Deep learning to assist composition classification and thyroid solid nodule diagnosis: a multicenter diagnostic study

OBJECTIVES

This study aimed to propose a deep learning (DL)-based framework for identifying the composition of thyroid nodules and assessing their malignancy risk.

METHODS

We conducted a retrospective multicenter study using ultrasound images from four hospitals. Convolutional neural network (CNN) models were constructed to classify ultrasound images of thyroid nodules into solid and non-solid, as well as benign and malignant. A total of 11,201 images of 6784 nodules were used for training, validation, and testing. The area under the receiver-operating characteristic curve (AUC) was employed as the primary evaluation index.

RESULTS

The models had AUCs higher than 0.91 in the benign and malignant grading of solid thyroid nodules, with the Inception-ResNet AUC being the highest at 0.94. In the test set, the best algorithm for identifying benign and malignant thyroid nodules had a sensitivity of 0.88, and a specificity of 0.86. In the human vs. DL test set, the best algorithm had a sensitivity of 0.93, and a specificity of 0.86. The Inception-ResNet model performed better than the senior physicians (p < 0.001). The sensitivity and specificity of the optimal model based on the external test set were 0.90 and 0.75, respectively.

CONCLUSIONS

This research demonstrates that CNNs can assist thyroid nodule diagnosis and reduce the rate of unnecessary fine-needle aspiration (FNA).

CLINICAL RELEVANCE STATEMENT

High-resolution ultrasound has led to increased detection of thyroid nodules. This results in unnecessary fine-needle aspiration and anxiety for patients whose nodules are benign. Deep learning can solve these problems to some extent.

KEY POINTS

• Thyroid solid nodules have a high probability of malignancy. • Our models can improve the differentiation between benign and malignant solid thyroid nodules. • The differential performance of one model was superior to that of senior radiologists. Applying this could reduce the rate of unnecessary fine-needle aspiration of solid thyroid nodules.

Dietary supplementation of proteases on growth performance, nutrient digestibility, blood characteristics and gut microbiota of growing pigs fed sorghum-based diets

Low-tannin sorghum is an excellent energy source in pig diets. However, sorghum contains several anti-nutritional factors that may have negative effects on nutrient digestibility. The impacts of proteases on growth performance, nutrient digestibility, blood parameters, and gut microbiota of growing pigs fed sorghum-based diets were studied in this study. Ninety-six pigs (20.66 ± 0.65 kg BW) were allocated into three groups (eight pens/group, four pigs/pen): (1) CON (control diet, sorghum-based diet included 66.98% sorghum), (2) PRO1 (CON + 200 mg/kg proteases), (3) PRO2 (CON + 400 mg/kg proteases) for 28 d. No differences were observed in growth performance and apparent total tract digestibility (ATTD) of nutrients between CON and PRO1 groups. Pigs fed PRO2 diet had increased (P < 0.05) BW on d 21 and 28, and increased (P < 0.05) average daily gain during d 14-21 and the overall period compared with pigs fed CON diet. In addition, pigs fed PRO2 diet had improved (P < 0.05) ATTD of gross energy, CP, and DM compared with pigs fed CON and PRO1 diets. Pigs fed PRO2 diet had lower (P < 0.05) plasma globulin (GLB) level and higher (P < 0.05) plasma glucose, albumin (ALB) and immunoglobulin G levels, and ALB/GLB ratio than pigs fed CON and PRO1 diets. Furthermore, pigs fed PRO2 diet had decreased (P < 0.05) the relative abundance of Acidobacteriota at the phylum level and increased (P < 0.05) the relative abundance of Prevotella_9 at the genus level. The linear discriminant analysis effect size analysis also showed that pigs fed PRO2 diet had significantly enriched short-chain fatty acid-producing bacteria, such as Subdoligranulum and Parabacteroides. In conclusion, protease supplementation at 400 mg/kg improved the growth performance of growing pigs fed sorghum-based diets, which may be attributed to the improvement of nutrient digestibility, host metabolism, immune status and associated with the altered gut microbiota profiles.

AI diagnosis of Bethesda category IV thyroid nodules

Thyroid nodules are a common disease, and fine needle aspiration cytology (FNAC) is the primary method to assess their malignancy. For the diagnosis of follicular thyroid nodules, however, FNAC has limitations. FNAC can classify them only as Bethesda IV nodules, leaving their exact malignant status and pathological type undetermined. This imprecise diagnosis creates difficulties in selecting the follow-up treatment. In this retrospective study, we collected ultrasound (US) image data of Bethesda IV thyroid nodules from 2006 to 2022 from five hospitals. Then, US image-based artificial intelligence (AI) models were trained to identify the specific category of Bethesda IV thyroid nodules. We tested the models using two independent datasets, and the best AI model achieved an area under the curve (AUC) between 0.90 and 0.95, demonstrating its potential value for clinical application. Our research findings indicate that AI could change the diagnosis and management process of Bethesda IV thyroid nodules.

Value of Artificial Intelligence in Improving the Accuracy of Diagnosing TI-RADS Category 4 Nodules

OBJECTIVE

Considerable heterogeneity is observed in the malignancy rates of thyroid nodules classified as category 4 according to the Thyroid Imaging Reporting and Data System (TI-RADS). This study was aimed at comparing the diagnostic performance of artificial intelligence algorithms and radiologists with different experience levels in distinguishing benign and malignant TI-RADS 4 (TR4) nodules.

METHODS

Between January 2019 and September 2022, 1117 TR4 nodules with well-defined pathological findings were collected for this retrospective study. An independent external data set of 125 TR4 nodules was incorporated for testing purposes. Traditional feature-based machine learning (ML) models, deep convolutional neural networks (DCNN) models and a fusion model that integrated the prediction outcomes from all models were used to classify benign and malignant TR4 nodules. A fivefold cross-validation approach was employed, and the diagnostic performance of each model and radiologists was compared.

RESULTS

In the external test data set, the area under the receiver operating characteristic curve (AUROC) of the three DCNN-based secondary transfer learning models-InceptionV3, DenseNet121 and ResNet50-were 0.852, 0.837 and 0.856, respectively. These values were higher than those of the three traditional ML models-logistic regression, multilayer perceptron and random forest-at 0.782, 0.790, and 0.767, respectively, and higher than that of an experienced radiologist (0.815). The fusion diagnostic model we developed, with an AUROC of 0.880, was found to outperform the experienced radiologist in diagnosing TR4 nodules.

CONCLUSION

The integration of artificial intelligence algorithms into medical imaging studies could improve the accuracy of identifying high-risk TR4 nodules pre-operatively and have significant clinical application potential.

Effects of dietary methionine supplementation from different sources on growth performance and meat quality of barrows and gilts

Methionine is indispensable for growth and meat formation in pigs. However, it is still unclear that increasing dietary sulphur-containing amino acid (SAA) levels using different methionine sources affects the growth performance and meat quality of barrows and gilts. To investigate this, 144 pigs (half barrows and half gilts) were fed the control (100% SAA, CON), DL-Methionine (125% SAA, DL-Met)-supplemented, or OH-Methionine (125% SAA, OH-Met)-supplemented diets during the 11-110 kg period. The results showed that plasma methionine levels varied among treatments during the experimental phase, with increased plasma methionine levels observed following increased SAA consumption during the 25-45 kg period. In contrast, pigs fed the DL-Met diet had lower plasma methionine levels than those fed the CON diet (95-110 kg). Additionally, gilts fed the DL-Met or OH-Met diets showed decreased drip loss in longissimus lumborum muscle (LM) compared to CON-fed gilts. OH-Met-fed gilts had higher pH45min values than those fed the CON or DL-Met diets, whereas OH-Met-fed barrows had higher L45min values than those fed the CON or DL-Met diets. Moreover, increased consumption of SAA, regardless of the methionine source, tended to decrease the shear force of the LM in pigs. In conclusion, this study indicates that increasing dietary levels of SAA (+25%) appeared to improve the meat quality of gilts by decreasing drip loss and increasing meat tenderness.

Complexity Metrics and Planning Dose-Based Pretreatment Patient-Specific Quality Assurance Prediction: Classification, Gamma Passing Rates, and DVH Deviation

PURPOSE/OBJECTIVE(S)

Patient-specific quality assurance (QA) prediction before treatment is beneficial to the clinical resource allocation and the dosimetric monitoring of the patient plans. The aim of this study is to investigate the potential of complexity metrics of radiotherapy plan and patient planning dose to predict QA result, gamma passing rates and dose-volume indices deviation.

MATERIALS/METHODS

Planning dose from treatment planning system (TPS), reconstructed dose from a vendor provided QA phantom and complexity metrics of the 499 radiotherapy plans of patients in our institution from March 2022 to September 2022 were used for methodology verification. Gamma passing rate (3%/2mm,10% threshold) 90% was regarded as criterion of QA pass or fail. A deep learning model ResNet-50 was modified to 3D dose processing and a multilayer perceptron (MLP) with three layers were adopted to extract features from 3D dose and 1D metrics in two parallel ways, then, the features were concatenate together to predict QA results. The dataset was split into 349 for train, 50 for validation and 100 for testing. Evaluation of predictions was based on absolute value deviation and area under the curves (AUC) of receiver operator characteristic (ROC) curve.

