A Mendelian randomization study between chronic periodontitis and non-alcoholic fatty liver disease

BACKGROUND AND OBJECTIVE

Observational studies have suggested a potential association between non-alcoholic fatty liver disease (NAFLD) and chronic periodontitis (CP). However, these studies are prone to confounding factors. The aim of this study was to assess the causal relationship between NAFLD and CP using a two-sample bidirectional Mendelian randomization (MR) analysis method.

METHODS

Datasets of CP and NAFLD were retrieved from the European database, and instrumental variables (IVs) related to exposure were selected for the MR analysis. Sensitivity tests, including heterogeneity and horizontal pleiotropy tests, were conducted to ensure the consistency of the selected IVs, following which the analysis results were visualized.

RESULTS

Genetic variants associated with CP and NAFLD were identified as IVs, and the MR assessment was performed using the summary data (CP: 3046 cases and 195 395 controls; NAFLD: 894 cases and 217 898 controls). CP increased the risk of NAFLD (inverse variance weighted [IVW], b = 0.132 > 0, p = .006 < .05), whereas the reverse was not observed (IVW, b = -0.024 < 0, p = .081 > .05). The sensitivity analysis indicated no heterogeneity or horizontal pleiotropy.

CONCLUSION

The MR analysis suggested that CP could increase the risk of NAFLD among European populations.

Mussel-inspired PDA@PEDOT nanocomposite hydrogel with excellent mechanical strength, self-adhesive, and self-healing properties for a flexible strain sensor

Conductive hydrogel sensors have attracted attention for use in human motion monitoring detection, but integrating excellent biocompatibility, mechanical, self-adhesive, and self-healing properties, and high sensitivity into a hydrogel remains a challenge. In this work, a novel multifunctional conductive particle was designed and added to a polyacrylamide (PAM) matrix to prepare the hydrogel. It is worth noting that with the addition of polydopamine@poly(3,4-ethylenedioxythiophene) (PDA@PEDOT), the PAM/PDA@PEDOT hydrogel (PAPP hydrogel) showed excellent mechanical properties and high adhesion strength on different substrate surfaces. Meanwhile, the PAPP hydrogel shows outstanding self-healing properties, the mechanical properties of PAPP hydrogel broken from the middle recovered 92% tensile strength and 95% elongation at break after 12 h, respectively. Furthermore, assembled as strain wireless sensors, the PAPP sensor displays high sensitivity, where the gauge factor (GF) is 2.82, which can be used to accurately detect human facial micro-expressions and movements. Overall, the PAPP hydrogel with excellent mechanical, self-adhesive, and self-healing properties, and high sensitivity, demonstrated promise for use in wearable devices and bionic skins.

Metformin switches cell death modes to soothe the apical periodontitis via ZBP1

Apical periodontitis (AP) is a disease caused by pathogenic microorganisms and featured with the degradation of periapical hard tissue. Our recent research showed the crucial role of Z-DNA binding protein 1 (ZBP1)-mediated necroptosis and apoptosis in the pathogenesis of AP. However, the specific regulatory mechanisms of ZBP1 in AP are not fully elucidated. It was found that metformin has a regulatory role in cell necroptosis and apoptosis. But whether and how metformin regulates necroptosis and apoptosis through the ZBP1 in the context of AP remains unknown. This study provided evidence that lipopolysaccharide (LPS) promotes the synthesis of left-handed Z-nucleic acids (Z-NA), which in turn activates ZBP1. Knockout of Zbp1 by CRISPR/Cas9 technology significantly reduced LPS-induced necroptosis and apoptosis in vitro. By using Zbp1-knockout mice, periapical bone destruction was alleviated. Moreover, type I interferon induced the expression of interferon-stimulated genes (ISGs), which serve as a major source of Z-NA. In addition, the RNA-editing enzyme Adenosine Deaminase RNA specific 1 (ADAR1) prevented the accumulation of endogenous Z-NA. Meanwhile, metformin suppressed the ZBP1-mediated necroptosis by inhibiting the expression of ZBP1 and the accumulation of ISGs. Metformin also promoted mitochondrial apoptosis, which is critical for the elimination of intracellular bacterial infection. The enhanced apoptosis further promoted the healing of infected apical bone tissues. In summary, these results demonstrated that the recognition of Z-NA by ZBP1 plays an important role in AP pathogenesis. Metformin suppressed ZBP1-mediated necroptosis and promoted apoptosis, thereby contributing to the soothing of inflammation and bone healing in AP.

Expert consensus on irrigation and intracanal medication in root canal therapy

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment. However, irrigant selection or irrigation procedures are far from clear. The vapor lock effect in the apical region has yet to be solved, impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes. Additionally, ambiguous clinical indications for root canal medication and non-standardized dressing protocols must be clarified. Inappropriate intracanal medication may present side effects and jeopardize the therapeutic outcomes. Indeed, clinicians have been aware of these concerns for years. Based on the current evidence of studies, this article reviews the properties of various irrigants and intracanal medicaments and elucidates their effectiveness and interactions. The evolution of different kinetic irrigation methods, their effects, limitations, the paradigm shift, current indications, and effective operational procedures regarding intracanal medication are also discussed. This expert consensus aims to establish the clinical operation guidelines for root canal irrigation and a position statement on intracanal medication, thus facilitating a better understanding of infection control, standardizing clinical practice, and ultimately improving the success of endodontic therapy.

CT whole lung radiomic nomogram: a potential biomarker for lung function evaluation and identification of COPD

BACKGROUND

Computed tomography (CT) plays a great role in characterizing and quantifying changes in lung structure and function of chronic obstructive pulmonary disease (COPD). This study aimed to explore the performance of CT-based whole lung radiomic in discriminating COPD patients and non-COPD patients.

METHODS

This retrospective study was performed on 2785 patients who underwent pulmonary function examination in 5 hospitals and were divided into non-COPD group and COPD group. The radiomic features of the whole lung volume were extracted. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied for feature selection and radiomic signature construction. A radiomic nomogram was established by combining the radiomic score and clinical factors. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the predictive performance of the radiomic nomogram in the training, internal validation, and independent external validation cohorts.

RESULTS

Eighteen radiomic features were collected from the whole lung volume to construct a radiomic model. The area under the curve (AUC) of the radiomic model in the training, internal, and independent external validation cohorts were 0.888 [95% confidence interval (CI) 0.869-0.906], 0.874 (95%CI 0.844-0.904) and 0.846 (95%CI 0.822-0.870), respectively. All were higher than the clinical model (AUC were 0.732, 0.714, and 0.777, respectively, P < 0.001). DCA demonstrated that the nomogram constructed by combining radiomic score, age, sex, height, and smoking status was superior to the clinical factor model.

CONCLUSIONS

The intuitive nomogram constructed by CT-based whole-lung radiomic has shown good performance and high accuracy in identifying COPD in this multicenter study.

Automatic segmentation of brain glioma based on XY-Net

Glioma is a malignant primary brain tumor, which can easily lead to death if it is not detected in time. Magnetic resonance imaging is the most commonly used technique to diagnose gliomas, and precise outlining of tumor areas from magnetic resonance images (MRIs) is an important aid to physicians in understanding the patient's condition and formulating treatment plans. However, relying on radiologists to manually depict tumors is a tedious and laborious task, so it is clinically important to investigate an automated method for outlining glioma regions in MRIs. To liberate radiologists from the heavy task of outlining tumors, we propose a fully convolutional network, XY-Net, based on the most popular U-Net symmetric encoder-decoder structure to perform automatic segmentation of gliomas. We construct two symmetric sub-encoders for XY-Net and build interconnected X-shaped feature map transmission paths between the sub-encoders, while maintaining the feature map concatenation between each sub-encoder and the decoder. Moreover, a loss function composed of the balanced cross-entropy loss function and the dice loss function is used in the training task of XY-Net to solve the class unevenness problem of the medical image segmentation task. The experimental results show that the proposed XY-Net has a 2.16% improvement in dice coefficient (DC) compared to the network model with a single encoder structure, and compare with some state-of-the-art image segmentation methods, XY-Net achieves the best performance. The DC, HD, recall, and precision of our method on the test set are 74.49%, 10.89 mm, 78.06%, and 76.30%, respectively. The combination of sub-encoders and cross-transmission paths enables the model to perform better; based on this combination, the XY-Net achieves an end-to-end automatic segmentation of gliomas on 2D slices of MRIs, which can play a certain auxiliary role for doctors in grasping the state of illness.

