Updating M6 pregnancy of unknown location risk-prediction model including evaluation of clinical factors.

OBJECTIVES: Ectopic pregnancy (EP) is a major high-risk outcome following a pregnancy of unknown location (PUL) classification. Biochemical markers are used to triage PUL as high vs low risk to guide appropriate follow-up. The M6 model is currently the best risk-prediction model. We aimed to update the M6 model and evaluate whether performance can be improved by including clinical factors. METHODS: This prospective cohort study recruited consecutive PUL between January 2015 and January 2017 at eight units (Phase 1), with two centers continuing recruitment between January 2017 and March 2021 (Phase 2). Serum samples were collected routinely and sent for ß-human chorionic gonadotropin (ß-hCG) and progesterone measurement. Clinical factors recorded were maternal age, pain score, bleeding score and history of EP. Based on transvaginal ultrasonography and/or biochemical confirmation during follow-up, PUL were classified subsequently as failed PUL (FPUL), intrauterine pregnancy (IUP) or EP (including persistent PUL (PPUL)). The M6 models with (M6P ) and without (M6NP ) progesterone were refitted and extended with clinical factors. Model validation was performed using internal-external cross-validation (IECV) (Phase 1) and temporal external validation (EV) (Phase 2). Missing values were handled using multiple imputation. RESULTS: Overall, 5473 PUL were recruited over both phases. A total of 709 PUL were excluded because maternal age was < 16 years or initial ß-hCG was ≤ 25 IU/L, leaving 4764 (87%) PUL for analysis (2894 in Phase 1 and 1870 in Phase 2). For the refitted M6P model, the area under the receiver-operating-characteristics curve (AUC) for EP/PPUL vs IUP/FPUL was 0.89 for IECV and 0.84-0.88 for EV, with respective sensitivities of 94% and 92-93%. For the refitted M6NP model, the AUCs were 0.85 for IECV and 0.82-0.86 for EV, with respective sensitivities of 92% and 93-94%. Calibration performance was good overall, but with heterogeneity between centers. Net Benefit confirmed clinical utility. The change in AUC when M6P was extended to include maternal age, bleeding score and history of EP was between -0.02 and 0.01, depending on center and phase. The corresponding change in AUC when M6NP was extended was between -0.01 and 0.03. At the 5% threshold to define high risk of EP/PPUL, extending M6P altered sensitivity by -0.02 to -0.01, specificity by 0.03 to 0.04 and Net Benefit by -0.005 to 0.006. Extending M6NP altered sensitivity by -0.03 to -0.01, specificity by 0.05 to 0.07 and Net Benefit by -0.005 to 0.006. CONCLUSIONS: The updated M6 model offers accurate diagnostic performance, with excellent sensitivity for EP. Adding clinical factors to the model improved performance in some centers, especially when progesterone levels were not suitable or unavailable. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Seeded optical parametric generation in CdSiP2 pumped by a Raman fiber amplifier at 1.24 µm.

We report a seeded optical parametric generator (OPG) producing tunable radiation from 4.2-4.6 µm. The seeded OPG employs a 13 mm long CdSiP2 (CSP) crystal cut for non-critical phase-matching, pumped by a nanosecond-pulsed, MHz repetition rate Raman fiber amplifier system at 1.24 µm. A filtered, continuous-wave fiber supercontinuum source at 1.72 µm is used as the seed. The source generates up to 0.25 W of mid-infrared (MIR) idler power with a total pump conversion of 42% (combined signal and idler).

External validation of models to predict the outcome of pregnancies of unknown location: a multicentre cohort study.

OBJECTIVE: To validate externally five approaches to predict ectopic pregnancy (EP) in pregnancies of unknown location (PUL): the M6P and M6NP risk models, the two-step triage strategy (2ST, which incorporates M6P), the M4 risk model, and beta human chorionic gonadotropin ratio cut-offs (BhCG-RC). DESIGN: Secondary analysis of a prospective cohort study. SETTING: Eight UK early pregnancy assessment units. POPULATION: Women presenting with a PUL and BhCG >25 IU/l. METHODS: Women were managed using the 2ST protocol: PUL were classified as low risk of EP if presenting progesterone ≤2 nmol/l; the remaining cases returned 2 days later for triage based on M6P. EP risk ≥5% was used to classify PUL as high risk. Missing values were imputed, and predictions for the five approaches were calculated post hoc. We meta-analysed centre-specific results. MAIN OUTCOME MEASURES: Discrimination, calibration and clinical utility (decision curve analysis) for predicting EP. RESULTS: Of 2899 eligible women, the primary analysis excluded 297 (10%) women who were lost to follow up. The area under the ROC curve for EP was 0.89 (95% CI 0.86-0.91) for M6P, 0.88 (0.86-0.90) for 2ST, 0.86 (0.83-0.88) for M6NP and 0.82 (0.78-0.85) for M4. Sensitivities for EP were 96% (M6P), 94% (2ST), 92% (N6NP), 80% (M4) and 58% (BhCG-RC); false-positive rates were 35%, 33%, 39%, 24% and 13%. M6P and 2ST had the best clinical utility and good overall calibration, with modest variability between centres. CONCLUSIONS: 2ST and M6P performed best for prediction and triage in PUL. TWEETABLE ABSTRACT: The M6 model, as part of a two-step triage strategy, is the best approach to characterise and triage PULs.

