Magnetic hydrogel particles improve nanopore sequencing of SARS-CoV-2 and other respiratory viruses

Presented here is a magnetic hydrogel particle enabled workflow for capturing and concentrating SARS-CoV-2 from diagnostic remnant swab samples that significantly improves sequencing results using the Oxford Nanopore Technologies MinION sequencing platform. Our approach utilizes a novel affinity-based magnetic hydrogel particle, circumventing low input sample volumes and allowing for both rapid manual and automated high throughput workflows that are compatible with Nanopore sequencing. This approach enhances standard RNA extraction protocols, providing up to 40 × improvements in viral mapped reads, and improves sequencing coverage by 20-80% from lower titer diagnostic remnant samples. Furthermore, we demonstrate that this approach works for contrived influenza virus and respiratory syncytial virus samples, suggesting that it can be used to identify and improve sequencing results of multiple viruses in VTM samples. These methods can be performed manually or on a KingFisher automation platform.

Heterogeneity in the onwards transmission risk between local and imported cases affects practical estimates of the time-dependent reproduction number

During infectious disease outbreaks, inference of summary statistics characterizing transmission is essential for planning interventions. An important metric is the time-dependent reproduction number (Rt), which represents the expected number of secondary cases generated by each infected individual over the course of their infectious period. The value of Rt varies during an outbreak due to factors such as varying population immunity and changes to interventions, including those that affect individuals' contact networks. While it is possible to estimate a single population-wide Rt, this may belie differences in transmission between subgroups within the population. Here, we explore the effects of this heterogeneity on Rt estimates. Specifically, we consider two groups of infected hosts: those infected outside the local population (imported cases), and those infected locally (local cases). We use a Bayesian approach to estimate Rt, made available for others to use via an online tool, that accounts for differences in the onwards transmission risk from individuals in these groups. Using COVID-19 data from different regions worldwide, we show that different assumptions about the relative transmission risk between imported and local cases affect Rt estimates significantly, with implications for interventions. This highlights the need to collect data during outbreaks describing heterogeneities in transmission between different infected hosts, and to account for these heterogeneities in methods used to estimate Rt. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

[Suppression of HMGB1 inhibits neuronal autophagy and apoptosis to improve neurological deficits in rats following intracerebral hemorrhage]

OBJECTIVE

To investigate the effect of suppressing high-mobility group box 1 (HMGB1) on neuronal autophagy and apoptosis in rats after intracerebral hemorrhage (ICH) in rats.

METHODS

Rat models of ICH induced by intracerebral striatum injection of 0.2 U/mL collagenase Ⅳ were treated with 1 mg/kg anti-HMGB1 mAb or a control anti-IgG mAb injected via the tail immediately and at 6 h after the operation (n=5). The rats in the sham-operated group (with intracranial injection of 2 μL normal saline) and ICH model group (n=5) were treated with PBS in the same manner after the operation. The neurological deficits of the rats were evaluated using modified neurological severity score (mNSS). TUNEL staining was used to detect apoptosis of the striatal neurons, and the expressions of HMGB1, autophagy-related proteins (Beclin-1, LC3-Ⅱ and LC3-Ⅰ) and apoptosis-related proteins (Bcl-2, Bax and cleaved caspase-3) in the brain tissues surrounding the hematoma were detected using Western blotting. The expression of HMGB1 in the striatum was detected by immunohistochemistry, and serum level of HMGB1 was detected with ELISA.

RESULTS

The rat models of ICH showed significantly increased mNSS (P < 0.05), which was markedly lowered after treatment with anti- HMGB1 mAb (P < 0.05). ICH caused a significant increase of apoptosis of the striatal neurons (P < 0.05), enhanced the expressions of beclin-1, LC3-Ⅱ, Bax and cleaved caspase-3 (P < 0.05), lowered the expressions of LC3-Ⅰ and Bcl-2 (P < 0.05), and increased the content of HMGB1 (P < 0.05). Treatment with anti-HMGB1 mAb obviously lowered the apoptosis rate of the striatal neurons (P < 0.05), decreased the expressions of Beclin-1, LC3-Ⅱ, Bax and cleaved caspase-3 (P < 0.05), increased the expressions of LC3-Ⅰ and Bcl-2 (P < 0.05), and reduced the content of HMGB1 in ICH rats (P < 0.05).

CONCLUSION

Down- regulation of HMGB1 by anti-HMGB1 improves neurological functions of rats after ICH possibly by inhibiting autophagy and apoptosis of the neurons.

[Clinical analysis of penetrating keratoplasty for infants with congenital corneal opacity]

Objective: To investigate the corneal graft survival and related risk factors of primary penetrating keratoplasty in congenital corneal opacity infants. Methods: It was a retrospective cohort study. Data were collected from forty-two infants (51 eyes) who were aged ≤12 months and diagnosed with congenital corneal opacity in Beijing Tongren Hospital and Beijing Anzhen Hospital from January 1, 2017 to January 31, 2018. The mean age at surgery was (5.7±2.2) months (3-12 months). The mean follow-up duration was (28.6±2.6) months (24-33 months). All the patients underwent penetrating keratoplasty. The status of the corneal grafts and complications were observed and recorded during the regular follow-up. The survival probabilities were estimated by using the Kaplan-Meier and Log-rank test. The graft survival between different influence factors was analyzed by using the χ² test. Results: The Kaplan-Meier survival rates for penetrating keratoplasty were 84.3% (43/51) at 6 months, 78.4% (40/51) at 12 months and 60.8% (31/51) at the last follow-up. The presence of corneal neovascularization was significantly correlated with graft failure (χ²=5.264, P=0.022). The graft survival differed between eyes receiving combined surgery and mere penetrating keratoplasty and in eyes with varied surgical indications (P=0.039, <0.01). Increased intraocular pressure (7 eyes, 13.7%) and persistent epithelial defects (7 eyes, 13.7%) were the most common postoperative complications, followed by complicated cataract (4 eyes, 7.8%) and posterior capsule opacification (2 eyes, 3.9%). Conclusions: The graft survival rate was satisfactory following pediatric keratoplasty although it had a tendency to decrease with the follow-up time. Corneal neovascularization was a major risk factor of graft failure. Surgical indications and procedures also had a certain effect on the graft survival.

