A C-type lectin (CTL2) mediated both humoral and cellular immunity against bacterial infection in Tribolium castaneum

C-type lectins (CTLs) play essential roles in humoral and cellular immune responses of invertebrates. Previous studies have demonstrated the involvement of CTLs in the humoral immunity of Tribolium castaneum, a worldwide pest in stored products. However, the function of CTLs in cellular immunity remains unclear. Here, we identified a CTL gene located on chromosome X and designated it as CTL2 (TcCTL2) from T. castaneum. It encodes a protein of 305 amino acids with a secretion signal peptide and a carbohydrate-recognition domain. TcCTL2 was mainly expressed in the early pupae and primarily distributed in the hemocytes in the late larvae. It was significantly upregulated after larvae were infected with Escherichia coli or Staphylococcus aureus, while knockdown of TcCTL2 exacerbates larval mortality and bacterial colonization after infection. The purified recombinant TcCTL2 (rTcCTL2) can bind to pathogen-associated molecular patterns and microbes and promote hemocyte-mediated encapsulation, melanization and phagocytosis in vitro. rTcCTL2 also induced bacterial agglutination in a Ca2+-dependent manner. Knockdown of TcCTL2 drastically suppressed encapsulation, melanization, and phagocytosis. Furthermore, silencing of TcCTL2 followed by bacterial infection significantly decreased the expression of transcription factors in Toll and IMD pathways, antimicrobial peptides, and prophenoloxidases and phenoloxidase activity. These results unveiled that TcCTL2 mediates both humoral and cellular immunity to promote bacterial clearance and protect T. castaneum from infectious microbes, which will deepen the understanding of the interaction between CTLs and innate immunity in T. castaneum and permit the optimization of pest control strategies by a combination of RNAi technology and bacterial infection.

Harnessing the Potential of Chitosan and Its Derivatives for Enhanced Functionalities in Food Applications

As one of the most abundant natural polysaccharides that possess good biological activity, chitosan is extracted from chitin. Its application in the food field is being increasingly valued. However, chitosan extraction is difficult, and its poor solubility limits its application. At present, the extraction methods include the acid-base method, new chemical methods, and biological methods. The extraction rates of chitin/chitosan are 4-55%, 13-14%, and 15-28%, respectively. Different chemical modifications have different effects on chitosan, making it applicable in different fields. This article reviews and compares the extraction and chemical modification methods of chitosan, emphasizing the importance of green extraction methods. Finally, the application prospects of chitosan in the food industry are discussed. This will promote the understanding of the advantages and disadvantages of different extraction methods for chitosan as well as the relationship between modification and application, providing valuable insights for the future development of chitosan.

The serine/threonine kinase Akt gene affects fecundity by reducing Juvenile hormone synthesis in Liposcelis entomophila (Enderlein)

The serine/threonine kinase Akt is an important component of the insulin signalling pathway (ISP) in regulating insect metabolism, growth, and reproduction. The psocid Liposcelis entomophila (Enderlein) is a distasteful stored products pest for its fecundity. However, the molecular mechanism of Akt that controls vitellogenesis and oviposition in L. entomophila remains obscure. In this study, the function of the Akt gene in the female reproduction of L. entomophila (designated as LeAkt) was characterized and investigated. LeAkt contains a 1587 bp open reading frame encoding a 529 amino acid protein that possesses a conserved Pleckstrin Homology domain (PH) and a Ser/Thr-type protein kinase (S_TKc) domain. The mRNA expression of LeAkt was the highest in female adult stages and peaked for 7-day female adults. In female adult tissues, LeAkt was highly expressed in the head and the ovary, indicating that LeAkt was closely correlated with female ovarian development. LeAkt transcription level was significantly suppressed by oral feeding on artificial diets mixed with dsRNA-LeAkt. RNAi-mediated silencing of LeAkt led to a severe inhibition of vitellogenein (Vg) expression and ovarian development, together with lower fecundity and hatchability compared to that of the normal feeding group, suggesting a critical role for LeAkt in L. entomophila reproduction. Further studies revealed that LeAkt silencing significantly decreased the mRNA levels of several signalling and biosynthetic genes in the juvenile hormone (JH) signalling pathway, such as methoprene-tolerant (LeMet), krüppel homolog 1 (LeKr-h1) and JH methyltransferase (LeJHAMT), leading to a severe inhibition of JH biosynthesis in L. entomophila female adults. These results suggested that LeAkt was affecting JH synthesis, thereby influencing Vg synthesis and ultimately L. entomophila reproduction.

