Controlled Fabrication of Unimolecular Micelles as Versatile Nanoplatform for Multifunctional Applications.

Unimolecular micelles (UMs) are nano-sized structures that are composed of single molecules with precise composition. Compared to self-assembled polymeric micelles, UMs possess ultra-stable property even in complex biological environment. With the development of controllable polymerization and coupling chemistry, the preparation of narrowly monodispersed UMs with precise morphology and size has been realized, which further facilitates their multifunctional applications. After brief introduction, state-of-the-art advances in the synthesis and applications of UMs are discussed with an emphasis on their bioapplications. It is believed that these UMs have great potential in future fabrication of multifunctional nanoplatforms.

1,3,6-Trigalloylglucose: A Novel Potent Anti-Helicobacter pylori Adhesion Agent Derived from Aqueous Extracts of Terminalia chebula Retz.

1,3,6-Trigalloylglucose is a natural compound that can be extracted from the aqueous extracts of ripe fruit of Terminalia chebula Retz, commonly known as "Haritaki". The potential anti-Helicobacter pylori (HP) activity of this compound has not been extensively studied or confirmed in scientific research. This compound was isolated using a semi-preparative liquid chromatography (LC) system and identified through Ultra-high-performance liquid chromatography-MS/MS (UPLC-MS/MS) and Nuclear Magnetic Resonance (NMR). Its role was evaluated using Minimum inhibitory concentration (MIC) assay and minimum bactericidal concentration (MBC) assay, scanning electron microscope (SEM), inhibiting kinetics curves, urea fast test, Cell Counting Kit-8 (CCK-8) assay, Western blot, and Griess Reagent System. Results showed that this compound effectively inhibits the growth of HP strain ATCC 700392, damages the HP structure, and suppresses the Cytotoxin-associated gene A (Cag A) protein, a crucial factor in HP infection. Importantly, it exhibits selective antimicrobial activity without impacting normal epithelial cells GES-1. In vitro studies have revealed that 1,3,6-Trigalloylglucose acts as an anti-adhesive agent, disrupting the adhesion of HP to host cells, a critical step in HP infection. These findings underscore the potential of 1,3,6-Trigalloylglucose as a targeted therapeutic agent against HP infections.

A Collaborative Data Collection Scheme Based on Optimal Clustering for Wireless Sensor Networks.

In recent years, energy-efficient data collection has evolved into the core problem in the resource-constrained Wireless Sensor Networks (WSNs). Different from existing data collection models in WSNs, we propose a collaborative data collection scheme based on optimal clustering to collect the sensed data in an energy-efficient and load-balanced manner. After dividing the data collection process into the intra-cluster data collection step and the inter-cluster data collection step, we model the optimal clustering problem as a separable convex optimization problem and solve it to obtain the analytical solutions of the optimal clustering size and the optimal data transmission radius. Then, we design a Cluster Heads (CHs)-linking algorithm based on the pseudo Hilbert curve to build a CH chain with the goal of collecting the compressed sensed data among CHs in an accumulative way. Furthermore, we also design a distributed cluster-constructing algorithm to construct the clusters around the virtual CHs in a distributed manner. The experimental results show that the proposed method not only reduces the total energy consumption and prolongs the network lifetime, but also effectively balances the distribution of energy consumption among CHs. By comparing it o the existing compression-based and non-compression-based data collection schemes, the average reductions of energy consumption are 17.9% and 67.9%, respectively. Furthermore, the average network lifetime extends no less than 20-times under the same comparison.

Abnormal bronchial origin in the right middle and lower lung.

Congenital anatomical abnormalities of the pediatric bronchus is a rare and easily overlooked condition. In this study, we identified an 8-year-old patient with congenital anomalies of bronchial origin that caused his clinical manifestations of cough and shortness of breath. This diagnosis needs to be taken into possible consideration when similar clinical manifestations occur in a pediatric patient without a cause.

Identification and RT-qPCR Validation of Biomarkers Based on Butyrate Metabolism-Related Genes to Predict Recurrent Miscarriage.