AB0864 A nomogram model combining inflammatory factors and MRI radiomics to assess the disease activity of the patients with axSpA in a prospective study

Background

Clinical and magnetic resonance imaging (MRI) disease activity score (DAS) are measuring different aspects of axial spondyloarthritis (axSpA), they are essential in disease activity assessment. The radiomics was on facilitating readings by clinical specialists via enhancing the medical images in which subtle data differences could be distinguished.

Objectives

If the additional information of MRI imaging can be considered as a predictor for axSpA disease activity? In this study, we sought to construct a nomogram integrating the sacroiliac joint (SIJ)- MRI radiomics features and the inflammatory biomarkers to assess disease activity and compare it with clinical disease acitivity index in axSpA patients.

Methods

203 patients data were collected prospectively and confirmed as axSpA were randomly divided into training (n = 143) and validation cohorts (n = 60). 1316 radiomics features were extracted from the 3.0T SIJ-MRI. A Nomogram model was constructed using multivariate logistic regression analysis Incorporating independent clinical factors and radiomics features score (Rad-score). The performance of clinics, Rad-score and nomogram models were evaluated by ROC analysis, calibration curve and decision curve analysis (DCA), and compared with the disease activity index(Ankylosing Spondylitis DAS (ASDAS)-C reactive protein (CRP), ASDAS-erythrocyte sedimentation rate (ESR), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI)) and Spondyloarthritis Research Consortium of Canada (SPARCC) MRI scoring system.

Results

The Rad-score allowed a good discrimination in the training (AUC, 0.91; 95% CI, 0.85-0.96) and the validation cohort (AUC, 0.84; 95% CI, 0.73-0.96). The CRP-radiomics nomogram model also showed favorable discrimination in the training (AUC, 0.96; 95% CI, 0.93-0.99) and the validation cohort (AUC, 0.89; 95% CI, 0.80-0.98), better than BASDAI(AUC, 0.58), ASDAS-CRP(AUC, 0.72), ASDAS-ESR(AUC, 0.77), ESR(AUC, 0.72), CRP(AUC, 0.77) and BASFI(AUC, 0.73), had no statistical difference with SPARCC(AUC, 0.87). Calibration curves and DCA demonstrated the nomogram fit well (p > 0.05) and was useful for activity evaluation.

Conclusion

Rad-score showed good discriminative ability to assess disease activity in axSpA. The nomogram can increase the efficacy for assessment axSpA disease activity, which might simplify clinical evaluation.

Figure 1.

Comparison of ROC curve analyses in prediction models. ROC curves of the clinical features (green curve), radiomics signature model (blue curve), and hybrid model (gold curve) of axSpA in the training cohort (A) and validation cohort (B), respectively. In addition, there are AUC of ASDAS-CRP(pink curve), ASDAS-ESR(brown curve), BASDAI(purple curve), BASFI(azure curve) and SPARCC scoring system(yellow curve) in the validation cohort (B), respectively. AUC: area under the curve; ROC: receiver operating characteristic; SPARCC: Spondyloarthritis Research Consortium of Canada; BASDAI: Bath Ankylosing Spondylitis Disease Activity Index; ASDAS: Ankylosing Spondylitis Disease Activity Score; CRP: C reactive protein; ESR: erythrocyte sedimentation rate; BASFI: Bath Ankylosing Spondylitis Disease Activity Index.

References

[1]Lee KH, Choi ST, Lee GY, Ha YJ, Choi SI. Method for Diagnosing the Bone Marrow Edema of Sacroiliac Joint in Patients with Axial Spondyloarthritis Using Magnetic Resonance Image Analysis Based on Deep Learning. Diagnostics (Basel). 2021;11(7).

[2]Zheng Q, Liu W, Huang Y, Gao Z, Wu Y, Wang X, et al. Predictive Value of Active Sacroiliitis in MRI for Flare Among Chinese Patients with Axial Spondyloarthritis in Remission. Rheumatol Ther. 2021;8(1):411-24.

Acknowledgements

No conflict of interest

Disclosure of Interests

None declared

POS0962 CAN RADIOMICS REPLACE SPARCC SCORING SYSTEM IN EVALUATING BONE MARROW OEDEMA OF THE SACROILIAC JOINTS IN AXIAL SPONDYLOARTHRITIS?

Background

Bone marrow oedema (BMO) of the sacroiliac joints (SIJs) is evaluated to diagnose, classify and monitor disease activity in patients with axial spondyloarthritis (axSpA). Available quantitative methodologies rely on human visual assessment, and errors can’t be completely avoided. Radiomics can extract and select discriminative and quantified features from regions of interest (ROIs), making a more accurate and objective description of BMO.

Objectives

To develop a more objective and efficient method based on radiomics to evaluate BMO of the SIJs by magnetic resonance imaging (MRI) in patients with axSpA in comparison with Spondyloarthritis Research Consortium of Canada (SPARCC) scoring system.

Methods

From September 2013 to July 2021, 523 patients with axSpA underwent 3.0T SIJ-MRI were included, who were randomly classified as training cohort(n=367) and validation cohort(n=156). The optimal radiomics features, selected from the 3.0T SIJ-MRI in the training cohort, were included to build the radiomics model. Four clinical risk predictors were adopted to build the clinical model. The performance of the clinical and radiomics models was evaluated by ROC analysis and decision curve analysis (DCA). Rad-scores were calculated by the radiomics model and SPARCC scores were performed to quantify the BMO of SIJs. We also assessed the correlation between Rad-score and SPARCC score.