RESULTS

In this dataset, 71% (355/499) plans pass the pretreatment QA test. For QA passing prediction in 100 testing cases, the AUC of ROC could achieve 0.92. For gamma passing rates prediction, a mean absolute error (MAE) of 1.8% could be observed for cases with gamma passing rates bigger than 90%, and a MAE of 4.5% deviation could be observed for cases with gamma passing rates from 80% to 90%. For PTV ΔD95 (%) and PTV ΔHI (%), the MAE of prediction and ground truth is 1%. The model with only complexity metrics and only 3D dose could achieve the AUC of ROC 0.91 and 0.84, respectively.

CONCLUSION

The complexity metrics and 3D planning dose-based model could predict pretreatment patient specific QA results with high accuracy and the complexity metrics play a leading role in the model. Dose-volume metrics deviations of PTV could be predicted and more clinically useful information could be provided.

A deep-learning model using enhanced chest CT images to predict PD-L1 expression in non-small-cell lung cancer patients

AIM

To develop a deep-learning model using contrast-enhanced chest computed tomography (CT) images to predict programmed death-ligand 1 (PD-L1) expression in patients with non-small-cell lung cancer (NSCLC).

MATERIALS AND METHODS

Preoperative enhanced chest CT images and immunohistochemistry results for PD-L1 expression (<1% and ≥1% were defined as negative and positive, respectively) were collected retrospectively from 125 NSCLC patients to train and validate a deep-learning radiomics model (DLRM) for the prediction of PD-L1 expression in tumours. The DLRM was developed by combining the deep-learning signature (DLS) obtained from a convolutional neural network and clinicopathological factors. The indexes of the area under the curve (AUC), integrated discrimination improvement (IDI), and decision curve analysis (DCA) were used to evaluate the efficiency of the DLRM.

RESULTS

DLS and tumour stage were identified as independent predictors of PD-L1 expression by the DLRM. The AUCs of the DLRM were 0.804 (95% confidence interval: 0.697-0.911) and 0.804 (95% confidence interval: 0.679-0.929) in the training and validation cohorts, respectively. IDI analysis showed the DLRM had better diagnostic accuracy than DLS (0.0028 [p<0.05]) in the validation cohort. Additionally, DCA revealed that the DLRM had more net benefit than the DLS for clinical utility.

CONCLUSION

The proposed DLRM using enhanced chest CT images could function as a non-invasive diagnostic tool to differentiate PD-L1 expression in NSCLC patients.

Feasibility of Using Pseudo-CT for Dosimetry, Radiomics, and Efficacy Assessment in IMRT/VMAT of Brain Tumors: A Multi-Omics Analysis

PURPOSE/OBJECTIVE(S)

Pseudo-CT generated by convolutional neural networks (CNN) and planning MRI has facilitated the promotion of MRI-Only. The technology not only reduces the time and money spent on CT scans, but also eliminates the cumbersome CT-MR registration. The feasibility in Stereotactic Brain Radiotherapy has been analyzed in previous studies by our team. However, when the prescribed requirements are not met, IMRT/VMAT are still selected. The study aims to evaluate the feasibility of pseudo-CT in IMRT/VMAT for brain cancer via the following 5 aspects: (1) image difference, (2) dose accuracy, (3) radiomics feature, (4) efficacy assessment, and (5) correlation analysis.

MATERIALS/METHODS

Brain tumor patients who had received radiotherapy at our institution and had planning MRI and CT were included in the study. Redesign of IMRT and VMAT radiotherapy plans according to 3 × 15Gy for each patient. Hounsfield unit (HU) values for PTV and OARs were used to assess image differences. And dose accuracy analysis contained a 2D dose volume histogram (DVH) metrics (Dmax, Dmean, D2%, D50%, D98%, HI, CI) and 3D gamma metrics (criteria: 1-3%/2mm, 1%/1mm, 10% threshold). Then 107 original image features of PTV and OARs were extracted for radiometry analysis. And tumor control probability (TCP) of PTV (Poisson model) and normal tissue complication probability (NTCP) of OARs (Lyman-Kutcher-Burman model) were used for the variance analysis of efficacy assessment. Wilcox-test was used for significance of differences test (0.05), and spearman correlation analysis was used to explore the key features of the dose bias.

RESULTS

A total of 42 patients were included, with 42 planning CTs and pseudo-CTs (mDixon-T1), and 38 pseudo-CTs (mDixon-T1-CE). The median volume of PTV was 4.1 cc (range 0.5-27.3), with no significant differences in HU, DVH, 3D gamma, and NTCP/TCP metrics. The median local gamma passing rates (1%/1mm) between planning CTs and pseudo-CTs (mDixon-T1) were 93.1% (range 65.5%-99.7%, IMRT) and 93.3% (range 63.9%-99.6%, VMAT). And more than 85% original radiomics features have significant difference. Further, the feature HU-Min was found to be more correlated with dose metrics in the correlation analysis. We speculate that it may be caused by the smoothing of the low frequency signal before outputting image. And since Shape_MeshVolume, Shape_VoxelVolume and PTV volume difference are highly correlated with dose deviation, it indicates that dose deviation affected by CT-MR registration.

CONCLUSION

This study has the potential to provide guidance for the clinical application of pseudo-CT in the MRI-Only workflow with IMRT/VMAT for brain tumors. These quantitative results strongly indicate pseudo-CT can be used as a substitute for the initial CT in IMRT/VMAT for small brain lesions (size <5 cm, numbers <5), but not for radiomics analysis. Additionally, the impact of inter-image differences on dose accuracy is less significant compared to the deviation caused by image registration.

Comparison of machine learning models based on multi-parametric magnetic resonance imaging and ultrasound videos for the prediction of prostate cancer

Objective

To establish machine learning (ML) prediction models for prostate cancer (PCa) using transrectal ultrasound videos and multi-parametric magnetic resonance imaging (mpMRI) and compare their diagnostic performance.

Materials and methods

We systematically collated the data of 383 patients, including 187 with PCa and 196 with benign lesions. Of them, 307 patients (150 with PCa and 157 with benign lesions) were randomly selected to train and validate the ML models, 76 patients were used as test set. B-Ultrasound videos (BUS), mpMRI T2 sequence (T2), and ADC sequence (ADC) were obtained from all patients. We extracted 851 features of each patient in the BUS, T2, and ADC groups and used a t-test, the Mann-Whitney U test, and LASSO regression to screen the features. Support vector machine (SVM), random forest (RF), adaptive boosting (ADB), and gradient boosting machine (GBM) models were used to establish radiomics models. In addition, we fused the features screened via LASSO regression from three groups as new features and rebuilt ML models. The performance of the ML models in diagnosing PCa in the BUS, T2, ADC, and fusion groups was compared using the area under the ROC curve (AUC), sensitivity, specificity, and accuracy.

Results

In the test cohort, the AUC of each model in the ADC group was higher than that of in the.BUS and T2 groups. Among the models, the RF model had the best diagnostic performance, with an AUC of 0.85, sensitivity of 0.78 (0.61-0.89), specificity of 0.84 (0.69-0.94), and accuracy of 0.83 (0.66-0.93). The SVM model in both the BUS and T2 groups performed best. Based on the features screened in the BUS, T2, and ADC groups fused to construct the models, the SVM model was found to perform best, with an AUC of 0.87, sensitivity of 0.73 (0.56-0.86), specificity of 0.79 (0.63-0.90), and accuracy of 0.77 (0.59-0.89). The difference in the results was statistically significant (p<0.05).

Conclusion

The ML prediction models had a good diagnostic ability for PCa. Among them, the SVM model in the fusion group showed the best performance in diagnosing PCa. These prediction models can help radiologists make better diagnoses.

A 2-Stage Root Analog Implant with Compact Structure, Uniform Roughness, and High Accuracy

Immediate implant placement has the advantages of shortening the operation time, reducing the treatment cycle and cost. At present, this technology has been used widely, but the indications of immediate implantation are still limited. Here, a novel type of root analog implant (RAI) was manufactured by selective laser melting technology to address the limitation. Under optimized condition, RAIs were printed with the internal density of 99.73% and the uniform surface roughness of 11 μm (Sa). Besides, the deviation between RAI specimen and design models is controlled within 0.15 mm after optimizing scanning parameters. The substrate printed could promote human bone marrow stromal cell proliferation, spreading, and osteogenic differentiation. The bone-implant contact (BIC, 75% ± 7%) and bone volume/total volume (BV/TV, 74% ± 7%) of RAIs were significantly higher than that of conventional implants (BIC, 66% ± 5%; BV/TV, 62% ± 5%) in in vivo experiments. Further, customized abutments were designed for the RAIs, improving the masticatory ability of the beagle dogs after crown restoration. This study aims to design a personalized 2-stage RAI with compact structure and uniform roughness, in order to achieve better fracture resistance, initial osseointegration efficiency, and dispersed stress in immediate implantation. It provides a certain guiding value for standardizing the manufacture and clinical application of RAI in immediate implantation.

