MAFFIN: Metabolomics Sample Normalization Using Maximal Density Fold Change with High-Quality Metabolic Features and Corrected Signal Intensities

Sample normalization is a critical step in metabolomics to remove differences in total sample amount or concentration of metabolites between biological samples. Here, we present MAFFIN, an accurate and robust post-acquisition sample normalization workflow that works universally for metabolomics data collected by mass spectrometry (MS)-based platforms. The most important design of MAFFIN is the calculation of normalization factor using maximal density fold change (MDFC) value computed by a kernel density-based approach. MDFC is more accurate than traditional median FC-based normalization, especially when the numbers of up- and down-regulated metabolic features are different. In addition, we showcase two essential steps that are overlooked by conventional normalization methods, and incorporated them into MAFFIN. First, instead of using all detected metabolic features, MAFFIN automatically extracts and uses only the high-quality features to calculate FCs and determine the normalization factor. In particular, multiple orthogonal criteria are proposed to pick up the high-quality features. Second, to guarantee the accuracy of the FCs, the MS signal intensities of the high-quality features are corrected using serial quality control (QC) samples. Using simulated data and urine metabolomics datasets, we demonstrated the critical need of high-quality feature selection, MS signal correction, and MDFC. We also show the superior performance of MAFFIN over other commonly used post-acquisition sample normalization methods. Finally, a biological application on a human saliva metabolomics study shows that MAFFIN provides robust sample normalization, leading to better data separation in principal component analysis (PCA) and the identification of more significantly altered metabolic features.

Single-Cells Isolation and Molecular Analysis: Focus on HER2-Low CTCs in Metastatic Breast Cancer

Although the detection of CTCs expressing HER2 at low intensity (HER2-low CTCs) has been shown to have a negative prognostic value in metastatic breast cancer (MBC) patients, the biological intrinsic nature of HER2-low CTCs remains unexplored. Considering the technical challenges behind the selective collection of immunophenotype-specific CTCs, we developed a pipeline to individually capture HER2-low CTCs. Four different breast cancer cell lines (MDA-MB-231, T47D, MDA-MB-453, and SKBR3), that are known to express HER2 at different immunohistochemistry levels (respectively classified as 0, 1+, 2+, and 3+), were spiked in healthy donor blood tubes (7.5 mL) and processed with the CellSearch® (Menarini Silicon Biosystems, Bologna, Italy) for enrichment and the DEPArray NxT™ for single cell selection. The HER2 signal-intensities of each cell line was compared using the nonparametric Mann–Whitney U test. The optimal cut-offs to distinguish HER2 1+ from 0 and 2+ cells were calculated performing the Receiver operating characteristic (ROC) curve. Median HER2 signal-intensities detected with the DEPArray NxT™ were: 2.59 (0), 3.58 (1+), 5.23 (2+) and 38.37 (3+). DEPArray NxT efficiently differentiated each single cell line (p < 0.001). The area under the ROC curve was 0.69 and 0.70 (respectively 0 vs. 1+ and 1+ vs. 2+) and the optimal calculated cut-offs were 2.85 (lower) and 4.64 (upper). HER2-low CTCs can be detected and separately collected using predetermined intensity cut-offs. This study will allow standardized single-cell or pooled collection of HER2-low CTCs for downstream molecular analyses.

MR Imaging of Pancreatic Lesions

Aim: The aim of this work was to evaluate the role of MRI in differentiating between benign and malignant pancreatic lesions and its correlation with histopathological results as the reference standard. Patients and Methods: This MRI study included 30 patients, 17 females and 13 males with a mean age 50 years. Sixteen patients had malignant masses (14 patients were adenocarcinoma, one patient was lymphoma and one patient was metastasis) and 14 patients had benign masses (7 patients were pancreatic pseudocysts, two patients were pancreatic abscesses, three patients were simple cysts and two patients were focal pancreatitis). The main clinical symptom was abdominal pain and most of masses were located in the head of the pancreas. Results: In our study, 25 cases of the 30 patients showed increased intensity at T2-weighted images. Most of malignant cases showed low or equal intensity on T1- and high intensity on T2-weighted images compared to normal pancreatic parenchyma. In our study, DW-MRI was performed on all subjects at b-values of 500 and 1000 s/mm2. Benign pancreatic masses as pancreatic pseudocyst, simple cyst and abscess show low signal intensities on DWI, however malignant pancreatic masses as adenocarcinoma, lymphoma and metastasis show high signal intensities on DWI with a cut-off value of 1.5 x10-3 s/mm2 for the differentiation of benign from malignant pancreatic masses by b-value 1000 s/mm2 with the sensitivity, specificity, PPV, NPV& p value were 100%, 83.33%, 100%, 88.88% and <0.001 respectively. Conclusion: MRI plays an important role in the diagnosis of different pancreatic lesions and can assess the neoplastic pancreatic lesions with accurate detection of extension, nodal involvement and hepatic metastatic lesions. It also has a major role in differentiation between benign and malignant pancreatic lesions by the aids of DWI.

