Challenges facing minimal residual disease testing for acute myeloid leukemia and promising strategies to overcome them.

INTRODUCTION: Minimal residual disease (MRD) has been an important biomarker for relapse prediction and treatment choice in patients with acute myeloid leukemia (AML). False-positive or false-negative MRD results due to the low specificity and sensitivity of techniques such as multiparameter flow cytometry (MFC), real-time quantitative polymerase chain reaction, and next-generation sequencing, as well as the biological characteristics of residual leukemia cells, including antigen shift, clone involution, heterogeneous genome of the blast cells, and lack of specific targets, all restrict the clinical use of MRD. AREAS COVERED: We summarized the challenges of the techniques for MRD detection, and their application in the clinical setting. We also discussed strategies to overcome these challenges, such as the MFC MRD method based on leukemia stem cells, single-cell DNA sequencing or single-cell RNA sequencing for the investigation of biological characteristics of residual leukemia cells, and the potential of omics techniques for MRD detection. We further noted out that prospective clinical trials are needed to answer clinical questions related to MRD in patients with AML. EXPERT OPINION: MRD is an important biomarker for individual therapy of patients with AML. In the future, it is important to increase the specificity and sensitivity of the detection techniques.

The added value of apparent diffusion coefficient and microcalcifications to the Kaiser score in the evaluation of BI-RADS 4 lesions.

PURPOSE: To explore the added value of combining microcalcifications or apparent diffusion coefficient (ADC) with the Kaiser score (KS) for diagnosing BI-RADS 4 lesions. METHODS: This retrospective study included 194 consecutive patients with 201 histologically verified BI-RADS 4 lesions. Two radiologists assigned the KS value to each lesion. Adding microcalcifications, ADC, or both these criteria to the KS yielded KS1, KS2, and KS3, respectively. The potential of all four scores to avoid unnecessary biopsies was assessed using the sensitivity and specificity. Diagnostic performance was evaluated by the area under the curve (AUC) and compared between KS and KS1. RESULTS: The sensitivity of KS, KS1, KS2, and KS3 ranged from 77.1% to 100.0%.KS1 yielded significantly higher sensitivity than other methods (P < 0.05), except for KS3 (P > 0.05), most of all, when assessing NME lesions. For mass lesions, the sensitivity of these four scores was comparable (p > 0.05). The specificity of KS, KS1, KS2, and KS3 ranged from 56.0% to 69.4%, with no statistically significant differences(P > 0.05), except between KS1 and KS2 (p < 0.05).The AUC of KS1 (0.877) was significantly higher than that of KS (0.837; P = 0.0005), particularly for assessing NME (0.847 vs 0.713; P < 0.0001). CONCLUSION: KS can stratify BI-RADS 4 lesions to avoid unnecessary biopsies. Adding microcalcifications, but not adding ADC, as an adjunct to KS improves diagnostic performance, particularly for NME lesions. ADC provides no additional diagnostic benefit to KS. Thus, only combining microcalcifications with KS is most conducive to clinical practice.

Development and validation of a clinical predictive model for 1-year prognosis in coronary heart disease patients combine with acute heart failure.

Background: The risk factors for acute heart failure (AHF) vary, reducing the accuracy and convenience of AHF prediction. The most common causes of AHF are coronary heart disease (CHD). A short-term clinical predictive model is needed to predict the outcome of AHF, which can help guide early therapeutic intervention. This study aimed to develop a clinical predictive model for 1-year prognosis in CHD patients combined with AHF. Materials and methods: A retrospective analysis was performed on data of 692 patients CHD combined with AHF admitted between January 2020 and December 2020 at a single center. After systemic treatment, patients were discharged and followed up for 1-year for major adverse cardiovascular events (MACE). The clinical characteristics of all patients were collected. Patients were randomly divided into the training (n = 484) and validation cohort (n = 208). Step-wise regression using the Akaike information criterion was performed to select predictors associated with 1-year MACE prognosis. A clinical predictive model was constructed based on the selected predictors. The predictive performance and discriminative ability of the predictive model were determined using the area under the curve, calibration curve, and clinical usefulness. Results: On step-wise regression analysis of the training cohort, predictors for MACE of CHD patients combined with AHF were diabetes, NYHA ≥ 3, HF history, Hcy, Lp-PLA2, and NT-proBNP, which were incorporated into the predictive model. The AUC of the predictive model was 0.847 [95% confidence interval (CI): 0.811-0.882] in the training cohort and 0.839 (95% CI: 0.780-0.893) in the validation cohort. The calibration curve indicated good agreement between prediction by nomogram and actual observation. Decision curve analysis showed that the nomogram was clinically useful. Conclusion: The proposed clinical prediction model we have established is effective, which can accurately predict the occurrence of early MACE in CHD patients combined with AHF.

