Alterations in Faecal Metagenomics and Serum Metabolomics Indicate Management Strategies for Patients With Budd-Chiari Syndrome

We investigated the effects of gut microbiota and serum metabolite levels in patients with Budd-Chiari syndrome (B-CS) and their importance for guiding clinical management strategies. In total, 214 B-CS patients (93 untreated and 121 treated) and 41 healthy controls were enrolled. Gut microbiota and serum metabolome were analysed using shotgun metagenomics and liquid chromatography-mass spectrometry. The gut microbiota of the patients showed abundance of Campylobacter and low levels of Saccharomyces, Deinococcus, and Thiomonas (P < 0.05). Thirty metabolites, including taurocholate and (R)-3-hydroxybutyric acid, were identified in the patients (VIP > 1, P < 0.05 and FC > 1.2 or FC < 0.83). Random forest (RF) models showed that serum metabolome could effectively identify B-CS from healthy controls and RF-metabolomics exhibited perfect discrimination (AUC = 100%, 95% CI: 100% – 100%), which was significantly higher than that achieved by RF-metagenomics (AUC = 58.48%, 95% CI: 38.46% – 78.5%). Campylobacter concisus and taurocholate showed significant positive correlation in patients with clinical manifestations (P < 0.05). Actinobacteria levels were significantly higher in untreated patients than in treated patients (P < 0.05). Campylobacter and Veillonella levels were significantly higher in treated patients than in healthy controls (P < 0.05). We identified major alterations in the gut microbiota and serum metabolome of patients with B-CS. Faecal metagenomics- and serum metabolomics-guided management strategies are required for patients with B-CS.

Quantum nonlocality without entanglement: explicit dependence on prior probabilities of nonorthogonal mirror-symmetric states

In the case of a multi-party system, through local operations and classical communication (LOCC), each party may not perform perfect discrimination of quantum states that are separable and orthogonal. This property of quantum ensemble is called “nonlocality without entanglement” since each local party has a limit to full information of given quantum states. When this property is extended to the case of minimum-error discrimination, one can see that it is revealed when a nonlocal measurement provides more information about the unentangled states than LOCC does. One may infer the fact that the property depends on quantum states composing the quantum ensemble. However, an essential but unsettled question about the property is whether an explicit dependence on prior probabilities in terms of minimum-error discrimination could be shown in nonlocality without entanglement. In a simple term, one can ask whether different quantum ensembles made of the same separable quantum states could exhibit explicitly different behavior of the nonlocality. We answer this question in the positive, and we furthermore provide the explicit functional dependence of guessing probability on prior probabilities for the mirror-symmetric ensemble.

Whole brain 3D MR fingerprinting in multiple sclerosis: a pilot study

Background MR fingerprinting (MRF) is a novel imaging method proposed for the diagnosis of Multiple Sclerosis (MS). This study aims to determine if MR Fingerprinting (MRF) relaxometry can differentiate frontal normal appearing white matter (F-NAWM) and splenium in patients diagnosed with MS as compared to controls and to characterize the relaxometry of demyelinating plaques relative to the time of diagnosis. Methods Three-dimensional (3D) MRF data were acquired on a 3.0T MRI system resulting in isotropic voxels (1 × 1 × 1 mm3) and a total acquisition time of 4 min 38 s. Data were collected on 18 subjects paired with 18 controls. Regions of interest were drawn over MRF-derived T1 relaxometry maps encompassing selected MS lesions, F-NAWM and splenium. T1 and T2 relaxometry features from those segmented areas were used to classify MS lesions from F-NAWM and splenium with T-distributed stochastic neighbor embedding algorithms. Partial least squares discriminant analysis was performed to discriminate NAWM and Splenium in MS compared with controls. Results Mean out-of-fold machine learning prediction accuracy for discriminant results between MS patients and controls for F-NAWM was 65 % (p = 0.21) and approached 90 % (p < 0.01) for the splenium. There was significant positive correlation between time since diagnosis and MS lesions mean T2 (p = 0.015), minimum T1 (p = 0.03) and negative correlation with splenium uniformity (p = 0.04). Perfect discrimination (AUC = 1) was achieved between selected features from MS lesions and F-NAWM. Conclusions 3D-MRF has the ability to differentiate between MS and controls based on relaxometry properties from the F-NAWM and splenium. Whole brain coverage allows the assessment of quantitative properties within lesions that provide chronological assessment of the time from MS diagnosis.