A meta-analysis of GFR slope as a surrogate endpoint for kidney failure

Glomerular filtration rate (GFR) decline is causally associated with kidney failure and is a candidate surrogate endpoint for clinical trials of chronic kidney disease (CKD) progression. Analyses across a diverse spectrum of interventions and populations is required for acceptance of GFR decline as an endpoint. In an analysis of individual participant data, for each of 66 studies (total of 186,312 participants), we estimated treatment effects on the total GFR slope, computed from baseline to 3 years, and chronic slope, starting at 3 months after randomization, and on the clinical endpoint (doubling of serum creatinine, GFR < 15 ml min-1 per 1.73 m2 or kidney failure with replacement therapy). We used a Bayesian mixed-effects meta-regression model to relate treatment effects on GFR slope with those on the clinical endpoint across all studies and by disease groups (diabetes, glomerular diseases, CKD or cardiovascular diseases). Treatment effects on the clinical endpoint were strongly associated with treatment effects on total slope (median coefficient of determination (R2) = 0.97 (95% Bayesian credible interval (BCI) 0.82-1.00)) and moderately associated with those on chronic slope (R2 = 0.55 (95% BCI 0.25-0.77)). There was no evidence of heterogeneity across disease. Our results support the use of total slope as a primary endpoint for clinical trials of CKD progression.

Social Determinants of Health and Their Impact on the Black Race Coefficient in Serum Creatinine-Based Estimation of GFR: Secondary Analysis of MDRD and CRIC Studies

BACKGROUND

The cause for differences in serum creatinine between Black and non-Black individuals incorporated into prior GFR-estimating equations is not understood. We explored whether social determinants of health can account for this difference.

METHODS

We conducted a secondary analysis of baseline data of the Modification of Diet in Renal Disease and Chronic Renal Insufficiency Cohort studies ( N =1628 and 1423, respectively). Data in both study cohorts were stratified by race (Black versus non-Black). We first evaluated the extent to which the coefficient of Black race in estimating GFR from creatinine is explained by correlations of race with social determinants of health and non-GFR determinants of creatinine. Second, we evaluated whether the difference between race groups in adjusted mean creatinine can be explained by social determinants of health and non-GFR determinants of creatinine.

RESULTS

In models regressing measured GFR on creatinine, age, sex, and race, the coefficient for Black race was 21% (95% confidence interval, 0.176 to 0.245) in Modification of Diet in Renal Disease and 13% (95% confidence interval, 0.097 to 0.155) in the Chronic Renal Insufficiency Cohort and was not attenuated by the addition of social determinants of health, alone or in combination. In both studies, the coefficient for Black race was larger at lower versus higher income levels. In models, regressing creatinine on measured GFR, age, and sex, mean creatinine was higher in Black versus non-Black participants in both studies, with no effect of social determinants of health.

CONCLUSIONS

Adjustment for selected social determinants of health did not influence the relationship between Black race and creatinine-based estimated GFR.

Geriatric Syndromes and Health-Related Quality of Life in Older Adults with Chronic Kidney Disease

Key Points

In older adults with CKD, geriatric syndromes are common and are associated with reduced quality of life. Addressing geriatric syndromes could potentially improve quality of life for older adults with CKD.

Background

Geriatric syndromes, which are multifactorial conditions common in older adults, predict health-related quality of life (HRQOL). Although CKD is associated with lower HRQOL, whether geriatric syndromes contribute to HRQOL in CKD is unknown. Our objective was to compare associations of geriatric syndromes and medical conditions with HRQOL in older adults with CKD.

Methods

This was a secondary analysis of a parallel-group randomized controlled clinical trial evaluating a 12-month exercise intervention in persons 55 years or older with CKD stage 3b–4. Participants were assessed for baseline geriatric syndromes (cognitive impairment, poor appetite, dizziness, fatigue, and chronic pain) and medical conditions (diabetes, hypertension, coronary artery disease, cancer, or chronic obstructive pulmonary disease). Participants' HRQOL was assessed with the Short Form Health Survey-36 (SF-36), EuroQol 5-Dimensions 5-Level, and the EuroQol Visual Analogue Scale. We examined the cross-sectional and longitudinal associations of geriatric syndromes and medical conditions with HRQOL using multiple linear regression.