Predictive Value of Non-high-Density Lipoprotein Cholesterol and Neutrophil-Lymphocyte Ratio for Coronary Artery Vulnerable Plaques in Type 2 Diabetes Mellitus.

Background: Patients with diabetes have an increased risk of developing vulnerable plaques (VPs), in which dyslipidemia and chronic inflammation play important roles. Non-high-density lipoprotein cholesterol (non-HDL-C) and neutrophil-lymphocyte ratio (NLR) have emerged as potential markers of both coronary artery VPs and cardiovascular prognosis. This study aimed to investigate the predictive value of non-HDL-C and NLR for coronary artery VPs in patients with type 2 diabetes mellitus (T2DM). Methods: We retrospectively enrolled 204 patients with T2DM who underwent coronary computed tomography angiography between January 2018 and June 2020. Clinical data including age, sex, hypertension, smoking, total cholesterol, low-density lipoprotein cholesterol, HDL-C, triglyceride, non-HDL-C, glycated hemoglobin, neutrophil count, lymphocyte count, NLR, and platelet count were analyzed. Multivariate logistic regression was used to estimate the association between non-HDL-C, NLR, and coronary artery VPs. Receiver operating curve analysis was performed to evaluate the value of non-HDL-C, NLR, and their combination in predicting coronary artery VPs. Results: In our study, 67 patients (32.84%) were diagnosed with VPs, 75 (36.77%) with non-VP, and 62 (30.39%) with no plaque. Non-HDL-C and NLR were independent risk factors for coronary artery VPs in patients with T2DM. The areas under the ROC curve of non-HDL-C, NLR, and their combination were 0.748 [95% confidence interval (CI): 0.676-0.818], 0.729 (95% CI: 0.650-0.800), and 0.825 (95% CI: 0.757-0.887), respectively. Conclusion: Either non-HDL-C or NLR could be used as a predictor of coronary artery VPs in patients with T2DM, but the predictive efficiency and sensitivity of their combination would be better.

Prevalence of Chromosomally Located blaCTX-M-55 in Salmonella Typhimurium ST34 Isolates Recovered from a Tertiary Hospital in Guangzhou, China.

