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A 47-year-old man was diagnosed with left buccal squamous cell carcinoma using FDG PET/CT, by which focal lesions in the left buccal and left neck lymph node were found. Three months after the operation, CT images revealed a left lower lung lesion. Pathology indicated a left lower lung adenocarcinoma. Second FDG PET/CT was performed more than 11 days later, and lesions with intense FDG uptake were found in the left lower lung, metastatic to the lymph nodes, lungs, bones, and liver. The prior FDG PET/CT scan showed negative findings in the lungs. However, lung cancer with multiple metastases appeared 4 months later. [ABSTRACT FROM AUTHOR]

Radiogenomic heterogeneity features in 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) have become popular in non-small cell lung cancer (NSCLC) research. However, the reliabilities of genomic heterogeneity features and of PET-based glycolytic features in different image matrix sizes have yet to be thoroughly tested. We conducted a prospective study with 46 NSCLC patients to assess the intra-class correlation coefficient (ICC) of different genomic heterogeneity features. We also tested the ICC of PET-based heterogeneity features from different image matrix sizes. The association of radiogenomic features with clinical data was also examined. The entropy-based genomic heterogeneity feature (ICC = 0.736) is more reliable than the median-based feature (ICC = −0.416). The PET-based glycolytic entropy was insensitive to image matrix size change (ICC = 0.958) and remained reliable in tumors with a metabolic volume of <10 mL (ICC = 0.894). The glycolytic entropy is also significantly associated with advanced cancer stages (p = 0.011). We conclude that the entropy-based radiogenomic features are reliable and may serve as ideal biomarkers for research and further clinical use for NSCLC. [ABSTRACT FROM AUTHOR]

This work proposes a novel malware identification model that is based on a graph neural network (GNN). The function call relationship and function assembly content obtained by analyzing the malware are used to generate a graph that represents the functional structure of a malware sample. In addition to establishing a multi-classification model for predicting malware family, this work implements a similarity model that is based on Siamese networks, measuring the distance between two samples in the feature space to determine whether they belong to the same malware family. The distance between the samples is gradually adjusted during the training of the model to improve the performance. A Malware Bazaar dataset analysis reveals that the proposed classification model has an accuracy and area under the curve (AUC) of 0.934 and 0.997, respectively. The proposed similarity model has an accuracy and AUC of 0.92 and 0.92, respectively. Further, the proposed similarity model identifies the unseen malware family with approximately 70% accuracy. Hence, the proposed similarity model exhibits better performance and scalability than the pure classification model and previous studies. [ABSTRACT FROM AUTHOR]

Simple Summary: Patients with advanced epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma have been known to respond to first-line tyrosine kinase inhibitor (TKI) treatment. However, a subgroup of patients are non-responsive to the treatment, with poor survival outcomes, and those who are initially responsive may still experience resistance. A reliable prognostic tool may provide a valuable direction for tailoring individual treatment strategies in this clinical setting. With this aim, the present study explores the prognostic power of the combination of the systemic inflammation index (portrayed by hematological markers) and tumor glycolytic heterogeneity (characterized by 18F-fluorodeoxyglucose positron emission tomography images). The model integrating these two biomarkers could be used to improve risk stratification, and the subsequent personalized management strategy in patients with advanced EGFR-mutated lung adenocarcinoma. Tyrosine kinase inhibitors (TKIs) are the first-line treatment for patients with advanced epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma. Over half of patients failed to achieve prolonged survival benefits from TKI therapy. Awareness of a reliable prognostic tool may provide a valuable direction for tailoring individual treatments. We explored the prognostic power of the combination of systemic inflammation markers and tumor glycolytic heterogeneity to stratify patients in this clinical setting. One hundred and five patients with advanced EGFR-mutated lung adenocarcinoma treated with TKIs were retrospectively analyzed. Hematological variables as inflammation-induced biomarkers were collected, including the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and systemic inflammation index (SII). First-order entropy, as a marker of heterogeneity within the primary lung tumor, was obtained by analyzing 18F-fluorodeoxyglucose positron emission tomography images. In a univariate Cox regression analysis, sex, smoking status, NLR, LMR, PLR, SII, and entropy were associated with progression-free survival (PFS) and overall survival (OS). After adjusting for confounders in the multivariate analysis, smoking status, SII, and entropy, remained independent prognostic factors for PFS and OS. Integrating SII and entropy with smoking status represented a valuable prognostic scoring tool for improving the risk stratification of patients. The integrative model achieved a Harrell's C-index of 0.687 and 0.721 in predicting PFS and OS, respectively, outperforming the traditional TNM staging system (0.527 for PFS and 0.539 for OS, both p < 0.001). This risk-scoring model may be clinically helpful in tailoring treatment strategies for patients with advanced EGFR-mutated lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