C60-CN: A bifunctional interface modification material for perovskite solar cells

Titanium dioxide (TiO2) is regularly used as an electron transport material in n-i-p perovskite solar cells (PSCs). However, massive defects exist on the TiO2 surface, which will lead to serious hysteresis and interface charge recombination of the device, thus affecting the device's efficiency. In this study, a cyano fullerene pyrrolidine derivative (C60-CN) was synthesized and applied to PSCs for the first time to modify the TiO2 electron transport layer. Systematic studies have shown that the addition of the C60-CN modification layer on the TiO2 surface will enlargement the perovskite grain size, improve the perovskite film quality, enhance electron transport, and reduce charge recombination. The C60-CN layer can significantly reduce the density of trap states in the perovskite solar cells. As a result, the PSCs based on C60-CN/TiO2 obtained a power conversion efficiency (PCE) of 18.60%, suppressing the hysteresis and improving the stability, whereas the PCE of the control device using the original TiO2 ETL was lower, 17.19%.

Research hotspots and trends of artificial intelligence in rheumatoid arthritis: A bibliometric and visualized study

Artificial intelligence (AI) applications on rheumatoid arthritis (RA) are becoming increasingly popular. In this bibliometric study, we aimed to analyze the characteristics of publications relevant to the research of AI in RA, thereby developing a thorough overview of this research topic. Web of Science was used to retrieve publications on the application of AI in RA from 2003 to 2022. Bibliometric analysis and visualization were performed using Microsoft Excel (2019), R software (4.2.2) and VOSviewer (1.6.18). The overall distribution of yearly outputs, leading countries, top institutions and authors, active journals, co-cited references and keywords were analyzed. A total of 859 relevant articles were identified in the Web of Science with an increasing trend. USA and China were the leading countries in this field, accounting for 71.59% of publications in total. Harvard University was the most influential institution. Arthritis Research & Therapy was the most active journal. Primary topics in this field focused on estimating the risk of developing RA, diagnosing RA using sensor, clinical, imaging and omics data, identifying the phenotype of RA patients using electronic health records, predicting treatment response, tracking the progression of the disease and predicting prognosis and developing new drugs. Machine learning and deep learning algorithms were the recent research hotspots and trends in this field. AI has potential applications in various fields of RA, including the risk assessment, screening, early diagnosis, monitoring, prognosis determination, achieving optimal therapeutic outcomes and new drug development for RA patients. Incorporating machine learning and deep learning algorithms into real-world clinical practice will be a future research hotspot and trend for AI in RA. Extensive collaboration to improve model maturity and robustness will be a critical step in the advancement of AI in healthcare.

Development and validation of a contrast-enhanced CT-based radiomics nomogram for differentiating mass-like thymic hyperplasia and low-risk thymoma

PURPOSE

To explore the efficiency of a contrast-enhanced CT-based radiomics nomogram integrated with radiomics signature and clinically independent predictors to distinguish mass-like thymic hyperplasia (ml-TH) from low-risk thymoma (LRT) preoperatively.

METHODS

135 Patients with histopathology confirmed ml-TH (n = 65) and LRT (n = 70) were randomly divided into training set (n = 94) and validation set (n = 41) at a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) algorithm was used to obtain the optimal features. Based on the selected features, four machine learning models, support vector machine (SVM), logistic regression (LR), extreme gradient boosting (XGBOOST), and random forest (RF) were constructed. Multivariate logistic regression was used to establish a radiomics nomogram containing clinically independent predictors and radiomics signature. Receiver operating characteristic (ROC), DeLong test, and calibration curves were used to detect the performance of the radiomics nomogram in training set and validation set.

RESULTS

In the validation set, the area under the curve (AUC) value of LR (0.857; 95% CI: 0.741, 0.973) was the highest of the four machine learning models. Radiomics nomogram containing radiomics signature and clinically independent predictors (including age, shape, and net enhancement degree) had better calibration and identification in the training set (AUC: 0.959; 95% CI: 0.922, 0.996) and validation set (AUC: 0.895; 95% CI: 0.795, 0.996).

CONCLUSION

We constructed a contrast-enhanced CT-based radiomics nomogram containing clinically independent predictors and radiomics signature as a noninvasive preoperative prediction method to distinguish ml-TH from LRT. The radiomics nomogram we constructed has potential for preoperative clinical decision making.

Clinical characteristics and prognostic analysis of idiopathic inflammatory myopathy with positive anti-aminoacyl-tRNA synthetase antibodies: A single center experience

OBJECTIVES

To identify the differences of clinical characteristics, laboratory findings, and the long-term outcomes in patients with anti-synthetase syndrome (ASS) of different anti-aminoacyl-transfer RNA synthetase antibodies.

METHODS

We retrospectively enrolled 119 patients with ASS, and the clinical characteristics and laboratory findings were collected. Additionally, multivariate COX regression analysis was performed to estimate the risk factors of prognosis in patients with ASS.

RESULTS

The frequency of interstitial lung disease (ILD) reached 93.3% in our cohort, of 28 (23.5%) was classified as rapidly progressive (RP)-ILD. The highest incidence of RP-ILD was 36.4% in the PL12 group of ASS patients. The ILD group was characterized by an older age, a lower prevalence of V sign, and a higher prevalence of pulmonary symptoms when contrasted with the non-ILD group. There were statistical differences of clinical significance in arthritis, myositis, mechanic's hands, triad, shawl sign, V sign, and Raynaud's phenomenon among the four subgroups (all p < .05). Additionally, the prevalence rates of arthritis, myositis, mechanic's hands, triad, and V sign in the anti-Jo1 antibody-positive group were significantly higher than anti-Jo1 antibody-negative patients with ASS (all p < .05). Multivariate Cox regression analysis showed mechanic's hands (odds ratio [OR] = 6.47, p < .001), anti-nuclear antibodies (ANA) (OR = 2.13, p = .026), ILD (OR = 10.50, p < .001), and V sign (OR = 0.30, p = .007) were independent factors affecting the prognosis of patients with ASS. The incidences of RP-ILD, arthritis, myositis, triad, mechanic's hands, and shawl sign were more frequent in the anti-Ro52 antibody-positive group than the anti-Ro52 antibody-negative patients with ASS (all p < .05).

CONCLUSIONS

Patients with ASS accompanied with ILD are highly prevalent. Mechanic's hands, ANA, and ILD may be a potential biomarker for predicting a poor prognosis in patients with ASS. Additionally, the detection of the anti-Ro52 antibody provides valuable insights for managing and predicting disease progression and long-term outcomes.

Application Potential of Radiomics based on the Unenhanced CT Image for the Identification of Benign or Malignant Pulmonary Nodules

OBJECTIVE

With the rapid development in computed tomography (CT), the establishment of artificial intelligence (AI) technology and improved awareness of health in folks in the decades, it becomes easier to detect and predict pulmonary nodules with high accuracy. The accurate identification of benign and malignant pulmonary nodules has been challenging for radiologists and clinicians. Therefore, this study applied the unenhanced CT imagesbased radiomics to identify the benign or malignant pulmonary nodules.

METHODS

One hundred and four cases of pulmonary nodules confirmed by clinicopathology were analyzed retrospectively, including 79 cases of malignant nodules and 25 cases of benign nodules. They were randomly divided into a training group (n = 74 cases) and test group (n = 30 cases) according to the ratio of 7:3. Using ITK-SNAP software to manually mark the region of interest (ROI), and using AK software (Analysis kit, Version 3.0.0.R, GE Healthcare, America) to extract image radiomics features, a total of 1316 radiomics features were extracted. Then, the minimum-redundancy-maximum-relevance (mRMR) algorithms were used to preliminarily reduce the dimension, and retain the 30 most meaningful features, and then the least absolute shrinkage and selection operator (LASSO) algorithm was used to select the optimal subset of features, so as to establish the final model. The performance of the model was evaluated by using the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), accuracy, sensitivity and specificity. Calibration refers to the agreement between observed endpoints and predictions, and the clinical benefit of the model to patients was evaluated by decision curve analysis (DCA).