Nontyphoidal Salmonella (NTS) is one of the most prevalent bacterial causes of gastrointestinal infections worldwide. Meanwhile, the detection rate of CTX-M-55 ESBL-positive has increased gradually in China. To identify the molecular epidemiological and genomic characteristics of blaCTX-M-55-carrying nontyphoidal Salmonella (NTS) clinical isolates, a total of 105 NTS isolates were collected from a Chinese tertiary hospital. Antimicrobial susceptibility testing was performed to determine the resistance phenotype. Whole-genome sequencing and bioinformatics analysis were used to determine the antimicrobial resistance genes, serotypes, phylogenetic relationships, and the genetic environment of the blaCTX-M-55 gene. The results showed that among the 22 ceftriaxone resistant isolates, the blaCTX-M-55 was the most common ß-Lactamase gene carried by 14 isolates, including serotypes S. Typhimurium (10/14), S. Muenster (2/14), S. Rissen (1/14), and S. Saintpaul (1/14). Phylogenetic analysis shows that 10 blaCTX-M-55-positive S. Typhimurium ST34 isolates were divided into two clusters. The genetic relationship of isolates in each cluster was very close (≤10 cgMLST loci). The blaCTX-M-55 gene was located on the chromosome in 10 isolates, on IncI1 plasmid in three isolates, and IncHI2 plasmid in one isolate. In conclusion, the blaCTX-M-55 gene, mainly located on the chromosome of S. Typhimurium ST34 isolates, was the main driving force associated with the resistance of NTS to cephalosporins. Therefore, close attention to the clonal dissemination of blaCTX-M-55-carrying S. Typhimurium ST34 in clinical settings must be monitored carefully. IMPORTANCE ESCs are the first choice for treating NTS infections. However, ESBLs and AmpC ß-lactamases are the most typical cause for ESCs resistance. The CTX-M-55 ESBL-positive rate has gradually increased in the clinic in recent years. At present, the research about blaCTX-M-55-positive Salmonella mainly focuses on the foodborne animals or the environment while less on clinical patients. Thus, this study was carried out for identifying molecular epidemiological and genomic characteristics of blaCTX-M-55-carrying NTS clinical isolates. The results showed that the blaCTX-M-55 gene, mainly located on the chromosome of S. Typhimurium ST34 isolates from Conghua District, was the main driving force associated with the resistance of NTS to cephalosporins. Therefore, our work highlights the importance of monitoring the clonal dissemination of blaCTX-M-55-carrying S. Typhimurium ST34 in clinical settings.

Effects of the Surface Structure on the Water Transport Behavior in PEMFC Carbon Fiber Papers.

In this paper, three kinds of carbon fiber papers (CFPs), including pure CFP, poly(tetrafluoroethylene) (PTFE)-treated CFP (PTFE-CFP), and microporous layer (MPL)-coated CFP (MPL-CFP), were used to investigate the effects of the surface structure on the water transport behavior in CFPs. Compared to pure CFP, applying PTFE on the CFP increases the breakthrough pressure by 0.2 times, while it decreases the water flow rate at initial penetration by 0.06 times, owing to the strong hydrophobicity of PTFE-CFP. The pore diameter of MPL-CFP reduces sharply after coating the MPL, which leads to increasing breakthrough pressure by 0.6 times. The Young-Laplace equation is applied to study the relationship between the structure (wettability and pore-size distribution) of CFPs and the water transport behavior (breakthrough pressure), and the results show that in addition to wettability and pore size, the pore-size gradient also plays a crucial role in water transport.

Intravoxel Incoherent Motion Magnetic Resonance Imaging for Prediction of Induction Chemotherapy Response in Locally Advanced Hypopharyngeal Carcinoma: Comparison With Model-Free Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

BACKGROUND: Multiparametric intravoxel incoherent motion (IVIM) provides diffusion and perfusion information for the treatment prediction of cancer. However, the superiority of IVIM over dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in locally advanced hypopharyngeal carcinoma (LAHC) remains unclear. PURPOSE: To compare the diagnostic performance of IVIM and model-free DCE in assessing induction chemotherapy (IC) response in patients with LAHC. STUDY TYPE: Prospective. POPULATION: Forty-two patients with LAHC. FIELD STRENGTH/SEQUENCE: 3.0 T MRI, including IVIM (12 b values, 0-800 seconds/mm2 ) with a single-shot echo planar imaging sequence and DCE-MRI with a volumetric interpolated breath-hold examination sequence. IVIM MRI is a commercially available sequence and software for calculation and analysis from vendor. ASSESSMENT: The IVIM-derived parameters (diffusion coefficient [D], pseudodiffusion coefficient [D*], and perfusion fraction [f]) and DCE-derived model-free parameters (Wash-in, time to maximum enhancement [Tmax], maximum enhancement [Emax], area under enhancement curve [AUC] over 60 seconds [AUC60 ], and whole area under enhancement curve [AUCw ]) were measured. At the end of IC, patients with complete or partial response were classified as responders according to the Response Evaluation Criteria in Solid Tumors. STATISTICAL TESTS: The differences of parameters between responders and nonresponders were assessed using Mann-Whitney U tests. The performance of parameters for predicting IC response was evaluated by the receiver operating characteristic curves. RESULTS: Twenty-three (54.8%) patients were classified as responders. Compared with nonresponders, the perfusion parameters D*, f, f × D*, and AUCw were significantly higher whereas Wash-in was lower in responders (all P-values <0.05). The f × D* outperformed other parameters, with an AUC of 0.84 (95% confidence interval [CI]: 0.69-0.93), sensitivity of 79.0% (95% CI: 54.4-93.9), and specificity of 82.6% (95% CI: 61.2-95.0). DATA CONCLUSION: The IVIM MRI technique may noninvasively help predict the IC response before treatment in patients with LAHC. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