We investigated whether the combination of primary tumor and nodal 18F-FDG PET parameters predict survival outcomes in patients with nodal metastatic non-small cell lung cancer (NSCLC) without distant metastasis. We retrospectively extracted pre-treatment 18F-FDG PET parameters from 89 nodal-positive NSCLC patients (stage IIB–IIIC). The Cox proportional hazard model was used to identify independent prognosticators of overall survival (OS) and progression-free survival (PFS). We devised survival stratification models based on the independent prognosticators and compared the model to the American Joint Committee on Cancer (AJCC) staging system using Harrell's concordance index (c-index). Our results demonstrated that total TLG (the combination of primary tumor and nodal total lesion glycolysis) and age were independent risk factors for unfavorable OS (p < 0.001 and p = 0.001) and PFS (both p < 0.001), while the Eastern Cooperative Oncology Group scale independently predicted poor OS (p = 0.022). Our models based on the independent prognosticators outperformed the AJCC staging system (c-index = 0.732 versus 0.544 for OS and c-index = 0.672 versus 0.521 for PFS, both p < 0.001). Our results indicate that incorporating total TLG with clinical factors may refine risk stratification in nodal metastatic NSCLC patients and may facilitate tailored therapeutic strategies in this patient group. [ABSTRACT FROM AUTHOR]

This study investigates whether baseline 18F-FDG PET radiomic features can predict survival outcomes in patients with diffuse large B-cell lymphoma (DLBCL). We retrospectively enrolled 83 patients diagnosed with DLBCL who underwent 18F-FDG PET scans before treatment. The patients were divided into the training cohort (n = 58) and the validation cohort (n = 25). Eighty radiomic features were extracted from the PET images for each patient. Least absolute shrinkage and selection operator regression were used to reduce the dimensionality within radiomic features. Cox proportional hazards model was used to determine the prognostic factors for progression-free survival (PFS) and overall survival (OS). A prognostic stratification model was built in the training cohort and validated in the validation cohort using Kaplan–Meier survival analysis. In the training cohort, run length non-uniformity (RLN), extracted from a gray level run length matrix (GLRLM), was independently associated with PFS (hazard ratio (HR) = 15.7, p = 0.007) and OS (HR = 8.64, p = 0.040). The International Prognostic Index was an independent prognostic factor for OS (HR = 2.63, p = 0.049). A prognostic stratification model was devised based on both risk factors, which allowed identification of three risk groups for PFS and OS in the training (p < 0.001 and p < 0.001) and validation (p < 0.001 and p = 0.020) cohorts. Our results indicate that the baseline 18F-FDG PET radiomic feature, RLNGLRLM, is an independent prognostic factor for survival outcomes. Furthermore, we propose a prognostic stratification model that may enable tailored therapeutic strategies for patients with DLBCL. [ABSTRACT FROM AUTHOR]

This meta-analysis aimed to assess the efficacy and safety of sitafloxacin in treating acute bacterial infection. PubMed, Embase, and Cochrane databases were searched up to August 13, 2019. Only randomized controlled trials (RCTs) evaluating sitafloxacin and comparators in the treatment of acute bacterial infections were included. The outcomes were clinical and microbiological responses and the risk of adverse event (AE). Five RCTs were enrolled, including 375 and 381 patients who received sitafloxacin and the comparator, respectively. Overall, the clinical response rate of sitafloxacin in the treatment of acute bacterial infections was 94.6%, which was noninferior to that of the comparator (92.5%) (odds ratio (OR), 1.01; 95% CI, 0.24–4.32; I2 = 66%). For patients with complicated urinary tract infection (cUTI)/acute pyelonephritis (APN), the clinical response rate of sitafloxacin and the comparator was 96.9% and 91.3%, respectively (OR, 2.08; 95% CI, 0.35–12.44; I2 = 54%). For patients with pneumonia, the clinical response rate of sitafloxacin was 88.6%, which was comparable to that of the comparator (OR, 0.36; 95% CI, 0.11–1.21; I2 = 0%). The microbiological response of sitafloxacin was 82.0%, which was noninferior to that of the comparator (77.8%) (OR, 1.59; 95% CI, 0.77–3.28; I2 = 47%). The risk of treatment-emergent adverse event (TEAE), drug-related TEAE, and all-cause mortality were similar between sitafloxacin and the comparators (TEAE, OR, 1.14; 95% CI, 0.64–2.01, drug-related TEAE, OR, 1.14; 95% CI, 0.48–2.69, mortality, OR, 0.93; 95% CI, 0.09–9.44). In conclusion, sitafloxacin is noninferior to other commonly used antibiotics with respect to both clinical and microbiological response rates in patients with an acute bacterial infection, including cUTI/APN and pneumonia. In addition, sitafloxacin is also as safe as the comparators. [ABSTRACT FROM AUTHOR]