Triaging women with pregnancy of unknown location using two-step protocol including M6 model: clinical implementation study.

OBJECTIVE: The M6 risk-prediction model was published as part of a two-step protocol using an initial progesterone level of ≤ 2 nmol/L to identify probable failing pregnancies (Step 1) followed by the M6 model (Step 2). The M6 model has been shown to have good triage performance for stratifying women with a pregnancy of unknown location (PUL) as being at low or high risk of harboring an ectopic pregnancy (EP). This study validated the triage performance of the two-step protocol in clinical practice by evaluating the number of protocol-related adverse events and how effectively patients were triaged. METHODS: This was a prospective multicenter interventional study of 3272 women with a PUL, carried out between January 2015 and January 2017 in four district general hospitals and four university teaching hospitals in the UK. The final pregnancy outcome was defined as: a failed PUL (FPUL), an intrauterine pregnancy (IUP) or an EP (including persistent PUL (PPUL)). FPUL and IUP were grouped as low-risk and EP/PPUL as high-risk PUL. Serum progesterone and human chorionic gonadotropin (hCG) levels were measured at presentation in all patients. If the initial progesterone level was ≤ 2 nmol/L, patients were discharged and were asked to have a follow-up urine pregnancy test in 2 weeks to confirm a negative result. If the progesterone level was > 2 nmol/L or a measurement had not been taken, hCG level was measured again at 48 h and results were entered into the M6 model. Patients were managed according to the outcome predicted by the protocol. Those classified as 'low risk, probable FPUL' were advised to perform a urine pregnancy test in 2 weeks and those classified as 'low risk, probable IUP' were invited for a scan a week later. When a woman with a PUL was classified as high risk (i.e. risk of EP ≥ 5%) she was reviewed clinically within 48 h. One center used a progesterone cut-off of ≤ 10 nmol/L and its data were analyzed separately. If the recommended management protocol was not adhered to, this was recorded as a protocol deviation and classified as: unscheduled visit for clinician reason, unscheduled visit for patient reason or incorrect timing of blood test or ultrasound scan. The classifications outlined in the UK Good Clinical Practice (GCP) guidelines were used to evaluate the incidence of adverse events. Data were analyzed using descriptive statistics. RESULTS: Of the 3272 women with a PUL, 2625 were included in the final analysis (317 met the exclusion criteria or were lost to follow-up, while 330 were evaluated using a progesterone cut-off of ≤ 10 nmol/L). Initial progesterone results were available for 2392 (91.1%) patients. In Step 1, 407 (15.5%) patients were classified as low risk (progesterone ≤ 2 nmol/L), of whom seven (1.7%) were ultimately diagnosed with an EP. In 279 of the remaining 2218 women with a PUL, the M6 model was not applied owing to protocol deviation or because the outcome was already known (usually on the basis of an ultrasound scan) before a second hCG reading was taken; of these patients, 30 were diagnosed with an EP. In Step 2, 1038 women with a PUL were classified as low risk, of whom eight (0.8%) had a final outcome of EP. Of 901 women classified as high risk at Step 2, 275 (30.5%) had an EP. Therefore, 275/320 (85.9%) EPs were correctly classified as high risk. Overall, 1445/2625 PUL (55.0%) were classified as low risk, of which 15 (1.0%) were EP. None of these cases resulted in a ruptured EP or significant clinical harm. Sixty-two women participating in the study had an adverse event, but no woman had a serious adverse event as defined in the UK GCP guidelines. CONCLUSIONS: This study has shown that the two-step protocol incorporating the M6 model effectively triaged the majority of women with a PUL as being at low risk of an EP, minimizing the follow-up required for these patients after just two visits. There were few misclassified EPs and none of these women came to significant clinical harm or suffered a serious adverse clinical event. The two-step protocol incorporating the M6 model is an effective and clinically safe way of rationalizing the management of women with a PUL. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

High average power parametric wavelength conversion at 3.31-3.48 m in MgO:PPLN.