Purpose: To date, the cause of recurrent miscarriage (RM) in at least 50% of patients remains unknown. However, no study has explored the correlation between butyrate metabolism-related genes (BMRGs) and RM. Methods: RM-related datasets (GSE165004, GSE111974, GSE73025, and GSE179996) were obtained from the Gene Expression Omnibus (GEO) database. First, 595 differentially expressed genes (DEGs) were identified between the RM and control samples in GSE165004. Subsequently, 213 differentially expressed BMRGs (DE-BMRGs) were identified by considering the intersection of DEGs with BMRGs. The protein-protein interaction (PPI)network of DE-BMRGs contained 156 nodes and 250 edges, and a key module was obtained. In total, four biomarkers (ACTR2, ANXA2, PFN1, and OAS1) were acquired through least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and random forest (RF). Immune analysis revealed two immune cells and three immune-related gene sets that were significantly different between the RM and control groups, namely, T helper cells, regulatory T cells (Treg), MHC class I, parainflammation, and type I IFN response. In addition, a TF-mRNA network based on the top 100 nodes ranked in the order of connectivity was created, including 100 nodes and 253 edges, such as MTERF2-ACTR2, NKX23-PFN1, STAT1-OAS1, and SP100-ANXA2. Results: Finally, 3 drugs (withaferin A, N-ethylmaleimide, and etoposide) were predicted to interact with 2 biomarkers (ANXA2 and ACTR2). Eventually, ANXA2 and OAS1 were significantly downregulated, and PFN1 was markedly overexpressed in the RM group, as determined by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Conclusion: Our findings authenticated four butyrate metabolism-related biomarkers for the diagnosis of RM, providing a scientific reference for further studies on RM treatment.

Evaluating the efficacy and suggesting technical optimizations for endoscopic lumbar interbody fusion across different lumbar spondylolisthesis types.

Purpose: To evaluate the efficacy of the endoscopic lumbar interbody fusion technique across different types of lumbar spondylolisthesis, specifically Grade I and Grade II, and suggest technical optimizations based on therapeutic outcomes, complications, and patient satisfaction for both grades. Methods: We analyzed data from 57 L4 to 5 spondylolisthesis patients, all categorized as either Grade I or Grade II, comprising 31 males and 26 females. Of these, 36 were diagnosed with Grade I and 21 with Grade II. All subjects underwent the endoscopic lumbar interbody fusion procedure. Primary evaluation metrics included pre and post-operative Vasual Analogue Scale（VAS） pain scores, Osewewtry Disability Index（ODI） functional scores, surgical duration, intraoperative blood loss, degree of spondylolisthesis correction, complications, and patient satisfaction levels. Results: At a minimum of 6 months post-operation, the VAS score for the Grade I cohort reduced from an initial 7.30 ± 0.69 to 2.97 ± 0.47, while the Grade II cohort saw a decrease from 7.53 ± 0.56 to 3.37 ± 0.62 (P = 0.0194). The ODI score in the Grade I group declined from 66.88 ± 5.15 % pre-operation to 29.88 ± 6.36 % post-operation, and in the Grade II group, it decreased from 69.33 ± 5.27 % to 34.66 ± 6.01 % (P = 0.0092). The average surgical duration for the Grade I group stood at 155.72 ± 17.75 min, compared to 180.38 ± 14.72 min for the Grade II group (P < 0.001). The mean intraoperative blood loss for the Grade I group was 144.58 ± 28.61 ml, whereas the Grade II group registered 188.23 ± 9.41 ml (P < 0.001). Post-surgery, 83 % of the Grade I patients achieved a correction degree exceeding 80 %, and 61 % of the Grade II patients surpassed 50 % (P = 0.0055). Complication rates were recorded at 8 % for Grade I and 16 % for Grade II. Patient satisfaction reached 94 % in the Grade I cohort and 90 % in the Grade II cohort. Conclusion: Endoscopic lumbar interbody fusion showcases promising therapeutic outcomes for both Grade I and Grade II lumbar spondylolisthesis. However, surgeries for Grade II spondylolisthesis tend to be lengthier, more challenging, involve greater blood loss, and have a heightened complication risk. Tailored technical adjustments and enhancements are essential for addressing the distinct spondylolisthesis types.

Altered dynamic functional connectivity of insular subdivisions among male cigarette smokers.

