Maternal Serum Macrophage Inhibitory Cytokine-1 as a Biomarker for Ectopic Pregnancy in Women with a Pregnancy of Unknown Location

Ectopic pregnancy (EP) occurs in 1-2% of pregnancies, but is over-represented as a leading cause of maternal death in early pregnancy. It remains a challenge to diagnose early and accurately. Women often present in early pregnancy with a 'pregnancy of unknown location' (PUL) and the diagnosis and exclusion of EP is difficult due to a lack of reliable biomarkers. A serum biomarker able to clearly distinguish between EP and other pregnancy outcomes would greatly assist clinicians in diagnosing and safely managing PULs. This study evaluates the ability of maternal serum macrophage inhibitory cytokine-1 (MIC-1) levels to differentiate between EP and other pregnancy outcomes in women with a PUL.Sera were collected from 120 women with a PUL at first clinical presentation and assayed for MIC-1 by ELISA. Results were classified according to ultimate pregnancy outcome and the discriminatory ability of MIC-1 to diagnose EP was assessed.Serum MIC-1 levels were lower in women with histologically confirmed (definite) EP (dEP) (median 552 ng/mL; interquartile range (IQR) 414-693 ng/mL) compared to women with definite viable intra-uterine pregnancies (dVIUPs) (722 ng/mL; IQR 412-1122 ng/mL), and higher when compared to women with definite non-viable intra-uterine pregnancies (dNVIUPs) (465 ng/mL; IQR 341-675 ng/mL). MIC-1 levels were significantly higher in women with dEP compared to women whose PULs resolved without medical intervention (srPUL) (401 ng/mL; IQR 315-475 ng/mL) (p<0.003). There were no women with an ectopic pregnancy where serum MIC-1>1000 ng/mL.Serum MIC-1 levels in PUL were not able to categorically diagnose EP, however, MIC-1 could distinguish women with an EP that required medical intervention and those women whose PULs spontaneously resolved. A single serum MIC-1 measurement also excluded EP at levels above 1000 ng/mL. MIC-1 may play a role in the development of a combined assay of biomarkers for the diagnosis of EP

Astronomical Spectroscopy

Spectroscopy is one of the most important tools that an astronomer has for studying the universe. This chapter begins by discussing the basics, including the different types of optical spectrographs, with extension to the ultraviolet and the near-infrared. Emphasis is given to the fundamentals of how spectrographs are used, and the trade-offs involved in designing an observational experiment. It then covers observing and reduction techniques, noting that some of the standard practices of flat-fielding often actually degrade the quality of the data rather than improve it. Although the focus is on point sources, spatially resolved spectroscopy of extended sources is also briefly discussed. Discussion of differential extinction, the impact of crowding, multi-object techniques, optimal extractions, flat-fielding considerations, and determining radial velocities and velocity dispersions provide the spectroscopist with the fundamentals needed to obtain the best data. Finally the chapter combines the previous material by providing some examples of real-life observing experiences with several typical instruments.Comment: An abridged version of a chapter to appear in Planets, Stars and Stellar Systems, to be published in 2011 by Springer. Slightly revise

