Target NF-κB p65 for preventing posttraumatic joint contracture in rats.

RelA/p65 is as a crucial component of the nuclear factor κB (NF-κB) signaling pathway that has a significant impact on various fibrotic diseases. However, its role in the fibrosis of tissues surrounding the joint after traumatic injury remains unclear. In this study, rats were divided into three groups: non-operated control (NC) group, p65-siRNA treated (siRNA-p65) group, and negative siRNA treated (siRNA-neg) group. Then, 10 µL (10 nmol) of p65-siRNA was injected into the joint of the siRNA-p65 group. Meanwhile, 10 µL of negative siRNA was administered to the knee joint of the operated siRNA-neg group for comparison. The rats in the NC group did not receive surgery or drug intervention. After 4 weeks of right knee fixation in each group, X-ray measurements revealed significantly reduced degree of knee flexion contracture following p65-siRNA treatment (siRNA-neg: 77.73° ± 2.799°; siRNA-p65: 105.7° ± 2.629°, p < 0.0001). Histopathological examination revealed that the number of dense fibrous connective tissues decreased following p65-siRNA inhibition. Western blot analysis revealed significantly different expression levels of fibrosis-related proteins between the siRNA-p65 and siRNA-neg groups. Immunohistochemical analysis revealed a reduction in the average number of myofibroblasts in the siRNA-p65 group compared with that in the siRNA-neg group. Thus, intra-articular p65-siRNA injection could attenuate fibroblast activation and fibrosis-related protein production, suppress periarticular tissue fibrosis, and prevent joint contracture by downregulating the NF-κB p65 pathway. Statement of clinical significance: Intra-articular injection of p65-siRNA could reduce myofibroblast proliferation and fibrosis-related protein expression by downregulating the NF-κB p65 pathway, inhibit periarticular tissue fibrosis, and prevent joint adhesion, which represents a potential therapy in the prevention of joint fibrosis following traumatic injury.

Novel LDLR variants affecting low density lipoprotein metabolism identified in familial hypercholesterolemia.

BACKGROUND: Familial hypercholesterolemia (FH) is an autosomal dominant disease of lipid metabolism mainly caused by mutations in the low-density lipoprotein receptor (LDLR) gene. Genetic detection of patients with FH help with precise diagnosis and treatment, thus reducing the risk of coronary heart disease (CHD) and other related diseases. The study aimed to identify the causative gene mutations in a Chinese FH family and reveal the pathogenicity and the mechanism of these mutations. METHODS AND RESULTS: Whole exome sequencing was performed in a patient with severe lipid metabolism dysfunction seeking fertility guidance from a Chinese FH family. Two LDLR variants c.1875 C > G (p.N625K; novel variant) and c.1448G > A (p.W483*) were identified in the family. Wildtype and mutant LDLR constructs were established by the site-direct mutagenesis technique. Functional studies were carried out by cell transfection to evaluate the impact of detected variants on LDLR activity. The two variants were proven to affect LDL uptake and binding, resulting in cholesterol clearance reduction to different degrees. According to The American College of Medical Genetics and Genomics (ACMG) Standards and Guidelines, the W483* variant was classified as "Pathogenic", while the N625K variant as "VUS". CONCLUSIONS: Our results provide novel experimental evidence of functional alteration by LDLR variants identified in our study and expand the mutational spectrum of LDLR mutation induced FH.

Vicinity Vision Transformer.