Results

The radiomics model, built by 15 optimal features, showed favorable discrimination about SPARCC score <2 or ≥2 both in the training (AUC, 0.91; 95% CI: 0.88-0.94) and the validation cohort (AUC, 0.89; 95% CI, 0.84-0.94). DCA confirmed that the radiomics model was clinically useful. Furthermore, Rad-score has significant correlation with SPARCC score for scoring the status of BMO (rs=0.78, P< 0.001), and moderation correlation for scoring the change (r=0.40, P=0.005).

Conclusion

The radiomics can accurately assess the BMO of the SIJs in axSpA, providing an alternative to SPARCC scoring system. There was a positive correlation between Rad-score and SPARCC score.

References

[1]van der Heijde D, Sieper J, Maksymowych WP, Lambert RG, Chen S, Hojnik M, et al. Clinical and MRI remission in patients with nonradiographic axial spondyloarthritis who received long-term open-label adalimumab treatment: 3-year results of the ABILITY-1 trial. Arthritis Res Ther. 2018;20(1):61.

[2]Landewé RB, Hermann KG, van der Heijde DM, Baraliakos X, Jurik AG, Lambert RG, et al. Scoring sacroiliac joints by magnetic resonance imaging. A multiple-reader reliability experiment. The Journal of rheumatology. 2005;32(10):2050-5.

[3]Cereser L, Zabotti A, Zancan G, Quartuccio L, Cicciò C, Giovannini I, et al. Magnetic resonance imaging assessment of ASAS-defined active sacroiliitis in patients with inflammatory back pain and suspected axial spondyloarthritis: a study of reliability. Clinical and experimental rheumatology. 2021.

[4]Maksymowych WP, Inman RD, Salonen D, Dhillon SS, Williams M, Stone M, et al. Spondyloarthritis research Consortium of Canada magnetic resonance imaging index for assessment of sacroiliac joint inflammation in ankylosing spondylitis. Arthritis Rheum. 2005;53(5):703-9.

[5]Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology. 2016;278(2):563-77.

Table 1.

Rad-scores corresponding to different SPARCC score intervals about the status of SIJ-BMO.

SPARCC scorenRad-scoreMean(sd)Median (iqr)Range0-1170-1.31(1.64)-1.39(2.16)-6.46, 2.352-61250.73(1.86)0.62(2.12)-3.08, 8.487-11552.25(1.80)2.36(1.79)-1.17, 8.3612-16432.65(2.14)2.66(3.21)-0.76, 7.3917-21383.31(2.05)3.25(2.88)-0.88, 7.5522-26263.08(1.55)3.38(2.12)-1.00, 5.3827-31253.77(1.36)3.77(1.59)0.40, 6.27>31414.10(1.51)4.32(2.28)1.00, 6.96

Disclosure of Interests

None declared

Halloysite-Based Nanorockets with Light-Enhanced Self-Propulsion for Efficient Water Remediation

Halloysite-based tubular nanorockets with chemical-/light-controlled self-propulsion and on-demand acceleration in velocity are reported. The nanorockets are fabricated by modifying halloysite nanotubes with nanoparticles of silver (Ag) and light-responsive α-Fe₂O₃ to prepare a composite of Ag-Fe₂O₃/HNTs. Compared to the traditional fabrication of tubular micro-/nanomotors, this strategy has merits in employing natural clay as substrates of an asymmetric tubular structure, of abundance, and of no complex instruments required. The velocity of self-propelled Ag-Fe₂O₃/HNTs nanorockets in fuel (3.0% H₂O₂) was ca. 1.7 times higher under the irradiation of visible light than that in darkness. Such light-enhanced propulsion can be wirelessly modulated by adjusting light intensity and H₂O₂ concentration. The highly repeatable and controlled "weak/strong" propulsion can be implemented by turning a light on and off. With the synergistic coupling of the photocatalysis of the Ag-Fe₂O₃ heterostructure and advanced oxidation in H₂O₂/visible light conditions, the Ag-Fe₂O₃/HNTs nanorockets achieve an enhanced performance of wastewater remediation. A test was done by the catalytic degradation of tetracycline hydrochloride. The light-enhanced propulsion is demonstrated to accelerate the degradation kinetics dramatically. All of these results illustrated that such motors can achieve efficient water remediation and open a new path for the photodegradation of organic pollutions.

Stoichiometric Control Synthesis of Pyrite and Greigite Particles Used for Photo-Fenton Degradation Catalysis

Two types of iron sulfide, i.e., highly crystalline pyrite (FeS2) and greigite (Fe3S4) were synthesized via hot-injection method only by changing the precursor ratios of iron to sulfur (Fe:S) from...

Universality of mesoporous coal gasification slag for reinforcement and deodorization in four common polymers

Mesoporous adsorbents and polymer deodorants are difficult to implement on a large scale because of their complicated preparation methods. Herein, a mesoporous adsorbent (CGSA) with a specific surface area of 564 m²g^-1and a pore volume of 0.807 cm³g^-1was prepared from solid waste coal gasification slag using a simple acid leaching process. The adsorption thermodynamics and adsorption kinetics results verified that the adsorption mechanism of propane on CGSA was mainly physisorption. Then the universality of CGSA in different polymers was investigated by introducing CGSA and its commercialized counterparts (CaCO₃, and zeolite) into four common polymers. When the filler content was 30 wt%, the average reinforcement effect of CGSA on the tensile, flexural, and impact strengths of the four polymers was 46.68%, 83.62%, and 211.90% higher than that of CaCO₃, respectively. Gas chromatography results also showed that CGSA significantly decreased total volatile organic compound emissions from the composites, and its optimal deodorization performance reached 69.58%, 81.33%, and 91.09% for different polymers, respectively, far exceeding that of zeolite. Therefore, this study showed that low-cost, high-performance, and multifunctional mesoporous polymer fillers with excellent universality can be manufactured from solid contaminants.