Value of deep learning models based on ultrasonic dynamic videos for distinguishing thyroid nodules

Objective

This study was designed to distinguish benign and malignant thyroid nodules by using deep learning(DL) models based on ultrasound dynamic videos.

Methods

Ultrasound dynamic videos of 1018 thyroid nodules were retrospectively collected from 657 patients in Zhejiang Cancer Hospital from January 2020 to December 2020 for the tests with 5 DL models.

Results

In the internal test set, the area under the receiver operating characteristic curve (AUROC) was 0.929(95% CI: 0.888,0.970) for the best-performing model LSTM Two radiologists interpreted the dynamic video with AUROC values of 0.760 (95% CI: 0.653, 0.867) and 0.815 (95% CI: 0.778, 0.853). In the external test set, the best-performing DL model had AUROC values of 0.896(95% CI: 0.847,0.945), and two ultrasound radiologist had AUROC values of 0.754 (95% CI: 0.649,0.850) and 0.833 (95% CI: 0.797,0.869).

Conclusion

This study demonstrates that the DL model based on ultrasound dynamic videos performs better than the ultrasound radiologists in distinguishing thyroid nodules.

Machine learning prediction of prostate cancer from transrectal ultrasound video clips

Objective

To build a machine learning (ML) prediction model for prostate cancer (PCa) from transrectal ultrasound video clips of the whole prostate gland, diagnostic performance was compared with magnetic resonance imaging (MRI).

Methods

We systematically collated data from 501 patients—276 with prostate cancer and 225 with benign lesions. From a final selection of 231 patients (118 with prostate cancer and 113 with benign lesions), we randomly chose 170 for the purpose of training and validating a machine learning model, while using the remaining 61 to test a derived model. We extracted 851 features from ultrasound video clips. After dimensionality reduction with the least absolute shrinkage and selection operator (LASSO) regression, 14 features were finally selected and the support vector machine (SVM) and random forest (RF) algorithms were used to establish radiomics models based on those features. In addition, we creatively proposed a machine learning models aided diagnosis algorithm (MLAD) composed of SVM, RF, and radiologists’ diagnosis based on MRI to evaluate the performance of ML models in computer-aided diagnosis (CAD). We evaluated the area under the curve (AUC) as well as the sensitivity, specificity, and precision of the ML models and radiologists’ diagnosis based on MRI by employing receiver operator characteristic curve (ROC) analysis.

Results

The AUC, sensitivity, specificity, and precision of the SVM in the diagnosis of PCa in the validation set and the test set were 0.78, 63%, 80%; 0.75, 65%, and 67%, respectively. Additionally, the SVM model was found to be superior to senior radiologists’ (SR, more than 10 years of experience) diagnosis based on MRI (AUC, 0.78 vs. 0.75 in the validation set and 0.75 vs. 0.72 in the test set), and the difference was statistically significant (p< 0.05).

Conclusion

The prediction model constructed by the ML algorithm has good diagnostic efficiency for prostate cancer. The SVM model’s diagnostic efficiency is superior to that of MRI, as it has a more focused application value. Overall, these prediction models can aid radiologists in making better diagnoses.

[Medial border of D3 lymphadenectomy for right colon cancer]

The extent of D3 lymphadenectomy for right colon cancer, especially the medial border of central lymph node dissection remains controversial. D3 lymphadenectomy and complete mesocolon excision (CME) are two standard procedures for locally advanced right colon carcinoma. D3 lymphadenectomy determines the medial border according to the distribution of the lymph nodes. The mainstream medial border should be the left side of superior mesenteric vein (SMV) according to the definition of D3, but there are also some reports that regards the left side of superior mesenteric artery (SMA) as the medial border. In contrast, the CME procedure emphasizes the beginning of the colonic mesentery and the left side of SMA should be considered as the medial border. Combined with the anatomical basis, oncological efficacy and technical feasibility of D3 lymph node dissection, we think that it is safe and feasible to take the left side of SMA as the medial boundary of D3 lymph node dissection. This procedure not only takes into account the integrity of mesangial and regional lymph node dissection, but also dissects more distant lymph nodes at risk of metastasis. It has its anatomical basis and potential oncological advantages. However, at present, this technical concept is still in the exploratory stage in practice, and the related clinical evidence is not sufficient.

Toward Elucidating the Physiological Impacts of Residual Stresses in the Colorectum

Irritable bowel syndrome afflicts 10-20% of the global population, causing visceral pain with increased sensitivity to colorectal distension and normal bowel movements. Understanding and predicting these biomechanics will further advance our understanding of visceral pain and complement the existing literature on visceral neurophysiology. We recently performed a series of experiments at three longitudinal segments (colonic, intermediate, and rectal) of the distal 30 mm of colorectums of mice. We also established and fitted constitutive models addressing mechanical heterogeneity in both the through-thickness and longitudinal directions of the colorectum. Afferent nerve endings, strategically located within the submucosa, are likely nociceptors that detect concentrations of mechanical stresses to evoke the perception of pain from the viscera. In this study, we aim to: (1) establish and validate a method for incorporating residual stresses into models of colorectums, (2) predict the effects of residual stresses on the intratissue mechanics within the colorectum, and (3) establish intratissue distributions of stretches and stresses within the colorectum in vivo. To these ends we developed two-layered, composite finite element models of the colorectum based on our experimental evidence and validated our approaches against independent experimental data. We included layer- and segment-specific residual stretches/stresses in our simulations via the prestrain algorithm built into the finite element software febio. Our models and modeling approaches allow researchers to predict both organ and intratissue biomechanics of the colorectum and may facilitate better understanding of the underlying mechanical mechanisms of visceral pain.

A mechanical, electrical dual autonomous self-healing multifunctional composite hydrogel

The versatile properties make hydrogels a potential multipurpose material that finds wide applications. However, the preparation of multipurpose hydrogels is very challenging. Here, we report a method based on free radical reaction and composite mechanisms to prepare mechanical and electrical self-healing multifunctional hydrogels. In this study, the introduction of imidazolium salt ionic liquids and glycerol in the hydrogel system endows the gels with good antibacterial, conductive, and adhesive properties and excellent antifreeze properties. The testing results show that the as-prepared hydrogel has stable mechanical and electrical properties even under the extremely cold condition of -50°C after self-healing. Moreover, the active esters formed in the dynamic radical reaction have better reducibility, thus further investing the as-prepared hydrogel with high antioxidant activity. The application results show that these comprehensive properties make such hydrogel system very useful in wound repair and wearable strain sensors.

Current practices of Western Australian general dentists regarding management of patients on anticoagulant/antiplatelet therapy

PURPOSE

Currently, there are little to no published studies outlining general dentists' knowledge in the management of patients on anticoagulant/antiplatelet therapies in Australia. The aim of this study was to investigate the current practices of Western Australian (WA) general dentists with regards to dental management of patients taking anticoagulants/antiplatelets.

MATERIALS AND METHODS

WA dentists were invited to undertake a survey to investigate their knowledge on the management of patients taking anticoagulant/antiplatelet. The questionnaire provided to WA general dentists consisted of pre-extraction advice on patients (direct oral anticoagulants [DOACs], antiplatelets, warfarin, dual antiplatelets and antiplatelet/anticoagulant). Results were analysed using descriptive statistics as well as chi-square tests.

RESULTS

Of the 89 participants, 40.5% had <5 years of general dental experience. Most WA general dentists (64%-71%) responded with 'no change' when performing extractions on patients on DOACs, antiplatelet therapy, warfarin, dual antiplatelets and antiplatelets/anticoagulants (P = 0.00). Furthermore, dentists with 6-10 years of experience were more likely to cease antiplatelet for 24 h before extractions (P < 0.05). Dentists who extracted 10-30 teeth per month were likely to stop antiplatelets and DOACs for more than 48 h compared to other groups (P < 0.05).

CONCLUSION

Most WA dentists would not cease anticoagulant/antiplatelet therapy when undergoing dental extractions.

Identification of Thioflavin T Binding Modes to DNA: A Structure-Specific Molecular Probe for Lasing Applications

The binding mechanism of thioflavin T (ThT) to DNA was studied using polarized light spectroscopy and fluorescence-based techniques in solutions and in solid films. Linear dichroism measurements showed that ThT binds to DNA duplex by intercalation. Time-resolved fluorescence studies revealed a second binding mode which is the external binding to the DNA phosphate groups. Both binding modes represent the nonspecific type of interactions. The studies were complemented with the analysis of short oligonucleotides having DNA cavities. The results indicate that the interplay between three binding modes-intercalation, external binding, and binding inside DNA cavities-determines the effective fluorescence quantum yield of the dye in the DNA structures. External binding was found to be responsible for fluorescence quenching because of energy transfer between intercalated and externally bound molecules. Finally, amplified spontaneous emission (ASE) was successfully generated in the ThT-stained films and used for detecting different DNA structures. ASE measurements show that ThT-stained DNA structures can be used for designing bioderived microlasers.

POS0262 IDENTIFYING EROSIVE DISEASE FROM RADIOLOGY REPORTS OF VETERANS WITH INFLAMMATORY ARTHRITIS USING NATURAL LANGUAGE PROCESSING

Background:

The presence of erosive disease influences diagnosis, management, and prognosis in inflammatory arthritis (IA).Research of IA in large datasets is limited by a lack of methods for identifying erosions.