Results

Among 99 participants, the mean age was 68.0 years, 25% were female, and 62% were Black. Participants had a baseline mean of 2.0 geriatric syndromes and 2.1 medical conditions; 49% had ≥ two geriatric syndromes and ≥ two medical conditions concurrently. Sixty-seven (68%) participants underwent 12-month assessments. In models using geriatric syndromes and medical conditions as concurrent exposures, the number of geriatric syndromes was cross-sectionally associated with SF-36 scores for general health (β =−0.385) and role limitations because of physical health (β =−0.374) and physical functioning (β =−0.300, all P <0.05). The number of medical conditions was only associated with SF-36 score for role limitations because of physical health (β =−0.205).

Conclusions

In older adults with CKD stage 3b–4, geriatric syndromes are common and are associated with lower HRQOL. Addressing geriatric conditions is a potential approach to improve HRQOL for older adults with CKD.

Clinical Trial registry name and registration number:

NCT01462097 ; Registration Date–October 26, 2011.

A Novel Creatinine Muscle Index Based on Creatinine Filtration: Associations with Frailty and Mortality

SIGNIFICANCE STATEMENT

Low muscle mass is related to frailty and increased mortality in older adults. However, muscle mass is not easily assessed in routine clinical practice. This paper describes a novel creatinine muscle index (CMI) on the basis of serum creatinine and cystatin C. CMI was moderately associated with frailty among older adults. A significantly higher proportion of individuals with weak grip strength were in the lowest tertile of CMI. The index was also associated with mortality. These results are consistent with the hypothesis that creatinine filtration may be an index of muscle mass, which may have utility in clinical practice.

BACKGROUND

Low muscle mass is related to frailty and increased mortality in older adults. However, muscle mass is not easily assessed in routine clinical practice.

METHODS

This study describes a novel creatinine muscle index (CMI) on the basis of serum creatinine and cystatin C in a community-based sample of older adults from the Atherosclerosis Risk in Communities Study. Analyses included 4639 participants who attended visit 5 (2011-2013) and 12,786 participants who attended visit 2 (1990-1992). CMI was defined as creatinine filtration (the product of serum creatinine times eGFR on the basis of cystatin C) and was analyzed in sex-specific tertiles. Cross-sectional associations of CMI with a frailty trichotomy, defined by the number (robust [0]/prefrail [1-2]/frail [3-5]) of five frailty components (weight loss, slowness, exhaustion, weakness, and low physical activity), were studied using polychotomous logistic regression and binary logistic regression with each frailty component. Cox regression was used to estimate associations of CMI at visit 5 and visit 2 with mortality. Models were adjusted for demographics, clinical variables, and comorbid conditions.

RESULTS

CMI (tertile 1 versus 3) was moderately associated with frailty (visit 5: adjusted odds ratio 4.23 [95% confidence interval (CI), 2.02 to 8.87] in men and 2.34 [95% CI, 1.41 to 3.89] in women) and with mortality (visit 5: adjusted hazard ratio 1.45 [95% CI, 1.08 to 1.94] in men and 1.55 [95% CI, 1.13 to 2.12] in women; similar results were seen at visit 2).

CONCLUSION

Lower CMI was associated with frailty and increased mortality, two clinical outcomes known to be associated with decreased muscle mass. Creatinine filtration may be an index of muscle mass and have utility in clinical practice, particularly at low levels.

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.

Effect of Long-term Exercise Training on Physical Performance and Cardiorespiratory Function in Adults With CKD: A Randomized Controlled Trial

RATIONALE & OBJECTIVE

The safety and efficacy of long-term exercise training in reducing physical functional loss in older adults with advanced CKD and comorbidity is uncertain.

STUDY DESIGN

Multicenter, parallel group, randomized controlled trial.

SETTINGS & PARTICIPANTS

Adults 55 years and older with estimated glomerular filtration rate (eGFR) of 15 to <45 mL/min/1.73 m2 enrolled from centers in Baltimore and Boston.

