while CPE could be a protective factor for AD. Besides, further PPI network found that GANC interacted with MGAM, and further interacted with CD33, a strong genetic locus related to AD. Conclusions In conclusion, the present study provides evidence of a causal association between diabetes and increased risk of AD, and also useful genetic clues for drug development.

The increasing prevalence of intelligent driving sightseeing vehicles in the tourism industry underscores the critical importance of real-time planning for effective local obstacle avoidance paths when these vehicles encounter obstacles during operation. To fulfill this requirement, it is imperative to establish real-time dynamic perception as the foundational element. Thus, this paper introduces a novel local path planning algorithm founded on the principles of spatial perception. In the diverse array of road environments characterized by varying spatial features, sightseeing vehicles can effectively achieve safe and comfortable obstacle avoidance maneuvers. The proposed approach employs a high-precision positioning module and a real-time dynamic perception module to acquire real-time spatial information pertaining to the sightseeing vehicle and the road environment. It comprehensively integrates spatiotemporal safety constraints and obstacle avoidance curvature constraints to derive control points for the obstacle avoidance path. Specific control points undergo optimization and adjustment, ultimately resulting in the generation of the obstacle avoidance spatiotemporal path through discrete interpolation using B-spline curves. These locally tailored paths are subsequently compared with local obstacle avoidance paths generated using Bezier curves. The empirical validation of the proposed local obstacle avoidance path algorithm is conducted through a combination of simulation analysis and real vehicle verification. The research outcomes affirm that the algorithm can indeed produce smoother local obstacle avoidance paths, resulting in reduced front-wheel steering angles and yaw angle variations. This enhancement substantially contributes to the overall stability of sightseeing vehicles during obstacle avoidance maneuvers.

To prepare high-performance asphalt cold replacement liquids, a composite modification preparation process was used to synthesize a styrene–butadiene–styrene (SBS) block copolymer, styrene–butadiene–rubber (SBR) copolymer, and polyphosphate acid (PPA), erucamide/diesel/acrylic ester as surfactants/diluents/reinforcing agent respectively. These six were blended to prepare an asphalt cold replenishment liquid (ACRL), and its modification effect on base asphalt was studied using base asphalt as the control group. A comparative study was conducted on the high- and low-temperature rheological properties and microstructure. The modification mechanisms of high-temperature asphalt cold replenishment liquid (H-ACRL) and low-temperature asphalt cold replenishment liquid (L-ACRL) were studied through dynamic shear rheometry, bending beam rheometry, Fourier-transform infrared spectroscopy, fluorescence microscopy, and atomic force microscopy. The results showed that the optimal dosages of PPA/SBS/SBR in H-ACRL and L-ACRL were (1.2%/5%/3%) and (0.9%/4%/4%), respectively. Within the optimal dosage range, the particles in the cold replenishment fluid were uniformly dispersed in the asphalt to form a dense and continuous network. No new functional groups were generated during the preparation of H-ACRL and L-ACRL, showing that the modifiers (surfactants/diluents/reinforcing agent) were only physically blended with the asphalt.

This study aimed to reveal the mechanism by which long noncoding RNAs (lncRNAs) modulate hepatocellular carcinoma (HCC) by regulating mRNA via the N6-methyladenosine (m6A) enzyme. The expression and clinical data of 365 HCC patients and 50 healthy control samples were downloaded from the the Cancer Genome Atlas (TCGA) database. Differentially expressed lncRNAs (DElncRNAs) and differentially expressed mRNAs (DEmRNAs) screened using limma packages from the R. m6A2Target database were used to predict the relationship between m6A enzyme-lncRNA and m6A enzyme-mRNA. The mRNAs in the lncRNA-m6A enzyme-mRNA network were subjected to enrichment analysis. Cox regression analysis was used to screen for RNAs significantly related to HCC prognosis. The expression of differentially expressed RNAs (DERs) was verified using the TCGA dataset and GSE55092. Eighty-five DElncRNAs and 747 DEmRNAs were identified. The mRNAs in the lncRNA-m6A enzyme-mRNA network were primarily involved in mitotic cell division, the p53 signaling pathway, and the cell cycle. Three lncRNAs and 14 mRNAs were significantly associated with HCC prognosis. Furthermore, the expression of 12 DERs differed significantly between patients in the early and advanced stages. LINC00665 was predicted to regulate 11 mRNAs by modulating IGF2BP1, IGF2BP2, and YTHDF1. Thus, this study provides new insights into the roles of lncRNA and m6A enzymes in HCC.

With the rapid advancement of artificial neural network (ANN) algorithms, many researchers have applied these methods to mine gas prediction and achieved numerous research achievements. It is of great significance to study methods that can accurately predict the gas content for the prevention of gas disasters in mining areas. In order to enhance the accuracy, stability, and generalization capability of the gas content prediction model, the GASA-KELM prediction model was established using the GASA algorithm to improve the KELM initial parameter assignment method, and the prediction model based on BPNN and SVM was established under the same conditions. The experimental results show that the GASA-BPNN model failed to achieve the desired outcome within 800 iterations. On the other hand, the GASA-SVM and GASA-KELM models accomplished the goal in significantly fewer iterations, taking only 673 and 487 iterations, respectively. Moreover, the overall average relative errors of the cross-validated gas content predictions were 15.74%, 13.85%, and 9.87% for the three models, respectively. Furthermore, the total average variance of the test set was 3.99, 2.76, and 2.05 for the GASA-BPNN, GASA-SVM, and GASA-KELM models, respectively. As a result, compared with other ANN models, the GASA-KELM model demonstrates higher accuracy, stronger prediction stability, and generalization ability in the practical application. This novel model provides a basis for accurately predicting gas content and proposing effective regional gas management measures.