Vision transformers have shown great success on numerous computer vision tasks. However, their central component, softmax attention, prohibits vision transformers from scaling up to high-resolution images, due to both the computational complexity and memory footprint being quadratic. Linear attention was introduced in natural language processing (NLP) which reorders the self-attention mechanism to mitigate a similar issue, but directly applying existing linear attention to vision may not lead to satisfactory results. We investigate this problem and point out that existing linear attention methods ignore an inductive bias in vision tasks, i.e., 2D locality. In this article, we propose Vicinity Attention, which is a type of linear attention that integrates 2D locality. Specifically, for each image patch, we adjust its attention weight based on its 2D Manhattan distance from its neighbouring patches. In this case, we achieve 2D locality in a linear complexity where the neighbouring image patches receive stronger attention than far away patches. In addition, we propose a novel Vicinity Attention Block that is comprised of Feature Reduction Attention (FRA) and Feature Preserving Connection (FPC) in order to address the computational bottleneck of linear attention approaches, including our Vicinity Attention, whose complexity grows quadratically with respect to the feature dimension. The Vicinity Attention Block computes attention in a compressed feature space with an extra skip connection to retrieve the original feature distribution. We experimentally validate that the block further reduces computation without degenerating the accuracy. Finally, to validate the proposed methods, we build a linear vision transformer backbone named Vicinity Vision Transformer (VVT). Targeting general vision tasks, we build VVT in a pyramid structure with progressively reduced sequence length. We perform extensive experiments on CIFAR-100, ImageNet-1 k, and ADE20 K datasets to validate the effectiveness of our method. Our method has a slower growth rate in terms of computational overhead than previous transformer-based and convolution-based networks when the input resolution increases. In particular, our approach achieves state-of-the-art image classification accuracy with 50% fewer parameters than previous approaches.

Study on Integrated Pharmacokinetics of the Component-Based Chinese Medicine of Ginkgo biloba Leaves Based on Nanocrystalline Solid Dispersion Technology.

Background: To improve the dissolution and bioavailability of the component-based Chinese medicine of Ginkgo biloba leaves (GBCCM), a novel nanocrystalline solid dispersion of GBCCM (GBCCM NC-SD) was first prepared. Methods: GBCCM mainly containing high pure flavonoid aglycones (FAs) and terpenoid lactones (TLs) was used as the model drug. PVP K30 and SDS were used as solubilizers, combined stabilizers and carriers, and GBCCM NC-SD was prepared by high-pressure homogenization combined with freeze-dryer. Morphology and crystal characteristic of GBCCM NC-SD were analyzed. The dissolution and bioavailability evaluation were performed to investigate the feasibility of GBCCM NC-SD by in vitro dissolution and in vivo integrated pharmacokinetic models. Results: After homogenizing for 30 cycles under the pressure of 650 bar and freeze-drying, GBCCM NC-SD with uniform quality would be obtained. The particle size, PDI and zeta potential were found to be 335.9 ± 32.8 nm, 0.29 ± 0.02 and -28.4 ± 0.7 mV respectively. Based on charged aerosol detector (CAD) technology, a new chromatographic method for simultaneous detection of eight components in GBCCM was developed. In vitro drug release study showed that the cumulative dissolution of FAs and TLs in GBCCM NC-SD increased from 12.77% to 52.92% (P < 0.01) and 90.91% to 99.21% (P < 0.05) respectively. In comparison with physical mixture of GBCCM and stabilizer (PM), the integrated pharmacokinetics AUC0-t of FAs and TLs in GBCCM NC-SD were significantly increased (P < 0.05), and the T1/2 of TLs was also significantly prolonged (P < 0.05). Conclusion: This study demonstrated that novel GBCCM NC-SD was prepared using Polyvinylpyrrolidone K30 (PVP K30) and Sodium dodecyl sulfate (SDS) as a synergetic stabilizer and also provided a feasible way to improve the dissolution and oral bioavailability of poorly soluble candidate antihypertensive drugs.

Preparation of pleated flower-like manganese-cobalt-silicate bimetallic electrode materials for supercapacitors.

Transition metal silicates (TMSS) have been studied as potential electrode materials for rechargeable batteries and supercapacitors (SCs), and delicate structural design can further enhance the capacity performance and cycling stability of TMSS electrode materials. Herein, a bimetallic doping modulation strategy was employed, and a novel metal-silicate structure was constructed to obtain SC anode materials with excellent electrochemical properties. Manganese cobalt silicate (AMMnCo) with a pleated flower-like structure was obtained by the reaction of Mn2+ and Co2+ with acid-etched montmorillonite (AM) substrates using a simple hydrothermal method. The benign, competitive bimetallic mechanism accelerates the growth of manganese silicate and cobalt silicate on treated montmorillonite (MMT), which results in more folded ion-transport channels on the lamellae and improves the electrochemical properties of the transition-metal silicates. AMMnCo exhibits a higher specific capacitance (979F·g-1/0.5 A·g-1) and better cycling performance (84 %/10,000 cycles) than its monometallic counterparts. Additionally, AMMnCo//AC (where AC is activated carbon), a hybrid supercapacitor (HSC) device, has a high mass specific capacitance and an energy density reaching 13.7 Wh·kg-1 at a power density of 246.9 W·kg-1. Therefore, AMMnCo is a prospective electrode material for high-performance SC applications.