Intensity of arterial structure acquired by Silent MRA estimates cerebral blood flow

Background Cerebral blood flow (CBF) and the morphology of the cerebral arteries are important for characterizing cerebrovascular disease. Silent magnetic resonance angiography (Silent MRA) is a MRA technique focusing on arterial structural delineation. This study was conducted to investigate the correlation between Silent MRA and CBF quantification, which has not yet been reported. Methods Both the Silent MRA and time-of-flight magnetic resonance angiography scans were applied in seventeen healthy participants to acquire the arterial structure and to find arterial intensities. Phase-contrast MRA (PC-MRA) was then used to perform the quantitative CBF measurement of 13 cerebral arteries. Due to different dataset baseline signal level of Silent MRA, the signal intensities of the selected 13 cerebral arteries were normalized to the selected ROIs of bilateral internal carotid arteries. The normalized signal intensities were used to determine the relationship between Silent MRA and CBF. Results The image intensity distribution of arterial regions generated by Silent MRA showed similar laminar shape as the phase distribution by PC-MRA (correlation coefficient > 0.62). Moreover, in both the results of individual and group-leveled analysis, the intensity value of arterial regions by Silent MRA showed positively correlation with the CBF by PC-MRA. The coefficient of determination (R2) of individual trends ranged from 0.242 to 0.956, and the R2 of group-leveled result was 0.550. Conclusions This study demonstrates that Silent MRA provides valuable CBF information despite arterial structure, rendering it a potential tool for screening for cerebrovascular disease.

Reproducibility Evaluation of Urinary Peptide Detection Using CE-MS

In recent years, capillary electrophoresis coupled to mass spectrometry (CE-MS) has been increasingly applied in clinical research especially in the context of chronic and age-associated diseases, such as chronic kidney disease, heart failure and cancer. Biomarkers identified using this technique are already used for diagnosis, prognosis and monitoring of these complex diseases, as well as patient stratification in clinical trials. CE-MS allows for a comprehensive assessment of small molecular weight proteins and peptides (<20 kDa) through the combination of the high resolution and reproducibility of CE and the distinct sensitivity of MS, in a high-throughput system. In this study we assessed CE-MS analytical performance with regards to its inter- and intra-day reproducibility, variability and efficiency in peptide detection, along with a characterization of the urinary peptidome content. To this end, CE-MS performance was evaluated based on 72 measurements of a standard urine sample (60 for inter- and 12 for intra-day assessment) analyzed during the second quarter of 2021. Analysis was performed per run, per peptide, as well as at the level of biomarker panels. The obtained datasets showed high correlation between the different runs, low variation of the ten highest average individual log2 signal intensities (coefficient of variation, CV < 10%) and very low variation of biomarker panels applied (CV close to 1%). The findings of the study support the analytical performance of CE-MS, underlining its value for clinical application.

Estimating nocturnal stroke onset times by magnetic resonance imaging in the WAKE-UP trial

Background Fluid-attenuated inversion recovery (FLAIR) sequences have gained a role to guide treatment of patients with unknown time of stroke symptom onset. Evolution of signal intensities in FLAIR is associated with time since stroke onset with continuous linear increases. Aims Estimating symptom onset during night-sleep in patients from the WAKE-UP trial based on relative signal intensities FLAIR (FLAIR-rSI) from acute stroke lesions an independent dataset (PRE-FLAIR study). Methods FLAIR-rSI was quantified in stroke lesions in PRE-FLAIR and WAKE-UP. The PRE-FLAIR study was a multicenter observational trial establishing FLAIR as a surrogate parameter for time since stroke onset. WAKE-UP was a randomized controlled trial that revealed a benefit for alteplase in patients selected based on a DWI-FLAIR mismatch. Stroke onset times were recorded in PRE-FLAIR and used to fit a linear regression model with FLAIR-rSI, adjusted for patient age and lesion volume. The model was applied to FLAIR-rSI of stroke lesions to estimate onset times in those patients enrolled in WAKE-UP who had symptom onset during night-sleep. Results FLAIR-rSI was quantified in 399 patients from PRE-FLAIR. Linear regression indicated a significant association of age ( p = 0.001), lesion volume ( p = 0.005) and FLAIR-rSI ( p < 0.001) with time since symptom onset (adjusted R2 = 0.179). In 813 patients from WAKE-UP, distribution of times of last seen well, symptom recognition and MRI examination were recorded. Median times of last seen well were 1 h before midnight (IQR 2.4 h) and symptom recognition 7 h after midnight (IRQ 2.2 h). Based on the FLAIR-rSI profiles, we estimated median stroke onset 6.1 h after midnight (IQR 2.7 h). Conclusion Nocturnal strokes during night-sleep may predominantly occur during the early morning hours. Our results are in line with evidence of characteristic diurnal patterns of cardiovascular events.