Objectives:

To develop methods for identifying articular erosions in radiology reports from veterans with IA.

Methods:

Included veterans had ≥2 ICD codes for ankylosing spondylitis (AS), psoriatic arthritis (PsA), or rheumatoid arthritis (RA) between 2005- 2019, in Veterans Affairs Corporate Data Warehouse. Chart review & annotation of radiology notes produced the reference standard, & identified erosion terms that informed classification rule development. A rule-based natural language processing (NLP) model was created & revised in training snippets. The NLP method was validated in an independent reference sample of IA patients at the snippet & patient levels

StepDescriptionNumber & example1 Radiology notesa.Select note titles potentially relevant to IAa. 35,141 notes titlesb.Extract notes with titles potentially related to IAb. 2,926,113 radiology notes2 Possible meaningful termsa.Compile list of root terms that may indicate erosiona. 11 root terms (i.e. ero*, pencil*cup, irreg*)b.Query radiology notes for root term variationsb. 1178 variations (i.e. erosion, erotic, erode)c.Select possible meaningful termsc. 179 possible terms (i.e. erosion, erode)3 Annotationa.Extract snippets^ containing possible meaningful termsa.5000 snippets from radiology notesb.Classify snippets according to: 1) Meaningful term, 2) Relevance to joint, 3) Attribution to IA, 4) Affirmationb.4068 classifications with 1017 snippets (in rounds of 50-417 snippets for NLP training & testing)4 Rule developmenta.Identify meaningful terms representing erosiona. 6 terms (pencil * cup, erosion, erosive, etc.)b.Exclude erosive processes irrelevant to joint(s)b. 28 irrelevant processes (i.e. gastric erosion)c. Exclude articular erosive processes not attributed to IAc. 5 non-IA processes IA (i.e. infection)d. Classify as affirmed/negated (erosion present/absent)d. 83 affirmation/negation rules5 NLP trainingDesign & revise NLP model until accuracy ≥90%6 rounds, 817 snippets (AS 417, RA 200, PsA 200)6 NLP testingTest NLP model200 snippets (AS 100, RA 50, PsA 50)7 Pt classificationa. Develop rules for classifying pts with discordant snippetsa. 5 rules developed in 368 ptsb. Build reference sample (pts classified as erosive or non-erosive via chart review)b. 30 IA pts (10 AS, 10 RA, 10 PsA)8 NLP validationValidate NLP model in reference sample at snippet level149 snippets (29 AS, 76 RA, 44 PsA)9 Method validationValidate methods (NLP+pt classification) at pt level30 IA pts (reference sample)

pt= patient. ^Snippets include text containing 30 words before & after meaningful terms

Results:

In 168,667 veterans with IA, the mean age was 63.1 & 90.3% were male. Method development involved radiology note & erosion term selection, rule development, NLP model building, & method validation. The NLP model accuracy was 94.6% at the snippet level & 90.0% at the patient level, for all IA patients.

Accuracy of methods.

Conclusion:

The methods accurately identify erosions from radiology reports of veterans with IA. They may facilitate a broad range of research involving cohort identification & disease severity stratification

References:

[1]Walsh JA, et al. J Rheumatol. 2020;47(1):42-49

Disclosure of Interests:

Gopi Penmetsa: None declared, Shaobo Pei: None declared, Brian Sauer Grant/research support from: I have been an investigator on research contracts supported by Abbvie., Jessica A. Walsh Consultant of: AbbVie, Amgen, Janssen, Lilly, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Merck, Pfizer, Bingjian Feng Grant/research support from: Bing-Jian Feng reports funding and sponsorship to his institution on his behalf from Pfizer Inc., Regeneron Genetics Center LLC, and Astra Zeneca (UK). The PERCH software, for which Bing-Jian Feng is the inventor, has been non-exclusively licensed to Ambry Genetics for clinical genetic testing services and research., Jodi Walker Shareholder of: Abbvie and mutual funds containing various pharmaceutical companies, Employee of: Abbvie, Kevin Douglas Shareholder of: employed by Abbvie, Employee of: employed by Abbvie, Jerry Clewell Shareholder of: Own Abbvie Shares and mutual funds that hold pharmaceutical and other health care stocks, Employee of: I am current Abbvie Inc employee and past employee of Eli Lilly co

[Value of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid enhanced magnetic resonance imaging and diffusion-weighted MR imaging in predicting microvascular invasion in hepatocellular carcinoma and the prognostic significance]

Objective: To investigate the combined value of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) in predicting pathological microvascular invasion (pMVI) preoperatively, and to determine the relationship between prediction results and prognosis in hepatocellular carcinoma (HCC) patients. Methods: A total of 181 newly diagnosed HCC patients were enrolled in this study. Imaging characteristics and the apparent diffusion coefficient (ADC) value of DWI were analyzed. The differences of imaging characteristics and ADC values between different pMVI groups were analyzed.Multivariate logistic regression and receiver operating characteristic (ROC) curve were used to analyze the value for pMVI prediction by using significant parameters. The patients were grouped based on MRI predicted MVI (mrMVI), and the relationship between mrMVI and recurrence free survival time (RFS) was analyzed. Results: Fifty-one patients were pMVI positive and 130 patients were pMVI negative. The ADC value in pMVI positive group were (1.10±0.17)×10(-3) mm(2)/s, significantly lower than (1.27±0.22)×10(-3) mm(2)/s of pEMVI negative group (P<0.001). The incidence rates of incomplete enhancing "capsule" , non-smooth tumor margin, arterial peritumoral enhancement, mosaic architecture and peritumoral hypointensity on hepatobiliary phase (HBP) in pMVI positive group were significantly higher than those of negative group (all P<0.05). Multivariate logistic regression analysis showed that tumor margin, arterial peritumoral enhancement, peritumoral hypointensity on HBP and ADC value were independently associated with pMVI. ROC analysis showed that the area under curve, sensitivity and specificity of pMVI predicted by combined parameters were 0.830, 76.5% and 81.5%, respectively. The median RFS of mrMVI positive group was 23.6 months, significantly lower than 38.2 months of mrEMVI negative group (P=0.004). Conclusion: Tumor margin, arterial peritumoral enhancement, peritumoral hypointensity on HBP and ADC value are independent predictors of pMVI in HCC, and mrMVI is related with RFS.

[An investigation of musculoskeletal disorders at multiple sites and related influencing factors among workers in an automobile assembly shop]

Objective: To investigate the current status of work-related musculoskeletal disorders (WMSDs) in automobile assembly workers, as well as the distribution of WMSDs at multiple sites and related influencing factors. Methods: From March to July 2019, cluster sampling was performed to select 663 male automobile assembly workers as respondents, and the musculoskeletal injury questionnaire was used to investigate their general status and working condition. A multinomial logistic regression analysis was used to analyze the influencing factors for WMSDs at multiple sites. Results: The detection rate of WMSDs within the past 7 days was 37.9% (251/663) among the automobile assembly workers, and the detection rate of WMSDs within the past 1 year was 51.9% (344/663) . Of all workers, 13.6% (90/663) had WMSDs involving only 1 site, while 38.3% (254/663) had WMSDs involving 2 or more sites. The multinomial logistic regression analysis showed that frequent turns during work was a risk factor for WMSDs involving 1-3, 4-6, and 7-9 sites (odds ratio [OR]=1.65, 2.47, and 3.65, respectively) . Repeated action of lower extremities and ankles was a risk factor for WMSDs involving 4-6 and 7-9 sites (OR=2.15 and 2.98, respectively) . Working in an uncomfortable position was a risk factor for WMSDs involving 1-3, 4-6, and 7-9 sites (OR=1.95, 2.67, and 3.04, respectively) . Prolonged standing during work was a risk factor for WMSDs involving 1-3 and 4-6 sites (OR= 1.87 and 1.79, respectively) . Working overtime was a risk factor for WMSDs involving 7-9 sites (OR=5.48) . Adequate time for rest was a protective factor against WMSDs involving 1-3 and 4-6 sites (OR=0.50 and 0.31, respectively) . Conclusion: There is a high detection rate of WMSDs in automobile assembly workers, and WMSDs at multiple sites are more common than WMSDs at a single site. Poor position and organizational management factors are risk factors for occupational WMSDs at multiple sites.