Background: Insular subdivisions show distinct patterns of resting state functional connectivity with specific brain regions, each with different functional significance in chronic cigarette smokers. This study aimed to explore the altered dynamic functional connectivity (dFC) of distinct insular subdivisions in smokers. Methods: Resting-state BOLD data of 31 smokers with nicotine dependence and 27 age-matched non-smokers were collected. Three bilateral insular regions of interest (dorsal, ventral, and posterior) were set as seeds for analyses. Sliding windows method was used to acquire the dFC metrics of different insular seeds. Support vector machine based on abnormal insular dFC was applied to classify smokers from non-smokers. Results: We found that smokers showed lower dFC variance between the left ventral anterior insula and both the right superior parietal cortex and the left inferior parietal cortex, as well as greater dFC variance the right ventral anterior insula with the right middle cingulum cortex relative to non-smokers. Moreover, compared to non-smokers, it is found that smokers demonstrated altered dFC variance of the right dorsal insula and the right middle temporal gyrus. Correlation analysis showed the higher dFC between the right dorsal insula and the right middle temporal gyrus was associated with longer years of smoking. The altered insular subdivision dFC can classify smokers from non-smokers with an accuracy of 89.66%, a sensitivity of 96.30% and a specify of 83.87%. Conclusions: Our findings highlighted the abnormal patterns of fluctuating connectivity of insular subdivision circuits in smokers and suggested that these abnormalities may play a significant role in the mechanisms underlying nicotine addiction and could potentially serve as a neural biomarker for addiction treatment.

Altered insular functional activity among electronic cigarettes users with nicotine dependence.

Electronic cigarettes (e-cigs) use, especially among youngsters, has been on the rise in recent years. However, little is known about the long-term effects of the use of e-cigs on brain functional activity. We acquired the resting-state functional magnetic resonance imaging (rs-fMRI) data from 93 e-cigs users with nicotine dependence and 103 health controls (HC). The local synchronization was analyzed via the regional homogeneity (ReHo) method at voxel-wise level. The functional connectivity (FC) between the nucleus accumbens (NAcc), the ventral tegmental area (VTA), and the insula was calculated at ROI-wise level. The support vector machining classification model based on rs-fMRI measures was used to identify e-cigs users from HC. Compared with HC, nicotine-dependent e-cigs users showed increased ReHo in the right rolandic operculum and the right insula (p < 0.05, FDR corrected). At the ROI-wise level, abnormal FCs between the NAcc, the VTA, and the insula were found in e-cigs users compared to HC (p < 0.05, FDR corrected). Correlation analysis found a significant negative correlation between ReHo in the left NAcc and duration of e-cigs use (r = -0.273, p = 0.008, FDR corrected). The following support vector machine model based on significant results of rs-fMRI successfully differentiates chronic e-cigs users from HC with an accuracy of 73.47%, an AUC of 0.781, a sensitivity of 67.74%, and a specificity of 78.64%. Dysregulated spontaneous activity and FC of addiction-related regions were found in e-cigs users with nicotine dependence, which provides crucial insights into the prevention of its initial use and intervention for quitting e-cigs.

Synthesis and Application of a Near-Infrared Light-Emitting Fluorescent Probe for Specific Imaging of Cancer Cells with High Sensitivity and Selectivity.

Background: The preclinical diagnosis of tumors is of great significance to cancer treatment. Near-infrared fluorescence imaging technology is promising for the in-situ detection of tumors with high sensitivity. Methods: Here, a fluorescent probe was synthesized on the basis of Au nanoclusters with near-infrared light emission and applied to fluorescent cancer cell labeling. Near-infrared methionine-N-Hydroxy succinimide Au nanoclusters (Met-NHs-AuNCs) were prepared successfully by one-pot synthesis using Au nanoclusters, methionine, and N-Hydroxy succinimide as frameworks, reductants, and stabilizers, respectively. The specific fluorescence imaging of tumor cells or tissues by fluorescent probe was studied on the basis of SYBYL Surflex-DOCK simulation model of LAT1 active site of overexpressed receptor on cancer cell surface. The results showed that Met-NHs-AuNCs interacted with the surface of LAT1, and C_Score scored the conformation of the probe and LAT1 as five. Results: Characterization and in vitro experiments were conducted to explore the Met-NHs-AuNCs targeted uptake of cancer cells. The prepared near-infrared fluorescent probe (Met-NHs-AuNCs) can specifically recognize the overexpression of L-type amino acid transporter 1 (LAT1) in cancer cells so that it can show red fluorescence in cancer cells. Meanwhile, normal cells (H9c2) have no fluorescence. Conclusion: The fluorescent probe demonstrates the power of targeting and imaging cancer cells.