INTERVENTION

Twelve months of in-center supervised exercise training incorporating majority aerobic but also muscle strengthening activities or a group health education control intervention, randomly assigned in 1:1 ratio.

OUTCOME

Primary outcomes were cardiorespiratory fitness and submaximal gait at 6 and 12 months quantified by peak oxygen consumption (Vo2peak) on graded exercise treadmill test and distance walked on the 6-minute walk test, respectively. Secondary outcomes were changes in lower extremity function, eGFR, albuminuria, glycemia, blood pressure, and body mass index.

RESULTS

Among 99 participants, the mean age was 68 years, 62% were African American, and the mean eGFR was 33 mL/min/1.73 m2; 59% had diabetes, and 29% had coronary artery disease. Among those randomized to exercise, 59% of exercise sessions were attended in the initial 6 months. Exercise was well tolerated without excess occurrence of adverse events. At 6 months, aerobic capacity was higher among exercise participants (17.9 ± 5.5 vs 15.9 ± 7.0 mL/kg/min, P = 0.03), but the differences were not sustained at 12 months. The 6-minute walk distance improved more in the exercise group (adjusted difference: 98 feet [P = 0.02; P = 0.03 for treatment-by-time interaction]). The exercise group had greater improvements on the Timed Up and Go Test (P = 0.04) but not the Short Physical Performance Battery (P = 0.8).

LIMITATIONS

Planned sample size was not reached. Loss to follow-up and dropout were greater than anticipated.

CONCLUSIONS

Among adults aged ≥55 years with CKD stages 3b-4 and a high level of medical comorbidity, a 12-month program of in-center aerobic and resistance exercise training was safe and associated with improvements in physical functioning.

FUNDING

Government grants (National Institutes of Health).

TRIAL REGISTRATION

Registered at ClinicalTrials.gov with study number NCT01462097.

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

Acute Treatment Effects on GFR in Randomized Clinical Trials of Kidney Disease Progression

BACKGROUND

Acute changes in GFR can occur after initiation of interventions targeting progression of CKD. These acute changes complicate the interpretation of long-term treatment effects.

METHODS

To assess the magnitude and consistency of acute effects in randomized clinical trials and explore factors that might affect them, we performed a meta-analysis of 53 randomized clinical trials for CKD progression, enrolling 56,413 participants with at least one estimated GFR measurement by 6 months after randomization. We defined acute treatment effects as the mean difference in GFR slope from baseline to 3 months between randomized groups. We performed univariable and multivariable metaregression to assess the effect of intervention type, disease state, baseline GFR, and albuminuria on the magnitude of acute effects.

RESULTS

The mean acute effect across all studies was -0.21 ml/min per 1.73 m2 (95% confidence interval, -0.63 to 0.22) over 3 months, with substantial heterogeneity across interventions (95% coverage interval across studies, -2.50 to +2.08 ml/min per 1.73 m2). We observed negative average acute effects in renin angiotensin system blockade, BP lowering, and sodium-glucose cotransporter 2 inhibitor trials, and positive acute effects in trials of immunosuppressive agents. Larger negative acute effects were observed in trials with a higher mean baseline GFR.

CONCLUSION

The magnitude and consistency of acute GFR effects vary across different interventions, and are larger at higher baseline GFR. Understanding the nature and magnitude of acute effects can help inform the optimal design of randomized clinical trials evaluating disease progression in CKD.

A prospective cross-sectional study estimated glomerular filtration rate from creatinine and cystatin C in adults with solid tumors

