Understanding foot conditions, morphologies and functions in children: a current review.

This study provided a comprehensive updated review of the biological aspects of children foot morphology across different ages, sex, and weight, aiming to reveal the patterns of normal and pathological changes in children feet during growth and development. This review article comprised 25 papers in total that satisfied the screening standards. The aim was to investigate how weight changes, age and sex affect foot type, and gain a deeper understanding of the prevalent foot deformities that occur during children growth. Three different foot morphological conditions were discussed, specifically including the effect of sex and age differences, the effect of weight changes, and abnormal foot morphologies commonly documented during growth. This review found that sex, age, and weight changes would affect foot size, bony structure, foot posture, and plantar pressures during child growth. As a result of this biological nature, the children's feet generally exhibit neutral and internally rotated foot postures, which frequently lead to abnormal foot morphologies (e.g., flat foot, pronated foot, etc.). In the future, attention shall be paid to the causal factors leading to specific foot morphologies during the growth and development of children. However, sufficient evidence could not be provided due to a relatively short period of investigation and non-uniformed research methodology in the current literature. A more comprehensive and in-depth exploration is recommended to provide scientific evidence for the discovery of children foot development and personalized growth pattern.

Breast cancer prediction model based on clinical and biochemical characteristics: clinical data from patients with benign and malignant breast tumors from a single center in South China.

OBJECTIVE: Breast cancer is the most prevalent cancer and is second leading cause of death from malignancy among women worldwide. In addition to tumor factors, the host characteristics of tumors have been paid more and more attention by the medical community. This study aimed to develop a breast cancer prediction model for the Chinese population using clinical and biochemical characteristics. METHODS: This is a retrospective study. From 2012 to 2021, we selected 19,751 patients with breast diseases from the Guangdong Hospital of Traditional Chinese Medicine, which included 5660 patients with breast cancer and 14,091 patients with benign breast diseases-75% of patients were randomly assigned to the training group and 25% to the test group using a total of 34 clinical and biochemical characteristics. Significant clinical signs were investigated, and logistic regression with recursive feature elimination (RFE) model was used to develop a prediction model for distinguishing benign from malignant breast diseases. The prediction model's accuracy, precision, sensitivity, specificity, and area under the ROC curve (AUC) were calculated. RESULTS: Clinical statistics demonstrated that the prediction model comprised 19 clinical characteristics had statistical separability in both the training group and the test group, as well as good sensitivity and prediction. CONCLUSIONS: This model based on biochemical parameters demonstrates a significant predictive effect for breast cancer and may be useful as a reference for invasive tissue biopsy in patients undergoing BI-RADS 3 and 4A breast imaging.

Comparison of pneumonitis risk between immunotherapy alone and in combination with chemotherapy: an observational, retrospective pharmacovigilance study.

Importance: Checkpoint inhibitor pneumonitis (CIP) is a rare but serious adverse event that may impact treatment decisions. However, there is limited information comparing CIP risks between immune checkpoint inhibitor (ICI) monotherapy and combination with chemotherapy due to a lack of direct cross-comparison in clinical trials. Objective: To determine whether ICI combination with chemotherapy is superior to ICI in other drug regimens (including monotherapy) in terms of CIP risk. Study Design and Methods: This observational, cross-sectional and worldwide pharmacovigilance cohort study included patients who developed CIP from the World Health Organization database (WHO) VigiBase and the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. Individual case safety reports (ICSR) were extracted from 2015 to 2020 in FAERS and from 1967 to 2020 in VigiBase. Timing and reporting odds ratio (ROR) of CIP in different treatment strategies were used to detect time-to-onset and the risk of pneumonitis after different immunotherapy regimens. Results: A total of 93,623 and 114,704 ICI-associated ICSRs were included in this study from VigiBase and FAERS databases respectively. 3450 (3.69%) and 3278 (2.86%) CIPs occurred after therapy initiation with a median of 62 days (VigiBase) and 40 days (FAERS). Among all the CIPs, 274 (7.9%) and 537 (16.4%) CIPs were associated with combination therapies. ICIs plus chemotherapy combination was associated with pneumonitis in both VigiBase [ROR 1.35, 95% CI 1.18-1.52] and FAERS [ROR 1.39, 95% CI 1.27-1.53]. The combination of anti-PD-1 antibodies and anti-CTLA-4 antibodies with chemotherapy demonstrated an association with pneumonitis in both VigiBase [PD-1+chemotherapy: 1.76, 95% CI 1.52-2.05; CTLA-4+chemotherapy: 2.36, 95% CI 1.67-3.35] and FAERS [PD-1+chemotherapy: 1.70, 95% CI 1.52-1.91; CTLA-4+chemotherapy: 1.70, 95% CI 1.31-2.20]. Anti-PD-L1 antibodies plus chemotherapy combinations did not show the association. Conclusion: Compared to ICI in other drug regimens (including monotherapy), the combination of ICI plus chemotherapy is significantly associated with higher pneumonitis toxicity. Anti-PD-1/CTLA4 medications in combination with chemotherapy should be obviated in patients with potential risk factors for CIP. Trial Registration: clinicaltrials.gov, ChiCTR2200059067.