We present results of high average power mid-infrared (mid-IR) generation employing synchronized nanosecond pulsed ytterbium and erbium fiber amplifier systems using periodically poled lithium niobate. We generate greater than 6 W of mid-IR radiation tunable in wavelength between 3.31-3.48 µm, at power conversion efficiencies exceeding 75%, with near diffraction limited beam quality (M2 = 1.4). Numerical modeling is used to verify the experimental results in differing pump depletion regimes.

The clinical performance of the M4 decision support model to triage women with a pregnancy of unknown location as at low or high risk of complications.

STUDY QUESTION: What are the adverse outcomes associated with using the M4 model in everyday clinical practice for women with pregnancy of unknown location (PUL)? SUMMARY ANSWER: There were 17/835 (2.0%) adverse events and no serious adverse events associated with the performance of the M4 model in clinical practice. WHAT IS KNOWN ALREADY: The M4 model has previously been shown to stratify women classified as a PUL as at low or high risk of complications with a good level of test performance. The triage performance of the M4 model is better than single measurements of serum progesterone or the hCG ratio (serum hCG at 48 h/hCG at presentation). STUDY DESIGN, SIZE, DURATION: A prospective multi-centre cohort study of 1022 women with a PUL carried out between August 2012 and December 2013 across 2 university teaching hospitals and 1 district general hospital. PARTICIPANTS/MATERIALS, SETTING, METHODS: All women presenting with a PUL to the early pregnancy units of the three hospitals were recruited. The final outcome for PUL was either a failed PUL (FPUL), intrauterine pregnancy (IUP) or ectopic pregnancy (EP) (including persistent PUL (PPUL)), with EP and PPUL considered high-risk PUL. Their hCG results at 0 and 48 h were entered into the M4 model algorithm. If the risk of EP was ≥5%, the PUL was predicted to be high-risk and the participant was asked to re-attend 48 h later for a repeat hCG and transvaginal ultrasound scan by a senior clinician. If the PUL was classified as 'low risk, likely failed PUL', the participant was asked to perform a urinary pregnancy test 2 weeks later. If the PUL was classified as 'low risk, likely intrauterine', the participant was scheduled for a repeat scan in 1 week. Deviations from the management protocol were recorded as either an 'unscheduled visit (participant reason)', 'unscheduled visit (clinician reason)' or 'differences in timing (blood test/ultrasound)'. Adverse events were assessed using definitions outlined in the UK Good Clinical Practice Guidelines' document. MAIN RESULTS AND THE ROLE OF CHANCE: A total of 835 (82%) women classified as a PUL were managed according to the M4 model (9 met the exclusion criteria, 69 were lost to follow-up, 109 had no hCG result at 48 h). Of these, 443 (53%) had a final outcome of FPUL, 298 (36%) an IUP and 94 (11%) an EP. The M4 model predicted 70% (585/835) PUL as low risk, of which 568 (97%) were confirmed as FPUL or IUP. Of the 17 EP and PPUL misclassified as low risk, 5 had expectant management, 7 medical management with methotrexate and 5 surgical intervention.Nineteen PUL had an unscheduled visit (participant reason), 38 PUL had an unscheduled visit (clinician reason) and 68 PUL had deviations from protocol due to a difference in timing (blood test/ultrasound).Adverse events were reported in 26 PUL and 1 participant had a serious adverse event. A total of 17/26 (65%) adverse events were misclassifications of a high risk PUL as low risk by the M4 model, while 5/26 (19%) adverse events were related to incorrect clinical decisions. Four of the 26 adverse events (15%) were secondary to unscheduled admissions for pain/bleeding. The serious adverse event was due to an incorrect clinical decision. LIMITATIONS, REASONS FOR CAUTION: A limitation of the study was that 69/1022 (7%) of PUL were lost to follow-up. A 48 h hCG level was missing for 109/1022 (11%) participants. WIDER IMPLICATIONS OF THE FINDINGS: The low number of adverse events (2.0%) suggests that expectant management of PUL using the M4 prediction model is safe. The model is an effective way of triaging women with a PUL as being at high- and low-risk of complications and rationalizing follow-up. The multi-centre design of the study is more likely to make the performance of the M4 model generalizable in other populations. STUDY FUNDING/COMPETING INTERESTS: None. TRIAL REGISTRATION NUMBER: Not applicable.