Interventions for improving oral health in people after stroke

BACKGROUND: For people with physical, sensory and cognitive limitations due to stroke, the routine practice of oral health care (OHC) may become a challenge. Evidence‐based supported oral care intervention is essential for this patient group. OBJECTIVES: To compare the effectiveness of OHC interventions with usual care or other treatment options for ensuring oral health in people after a stroke. SEARCH METHODS: We searched the Cochrane Stroke Group and Cochrane Oral Health Group trials registers, CENTRAL, MEDLINE, Embase, and six other databases in February 2019. We scanned reference lists from relevant papers and contacted authors and researchers in the field. We handsearched the reference lists of relevant articles and contacted other researchers. There were no language restrictions. SELECTION CRITERIA: We included randomised controlled trials (RCTs) that evaluated one or more interventions designed to improve the cleanliness and health of the mouth, tongue and teeth in people with a stroke who received assisted OHC led by healthcare staff. We included trials with a mixed population provided we could extract the stroke‐specific data. The primary outcomes were dental plaque or denture plaque. Secondary outcomes included presence of oral disease, presence of related infection and oral opportunistic pathogens related to OHC and pneumonia, stroke survivor and providers' knowledge and attitudes to OHC, and patient satisfaction and quality of life. DATA COLLECTION AND ANALYSIS: Two review authors independently screened abstracts and full‐text articles according to prespecified selection criteria, extracted data and assessed the methodological quality using the Cochrane 'Risk of bias' tool. We sought clarification from investigators when required. Where suitable statistical data were available, we combined the selected outcome data in pooled meta‐analyses. We used GRADE to assess the quality of evidence for each outcome. MAIN RESULTS: Fifteen RCTs (22 randomised comparisons) involving 3631 participants with data for 1546 people with stroke met the selection criteria. OHC interventions compared with usual care Seven trials (2865 participants, with data for 903 participants with stroke, 1028 healthcare providers, 94 informal carers) investigated OHC interventions compared with usual care. Multi‐component OHC interventions showed no evidence of a difference in the mean score (DMS) of dental plaque one month after the intervention was delivered (DMS –0.66, 95% CI –1.40 to 0.09; 2 trials, 83 participants; I(2) = 83%; P = 0.08; very low‐quality evidence). Stroke survivors had less plaque on their dentures when staff had access to the multi‐component OHC intervention (DMS –1.31, 95% CI –1.96 to –0.66; 1 trial, 38 participants; P < 0.0001; low‐quality evidence). There was no evidence of a difference in gingivitis (DMS –0.60, 95% CI –1.66 to 0.45; 2 trials, 83 participants; I(2) = 93%; P = 0.26: very low‐quality evidence) or denture‐induced stomatitis (DMS –0.33, 95% CI –0.92 to 0.26; 1 trial, 38 participants; P = 0.69; low‐quality evidence) among participants receiving the multi‐component OHC protocol compared with usual care one month after the intervention. There was no difference in the incidence of pneumonia in participants receiving a multi‐component OHC intervention (99 participants; 5 incidents of pneumonia) compared with those receiving usual care (105 participants; 1 incident of pneumonia) (OR 4.17, CI 95% 0.82 to 21.11; 1 trial, 204 participants; P = 0.08; low‐quality evidence). OHC training for stroke survivors and healthcare providers significantly improved their OHC knowledge at one month after training (SMD 0.70, 95% CI 0.06 to 1.35; 3 trials, 728 participants; I(2) = 94%; P = 0.03; very low‐quality evidence). Pooled data one month after training also showed evidence of a difference between stroke survivor and providers' oral health attitudes (SMD 0.28, 95% CI 0.01 to 0.54; 3 trials, 728 participants; I(2) = 65%; P = 0.06; very low‐quality evidence). OHC interventions compared with placebo Three trials (394 participants, with data for 271 participants with stroke) compared an OHC intervention with placebo. There were no data for primary outcomes. There was no evidence of a difference in the incidence of pneumonia in participants receiving an OHC intervention compared with placebo (OR 0.39, CI 95% 0.14 to 1.09; 2 trials, 242 participants; I(2) = 42%; P = 0.07; low‐quality evidence). However, decontamination gel reduced the incidence of pneumonia among the intervention group compared with placebo gel group (OR 0.20, 95% CI 0.05 to 0.84; 1 trial, 203 participants; P = 0.028). There was no difference in the incidence of pneumonia in participants treated with povidone‐iodine compared with a placebo (OR 0.81, 95% CI 0.18 to 3.51; 1 trial, 39 participants; P = 0.77). One OHC intervention compared with another OHC intervention Twelve trials (372 participants with stroke) compared one OHC intervention with another OHC intervention. There was no difference in dental plaque scores between those participants that received an enhanced multi‐component OHC intervention compared with conventional OHC interventions at three months (MD –0.04, 95% CI –0.33 to 0.25; 1 trial, 61 participants; P = 0.78; low‐quality evidence). There were no data for denture plaque. AUTHORS' CONCLUSIONS: We found low‐ to very low‐quality evidence suggesting that OHC interventions can improve the cleanliness of patient's dentures and stroke survivor and providers' knowledge and attitudes. There is limited low‐quality evidence that selective decontamination gel may be more beneficial than placebo at reducing the incidence of pneumonia. Improvements in the cleanliness of a patient's own teeth was limited. We judged the quality of the evidence included within meta‐analyses to be low or very low quality, and this limits our confidence in the results. We still lack high‐quality evidence of the optimal approach to providing OHC to people after stroke

Perceived barriers for treatment of chronic heart failure in general practice; are they affecting performance?

BACKGROUND: The aim of this study is to determine to what extent barriers perceived by general practitioners (GPs) for prescribing angiotensin-converting enzyme inhibitors (ACE-I) in chronic heart failure (CHF) patients are related to underuse and underdosing of these drugs in actual practice. METHODS: Barriers were assessed with a semi-structured questionnaire. Prescribing data were extracted from GPs' computerised medical records for a random sample of their CHF patients. Relations between barriers and prescribing behaviour were assessed by means of Spearman rank correlation and multivariate regression modelling. RESULTS: GPs prescribed ACE-I to 45% of their patients and had previously initiated such treatment in an additional 3.5%, in an average standardised dose of 13.5 mg. They perceived a median of four barriers in prescribing ACE-I or optimising ACE-I dose. Many GPs found it difficult to change treatment initiated by a cardiologist. Furthermore, initiating ACE-I in patients already using a diuretic or stable on their current medication was perceived as barrier. Titrating the ACE-I dose was seen as difficult by more than half of the GPs. No significant relationships could be found between the barriers perceived and actual ACE-I prescribing. Regarding ACE-I dosing, the few GPs who did not agree that the ACE-I should be as high as possible prescribed higher ACE-I doses. CONCLUSION: Variation between GPs in prescribing ACE-I for CHF cannot be explained by differences in the barriers they perceive. Tailor-made interventions targeting only those doctors that perceive a specific barrier will therefore not be an efficient approach to improve quality of care