Multi-Organ Foundation Model for Universal Ultrasound Image Segmentation with Task Prompt and Anatomical Prior.

Semantic segmentation of ultrasound (US) images with deep learning has played a crucial role in computer-aided disease screening, diagnosis and prognosis. However, due to the scarcity of US images and small field of view, resulting segmentation models are tailored for a specific single organ and may lack robustness, overlooking correlations among anatomical structures of multiple organs. To address these challenges, we propose the Multi-Organ FOundation (MOFO) model for universal US image segmentation. The MOFO is optimized jointly from multiple organs across various anatomical regions to overcome the data scarcity and explore correlations between multiple organs. The MOFO extracts organ-invariant representations from US images. Simultaneously, the task prompt is employed to refine organ-specific representations for segmentation predictions. Moreover, the anatomical prior is incorporated to enhance the consistency of the anatomical structures. A multi-organ US database, comprising 7039 images from 10 organs across various regions of the human body, has been established to evaluate our model. Results demonstrate that the MOFO outperforms single-organ methods in terms of the Dice coefficient, 95% Hausdorff distance and average symmetric surface distance with statistically sufficient margins. Our experiments in multi-organ universal segmentation for US images serve as a pioneering exploration of improving segmentation performance by leveraging semantic and anatomical relationships within US images of multiple organs.

Can incorporating image resolution into neural networks improve kidney tumor classification performance in ultrasound images?

Deep learning has been widely used in ultrasound image analysis, and it also benefits kidney ultrasound interpretation and diagnosis. However, the importance of ultrasound image resolution often goes overlooked within deep learning methodologies. In this study, we integrate the ultrasound image resolution into a convolutional neural network and explore the effect of the resolution on diagnosis of kidney tumors. In the process of integrating the image resolution information, we propose two different approaches to narrow the semantic gap between the features extracted by the neural network and the resolution features. In the first approach, the resolution is directly concatenated with the features extracted by the neural network. In the second approach, the features extracted by the neural network are first dimensionally reduced and then combined with the resolution features to form new composite features. We compare these two approaches incorporating the resolution with the method without incorporating the resolution on a kidney tumor dataset of 926 images consisting of 211 images of benign kidney tumors and 715 images of malignant kidney tumors. The area under the receiver operating characteristic curve (AUC) of the method without incorporating the resolution is 0.8665, and the AUCs of the two approaches incorporating the resolution are 0.8926 (P < 0.0001) and 0.9135 (P < 0.0001) respectively. This study has established end-to-end kidney tumor classification systems and has demonstrated the benefits of integrating image resolution, showing that incorporating image resolution into neural networks can more accurately distinguish between malignant and benign kidney tumors in ultrasound images.

Adsorption and release of active species into and from multifunctional ionic microgel particles.

We synthesize monodisperse ionic microgel particles which undergo a large change in volume in response to environmental stimuli such as pH and temperature. In addition, the study elucidates the effective uptake and release of rheology modifiers from these microgel particles to alter the bulk viscosity of a surrounding fluid. Moreover, we found that the prepared ionic microgel particles can demonstrate abilities to adsorb and repel iron oxide nanoparticles (Fe3O4-NPs) upon pH variation. The extent of the loading of Fe3O4-NPs within the colloidal particles and morphology can be manipulated by tunable interactions between the Fe3O4-NPs and ionic microgel particles.

CCT-Unet: A U-Shaped Network Based on Convolution Coupled Transformer for Segmentation of Peripheral and Transition Zones in Prostate MRI.