Anatomical study for the treatment of proximal humeral fracture through the medial approach.

BACKGROUND: The treatment of complex 3- and 4-part proximal humeral fractures has been controversial due to numerous postoperative complications. With the further study of medial support and blood supply of humeral head, new techniques and conception are developing. The study aims to illustrate the medial approach of the proximal humeral fracture through cadaver autopsy. METHOD: Upper limbs from 19 cadavers have been dissected to expose the shoulder joint. We selected the coracoid process as the bony reference. Vernier caliper will be used to measure the following data, including distance from coracoid process to circumflex brachial artery, distance between anterior humeral circumflex artery (ACHA) and posterior circumflex brachial artery (PCHA) and their diameters. Assessment included the characteristics of the vascular supply around the humeral head, identification of the structures at risk, quality of exposure of the bony structures, and feasibility of fixation. RESULTS: The medial approach is appropriate in 86.84% anatomical patterns. Between the lower part of the shoulder capsule and the insertion of conjoined tendon, the bony surface exposed was limited by the interval between ACHA and PCHA. An interval of 2 to 3 cm (24.29 ± 3.42 mm) was available for medial plate. ACHA (49.35 ± 8.13 mm, 35.14-68.53 mm) and PCHA (49.62 ± 7.82 mm, 37.67-66.76 mm) were about 5 cm away from the coracoid process. Risk structures including ACHA and PCHA originate in common, PCHA originated from the deep brachial artery (DBA), the presence of perforator vessels, musculocutaneous nerve intersects with ACHA, the diameter of PCHA: ACHA < 1.5. In 13.15% anatomical patterns, this risk structure should be taken seriously. CONCLUSION: The medial approach opens a new perspective in the optimal management of complex fractures of proximal humerus. Anatomical research proves that the medial approach is feasible. The interval between ACHA and PCHA is suitable for placement. Anatomical pattern and indication have been discussed, and we hypothesized that ACHA has been destroyed in complex PHFs. With further studies on the anatomy and mechanism of injury, the development of more clinical cases will be an important work of our institution in the future.

Minimally invasive open reduction of greater tuberosity fractures by a modified suture bridge procedure.

BACKGROUND: Most greater tuberosity fractures can be treated without surgery but some have a poor prognosis. The surgical procedures for avulsion fractures of the humeral greater tuberosity include screw fixation, suture anchor fixation, and plate fixation, all of which have treatment-associated complications. To decrease surgical complications, we used a modified suture bridge procedure under direct vision and a minimally invasive small incision to fix fractures of the greater tuberosity of the humerus. AIM: To investigate the clinical efficacy and outcomes of minimally invasive modified suture bridge open reduction of greater tuberosity evulsion fractures. METHODS: Sixteen patients diagnosed between January 2016 and January 2019 with an avulsion-type greater tuberosity fracture of the proximal humerus and treated by minimally invasive open reduction and modified suture bridges with anchors were studied retrospectively. All were followed up by clinical examination and radiographs at 3 and 6 wk, 3, 6 and 12 mo after surgery, and thereafter every 6 mo. Outcomes were assessed preoperatively and postoperatively by a visual analog scale (VAS), the University of California Los Angeles (UCLA) shoulder score, the American Shoulder and Elbow Surgeon score (ASES), and range of motion (ROM) for shoulders. RESULTS: Seven men and nine women, with an average age of 44.94 years, were evaluated. The time between injury and surgery was 1-2 d, with an average of 1.75 d. The mean operation time was 103.1 ± 7.23 min. All patients achieved bone union within 3 mo after surgery. VAS scores were significantly decreased (P = 0.002), and the mean degrees of forward elevation (P = 0.047), mean degrees of abduction (P = 0.035), ASES score (P = 0.092) were increased at 3 wk. The UCLA score was increased at 6 wk (P = 0.029) after surgery. The average degrees of external rotation and internal rotation both improved at 3 mo after surgery (P = 0.012 and P = 0.007, respectively). No procedure-related deaths or incision-related superficial or deep tissue infections occurred. CONCLUSION: Modified suture bridge was effective for the treatment of greater tuberosity evulsion fractures, was easier to perform, and had fewer implants than other procedures.