Prolonged-Photoresponse-Lifetime Ni2P Nanocrystalline with Highly Exposed (001) for Efficient Photoelectrocatalytic Hydrogen Evolution

Seeking highly efficient non-preference electrocatalytic materials that serve photoelectrochemical (PEC) water splitting in acidic systems is expectant in the context of environmentally friendly production. We designed Ni₂P electrocatalysts synthesized in oil phases via the hot-bubbling method with superb stability in air and sulfuric acid solution for PEC, which were found with excellent hydrogen evolution performance. A tunable particle size and highly exposed (001) planes of Ni₂P nanocrystals were achieved. The designed catalysts achieved a notable promotion in the hydrogen evolution reaction activity compared to that of Ni₂P synthesized in the water phase. More specifically, the electrode prepared by self-assembled Ni₂P nanoparticles was found to have decent over-potential of η₁₀ = 164 mV in darkness and was further decreased to 129 mV with irradiation of visible light. The cyclic stability tests manifested brilliant durability in 0.5 M H₂SO₄. Measurement of the transient photocurrent response and PEC water splitting catalytic performance indicated that the Ni₂P had high carrier concentration upon irradiation, lower carrier recombination probability, and prolonged photo-response lifetime (3.03-3.14 s).

Self-Propelled Nanojets for Fenton Catalysts Based on Halloysite with Embedded Pt and Outside-Grafted Fe3O4

Taking inspirations from nature, we endeavor to develop catalytically self-propelled nanojets from a type of tubular clay minerals, halloysite nanotubes (HNTs), and utilize them as catalysts targeted for catalysis where the traditional means of mechanical agitation cannot be implemented. Nanojets of Fe₃O₄@HNTs/Pt were prepared by impregnating platinum nanoparticles (Pt NPs) in lumens of HNTs and selective grafting of magnetite (Fe₃O₄) particles on the external surface. The HNT-based nanojets were validated to be highly suitable both in free bulk solution and in microfluidic flow. An example of Fenton degradation catalyzed by these jets was demonstrated. The powerful movement of Fe₃O₄@HNTs/Pt (368 ± 50 μm·s^-1) fueled by 5.0% wt. H₂O₂ was found to follow a bubble propulsion mechanism, and the motion exhibits collective behavior as swarms. The clay tubes were for the first time observed to self-assemble into fish-like aggregates during swimming, reflecting natural occurrence of motion-evolution philosophy. Guided motion was realized by employing magnetic manipulation which makes jets feasible for reactors with complex microchannels/reactors.

Fabrication of Pd/Mg2 P2 O7 via a Struvite-Template Way from Wastewater and Application as Chemoselective Catalyst in Hydrogenation of Nitroarenes

A highly efficient heterogeneous catalyst Pd/Mg₂ P₂ O₇ was fabricated by combining palladium nanoparticles (PdNPs) and mesoporous Mg₂ P₂ O₇ fibers/rods. Mg₂ P₂ O₇ fibers with ultra-high specific surface area were prepared from struvite as templates, which were synthesized from waste water containing N- and P-containing pollutants. This strategy provided a novel pathway for developing advanced catalysts from eutrophication-polluted water. The composite Pd/Mg₂ P₂ O₇ showed brilliant performance in selective hydrogenation of nitro aromatics to give anilines. As an example of nitrobenzene hydrogenation, the conversion to aniline and selectivity were found to reach almost 100 % at a temperature of T=90 °C and under a pressure of P H 2 =2.0 MPa. The superior performance was found to originate from PdNPs, which were boosted by electron transfer afforded by the nanofiber Mg₂ P₂ O₇ supports. The favorable adsorption of withdrawing groups (-NO₂ ) was realized by synergistic effects between Pd and oxygen vacancies provided by pyrolysis of struvite. The catalyst remained stable after cycles of reuse with little degradation in catalytic performance.

Separation of K2CO3 from Li+ Brine with Aid of CO2 and Trace of Metastable Quaternary System Li+–K+–CO3 2−–HCO3 −–H2O

It is of importance to reclaim single-salt of potash from Li+-type brines of low concentration. In this work the potassium salts KHCO3 was efficiently separated from the lithium carbonate-type brines with the aid of CO2 carbonation. The phase field was provided in which the precipitation of KHCO3 occurs and single-salt of potassium can be obtained. The low concentration of [Li+] was also successfully concentrated to a high level (8.1 g/L), and this concentration can be used as sources for Li+-salts production using pre-developed strategies, which looks forward wider applications of the lithium resources of natural brine. This state-of-art was traced via isotherm evaporation on the quaternary system of Li+–K+–CO3 2−–H2O at 298.15 K in which the carbonation steps were performed by CO2. Metastable phase diagram was found to consist of three invariant points, seven univariant curves, and four crystallization fields corresponding to Li2CO3, KHCO3, potassium carbonate sesquihydrate (K2CO3 ⋅ 3/2H2O), and a potassium carbonate and potassium bicarbonate double salt (K2CO3 ⋅ 2 KHCO3 ⋅ 1.5H2O). There was no crystallization field corresponding to LiHCO3. The pH-composition diagram and density-composition diagram were also plotted. This work was carried out in aim of extracting/separating single salts of alkali metals from carbonate-type brines of west China.

Highly Stable and Recyclable Sequestration of CO2 Using Supported Melamine on Layered-Chain Clay Mineral

A type of highly stable and recyclable clay-based composite was developed for sequestration of CO₂, which was synthesized by loading melamine (MEL) onto attapulgite (ATT) via a wet impregnation method. The synthesized materials were characterized by N₂ adsorption-desorption, Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TG), and transmission electron microscopy (TEM). By means of thermal and acidic treatments more active sites of ATT were exposed, and large surface areas were obtained. The MEL molecules were well combined with those exposed sites, which enhanced stability and cyclability for CO₂ sequestration. On the basis of CO₂ adsorption-desorption measurements, the composite of ATT-MEL was found to have a higher CO₂ adsorption capacity (4.91 cm³/g) which was much higher than that of CO₂ absorption on bare MEL (1.30 cm³/g) at 30 °C. After ten cycles of reusing, the composite exhibited even higher capacity for CO₂ adsorption by an increased percentage of 5.91% (30 °C) and 5.77% (70 °C) compared to the capacity in the first cycle. The reason lies in the strong interaction between melamine and attapulgite matrix which was further confirmed by DFT calculations. The MEL was validated to have advantages over aliphatic amines (TEPA) in modifying ATT to get high stability of CO₂-adsorbents.