Segmentation of skin lesion images facilitates the early diagnosis of melanoma. However, this remains a challenging task due to the diversity of target scales, irregular segmentation shapes, low contrast, and blurred boundaries of dermatological graphics. This paper proposes a multi-scale feature fusion network (MSF-Net) based on comprehensive attention convolutional neural network (CA-Net). We introduce the spatial attention mechanism in the convolution block through the residual connection to focus on the key regions. Meanwhile, Multi-scale Dilated Convolution Modules (MDC) and Multi-scale Feature Fusion Modules (MFF) are introduced to extract context information across scales and adaptively adjust the receptive field size of the feature map. We conducted many experiments on the public data set ISIC2018 to verify the validity of MSF-Net. The ablation experiment demonstrated the effectiveness of our three modules. The comparison experiment with the existing advanced network confirms that MSF-Net can achieve better segmentation under fewer parameters.

Abstract Skeletal interoception regulates bone homeostasis through the prostaglandin E2 (PGE2) concentration in bone. Vertebral endplates undergo ossification and become highly porous during intervertebral disc degeneration and aging. We found that the PGE2 concentration was elevated in porous endplates to generate spinal pain. Importantly, treatment with a high-dose cyclooxygenase 2 inhibitor (celecoxib, 80 mg·kg−1 per day) decreased the prostaglandin E2 concentration and attenuated spinal pain in mice with lumbar spine instability. However, this treatment impaired bone formation in porous endplates, and spinal pain recurred after discontinuing the treatment. Interestingly, low-dose celecoxib (20 mg·kg−1 per day, which is equivalent to one-quarter of the clinical maximum dosage) induced a latent inhibition of spinal pain at 3 weeks post-treatment, which persisted even after discontinuing treatment. Furthermore, when the prostaglandin E2 concentration was maintained at the physiological level with low-dose celecoxib, endplate porosity was reduced significantly, which was associated with decreased sensory nerve innervation and spinal pain. These findings suggest that low-dose celecoxib may help to maintain skeletal interoception and decrease vertebral endplate porosity, thereby reducing sensory innervation and spinal pain in mice.

Introduction: Metabolic deregulation, a hallmark of cancer, fuels cancer cell growth and metastasis. Phosphoserine phosphatase (PSPH), an enzyme of the serine metabolism pathway, has been shown to affect patients’ prognosis in many cancers but its significance in neuroblastoma remains unknown. Here, we show that the functional role and potential mechanism of PSPH and it is correlated with survival of neuroblastoma patients.Patients and Methods: The TARGET dataset (n = 151) and our hospital-based cases (n = 55) were used for assessing the expression level of PSPH associated with survival in neuroblastoma patients, respectively. Then, in vitro experiments were performed to define the role of PSPH in neuroblastoma. The ESTIMATE and TIMER algorithms were utilized to examine the correlation between PSPH expression level and abundance of immune cells. Further, Kaplan-Meier survival analysis was performed to evaluate the effect of both PSPH and immune cells on patients’ prognosis.Results: High expression of PSPH was significantly associated with unfavorable overall survival (OS) and event-free survival (EFS) in both the TARGET dataset and our hospital-based cases, and was an independent predictor of OS (hazard ratio, 2.00; 95% confidence intervals, 1.21–3.30, p = 0.0067). In vitro experiments showed that high expression of PSPH significantly promoted cell growth and metastasis. Further, the ESTIMATE result suggested that high expression level of PSPH was negatively associated with low stromal and ESTIMATE score. Specifically, high PSPH expression was found to be negatively associated with CD8+ T cell, macrophages and neutrophils, which negatively affected survival of neuroblastoma patients (p < 0.0001, p = 0.0005, and p = 0.0004, respectively).Conclusion: These findings suggested that PSPH expression could be a promising indicator for prognosis and immunotherapy in neuroblastoma patients by potentially influencing infiltration levels of immune cells.

Rationale: Endoplasmic reticulum (ER) stress and mitochondrial dysfunction are important mechanisms of atrial remodeling, predisposing to the development of atrial fibrillation (AF) in type 2 diabetes mellitus (T2DM). However, the molecular mechanisms underlying these processes especially their interactions have not been fully elucidated. Objective: To explore the potential role of ER stress–mitochondrial oxidative stress in atrial remodeling and AF induction in diabetes. Methods and results: Mouse atrial cardiomyocytes (HL-1 cells) and rats with T2DM were used as study models. Significant ER stress was observed in the diabetic rat atria. After treatment with tunicamycin (TM), an ER stress agonist, mass spectrometry (MS) identified several known ER stress and calmodulin proteins, including heat shock protein family A (HSP70) member [HSPA] 5 [GRP78]) and HSPA9 (GRP75, glucose-regulated protein 75). In situ proximity ligation assay indicated that TM led to increased protein expression of the IP3R1–GRP75–VDAC1 (inositol 1,4,5-trisphosphate receptor 1–glucose-regulated protein 75–voltage-dependent anion channel 1) complex in HL-1 cells. Small interfering RNA silencing of GRP75 in HL-1 cells and GRP75 conditional knockout in a mouse model led to impaired calcium transport from the ER to the mitochondria and alleviated mitochondrial oxidative stress and calcium overload. Moreover, GRP75 deficiency attenuated atrial remodeling and AF progression in Myh6-Cre+/Hspa9flox/flox + TM mice. Conclusions: The IP3R1–GRP75–VDAC1 complex mediates ER stress–mitochondrial oxidative stress and plays an important role in diabetic atrial remodeling.

