The private, the public and the hybrid in umbilical cord blood banking – a global perspective

No description supplie

Occult axillary node metastases in breast cancer: their detection and prognostic significance.

Although the presence of axillary node metastases in breast cancer is a key prognostic indicator and may influence treatment decisions, a significant proportion of patients diagnosed as axillary node negative (ANN) using standard histopathological techniques may have occult nodal metastases (OMs). A combination of limited step-sectioning (4 x 100 microns intervals) and immunohistochemical staining (with cytokeratin (MNF.116) and MUC1 (BC2) antibodies) was used to detect OM in a retrospective series of 208 ANN patients. OMs were found in 53 patients (25%), and both step-sectioning and immunohistochemical detection significantly improved detection (P < 0.05). Detection using BC2 (25%) was superior to MNF.116 (18%) and haematoxylin and eosin (H&E) (8%). OMs were found in 51 patients using only the first and deepest sectioning levels and BC2 staining. OMs were more frequently found in lobular (38%) than ductal carcinoma (25%), and more frequently in women less than 50 years (41%) than in older women (19%). Univariate overall and disease-free survival analyses showed that the presence, size and number of OM had prognostic significance as did tumour size (disease-free only) and histological and nuclear grade (P > 0.05). Cox multivariate proportional hazard regression analyses showed that the presence and increasing size of OMs were significantly associated with poorer disease-free survival, independently of other prognostic factors (P < 0.05). However there was not a significant independent association of the presence of occult metastases with overall survival (P = 0.11). These findings have important implications with regard to selection of ANN patients for adjuvant therapy

How High? Trends in Cannabis Use Prior to First Admission to Inpatient Psychiatry in Ontario, Canada, between 2007 and 2017

Objectives: To examine the trends in cannabis use within 30 days of first admission to inpatient psychiatry in Ontario, Canada, between 2007 and 2017, and the characteristics of persons reporting cannabis use. Methods: A retrospective cross-sectional analysis was conducted for first-time admissions to nonforensic inpatient psychiatric beds in Ontario, Canada, between January 1, 2007, and December 31, 2017, using data from the Ontario Mental Health Reporting System (N = 81,809). Results: Across all years, 20.1% of patients reported cannabis use within 30 days of first admission. Use increased from 16.7% in 2007 to 25.9% in 2017, and the proportion with cannabis use disorders increased from 3.8% to 6.0%. In 2017, 47.9% of patients aged 18 to 24 and 39.2% aged 25 to 34 used cannabis, representing absolute increases of 8.3% and 10.7%, respectively. Increases in cannabis use were found across almost all diagnostic groups, with the largest increases among patients with personality disorders (15% increase), schizophrenia or other psychotic disorders (14% increase), and substance use disorders (14% increase). A number of demographic and clinical factors were significantly associated with cannabis use, including interactions between schizophrenia and gender (area under the curve = 0.88). Conclusions: As medical cannabis policies in Canada have evolved, cannabis use reported prior to first admission to inpatient psychiatry has increased. The findings of this study establish a baseline for evaluating the impact of changes in cannabis-related policies in Ontario on cannabis use prior to admission to inpatient psychiatry

Monoclonal antibodies reacting with the MUC2 mucin core protein.