RESULTS

The accuracy, sensitivity, and specificity of the training and testing groups were 81.0%, 77.7%, 82.1% and 76.6%, 85.7%, 73.9%, respectively, and the corresponding AUCs were of 0.83 in both groups.

CONCLUSION

CT image-based radiomics could differentiate benign from malignant pulmonary nodules, which might provide a new method for clinicians to detect benign and malignant pulmonary nodules.

Radiomics in the Diagnosis of Gastric Cancer: Current Status and Future Perspectives

Gastric cancer is a malignant cancerous lesion with high morbidity and mortality. Preoperative diagnosis of gastric cancer is challenging owing to the presentation of atypical symptoms and the diversity of occurrence of focal gastric lesions. Therefore, an endoscopic biopsy is used to diagnose gastric cancer in combination with imaging examination for a comprehensive evaluation of the local tumor range (T), lymph node status (N), and distant metastasis (M). The resolution of imaging examinations has significantly improved with the technological advancement in this sector. However, imaging examinations can barely provide valuable information. In clinical practice, an examination method that can provide information on the biological behavior of the tumor is critical to strategizing the treatment plan. Artificial intelligence (AI) allows for such an inspection procedure by reflecting the histological features of lesions using quantitative information extracted from images. Currently, AI is widely employed across various medical fields, especially in the processing of medical images. The basic application process of radiomics has been described in this study, and its role in clinical studies of gastric cancer has been discussed.

Experts consensus on the procedure of dental operative microscope in endodontics and operative dentistry

The dental operative microscope has been widely employed in the field of dentistry, particularly in endodontics and operative dentistry, resulting in significant advancements in the effectiveness of root canal therapy, endodontic surgery, and dental restoration. However, the improper use of this microscope continues to be common in clinical settings, primarily due to operators' insufficient understanding and proficiency in both the features and established operating procedures of this equipment. In October 2019, Professor Jingping Liang, Vice Chairman of the Society of Cariology and Endodontology, Chinese Stomatological Association, organized a consensus meeting with Chinese experts in endodontics and operative dentistry. The objective of this meeting was to establish a standard operation procedure for the dental operative microscope. Subsequently, a consensus was reached and officially issued. Over the span of about four years, the content of this consensus has been further developed and improved through practical experience.

Survival and prognosis analysis of systemic lupus erythematosus patients with pulmonary hypertension: A systematic review and meta-analysis

BACKGROUND

The study aimed to evaluate survival rates and prognosis in systemic lupus erythematosus (SLE) patients with pulmonary hypertension (PH) using meta-analysis.

METHODS

PubMed, EMBASE, Cochrane central register of controlled trials, China National Knowledge Infrastructure, China Science and Technology Journal Database, Wan-Fang Database, and Chinese biomedical database were searched. Information and data were screened and extracted by 2 researchers. The obtained data were analyzed using the R software meta package. Quality assessment was conducted using Newcastle-Ottawa Scale. The causes of heterogeneity were analyzed using subgroup analysis and sensitivity analysis. Publication bias was evaluated using Begger funnel plots and Egger test.

RESULTS

The search strategy yielded a total of 21 studies involving 875 patients included in the final analysis. The pooled 1-, 3- and 5-year survival rates of patients with SLE-PH were 0.9020 (95%CI: 0.8576; 0.9397), 0.8363 (96%CI: 0.7813; 0.8852), 0.7301 (95%CI: 0.6327; 0.8181). The 1-, 3- and 5-year survival rates of echocardiography subgroup were 0.9000 (95%CI: 0.8480; 0.9551), 0.8435 (95%CI: 0.7744; 0.9187), 0.6795 (95%CI: 0.5746; 0.8035), respectively; and there were 0.9174 (95%CI: 0.8951; 0.9402), 0.8529 (95%CI: 0.8255; 0.8812), 0.7757 (95%CI: 0.7409; 0.8121) at right heart catheterization subgroup in the meantime. Multivariate analysis for predicting mortality in SLE-PH patients revealed that diminishing left ventricular ejection fraction, New York Heart Association classification, lupus nephritis, lower cardiac index, and higher red blood cell distribution width level were significantly associated with a higher mortality rate. Treatment with huge doses of cyclophosphamide, tricuspid annular plane systolic excursion/pulmonary artery systolic pressure, and Raynaud phenomenon signaled favorable outcomes.

CONCLUSION

The 1-, 3-, and 5-year survival rates of SLE-PH patients in recent years (0.9020, 0.8363, 0.7301) were estimated in this study. SLE-PH patients diagnosed by echocardiography have a worse long-term prognosis than those diagnosed by right heart catheterization. Studies after 2015 have shown significantly better survival than earlier studies.

Necroptosis in apical periodontitis: A programmed cell death with multiple roles

Programmed cell death (PCD) has been a research focus for decades and different mechanisms of cell death, such as necroptosis, pyroptosis, ferroptosis, and cuproptosis have been discovered. Necroptosis, a form of inflammatory PCD, has gained increasing attention in recent years due to its critical role in disease progression and development. Unlike apoptosis, which is mediated by caspases and characterized by cell shrinkage and membrane blebbing, necroptosis is mediated by mixed lineage kinase domain-like protein (MLKL) and characterized by cell enlargement and plasma membrane rupture. Necroptosis can be triggered by bacterial infection, which on the one hand represents a host defense mechanism against the infection, but on the other hand can facilitate bacterial escape and worsen inflammation. Despite its importance in various diseases, a comprehensive review on the involvement and roles of necroptosis in apical periodontitis is still lacking. In this review, we tried to provide an overview of recent progresses in necroptosis research, summarized the pathways involved in apical periodontitis (AP) activation, and discussed how bacterial pathogens induce and regulated necroptosis and how necroptosis would inhibit bacteria. Furthermore, the interplay between various types of cell death in AP and the potential treatment strategy for AP by targeting necroptosis were also discussed.

Value of the application of computed tomography-based radiomics for preoperative prediction of unfavorable pathology in initial bladder cancer

OBJECTIVES

To construct and validate unfavorable pathology (UFP) prediction models for patients with the first diagnosis of bladder cancer (initial BLCA) and to compare the comprehensive predictive performance of these models.

MATERIALS AND METHODS

A total of 105 patients with initial BLCA were included and randomly enrolled into the training and testing cohorts in a 7:3 ratio. The clinical model was constructed using independent UFP-risk factors determined by multivariate logistic regression (LR) analysis in the training cohort. Radiomics features were extracted from manually segmented regions of interest in computed tomography (CT) images. The optimal CT-based radiomics features to predict UFP were determined by the optimal feature filter and the least absolute shrinkage and selection operator algorithm. The radiomics model consist with the optimal features was constructed by the best of the six machine learning filters. The clinic-radiomics model combined the clinical and radiomics models via LR. The area under the curve (AUC), accuracy, sensitivity, specificity, positive and negative predictive value, calibration curve and decision curve analysis were used to evaluate the predictive performance of the models.

RESULTS

Patients in the UFP group had a significantly older age (69.61 vs. 63.93 years, p = 0.034), lager tumor size (45.7% vs. 11.1%, p = 0.002) and higher neutrophil to lymphocyte ratio (NLR; 2.76 vs. 2.33, p = 0.017) than favorable pathologic group in the training cohort. Tumor size (OR, 6.02; 95% CI, 1.50-24.10; p = 0.011) and NLR (OR, 1.50; 95% CI, 1.05-2.16; p = 0.026) were identified as independent predictive factors for UFP, and the clinical model was constructed using these factors. The LR classifier with the best AUC (0.817, the testing cohorts) was used to construct the radiomics model based on the optimal radiomics features. Finally, the clinic-radiomics model was developed by combining the clinical and radiomics models using LR. After comparison, the clinic-radiomics model had the best performance in comprehensive predictive efficacy (accuracy = 0.750, AUC = 0.817, the testing cohorts) and clinical net benefit among UFP-prediction models, while the clinical model (accuracy = 0.625, AUC = 0.742, the testing cohorts) was the worst.