Rapid improvements in underwater vehicle technology have led to a significant increase in the demand for underwater sound absorption materials. These materials, unlike their counterparts utilized in air, must have high hydrostatic pressure resistance, corrosion resistance, and other advantageous attributes. This necessitates the development of innovative, composite sound-absorbing materials with multifunctional properties, which presents substantial challenges for researchers. In this comprehensive review, we systematically analyze and categorize the mechanisms governing underwater sound absorption, hydrostatic pressure resistance, and corrosion prevention while considering related research advances. Furthermore, we provide an extensive overview of research advancements, existing challenges, and potential solutions pertaining to multifunctional and integrated underwater sound-absorbing materials. This review aims to serve as a valuable resource for future investigations into the development and optimization of multifunctional integrated underwater sound-absorbing materials, thereby contributing to the advancement of underwater vehicle technology.

The FDA-approved drug edaravone has a neuroprotective effect on spinal cord injury (SCI) and many other central nervous system diseases. However, its molecular mechanism remains unclear. Since edaravone is a lipid peroxidation scavenger, we hypothesize that edaravone exerts its neuroprotective effect by inhibiting ferroptosis in SCI. Edaravone treatment after SCI upregulates glutathione peroxidase 4 (GPX4) and system Xc-light chain (xCT), which are anti-ferroptosis proteins. It downregulates pro-ferroptosis proteins Acyl-CoA synthetase long-chain family member 4 (ACSL4) and 5-lipoxygenase (5-LOX). The most significant changes in edaravone treatment occur in the acute phase, two days post injury. Edaravone modulates neuronal GPX4/ACSL4/5-LOX in the spinal segment below the lesion, which is critical for maintaining locomotion. Moreover, the GPX4/ACSL4/5-LOX in motor neuron is also modulated by edaravone in the spinal cord. Therefore, secondary injury below the lesion site is reversed by edaravone via ferroptosis inhibition. The cytokine array revealed that edaravone upregulated some anti-inflammatory cytokines such as IL-10, IL-13, and adiponectin. Edaravone reduced microgliosis and astrogliosis, indicating reduced neuroinflammation. Edaravone has a long-term effect on neuronal survival, spinal cord tissue sparing, and motor function recovery. In summary, we revealed a novel mechanism of edaravone in inhibiting neuronal ferroptosis in SCI. This mechanism may be generalizable to other neurological diseases.

Apodemus is the most common small rodent species in the Palearctic realm and an ideal species for biogeographical research and understanding environmental changes. Elucidating phylogenetic relationships will help us better understand species adaptation and genetic evolution. Due to its stable structure, maternal inheritance, and rapid evolution, the mitogenome has become a hot spot for taxonomic and evolutionary studies. In this research, we determined the mitochondrial genome of Apodemus agrarius ningpoensis and Apodemus draco draco and studied the phylogeny of Muridae using ML and BI trees based on all known complete mitogenomes. The mitochondrial genome of Apodemus agrarius ningpoensis was 16,262 bp, whereas that of Apodemus draco draco was 16,222 bp, and both encoded 13 protein-coding genes, 2 ribosomal RNA genes, and 22 transfer RNA genes. Analysis of base composition showed a clear A-T preference. All tRNAs except tRNASer and tRNALys formed a typical trilobal structure. All protein-coding genes contained T- and TAA as stop codons. Phylogeny analysis revealed two main branches in the Muridae family. Apodemus agrarius ningpoensis formed sister species with Apodemus chevrieri, whereas Apodemus draco draco with Apodemus latronum. Our findings provide theoretical basis for future studies focusing on the mitogenome evolution of Apodemus.

Hooded Cranes (Grus monacha) rely on wetlands for the majority of their life cycle and respond to the environmental conditions during the wintering period. Future conservation planning should be driven by an understanding of how cranes respond to environmental factors at degraded wetland sites and the changes in their spatio-temporal distribution. In recent years, the spatial and temporal distribution of waterbirds and determinant factors have become a research focus. However, research on the specific factors influencing the relative abundance of Hooded Cranes from multiple perspectives in the different habitat patches at Shengjin and Caizi Lakes is lacking. Therefore, from 2021 to 2022, we investigated the quantity and distribution of Hooded Cranes in the upper part of Shengjin and Baitu Lake part of Caizi Lakes. We considered multiple habitat variables, including patch size, food biomass, food availability, and human disturbance, and analyzed the dynamic changes in the distribution of the population in different wintering periods. We used model selection and averaging to select the best model and identify key variables. During different wintering periods, the spatio-temporal distribution of the crane population differed in the upper part of Shengjin Lake, but the crane was mainly distributed in the northern part of the Baitu Lake part of Caizi Lake. The model that included food biomass and patch size was the best for predicting the relative abundance of Hooded Cranes. Cranes foraged in areas with large patches and abundant food resources. Therefore, we suggest reserving patch integrity and availability in the current habitats and protecting and restoring the main food resources to provide high-quality habitat patches and plentiful food resources for wintering populations of Hooded Cranes.