Biomechanical properties of a novel fixation system for intra-articular distal humerus fractures: a finite element analysis.

BACKGROUND: The traditional strategy for fixing intra-articular distal humerus fractures is double plating placed in an orthogonal configuration, based on posterior approach. With a combined medial and lateral approach, a novel configuration of plating (combined anteromedial and anterolateral plating) has been used. In this study, we investigated the biomechanical properties of the novel plating by comparing it with some traditional strategies. METHODS: Based on the 3D morphology of a healthy subject's humerus, models of three types of intra-articular distal humeral fractures were established using a variety of different internal fixation methods: (a) treatment of a simple intra-articular fracture of the distal humerus with the novel double plate and a traditional orthogonal plate; (b) treatment of a comminuted fracture of the lower distal humerus with the novel double plate, a traditional orthogonal plate and a traditional orthogonal plate combined with distally extended tension screws; (c) treatment of a coronal shear fracture of the distal humerus with the novel double plate, a traditional orthogonal plate and the intra-articular placement of three screws. The material properties of all plates and screws were isotropic and linearly elastic. The Poisson ratio of the implant and bone was 0.3, and the elastic modulus of the implant was 114,000 MPa. The axial loading is 200 N, the bending loading is 30 N and varus rotation is 7.5 Nm in the longitudinal direction. RESULTS: A simple model of intra-articular fracture of the distal humerus (AO C1 type) was established. Under all experimental conditions, the novel double plate showed greater stiffness than the orthogonal double plate. The axial straightening, bending compression and varus torsion increased by 18.00%, 16.00% and 44.00%, respectively. In the model of comminuted fracture of the lower distal humerus, the novel double plate showed the best stiffness under three experimental conditions (163.93 N/mm, 37.97 N/mm, 2697.84 N mm/°), and the stiffness of the traditional orthogonal plate combined with the distally extended tension screws was similar to that of the traditional orthogonal plate (121.21 N/mm, 32.61 N/mm, 1968.50 N mm/°). In the model of coronal shear fracture of the distal humerus, the novel double plate showed the best stiffness under all test conditions (194.17 N/mm, 38.46 N/mm, 2929.69 N mm/°), followed by the traditional plate (153.85 N/mm, 33.33 N/mm, 2650.18 N mm/°), while the stiffness of the three screws was the smallest (115.61 N/mm, 28.30 N/mm, 2180.23 N mm/°). CONCLUSIONS: In terms of biomechanics, compared with other internal fixation methods, the novel combined anteromedial and anterolateral anatomical locking double-plate showed less stress, less displacement and greater stiffness. The novel double-plate method can be used to treat not only simple intra-articular fractures of the humerus but also complex comminuted fractures of the lower distal humerus and coronal shear fractures of the distal humerus, with a better effect than current traditional internal fixation methods.

SPMLMI: predicting lncRNA-miRNA interactions in humans using a structural perturbation method.