The accurate segmentation of prostate region in magnetic resonance imaging (MRI) can provide reliable basis for artificially intelligent diagnosis of prostate cancer. Transformer-based models have been increasingly used in image analysis due to their ability to acquire long-term global contextual features. Although Transformer can provide feature representations of the overall appearance and contour representations at long distance, it does not perform well on small-scale datasets of prostate MRI due to its insensitivity to local variation such as the heterogeneity of the grayscale intensities in the peripheral zone and transition zone across patients; meanwhile, the convolutional neural network (CNN) could retain these local features well. Therefore, a robust prostate segmentation model that can aggregate the characteristics of CNN and Transformer is desired. In this work, a U-shaped network based on the convolution coupled Transformer is proposed for segmentation of peripheral and transition zones in prostate MRI, named the convolution coupled Transformer U-Net (CCT-Unet). The convolutional embedding block is first designed for encoding high-resolution input to retain the edge detail of the image. Then the convolution coupled Transformer block is proposed to enhance the ability of local feature extraction and capture long-term correlation that encompass anatomical information. The feature conversion module is also proposed to alleviate the semantic gap in the process of jumping connection. Extensive experiments have been conducted to compare our CCT-Unet with several state-of-the-art methods on both the ProstateX open dataset and the self-bulit Huashan dataset, and the results have consistently shown the accuracy and robustness of our CCT-Unet in MRI prostate segmentation.

Establishment and Clinical Application of the Nomogram Related to Risk or Prognosis of Hepatocellular Carcinoma: A Review.

Hepatocellular carcinoma (HCC) is the most prevalent primary liver malignancy, accounting for approximately 90% of all primary liver cancers, with high mortality and a poor prognosis. A large number of predictive models have been applied that integrate multiple clinical factors and biomarkers to predict the prognosis of HCC. Nomograms, as easy-to-use prognostic predictive models, are widely used to predict the probability of clinical outcomes. We searched PubMed with the keywords "hepatocellular carcinoma" and "nomogram", and 974 relative literatures were retrieved. According to the construction methodology and the real validity of the nomograms, in this study, 97 nomograms for HCC were selected in 77 publications. These 97 nomograms were established based on more than 100,000 patients, covering seven main prognostic outcomes. The research data of 56 articles are from hospital-based HCC patients, and 13 articles provided external validation results of the nomogram. In addition to AFP, tumor size, tumor number, stage, vascular invasion, age, and other common prognostic risk factors are included in the HCC-related nomogram, more and more biomarkers, including gene mRNA expression, gene polymorphisms, and gene signature, etc. were also included in the nomograms. The establishment, assessment and validation of these nomograms are also discussed in depth. This study would help clinicians construct and select appropriate nomograms to guide precise judgment and appropriate treatments.

Machine learning based on gadoxetic acid-enhanced MRI for differentiating atypical intrahepatic mass-forming cholangiocarcinoma from poorly differentiated hepatocellular carcinoma.

PURPOSE: The study was to develop a Gd-EOB-DTPA-enhanced MRI radiomics model for differentiating atypical intrahepatic mass-forming cholangiocarcinoma (aIMCC) from poorly differentiated hepatocellular carcinoma (pHCC). MATERIALS AND METHODS: A total of 134 patients (51 aIMCC and 83 pHCC) who underwent Gadoxetic acid-enhanced MRI between March 2016 and March 2022 were enrolled in this study and then randomly assigned to the training and validation cohorts by 7:3 (93 patients and 41 patients, respectively). The radiomics features were extracted from the hepatobiliary phase of Gadoxetic acid-enhanced MRI. In the training cohort, the SelectKBest and the least absolute shrinkage and selection operator (LASSO) were used to select the radiomics features. The clinical, radiomics, and clinical-radiomics model were established using four machine learning algorithms. The performance of the model was evaluated by the receiver operating characteristic (ROC) curve. Comparison of the radiomics and clinical-radiomics model was done by the Delong test. The clinical usefulness of the model was evaluated using decision curve analysis (DCA). RESULTS: In 1132 extracted radiomic features, 15 were selected to develop radiomics signature. For identifying aIMCC and pHCC, the radiomics model constructed by random forest algorithm showed the high performance (AUC = 0.90) in the training cohort. The performance of the clinical-radiomics model (AUC = 0.89) was not significantly different (P = 0.88) from that of the radiomics model constructed by random forest algorithm (AUC = 0.86) in the validation cohort. DCA demonstrated that the clinical-radiomics model constructed by random forest algorithm had a high net clinical benefit. CONCLUSION: The clinical-radiomics model is an effective tool to distinguish aIMCC from pHCC and may provide additional value for the development of treatment plans.