In order to solve the problems of low accuracy and low efficiency of point cloud registration for stereo camera systems, we propose a binocular stereo camera point cloud registration method based on IWOA and Improved ICP. We propose the following approaches in this paper—the registration process is divided into two steps to complete the initial coarse registration and the exact registration. In the initial registration stage, an improved Whale Optimization Algorithm (IWOA) based on nonlinear convergence factor and adaptive weight coefficients was proposed to realize the initial registration in combination with the RANSAC algorithm, and the obtained transformation matrix was used as the initial estimate of the subsequent exact registration algorithm. In the second step of the exact registration stage, an IICP algorithm with the introduction of normal vector weighting constraints at key points was proposed for achieving point cloud exact registration. This algorithm was verified by using Stanford point clouds (bunnies and monkeys) and our own point clouds algorithm, and the proposed algorithm in this paper has high registration accuracy, improved registration speed, and convergence speed.

Beige fat dissipates energy and functions as a defense against cold and obesity, but the mechanism for its development is unclear. We found that interleukin (IL)-25 signaling through its cognate receptor, IL-17 receptor B (IL-17RB), increased in adipose tissue after cold exposure and β3-adrenoceptor agonist stimulation. IL-25 induced beige fat formation in white adipose tissue (WAT) by releasing IL-4 and IL-13 and promoting alternative activation of macrophages that regulate innervation and up-regulate tyrosine hydroxylase (TH) up-regulation to produce more catecholamine including norepinephrine (NE). Blockade of IL-4Rα or depletion of macrophages with clodronate-loaded liposomes in vivo significantly impaired the beige fat formation in WAT. Mice fed with a high-fat diet (HFD) were protected from obesity and related metabolic disorders when given IL-25 through a process that involved the uncoupling protein 1 (UCP1)-mediated thermogenesis. In conclusion, the activation of IL-25 signaling in WAT may have therapeutic potential for controlling obesity and its associated metabolic disorders. Beige fat dissipates energy and functions as a defense against cold and obesity, but the mechanism for its development is unclear. This study reveals that IL-25 is upregulated upon cold exposure and induces beige fat formation, with corresponding benefits to metabolic homeostasis; the effects of IL-25 are mediated by changes in macrophage polarization, which in turn influence tissue innervation.

Lead (Pb) is among the deleterious heavy metal and has caused global health concerns due to its tendency to cause a detrimental effect on the development of the central nervous system (CNS). Despite being a serious health concern, treatment of Pb poisoning is not yet available, reflecting the pressing need for compounds that can relieve Pb-induced toxicity, especially neurotoxicity. In the quest of exploring protective strategies against Pb-induced developmental neurotoxicity, compounds from natural resources have gained increased attention. Chlorogenic acid (CGA) and its analogues neochlorogenic acid (NCGA) and cryptochlorogenic acid (CCGA) are the important phenolic compounds widely distributed in plants. Herein, utilizing zebrafish as a model organism, we modeled Pb-induced developmental neurotoxicity and investigated the protective effect of CGA, NCGA, and CCGA co-treatment. In zebrafish, Pb exposure (1,000 μg/L) for 5 days causes developmental malformation, loss of dopaminergic (DA) neurons, and brain vasculature, as well as disrupted neuron differentiation in the CNS. Additionally, Pb-treated zebrafish exhibited abnormal locomotion. Notably, co-treatment with CGA (100 µM), NCGA (100 µM), and CCGA (50 µM) alleviated these developmental malformation and neurotoxicity induced by Pb. Further underlying mechanism investigation revealed that these dietary phenolic acid compounds may ameliorate Pb-induced oxidative stress and autophagy in zebrafish, therefore protecting against Pb-induced developmental neurotoxicity. In general, our study indicates that CGA, NCGA, and CCGA could be promising agents for treating neurotoxicity induced by Pb, and CCGA shows the strongest detoxifying activity.

Precise and efficient insertion of large DNA fragments into somatic cells using gene editing technologies to label or modify endogenous proteins remains challenging. Non-specific insertions/deletions (INDELs) resulting from the non-homologous end joining pathway make the process error-prone. Further, the insert is not readily removable. Here, we describe a method called CRISPR-mediated insertion of exon (CRISPIE) that can precisely and reversibly label endogenous proteins using CRISPR/Cas9-based editing. CRISPIE inserts a designer donor module, which consists of an exon encoding the protein sequence flanked by intron sequences, into an intronic location in the target gene. INDELs at the insertion junction will be spliced out, leaving mRNAs nearly error-free. We used CRISPIE to fluorescently label endogenous proteins in mammalian neurons in vivo with previously unachieved efficiency. We demonstrate that this method is broadly applicable, and that the insert can be readily removed later. CRISPIE permits protein sequence insertion with high fidelity, efficiency, and flexibility.

Abstract Background The protective effect of metformin (MET) on abdominal aortic aneurysm (AAA) has been reported. However, the related mechanism is still poor understood. In this study, we deeply investigated the role of metformin in AAA pathophysiology. Methods Angiotensin II (Ang-II) was used to construct the AAA model in ApoE −/− mice. The related mechanism was explored using Western blot and quantitative real time PCR (qRT-PCR). We also observed the morphological changes in the abdominal aorta and the influence of metformin on biological behaviors of rat abdominal aortic VSMCs. Results The PI3K/AKT/mTOR pathway was activated in aneurysmal wall tissues of AAA patients and rat model. Treatment with metformin inhibited the breakage and preserved the elastin structure of the aorta, the loss of collagen, and the apoptosis of aortic cells. In addition, metformin significantly suppressed the activation of the PI3K/AKT/mToR pathway and decreased the mRNA and protein levels of LC3B and Beclin1, which were induced by Ang-II. Moreover, PI3K inhibitors enhanced the effect of metformin while PI3K agonists largely reversed this effect. Interestingly, the cell proliferation, apoptosis, migration and autophagy of vascular smooth muscle cells (VSMCs) induced by Ang-II were also decreased following metformin treatment. PI3K inhibitors and agonists strengthened and weakened the effects of metformin in VSMCs, respectively. Conclusions Metformin represses the pathophysiology of AAA by inhibiting the activation of PI3K/AKT/mTOR/autophagy pathway. This repression may be useful as a new therapeutic strategy for AAA.