Differential gene expression profile reveals deregulation of pregnancy specific β1 glycoprotein 9 early during colorectal carcinogenesis

BACKGROUND: APC (Adenomatous polyposis coli) plays an important role in the pathogenesis of both familial and sporadic colorectal cancer. Patients carrying germline APC mutations develop multiple colonic adenomas at younger age and higher frequency than non-carrier cases which indicates that silencing of one APC allele may be sufficient to initiate the transformation process. METHODS: To elucidate the biological dysregulation underlying adenoma formation we examined global gene expression profiles of adenomas and corresponding normal mucosa from an FAP patient. Differential expression of the most significant gene identified in this study was further validated by mRNA in situ hybridization, reverse transcriptase PCR and Northern blotting in different sets of adenomas, tumours and cancer cell lines. RESULTS: Eighty four genes were differentially expressed between all adenomas and corresponding normal mucosa, while only seven genes showed differential expression within the adenomas. The first group included pregnancy specific β-1 glycoprotein 9 (PSG9) (p < 0.006). PSG9 is a member of the carcinoembryonic antigen (CEA)/PSG family and is produced at high levels during pregnancy, mainly by syncytiotrophoblasts. Further analysis of sporadic and familial colorectal cancer confirmed that PSG9 is ectopically upregulated in vivo by cancer cells. In total, deregulation of PSG9 mRNA was detected in 78% (14/18) of FAP adenomas and 75% (45/60) of sporadic colorectal cancer cases tested. CONCLUSION: Detection of PSG9 expression in adenomas, and at higher levels in FAP cases, indicates that germline APC mutations and defects in Wnt signalling modulate PSG9 expression. Since PSG9 is not found in the non-pregnant adult except in association with cancer, and it appears to be an early molecular event associated with colorectal cancer monitoring of its expression may be useful as a biomarker for the early detection of this disease

How to screen for non-adherence to antihypertensive therapy

The quality of assessment of non-adherence to treatment in hypertensive is poor. Within this review, we discuss the different methods used to assess adherence to blood-pressure-lowering medications in hypertension patients. Subjective reports such as physicians’ perceptions are inaccurate, and questionnaires completed by patients tend to overreport adherence and show a low diagnostic specificity. Indirect objective methods such as pharmacy database records can be useful, but they are limited by the robustness of the recorded data. Electronic medication monitoring devices are accurate but usually track adherence to only a single medication and can be expensive. Overall, the fundamental issue with indirect objective measures is that they do not fully confirm ingestion of antihypertensive medications. Detection of antihypertensive medications in body fluids using liquid chromatography–tandem mass spectrometry is currently, in our view, the most robust and clinically useful method to assess non-adherence to blood-pressure-lowering treatment. It is particularly helpful in patients presenting with resistant, refractory or uncontrolled hypertension despite the optimal therapy. We recommend using this diagnostic strategy to detect non-adherence alongside a no-blame approach tailoring support to address the perceptions (e.g. beliefs about the illness and treatment) and practicalities (e.g. capability and resources) influencing motivation and ability to adhere

Consistency analysis of metabolic correlation networks

<p>Abstract</p> <p>Background</p> <p>Metabolic correlation networks are derived from the covariance of metabolites in replicates of metabolomics experiments. They constitute an interesting intermediate between topology (i.e. the system's architecture defined by the set of reactions between metabolites) and dynamics (i.e. the metabolic concentrations observed as fluctuations around steady-state values in the metabolic network).</p> <p>Results</p> <p>Here we analyze, how such a correlation network changes over time, and compare the relative positions of metabolites in the correlation networks with those in established metabolic networks derived from genome databases. We find that network similarity indeed decreases with an increasing time difference between these networks during a day/night course and, counter intuitively, that proximity of metabolites in the correlation network is no indicator of proximity of the metabolites in the metabolic network.</p> <p>Conclusion</p> <p>The organizing principles of correlation networks are distinct from those of metabolic reaction maps. Time courses of correlation networks may in the future prove an important data source for understanding these organizing principles.</p