Effective removal of aromatic pollutants via adsorption and photocatalysis of porous organic frameworks

PAF-45 with a wholly aromatic framework, intrinsic microporosity and π–π conjugation system shows excellent performance in aromatic pollutant removal. It exhibits a high adsorption capacity for the benzene series and moderate photocatalytic performance. As an adsorbent, PAF-45 can adsorb 35 wt% benzene and 68 wt% chlorobenzene in static adsorption experiments at room temperature and pressure. In benzene simulation wastewater, PAF-45 also shows excellent adsorption capacity, without significant reduction after 10 cycles of the adsorption–desorption process. Moreover, PAF-45 exhibits an impressive photocatalytic degradability of aromatic compounds, like aniline and phenol, under visible light illumination.

PAF-45 with a wholly aromatic framework, intrinsic microporosity and π–π conjugation system shows excellent performance in aromatic pollutant removal.

SAT0564 BONE TEXTURE ANALYSIS WITH DEEP LEARNING IN HAND RADIOGRAPHS FOR ASSESSING THE RISK OF RHEUMATOID ARTHRITIS

Background:

Conventional x-rays are essential to identify radiographic changes of rheumatoid arthritis (RA) in structure and bone texture. Limited evidence suggests that the bone texture analysis may quantify the radiographic changes in RA;1however, current techniques such as the fractal dimension characterize fixed texture features. Deep learning offers novel methods to ‘learn’ radiographic texture features relevant to RA.

Objectives:

To develop a deep learning model to assess the radiographic bone texture in the distal metacarpal bone relevant to RA.

Methods:

We collected 3,738 conventional hand radiographs from 2,128 individuals (RA, n = 908; non-RA, n = 1220). The second, third, and fourth metacarpal bone images were segmented using a curve Graph Convolutional Network (GCN), and the distal third was used as the input to train a texture model to classify RA. The texture model was based on the Deep Texture Encoding Network (Deep-TEN) architecture (figure 1),2which put an encoding layer on top of a pre-trained 18-layered residual network (ResNet18). The vectors produced by the model represent the orderless texture features that were used to generate a texture score for RA. Five texture models are trained using 5-fold cross-validation and are ensembled during inference by averaging the model outputs to produce the final score. We then validate the model using hand radiographs of 166 RA patients and 166 non-RA patients. Overall model performance was measured by area under the curve of the receiver operator curve (AUROC). Multivariate logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI) of RA.

Figure 1.

Schematic representation of deep learning models to extract and encode texture features for RA classification.

Results:

We included 140 women and 26 men with RA (mean age, 55.9±1.8 years) and 166 non-RA individuals (F: M, 140:26; mean age, 55.5 ± 1.8 years). The mean texture score was 0.49 (95% CI, 0.48–0.50) in RA patients, which is significantly higher than non-RA patients (0.42, 95% CI, 0.40–0.43; p<0.01). The AUROC of the model was 0.68. In the multivariate logistic regression model, a high texture score (>0.43) is associated with an OR (95% CI) of 3.42 (2.48–4.72) for RA, adjusted by age and sex.

Conclusion:

This study indicates that the texture model can delineate radiographic changes in texture relevant to RA and, coupled with automatic joint detection and segmentation, it has the potential to aid early RA diagnosis and monitor radiographic progression.

References:

[1]Zandieh S, Haller J, Bernt R, et al. Fractal analysis of subchondral bone changes of the hand in rheumatoid arthritis. Medicine (Baltimore) 2017;96(11):e6344.

[2]Zhang H, Xue J, Dana K. Deep TEN: Texture Encoding Network. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017:708-17.

Disclosure of Interests:

None declared

OP0301 PREDICTION OF LOW BONE MINERAL DENSITY AND FRAX SCORE BY ASSESSING HIP BONE TEXTURE WITH DEEP LEARNING

Background:

Osteoporosis is a widespread health concern associated with an increased risk of fractures in individuals with low bone mineral density (BMD). Dual-energy x-ray absorptiometry (DXA) is the gold standard to measure BMD, but methods based on the assessment of plain films, such as the digital radiogrammetry,1are also available. We describe a novel approach based on the assessment of hip texture with deep learning to estimate BMD.

Objectives:

To compare the BMD estimated by assessing hip texture using a deep learning model and that measured by DXA.

Methods:

In this study, we identified 1,203 patients who underwent DXA of left hip and hip plain film within six months. The dataset was split into a training set with 1,024 patients and a testing set with 179 patients. Hip images were obtained and regions of interest (ROI) around left hips were segmented using a tool based on the curve Graph Convolutional Network. The ROIs are processed using a Deep Texture Encoding Network (Deep-TEN) model,2which comprises the first 3 blocks of Residual Network with 18 layers (ResNet-18) model followed by a dictionary encoding operator (Figure 1). The encoded features are processed using a fully connected layer to estimate BMD. Five-fold cross-validation was conducted. Pearson’s correlation coefficient was used to assess the correlation between predicted and reference BMD. We also test the performance of the model to identify osteoporosis (T-score ≤ -2.5)

Figure 1.

Schematic representation of deep learning models to extract and encode texture features for estimation of hip bone density.