Ischemic cerebrovascular disease is a significant and common public health issue worldwide. The emerging roles of mesenchymal stem cells (MSCs)-derived extracellular vesicles (EVs) in ischemic neuronal injury continue to be investigated. The current study aimed to investigate the role of EV-derived miR-132 from MSCs in ischemic neuronal injury. EVs were initially isolated from bone MSCs (BMSCs) and subsequently evaluated. A middle cerebral artery occlusion (MCAO) mouse model was constructed with the neurological function evaluated through a series of neurological scores, a pole test, and a foot fault test. Histopathological changes, neuron viability, and apoptosis, as well as cerebral infarction, were detected by hematoxylin and eosin (HE) staining and 2,3,5-triphenyltetrazolium hydrochloride (TTC) staining. The targeting relationship between microRNA (miR)-132 and Activin receptor type IIB (Acvr2b) was further confirmed based on dual-luciferase reporter gene assay results. Loss- and gain-of-function assays were conducted to elucidate the role of miR-132, EV-derived miR-132, Acvr2b, and Smad2 in oxygen-glucose deprivation (OGD)-treated neurons, and in mice models. Neuronal cell viability and apoptosis were evaluated via Cell Counting kit-8 (CCK-8) and flow cytometry. Our results indicated that Acvr2b was highly expressed, while miR-132 was poorly expressed in the MCAO mice and OGD-treated neurons. Acvr2b silencing or upregulation of miR-132 led to an elevation in neuronal activity, decreased neuronal apoptosis, reduced expression of Bax, and cleaved-caspase 3, as well as increased Bcl-2 expression. Acvr2b expression was targeted and inhibited by miR-132. EV-derived Acvr2b promoted activation of phosphorylated-Smad2 (p-Smad2)/c-jun signaling pathway, ultimately inducing neuronal injury. Our study provides evidence demonstrating that the overexpression of c-jun inhibits the protective role of MSCs-derived EV-miR-132 in neuronal injury. Upregulation of EV-derived miR-132 released from MSCs attenuates ischemic neuronal injury by inhibiting Smad2/c-jun pathways via the suppression of Acvr2b.

Renal fibrosis represents a key pathophysiological process in patients with chronic kidney diseases (CKD) and is typically associated with a poor prognosis. Renal tubular epithelial cells (RTECs), in response to a host of pro-fibrogenic stimuli, can trans-differentiate into myofibroblast-like cells and produce extracellular matrix proteins to promote renal fibrosis. In the present study we investigated the role of histone deacetylase 11 (HDAC11) in this process and the underlying mechanism. We report that expression levels of HDAC11 were up-regulated in the kidneys in several different animal models of renal fibrosis. HDAC11 was also up-regulated by treatment of Angiotensin II (Ang II) in cultured RTECs. Consistently, pharmaceutical inhibition with a small-molecule inhibitor of HDAC11 (quisinostat) attenuated unilateral ureteral obstruction (UUO) induced renal fibrosis in mice. Similarly, HDAC11 inhibition by quisinostat or HDAC11 depletion by siRNA blocked Ang II induced pro-fibrogenic response in cultured RTECs. Mechanistically, HDAC11 interacted with activator protein 2 (AP-2α) to repress the transcription of Kruppel-like factor 15 (KLF15). In accordance, KLF15 knockdown antagonized the effect of HDAC11 inhibition or depletion and enabled Ang II to promote fibrogenesis in RTECs. Therefore, we data unveil a novel AP-2α-HDAC11-KLF15 axis that contributes to renal fibrosis.

Kisspeptin is a multifunctional peptide encoded by the Kiss1 gene that plays critical roles in mammalian puberty onset modulation and fertility maintenance in the hypothalamus. Understanding how Kiss1 expression is regulated is essential for elucidating the molecular mechanisms responsible for these reproductive events. In this study, we constructed an in vitro dual fluorescence reporter system to facilitate high throughput screening of effectors influencing the expression of Kiss1. In GT1‐7 cells, an enhanced GFP gene was placed under the control of the Kiss1 gene regulatory elements and translated together with this gene. A tdTomato gene cassette was simultaneously introduced into the same cell for normalization of the fluorescence signal. After treatment with different effectors, the cells were analyzed by flow cytometry. We first tested the efficacy of the system using canonical regulators and then carried out high throughput functional screening to identify chemical compounds that can regulate Kiss1 gene expression. Of 22 tested compounds from natural sources, 13 significantly affected Kiss1 expression. Verification by western blot and quantitative reverse transcription PCR (qRT‐PCR) assays and structural analysis identified two chalcone compounds as possible regulators of Kiss1 gene expression. This system may be suitable for gene functional analysis, drug screening and pharmaceutical studies.