Long non-coding RNA (lncRNA)-microRNA (miRNA) interactions are quickly emerging as important mechanisms underlying the functions of non-coding RNAs. Accordingly, predicting lncRNA-miRNA interactions provides an important basis for understanding the mechanisms of action of ncRNAs. However, the accuracy of the established prediction methods is still limited. In this study, we used structural consistency to measure the predictability of interactive links based on a bilayer network by integrating information for known lncRNA-miRNA interactions, an lncRNA similarity network, and an miRNA similarity network. In particular, by using the structural perturbation method, we proposed a framework called SPMLMI to predict potential lncRNA-miRNA interactions based on the bilayer network. We found that the structural consistency of the bilayer network was higher than that of any single network, supporting the utility of bilayer network construction for the prediction of lncRNA-miRNA interactions. Applying SPMLMI to three real datasets, we obtained areas under the curves of 0.9512 ± 0.0034, 0.8767 ± 0.0033, and 0.8653 ± 0.0021 based on 5-fold cross-validation, suggesting good model performance. In addition, the generalizability of SPMLMI was better than that of the previously established methods. Case studies of two lncRNAs (i.e., SNHG14 and MALAT1) further demonstrated the feasibility and effectiveness of the method. Therefore, SPMLMI is a feasible approach to identify novel lncRNA-miRNA interactions underlying complex biological processes.

Bioactivity-Guided Isolation of Phytochemicals from Vaccinium dunalianum Wight and Their Antioxidant and Enzyme Inhibitory Activities.

Vaccinium dunalianum Wight, usually processed as a traditional folk tea beverage, is widely distributed in the southwest of China. The present study aimed to investigate the antioxidant, α-glucosidase and pancreatic lipase inhibitory activities of V.dunalianum extract and isolate the bioactive components. In this study, the crude extract (CE) from the buds of V. dunalianum was prepared by the ultrasound-assisted extraction method in 70% methanol and then purified with macroporous resin D101 to obtain the purified extract (PM). Five fractions (Fr. A-E) were further obtained by MPLC column (RP-C18). Bioactivity assays revealed that Fr. B with 40% methanol and Fr. D with 80% methanol had better antioxidant with 0.48 ± 0.03 and 0.62 ± 0.01 nM Trolox equivalent (TE)/mg extract for DPPH, 0.87 ± 0.02 and 1.58 ± 0.02 nM TE/mg extract for FRAP, 14.42 ± 0.41 and 19.25 ± 0.23 nM TE/mg extract for ABTS, and enzyme inhibitory effects with IC50 values of 95.21 ± 2.21 and 74.55 ± 3.85 for α-glucosidase, and 142.53 ± 11.45 and 128.76 ± 13.85 µg/mL for pancreatic lipase. Multivariate analysis indicated that the TPC and TFC were positively related to the antioxidant activities. Further phytochemical purification led to the isolation of ten compounds (1-10). 6-O-Caffeoylarbutin (7) showed significant inhibitory effects on α-glucosidase and pancreatic lipase enzymes with values of 38.38 ± 1.84 and 97.56 ± 7.53 µg/mL, and had the highest antioxidant capacity compared to the other compounds.

EpiMOGA: An Epistasis Detection Method Based on a Multi-Objective Genetic Algorithm.

In genome-wide association studies, detecting high-order epistasis is important for analyzing the occurrence of complex human diseases and explaining missing heritability. However, there are various challenges in the actual high-order epistasis detection process due to the large amount of data, "small sample size problem", diversity of disease models, etc. This paper proposes a multi-objective genetic algorithm (EpiMOGA) for single nucleotide polymorphism (SNP) epistasis detection. The K2 score based on the Bayesian network criterion and the Gini index of the diversity of the binary classification problem were used to guide the search process of the genetic algorithm. Experiments were performed on 26 simulated datasets of different models and a real Alzheimer's disease dataset. The results indicated that EpiMOGA was obviously superior to other related and competitive methods in both detection efficiency and accuracy, especially for small-sample-size datasets, and the performance of EpiMOGA remained stable across datasets of different disease models. At the same time, a number of SNP loci and 2-order epistasis associated with Alzheimer's disease were identified by the EpiMOGA method, indicating that this method is capable of identifying high-order epistasis from genome-wide data and can be applied in the study of complex diseases.

Deep6mA: A deep learning framework for exploring similar patterns in DNA N6-methyladenine sites across different species.