Results:

We included 151 women and 18 men in the testing dataset (mean age, 66.1 ± 1.7 years). The mean predicted BMD was 0.724 g/cm2compared with the mean BMD measured by DXA of 0.725 g/cm2(p = 0.51). Pearson’s correlation coefficient between predicted and true BMD was 0.88. The performance of the model to detect osteoporosis/osteopenia was shown in Table 1. The positive predictive value was 87.46% for a T-score ≤ -1 and 83.3% for a T-score ≤ -2.5. Furthermore, the mean FRAX® 10-year major fracture risk did not differ significantly between scores based on predicted (6.86%) and measured BMD (7.67%, p=0.52). The 10-year probability of hip fracture was lower in the predicted score (1.79%) than the measured score (2.43%, p = 0.01).

Table 1.

Performance matrices of the deep texture model to detect osteoporosis/osteopenia

T-score ≤ -1T-score ≤ -2.5Sensitivity91.11%(95% CI, 83.23% to 96.08%)33.33%(95% CI, 17.29% to 52.81%)Specificity86.08%(95% CI, 76.45% to 92.84%)98.56%(95% CI, 94.90% to 99.83%)Positive predictive value88.17%(95% CI, 81.10% to 92.83%)83.33%(95% CI, 53.58% to 95.59%)Negative predictive value89.47%(95% CI, 81.35% to 94.31%)87.26%(95% CI, 84.16% to 89.83%)

Conclusion:

This study demonstrates the potential of the bone texture model to detect osteoporosis and to predict the FRAX score using plain hip radiographs.

References:

[1]Zandieh S, Haller J, Bernt R, et al. Fractal analysis of subchondral bone changes of the hand in rheumatoid arthritis. Medicine (Baltimore) 2017;96(11):e6344.

[2]Zhang H, Xue J, Dana K. Deep TEN: Texture Encoding Network. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017:708-17.

Disclosure of Interests:

None declared

OP0062 PREDICTIVE VALUE OF BONE TEXTURE FEATURES EXTRACTED BY DEEP LEARNING MODELS FOR THE DETECTION OF OSTEOARTHRITIS: DATA FROM THE OSTEOARTHRITIS INITIATIVE

Background:

Osteoarthritis is a degenerative disorder characterized by radiographic features of asymmetric loss of joint space, subchondral sclerosis, and osteophyte formation. Conventional plain films are essential to detect structural changes in osteoarthritis. Recent evidence suggests that fractal- and entropy-based bone texture parameters may improve the prediction of radiographic osteoarthritis.1In contrast to the fixed texture features, deep learning models allow the comprehensive texture feature extraction and recognition relevant to osteoarthritis.

Objectives:

To assess the predictive value of deep learning-extracted bone texture features in the detection of radiographic osteoarthritis.

Methods:

We used data from the Osteoarthritis Initiative, which is a longitudinal study with 4,796 patients followed up and assessed for osteoarthritis. We used a training set of 25,978 images from 3,086 patients to develop the textual model. We use the BoneFinder software2to do the segmentation of distal femur and proximal tibia. We used the Deep Texture Encoding Network (Deep-TEN)3to encode the bone texture features into a vector, which is fed to a 5-way linear classifier for Kellgren and Lawrence grading for osteoarthritis classification. We also developed a Residual Network with 18 layers (ResNet18) for comparison since it deals with contours as well. Spearman’s correlation coefficient was used to assess the correlation between predicted and reference KL grades. We also test the performance of the model to identify osteoarthritis (KL grade≥2).

Results:

We obtained 6,490 knee radiographs from 446 female and 326 male patients who were not in the training sets to validate the performance of the models. The distribution of the KL grades in the training and testing sets were shown in Table 1. The Spearman’s correlation coefficient was 0.60 for the Deep-TEN and 0.67 for the ResNet18 model. Table 2 shows the performance of the models to detect osteoarthritis. The positive predictive value for Deep-TEN and ResNet18 model classification for OA was 81.37% and 87.46%, respectively.

Table 1

Distribution of KL grades in the training and testing sets.

KL grades01234TotalTraining set1089341.9%458218.7%611423.5%332012.8%7993.1%25,978Testing set247238.1%135320.8%169626.1%77511.9%1943.0%6,490Table 2

Performance matrices of the Deep-Ten and ResNet18 models to detect osteoarthritis

Deep-TENResNet18Sensitivity62.29%(95% CI, 60.42%–64.13%)59.14%(95% CI, 57.24%–61.01%)Specificity90.07%(95% CI, 89.07%–91.00%)94.09%(95% CI, 93.30%–94.82%)Positive predictive value81.37%(95% CI, 79.81%–82.84%)87.46%(95% CI, 85.96%–88.82%)Negative predictive value77.42%(95% CI, 77.64%–79.65%)76.77%(95% CI, 75.93%–77.59%)

Conclusion:

This study demonstrates that the bone texture model performs reasonably well to detect radiographic osteoarthritis with a similar performance to the bone contour model.

References:

[1]Bertalan Z, Ljuhar R, Norman B, et al. Combining fractal- and entropy-based bone texture analysis for the prediction of osteoarthritis: data from the multicenter osteoarthritis study (MOST). Osteoarthritis Cartilage 2018;26:S49.

[2]Lindner C, Wang CW, Huang CT, et al. Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms. Sci Rep 2016;6:33581.

[3]Zhang H, Xue J, Dana K. Deep TEN: Texture Encoding Network. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017:708-17.