Can risk factors, clinical history and symptoms be used to predict risk of ectopic pregnancy in women attending an early pregnancy assessment unit?

OBJECTIVE: To examine whether risk factors and symptoms may be used to predict the likelihood of ectopic pregnancy (EP) in women attending early pregnancy assessment units in the UK. METHODS: This was an observational cohort study of pregnant women under 12 weeks' gestation who were recruited from three London university hospitals between August 2012 and April 2013. One hospital continued recruitment between January and June 2015. A standardized information sheet incorporating patient demographics, medical history and symptoms was completed by patients and confirmed by examining clinicians. The outcome measure was final pregnancy location. RESULTS: There were 1320 eligible patients included in the analysis, with a total of 72 EPs (rate of 6%). Pelvic pain and diarrhea > three times in the previous 24 h were independent symptoms that increased the risk of EP, with relative risks of 2.4 (95% CI, 1.4-4.0; P = 0.002) and 2.2 (95% CI, 1.08-4.5; P = 0.03), respectively. The only other independent marker of risk of EP was duration of vaginal bleeding; the risk of EP increased by 20% (95% CI, 14%-27%) for every 1-day increment in duration (P < 0.001). A logistic regression model incorporating these factors demonstrated an area under the receiver-operating characteristics curve of 0.73 (95% CI, 0.67-0.79). The prevalence of EP was low when there was no pelvic pain, no diarrhea and the duration of bleeding was ≤ 3 days, with an EP rate of 2% (6/391). In the presence of a single risk factor, the EP rate increased to 5% (29/631) when only pelvic pain was present, 8% (1/12) when only diarrhea > three times in the previous 24 h was reported and 9% (9/103) when there was only vaginal bleeding with a duration > 3 days. Women with pelvic pain and vaginal bleeding of any severity for > 3 days had a high EP rate of 16% (23/146). In the nine women who also reported diarrhea > three times in the previous 24 h, two had EP. CONCLUSIONS: Only the presence of pelvic pain, diarrhea > three times in the previous 24 h and duration of bleeding were symptoms that significantly increased the risk for EP in women attending early pregnancy assessment units. Risk factors and symptoms alone could not be used to predict reliably an EP. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

Managing pregnancy of unknown location based on initial serum progesterone and serial serum hCG levels: development and validation of a two-step triage protocol.

OBJECTIVES: A uniform rationalized management protocol for pregnancies of unknown location (PUL) is lacking. We developed a two-step triage protocol to select PUL at high risk of ectopic pregnancy (EP), based on serum progesterone level at presentation (step 1) and the serum human chorionic gonadotropin (hCG) ratio, defined as the ratio of hCG at 48 h to hCG at presentation (step 2). METHODS: This was a cohort study of 2753 PUL (301 EP), involving a secondary analysis of prospectively and consecutively collected PUL data from two London-based university teaching hospitals. Using a chronological split we used 1449 PUL for development and 1304 for validation. We aimed to assign PUL as low risk with high confidence (high negative predictive value (NPV)) while classifying most EP as high risk (high sensitivity). The first triage step assigned PUL as low risk using a threshold of serum progesterone at presentation. The remaining PUL were triaged using a novel logistic regression risk model based on hCG ratio and initial serum progesterone (second step), defining low risk as an estimated EP risk of < 5%. RESULTS: On validation, initial serum progesterone ≤ 2 nmol/L (step 1) classified 16.1% PUL as low risk. Second-step classification with the risk model selected an additional 46.0% of all PUL as low risk. Overall, the two-step protocol classified 62.1% of PUL as low risk, with an NPV of 98.6% and a sensitivity of 92.0%. When the risk model was used in isolation (i.e. without the first step), 60.5% of PUL were classified as low risk with 99.1% NPV and 94.9% sensitivity. CONCLUSION: PUL can be classified efficiently into being either high or low risk for complications using a two-step protocol involving initial progesterone and hCG levels and the hCG ratio. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

Multifunctional biosensors based on peptide-polyelectrolyte conjugates.