Effectiveness of immunosuppressant use for the treatment of immune checkpoint inhibitor-induced liver injury: A systematic review and meta-analysis.

Background: Immune-mediated liver injury caused by checkpoint inhibitors (ILICI) is a challenging clinical management issue. Although immunosuppressants are widely used to manage ILICI, no large-scale studies have proved definitive evidence for the most effective form of patient management. Aim: Analysis of the effectiveness of immunosuppression for immune-related liver injury. Methods: We performed a systematic review and meta-analysis of the clinical outcomes of immunosuppressive treatment of ILICI patients. A literature search of PubMed, Ovid, and Cochrane Library was completed for dates from 2000 to January 1, 2022. The primary outcome was the response rate to immunosuppressive therapy for ILICI, with subgroup analysis based on the type of cancer, immune checkpoint inhibitor regimen, and severity of liver injury. The secondary outcome was the median time to recovery from ILICI with immunosuppressive therapy. Results: A total of 30 studies that included 1120 patients were collected. The pooled ILICI response rate was 79% (95% CI 0.73-0.84) for treatment with corticosteroids and 93% (95% CI 0.79-1.0) for treatment with mycophenolate mofetil. For ILICI treated with corticosteroids, the median recovery time was 47.59 (95% CI 39.79-55.40) days compared to 37.74 (95% CI 31.12-44.35) days for all forms of immunosuppression. Conclusion: Findings support the effectiveness of corticosteroids and mycophenolate mofetil for the treatment of ILICI. The identified median time to recovery is a beneficial guide for patients and physicians, allowing for realistic expectations and appropriate treatment management. Future prospective randomized controlled trials are required to define a standardized management approach to immunosuppressive therapy of ILICI. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022313454.

DAPL1 deficiency in mice impairs antioxidant defenses in the RPE and leads to retinal degeneration with AMD-like features.

The decreased antioxidant capacity in the retinal pigment epithelium (RPE) is the hallmark of retinal degenerative diseases including age-related macular degeneration (AMD). Nevertheless, the exact regulatory mechanisms underlying the pathogenesis of retinal degenerations remain largely unknown. Here we show in mice that deficiencies in Dapl1, a susceptibility gene for human AMD, impair the antioxidant capacity of the RPE and lead to age-related retinal degeneration in the 18-month-old mice homozygous for a partial deletion of Dapl1. Dapl1-deficiency is associated with a reduction of the RPE's antioxidant capacity, and experimental re-expression of Dapl1 reverses this reduction and protects the retina from oxidative damage. Mechanistically, DAPL1 directly binds the transcription factor E2F4 and inhibits the expression of MYC, leading to upregulation of the transcription factor MITF and its targets NRF2 and PGC1α, both of which regulate the RPE's antioxidant function. When MITF is experimentally overexpressed in the RPE of DAPL1 deficient mice, antioxidation is restored and retinas are protected from degeneration. These findings suggest that the DAPL1-MITF axis functions as a novel regulator of the antioxidant defense system of the RPE and may play a critical role in the pathogenesis of age-related retinal degenerative diseases.

Stereo Coverage and Overall Stiffness of Biomaterial Arrays Underly Parts of Topography Effects on Cell Adhesion.