CONCLUSION

Our study demonstrates that the clinic-radiomics model exhibits the best predictive efficacy and clinical net benefit for predicting UFP in initial BLCA compared with the clinical and radiomics model. The integration of radiomics features significantly improves the comprehensive performance of the clinical model.

Antibacterial Activity and Mechanism of Canagliflozin against Methicillin-Resistant Staphylococcus aureus

Diabetic foot infection (DFI) is a common complication in diabetes patients, with foot infections being the leading cause of amputations. Staphylococcus aureus is frequently found in diabetic foot infections, of which methicillin-resistant Staphylococcus aureus (MRSA) has become a major clinical and epidemiological challenge. Since MRSA strains are resistant to most β-lactam antibiotics, and also partially resistant to other antibiotics, treatment is difficult and costly. The emergence of drug-resistant bacteria often arises from overuse or misuse of antibiotics. Clinically, canagliflozin is commonly used for the treatment of type 2 diabetes. On this basis, we investigated the antibacterial activity and mechanism of canagliflozin against MRSA, with the aim to discover novel functions of canagliflozin and provide new insights for the treatment of MRSA. Using the microbroth dilution method to determine the half maximal inhibitory concentration of drugs, we found that canagliflozin not only can inhibit the growth of methicillin-sensitive Staphylococcus aureus (MSSA) but also exhibits antibacterial activity against MRSA. The IC50 values, at approximately 56.01 μM and 57.60 μM, were almost the same. At 12 h, canagliflozin showed a significant antibacterial effect against MRSA at and above 30 μM. In addition, its combined use with penicillin achieved better antibacterial effects, which were increased by about three times. Additive antibacterial activity (FICI = 0.69) was found between penicillin and canagliflozin, which was better than that of doxycycline and canagliflozin (FICI = 0.95). Canagliflozin also affected bacterial metabolic markers, such as glucose, ATP, and lactic acid. The results of crystal violet staining indicate that canagliflozin disrupted the formation of bacterial biofilm. Our electron microscopy results showed that canagliflozin distorted the bacterial cell wall. The results of RT-PCR suggest that canagliflozin down-regulated the expressions of biofilm-related gene (clfA, cna, agrC, mgrA, hld) and methicillin-resistance gene (mecA), which was related to MRSA. Molecular docking also indicated that canagliflozin affected some interesting targets of MRSA, such as the sarA, crtM and fnbA proteins. In conclusion, canagliflozin exhibits antibacterial activity against MRSA by affecting bacterial metabolism, inhibiting its biofilm formation, distorting the bacterial cell wall, and altering the gene expression of biofilm formation and its virulence. Our study reveals the antibacterial activity of canagliflozin against MRSA, providing a new reference for treating diabetic foot infections.

New insights into nanosystems for non-small-cell lung cancer: diagnosis and treatment

Lung cancer is caused by a malignant tumor that shows the fastest growth in both incidence and mortality and is also the greatest threat to human health and life. At present, both in terms of incidence and mortality, lung cancer is the first in male malignant tumors, and the second in female malignant tumors. In the past two decades, research and development of antitumor drugs worldwide have been booming, and a large number of innovative drugs have entered clinical trials and practice. In the era of precision medicine, the concept and strategy of cancer from diagnosis to treatment are experiencing unprecedented changes. The ability of tumor diagnosis and treatment has rapidly improved, the discovery rate and cure rate of early tumors have greatly improved, and the overall survival of patients has benefited significantly, with a tendency to transform to a chronic disease with tumor. The emergence of nanotechnology brings new horizons for tumor diagnosis and treatment. Nanomaterials with good biocompatibility have played an important role in tumor imaging, diagnosis, drug delivery, controlled drug release, etc. This article mainly reviews the advancements in lipid-based nanosystems, polymer-based nanosystems, and inorganic nanosystems in the diagnosis and treatment of non-small-cell lung cancer (NSCLC).

MicroRNA-146a-5p induces cell cycle arrest and enhances apoptosis in gastric cancer via targeting CDC14A

Objective: The present study was designed to investigate the expression of miRNA-146a-5p in gastric cancer (GC) tissues and the paired nonmalignant counterparts, to explore the influences of miRNA-146a-5p on the cell biological behavior of MKN-28 cells (highly metastatic human gastric cancer cells), and to identify the function of abnormal expression of its target gene cell division cycle 14 homolog A (CDC14A) in GC. Methods: We detected the expression of miRNA-146a-5p in formalin-fixed and paraffin-embedded (FFPE) GC tissues through microarray and quantitative real-time polymerase chain reaction (qRT-PCR). Then, we employed cell counting kit-8 (CCK-8) assays, cell cycle assays, and apoptosis analysis to uncover the latent function of miRNA-146a-5p in MKN-28 human GC cells. We also validated the target of miRNA-146a-5p via luciferase reporter assays. Results: miRNA-146a-5p levels were examined in the majority of primary GC tissues and several GC cell lines. As a result, miRNA-146a-5p levels were significantly declined in the GC tissues and cells. In addition, miRNA-146a-5p demonstrated a straight act on its 3'-untranslated region (3'-UTR) of CDC14A mRNA, accordingly decreasing the contents of CDC14A mRNA as well as its protein expression. An inverse correlation between CDC14A and miRNA-146a-5p was observed. Conclusion: The data suggest miRNA-146a-5p may contribute to inducing cell cycle arrest as well as prompting GC cell apoptosis via directly targeting CDC14A. Therefore, miRNA-146a-5p may be a potential indicator of the occurrence and development of GC.

Enhanced in vitro antibacterial effect against Enterococcus faecalis by using both low-dose cetylpyridinium chloride and silver ions

BACKGROUND

Enterococcus faecalis (E. faecalis) is frequently isolated from root canals with failed root canal treatments. Due to the strong ability of E. faecalis to resist many often-used antimicrobials, coping with E. faecalis infections remains a challenge. The aim of this study was to investigate the synergistic antibacterial effect of low-dose cetylpyridinium chloride (CPC) and silver ions (Ag⁺) against E. faecalis in vitro.

METHODS

The minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC) and the fractional inhibitory concentration index (FICI) were used to confirm the existence of the synergic antibacterial activity between low-dose CPC and Ag⁺. Colony-forming unit (CFU) counting, time-killing curve and dynamic growth curve were used to evaluate the antimicrobial effects of CPC and Ag⁺ combinations against planktonic E. faecalis. Four weeks biofilms were treated with drug-contained gels to determine the antimicrobial effect on biofilm-resident E.faecalis, and the integrity of E.faecalis and its biofilms were observed by FE-SEM. CCK-8 assays was used to test the cytotoxicity of CPC and Ag⁺ combinations on MC3T3-E1 cells.

RESULTS

The results confirmed the synergistic antibacterial effect of low-dose CPC and Ag⁺ against both planktonic and 4-week biofilm E. faecalis. After the addition of CPC, the sensitivity of both planktonic and biofilm-resident E. faecalis to Ag⁺ improved, and the combination showed good biocompatibility on MC3T3-E1 cells.

CONCLUSIONS

Low-dose CPC enhanced the antibacterial ability of Ag⁺ against both planktonic and biofilm E.faecalis with good biocompatibility. It may be developed into a novel and potent antibacterial agent against E.faecalis, with low toxicity for root canal disinfection or other related medical applications.

Machine learning models combining computed tomography semantic features and selected clinical variables for accurate prediction of the pathological grade of bladder cancer

Objective

The purpose of this research was to develop a radiomics model that combines several clinical features for preoperative prediction of the pathological grade of bladder cancer (BCa) using non-enhanced computed tomography (NE-CT) scanning images.

Materials and methods

The computed tomography (CT), clinical, and pathological data of 105 BCa patients attending our hospital between January 2017 and August 2022 were retrospectively evaluated. The study cohort comprised 44 low-grade BCa and 61 high-grade BCa patients. The subjects were randomly divided into training (n = 73) and validation (n = 32) cohorts at a ratio of 7:3. Radiomic features were extracted from NE-CT images. A total of 15 representative features were screened using the least absolute shrinkage and selection operator (LASSO) algorithm. Based on these characteristics, six models for predicting BCa pathological grade, including support vector machine (SVM), k-nearest neighbor (KNN), gradient boosting decision tree (GBDT), logical regression (LR), random forest (RF), and extreme gradient boosting (XGBOOST) were constructed. The model combining radiomics score and clinical factors was further constructed. The predictive performance of the models was evaluated based on the area under the receiver operating characteristic (ROC) curve, DeLong test, and decision curve analysis (DCA).