Current guidelines recommend estimating glomerular filtration rate (eGFR) using creatinine (eGFRcr) with the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation as the first test for GFR evaluation, but the Cockcroft-Gault (CG) equation is still commonly used in oncology practice and clinical trials despite increasing evidence of its inaccuracy compared to measured GFR (mGFR). Guidelines recommend eGFR using cystatin C (eGFRcys) or both markers (eGFRcr-cys) as a confirmatory test, but neither was carefully evaluated in cancer patients. Therefore, we compared performance of the CKD-EPI equations and others to the CG equation in adults with a variety of solid tumors. The mGFR was determined by plasma clearance of ⁵¹Cr-EDTA. Bias was defined as the median of the differences between mGFR and eGFR while accuracy was defined as the percentage of estimates that differed by more than 30% from the measured GFR (1-P30). We prospectively recruited 1,200 patients between April 2015 and September 2017 with a mean age and mGFR of 58.8 years and 78.4 ml/min/1.73m², respectively. Bias among eGFRcr equations varied from -8.1 to +6.1 ml/min/1.73 m². CG was the least accurate, 1-P30 (95% confidence interval) was 24.9 (22.4- 27.3)%; CKD-EPI had 1-P30 of 19.1 (16.8-21.2)% while eGFRcr-cys had the best performance: bias -2.0 (-2.6 to -1.1) ml/min/1.73m² and 1-P30 7.8 (6.3-9.4)%. Thus, the CG equation should not be preferred over CKD-EPI equation, and eGFRcr-cys can be used as a confirmatory test in adults with solid tumors. Hence, a major policy implication would be to adopt general practice guideline-recommended methods for GFR evaluation in oncology practice and clinical trials.

Association of Treatment Effects on Early Change in Urine Protein and Treatment Effects on GFR Slope in IgA Nephropathy: An Individual Participant Meta-analysis

RATIONALE & OBJECTIVE

An early change in proteinuria is considered a reasonably likely surrogate end point in immunoglobulin A nephropathy (IgAN) and can be used as a basis for accelerated approval of therapies, with verification in a postmarketing confirmatory trial. Glomerular filtration rate (GFR) slope is a recently validated surrogate end point for chronic kidney disease progression and may be considered as the end point used for verification. We undertook a meta-analysis of clinical trials in IgAN to compare treatment effects on change in proteinuria versus change in estimated GFR (eGFR) slope.

STUDY DESIGN

Individual patient-level meta-analysis.

SETTING & STUDY POPULATIONS

Individual data of 1,037 patients from 12 randomized trials.

SELECTION CRITERIA FOR STUDIES

Randomized trials of IgAN with proteinuria measurements at baseline and 6 (range, 2.5-14) months and at least a further 1 year of follow-up for the clinical outcome.

ANALYTICAL APPROACH

For each trial, we estimated the treatment effects on proteinuria and on the eGFR slope, computed as the total slope starting at baseline or the chronic slope starting 3 months after randomization. We used a Bayesian mixed-effects analysis to relate the treatment effects on proteinuria to effects on GFR slope across these studies and developed a prediction model for the treatment effect on the GFR slope based on the effect on proteinuria.

RESULTS

Across all studies, treatment effects on proteinuria accurately predicted treatment effects on the total slope at 3 years (median R2 = 0.88; 95% Bayesian credible interval [BCI], 0.06-1) and on the chronic slope (R2 = 0.98; 95% BCI, 0.29-1). For future trials, an observed treatment effect of approximately 30% reduction in proteinuria would confer probabilities of at least 90% for nonzero treatment benefits on the total and chronic slopes of eGFR. We obtained similar results for proteinuria at 9 and 12 months and total slope at 2 years.

LIMITATIONS

Study population restricted to 12 trials of small sample size, leading to wide BCIs. There was heterogeneity among trials with respect to study design and interventions.

CONCLUSIONS

These results provide new evidence supporting that early reduction in proteinuria can be used as a surrogate end point for studies of chronic kidney disease progression in IgAN.

Long-Term Longitudinal Stability of Kidney Filtration Marker Measurements: Implications for Epidemiological Studies and Clinical Care

BACKGROUND

Establishment and improvement of glomerular filtration rate estimating equations requires accurate and precise laboratory measurement procedures (MPs) for filtration markers. The Advanced Research and Diagnostic Laboratory (ARDL) at the University of Minnesota, which has served as the central laboratory for the Chronic Kidney Disease Epidemiology Collaboration since 2009, has implemented several quality assurance measures to monitor the accuracy and stability of filtration marker assays over time.

METHODS

To assess longitudinal stability for filtration marker assays, a 40-sample calibration panel was created using pooled serum, divided into multiple frozen aliquots stored at -80 °C. ARDL monitored 4 markers-creatinine, cystatin C, beta-2-microglobulin (B2M) and beta-trace protein-measuring 15 calibration panel aliquots from 2009 to 2019. Initial target values were established using the mean of the first 3 measurements performed in 2009-10, and differences from target were monitored over time. New MPs for cystatin C and B2M were added in 2012, with target values established using the first measurement.