Surface topography is a biophysical factor affecting cell behaviors, yet the underlying cues are still not clear. Herein, we hypothesized that stereo coverage and overall stiffness of biomaterial arrays on the scale of single cells underly parts of topography effects on cell adhesion. We fabricated a series of microarrays (micropillar, micropit, and microtube) of poly(l-lactic acid) (PLLA) using mold casting based on pre-designed templates. The characteristic sizes of array units were less than that of a single cell, and thus, each cell could sense the micropatterns with varied roughness. With human umbilical vein endothelial cells (HUVECs) as the model cell type, we examined spreading areas and cell viabilities on different surfaces. "Stereo coverage" was defined to quantify the actual cell spreading fraction on a topographic surface. Particularly in the case of high micropillars, cells were confirmed not able to touch the bottom and had to partially hang among the micropillars. Then, in our opinion, a cell sensed the overall stiffness combining the bulk stiffness of the raw material and the stiffness of the culture medium. Spreading area and single cell viability were correlated to coverage and topographic feature of the prepared microarrays in particular with the significantly protruded geometry feather. Cell traction forces exerted on micropillars were also discussed. These findings provide new insights into the surface modifications toward biomedical implants.

Enhancing docosahexaenoic acid production of Schizochytrium sp. by optimizing fermentation using central composite design.

Docosahexaenoic acid (DHA) can improve human and animal health, particularly including anti-inflammatory, antioxidant, anticancer, neurological, and visual functions. Schizochytrium sp. is a marine heterotrophic protist producing oil with high DHA content, which is widely used in animal and food production. However, different fermentation conditions have intensive impacts on the growth and DHA content of Schizochytrium sp. Thus, this study aimed to enhance the DHA yield and concentration of Schizochytrium sp. I-F-9 by optimizing the fermentation medium. First, a single-factor design was conducted to select a target carbon and nitrogen source from several generic sources (glucose, sucrose, glycerol, maltose, corn syrup, yeast extract, urea, peptone, and ammonium sulfate). The Plackett-Burman design and the central composite design (CCD) were utilized to optimize the fermentation mediums. Schizochytrium sp. in 50-mL fermentation broth was cultured in a 250 mL shake flask at 28 °C and 200 rpm for 120 h before collecting the cell pellet. Subsequently, the cell walls were destroyed with hydrochloric acid to extract the fatty acid using n-hexane. The DHA content was detected by gas chromatography. The single-factor test indicated that glucose and peptone, respectively, significantly improved the DHA content of Schizochytrium sp. compared to the other carbon and nitrogen sources. Glucose, sodium glutamate, and sea crystal were the key factors affecting DHA production in the Plackett-Burman test (P = 0.0247). The CCD result showed that DHA production was elevated by 34.73% compared with the initial yield (from 6.18 ± 0.063 to 8.33 ± 0.052 g/L). Therefore, the results of this study demonstrated an efficient strategy to increase the yield and content of DHA of Schizochytrium sp.

RGD Nanoarrays with Nanospacing Gradient Selectively Induce Orientation and Directed Migration of Endothelial and Smooth Muscle Cells.

Directed migration of cells through cell-surface interactions is a paramount prerequisite in biomaterial-induced tissue regeneration. However, whether and how the nanoscale spatial gradient of adhesion molecules on a material surface can induce directed migration of cells is not sufficiently known. Herein, we employed block copolymer micelle nanolithography to prepare gold nanoarrays with a nanospacing gradient, which were prepared by continuously changing the dipping velocity. Then, a self-assembly monolayer technique was applied to graft arginine-glycine-aspartate (RGD) peptides on the nanodots and poly(ethylene glycol) (PEG) on the glass background. Since RGD can trigger specific cell adhesion via conjugating with integrin (its receptor in the cell membrane) and PEG can resist protein adsorption and nonspecific cell adhesion, a nanopattern with cell-adhesion contrast and a gradient of RGD nanospacing was eventually prepared. In vitro cell behaviors were examined using endothelial cells (ECs) and smooth muscle cells (SMCs) as a demonstration. We found that SMCs exhibited significant orientation and directed migration along the nanospacing gradient, while ECs exhibited only a weak spontaneously anisotropic migration. The gradient response was also dependent upon the RGD nanospacing ranges, namely, the start and end nanospacings under a given distance and gradient. The different responses of these two cell types to the RGD nanospacing gradient provide new insights for designing cell-selective nanomaterials potentially used in cell screening, wound healing, etc.

A Facile Composite Strategy to Prepare a Biodegradable Polymer Based Radiopaque Raw Material for "Visualizable" Biomedical Implants.