Lyophilized mRNA-lipid nanoparticle vaccines with long-term stability and high antigenicity against SARS-CoV-2.

Advanced mRNA vaccines play vital roles against SARS-CoV-2. However, most current mRNA delivery platforms need to be stored at -20 °C or -70 °C due to their poor stability, which severely restricts their availability. Herein, we develop a lyophilization technique to prepare SARS-CoV-2 mRNA-lipid nanoparticle vaccines with long-term thermostability. The physiochemical properties and bioactivities of lyophilized vaccines showed no change at 25 °C over 6 months, and the lyophilized SARS-CoV-2 mRNA vaccines could elicit potent humoral and cellular immunity whether in mice, rabbits, or rhesus macaques. Furthermore, in the human trial, administration of lyophilized Omicron mRNA vaccine as a booster shot also engendered strong immunity without severe adverse events, where the titers of neutralizing antibodies against Omicron BA.1/BA.2/BA.4 were increased by at least 253-fold after a booster shot following two doses of the commercial inactivated vaccine, CoronaVac. This lyophilization platform overcomes the instability of mRNA vaccines without affecting their bioactivity and significantly improves their accessibility, particularly in remote regions.

Insulin resistance in school-aged girls with overweight and obesity is strongly associated with elevated white blood cell count and absolute neutrophil count.

Background: The primary objective of the study was to discuss the sex differences in insulin resistance-induced changes in metabolic and inflammatory markers in school-aged children with overweight and obesity. Methods: A cross-sectional study of 800 children aged seven and twelve years was performed. Questionnaires, anthropometric data and fasting blood samples were collected. Results: Children with overweight and obesity showed statistically significant differences in multiple metabolic and inflammatory markers compared with children with normal BMI. The correlation coefficient (r) between white blood cell count, absolute neutrophil count, fasting plasma insulin, HOMA-IR, HOMA-ß, triglyceride, HDL-C, triglyceride/HDL ratio, alanine transaminase, serum uric acid, systolic blood pressure and BMI were higher in all children, but the linear relationships between white blood cell count, absolute neutrophil count and BMI were stronger in girls with overweight and obesity than in boys with overweight and obesity. Subsequently, HOMA-IR was shown to be more strongly associated with increased white blood cell count and absolute neutrophil count in school-aged girls with overweight and obesity by partial correlation analysis and the multiple linear regression analysis. Conclusions: Elevated white blood cell count and absolute neutrophil count in children with overweight and obesity, especially girls, can serve as markers of insulin resistance.

Aberrant lncRNA-mRNA expression profile and function networks during the adipogenesis of mesenchymal stem cells from patients with ankylosing spondylitis.

Objective: We have already demonstrated that mesenchymal stem cells from patients with ankylosing spondylitis (ASMSCs) exhibited greater adipogenic differentiation potential than those from healthy donors (HDMSCs). Here, we further investigated the expression profile of long noncoding RNA (lncRNA) and mRNA, aiming to explore the underlying mechanism of abnormal adipogenic differentiation in ASMSCs. Methods: HDMSCs and ASMSCs were separately isolated and induced with adipogenic differentiation medium for 10 days. Thereafter, lncRNAs and mRNAs that were differentially expressed (DE) between HDMSCs and ASMSCs were identified via high-throughput sequencing and confirmed by quantitative real-time PCR (qRT-PCR) assays. Then, the DE genes were annotated and enriched by GO analysis. In addition, protein interaction network was constructed to evaluate the interactions between DE mRNAs and to find hub nodes and study cliques. Besides, co-expression network analysis was carried out to assess the co-expressions between DE mRNA and DE lncRNAs, and competing endogenous RNA (ceRNA) network analysis were conducted to predict the relationships among lncRNAs, mRNAs and miRNAs. The signaling pathways based on the DE genes and the predicted DE genes were enriched by KEGG analysis. Results: A total of 263 DE lncRNAs and 1376 DE mRNAs were found during adipogenesis in ASMSCs. qRT-PCR indicated that the expression of the top 20 mRNAs and the top 10 lncRNAs was consistent with the high-throughput sequencing data. Several lncRNAs (NR_125386.1, NR_046473.1 and NR_038937.1) and their target genes (SPN and OR1AIP2), together with the significantly co-expressed pairs of DE lncRNAs and DE mRNAs (SLC38A5-ENST00000429588.1, TMEM61-ENST00000400755.3 and C5orf46-ENST00000512300.1), were closely related to the enhanced adipogenesis of ASMSCs by modulating the PPAR signaling pathway. Conclusion: Our study analyzed the expression profiles of DE lncRNAs and DE mRNAs during adipogenesis in ASMSCs and HDMSCs. Several DE lncRNAs, DE mRNAs and signaling pathways that probably participate in the aberrant adipogenesis of ASMSCs were selected for future study. These results will likely provide potential targets for our intervention on fat metaplasia and subsequent new bone formation in patients with AS in the future.