N6-methyladenine (6mA) is an important DNA modification form associated with a wide range of biological processes. Identifying accurately 6mA sites on a genomic scale is crucial for under-standing of 6mA's biological functions. However, the existing experimental techniques for detecting 6mA sites are cost-ineffective, which implies the great need of developing new computational methods for this problem. In this paper, we developed, without requiring any prior knowledge of 6mA and manually crafted sequence features, a deep learning framework named Deep6mA to identify DNA 6mA sites, and its performance is superior to other DNA 6mA prediction tools. Specifically, the 5-fold cross-validation on a benchmark dataset of rice gives the sensitivity and specificity of Deep6mA as 92.96% and 95.06%, respectively, and the overall prediction accuracy is 94%. Importantly, we find that the sequences with 6mA sites share similar patterns across different species. The model trained with rice data predicts well the 6mA sites of other three species: Arabidopsis thaliana, Fragaria vesca and Rosa chinensis with a prediction accuracy over 90%. In addition, we find that (1) 6mA tends to occur at GAGG motifs, which means the sequence near the 6mA site may be conservative; (2) 6mA is enriched in the TATA box of the promoter, which may be the main source of its regulating downstream gene expression.

Mining influential genes based on deep learning.

BACKGROUND: Currently, large-scale gene expression profiling has been successfully applied to the discovery of functional connections among diseases, genetic perturbation, and drug action. To address the cost of an ever-expanding gene expression profile, a new, low-cost, high-throughput reduced representation expression profiling method called L1000 was proposed, with which one million profiles were produced. Although a set of ~ 1000 carefully chosen landmark genes that can capture ~ 80% of information from the whole genome has been identified for use in L1000, the robustness of using these landmark genes to infer target genes is not satisfactory. Therefore, more efficient computational methods are still needed to deep mine the influential genes in the genome. RESULTS: Here, we propose a computational framework based on deep learning to mine a subset of genes that can cover more genomic information. Specifically, an AutoEncoder framework is first constructed to learn the non-linear relationship between genes, and then DeepLIFT is applied to calculate gene importance scores. Using this data-driven approach, we have re-obtained a landmark gene set. The result shows that our landmark genes can predict target genes more accurately and robustly than that of L1000 based on two metrics [mean absolute error (MAE) and Pearson correlation coefficient (PCC)]. This reveals that the landmark genes detected by our method contain more genomic information. CONCLUSIONS: We believe that our proposed framework is very suitable for the analysis of biological big data to reveal the mysteries of life. Furthermore, the landmark genes inferred from this study can be used for the explosive amplification of gene expression profiles to facilitate research into functional connections.

Revealing Prognosis-Related Pathways at the Individual Level by a Comprehensive Analysis of Different Cancer Transcription Data.

Identifying perturbed pathways at an individual level is important to discover the causes of cancer and develop individualized custom therapeutic strategies. Though prognostic gene lists have had success in prognosis prediction, using single genes that are related to the relevant system or specific network cannot fully reveal the process of tumorigenesis. We hypothesize that in individual samples, the disruption of transcription homeostasis can influence the occurrence, development, and metastasis of tumors and has implications for patient survival outcomes. Here, we introduced the individual-level pathway score, which can measure the correlation perturbation of the pathways in a single sample well. We applied this method to the expression data of 16 different cancer types from The Cancer Genome Atlas (TCGA) database. Our results indicate that different cancer types as well as their tumor-adjacent tissues can be clearly distinguished by the individual-level pathway score. Additionally, we found that there was strong heterogeneity among different cancer types and the percentage of perturbed pathways as well as the perturbation proportions of tumor samples in each pathway were significantly different. Finally, the prognosis-related pathways of different cancer types were obtained by survival analysis. We demonstrated that the individual-level pathway score (iPS) is capable of classifying cancer types and identifying some key prognosis-related pathways.

Polydopamine coating with static magnetic field promotes the osteogenic differentiation of human bone-derived mesenchymal stem cells on three-dimensional printed porous titanium scaffolds by upregulation of the BMP-Smads signaling pathway.