Results

The selected clinical factors for the model included age and tumor size. LASSO regression analysis identified 15 features most linked to BCa grade, which were included in the machine learning model. The SVM analysis revealed that the highest AUC of the model was 0.842. A nomogram combining the radiomics signature and selected clinical variables showed accurate prediction of the pathological grade of BCa preoperatively. The AUC of the training cohort was 0.919, whereas that of the validation cohort was 0.854. The clinical value of the combined radiomics nomogram was validated using calibration curve and DCA.

Conclusion

Machine learning models combining CT semantic features and the selected clinical variables can accurately predict the pathological grade of BCa, offering a non-invasive and accurate approach for predicting the pathological grade of BCa preoperatively.

Application of DCE-MRI radiomics signature analysis in differentiating molecular subtypes of luminal and non-luminal breast cancer

Background

The goal of this study was to develop and validate a radiomics signature based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) preoperatively differentiating luminal and non-luminal molecular subtypes in patients with invasive breast cancer.

Methods

One hundred and thirty-five invasive breast cancer patients with luminal (n = 78) and non-luminal (n = 57) molecular subtypes were divided into training set (n = 95) and testing set (n = 40) in a 7:3 ratio. Demographics and MRI radiological features were used to construct clinical risk factors. Radiomics signature was constructed by extracting radiomics features from the second phase of DCE-MRI images and radiomics score (rad-score) was calculated. Finally, the prediction performance was evaluated in terms of calibration, discrimination, and clinical usefulness.

Results

Multivariate logistic regression analysis showed that no clinical risk factors were independent predictors of luminal and non-luminal molecular subtypes in invasive breast cancer patients. Meanwhile, the radiomics signature showed good discrimination in the training set (AUC, 0.86; 95% CI, 0.78-0.93) and the testing set (AUC, 0.80; 95% CI, 0.65-0.95).

Conclusion

The DCE-MRI radiomics signature is a promising tool to discrimination luminal and non-luminal molecular subtypes in invasive breast cancer patients preoperatively and noninvasively.

A First Report of Thyroid pneumatosis as a Complication of Ultrasound-Guided Thyroid Biopsy

BACKGROUND

Ultrasound-guided needle biopsies, including fine-needle aspirations (FNA) and core needle biopsies (CNB), have become an effective technique in the evaluation of thyroid nodules. In this report, we discuss the first reported case, to our knowledge, of thyroid pneumatosis after ultrasound-guided FNA.

CASE PRESENTATION

A 44-year-old woman underwent ultrasound-guided FNA in other hospitals after thyroid ultrasound revealed a solid lesion in the left lobe classified as TI-RADS 4. Two days later, this female presented to our hospital for an excision of a thyroid mass. Pre- and post-contrast CT scans of the thyroid showed extensive accumulation of gas in the thyroid gland and the retropharyngeal and retrotracheal space. A CT scan of the thyroid two days later revealed obvious absorption of thyroid gas and faint low-density nodules in the left lobe of the thyroid. The lesion was histopathologically confirmed as papillary carcinoma of the thyroid.

CONCLUSION

We thought the aforementioned issues originating from the limited imaging capacity of ultrasound in the context of thyroid biopsy. To avoid these limitations, we highlight the need to thoroughly examine the location of a lesion prior to thyroid biopsy to understand in detail the relationship between the lesion and the adjacent tissues, especially the proximity of the lesion to the trachea, the occurrence of coughing during a biopsy (indicating puncture of the trachea) is what operators need to be aware of so that they can manage such cases. On the other hand, we recommend that pre-operative use of CT before thyroid biopsy and especially if CT is needed anyway later for nodules evaluation before surgery to ensure the CT image quality.

Inactivated whole-virion SARS-CoV-2 vaccines and long-term clinical outcomes in patients with coronary atherosclerosis disease in China: a prospective cohort study

AIMS

Publicized adverse events after vaccination agianst SARS-CoV-2 raised concern among patients with coronary atherosclerosis disease (CAD). We sought to study the association between SARS-CoV-2 vaccines and long-term clinical outcomes including ischemic and bleeding events among patients with CAD.

METHODS AND RESULTS

Inpatients diagnosed with CAD by coronary angiography, without a history of SARS-CoV-2 infection and vaccination were included between January 1 and April 30, 2021, and underwent follow-up until January 31, 2022. Two doses of inactivated whole-virion SARS-CoV-2 vaccine (CoronaVac, BBIBPCorV or WIBP-CorV) were available after discharge, and the group was stratified by vaccination. The primary composite outcomes were cardiovascular death, nonfatal myocardial infarction, stent thrombosis, unplanned revascularization, ischemic stroke, venous thromboembolism or peripheral arterial thrombosis. The bleeding outcomes were Bleeding Academic Research Consortium (BARC) type 3 or 5 bleeding. Cox regression models with vaccination status as time-dependent covariate were used to calculate the hazard ratio (HR) for the outcomes. Propensity score matching method was used to reduce confounding biases. This prospective cohort study included 2078 individuals with CAD, 1021 (49.1%) were vaccinated. During a median follow-up of 9.1 months, 45 (4.3%) primary composite outcomes occurred in the unvaccinated group, and 33 (3.2%) in the vaccinated group. In Cox regression, the adjusted HR was 1.13 [95% CI 0.65-1.93]. The adjusted HR for the bleeding outcomes associated with vaccination was 0.81 [95% CI 0.35-1.19]. After matching, the adjusted HR for the primary composite outcomes associated with vaccination was 1.06 [95% CI 0.57-1.99] and for the bleeding outcomes was 0.91 [95% CI 0.35-2.38]. Similar results were found in the seven prespecified subgroups. No grade 3 adverse reactions after vaccination were recorded.

CONCLUSIONS

Our results indicated no evidence of an increased ischemic or bleeding risk after vaccination with inactivated SARS-CoV-2 vaccine among Chinese patients with CAD, with limited statistical power.

Acromegaly with joint pain as an initial symptom: A case report

BACKGROUND

Acromegaly is caused by the long-term excessive secretion of growth hormone (GH) and insulin-like growth factor-1 (IGF-1). It can cause excessive hyperplasia of bone, cartilage, and soft tissue.

CASE PRESENTATION

A 50-year-old woman had a history of joint pain and swelling for more than 1 year. She visited a local primary care clinic, but her illness was not diagnosed by a primary care physician. After relevant examination in our hospital, we excluded inflammatory arthritis such as rheumatoid arthritis, immune disease-related arthritis, and infectious arthritis, and considered osteoarthritis or endocrine-metabolic arthritis. When we examined her again, we found that her fingers and toes were enlarged. She was diagnosed with acromegaly after IGF-1 test, and pituitary magnetic resonance imaging. Her joint symptoms were significantly relieved and her prognosis was good after surgery in another hospital.

CONCLUSIONS

Acromegaly is a complex and rare disease, which is difficult to diagnose. When a patient presents with arthralgia, it is easily misdiagnosed as a rheumatic disease, and the diagnosis and treatment are delayed.

Development and validation of a MRI-based combined radiomics nomogram for differentiation in chondrosarcoma

Objective

This study aims to develop and validate the performance of an unenhanced magnetic resonance imaging (MRI)-based combined radiomics nomogram for discrimination between low-grade and high-grade in chondrosarcoma.

Methods

A total of 102 patients with 44 in low-grade and 58 in high-grade chondrosarcoma were enrolled and divided into training set (n=72) and validation set (n=30) with a 7:3 ratio in this retrospective study. The demographics and unenhanced MRI imaging characteristics of the patients were evaluated to develop a clinic-radiological factors model. Radiomics features were extracted from T1-weighted (T1WI) images to construct radiomics signature and calculate radiomics score (Rad-score). According to multivariate logistic regression analysis, a combined radiomics nomogram based on MRI was constructed by integrating radiomics signature and independent clinic-radiological features. The performance of the combined radiomics nomogram was evaluated in terms of calibration, discrimination, and clinical usefulness.