Enabling a biodegradable polymer radiopaque under X-ray is much desired for many medical devices. Physical blending of a present biodegradable polymer and a commercialized medical contrast agent is convenient yet lacks comprehensive fundamental research. Herein, we prepared a biodegradable polymer-based radiopaque raw material by blending poly(l-lactic acid) (PLLA or simply PLA) and iohexol (IHX), where PLA constituted the continuous phase and IHX particles served as the dispersed phase. The strong X-ray adsorption of IHX enabled the composite radiopaque; the hydrolysis of the polyester and the water solubility of the contrast agent enabled the composite biodegradable in an aqueous medium. The idea was confirmed by in vitro characterizations of the resultant composite, in vivo subcutaneous implantation in rats up to 6 months, and the clear visualization of a part of a biodegradable occluder in a Bama piglet under X-ray. We also found that the crystallization of PLA was significantly enhanced in the presence of the solid particles, which should be taken into consideration in the design of an appropriate biomaterial composite because crystallization degree influences the biodegradation rate and mechanical property of a material to a large extent. We further tried to introduce a small amount of poly(vinylpyrrolidone) into the blend of PLA and IHX. Compared to the bicomponent composite, the tricomponent one exhibited decreased modulus and increased elongation at break and tensile strength. This paves more ways for researchers to select appropriate raw materials according to the regenerated tissue and the application site.

Two-Layer numerical model of soil moisture dynamics: Model assessment and Bayesian uncertainty estimation.

A two-layer model based on the integrated form of Richards' equation (RE) was recently developed to simulate the soil water movement in the roots layer and the vadose zone with a relatively shallow and dynamic water table. The model simulates thickness-averaged volumetric water content and matric suction as opposed to point values and was numerically verified for three soil textures using HYDRUS as a benchmark. However, the strengths and limitations of the two-layer model and its performance in stratified soils and under actual field conditions have not been tested. This study further examined the two-layer model using two numerical verification experiments and, most importantly, tested its performance at site-level under actual, highly variable hydroclimate conditions. Moreover, model parameters were estimated and uncertainty and sources of errors were quantified using a Bayesian framework. First, the two-layer model was evaluated for 231 soil textures under varying soil layer thicknesses with a uniform soil profile. Second, the two-layer model was assessed for stratified conditions where the top and bottom soil layers have contrasting hydraulic conductivities. The model was evaluated by comparing soil moisture and flux estimates to those from the HYDRUS model. Last, a case study of model application using data from a Soil Climate Analysis Network (SCAN) site was presented. Bayesian Monte Carlo (BMC) method was implemented for model calibration and quantifying sources of uncertainty under real hydroclimate and soil conditions. For a homogeneous soil profile, the two-layer model generally had excellent performance in estimating volumetric water content and fluxes, while the model performance slightly declined with increasing layer thickness and coarser textured soils. The model configurations regarding layer thicknesses and soil textures that generate accurate soil moisture and flux estimations were further suggested. With the two layers of contrasting permeability, model-simulated soil moisture contents and fluxes agreed well with those computed by HYDRUS, indicating that the two-layer model accurately handles the water flow dynamics around the layer interface. In the field application, given the highly variable hydroclimate conditions, the two-layer model combined with the BMC method showed good agreement with the observed average soil moisture of the root zone and the vadose zone below (RMSE <0.021 during calibration and <0.023 during validation periods). The contribution of parametric uncertainty to the total model uncertainty was too small compared to other sources. The numerical tests and the site level application showed that the two-layer model can reliably simulate thickness-averaged soil moisture and estimate fluxes in the vadose zone under various soil and hydroclimate conditions. Results also indicated that the BMC method could be a robust framework for vadose zone hydraulic parameters identification and model uncertainty estimation.

Critical adhesion areas of cells on micro-nanopatterns.

Cell adhesion to extracellular matrices (ECM) is critical to physiological and pathological processes as well as biomedical and biotechnological applications. It has been known that a cell can adhere on an adhesive microisland only over a critical size. But no publication has concerned critical adhesion areas of cells on microislands with nanoarray decoration. Herein, we fabricated a series of micro-nanopatterns with different microisland sizes and arginine-glycine-aspartate (RGD) nanospacings on a nonfouling poly(ethylene glycol) background. Besides reproducing that nanospacing of RGD, a ligand of its receptor integrin (a membrane protein), significantly influences specific cell adhesion on bioactive nanoarrays, we confirmed that the concept of critical adhesion area originally suggested in studies of cells on micropatterns was justified also on the micro-nanopatterns, yet the latter exhibited more characteristic behaviors of cell adhesion. We found increased critical adhesion areas of human mesenchymal stem cells (hMSCs) on nanoarrayed microislands with increased RGD nanospacings. However, the numbers of nanodots with respect to the critical adhesion areas were not a constant. A unified interpretation was then put forward after combining nonspecific background adhesion and specific cell adhesion. We further carried out the asymptotic analysis of a series of micro-nanopatterned surfaces to obtain the effective RGD nanospacing on unpatterned free surfaces with densely grafted RGD, which could be estimated nonzero but has never been revealed previously without the assistance of the micro-nanopatterning techniques and the corresponding analysis. Electronic Supplementary Material: Supplementary materials and methods (details of fabrication of micro-nanopatterns), and supplementary results (selective adhesion or localization of hMSCs on nanoarrayed microislands with non-fouling background, calculation of critical number of integrin-ligand binding N*, etc.) are available in the online version of this article at 10.1007/s12274-021-3711-6.