This study aims to assess the efficacy and safety of doripenem on treating patients with acute bacterial infections. The Pubmed, Embase, and Cochrane databases were searched up to April 2019. Only randomized clinical trials comparing doripenem and other comparators for the treatment of acute bacterial infection were included. The primary outcome was the clinical success rate and the secondary outcomes were microbiological eradication rate and risk of adverse events. Eight randomized controlled trials (RCTs) were included. Overall, doripenem had a similar clinical success rate with comparators (odds ratio [OR], 1.15; 95% CI, 0.79–1.66, I2 = 58%). Similar clinical success rates were noted between doripenem and comparators for pneumonia (OR, 0.84; 95% CI, 0.46–1.53, I2 = 72%) and for intra-abdominal infections (OR, 1.00; 95% CI, 0.57–1.72). For complicated urinary tract infection, doripenem was associated with higher success rate than comparators (OR, 1.89, 95% CI, 1.13–3.17, I2 = 0%). The pool analysis comparing doripenem and other carbapenems showed no significant differences between each other (OR, 0.96, 95% CI, 0.59–1.58, I2 = 63%). Doripenem also had a similar microbiological eradication rate with comparators (OR, 1.08; 95% CI, 0.86–1.36, I2 = 0%). Finally, doripenem had a similar risk of treatment-emergent adverse events as comparators (OR, 0.98; 95% CI, 0.83–1.17, I2 = 33%). In conclusion, the clinical efficacy of doripenem is as high as that of the comparator drugs in the treatment of acute bacterial infection; furthermore, this antibiotic is as well tolerated as the comparators. [ABSTRACT FROM AUTHOR]

This meta-analysis aims to compare intravenous colistin monotherapy and colistin-based combination therapy against carbapenem-resistant gram-negative bacteria (GNB) infections. PubMed, Embase, and Cochrane databases were searched up to July 2018. Only randomized controlled trials (RCTs) evaluating colistin alone and colistin-based combination therapy in the treatment of carbapenem-resistant GNB infections were included. The primary outcome was all-cause mortality. Five RCTs including 791 patients were included. Overall, colistin monotherapy was associated with a risk ratio (RR) of 1.03 (95% confidence interval (CI), 0.89–1.20, I2 = 0%) for all-cause mortality compared with colistin-based combination therapy. The non-significant difference was also detected in infection-related mortality (RR, 1.23, 95% CI, 0.91–1.67, I2 = 0%) and microbiologic response (RR, 0.86, 95% CI, 0.72–1.04, I2 = 62%). In addition, no significant difference was observed in the subgroup analysis—high or low dose, with or without a loading dose, carbapenem-resistant Acinetobacter baumannii infections, and in combination with rifampicin. Finally, colistin monotherapy was not associated with lower nephrotoxicity than colistin combination therapy (RR, 0.98; 95% CI, 0.84–1.21, I2 = 0%). Based on the analysis of the five RCTs, no differences were found between colistin monotherapy and colistin-based combination therapy against carbapenem-resistant GNB infections, especially for A. baumannii infections. [ABSTRACT FROM AUTHOR]

Accurate analysis at the single-cell level has become a highly attractive tool for investigating cellular content. An electroosmotic-driven microfluidic chip with arrays of 30-μm-diameter microwells was developed for single-cell electric lysis in the present study. The cellular occupancy in the microwells when the applied voltage was 5 V (82.4%) was slightly higher than that at an applied voltage of 10 V (81.8%). When the applied voltage was increased to 15 V, the cellular occupancy in the microwells dropped to 64.3%. More than 50% of the occupied microwells contain individual cells. The results of electric lysis experiments at the single-cell level indicate that the cells were gradually lysed as the DC voltage of 30 V was applied; the cell was fully lysed after 25 s. Single-cell electric lysis was demonstrated in the proposed microfluidic chip, which is suitable for high-throughput cell lysis.