Bone regeneration has always been a hot topic for orthopedic surgeons. The role of polydopamine coating in promoting bone regeneration has attracted much attention. Static magnetic field (SMF) is considered an effective and noninvasive treatment for enhancing bone regeneration. However, the effect of polydopamine combined with SMF on bone regeneration on scaffolds is not clear. The aim of this study was to investigate the effects and potential mechanism of polydopamine coating combined with SMF on bone regeneration in three-dimensional printed scaffolds. The polydopamine coating (pTi group) was applied onto porous Ti6Al4V scaffolds (Ti group). Surface characterization was performed by scanning electron microscopy. The 100 mT SMF environment (pTi-SMF group) was established to enhance osteogenic differentiation of human bone-derived mesenchymal stem cells (hBMSCs) on polydopamine coating scaffolds. The cell viability and proliferation were significantly enhanced in the SMF environment (pTi-SMF vs. Ti: P=0.005). Improved morphology (pTi-SMF vs. pTi: P=0.024, pTi-SMF vs. Ti: P=0.001) and adhesion (Ti: x̅±s=1.585±0.324; pTi: x̅±s=2.164±0.314; pTi-SMF: x̅±s=4.634±0.247, P<0.001) of hBMSCs were observed in the pTi-SMF group. The high expression of osteogenesis-related RNA and protein (ALP: Ti, x̅±s=1.249±0.218; pTi, x̅±s=2.503±0.209; pTi-SMF, x̅±s=2.810±0.246. OCN: Ti, x̅±s=1.483±0.304; pTi, x̅±s=3.636±0.322; pTi-SMF, x̅±s=4.641±0.278. Runx2: Ti, x̅±s=1.372±0.227; pTi, x̅±s=3.054±0.229; pTi-SMF, x̅±s=3.914±0.253) was found in the pTi-SMF group (pTi-SMF vs. Ti: P<0.001). Proteomics was applied to explore the osteogenic mechanism of polydopamine coating combined with SMF. A total of 147 different proteins were identified between the pTi-SMF and Ti group. The osteogenic effect might be associated with the BMP-Smads signaling pathway (pTi-SMF vs. Ti: BMPR1A, P=0.001; BMPR2, P<0.001; Smad4, P=0.001; Smad1/5/8, P=0.008). In conclusion, the osteogenic differentiation of hBMSCs on polydopamine coating scaffolds could be enhanced by SMF stimulation by upregulation of the BMP-Smads signaling pathway.

RETRACTED: Quercetin ameliorates lipopolysaccharide-caused inflammatory damage via down-regulation of miR-221 in WI-38 cells

This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This article has been retracted at the request of the Editor-in-Chief. Given the comments of Dr Elisabeth Bik regarding this article "… the Western blot bands in all 400+ papers are all very regularly spaced and have a smooth appearance in the shape of a dumbbell or tadpole, without any of the usual smudges or stains. All bands are placed on similar looking backgrounds, suggesting they were copy/pasted from other sources, or computer generated", the journal requested the authors to provide the raw data. However, the authors were not able to fulfil this request and therefore the Editor-in-Chief decided to retract the article.

Physiological response of tomatoes at drought, heat and their combination followed by recovery.

In nature, crops encounter a combination of abiotic stresses that severely limit yield. Our aim was to dynamically expose the changes of tomatoes' physiological parameters to drought, heat and their combination and thereby clarify the relationship between the responses to single and combined stress. We studied the effect of single and combined drought and heat stresses on the shoot and root of two tomato cultivars (Sufen No.14 as CV1; Jinlingmeiyu as CV2). After being exposed to combined stress for 6 days, the dry weight of shoot and root significantly decreased. The Fq '/Fm ' (quantum yield of photosystem II) was significantly lower in CV1 upon drought and combined stress and in CV2 subjected to combined stress (between days 4 and 6) compared to control. The relative water content during combined stress was significantly lower than control from day 4 to recovery day 2. On days 3 and 6, the water loss rate significantly increased under heat stress and decreased at drought and combined stress, respectively. The combined stress caused severe damages on photosystem II and chloroplast ultrastructure. The root activity after stress recovered even though drought significantly increased the activity from day 2 to day 6. Combined stress result in complex responses during tomato growth. The CV1 was more heat tolerant than CV2, but there was no varietal difference at drought and combined stress. This study contributes to the understanding of the underlying physiological response mechanism of plant to combined stress and crop improvement by providing valuable information for abiotic stress-tolerant tomato breeding.