A Nomogram for Pretreatment Prediction of Response to Induction Chemotherapy in Locally Advanced Hypopharyngeal Carcinoma.

BACKGROUND: Induction chemotherapy (IC) significantly improves the rate of larynx preservation; however, some patients could not benefit from it. Hence, it is of clinical importance to predict the response to IC to determine the necessity of IC. We aimed to develop a clinical nomogram for predicting the treatment response to IC in locally advanced hypopharyngeal carcinoma. METHODS: We retrospectively include a total of 127 patients with locally advanced hypopharyngeal carcinoma who underwent MRI scans prior to IC between January 2014 and December 2017. The clinical characteristics were collected, which included age, sex, tumor location, invading sites, histological grades, T-stage, N-stage, overall stage, size of the largest lymph node, neutrophil-to-lymphocyte ratio, hemoglobin concentration, and platelet count. Univariate and multivariate logistic regression was used to select the significant predictors of IC response. A nomogram was built based on the results of stepwise logistic regression analysis. The predictive performance and clinical usefulness of the nomogram were determined based on the area under the curve (AUC), calibration curve, and decision curve. RESULTS: Age, T-stage, hemoglobin, and platelet were four independent predictors of IC treatment response, which were incorporated into the nomogram. The AUC of the nomogram was 0.860 (95% confidence interval [CI]: 0.780-0.940), which was validated using 3-fold cross-validation (AUC, 0.864; 95% CI: 0.755-0.973). The calibration curve demonstrated good consistency between the prediction by the nomogram and actual observation. Decision curve analysis shows that the nomogram was clinically useful. CONCLUSION: The proposed nomogram resulted in an accurate prediction of the efficacy of IC for patients with locally advanced hypopharyngeal carcinoma.

Comparison between linear and nonlinear machine-learning algorithms for the classification of thyroid nodules.

BACKGROUND: A key challenge in thyroid carcinoma is preoperatively diagnosing malignant thyroid nodules. The purpose of this study was to compare the classification performance of linear and nonlinear machine-learning algorithms for the evaluation of thyroid nodules using pathological reports as reference standard. METHODS: Ethical approval was obtained for this retrospective analysis, and the informed consent requirement was waived. A total of 1179 thyroid nodules (training cohort, n = 700; validation cohort, n = 479) were confirmed by pathological reports or fine-needle aspiration (FNA) biopsy. The following ultrasonography (US) featu res were measured for each nodule: size (maximum diameter), margins, shape, aspect ratio, capsule, hypoechoic halo, composition, echogenicity, calcification pattern, vascularity, and cervical lymph node status. We analyzed five nonlinear and three linear machine-learning algorithms. The diagnostic performance of each algorithm was compared by using the area under the curve (AUC) of the receiver operating characteristic curve. We repeated this process 1000 times to obtain the mean AUC and 95% confidence interval (CI). RESULTS: Overall, nonlinear machine-learning algorithms demonstrated similar AUCs compared with linear algorithms. The Random Forest and Kernel Support Vector Machines algorithms achieved slightly greater AUCs in the validation cohort (0.954, 95% CI: 0.939-0.969; 0.954 95%CI: 0.939-0.969, respectively) than other algorithms. CONCLUSIONS: Overall, nonlinear machine-learning algorithms share similar performance compared with linear algorithms for the evaluation the malignancy risk of thyroid nodules.