Results

Using multivariate logistic regression analysis, only one clinic-radiological feature (marrow edema OR=0.29, 95% CI=0.11-0.76, P=0.012) was found to be independent predictors of differentiation in chondrosarcoma. Combined with the above clinic-radiological predictor and the radiomics signature constructed by LASSO [least absolute shrinkage and selection operator], a combined radiomics nomogram based on MRI was constructed, and its predictive performance was better than that of clinic-radiological factors model and radiomics signature, with the AUC [area under the curve] of the training set and the validation set were 0.78 (95%CI =0.67-0.89) and 0.77 (95%CI =0.59-0.94), respectively. DCA [decision curve analysis] showed that combined radiomics nomogram has potential clinical application value.

Conclusion

The MRI-based combined radiomics nomogram is a noninvasive preoperative prediction tool that combines clinic-radiological feature and radiomics signature and shows good predictive effect in distinguishing low-grade and high-grade bone chondrosarcoma, which may help clinicians to make accurate treatment plans.

Fusobacterium nucleatum triggers proinflammatory cell death via Z-DNA binding protein 1 in apical periodontitis

BACKGROUND

Z-DNA binding protein 1 (ZBP1) is a vital innate immune sensor that regulates inflammation during pathogen invasion. ZBP1 may contribute to pyroptosis, apoptosis and necroptosis in infectious diseases. In this study, Fusobacterium nucleatum (F. nucleatum) infection caused periapical inflammation through proinflammatory cell death and ZBP1 was involved in regulating the inflammatory activities caused by F. nucleatum infection in apical periodontitis (AP).

METHODS

Human periapical tissues were tested by fluorescent in situ hybridization, immunohistochemical staining, immunofluorescence staining, quantitative real-time PCR (qRT‒PCR) and western blotting. F. nucleatum-infected and F. nucleatum extracellular vesicles (F. nucleatum-EVs)-treated RAW264.7 cells were used to detect the expression of inflammatory cytokines and different cell death mechanisms by qRT‒PCR and western blotting. ZBP1 expression in F. nucleatum-infected tissues and RAW264.7 cells was detected by qRT‒PCR, western blotting, and immunohistochemical and immunofluorescence staining. Furthermore, the expression of ZBP1 was inhibited by siRNA and different cell death pathways, including pyroptosis, apoptosis, and necroptosis, and inflammatory cytokines were measured in F. nucleatum-infected RAW264.7 cells.

RESULTS

F. nucleatum was detected in AP tissues. F. nucleatum-infected RAW264.7 cells polarized to the M1 phenotype, and this was accompanied by inflammatory cytokine production. High levels of ZBP1 and GSDME (gasdermin E)-mediated pyroptosis, caspase-3-mediated apoptosis and MLKL-mediated necroptosis (PANoptosis) were identified in F. nucleatum-infected tissues and RAW264.7 cells. ZBP1 inhibition reduced inflammatory cytokine secretion and the occurrence of PANoptosis.

CONCLUSION

The present study identified a previously unknown role of ZBP1 in regulating F. nucleatum-induced proinflammatory cell death and inflammatory activation. Video abstract.

Applicative value of T2 mapping in evaluating lumbosacral nerve root injury induced by lumbosacral disc herniation

BACKGROUND

To alleviate the damage caused by nerve root entrapment mediated by lumbosacral disc herniation (LDH), an imaging method that allows quantitative evaluation of the lumbosacral nerve injury is necessary.

PURPOSE

To investigate the diagnostic value of magnetic resonance (MR) T2 mapping in nerve root injury caused by LDH.

MATERIAL AND METHODS

A total of 70 patients with unilateral sciatic nerve pain and 35 healthy volunteers were divided into three groups: LDH with nerve root entrapment; LDH without nerve root entrapment; and 35 healthy volunteers. All participants underwent 3.0-T MR with T1-weighted (T1W) imaging, T2-weighted (T2W) imaging, and T2-mapping images. T2 was measured and observed with the left and right nerve roots of the L4-S1 segments in healthy volunteers; the differences between the three groups were compared. T2 and the relaxation rate of nerve root injury were analyzed.

RESULTS

T2 showed significant differences among the three groups (F = 89.494; P = 0.000), receiver operating characteristic curve revealed that the T2 relaxation threshold was 79 ms, the area under curve (AUC) area was 0.86, sensitivity was 0.77, and specificity was 0.74; the T2 relaxation rate was 1.06, the AUC area was 0.88, sensitivity was 0.74, and specificity was 0.85.

CONCLUSION

T2 mapping could quantitatively evaluate the nerve root injury with lumbar disc degeneration. Hence, it can be used for the clinical evaluation of nerve root entrapment caused by LDH.

Application of a combined radiomics nomogram based on CE-CT in the preoperative prediction of thymomas risk categorization

Objective

This study aimed to establish a combined radiomics nomogram to preoperatively predict the risk categorization of thymomas by using contrast-enhanced computed tomography (CE-CT) images.

Materials and Methods

The clinical, pathological, and CT data of 110 patients with thymoma (50 patients with low-risk thymomas and 60 patients with high-risk thymomas) collected in our Hospital from July 2017 to March 2022 were retrospectively analyzed. The study subjects were randomly divided into the training set (n = 77) and validation set (n = 33) in a 7:3 ratio. Radiomics features were extracted from the CT images, and the least absolute shrinkage and selection operator (LASSO) algorithm was performed to select 13 representative features. Five models, including logistic regression (LR), support vector machine (SVM), random forest (RF), decision tree (DT), and gradient boosting decision tree (GBDT) were constructed to predict thymoma risks based on these features. A combined radiomics nomogram was further established based on the clinical factors and radiomics scores. The performance of the models was evaluated using receiver operating characteristic (ROC) curve, DeLong tests, and decision curve analysis.

Results

Maximum tumor diameter and boundary were selected to build the clinical factors model. Thirteen features were acquired by LASSO algorithm screening as the optimal features for machine learning model construction. The LR model exhibited the highest AUC value (0.819) among the five machine learning models in the validation set. Furthermore, the radiomics nomogram combining the selected clinical variables and radiomics signature predicted the categorization of thymomas at different risks more effectively (the training set, AUC = 0.923; the validation set, AUC = 0.870). Finally, the calibration curve and DCA were utilized to confirm the clinical value of this combined radiomics nomogram.

Conclusion

We demonstrated the clinical diagnostic value of machine learning models based on CT semantic features and the selected clinical variables, providing a non-invasive, appropriate, and accurate method for preoperative prediction of thymomas risk categorization.

Genomic and Transcriptomic Analyses Reveal Pathways and Genes Associated With Brittle Stalk Phenotype in Maize

The mechanical strength of the stalk affects the lodging resistance and digestibility of the stalk in maize. The molecular mechanisms regulating the brittleness of stalks in maize remain undefined. In this study, we constructed the maize brittle stalk mutant (bk5) by crossing the W22:Mu line with the Zheng 58 line. The brittle phenotype of the mutant bk5 existed in all of the plant organs after the five-leaf stage. Compared to wild-type (WT) plants, the sclerenchyma cells of bk5 stalks had a looser cell arrangement and thinner cell wall. Determination of cell wall composition showed that obvious differences in cellulose content, lignin content, starch content, and total soluble sugar were found between bk5 and WT stalks. Furthermore, we identified 226 differentially expressed genes (DEGs), with 164 genes significantly upregulated and 62 genes significantly downregulated in RNA-seq analysis. Some pathways related to cellulose and lignin synthesis, such as endocytosis and glycosylphosphatidylinositol (GPI)-anchored biosynthesis, were identified by the Kyoto Encyclopedia of Gene and Genomes (KEGG) and gene ontology (GO) analysis. In bulked-segregant sequence analysis (BSA-seq), we detected 2,931,692 high-quality Single Nucleotide Polymorphisms (SNPs) and identified five overlapped regions (11.2 Mb) containing 17 candidate genes with missense mutations or premature termination codons using the SNP-index methods. Some genes were involved in the cellulose synthesis-related genes such as ENTH/ANTH/VHS superfamily protein gene (endocytosis-related gene) and the lignin synthesis-related genes such as the cytochrome p450 gene. Some of these candidate genes identified from BSA-seq also existed with differential expression in RNA-seq analysis. These findings increase our understanding of the molecular mechanisms regulating the brittle stalk phenotype in maize.