Disclosure of Interests:

None declared

Flexible Multifunctional Porous Nanofibrous Membranes for High-Efficiency Air Filtration

Particulate matter (PM) discharged along with the rapid industrialization and urbanization hazardously threatens ecosystems and human health. Membrane-based filtration technology has been proved to be an effective approach to capture PM from the polluted air. However, the fabrication of filtration membranes with excellent reusability and antibacterial activity has rarely been reported. Herein, the flexible multifunctional porous nanofibrous membranes were fabricated by embedding Ag nanoparticles into the electrospun porous SiO₂-TiO₂ nanofibers via an impregnation method, which integrated the abilities of PM filtration and antibacterial performance. Compared with the reported air filters, the resultant membrane (Ag@STPNM) with high surface polarity and porous structure possessed the low density, high removal efficiency, and small pressure drop. For instance, the removal efficiency and the pressure drop of Ag@STPNM with a basis weight of only 3.9 g m^-2 for PM_2.5 reached 98.84% and 59 Pa, respectively. In terms of the excellent thermal stability of Ag@STPNM, the adsorbed PM could be removed simply by a calcination process. The filtration performance of Ag@STPNM kept stable during five purification-regeneration cycles and the long-time filtration for 12 h, exhibiting excellent recyclability and durability. Furthermore, the embedded Ag nanoparticles could achieve the effective resistance to the breeding of bacteria on Ag@STPNM, giving the bacteriostatic rate of 95.8%. Therefore, Ag@STPNM holds promising potentials as a highly efficient, reusable, and antibacterial air filter in the practical purification of the indoor environment or personal air.

Amino-Functionalized Porous Nanofibrous Membranes for Simultaneous Removal of Oil and Heavy-Metal Ions from Wastewater

Both oil spill and heavy-metal ions in the industrial wastewater cause severe problems for aquatic ecosystem and human health. In the present work, the electrospun superamphiphilic SiO₂-TiO₂ porous nanofibrous membranes (STPNMs) comprised of intrafiber mesopores and interfiber macropores are modified by an amino-silanization reaction, which affords the membrane (ASTPNMs) the ability to simultaneously remove the oil contaminants and the water-soluble heavy-metal ions from wastewater. The underwater superoleophobicity of ASTPNMs facilitates the highly efficient separation of water and various oils, even emulsifier-stabilized emulsion. Meanwhile, an optimal modification time (15 min, ASTPNM-15) is important for maintaining the under-oil superhydrophilicity of the membrane, based on which the oil contaminant in membrane can be easily cleaned by water alone, showing excellent self-cleaning performance. The adsorption of Pb²⁺ over ASTPNM-15 reaches equilibrium at around 20 min, and the monolayer adsorption capacity is 142.86 mg g^-1 at pH = 5 at 20 °C. In the breakthrough processes, the permeation volume of ASTPNM-15 for the purification of Pb²⁺ (5 ppm, pH = 5) reaches 160 mL when the concentration of Pb²⁺ in the filtrate increases to 0.05 ppm. The separation efficiencies of ASTPNM-15 for simulated wastewater containing both oil spill and various heavy-metal ions (Pb²⁺, Cr³⁺, Ni²⁺) are larger than 99.5%. In addition, the separation capacity keeps stable over five purification-regeneration cycles without obvious decrease, proving excellent recyclability and reusability of ASTPNM-15 for practical applications.

Extraction of K2CO3 from Low Concentration [K+] Solutions with the Aid of CO2: A Study on the Metastable Phase Equilibrium of K2CO3-Na2CO3-H2O Ternary System

Food grade (K2CO3 wt.%>99.0%, GB/T 25588-2010) potassium carbonate (K2CO3) has been extracted from low concentration [K+] solutions of K2CO3-Na2CO3-H2O, which refers to a subsystem of brine water in the Lop Nor Lake in West China. Procedures of the isothermal evaporation, crystallization, CO2 acidification, filtration, and calcination were employed to prepare the K2CO3. This research focuses on the phase study of metastable equilibria between K2CO3-Na2CO3-H2O and KHCO3-NaHCO3-H2O. The solubility, density, conductivity, and pH values were determined. Phase diagrams were plotted at temperatures of 298.2 and 313.2 K. At 298.2 K the ternary system of K2CO3-Na2CO3-H2O was found to have double salts in form of solid solutions Na2CO3·K2CO3·(6–12)H2O, which would hinder the process of getting pure K2CO3 by the means of isothermal evaporation. In this protocol the high-pressure CO2 was charged to the ternary carbonate solution, and the K2CO3-Na2CO3-H2O was moved to bicarbonate system KHCO3-NaHCO3-H2O. This quaternary system is of a simple co-saturation type of diagram, in which a solid solution (KHCO3·NaHCO3) was found to be greatly affected by temperatures. This finding affords efficient separation of KHCO3 from the KHCO3-NaHCO3-H2O solutions.

Microtubular Fuel Cell with Ultrahigh Power Output per Footprint

A novel realization of microtubular direct methanol fuel cells (µDMFC) with ultrahigh power output is reported by using "rolled-up" nanotechnology. The microtube (Pt-RuO₂ -RUMT) is prepared by rolling up Ru₂ O layers coated with magnetron-sputtered Pt nanoparticles (cat-NPs). The µDMFC is fabricated by embedding the tube in a fluidic cell. The footprint of per tube is as small as 1.5 × 10^-4 cm² . A power density of ≈257 mW cm^-2 is obtained, which is three orders of magnitude higher than the present microsized DFMCs. Atomic layer deposition technique is applied to alleviate the methanol crossover as well as improve stability of the tube, sustaining electrolyte flow for days. A laminar flow driven mechanism is proposed, and the kinetics of the fuel oxidation depends on a linear-diffusion-controlled process. The electrocatalytic performance on anode and cathode is studied by scanning both sides of the tube wall as an ex situ working electrode, respectively. This prototype µDFMC is extremely interesting for integration with micro- and nanoelectronics systems.

Scatter to volume registration for model-free respiratory motion estimation from dynamic MRIs

Respiratory motion is one major complicating factor in many image acquisition applications and image-guided interventions. Existing respiratory motion estimation and compensation methods typically rely on breathing motion models learned from certain training data, and therefore may not be able to effectively handle intra-subject and/or inter-subject variations of respiratory motion. In this paper, we propose a respiratory motion compensation framework that directly recovers motion fields from sparsely spaced and efficiently acquired dynamic 2-D MRIs without using a learned respiratory motion model. We present a scatter-to-volume deformable registration algorithm to register dynamic 2-D MRIs with a static 3-D MRI to recover dense deformation fields. Practical considerations and approximations are provided to solve the scatter-to-volume registration problem efficiently. The performance of the proposed method was investigated on both synthetic and real MRI datasets, and the results showed significant improvements over the state-of-art respiratory motion modeling methods. We also demonstrated a potential application of the proposed method on MRI-based motion corrected PET imaging using hybrid PET/MRI.