Application of Artificial Neural Network Based on Traditional Detection and GC-MS in Prediction of Free Radicals in Thermal Oxidation of Vegetable Oil

In this study, electron paramagnetic resonance (EPR) and gas chromatography-mass spectrometry (GC-MS) techniques were applied to reveal the variation of lipid free radicals and oxidized volatile products of four oils in the thermal process. The EPR results showed the signal intensities of linseed oil (LO) were the highest, followed by sunflower oil (SO), rapeseed oil (RO), and palm oil (PO). Moreover, the signal intensities of the four oils increased with heating time. GC-MS results showed that (E)-2-decenal, (E,E)-2,4-decadienal, and 2-undecenal were the main volatile compounds of oxidized oil. Besides, the oxidized PO and LO contained the highest and lowest contents of volatiles, respectively. According to the oil characteristics, an artificial neural network (ANN) intelligent evaluation model of free radicals was established. The coefficients of determination (R2) of ANN models were more than 0.97, and the difference between the true and predicted values was small, which indicated that oil profiles combined with chemometrics can accurately predict the free radical of thermal oxidized oil.

Human metabolism and urinary excretion of seven neonicotinoids and neonicotinoid-like compounds after controlled oral dosages

Few human data on exposure and toxicity are available on neonicotinoids and neonicotinoid-like compounds (NNIs), an important group of insecticides worldwide. Specifically, exposure assessment of humans by biomonitoring remains a challenge due to the lack of appropriate biomarkers. We investigated the human metabolism and metabolite excretion in urine of acetamiprid (ACE), clothianidin (CLO), flupyradifurone (FLUP), imidacloprid (IMI), sulfoxaflor (SULF), thiacloprid (THIAC) and thiamethoxam (THIAM) after single oral dosages at the currently acceptable daily intake levels of the European Food Safety Authority. Consecutive post-dose urine samples were collected up to 48 h. Suspect screening of tentative metabolites was carried out by liquid chromatography–high-resolution mass spectrometry. Screening hits were identified based on their accurate mass, isotope signal masses and ratios, product ion spectra, and excretion kinetics. We found, with the exception of SULF, extensive metabolization of NNIs to specific metabolites which were excreted next to the parent compounds. Overall, 24 metabolites were detected with signal intensities indicative of high metabolic relevance. Phase-I metabolites were predominantly derived by mono-oxidation (such as hydroxy-FLUP, -IMI, and -THIAC) and by oxidative N-desalkylation (such as N-desdifluoroethyl-FLUP and N-desmethyl-ACE, -CLO and -THIAM). IMI-olefin, obtained by dehydration of hydroxylated IMI, was identified as a major metabolite of IMI. SULF was excreted unchanged in urine. Previously reported metabolites of NNIs such as 6-chloronicotinic acid or 2-chlorothiazole-4-carboxylic acid and their glycine derivatives were detected either at low signal intensities or not at all and seem less relevant for human biomonitoring. Our highly controlled approach provides specific insight into the human metabolism of NNIs and suggests suitable biomarkers for future exposure assessment at environmentally relevant exposures.

Tubercular Tenosynovitis of Extensor Tendons of Ankle : A Case Report

Introduction:India being an endemic region for Tuberculosis (TB) has a high incidence of musculoskeletal TB with various presentations. Tenosynovitis is a rare presentation and few cases have been reported involving the hand and wrist but isolated involvement of extensor tendons at the ankle is even rarer and unreported. Case Report:Thirty-five-year-old female patient presenting with a dumbbell-shaped swelling over the anterolateral aspect of right ankle with mild dull aching pain. MRI revealed altered signal intensities surrounding the extensor tendons at the ankle without the involvement of the joint. Surgical debridement was done and six-month ATT was given. Gross specimen revealed rice bodies and histopathological examination showed caseous necrosis and epitheloid cell granulomas. Conclusion:Tuberculosis TB being endemic can have varied presentations, early diagnosis can be made if clinical suspicion for TB is considered. ATT is the mainstay of treatment, but surgical debridement is necessary for extensive lesions with compressive symptoms. Keywords:Tuberculosis, tenosynovitis, rice bodies, dumbbell dumbbell-shaped mass.