3-D Gabor-based anisotropic diffusion for speckle noise suppression in dynamic ultrasound images.

Speckle noise contaminates medical ultrasound images, and the suppression of speckle noise is helpful for image interpretation. Traditional ultrasound denoising (i.e., despeckling) methods are developed on two-dimensional static images. However, one of the advantages of ultrasonography is its nature of dynamic imaging. A method for dynamic ultrasound despeckling is expected to incorporate both the spatial and temporal information in successive images of dynamic ultrasound and thus yield better denoising performance. Here we regard a dynamic ultrasound video as three-dimensional (3-D) images with two dimensions in the spatial domain and one in the temporal domain, and we propose a despeckling algorithm for dynamic ultrasound named the 3-D Gabor-based anisotropic diffusion (GAD-3D). The GAD-3D expands the classic two-dimensional Gabor-based anisotropic diffusion (GAD) into 3-D domain. First, we proposed a robust 3-D Gabor-based edge detector by capturing the edge with 3-D Gabor transformation. Then we embed this novel detector into the partial differential equation of GAD to guide the 3-D diffusion process. In the simulation experiment, when the noise variance is as high as 0.14, the GAD-3D improves the Pratt's figure of merit, mean structural similarity index and peak signal-to-noise ratio by 24.32%, 10.98%, and 6.51%, respectively, compared with the best values of seven other methods. Experimental results on clinical dynamic ultrasonography suggest that the GAD-3D outperforms the other seven methods in noise reduction and detail preservation. The GAD-3D is effective for dynamic ultrasound despeckling and may be potentially valuable for disease assessment in dynamic medical ultrasonography.

Association of two polymorphisms Asp299Gly and Thr399Ile in Toll-like receptor 4 with rheumatoid arthritis: A meta-analysis.

Our meta-analysis aims to evaluate the association of Asp299Gly and Thr399Ile with rheumatoid arthritis (RA) susceptibility and severity. By manually searching 3 electronic databases (PubMed, Embase and Web of Science), relevant articles were collected. After checking eligibility for every study, this meta-analysis on eligible studies was performed under 5 genetic models: (1) allelic contrast; (2) heterozygous model; (3) homozygous model; (4) dominant model; (5) recessive model. In Spanish populations, a significantly decreased RA risk was identified in allelic comparison (odds ratio [OR] = 0.73, 95% CI 0.55 ~ 0.96) and dominant model (OR = 0.74, 95% CI 0.56 ~ 0.99) of Asp299Gly polymorphism. A trend of reduced risk was also observed under the heterozygous model (OR = 0.77, 95% CI 0.58 ~ 1.03). As for Thr399Ile, it might also have a protective effect on Spanish populations in allelic comparison (OR = 0.71, 95% CI 0.44 ~ 1.15). In contrast, for both Asp299Gly and Thr399Ile, a higher risk of RA was detected in Chinese Han populations. The frequency of both Asp299Gly and Thr399Ile increased in rheumatoid factor (RF)-positive subjects in Chinese patients (Asp299Gly, RF+:RF- = 0.165:0.145; Thr399Ile, RF+:RF- = 0.170:0.161) and decreased in Spanish patients (Asp299Gly, RF+:RF- = 0.060:0.073; Thr399Ile, RF+:RF- = 0.046:0.056), but not to a statistically significant extent. Our meta-analysis suggested that both Asp299Gly and Thr399Ile might have a protective effect on Spanish populations, but the 2 polymorphisms could act as a susceptible factor in Chinese Han populations. To confirm our results, further investigation concerning the functional impacts of Asp299Gly and Thr399Ile are still needed.