RESULTS

The mean percentage difference from mean target values across time was <2% for all original MPs (-0.59% for creatinine; -0.94% for cystatin C; -0.82% for B2M; 1.24% for beta-trace protein).

CONCLUSIONS

Close monitoring of filtration marker trends with a calibration panel at ARDL demonstrates remarkable long-term stability of the MPs. Routine use of a calibration panel for both research studies and clinical care is recommended for filtration markers where longitudinal monitoring is important to detect analytical biases, which can mask or confound true clinical trends in patients.

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

GFR Estimation Using a Panel of Filtration Markers in Shanghai and Beijing

RATIONALE & OBJECTIVES

Estimated glomerular filtration rate (eGFR) using creatinine and cystatin C (eGFRcr-cys) may be less accurate compared to measured GFR (mGFR) in China than in North America, Europe, and Australia due to variation across regions in their non-GFR determinants. The non-GFR determinants of β2-microglobulin (B2M) and β-trace protein (BTP) differ from those of creatinine and cystatin C. Thus, the average eGFR using all 4 markers (eGFRavg) could be more accurate than eGFRcr-cys in China.

STUDY DESIGN

Diagnostic test study.

SETTING & PARTICIPANTS

1,066 participants in Shanghai and Beijing with creatinine and cystatin C and 666 participants with all 4 filtration markers.

TESTS COMPARED

Index tests were previously developed equations for eGFR using creatinine, cystatin C, B2M, and BTP and combinations. The reference test was mGFR using plasma clearance of iohexol. We compared the performance of eGFRavg to eGFRcr-cys using the proportion of participants with errors in eGFR >30% of mGFR (1 - P30) and root mean square error (RMSE) of the regression of eGFR on mGFR on the logarithmic scale. We also compared classification and reclassification of mGFR categories using eGFRavg compared to eGFRcr-cys.

OUTCOMES

Accuracy was significantly better for eGFRavg (1 - P30 of 10.4% and RMSE of 0.214) compared to eGFRcr-cys (1 - P30 of 13.8% and RMSE of 0.232; P = 0.004 and P = 0.006, respectively). However, improvements in accuracy did not generally translate into significant improvement in classification or reclassification of mGFR categories.

LIMITATIONS

Study population may not be generalizable to clinical settings other than large urban medical centers in China.

CONCLUSIONS

A panel of endogenous filtration markers including B2M and BTP in addition to creatinine and cystatin C may improve GFR estimation in China. Further study is necessary to determine whether GFR estimation using B2M and BTP can be improved and whether these improvements lead to useful clinical applications.

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.

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.

Recombinant Mycobacterium smegmatis expressing an ESAT6-CFP10 fusion protein induces anti-mycobacterial immune responses and protects against Mycobacterium tuberculosis challenge in mice

The currently used vaccine against tuberculosis, Bacille Calmette-Guérin (BCG), has variable efficacy, so new vaccine development is crucial. In this study, we evaluated a recombinant vaccine prepared from non-pathogenic Mycobacterium smegmatis (rMS) that expresses a fusion of early secreted antigenic target 6-kDa antigen (ESAT6) and culture filtrate protein 10 (CFP10). C57BL/6 mice were immunized with the rMS expressing the ESAT6-CFP10 fusion protein (rM.S-e6c10) or with BCG. The mice in the rM.S-e6c10 group had a significantly higher titre of anti-ESAT6-CFP10 antibodies than did animals in the BCG or saline groups. Spleen cells from rM.S-e6c10-immunized mice exhibited a cytotoxic response to ESAT6 and CFP10-expressed target cells, but spleen cells from animals in the other groups did not. Levels of IFN-γ and IL-2 production by purified T cells from spleens were significantly higher in rM.S-e6c10 group than in BCG group. Finally, after M. tuberculosis (MTB)-challenged mice, dramatic reduction in the numbers of MTB colony-forming units (CFUs) in the lungs was observed for the mice immunized with the rMS. The protective efficacy of rM.S-e6c10 and BCG vaccination was similar based on measures of MTB burden and lung pathology. Our data indicate that the recombinant M. smegmatis vaccine expressing the ESAT6-CFP10 fusion protein has potential in clinic application.