Real-time 6DoF pose recovery from X-ray images using library-based DRR and hybrid optimization

PURPOSE

Real-time 6 degrees of freedom (6DoF) pose recovery and tracking from X-ray images is a key enabling technology for many interventional imaging applications. However, real-time 2D/3D registration is a very challenging problem because of the heavy computation in iterative digitally reconstructed radiograph (DRR) generation. In this paper, we propose a real-time 2D/3D registration framework using library-based DRRs to achieve high computational efficiency.

METHOD

The proposed method pre-computes a library of canonical DRRs and reconstructs library-based DRRs (libDRRs) during registration without online rendering. The transformation parameters are decoupled to 2 geometry-relevant and 4 geometry-irrelevant ones so that canonical DRRs only need to cover the variation of 2 geometry-relevant parameters, making it practical to be pre-computed and stored. The 2D/3D registration using libDRRs is then solved as a hybrid optimization problem, i.e., continuous in geometry-irrelevant parameters while discrete in geometry-relevant parameters.

RESULTS

On 5 fluoroscopic sequences with 246 frames acquired during animal studies with a transesophageal echocardiography (TEE) probe in the field of view, 6DoF tracking of the TEE probe using the proposed method achieved a mean target registration error in the projection direction (mTREproj) of 0.81 mm, a success rate of 100 % (defined as mTREproj [Formula: see text]2.5 mm), and a registration frame rate of 23.1 fps on a pure CPU-based implementation executed in a single thread.

CONCLUSION

Using libDRRs with a hybrid optimization can significantly improve the computational efficiency (up to tenfold) for 6DoF pose recovery and tracking with little degradation in robustness and accuracy, compared to conventional intensity-based 2D/3D registration using ray casting DRRs with a continuous optimization.

High Efficiency Dye-sensitized Solar Cells Constructed with Composites of TiO2 and the Hot-bubbling Synthesized Ultra-Small SnO2 Nanocrystals

An efficient photo-anode for the dye-sensitized solar cells (DSSCs) should have features of high loading of dye molecules, favorable band alignments and good efficiency in electron transport. Herein, the 3.4 nm-sized SnO₂ nanocrystals (NCs) of high crystallinity, synthesized via the hot-bubbling method, were incorporated with the commercial TiO₂ (P25) particles to fabricate the photo-anodes. The optimal percentage of the doped SnO₂ NCs was found at ~7.5% (SnO₂/TiO₂, w/w), and the fabricated DSSC delivers a power conversion efficiency up to 6.7%, which is 1.52 times of the P25 based DSSCs. The ultra-small SnO₂ NCs offer three benefits, (1) the incorporation of SnO₂ NCs enlarges surface areas of the photo-anode films, and higher dye-loading amounts were achieved; (2) the high charge mobility provided by SnO₂ was confirmed to accelerate the electron transport, and the photo-electron recombination was suppressed by the highly-crystallized NCs; (3) the conduction band minimum (CBM) of the SnO₂ NCs was uplifted due to the quantum size effects, and this was found to alleviate the decrement in the open-circuit voltage. This work highlights great contributions of the SnO₂ NCs to the improvement of the photovoltaic performances in the DSSCs.

Extraordinary high ductility/strength of the interface designed bulk W-ZrC alloy plate at relatively low temperature

The refractory tungsten alloys with high ductility/strength/plasticity are highly desirable for a wide range of critical applications. Here we report an interface design strategy that achieves 8.5 mm thick W-0.5 wt. %ZrC alloy plates with a flexural strength of 2.5 GPa and a strain of 3% at room temperature (RT) and ductile-to-brittle transition temperature of about 100 °C. The tensile strength is about 991 MPa at RT and 582 MPa at 500 °C, as well as total elongation is about 1.1% at RT and as large as 41% at 500 °C, respectively. In addition, the W-ZrC alloy plate can sustain 3.3 MJ/m² thermal load without any cracks. This processing route offers the special coherent interfaces of grain/phase boundaries (GB/PBs) and the diminishing O impurity at GBs, which significantly strengthens GB/PBs and thereby enhances the ductility/strength/plasticity of W alloy. The design thought can be used in the future to prepare new alloys with higher ductility/strength.

INHIBITORY EFFECT OF TETRAMETHYLPYRAZINE ON HEPATOCELLULAR CARCINOMA: POSSIBLE ROLE OF APOPTOSIS AND CELL CYCLE ARREST

Hepatocellular carcinoma (HCC) is the fifth most common cancer. An important approach to control HCC is chemoprevention. This study aims at investigating the antitumor effect of Tetramethylpyrazine (TMP). Rats were injected with N-Nitrosodiethylamine (DEN) to establish HCC. Tumor development was observed. Liver function was evaluated. Apoptosis and cell cycle arrest-related makers and signaling cascades were determined by Western blot, RT-PCR and flow cytometric analysis. The administration of TMP could significantly inhibit tumor development in DEN-induced HCC rats, shown by reduced incidence of tumor, decreased number of tumor nodules and reduced maximal size of tumor. DEN-induced increase of aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase and alkaline phosphatase activities were significantly inhibited by TMP. TMP exhibited inhibitory effect on HCC through induction of apoptosis and cell cycle arrest in rats. TMP induced apoptosis through increasing Bax, decreasing Bcl-2, increasing the release of cytochrome c, and activating caspase, which consisted of the mitochondrial apoptotic pathway. TMP induced G2/M cell cycle arrest through down-regulation of cyclin B1/cdc2. In addition, inhibition of Akt and ERK signaling and the antioxidant activities of TMP may also contribute to its antitumor effect. These data provide new insight into the mechanisms underlying the antitumor effect of TMP.