It is vital to understand the conservation and evolution of gene promoter sequences in order to understand environmental adaptation. The level of promoter conservation varies greatly between housekeeping (HK) and tissue-specific (TS) genes, denoting differences in the strength of the evolutionary constraints. Here, we analyzed promoter conservation and evolution to exploit differential regulation between HK and TS genes. The analysis of conserved elements showed CpG islands, short tandem repeats and G-quadruplex sequences are highly enriched in HK promoters relative to TS promoters. In addition, the type and density of regulatory motifs in TS promoters are much higher than HK promoters, indicating that TS genes show more complex regulatory patterns than HK genes. Moreover, the evolutionary dynamics of promoters showed similar evolutionary trend to coding sequences. HK promoters suffer more stringent selective pressure in the long-term evolutionary process. HK genes tend to show increased upstream sequence conservation due to stringent selection pressures acting on the promoter regions. The specificity of TS gene expression may be due to complex regulatory motifs acting in different tissues or conditions. The results from this study can be used to deepen our understanding of adaptive evolution.

Benzyl isothiocyanate (BITC) has been shown to inhibit invasion and induce apoptosis of various types of cancer. However, its role on human oral squamous cell carcinoma (OSCC) cells is still not well elucidated. In the present study, we investigated the effect of BITC on apoptosis and invasion of SCC9 cells, and its underlying mechanisms in vitro and in vivo. SCC9 cells were exposed to BITC (5 and 25 μM) for 24 and 48 h. Cell growth, apoptosis, invasion, and migration were detected in vitro by MTT, FITC-conjugated annexin V/propidium iodide staining followed by flow cytometry, Matrigel-coated semi-permeable modified Boyden, and wound-healing assay. S100A4, PUMA, and MMP-9 expressions were detected to investigate its mechanisms. Xenotransplantation experiments were used to investigate the role of BITC on tumor growth and lung metastasis. BITC inhibited cell viability and induced cell apoptosis in a dose- and time-dependent manner through upregulation of PUMA signals. BITC inhibited cell invasion and migration by downregulation of S100A4 dependent MMP-9 signals. The ip administration of BITC reduced tumor growth but not lung metastasis of SCC9 cells subcutaneously implanted in nude mice. BITC treatment activated pro-apoptotic PUMA and inhibited S100A4-dependent MMP-9 signals, resulting in the inhibition of cell growth and invasion in cultured and xenografted SCC9 cells. Thereby, BITC is a potential therapeutic approach for OSCC.

Background Self-renewal and pluripotency are considered as unwavering features of embryonic stem cells (ESCs). How ESCs regulate the self-renewal and differentiation is a central question in development and regenerative medicine research. Epidermal growth factor receptor (EGFR) was identified as a critical regulator in embryonic development, but its role in the maintenance of ESCs is poorly understood. Methods Here, EGFR was disrupted by its specific inhibitor AG1478 in mouse ESCs (mESCs), and its self-renewal and pluripotency were characterized according to their proliferation, expression of pluripotency markers, embryoid body (EB) formation, and mRNA expression patterns. We also used another EGFR inhibitor (gefitinib) and RNA interference assay to rule out the possibility of non-specific effects of AG1478. Results EGFR inhibition by AG1478 treatment in mESCs markedly reduced cell proliferation, caused cell cycle arrest at G0/G1 phase, and altered protein expressions of the cell cycle regulatory genes (CDK2 (decreased 11.3%) and proliferating cell nuclear antigen (decreased 25.2%)). The immunoreactivities and protein expression of pluripotency factors (OCT4 (decreased 26.9%)) also dramatically decreased, while the differentiation related genes (GATA4 (increased 1.6-fold)) were up-regulated in mESCs after EGFR inhibition. Meanwhile, EGFR inhibition in mESCs disrupted EB formation, indicating its impaired pluripotency. Additionally, the effects observed by EGFR inhibition with another inhibitor gefitinib and siRNA were consistent with those observed by AG1478 treatment in mESCs. These effects were manifested in the decreased expression of proliferative and pluripotency-related genes and the increased expression of genes involved in differentiation. Moreover, RNA-seq analysis displayed that transcript profiling was changed significantly after EGFR inhibition by AG1478. A large number of differentially expressed genes were involved in cell cycle, apoptotic process, epigenetic modification, and metabolic process, which were related to self-renewal and pluripotency, confirming that EGFR deficiency impaired self-renewal and pluripotency in mESCs. Conclusions Taken together, our results demonstrated the importance of EGFR in guarding the stemness of mESCs.

A broadband generalized sidelobe canceler (Broadband-GSC) application for near-field beamforming is proposed. This approach is implemented in the wavelet domain. Broadband-GSC provides a set of complex, adapted apodization weights for each wavelet subband. The proposed method constrains interference and noise signal to improve the lateral resolution with only one single emission. Performance of the proposed beamforming is tested on simulated data obtained with Field II. Experiments have proved that the new beamforming can significantly increase the image quality compared with delay-and-sum (DAS) and synthetic aperture (SA). Imaging of scattering points show that Broadband-GSC improves the lateral resolution by 43.2% and 58.0% compared with SA and DAS, respectively. Meanwhile，Broadband-GSC reduces the peak sidelobe level by 11.6 dB and 26.4 dB compared with SA and DAS, respectively. Plane wave emission experiment indicates that Broadband-GSC can improve the lateral resolution by 44.2% compared with DAS. Furthermore, the new beamforming introduces the possibility for higher frame-rate and higher investigation depth with increased lateral resolution.