Application Value of Radiomic Nomogram in the Differential Diagnosis of Prostate Cancer and Hyperplasia

Objective

Prostate cancer and hyperplasia require different treatment strategies and have completely different outcomes; thus, preoperative identification of prostate cancer and hyperplasia is very important. The purpose of this study was to evaluate the application value of magnetic resonance imaging (MRI)-derived radiomic nomogram based on T2-weighted images (T2WI) in differentiating prostate cancer and hyperplasia.

Materials and Methods

One hundred forty-six patients (66 cases of prostate cancer and 80 cases of prostate hyperplasia) who were confirmed by surgical pathology between September 2019 and September 2019 were selected. We manually delineated T2WI of all patients using ITK-SNAP software and radiomic analysis using Analysis Kit (AK) software. A total of 396 tumor texture features were extracted. Subsequently, the effective features were selected using the LASSO algorithm, and the radiomic feature model was constructed. Next, combined with independent clinical risk factors, a multivariate Logistic regression model was used to establish a radiomic nomogram. The receiver operator characteristic (ROC) curve was used to evaluate the prediction performance of the radiomic nomogram. Finally, the clinical application value of the nomogram was evaluated by decision curve analysis.

Results

The PSA and the selected imaging features were significantly correlated with the differential diagnosis of prostate cancer and hyperplasia. The radiomic model had good discrimination efficiency for prostate cancer and hyperplasia. The training set (AUC = 0.85; 95% CI: 0.77–0.92) and testing set (AUC = 0.84; 95% CI: 0.72–0.96) were effective. The radiomic nomogram, combined with the radiomic characteristics of MRI and independent clinical risk factors, showed better differentiation efficiency in the training set (AUC = 0.91; 95% CI: 0.85–0.97) and testing set (AUC = 0.90; 95% CI: 0.81–0.99). The decision curve showed the clinical application value of the radiomic nomogram.

Conclusion

The radiomic nomogram of T2-MRI combined with clinical risk factors can easily identify prostate cancer and hyperplasia. It also provides suggestions for further clinical events.

Diagnostic value of chest computed tomography images in adult Poland syndrome: a report of two cases

Poland syndrome is a rare congenital developmental deformity characterized by unilateral agenesis or hypoplasia of thoracic wall soft tissue. We report two adult cases of Poland syndrome detected by computed tomography (CT) images. CT images of the two cases depicted an asymmetric chest wall with the absence of a breast and agenesis of the pectoralis muscles. A physical examination of case 1 showed a thin right chest wall with depression of the right nipple region. Hand deformities were also observed, including brachydactyly and syndactyly. In case 2, hand deformities were not found in a physical examination. Using multi-planar reconstruction, the size, position, origin, and termination of bilateral pectoral muscles could be compared symmetrically. For patients with Poland syndrome, a timely diagnosis and treatment are important. The use of chest CT in clinical practice could play an important role in the early diagnosis and treatment of Poland syndrome.

Synergistic In Vitro Antimicrobial Activity of Triton X-100 and Metformin against Enterococcus faecalis in Normal and High-Glucose Conditions

The prevention and treatment of oral diseases is more difficult in diabetic patients with poorly controlled blood glucose levels. This study aims to explore an effective, low-cytotoxicity medication for root canal treatment in diabetic patients. The antibacterial effect of the combination of Triton X-100 (TX-100) and metformin (Met) on Enterococcus faecalis (E. faecalis) was evaluated by determining the minimum inhibitory concentration (MIC), minimum bactericidal concentration required to kill 99% bacteria (MBC₉₉) and by conducting dynamic time-killing assays. While the antibiofilm activity was measured by crystal violet (CV) assay, field emission scanning electron microscope (FE-SEM), confocal laser scanning microscope (CLSM) and colony-forming unit (CFU) counting assays. The expression of relative genes was evaluated by real-time quantitative polymerase chain reaction (RT-qPCR), and the cytotoxicity of the new combination on MC3T3-E1 cell was also tested. Results showed that the antibacterial and antibiofilm activities of Met could be significantly enhanced by very low concentrations of TX-100 in both normal and high-glucose conditions, with a much lower cytotoxicity than 2% chlorhexidine (CHX). Thus, the TX-100 + Met combination may be developed as a promising and effective root canal disinfectant for patients with diabetes.

Analysis of misdiagnosis and 18F-FDG PET/CT findings of lymph node tuberculosis

OBJECTIVE

To investigate 18F-FDG PET/CT findings of tuberculous lymphadenitis and analyze the causes of misdiagnosis.

METHOD

Between 2013 and 2021, a retrospective review was conducted on 22 patients at Jiangxi Provincial People's Hospital Affiliated with Nanchang University who had lymph node tuberculosis confirmed by histology or clinical investigation. Subjective judgment and quantitative analysis were adopted.

RESULTS

Out of 22 patients, 14 are male and 8 are female. The average age was 55.5 years (55.5±12.4). The most common site of lymph node tuberculosis (LNTB) is the mediastinum (41.5%), followed by the neck (24.4%) and the abdominal cavity (21.9%). Half of the patients have more than one site affected. More than half of LNTB patients (54.5%) are concurrent with other types of TB, especially PTB. Among the 41 biggest affected lymph nodes, the average maximum diameter, minimum diameter, SUVmax and the lesion SUVmax/SUVmean liver ratio are 22.04±8.39, 16.93±6.75, 9.72±5.04 and 6.72±3.60, respectively. There is a poor correlation coefficient of 0.236 between the FDG uptake and the size of the biggest affected lymph node. Patients who are concurrent with no other TB have the significantly higher FDG uptake than patients who are concurrent with other TB (12.42 vs 8.02) (p = 0.005). Among these cases, 6 cases (27.3%) are accurately diagnosed with LNTB, all of which have pulmonary tuberculosis as a complication. However, 16 cases (72.7%) are misdiagnosed as lymphoma (50%), sarcoidosis (13.6%), and lymph node metastasis (9%).

CONCLUSIONS

This study demonstrates that 18F-FDG PET/CT is very useful in detecting LNTB because tuberculous granulomas show significant levels of glucose uptake. It proves to be an effective method for revealing lesion extent and discovering additional lesions that morphological imaging is missed. However, 18F-FDG PET/CT is not able to reliably distinguish LNTB from lymphoma, sarcoidosis, and metastatic lymph nodes. Nonetheless, 18F-FDG PET/CT allows for the selection of the most optimal biopsy location, and thus has potential to detect early treatment response and distinguish between active and inactive lesions.

Application of Enhanced T1WI of MRI Radiomics in Glioma Grading

OBJECTIVE

To explore the application value of the radiomics method based on enhanced T1WI in glioma grading.

MATERIALS AND METHODS

A retrospective analysis was performed using data of 114 patients with glioma, which was confirmed using surgery and pathological tests, at our hospital between January 2017 and November 2020. The patients were randomly divided into the training and test groups in a ratio of 7 : 3. The Analysis Kit (AK) software was used for radiomic analysis, and a total of 461 tumor texture features were extracted. Spearman correlation analysis and the least absolute shrinkage and selection (LASSO) algorithm were employed to perform feature dimensionality reduction on the training group. A radiomics model was then constructed for glioma grading, and the validation group was used for verification.

RESULTS

The area under the ROC curve (AUC) of the proposed model was calculated to identify its performance in the training group, which was 0.95 (95% CI = 0.905-0.994), accuracy was 84.8%, sensitivity was 100%, and specificity was 77.8%. The AUC of the validation group was 0.952 (95% CI = 0.871-1.000), accuracy was 93.9%, sensitivity was 90.0%, and specificity was 95.6%.

CONCLUSIONS

The radiomics model based on enhanced T1WI improved the accuracy of glioma grading and better assisted clinical decision-making.