LncRNA NEAT1 Recruits SFPQ to Regulate MITF Splicing and Control RPE Cell Proliferation.

Purpose: Retinal pigment epithelium (RPE) cell proliferation is precisely regulated to maintain retinal homoeostasis. Microphthalmia-associated transcription factor (MITF), a critical transcription factor in RPE cells, has two alternatively spliced isoforms: (+)MITF and (-)MITF. Previous work has shown that (-)MITF but not (+)MITF inhibits RPE cell proliferation. This study aims to investigate the role of long non-coding RNA (lncRNA) nuclear-enriched abundant transcript 1 (NEAT1) in regulating MITF splicing and hence proliferation of RPE cells. Methods: Mouse RPE, primary cultured mouse RPE cells, and different proliferative human embryonic stem cell (hESC)-RPE cells were used to evaluate the expression of (+)MITF, (-)MITF, and NEAT1 by reverse-transcription PCR (RT-PCR) or quantitative RT-PCR. NEAT1 was knocked down using specific small interfering RNAs (siRNAs). Splicing factor proline- and glutamine-rich (SFPQ) was overexpressed with the use of lentivirus infection. Cell proliferation was analyzed by cell number counting and Ki67 immunostaining. RNA immunoprecipitation (RIP) was used to analyze the co-binding between the SFPQ and MITF or NEAT1. Results: NEAT1 was highly expressed in proliferative RPE cells, which had low expression of (-)MITF. Knockdown of NEAT1 in RPE cells switched the MITF splicing pattern to produce higher levels of (-)MITF and inhibited cell proliferation. Mechanistically, NEAT1 recruited SFPQ to bind directly with MITF mRNA to regulate its alternative splicing. Overexpression of SFPQ in ARPE-19 cells enhanced the binding enrichment of SFPQ to MITF and increased the splicing efficiency of (+)MITF. The binding affinity between SFPQ and MITF was decreased after NEAT1 knockdown. Conclusions: NEAT1 acts as a scaffold to recruit SFPQ to MITF mRNA and promote its binding affinity, which plays an important role in regulating the alternative splicing of MITF and RPE cell proliferation.

Enlargement, Reduction, and Even Reversal of Relative Migration Speeds of Endothelial and Smooth Muscle Cells on Biomaterials Simply by Adjusting RGD Nanospacing.

Although many tissue regeneration processes after biomaterial implantation are related to migrations of multiple cell types on material surfaces, available tools to adjust relative migration speeds are very limited. Herein, we put forward a nanomaterial strategy to employ surface modification with arginine-glycine-aspartate (RGD) nanoarrays to tune in vitro cell migration using endothelial cells (ECs) and smooth muscle cells (SMCs) as demonstrated cell types. We found that migrations of both cell types exhibited a nonmonotonic trend with the increase of RGD nanospacing, yet with different peaks-74 nm for SMCs but 95 nm for ECs. The varied sensitivities afford a facile way to regulate the relative migration speeds. Although ECs migrated at a speed similar to SMCs on a non-nano surface, the migration of ECs could be controlled to be significantly faster or slower than SMCs simply by adjusting the RGD nanospacing. This study suggests a potential application of surface modification of biomaterials on a nanoscale level.

A two-layer numerical model of soil moisture dynamics: Model development.