A nomogram for individual prediction of vascular invasion in primary breast cancer.

OBJECTIVES: To explore the feasibility of preoperative prediction of vascular invasion (VI) in breast cancer patients using nomogram based on multiparametric MRI and pathological reports. METHODS: We retrospectively collected 200 patients with confirmed breast cancer between January 2016 and January 2018. All patients underwent MRI examinations before the surgery. VI was identified by postoperative pathology. The 200 patients were randomly divided into training (n = 100) and validation datasets (n = 100) at a ratio of 1:1. Least absolute shrinkage and selection operator (LASSO) regression was used to select predictors most associated with VI of breast cancer. A nomogram was constructed to calculate the area under the curve (AUC) of receiver operating characteristics, sensitivity, specificity, accuracy, positive prediction value (PPV) and negative prediction value (NPV). We bootstrapped the data for 2000 times without setting the random seed to obtain corrected results. RESULTS: VI was observed in 79 patients (39.5%). LASSO selected 10 predictors associated with VI. In the training dataset, the AUC for nomogram was 0.94 (95% confidence interval [CI]: 0.89-0.99, the sensitivity was 78.9% (95%CI: 72.4%-89.1%), the specificity was 95.3% (95%CI: 89.1%-100.0%), the accuracy was 86.0% (95%CI: 82.0%-92.0%), the PPV was 95.7% (95%CI: 90.0%-100.0%), and the NPV was 77.4% (95%CI: 67.8%-87.0%). In the validation dataset, the AUC for nomogram was 0.89 (95%CI: 0.83-0.95), the sensitivity was 70.3% (95%CI: 60.7%-79.2%), the specificity was 88.9% (95%CI: 80.0%-97.1%), the accuracy was 77.0% (95%CI: 70.0%-83.0%), the PPV was 91.8% (95%CI: 85.3%-98.0%), and the NPV was 62.7% (95%CI: 51.7%-74.0%). The nomogram calibration curve shows good agreement between the predicted probability and the actual probability. CONCLUSION: The proposed nomogram could be used to predict VI in breast cancer patients, which was helpful for clinical decision-making.

Development and validation of an ultrasound-based nomogram to improve the diagnostic accuracy for malignant thyroid nodules.

OBJECTIVES: The aim of this study was to develop an ultrasound-based nomogram to improve the diagnostic accuracy of the identification of malignant thyroid nodules. METHODS: A total of 1675 histologically proven thyroid nodules (1169 benign, 506 malignant) were included in this study. The nodules were grouped into the training dataset (n = 700), internal validation dataset (n = 479), or external validation dataset (n = 496). The grayscale ultrasound features included the nodule size, shape, aspect ratio, echogenicity, margins, and calcification pattern. We applied least absolute shrinkage and selection operator (lasso) regression to select the strongest features for the nomogram. Nomogram discrimination (area under the receiver operating characteristic curve, AUC) and calibration were assessed. The nomogram was subjected to bootstrapping validation (1000 bootstrap resamples) to calculate a mean AUC and 95% confidence interval (CI). RESULTS: The nomogram showed good discrimination in the training dataset, with an AUC of 0.936 (95% CI: 0.918-0.953) and good calibration. Application of the nomogram to the internal validation dataset also resulted in good discrimination (AUC: 0.935; 95% CI, 0.915-0.954) and good calibration. The model tested in an external validation dataset demonstrated a lower AUC of 0.782 (95% CI: 0.776-0.789). CONCLUSIONS: This ultrasound-based nomogram can be used to quantify the probability of malignant thyroid nodules. KEY POINTS: • Ultrasound examination is helpful in the differential diagnosis of malignant and benign thyroid nodules. • However, ultrasound accuracy relies heavily on examiner experience. • A less subjective diagnostic model is desired, and the developed nomogram for thyroid nodules showed good discrimination and good calibration.