This study sought to produce monoclonal antibodies (MAbs) which reacted with the MUC2 core protein. Two MAbs [3A2 (IgG1) and 4F1 (IgM)] were produced by immunising female BALB/c mice with gel-formed mucin from the LS174T colon cancer cell line followed by a KLH conjugate of a 29 amino acid synthetic peptide whose sequence was derived from the variable number of tandem repeats (VNTR) region of a MUC2 cDNA clone. The MAbs reacted with synthetic MUC2 VNTR peptides but not synthetic MUC1 or MUC3 VNTR peptides, and showed specific reactivity in Western blotting with a high molecular weight protein produced by the LS174T colon carcinoma cell line. The use of shorter peptides indicated that the minimum peptide epitopes for these MAbs were different. Mab 3A2 reacted with amino acids 5-19 of the MUC2 VNTR by inhibition ELISA but not by direct ELISA, while 4F1 reacted with this peptide in both assays. Furthermore, 4F1 reacted in direct ELISA when a larger (29 amino acid) MUC2-derived peptide was coated onto the assay plate by incubating in carbonate buffer or by drying the peptide onto the assay plate, while 3A2 only reacted when this peptide was coated in carbonate buffer. The different specificity of the MAbs was also illustrated by the reactivity of 4F1 but not 3A2 with partially deglycosylated cystic fibrosis mucin. Immunohistochemical analysis with these MAbs revealed a strong reactivity with lung, gastric and colon tumours relative to normal tissue, with some breast and ovarian tumours also reacting. Both MAbs stained some normal goblet cells in the perinuclear region but not the mucin droplet or secreted mucin, indicating a reaction with immature (poorly glycosylated) mucin in the endoplasmic reticulum and/or golgi, but not with mature (fully glycosylated) mucin. In contrast, tumours showed strong diffuse cytoplasmic staining. 4F1 also showed weak apical cytoplasmic staining in some goblet cells and stained some tumours which showed no reactivity with 3A2. These antibodies should prove useful in the study of MUC2 structure and function, and in the diagnosis of some tumours

Real-Time Cavity Fault Prediction in CEBAF Using Deep Learning

Data-driven prediction of future faults is a major research area for many industrial applications. In this work, we present a new procedure of real-time fault prediction for superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF) using deep learning. CEBAF has been afflicted by frequent downtime caused by SRF cavity faults. We perform fault prediction using pre-fault RF signals from C100-type cryomodules. Using the pre-fault signal information, the new algorithm predicts the type of cavity fault before the actual onset. The early prediction may enable potential mitigation strategies to prevent the fault. In our work, we apply a two-stage fault prediction pipeline. In the first stage, a model distinguishes between faulty and normal signals using a U-Net deep learning architecture. In the second stage of the network, signals flagged as faulty by the first model are classified into one of seven fault types based on learned signatures in the data. Initial results show that our model can successfully predict most fault types 200 ms before onset. We will discuss reasons for poor model performance on specific fault types

IL-22 mediates goblet cell hyperplasia and worm expulsion in intestinal helminth infection.

Type 2 immune responses are essential in protection against intestinal helminth infections. In this study we show that IL-22, a cytokine important in defence against bacterial infections in the intestinal tract, is also a critical mediator of anti-helminth immunity. After infection with Nippostrongylus brasiliensis, a rodent hookworm, IL-22-deficient mice showed impaired worm expulsion despite normal levels of type 2 cytokine production. The impaired worm expulsion correlated with reduced goblet cell hyperplasia and reduced expression of goblet cell markers. We further confirmed our findings in a second nematode model, the murine whipworm Trichuris muris. T.muris infected IL-22-deficient mice had a similar phenotype to that seen in N.brasiliensis infection, with impaired worm expulsion and reduced goblet cell hyperplasia. Ex vivo and in vitro analysis demonstrated that IL-22 is able to directly induce the expression of several goblet cell markers, including mucins. Taken together, our findings reveal that IL-22 plays an important role in goblet cell activation, and thus, a key role in anti-helminth immunity

Prostate-Specific Ets (PSE) factor: a novel marker for detection of metastatic breast cancer in axillary lymph nodes