Computational Modeling of Mouse Colorectum Capturing Longitudinal and Through-thickness Biomechanical Heterogeneity

Mechanotransduction, the encoding of local mechanical stresses and strains at sensory endings into neural action potentials at the viscera, plays a critical role in evoking visceral pain, e.g., in the distal colon and rectum (colorectum). The wall of the colorectum is structurally heterogeneous, including two major composites: the inner consists of muscular and submucosal layers, and the outer consists of circular muscular, intermuscular, longitudinal muscular, and serosal layers. In fact the colorectum presents biomechanical heterogenity across both the longitudinal and through-thickness directions thus highlighting the differential roles of sensory nerve endings within different regions of the colorectum in visceral mechanotransduction. We determined constitutive models and model parameters for individual layers of the colorectum from three longitudinal locations (colonic, intermediate, and distal) using nonlinear optimization to fit our experimental results from biaxial extension tests on layer-separated colorectal tissues (mouse model, 7×7 mm2, Siri et al., Am. J. Physiol. Gastrointest. Liver Physiol. 316, G473-G481 and 317, G349-G358), and quantified the thicknesses of the layers. In this study we also quantified the residual stretches stemming from separating colorectal specimens into inner and outer composites and we completed new pressure-diameter mechanical testing to provide an additional validation case. We implemented the constitutive equations and created two-layered, 3-D finite element models using FEBio (University of Utah), and incorporated the residual stretches. We validated the modeling framework by comparing FE-predicted results for both biaxial extension testing of bulk specimens of colorectum and pressure-diameter testing of bulk segments against corresponding experimental results independent of those used in our model fitting. We present the first theoretical framework to simulate the biomechanics of distal colorectum, including both longitudinal and through-thickness heterogeneity, based on constitutive modeling of biaxial extension tests of colon tissues from mice. Our constitutive models and modeling framework facilitate analyses of both fundamental questions (e.g., the impact of organ/tissue biomechanics on mechanotransduction of the sensory nerve endings, structure-function relationships, and growth and remodeling in health and disease) and specific applications (e.g., device design, minimally invasive surgery, and biomedical research).

MULTIPHYSICS MODELING OF PRECURSORS IN MOLTEN SALT FAST REACTORS USING PROTEUS AND Nek5000

The goal of this work was to calculate the impact of the delayed neutron precursor drift in fast spectrum Molten Salt Reactors (MSRs) using coupled solutions from the neutronics code PROTEUS and the computational fluid dynamics code Nek5000. Specifically, using a multiphysics approach to solve the effective delayed neutron fraction (βeff) or delayed neutron precursor distribution for reactors with flowing fuel salts would provide valuable information for transient simulations and safety assessments. Given the multiple options for the flux solution and geometric resolution/fidelity in PROTEUS, two approaches were developed and applied to various test cases: PROTEUS-NODAL/Nek5000 and PROTEUS-SN/Nek5000. For the former, the precursors are tracked in the built-in precursor drift model in PROTEUS-NODAL, whereas in the latter, Nek5000 directly tracks the precursors. Both approaches were used to solve a single test channel problem and showed excellent agreement in the calculated βeff. Separately, a 3D hourglass-shaped core was modeled using the PROTEUS-SN/Nek5000 approach. This problem was designed to demonstrate the capability of the discrete ordinates (SN) solver and Nek5000 to model complex core designs with axially varying geometries and the ability for Nek5000 to track the precursors and calculate the resulting βeff. In addition, the Nek5000 calculations revealed the presence of recirculation zones in the hourglass design, which could lead to significant temperatures in the fuel salt and surrounding materials. These first coupled solutions show why these approaches may be necessary for not only predicting the precursor drift effect in fast MSRs but also for reactor design and performance assessments.

Application of sensitivity analysis in DYMOND/Dakota to fuel cycle transition scenarios

The ability to perform sensitivity analysis has been enabled for the nuclear fuel cycle simulator DYMOND through its coupling with the design and analysis toolkit Dakota. To test and demonstrate these new capabilities, a transition scenario and multi-parameter study were devised. The transition scenario represents a partial transition from the US nuclear fleet to a closed fuel cycle with small modular LWRs and fast reactors fueled by reprocessed used nuclear fuel. Four uncertain parameters in this transition were studied – start date of reprocessing, total reprocessing capacity, the nuclear energy demand growth, and the rate at which the fast reactors are deployed – with respect to their impact on four response metrics. The responses – total natural uranium consumed, maximum annual enrichment capacity required, total disposed mass, and total cost of the nuclear fuel cycle – were chosen based on measures known to be of interest in transition scenarios [2] and to be significantly impacted by the varying parameters. Analysis of this study was performed both from the direct sampling and through surrogate models developed in Dakota to calculate the global sensitivity measures Sobol’ indices. This example application of this new capability showed that the most consequential parameter to most metrics was the share of new build capacity that is fast reactors. However, for the cost metric, the scaling factor of the energy demand growth was significant and had synergistic behavior with the fast reactor new build share.

MSRE TRANSIENT BENCHMARKS USING SAM

In recent years, there has been renewed interest in Molten Salter Reactors (MSRs) for their potential advantages compared to reactors that rely on solid fuel. In response to such interest, the System Analysis Module (SAM) was enhanced to include MSR-specific modeling features including a delayed neutron precursor drift model and a modified point kinetics model. This paper discusses the validation of these features using the experiments conducted in the Molten Salt Reactor Experiment (MSRE). These experiments include the pump start-up and coast-down tests at zero power and a thermal convection test. For the zero power tests, the change in pump speeds induces flow rate changes in the core that impact the precursor concentrations. This introduces a neutron imbalance and requires the adjustment of the control rods to counter-balance this effect. SAM was used to evaluate the precursor concentration in the core as a function of time, and the resulting changes in reactivity were evaluated through the modified point kinetics equation. The results show good agreement with the experimental data. It should be noted that the pump performance curve used in this analysis was re-constructed based on the initial water test data of the fuel pump. The steady-state pump curve is assumed to be applicable to transient flow operations. The thermal convection test was conducted by shutting off the pumps, reducing the inlet core temperature for 360 minutes, and allowing the power to be adjusted by the inherent feedbacks of the system. The power level during this transient was evaluated by SAM as a function of time.

[Application value of urinary IGFBP7 and TIMP-2 in acute kidney injury with decompensated hepatitis B virus-related liver cirrhosis]

Objective: To investigate the application value of new urinary biomarkers insulin-like growth factor binding protein 7 (IGFBP7) and tissue matrix metalloproteinase inhibitor-2 (TIMP-2) in acute kidney injury with decompensated hepatitis B virus-related liver cirrhosis. Methods: 45 newly hospitalized cases with decompensated hepatitis B virus-related liver cirrhosis were selected. Among them, 19 cases were combined with AKI on admission (cirrhosis-AKI group), 26 cases without AKI (cirrhosis-non-AKI group), and 12 healthy cases (normal control group). First-morning urine samples were collected and IGFBP7 and TIMP-2 were detected by enzyme-linked immunosorbent assay (ELISA). Urinary IGFBP7 and serum creatinine (SCr) were dynamically monitored after hospitalization in cirrhosis-non-AKI group. Normally distributed measurement data were compared by t-test, and non-normally distributed measurement data were compared by rank sum test. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the diagnostic accuracy of the indicators. Results: Urinary IGFBP7, IGFBP7 with TIMP-2 (IGFBP7×TIMP-2) in cirrhosis-AKI group (n = 19) were equally higher than that of the cirrhosis-non-AKI group (P < 0.05). Urinary IGFBP7, TIMP-2 and IGFBP7×TIMP-2 in cirrhosis-AKI group or cirrhosis-non-AKI group were significantly higher than those of the normal control group (P < 0.01). The AUC of urinary IGFBP7 and urinary IGFBP7×TIMP-2 for diagnosis of AKI were 0.703 (95% CI 0.547-0.860) and 0.700 (95% CI 0.541-0.859), respectively. In the liver cirrhosis-non-AKI group (n = 26), 5 cases of AKI were newly diagnosed according to the changes in SCr during hospitalization (progressive group). Urinary IGFBP7 was significantly increased 2 days before the diagnosis of AKI. The concentration of urinary IGFBP7 at admission in the progressive group (n = 5) was higher than that of the non-progressive group (n = 21) (P < 0.05). Conclusion: Urinary IGFBP7 and TIMP-2 concentrations were significantly increased in patients with decompensated hepatitis B virus-related liver cirrhosis. When AKI occurred, urinary IGFBP7 and IGFBP7×TIMP-2 was further increased. Urinary IGFBP7 is valuable for early AKI diagnosis, and may play a role in predicting AKI occurrence.

The acquisition of Mycobacterium tuberculosis infection in village doctors in China: a prospective study

BACKGROUND: Occupational exposure-related risk of Mycobacterium tuberculosis infection has been reported for village doctors in China. This prospective study aims to estimate the infection acquisition in this key population.METHODS: At baseline, all village doctors registered in Zhongmu County were tested by QuantiFERON^®-TB Gold In-Tube (QFT) and QuantiFERON^®-TB Gold Plus (QFT-Plus) in parallel. Those negatives for either of the tests were retested to identify conversions at the 2-year follow-up investigation.RESULTS: A total of 367 eligible participants completed the 2-year follow-up survey with frequency of conversion of 5.0% (18/361) for QFT and 6.1% (21/343) for QFT-Plus. The agreement of follow-up results between the tests was 93.2% with a κ coefficient of 0.43 (95%CI 0.20-0.65). Among QFT-Plus convertors, the difference between TB1 and TB2 tubes (TB2-TB1) was significantly increased as compared with baseline results (P = 0.039). Participants from the villages with occurrence of microbiologically confirmed pulmonary TB showed higher frequency of QFT conversions (11.0% vs. 3.2%, P = 0.011) and QFT-Plus conversions (12.3% vs. 4.4%, P = 0.027) than those from the villages without occurrence.CONCLUSION: Our results consistently suggest that capability on occupational protection and M. tuberculosis infection control should be improved in village doctors in China.