Development of a preprocedure nomogram for predicting contrast-induced acute kidney injury after coronary angiography or percutaneous coronary intervention.

Most of the risk models for predicting contrast-induced acute kidney injury (CI-AKI) are available for postcontrast exposure prediction, thus have limited values in practice. We aimed to develop a novel nomogram based on preprocedural features for early prediction of CI-AKI in patients after coronary angiography (CAG) or percutaneous coronary intervention (PCI). A total of 245 patients were retrospectively reviewed from January 2015 to January 2017. Least absolute shrinkage and selection operator (Lasso) regression model was applied to select most strong predictors for CI-AKI. The CI-AKI risk score was calculated for each patient as a linear combination of selected predictors that were weighted by their respective coefficients. The discrimination of nomogram was assessed by C-statistic. The occurrence of CI-AKI was 13.9% (34 out of 245). We identified ten predictors including sex, diabetes mellitus, lactate dehydrogenase level, C-reactive protein, years since drinking, chronic kidney disease (CKD), stage of CKD, stroke, acute myocardial infarction, and systolic blood pressure. The CI-AKI prediction nomogram obtained good discrimination (C-statistic, 0.718, 95%CI: 0.637-0.800, p = 7.23 × 10-5). The cutoff value of CI-AKI risk score was -1.953. Accordingly, the novel nomogram we developed is a simple and accurate tool for preprocedural prediction of CI-AKI in patients undergoing CAG or PCI.

Beneficial effect of tripterine on systemic lupus erythematosus induced by active chromatin in BALB/c mice.

The aim of this study was to determine whether tripterine, isolated from Tripterygium wilfordii Hoog f. in China, had beneficial effects on experimental systemic lupus erythematosus induced by active chromatin in BALB/c mice. BALB/c mice were immunized with active chromatin isolated from concanavalin A-activated syngenetic spleno-lymphocytes on day 0. Tripterine 6 or 12 mg kg(-1) day(-1), or prednisone 5 mg kg(-1) day(-1) was given to BALB/c mice intragastrically from day 35 to day 50. Treatment with tripterine 12 mg kg(-1) day(-1) for 15 days protected renal from glomerular injury with a concomitant reduction of serum autoantibodies and total immunoglobulin G (IgG) also with a improvement of splenocyte proliferation stimulated with concanavalin A and lipopolysaccharide. The effects were associated with reduced interleukin-10 production and serum nitric oxide (NO) level but not interferon-gamma compared with vehicle-treated control group. Tripterine 6 mg kg(-1) day(-1) had no significant protective effect against glomerular injury. It inhibited autoantibodies and interleukin-10 production but had no effect on splenocyte proliferation, serum NO level, and interferon-gamma production. These findings suggested that tripterine had a beneficial effect on systemic lupus erythematosus induced by active chromatin in BALB/c mice.

Induction of systemic lupus erythematosus syndrome in BALB/c mice by immunization with active chromatin.

AIM: To establish an animal model for systemic lupus erythematosus (SLE)-like syndrome in mice. METHODS: BALB/c mice were immunized with active chromatin isolated from ConA-activated syngeneic spleno-lymphocytes. Plasma samples of mice were tested by enzyme-linked immunosorbent assays (ELISA) for the presence of IgG anti-dsDNA, -ssDNA, and anti-histone antibodies. Tumor necrosis factor-alpha (TNF-alpha) in serum was measured by ELISA. Spleno-lymphocyte proliferation assays and the levels of interferon-gamma (IFN-gamma) in supernatants were tested respectively. Proteinuria was measured. Kidneys were examined by direct immunohistochemical method and light microscopy. RESULTS: Anti-ds DNA, ssDNA, and histone antibodies were induced in active chromatin-immunized mice, the proliferation response of splenocytes to ConA and LPS were reduced, levels of interferon-gamma in supernatants and TNF-alpha in serum were lowered. Lupus nephritis was assessed by the presence of Ig deposits, glomerular pathology and proteinuria. CONCLUSION: The active chromatin-induced SLE-like mouse model was similar to idiopathic SLE in human.