Multiple-shot and unambiguous discrimination of von Neumann measurements

We present an in-depth study of the problem of multiple-shot discrimination of von Neumann measurements in finite-dimensional Hilbert spaces. Specifically, we consider two scenarios: minimum error and unambiguous discrimination. In the case of minimum error discrimination, we focus on discrimination of measurements with the assistance of entanglement. We provide an alternative proof of the fact that all pairs of distinct von Neumann measurements can be distinguished perfectly (i.e. with the unit success probability) using only a finite number of queries. Moreover, we analytically find the minimal number of queries needed for perfect discrimination. We also show that in this scenario querying the measurements in parallel gives the optimal strategy, and hence any possible adaptive methods do not offer any advantage over the parallel scheme. In the unambiguous discrimination scenario, we give the general expressions for the optimal discrimination probabilities with and without the assistance of entanglement. Finally, we show that typical pairs of Haar-random von Neumann measurements can be perfectly distinguished with only two queries.

A MALDI-TOF MS database for fast identification of Vibrio spp. potentially pathogenic to marine mollusks

In mollusk aquaculture, a large number of Vibrio species are considered major pathogens. Conventional methods based on DNA amplification and sequencing used to accurately identify Vibrio species are unsuitable for monitoring programs because they are time-consuming and expensive. The aim of this study was, therefore, to develop the MALDI-TOF MS method in order to establish a rapid identification technique for a large panel of Vibrio species. We created the EnviBase containing 120 main spectra projections (MSP) of the Vibrio species that are potentially responsible for mollusk diseases, comprising 25 species: V. aestuarianus, V. cortegadensis, V. tapetis and species belonging to the Coralliilyticus, Harveyi, Mediterranei, and Orientalis clades. Each MSP was constructed by the merger of raw spectra obtained from three different media and generated by three collaborating laboratories to increase the diversity of the conditions and thus obtain a good technique robustness. Perfect discrimination was obtained with all of the MSP created for the Vibrio species and even for very closely related species as V. europaeus and V. bivalvicida. The new EnviBase library was validated through a blind test on 100 Vibrio strains performed by our three collaborators who used the direct transfer and protein extraction methods. The majority of the Vibrio strains were successfully identified with the newly created EnviBase by the three laboratories for both protocol methods. This study documents the first development of a freely accessible database exclusively devoted to Vibrio found in marine environments, taking into account the high diversity of this genus. Key points • Development of a MALDI-TOF MS database to quickly affiliate Vibrio species. • Increase of the reactivity when faced with Vibrio associated with mollusk diseases. • Validation of MALDI-TOF MS as routine diagnostic tool.

Whole Brain 3D MR Fingerprinting in Multiple Sclerosis: A Pilot Investigation

Background: MR fingerprinting (MRF) is a novel imaging method proposed for the diagnosis of Multiple Sclerosis (MS). This study aims to determine if MR Fingerprinting (MRF) relaxometry can differentiate frontal normal appearing white matter (F-NAWM) and splenium in patients diagnosed with MS as compared to controls and to characterize the relaxometry of demyelinating plaques relative to the time of diagnosis.Methods: Three-dimensional (3D) MRF data were acquired on a 3.0T MRI system resulting in isotropic voxels (1x1x1mm3) and a total acquisition time of 4min 38s. Data were collected on 18 subjects paired with 18 controls. Regions of interested were drawn over MRF-derived T1 relaxometry maps encompassing selected MS lesions, F-NAWM and splenium. T1 and T2 relaxometry features from those segmented areas were used to classify MS lesions from F-NAWM and splenium with T-distributed stochastic neighbor embedding algorithms (T-SNE). Partial least squares discriminant analysis (PLS-DA) was performed to discriminate NAWM and Splenium in MS compared with controls. Results: Mean out-of-fold machine learning prediction accuracy for discriminant results between MS patients and controls for F-NAWM was 65% and approached 90% for the splenium. There was significant positive correlation between time since diagnosis and MS lesions mean T2 (p=0.015), minimum T1 (p=0.03) and negative correlation with splenium uniformity (p=0.04). Perfect discrimination (AUC=1) was achieved between selected features from MS lesions and F-NAWM.Conclusions: 3D-MRF has the ability to differentiate between MS and controls based on relaxometry properties from the F-NAWM and splenium. Whole brain coverage allows the assessment of quantitative properties within lesions that provide chronological assessment of the time from MS diagnosis.