[Investigation on occupational hazards in a refrigeration equipment manufacturing enterprise]

Objective: To investigate the distribution and intensity of noise and ultraviolet radiation of welding posts in a refrigeration equipment manufacturing enterprise, in conjunction with the health status of welding workers, providing scientific evidence for the prevention and control of occupational diseases in this type of post. Methods: In May 2019, a cross-sectional survey method was used to select 576 welding workers in the pressure vessel workshop and the unit assembly workshop of a refrigeration complete equipment manufacturer from 2016 to 2018 as the research objects. The occupational hygiene survey and occupational hazard factor measurement were carried out in the workplace, and the measurement data and occupational health examination results were statistically analyzed. Results: The over standard rate of individual Lex in pressure vessel workshop was 82.2% (37/45) . Compared with the unit assembly workshop, the individual Lex of welding workers in pressure vessel workshop was higher than that in unit assembly workshop (t=13.43, P= 0.00) ; the effective irradiance exceeding rate of welding workers in pressure vessel workshop and unit assembly workshop was 33.3% (4/12) and 25.0% (3/12) , The meacurement of ovradiation in the moskment the occupational exposure limit. The deaf rate and hearing loss rate in pressure vessel workshop were 1.5% (5/336) 20.5% (69/336) , respectively, significantly higher than that in umit assembly workshop (P<0.05) . The detection rate of hearing loss of pressure vessel workshop workers increased year by year, and the difference was statistically significant (χ(2trend)=22.42, P<0.01) ; compared with the unit assembly workshop from 2016 to 2018, the detection rates of lens opacity, corneal cloudiness and hearing loss of pressure vessel workshop workers were statistically significant (χ(2)=9.45, 14.80, 55.99, P<0.01) . Conclusion: Welding workers exposed to noise and ultraviolet radiation are easy to be ignored. The enterprise management department should attach great importance to it and take comprehensive measures to protect the health of welding workers.

Protective effects of gliclazide on high glucose and AGEs-induced damage of glomerular mesangial cells and renal tubular epithelial cells via inhibiting RAGE-p22phox-NF-kB pathway

OBJECTIVE

Gliclazide is one of the most widely used therapeutic drugs for diabetes. As a second-generation sulfonylurea oral hypoglycemic drug, it can lower blood glucose level and delay the occurrence and development of diabetic nephropathy (DN). However, the underlying mechanism remains unclear. Therefore, the aim of this study was to explore whether gliclazide had protective effects on high glucose and advanced glycation end products (AGEs)-induced injury of human mesangial cells (HMCs) and renal tubular epithelial cells.

MATERIALS AND METHODS

HMC and renal tubular epithelial cell lines [human kidney 2 (HK-2)] were cultured in vitro. All cells were then divided into the follow groups: 1) blank control group (5.6 mmol/L glucose), 2) AGEs group [400 μg/mL AGE-bovine serum albumin (AGE-BSA)], 3) high glucose group (25 mmol/L glucose), 4) gliclazide + AGEs group (400 μg/mL AGE-BSA + 20 μmol/L gliclazide) and 5) gliclazide + high glucose group (25 mmol/L glucose + 20 μmol/L gliclazide). Cell counting kit-8 (CCK-8) assay was adopted to determine cell viability. Flow cytometry was used to detect cell apoptosis. The levels of malondialdehyde (MDA), superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) were measured as well. Furthermore, the mRNA expressions of receptor for AGE (RAGE), p22phox and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) were measured via fluorescence quantitative Real-time polymerase chain reaction (qRT-PCR).

RESULTS

Compared with control group, significantly accelerated apoptosis of HMCs and HK-2, increased MDA level, decreased SOD and GSH-Px levels, and up-regulated mRNA expressions of RAGE, p22phox and NF-κB were observed in HMCs and HK-2 of high glucose group and AGEs group. Meanwhile, there were obviously alleviated apoptosis of HMCs and HK-2, decreased MDA level, increased SOD and GSH-Px levels, as well as down-regulated mRNA expressions of RAGE, p22phox and NF-κB in HMCs and HK-2 of gliclazide group compared with high glucose and AGEs group. Furthermore, significant correlations were found between the mRNA expression of RAGE and the apoptosis rate of HMCs and HK-2 (HMCs: r=0.701, p=0.004 and HK-2: r=0.633, p=0.011).

CONCLUSIONS

Gliclazide has protective effects on high glucose and AGEs-induced damage of glomerular mesangial cells and renal tubular epithelial cells via inhibiting RAGE-NADPH oxidase-NF-kB pathway.

Clinical effectiveness of 3 days preoperative treatment with recombinant human erythropoietin in total knee arthroplasty surgery: a clinical trial

AIMS

The purpose of study is to evaluate the effect and complication of preoperative short-term daily recombinant human erythropoietin (rhEPO) treatment for blood-saving in patients undergoing unilateral primary total knee arthroplasty (TKA).

METHODS

This three-arm randomized clinical trial compared three different rhEPO-based treatment protocols for unilateral primary TKA. Group A: application of daily doses of rhEPO combined with iron supplement starting 3 days before surgery; Group B: application of daily doses of rhEPO combined with iron supplement starting the day of surgery; Group C: iron supplement alone. Perioperative hemoglobin (Hb) level gaps, total perioperative blood loss, reticulocyte levels and treatment-related complications were studied.

RESULTS

A total of 102 patients were included (35, 35 and 32 patients in Groups A, B and C, respectively). Total blood loss (TBL) in Groups A, B and C was 490.84, 806.76 and 924.21 ml, respectively. Patients in Group A had a significant lower TBL than Groups B and C (A vs. B: P = 0.010; A vs. C: P < 0.001). There was no difference as for TBL between Groups B and C (P = 0.377). Group A patients had significant smaller Hb decline than Group C on the third and fifth postoperative day (P = 0.049, P = 0.037), as well as than Group B on the fifth postoperative day (P = 0.048). There was no difference as for Hb decline between Groups B and C. No difference was shown in levels of inflammatory biomarkers or blood-saving protocol-related complications among three groups.

CONCLUSIONS

Daily dose of rhEPO combined with iron supplement administered 3 days before TKA procedures could significantly decrease perioperative blood loss and improve postoperative Hb levels, without significantly elevating risks of complication, when compared with admission of rhEPO on the day of surgery and iron supplement alone. Preoperative daily rhEPO treatment could be a more effective blood-saving protocol in TKA procedures.

Surface-state Coulomb repulsion accelerates a metal-insulator transition in topological semimetal nanofilms

The emergence of quantization at the nanoscale, the quantum size effect (QSE), allows flexible control of matter and is a rich source of advanced functionalities. A QSE-induced transition into an insulating phase in semimetallic nanofilms was predicted for bismuth a half-century ago and has regained new interest with regard to its surface states exhibiting nontrivial electronic topology. Here, we reveal an unexpected mechanism of the transition by high-resolution angle-resolved photoelectron spectroscopy combined with theoretical calculations. Anomalous evolution and degeneracy of quantized energy levels indicate that increased Coulomb repulsion from the surface states deforms a quantum confinement potential with decreasing thickness. The potential deformation strongly modulates spatial distributions of quantized wave functions, which leads to acceleration of the transition beyond the original QSE picture. This discovery establishes a complete picture of the long-discussed transition and highlights a new class of size effects dominating nanoscale transport in systems with metallic surface states.

A multi-layered model of human skin elucidates mechanisms of wrinkling in the forehead

Skin wrinkling, especially in the facial area, is a prominent sign of aging and is a growing area of research aimed at developing cosmetics and dermatological treatments. To better understand and treat undesirable skin wrinkles, it is vitally important to elucidate the underlying mechanisms of skin wrinkling, a largely mechanical process. Human skin, a multi-layer composite, has six mechanically distinct layers: from the outermost inward they are the stratum corneum, viable epidermis, dermal-epidermal-junction, papillary dermis, reticular dermis, and hypodermis. To better address the through-thickness hierarchy, and the development of wrinkling within this complicated hierarchy, we established a six-layered model of human skin realized with finite element modeling, by leveraging available morphological and biomechanical data on human skin of the forehead. Exercising our new model we aimed to quantify the effects of three potential mechanisms of wrinkle formation: (1) skin compression due to muscle contraction (dynamic wrinkles); (2) age-related volumetric tissue loss (static wrinkles); and (3) the combined effects of both mechanisms. Since hydration of the stratum corneum significantly affects its stiffness we also aimed to quantify the influence its hydration with these three potential mechanisms of wrinkle formation. Our six-layered skin model, combined with the proposed wrinkling mechanisms, successfully predicts the formation of dynamic and static wrinkles in the forehead consistent with the experimental literature. We observed three wrinkling modes in the forehead where the deepest wrinkles could reach to the reticular dermis. With further refinement our new six-layered model of human skin can be applied to study other region-specific wrinkle types such as the "crow's feet" and the nasolabial folds.