Housekeeping genes are ubiquitously expressed and maintain basic cellular functions across tissue/cell type conditions. The present study aimed to develop a set of pig housekeeping genes and compare the structure, evolution and function of housekeeping genes in the human–pig lineage. By using RNA sequencing data, we identified 3,136 pig housekeeping genes. Compared with human housekeeping genes, we found that pig housekeeping genes were longer and subjected to slightly weaker purifying selection pressure and faster neutral evolution. Common housekeeping genes, shared by the two species, achieve stronger purifying selection than species-specific genes. However, pig- and human-specific housekeeping genes have similar functions. Some species-specific housekeeping genes have evolved independently to form similar protein active sites or structure, such as the classical catalytic serine–histidine–aspartate triad, implying that they have converged for maintaining the basic cellular function, which allows them to adapt to the environment. Human and pig housekeeping genes have varied structures and gene lists, but they have converged to maintain basic cellular functions essential for the existence of a cell, regardless of its specific role in the species. The results of our study shed light on the evolutionary dynamics of housekeeping genes.

Breast cancer is the leading cause of cancer death in women, and early detection can reduce mortality. Architectural distortion (AD) is a feature of clinical manifestations for breast cancer, however, due to its complex structure and low detection accuracy, which cause a high mortality of breast cancer. In order to improve the accuracy of AD detection and reduce the mortality of breast cancer, this paper proposes a new method by combining the non-subsampled contourlet transform (NSCT) with the improved pulse coupled neural network (PCNN). Firstly, the top−bottom hat transformation and the exponential transformation are employed to enhance the image. Secondly, the NSCT is employed to expand the overall contrast of the mammograms and filter out the noise. Finally, the improved PCNN by the maximum inter-class variance threshold selection method is employed to complete the AD detection. This proposed approach is tested on the public and authoritative database—Digital Database for Screening Mammography (DDSM). The specificity of the method is 98.73%, the accuracy is 93.16%, and the F1-score is 79.80%, and the area under curve (AUC) of the receiver operating characteristic (ROC) curve is 0.93, these results clearly demonstrate that the proposed method is comparable with those methods in recent literatures. This proposed method is simple, furthermore it can achieve high accuracy and help doctors to perform computer-aided detection of AD effectively.

Melanocyte loss in vitiligo vulgaris is believed to be an autoimmune process. Macrophage migration inhibitory factor (MIF) is involved in many autoimmune skin diseases. We determined the possible role of MIF in the pathogenesis of vitiligo vulgaris, and describe the relationship between MIF expressions and disease severity and activity. Serum MIF concentrations and mRNA levels in PBMCs were measured in 44 vitiligo vulgaris patients and 32 normal controls, using ELISA and real-time RT-PCR. Skin biopsies from 15 patients and 6 controls were analyzed by real-time RT-PCR. Values are reported as median (25th-75th percentile). Serum MIF concentrations were significantly increased in patients [35.81 (10.98-43.66) ng/mL] compared to controls [7.69 (6.01-9.03) ng/mL]. MIF mRNA levels were significantly higher in PBMCs from patients [7.17 (3.59-8.87)] than controls [1.67 (1.23-2.42)]. There was also a significant difference in MIF mRNA levels in PBMCs between progressive and stable patients [7.86 (5.85-9.13) vs 4.33 (2.23-8.39)] and in serum MIF concentrations [40.47 (27.71-46.79) vs 26.80 (10.55-36.07) ng/mL]. In addition, the vitiligo area severity index scores of patients correlated positively with changes of both serum MIF concentrations (r = 0.488) and MIF mRNA levels in PBMCs (r = 0.426). MIF mRNA levels were significantly higher in lesional than in normal skin [2.43 (2.13-7.59) vs 1.18 (0.94-1.83)] and in patients in the progressive stage than in the stable stage [7.52 (2.43-8.84) vs 2.13 (1.98-2.64)]. These correlations suggest that MIF participates in the pathogenesis of vitiligo vulgaris and may be useful as an index of disease severity and activity.

Background: In previous studies, both 17β-estradiol (E2) and resveratrol (RES) were reported to protect intervertebral disc cells against aberrant apoptosis. Given that E2 has a better anti-apoptotic effect with more cancer risk and RES has an anti-apoptotic effect with less cancer risk, the combined use of E2 with RES is promising in developing clinical therapies to treat apoptosis-related diseases such as intervertebral disc degeneration in the future. Objective: The purpose of this study was to explore the combined effect of E2 with RES on rat nucleus pulposus cells and the underlying mechanisms. Methods: TUNEL assay and FACS analysis were used to determine apoptotic incidence of nucleus pulposus cells. MTS assay was used to determine cell viability, and cellular binding assay was used to determine cell-ECM (extracellular matrix) ability. Real-time quantitative RT-PCR was to determine mRNA level of target genes. And Western blot was used to determine the protein level. Results: Both E2 and RES decreased apoptotic incidence when used singly; interestingly, they decreased apoptosis more efficiently when used combinedly. Meanwhile, E2 and RES combined together against the decrease of cell viability and binding ability resulting from IL-1β cytotoxicity. As well, activated caspase-3 was suppressed by the combined effect. Furthermore, IL-1β downregulated expression level of type II collagen and aggrecan (standing for anabolism), while upregulated MMP-3 and MMP-13 (standing for catabolism). However, the combined use of E2 with RES effectively abolished the above negative effects caused by IL-1β, better than either single use. Finally, it turned out to be that E2 and RES combined together against apoptosis via the activation of PI3K/Akt/caspase-3 pathway. Conclusion: This study presented that IL-1β induced aberrant apoptosis, which was efficiently resisted by the combined use of E2 with RES via PI3K/Akt/caspase-3 pathway.