Prostate Specific Ets factor is a recently identified transcriptional activator that is overexpressed in prostate cancer. To determine whether this gene is overexpressed in breast cancer, we performed a virtual Northern blot using data available online at the Cancer Genome Anatomy Project website. Ninety-five SAGE libraries were probed with a unique sequence tag to the Prostate Specific Ets gene. The results indicate that Prostate Specific Ets is expressed in 14 out of 15 breast cancer libraries (93%), nine out of 10 prostate cancer libraries (90%), three out of 40 libraries from other cancers (7.5%), and four out of 30 normal tissue libraries (13%). To determine the possibility that the Prostate Specific Ets gene is a novel marker for detection of metastatic breast cancer in axillary lymph nodes, quantitative real-time RT–PCR analyses were performed. The mean level of Prostate Specific Ets expression in lymph nodes containing metastatic breast cancer (n=22) was 410-fold higher than in normal lymph node (n=51). A receiver operator characteristic curve analysis indicated that Prostate Specific Ets was overexpressed in 18 out of 22 lymph nodes containing metastatic breast cancer (82%). The receiver operator characteristic curve analysis also indicated that the diagnostic accuracy of the Prostate Specific Ets gene for detection of metastatic breast cancer in axillary lymph nodes was 0.949. These results provide evidence that Prostate Specific Ets is a potentially informative novel marker for detection of metastatic breast cancer in axillary lymph nodes, and should be included in any study that involves molecular profiling of breast cancer

Use of Binary Cumulative Sums and Moving Averages in Nosocomial Infection Cluster Detection1

Clusters of nosocomial infection often occur undetected, at substantial cost to the medical system and individual patients. We evaluated binary cumulative sum (CUSUM) and moving average (MA) control charts for automated detection of nosocomial clusters. We selected two outbreaks with genotyped strains and used resistance as inputs to the control charts. We identified design parameters for the CUSUM and MA (window size, k, α, β, p0, p1) that detected both outbreaks, then calculated an associated positive predictive value (PPV) and time until detection (TUD) for sensitive charts. For CUSUM, optimal performance (high PPV, low TUD, fully sensitive) was for 0.1 <α ≤0.25 and 0.2 <β <0.25, with p0 = 0.05, with a mean TUD of 20 (range 8–43) isolates. Mean PPV was 96.5% (relaxed criteria) to 82.6% (strict criteria). MAs had a mean PPV of 88.5% (relaxed criteria) to 46.1% (strict criteria). CUSUM and MA may be useful techniques for automated surveillance of resistant infections

Is the impact of hospital performance data greater in patients who have compared hospitals?

<p>Abstract</p> <p>Background</p> <p>Public information on average has limited impact on patients' hospital choice. However, the impact may be greater in consumers who have compared hospitals prior to their hospital choice. We therefore assessed whether patients who have compared hospitals based their hospital choice mainly on public information, rather than e.g. advice of their general practitioner and consider other information important than patients who have not compared hospitals.</p> <p>Methods</p> <p>337 new surgical patients completed an internet-based questionnaire. They were asked whether they had compared hospitals prior to their hospital choice and which factors influenced their choice. They were also asked to select between four and ten items of hospital information (total: 41 items) relevant for their future hospital choice. These were subsequently used in a hospital choice experiment in which participants were asked to compare hospitals in an Adaptive Choice-Based Conjoint analysis to estimate which of the hospital characteristics had the highest Relative Importance (RI).</p> <p>Results</p> <p>Patients who have compared hospitals more often used public information for their hospital choice than patients who have not compared hospitals (12.7% vs. 1.5%, p < 0.001). However, they still mostly relied on their own (47.9%) and other people's experiences (31%) rather than to base their decision on public information. Both groups valued physician's expertise (RI 20.2 [16.6-24.8] in patients comparing hospitals vs. 16.5 [14.2-18.8] in patients not comparing hospitals) and waiting time (RI 15.1 [10.7-19.6] vs. 15.6 [13.2-17.9] respectively) as most important public information. Patients who have compared hospitals assigned greater importance to information on wound infections (p = 0.010) and respect for patients (p = 0.022), but lower importance to hospital distance (p = 0.041).</p> <p>Conclusion</p> <p>Public information has limited impact on patient's hospital choice, even in patients who have actually compared hospitals prior to hospital choice.</p