Dynamic changes of interferon gamma release assay results with latent tuberculosis infection treatment

OBJECTIVES

Using QuantiFERON-TB Gold In-Tube (QFT-GIT) for monitoring tuberculosis (TB) and latent TB infection treatment effect is controversial. The present study aimed to evaluate the dynamic changes of interferon gamma (IFN-γ) levels along with latent TB infection treatment via a randomized controlled study.

METHODS

A total of 910 participants treated with 8 weeks of once-weekly rifapentine plus isoniazid (group A), 890 treated with 6 weeks of twice-weekly rifapentine plus isoniazid (group B) and 818 untreated controls (group C) were followed for 2 years to track active TB development. QFT-GIT tests were repeated three times for all groups: before treatment (T0), at completion of treatment (T1) and 3 months after completion of treatment (T2).

RESULTS

Similar rates of persistent QFT-GIT reversion were observed in groups A (19.0%, 173/910), B (18.5%, 165/890) and C (20.7%, 169/818) (p 0.512). The dynamic changes of IFN-γ levels were not statistically significant among the three groups. In treated participants, individuals with higher baseline IFN-γ levels showed increased TB occurrence (1.0%, 9/896) compared to those with lower baseline levels (0.2%, 2/904) (p 0.037). A similar but statistically insignificant trend was also observed in untreated controls (1.8% (7/400) vs. 0.5% (2/418), p 0.100). When TB cases were matched with non-TB cases on baseline IFN-γ levels, no significant differences were found with respect to the dynamic changes in IFN-γ levels with time, regardless of whether they received treatment.

CONCLUSIONS

QFT-GIT reversion or decreased IFN-γ levels should not be used for monitoring host response to latent TB infection treatment.

[Spectrum analysis of pathological classification in 463 cases with nasal and paranasal sinuses malignant tumors]

Objective:The characteristics of pathological histological classification of nasal and paranasal sinuses malignant tumors in the past 10 years were analyzed, so as to provide possible basis, direction and ideas for the development of relevant effective treatment measures for nasal and paranasal sinuses malignant tumors in clinical practice. Method:The clinical data of patients with nasal and paranasal sinuses malignant tumors admitted to PLA general hospital from January 2009 to December 2018 were collected. Pathological types were retrospectively analyzed, and disease spectrum distribution, composition ratio and variation tendency of these patients were calculated. Result:Among the 463 patients, the overall pathological types in the top 5 were as follows: squamous cell carcinoma, adenoid cystadenocarcinoma, olfactory neuroblastoma, melanoma, adenocarcinoma. As for male patients, the pathological types in the top 5 were squamous cell carcinoma, adenoid cystic carcinoma, olfactory neuroblastoma, adenocarcinoma, neuroendocrine carcinoma and rhabdomyosarcoma were tied for fifth; the top 5 most common pathological types in female patients were squamous cell carcinoma, adenoid cystic carcinoma, melanoma, rhabdomyosarcoma, and adenocarcinoma. From 2009 to 2013, there were 183 patients with nasal and paranasal sinuses malignant tumors, the top 5 pathological types were squamous cell carcinoma, adenoid cystadenocarcinoma, olfactory neuroblastoma, melanoma, neuroendocrine carcinoma and rhabdomyosarcoma were tied for fifth; From 2014 to 2018, 280 patients with nasal and paranasal sinuses malignant tumors were diagnosed, the top 5 pathological types were squamous cell carcinoma, adenoid cystadenocarcinoma, melanoma, adenocarcinoma, and rhabdomyosarcoma. The ratio of the number of patients from 2009 to 2013 and 2014 to 2018 was about 0.65∶1. Malignant tumors of the nasal and paranasal sinuses tend to occur between the ages of 41 and 60, and the pathological types in the top 5 were squamous cell carcinoma,adenoid cystic carcinoma, adenocarcinoma, melanoma, neuroendocrine carcinoma. Conclusion:Malignant tumors of nasal cavity and sinus were more common in male, and the pathological types such as squamous cell carcinoma, adenoid cystic carcinoma, olfactory neuroblastoma were more common. All age groups have the disease, but the age group of 41-60 years old is the high-risk group of nasal and nasal sinus malignant tumors. However, the incidence rate of melanoma has gradually increased in the past five years, which needs to be paid more attention to.

The emission of γ-Ray beams with orbital angular momentum in laser-driven micro-channel plasma target

We investigated the emission of multi-MeV γ-Ray beams with orbital angular momentum (OAM) from the interaction of an intense circularly polarized (CP) laser with a micro-channel plasma target. The driving laser can generate high energy electrons via direct laser acceleration within the channel. By attaching a plasma foil as the reflecting mirror, the CP laser is reflected and automatically colliding with the electrons. High energy gamma-photons are emitted through inverse Compton scattering (ICS) during collision. Three-dimensional particle-in-cell simulations reveal that the spin angular momentum (SAM) of the CP laser can be transferred to the OAM of accelerated electrons and further to the emitted gamma-ray beam. These results may guide future experiments in laser-driven gamma-ray sources using micro-structures.

A multi-layered computational model for wrinkling of human skin predicts aging effects

The development and progression of wrinkles from young to aged human skin relates to both structural and mechanical changes induced by aging. Here we aim to better understand the interaction of skin's layered morphology with dynamic wrinkles predicted in young and aged skin. First, we compare the predictions of wrinkling from 3-D finite element models of human skin including two to six distinct and anatomically motivated layers. Second, we perform parametric analyses using our six-layered model to determine how age-related changes in the architecture of human skin affect dynamic surface wrinkling. Specifically, we consider the following aging-related changes in the morphology of skin: flattening of the dermal-epidermal junction (DEJ) interface; thinning of both the viable epidermis (VE) and the reticular dermis (RD); and thickening of the papillary dermis (PD). We use skin compression to model dynamic, expressional wrinkles due to muscle contraction, and volumetric tissue loss to model effects of aging in wrinkling simulations. Our results highlight the role of skin's multi-layered structure in the modeling of wrinkling formation. Our six-layered model, consisting of all of the mechanical layers, predicts deep wrinkles with better fidelity than models including fewer layers. From our parametric study, applying our six-layered model, we conclude that: (1) the relative thicknesses of the layers in the epidermis or dermis significantly influences surface wrinkling in skin; and, (2) flattening of the DEJ with aging enhances surface wrinkling. Thinning of VE increases the relative stiffness of the epidermis and thus enhances dynamic wrinkling, while thickening of PD or thinning of RD has the same effect by reducing the equivalent stiffness of the substrate. Consequently, strategies to minimize wrinkling could maintain the undulating morphology of the DEJ, thereby delaying dynamic wrinkling and delaying the propagation of buckling into the deeper dermis or hypodermis. Additional strategies to minimize wrinkling could target preventing the VE and RD from thinning or preventing the PD from thickening.

[The status analysis of diagnosis and treatment of synchronous peritoneal carcinomatosis from colorectal cancer in China: a report of 1 003 cases in 16 domestic medical centers]

Objective: To analyze the status of domestic surgical treatment of synchronous peritoneal carcinomatosis from colorectal cancer in China. Methods: Clinicopathological data of patients who underwent surgery from October 2003 to October 2018 in 16 domestic medical centers was retrospectively analyzed. Excel database was created which covered 77 fields of 7 parts: baseline information of patients, laboratory tests, imaging tests, chemoradiotherapy information, intra-operative findings, postoperative pathology and follow-up data. The Wilcoxon rank-sum test was used for comparison of the measurement data between groups. The χ(2) test was used for comparison of the categorical data between groups. The survival curve was calculated by the Kaplan-Meier method. Results: Of the 1 003 patients, there were 575 male and 428 female patients with the age of (58.5±14.1) years (range: 18 to 92 years). In a total of 920 patients, the carcinoma of sigmoid colon was performed in 292 cases (31.8%) with the highest ratio. The proportion of patients with liver metastasis and lung metastasis were 27.9% (219/784) and 8.3% (64/769). Preoperative detection of carcino-embryonic antigen level was the most common method in China (87.74%, 880/1 003), and the positive rate was 64.5% (568/880). The correct rate of preoperative imaging tests was 40.7% (280/688). The ratio of peritoneal carcinomatosis index (PCI) scores between 0 and 10 was the highest (59.6%, 170/285). Two hundred and sixty-two (27.0%) patients were performed by totally laparoscopic operation in 971 patients. The resection of primary tumor was performed in 588 of the 817 patients (72.0%). In a total of 457 cases, 253 (55.4%) patients were performed cytoreduction which group scored completeness of cytoreduction (CCR) 0. The postoperative hyperthermic intraperitoneal chemotherapy was implemented in 70 of the 334 cases (21.0%). Among 1 003 cases, 562 cases (56.03%) had complete follow-up data and the median overall survival was 15 months. The primary tumor resection and the CCR scores were affected by the PCI scores. The patients underwent primary tumor resection (187/205 vs. 26/80, χ(2)=105.085, P=0.000) and the patients were performed cytoreduction which scored CCR 0 or CCR 1 (162/204 vs. 8/78, Z=-10.465, P=0.000) had significant difference between the groups of PCI<20 and ≥20. There was a close correlation between the surgical method and the CCR scores (Z=-3.246,P=0.001).When the maximum degree of tumor reduction was planned, most surgeons would choose laparotomy. The overall survival time was longer in patients with primary tumor resection (P=0.000). The median survival time was 18.6 months in the group of primary tumor resection. Conclusions: It is difficult to diagnose the synchronous peritoneal carcinomatosis from colorectal cancer before the operation. Primary tumor resection has an obvious effect to prolong the survival time. It is necessary to standardize the treatment of peritoneal metastasis.