Abstract Background Single-copy integration vectors based upon the site-specific recombination systems of bacteriophage are invaluable tools in the study of bacterial pathogenesis. The utility of such vectors is often limited, however, by the fact that integration often results in the inactivation of bacterial genes or has undesirable effects on gene transcription. The aim of this study is to develop an integration vector that does not have a detectable effect on gene transcription upon integration. Findings We have developed a single-copy integration system that enables the cloning vector to integrate at a specific engineered site, within an untranscribed intergenic region, in the chromosome of Staphylococcus aureus. This system is based on the lysogenic phage L54a site-specific recombination system in which the L54a phage (attP) and chromosome (attB) attachment sites, which share an 18-bp identical core sequence, were modified with identical mutations. The integration vector, pLL102, was constructed to contain the modified L54a attP site (attP2) that was altered at 5 nucleotide positions within the core sequence. In the recipient strain, the similarly modified attB site (attB2) was inserted in an intergenic region devoid of detectable transcription read-through. Integration of the vector, which is unable to replicate in S. aureus extrachromosomally, was achieved by providing the L54a integrase gene in a plasmid in the recipient. We showed that pLL102 integrated specifically at the engineered site rather than at the native L54a attB site and that integration did not have a significant effect on transcription of genes immediately upstream or downstream of the integration site. Conclusions In this work, we describe an E. coli-S. aureus shuttle vector that can be used to introduce any cloned gene into the S. aureus chromosome at a select site without affecting gene expression. The vector should be useful for genetic manipulation of S. aureus and for marking strains for in vivo studies.

Abstract Background Microarray pre-processing usually consists of normalization and summarization. Normalization aims to remove non-biological variations across different arrays. The normalization algorithms generally require the specification of reference and target arrays. The issue of reference selection has not been fully addressed. Summarization aims to estimate the transcript abundance from normalized intensities. In this paper, we consider normalization and summarization jointly by a new strategy of reference selection. Results We propose a Probe-Treatment-Reference (PTR) model to streamline normalization and summarization by allowing multiple references. We estimate parameters in the model by the Least Absolute Deviations (LAD) approach and implement the computation by median polishing. We show that the LAD estimator is robust in the sense that it has bounded influence in the three-factor PTR model. This model fitting, implicitly, defines an "optimal reference" for each probe-set. We evaluate the effectiveness of the PTR method by two Affymetrix spike-in data sets. Our method reduces the variations of non-differentially expressed genes and thereby increases the detection power of differentially expressed genes. Conclusion Our results indicate that the reference effect is important and should be considered in microarray pre-processing. The proposed PTR method is a general framework to deal with the issue of reference selection and can readily be applied to existing normalization algorithms such as the invariant-set, sub-array and quantile method.

Abstract Background The identification of transcription factors (TFs) associated with a biological process is fundamental to understanding its regulatory mechanisms. From microarray data, however, the activity changes of TFs often cannot be directly observed due to their relatively low expression levels, post-transcriptional modifications, and other complications. Several approaches have been proposed to infer TF activity changes from microarray data. In some models, a linear relationship between gene expression and TF-gene binding strength is assumed. In some other models, the target genes of a TF are first determined by a significance cutoff to binding affinity scores, and then expression differentiation is checked between the target and other genes. Results We propose a novel method, referred to as BASE (binding association with sorted expression), to infer TF activity changes from microarray expression profiles with the help of binding affinity data. It searches the maximum association between bind affinity profile of a TF and expression change profile along the direction of sorted differentiation. The method does not make hard target gene selection, rather, the significances of TF activity changes are evaluated by permutation tests of binding association at the end. To show the effectiveness of this method, we apply it to three typical examples using different kinds of binding affinity data, namely, ChIP-chip data, motif discovery data, and positional weighted matrix scanning data, respectively. The implications obtained from all three examples are consistent with established biological results. Moreover, the inferences suggest new and biological meaningful hypotheses for further investigation. Conclusion The proposed method makes transcription inference from profiles of expression and binding affinity. The same machinery can be used to deal with various kinds of binding affinity data. The method does not require a linear assumption, and has the desirable property of scale-invariance with respect to TF-specific binding affinity. This method is easy to implement and can be routinely applied for transcriptional inferences in microarray studies.

Abstract Background Single Nucleotide Polymorphisms (SNPs) are the most common type of polymorphisms found in the human genome. Effective genetic association studies require the identification of sets of tag SNPs that capture as much haplotype information as possible. Tag SNP selection is analogous to the problem of data compression in information theory. According to Shannon's framework, the optimal tag set maximizes the entropy of the tag SNPs subject to constraints on the number of SNPs. This approach requires an appropriate probabilistic model. Compared to simple measures of Linkage Disequilibrium (LD), a good model of haplotype sequences can more accurately account for LD structure. It also provides a machinery for the prediction of tagged SNPs and thereby to assess the performances of tag sets through their ability to predict larger SNP sets. Results Here, we compute the description code-lengths of SNP data for an array of models and we develop tag SNP selection methods based on these models and the strategy of entropy maximization. Using data sets from the HapMap and ENCODE projects, we show that the hidden Markov model introduced by Li and Stephens outperforms the other models in several aspects: description code-length of SNP data, information content of tag sets, and prediction of tagged SNPs. This is the first use of this model in the context of tag SNP selection. Conclusion Our study provides strong evidence that the tag sets selected by our best method, based on Li and Stephens model, outperform those chosen by several existing methods. The results also suggest that information content evaluated with a good model is more sensitive for assessing the quality of a tagging set than the correct prediction rate of tagged SNPs. Besides, we show that haplotype phase uncertainty has an almost negligible impact on the ability of good tag sets to predict tagged SNPs. This justifies the selection of tag SNPs on the basis of haplotype informativeness, although genotyping studies do not directly assess haplotypes. A software that implements our approach is available.