Simulating water moisture flow in variably saturated soils with a relatively shallow water table is challenging due to the high nonlinear behavior of Richards' equation (RE). A two-layer approximation of RE was derived in this paper, which describes vertically-averaged soil moisture content and flow dynamics in the root zone and the unsaturated soil below. To this end, the partial differential equation (PDE) describing RE was converted into two-coupled ordinary differential equations (ODEs) describing dynamic vertically-averaged soil moisture variations in the two soil zones subject to a deep or shallow water table in addition to variable soil moisture flux and pressure conditions at the surface. The coupled ODEs were solved numerically using the iterative Huen's method for a variety of flux and pressure-controlled top and bottom boundary conditions (BCs). The numerical model was evaluated for three typical soil textures with free-drainage and mixed flux-pressure head at the bottom boundary under various atmospheric conditions. The results of soil water contents and fluxes were validated using HYDRUS-1D as a benchmark. Simulated values showed that the new model is numerically stable and generally accurate in simulating vertically-averaged soil moisture in the two layers under various flux and prescribed pressure BCs. A hypothetical simulation scenario involving desaturation of initially saturated soil profile caused by exponentially declining water table demonstrated the robustness of the numerical model in tracking vertically-averaged moisture contents in the roots layer and the lower vadose soil as the water table continued to fall. The two-layer model can be used by researchers to simulate variably saturated soils in wetlands and by water resources planners for efficient coupling of land-surface systems to groundwater and management of conjunctive use of surface and groundwater.

Effects of Heat Stress on the Ruminal Epithelial Barrier of Dairy Cows Revealed by Micromorphological Observation and Transcriptomic Analysis.

Heat stress (HS) alters the rumen fermentation of dairy cows thereby affecting the metabolism of rumen papillae and thus the epithelial barrier function. The aim of the present study was to investigate if HS damages the barrier function of ruminal epithelia. Eight multiparous Holstein dairy cows with rumen cannula were randomly equally allocated to two replicates (n = 4), with each replicate being subjected to heat stress or thermal neutrality and pair-feeding in four environmental chambers. Micromorphological observation showed HS aggravated the shedding of the corneum and destroyed the physical barrier of the ruminal epithelium to a certain extent. Transcriptomics analysis of the rumen papillae revealed pathways associated with DNA replication and repair and amino acid metabolism were perturbated, the biological processes including sister chromatid segregation, etc. were up-regulated by HS, while the MAPK and NF-kB cell signaling pathways were downregulated. However, no heat stress-specific change in the expression of tight junction protein or TLR4 signaling was found, suggesting that HS negatively affected the physical barrier of the ruminal epithelium to some extent but did not break the ruminal epithelium. Heat stress invoked mechanisms to maintain the integrity of the rumen epithelial barrier by upregulating the expression of heat shock protein and repairments in rumen papillae. The increase in amino acid metabolism in rumen papillae might affect the nutrient utilization of the whole body. The findings of this study may inform future research to better understand how heat stress affects the physiology and productivity of lactating cows and the development of mitigation strategies.

Cell migration regulated by RGD nanospacing and enhanced under moderate cell adhesion on biomaterials.

While nanoscale modification of a biomaterial surface is known to influence various cell behaviors, it is unclear whether there is an optimal nanospacing of a bioactive ligand with respect to cell migration. Herein, we investigated the effects of nanospacing of arginine-glycine-aspartate (RGD) peptide on cell migration and its relation to cell adhesion. To this end, we prepared RGD nanopatterns with varied nanospacings (31-125 nm) against the nonfouling background of poly(ethylene glycol), and employed human umbilical vein endothelial cells (HUVECs) to examine cell behaviors on the nanopatterned surfaces. While HUVECs adhered well on surfaces of RGD nanospacing less than 70 nm and exhibited a monotonic decrease of adhesion with the increase of RGD nanospacing, cell migration exhibited a nonmonotonic change with the ligand nanospacing: the maximum migration velocity was observed around 90 nm of nanospacing, and slow or very slow migration occurred in the cases of small or large RGD nanospacings. Therefore, moderate cell adhesion is beneficial for fast cell migration. Further molecular biology studies revealed that attenuated cell adhesion and activated dynamic actin rearrangement accounted for the promotion of cell migration, and the genes of small G proteins such as Cdc42 were upregulated correspondingly. The present study sheds new light on cell migration and its relation to cell adhesion, and paves a way for designing biomaterials for applications in regenerative medicine.

Twadn: an efficient alignment algorithm based on time warping for pairwise dynamic networks.