Development of a diagnostic assay for race differentiation of Podosphaera macularis

Hop powdery mildew (caused by Podosphaera macularis) was confirmed in the Pacific Northwest in 1996. Before 2012, the most common race of P. macularis was able to infect plants that possessed powdery mildew resistance based on the R-genes Rb, R3, and R5. After 2012, two additional races of P. macularis were discovered that can overcome the resistance gene R6 and the partial resistance found in the cultivar Cascade. These three races now occur throughout the region, which can complicate management and research efforts because of uncertainty on which race(s) may be present in the region and able to infect susceptible hop genotypes. Current methods for determining the races of P. macularis are labor intensive, costly, and typically require more than 14 days to obtain results. We sought to develop a molecular assay to differentiate races of the fungus possessing virulence on plants with R6, referred to as V6-virulent, from other races. The transcriptomes of 46 isolates of P. macularis were sequenced to identify loci and variants unique to V6-isolates. Fourteen primer pairs were designed for 10 candidate loci that contained single nucleotide polymorphisms (SNP) and short insertion-deletion polymorphisms. Two differentially-labeled locked nucleic acid probes were designed for a contig that contained a conserved SNP associated with V6-virulence. The resulting duplexed real-time PCR assay was validated against 46 V6 and 54 non-V6 P. macularis isolates collected from the United States and Europe. The assay had perfect discrimination of V6-virulence among isolates of P. macularis originating from the western U.S. but failed to predict V6-virulence in three isolates collected from Europe. The specificity of the assay was tested with different species of powdery mildew fungi and other microorganisms associated with hop. Weak non-specific amplification occurred with powdery mildew fungi collected from Vitis vinifera, Fragaria sp., and Zinnia sp.; however, non-specification amplification is not a concern when differentiating pathogen race from colonies on hop. The assay has practical applications in hop breeding, epidemiological studies, and other settings where rapid confirmation of pathogen race is needed.

Androgen excess and diagnostic steroid biomarkers for nonclassic 21-hydroxylase deficiency without cosyntropin stimulation

Objectives The clinical presentation of patients with nonclassic 21-hydroxylase deficiency (N21OHD) is similar with that for other disorders of androgen excess. The diagnosis of N21OHD typically requires cosyntropin stimulation. Additionally, the management of such patients is limited by the lack of reliable biomarkers of androgen excess. Herein, we aimed to: (1.) compare the relative contribution of traditional and 11-oxyandrogens in N21OHD patients and (2.) identify steroids that accurately diagnose N21OHD with a single baseline blood draw. Design We prospectively enrolled patients who underwent a cosyntropin stimulation test for suspected N21OHD in two tertiary referral centers between January 2016 and August 2019. Methods Baseline sera were used to quantify 15 steroids by liquid chromatography-tandem mass spectrometry. Logistic regression modeling was implemented to select steroids that best discriminate N21OHD from controls. Results Of 86 participants (72 females), median age 26, 32 patients (25 females) had N21OHD. Age, sex distribution, and BMI were similar between patients with N21OHD and controls. Both testosterone and androstenedione were similar in patients with N21OHD and controls, while four 11-oxyandrogens were significantly higher in patients with N21OHD (ratios between medians: 1.7 to 2.2, P < 0.01 for all). 17α-Hydroxyprogesterone (6.5-fold), 16α-hydroxyprogesterone (4.1-fold), and 21-deoxycortisol (undetectable in 80% of the controls) were higher, while corticosterone was 3.6-fold lower in patients with N21OHD than in controls (P < 0.001). Together, baseline 17α-hydroxyprogesterone, 21-deoxycortisol, and corticosterone showed perfect discrimination between N21OHD and controls. Conclusions Adrenal 11-oxyandrogens are disproportionately elevated compared to conventional androgens in N21OHD. Steroid panels can accurately diagnose N21OHD in unstimulated blood tests.