Application of Radiomics Model of CT Images in the Identification of Ureteral Calculus and Phlebolith

OBJECTIVE

To investigate the clinical application of the three-dimensional (3D) radiomics model of the CT image in the diagnosis and identification of ureteral calculus and phlebolith.

METHOD

Sixty-one cases of ureteral calculus and 61 cases of phlebolith were retrospectively investigated. The enrolled patients were randomly categorized into the training set (n = 86) and the testing set (n = 36) with a ratio of 7 : 3. The plain CT scan images of all samples were manually segmented by the ITK-SNAP software, followed by radiomics analysis through the Analysis Kit software. A total of 1316 texture features were extracted. Then, the maximum correlation minimum redundancy criterion and the least absolute shrinkage and selection operator algorithm were used for texture feature selection. The feature subset with the most predictability was selected to establish the 3D radiomics model. The performance of the model was evaluated by the receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC) was also calculated. Additionally, the decision curve was used to evaluate the clinical application of the model.

RESULTS

The 10 selected radiomics features were significantly related to the identification and diagnosis of ureteral calculus and phlebolith. The radiomics model showed good identification efficiency for ureteral calculus and phlebolith in the training set (AUC = 0.98; 95%CI: 0.96-1.00) and testing set (AUC = 0.98; 95%CI: 0.95-1.00). The decision curve thus demonstrated the clinical application of the radiomics model.

CONCLUSIONS

The 3D radiomics model based on plain CT scan images indicated good performance in the identification and prediction of ureteral calculus and phlebolith and was expected to provide an effective detection method for clinical diagnosis.

Further evidence for Zenker's diverticulum in a slim woman with body figure predisposition: a case report and literature review

Zenker’s diverticulum (ZD) is a bag-like pharyngeal pouch that protrudes to the outside of the pharynx. It is thought to be an acquired disease that occurs following the dysfunction of laryngopharynx muscle, and certain body shapes may be predisposed to this condition. We report a 56-year-old female of slim build with ZD. Computed tomography scanning revealed a hypodense lesion on the left posterior side of her upper esophagus that was filled with air and had no obvious wall. To verify this finding, a barium esophagogram was carried out which showed a round pouch at the level of the 6th cervical vertebral body that communicated with the esophagus through a narrow neck. ZD was subsequently confirmed by endoscopy. These findings provide further evidence in support of a body shape predisposition for ZD.

Enhanced antibacterial effect against Enterococcus faecalis by silver ions plus Triton X-100 with low concentrations and cytotoxicity

Enterococcus faecalis (E. faecalis) is commonly considered to be one of chief culprits of secondary and persistent root canal infections. As antibiotic resistance has become a global issue, in order to reduce the use of antibiotics, metal ions have recently been widely used as an alternative. Silver ions (Ag⁺) have been proved to be a strong bactericide but with high cytotoxicity and discoloration property. Triton X-100 (TX-100) and Ag⁺ were co-used for the first time as a clinical intracanal medication to obtain both enhanced antibacterial effect and low cytotoxicity. The synergistic antibacterial effect of TX-100 + Ag⁺ was tested on both planktonic and biofilm-resident E. faecalis on dentine. And the cytotoxicity was tested on MC3T3-E1 cells. Results confirmed the antibacterial activity against both planktonic and biofilm-resident E. faecalis was dramatically improved after TX-100 incorporation. TX-100 and Ag⁺ mixture demonstrated a similar inhibitory effect as the 2% chlorhexidine (CHX), while the cytotoxicity was much lower than 2% CHX (p < 0.05). In conclusion, TX-100 + Ag⁺ mixture might be developed into a new effective intracanal medication as the 2% CHX.

Efficient Degradation of Iopromide by Using Sulfite Activated with Mackinawite

Iopromide (IOP), an iodinated X-ray contrast medium (ICM), is identified as a precursor to iodide disinfection byproducts that have high genotoxicity and cytotoxicity to mammals. ICM remains persistent through typical wastewater treatment processes and even through some hydroxyl radical-based advanced oxidation processes. The development of new technologies to remove ICMs is needed. In this work, mackinawite (FeS)-activated sulfite autoxidation was employed for the degradation of IOP-containing water. The experiment was performed in a 500 mL self-made temperature-controlled reactor with online monitoring pH and dissolved oxygen in the laboratory. The effects of various parameters, such as initial pH values, sulfite dosages, FeS dosages, dissolved oxygen, and inorganic anions on the performance of the treatment process have been investigated. Eighty percent of IOP could be degraded in 15 min with 1 g L-1 FeS, 400 μmol L-1 sulfite at pH 8, and high efficiency on the removal of total organic carbon (TOC) was achieved, which is 71.8% via a reaction for 1 h. The generated hydroxyl and oxysulfur radicals, which contributed to the oxidation process, were identified through radical quenching experiments. The dissolved oxygen was essential for the degradation of IOP. The presence of Cl- could facilitate IOP degradation, while NO3- and CO32- could inhibit the degradation process. The reaction pathway involving H-abstraction and oxidative decarboxylation was proposed, based on product identification. The current system shows good applicability for the degradation of IOP and may help in developing a new approach for the treatment of ICM-containing water.

Synergistic effects of silver ions and metformin against enterococcus faecalis under high-glucose conditions in vitro

Background

This study aimed to evaluate the synergistic antibacterial activities of silver ions (Ag⁺) and metformin hydrochloride (Met) against Enterococcus faecalis (E. faecalis) under normal or high-glucose conditions.

Results

The minimum inhibitory concentration, minimum bactericidal concentration, growth curves, and colony-forming units were used to evaluate the antibacterial effects of Ag⁺ and Met on planktonic E. faecalis in Brain Heart Infusion broth with or without additional glucose. The influences of Ag⁺ and Met on four weeks E. faecalis biofilm on human dentin slices was also tested. Cytotoxicity was tested on MC3T3-E1 osteoblastic cells using CCK-8 assays. The results indicated that E. faecalis showed higher resistance to drug treatment under high-glucose conditions. Ag⁺ (40 μg/mL) plus Met (3.2% or 6.4%) showed enhanced antibacterial activities against both planktonic E. faecalis and biofilm on dentin slices, with low cytotoxicity.

Conclusions

Met enhanced the bactericidal effects of Ag⁺ against both planktonic and biofilm E. faecalis under normal or high-glucose conditions with low cytotoxicity. Further molecular studies are needed to be conducted to understand the mechanisms underlying the synergistic activity between Met and Ag⁺.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02291-2.

Mesoporous Calcium-Silicate Nanoparticles Loaded with Low-Dose Triton-100+Ag+ to Achieve Both Enhanced Antibacterial Properties and Low Cytotoxicity for Dentin Disinfection of Human Teeth

Mesoporous calcium-silicate nanoparticles (MCSNs) are excellent biomaterials for controlled drug delivery and mineralization induction. In this study, MCSNs were loaded with low-dose silver ion (Ag⁺) and Triton X-100 (TX-100) as the M-AgTX to achieve both enhanced antibacterial properties and low cytotoxicity for dentin disinfection. The physicochemical property, biocompatibility, infiltration ability into dentinal tubules, anti-bacterial ability against both planktonic Enterococcusfaecalis (E. faecalis) and its biofilm on dentin, effects on dentin microhardness and in vitro mineralization property were systematically investigated. Results confirmed that the MCSNs and M-AgTX nanoparticles showed typical morphology of mesoporous materials and exhibited sustained release of chemicals with an alkaline pH value over time. M-AgTX also exhibited excellent biocompatibility on MC3T3-E1 cells and could eliminate 100% planktonic E. faecalis after 48-h treatment. On dentin slices, it could enter dentinal tubules by ultrasonic activation and inhibit the growth of E. faecalis on dentin. M-AgTX could completely inactive 28-day E. faecalis biofilm. TEM confirmed the destruction of cell membrane integrity and Ag⁺ infiltration into bacteria by M-AgTX. Besides, dentin slices medicated with M-AgTX nanoparticles displayed an increased microhardness. After being immersed in SBF for 7 days, apatite crystals could be observed on the surface of the material tablets. M-AgTX could be developed into a new multifunctional intra-canal medication or bone defect filling material for infected bone defects due to its sustained release profile, low cytotoxicity, infiltration ability, enhanced anti-bacterial and mineralization features.