BACKGROUND: Network alignment is an efficient computational framework in the prediction of protein function and phylogenetic relationships in systems biology. However, most of existing alignment methods focus on aligning PPIs based on static network model, which are actually dynamic in real-world systems. The dynamic characteristic of PPI networks is essential for understanding the evolution and regulation mechanism at the molecular level and there is still much room to improve the alignment quality in dynamic networks. RESULTS: In this paper, we proposed a novel alignment algorithm, Twadn, to align dynamic PPI networks based on a strategy of time warping. We compare Twadn with the existing dynamic network alignment algorithm DynaMAGNA++ and DynaWAVE and use area under the receiver operating characteristic curve and area under the precision-recall curve as evaluation indicators. The experimental results show that Twadn is superior to DynaMAGNA++ and DynaWAVE. In addition, we use protein interaction network of Drosophila to compare Twadn and the static network alignment algorithm NetCoffee2 and experimental results show that Twadn is able to capture timing information compared to NetCoffee2. CONCLUSIONS: Twadn is a versatile and efficient alignment tool that can be applied to dynamic network. Hopefully, its application can benefit the research community in the fields of molecular function and evolution.

Quantifying China's iron in-use stock and its driving factors analysis.

China is experiencing unprecedented industrialization and urbanization which promotes the rapid growth of iron resource consumption and in-use stock. The material flow analysis (MFA) model and the average use life method were applied to analyze China's iron in-use stock (IIUS), and the IIUS reached 7.07 billion tons in 2016 in the reference scenario. Three driving factors of the intensity of IIUS were analyzed. Among them, the per capita IIUS was rising, and it was 5.11 t/cap in 2016 in the reference scenario. In addition, the per capita crude steel output has stabilized, which was 0.58 t/cap in 2016. The intensity of crude steel use was declining and showed the inverted U-shape. The decoupling indicator was applied to analyze the relationship between IIUS and economic growth. The decoupling of IIUS from economic growth was later than that of actual iron consumption, and the IIUS did not decoupling from economic growth in recent years. The actual iron consumption has continued to decoupling from economic growth since 2010, and the decoupling indicator peaked at 1.76 in 2015. The future per capita IIUS was predicted in different scenario and the relationship between future IIUS and GDP was analyzed. The per capita IIUS will reach saturation in 2030-2040, and the intensity of IIUS also conforms to the inverted U-shape.

A novel algorithm for alignment of multiple PPI networks based on simulated annealing.

Proteins play essential roles in almost all life processes. The prediction of protein function is of significance for the understanding of molecular function and evolution. Network alignment provides a fast and effective framework to automatically identify functionally conserved proteins in a systematic way. However, due to the fast growing genomic data, interactions and annotation data, there is an increasing demand for more accurate and efficient tools to deal with multiple PPI networks. Here, we present a novel global alignment algorithm NetCoffee2 based on graph feature vectors to discover functionally conserved proteins and predict function for unknown proteins. To test the algorithm performance, NetCoffee2 and three other notable algorithms were applied on eight real biological datasets. Functional analyses were performed to evaluate the biological quality of these alignments. Results show that NetCoffee2 is superior to existing algorithms IsoRankN, NetCoffee and multiMAGNA++ in terms of both coverage and consistency. The binary and source code are freely available under the GNU GPL v3 license at https://github.com/screamer/NetCoffee2.

MD-SVM: a novel SVM-based algorithm for the motif discovery of transcription factor binding sites.

BACKGROUND: Transcription factors (TFs) play important roles in the regulation of gene expression. They can activate or block transcription of downstream genes in a manner of binding to specific genomic sequences. Therefore, motif discovery of these binding preference patterns is of central significance in the understanding of molecular regulation mechanism. Many algorithms have been proposed for the identification of transcription factor binding sites. However, it remains a challengeable problem. RESULTS: Here, we proposed a novel motif discovery algorithm based on support vector machine (MD-SVM) to learn a discriminative model for TF binding sites. MD-SVM firstly obtains position weight matrix (PWM) from a set of training datasets. Then it translates the MD problem into a computational framework of multiple instance learning (MIL). It was applied to several real biological datasets. Results show that our algorithm outperforms MI-SVM in terms of both accuracy and specificity. CONCLUSIONS: In this paper, we modeled the TF motif discovery problem as a MIL optimization problem. The SVM algorithm was adapted to discriminate positive and negative bags of instances. Compared to other svm-based algorithms, MD-SVM show its superiority over its competitors in term of ROC AUC. Hopefully, it could be of benefit to the research community in the understanding of molecular functions of DNA functional elements and transcription factors.