[Situation analysis of timing of first visit of anti-mitochondrial antibody-positive patients]

Objective: To understand the basic information of anti-mitochondrial antibody (anti-AMA)-positive patients after initial diagnosis, and to set groundwork for further exploring the clinical significance of AMA in various diseases. Methods: Demographic data and related clinical information recorded through the Information System of Peking University People's Hospital from January 2013 to December 2016 were collected. Patients whose AMA and/or AMA-M2 first- tested as positive were recorded. Complications were classified according to the International Classification of Diseases. Results: A total of 1323 AMA positive cases were discovered for the first time. Among them, 78.0% were women, and the age of initial diagnosis was 56.8 ± 16.0 years. The first three initially diagnosed departments were rheumatology and immunology (37.4%), liver Disease (15.9%) and hematology (15.9%) relevant to musculoskeletal and connective tissue diseases (45.2%), hematology and hematopoietic organs and immune diseases (30.6%) and circulatory system diseases (29.7%). There were 297 newly confirmed cases of primary biliary cholangitis (PBC); accounting for 89.2% of women, and the age of initial diagnosis was 60.1 ± 12.4 years. The top three departments of initially diagnosed as PBC were liver disease (37.7%), rheumatology (33.0%) and gastroenterology (15.2%), of which 39.7% had musculoskeletal and connective tissue diseases, 27.9% had circulatory diseases, and 24.9 % were combined with endocrine and metabolic diseases. Conclusion: Besides PBC and other autoimmune diseases, AMA and / or AMA-M2 positivity can be observed in a variety of diseases in several clinical departments, and its clinical significance remains to be further clarified.

Risk factors of perioperative complications and transfusion following total hip arthroplasty in systemic lupus erythematosus patients

BACKGROUND

In recent years, hip arthroplasty rates in systemic lupus erythematosus (SLE) patients have been increasing rapidly. Although patients with SLE generally show beneficial or desirable functional outcomes following total hip arthroplasty (THA), it has been reported that SLE patients after THA have increased risk of postoperative complications, especially during the period of hospitalization.

OBJECTIVES

In the present study, we aimed to identify possible factors associated with complications or transfusion of THA in SLE patients during hospitalization.

METHODS

The present study was a retrospective study conducted in Peking Union Medical College Hospital. Data were collected from medical records of patients who underwent THA from January 2012 to June 2018. The primary outcome variable was perioperative complications, which was defined as having one or more of the following conditions: high fever, infection, impaired wound healing, venous thrombosis of the lower extremities, hematoma, arrhythmia, implant complications. The secondary outcome was perioperative transfusion.

RESULTS

During January 2012 to June 2018, 100 patients had taken the surgery of THA. After multivariate analysis, independent risk factors for perioperative complications were: age ≥ 45 years (p = 0.001), SLE with other connective tissue diseases (p = 0.029), high temperature (p = 0.030), positive anti-dsDNA antibody (p = 0.043), and Systemic Lupus International Collaborative Clinics/American College of Rheumatology (SLICC/ACR) Damage Index ≥ 3 (p = 0.008). Independent risk factors for perioperative transfusion were bilateral THA (p = 0.029), low hemoglobin (p = 0.021) and abnormal renal function (p = 0.021).

CONCLUSION

For SLE patients following THA, age > 45 years, SLE with other connective tissue disease, high temperature, positive anti-dsDNA antibody and SLICC/ACR Damage Index ≥ 3 were the risk factors of complications during hospitalization and bilateral THA, low hemoglobin and abnormal renal function were the risk factors of transfusion.

[Qualitative pathological assessment of liver fibrosis regression after antiviral therapy in patients with chronic hepatitis B]

Objective: To investigate the methods for qualitative pathological assessment of dynamic changes in liver fibrosis/cirrhosis after antiviral therapy in patients with chronic hepatitis B (CHB), since antiviral therapy can partially reverse liver fibrosis and cirrhosis caused by hepatitis B and semi-quantitative, rather than qualitative, pathological assessment is often used for the research on liver fibrosis regression. Methods: Previously untreated CHB patients with liver fibrosis and cirrhosis were enrolled, and liver biopsy was performed before treatment and at 78 weeks after the antiviral therapy based on entecavir. The follow-up assessment was performed once every half a year. Based on the proportion of different types of fibrous septum, we put forward the new qualitative criteria called P-I-R classification (predominantly progressive, predominantly regressive, and indeterminate) for evaluating dynamic changes in liver fibrosis. This classification or Ishak fibrosis stage was used to evaluate the change in liver fibrosis after treatment and Ishak liver inflammation score was used to evaluate the change in liver inflammation after treatment. Results: A total of 112 CHB patients who underwent liver biopsy before and after treatment were enrolled, and among these patients, 71 with an Ishak stage of ≥3 and qualified results of live biopsy were included in the final analysis. Based on the P-I-R classification, 58% (41/71) were classified as predominantly progressive, 29% (21/71) were classified as indeterminate, and 13% (9/71) were classified as predominantly regressive; there were no significant differences between the three groups in alanine aminotransferase, aspartate aminotransferase, albumin, HBeAg positive rate, HBV DNA, and liver stiffness (P < 0.05). After treatment, the proportion of predominantly progressive, indeterminate, or predominantly regressive patients changed to 11% (8/71), 11% (8/71), and 78% (55/71), respectively. Among the 35 patients who had no change in Ishak stage after treatment, 72% (25/35) were classified as predominantly regressive and had certain reductions in the Laennec score, percentage of collagen area, and liver stiffness. Conclusion: This new P-I-R classification can be used to assess the dynamic changes in liver fibrosis after antiviral therapy in CHB patients.

[Incidence of depressive disorders and related independent risk factors in patients with chronic hepatitis C]

Objective: To investigate the incidence and related independent risk factors of depression in treatment-naïve Han ethnic Chinese patients with chronic hepatitis C. Methods: Nine hundred and ninety-seven Han Chinese patients with confirmed chronic HCV infection were enrolled. Beck's depression inventory scale was used to assess depression score. Patients were divided into two groups according to the score: score≥17, depression group (16.85%, 168/997); score <17, no depression group (83.15%, 829/997). Multivariate logistic regression was used to analyze independent risk factors related with the onset of depression in patients with chronic hepatitis C. Results: There was a statistically significant difference between the two groups in terms of gender distribution, marital status, education level, income level and smoking status (P < 0.05). Independent risk factors were female [odds ratio (OR) = 3.85; 95% CI: 2.28-6.50, P = 0.001], decompensated cirrhosis [OR = 2.31; 95% CI: 1.20-4.48, P = 0.013], unmarried [OR = 2.01; 95% CI: 1.12-3.60, P = 0.019], separated [OR = 17.39; 95% CI: 1.64-184.47, P = 0.018], divorced [OR = 3.82; 95% CI: 1.36-10.74, P = 0.011], without higher education [OR = 2.04; 95% CI: 1.22-3.42, P = 0.007], low income [OR = 3.94; 95% CI: 1.38-11.28, P = 0.011], middle income [OR = 2.96; 95% CI: 1.02-8.62, P = 0.047], uninterrupted smoking [OR = 3.67; 95% CI: 2.13-6.31, P = 0.001], and previously smoked [OR = 3.33, 95% CI: 1.66-6.68, P = 0.001]. Conclusion: The incidence of depression in patients with chronic hepatitis C is relatively high. The independent risk factors related with depression include female, unmarried, separated, and divorced, without higher education, low and middle-income level, smoking and disease progression to decompensated cirrhosis, but no significant correlation between hepatitis C virus genotypes and viral load.

[Proper patient education improves hepatitis C patients' disease-related knowledge and antiviral treatment acceptance in rural China]

Objective: To evaluate the affect of hepatitis C virus (HCV) education in chronic hepatitis C patients' disease related knowledge and antiviral treatment acceptance in rural china. Methods: Rural HCV patients of attended CHC project of HCV education. Doctor delivered subsequent interactive lecture, and patients completed pre- and post-education questionnaires before and after taking the lectures. Results: 151 CHC patients were included. Mean age was 57.3 years old, 50.3% were male, 51.0% of the students had primary school education or illiterate, and 76.2% had a monthly income below RMB 3,000. 98.0% of patients defined their baseline HCV knowledge as "nothing" or "a little bit". A multivariate analysis reveled baseline knowledge scores were associated with age and household income. After education, mean knowledge score (range: 0-28) increased from 13.1 to 23.0 (P < 0.001) and average percent of patients with correct answers from the topic rose from 46.8% to 82.1% (P < 0.001), and patients' antiviral treatment acceptance increased from 33.9% to 65.6% (P < 0.001). Conclusion: A rural Chinese patients had less education, HCV education delivered on the preferred format of patients substantially improved hepatitis C patients' disease-related knowledge and antiviral treatment acceptance in rural china.