A novel enzymatic platform for the sensing of H2O2 and glucose that uses L,L-diphenylalanine micro/nanostructures (FF-MNSs) as an enzyme support is shown. This platform is obtained by the self-assembly of poly(allylamine hydrochloride) (PAH), FF-MNSs, and microperoxidase-11 (MP11) anchored onto the peptide matrix, in two different crystal structures of FF-MNSs: hexagonal (P61) and orthorhombic (P22121). The electroactive area of the electrodes increases in the presence of FF-MNSs. We also demonstrate via theoretical calculations that the valence band energy of the orthorhombic structure allows it to be doped, similarly to p-type semiconductors, where PAH acts as a doping agent for the orthorhombic peptide structure, decreasing the band-gap by around 1 eV, which results in a smaller charge transfer resistance. These results are consistent with electrochemical impedance spectroscopy measurements, which further elucidate the role of the band structure of the orthorhombic FF-MNSs in the conductivity and electron transfer rates of the hybrid material. An effective communication between the electrode and the active site of a glucose oxidase enzyme through MP11-protein complexes occurs, paving the way for FF-MNSs in the orthorhombic phase for the future development of bioelectronics sensing devices.

High rate of disease-related copy number variations in childhood onset schizophrenia.

Copy number variants (CNVs) are risk factors in neurodevelopmental disorders, including autism, epilepsy, intellectual disability (ID) and schizophrenia. Childhood onset schizophrenia (COS), defined as onset before the age of 13 years, is a rare and severe form of the disorder, with more striking array of prepsychotic developmental disorders and abnormalities in brain development. Because of the well-known phenotypic variability associated with pathogenic CNVs, we conducted whole genome genotyping to detect CNVs and then focused on a group of 46 rare CNVs that had well-documented risk for adult onset schizophrenia (AOS), autism, epilepsy and/or ID. We evaluated 126 COS probands, 69 of which also had a healthy full sibling. When COS probands were compared with their matched related controls, significantly more affected individuals carried disease-related CNVs (P=0.017). Moreover, COS probands showed a higher rate than that found in AOS probands (P<0.0001). A total of 15 (11.9%) subjects exhibited at least one such CNV and four of these subjects (26.7%) had two. Five of 15 (4.0% of the sample) had a 2.5-3 Mb deletion mapping to 22q11.2, a rate higher than that reported for adult onset (0.3-1%) (P<0.001) or autism spectrum disorder and, indeed, the highest rate reported for any clinical population to date. For one COS subject, a duplication found at 22q13.3 had previously only been associated with autism, and for four patients CNVs at 8q11.2, 10q22.3, 16p11.2 and 17q21.3 had only previously been associated with ID. Taken together, these findings support the well-known pleiotropic effects of these CNVs suggesting shared abnormalities early in brain development. Clinically, broad CNV-based population screening is needed to assess their overall clinical burden.

Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the Cognitive Genomics consorTium (COGENT).

It has long been recognized that generalized deficits in cognitive ability represent a core component of schizophrenia (SCZ), evident before full illness onset and independent of medication. The possibility of genetic overlap between risk for SCZ and cognitive phenotypes has been suggested by the presence of cognitive deficits in first-degree relatives of patients with SCZ; however, until recently, molecular genetic approaches to test this overlap have been lacking. Within the last few years, large-scale genome-wide association studies (GWAS) of SCZ have demonstrated that a substantial proportion of the heritability of the disorder is explained by a polygenic component consisting of many common single-nucleotide polymorphisms (SNPs) of extremely small effect. Similar results have been reported in GWAS of general cognitive ability. The primary aim of the present study is to provide the first molecular genetic test of the classic endophenotype hypothesis, which states that alleles associated with reduced cognitive ability should also serve to increase risk for SCZ. We tested the endophenotype hypothesis by applying polygenic SNP scores derived from a large-scale cognitive GWAS meta-analysis (~5000 individuals from nine nonclinical cohorts comprising the Cognitive Genomics consorTium (COGENT)) to four SCZ case-control cohorts. As predicted, cases had significantly lower cognitive polygenic scores compared to controls. In parallel, polygenic risk scores for SCZ were associated with lower general cognitive ability. In addition, using our large cognitive meta-analytic data set, we identified nominally significant cognitive associations for several SNPs that have previously been robustly associated with SCZ susceptibility. Results provide molecular confirmation of the genetic overlap between SCZ and general cognitive ability, and may provide additional insight into pathophysiology of the disorder.

Self-calibrating highly sensitive dynamic capacitance sensor: towards rapid sensing and counting of particles in laminar flow systems.

In this report we propose a sensor architecture and a corresponding read-out technique on silicon for the detection of dynamic capacitance change. This approach can be applied to rapid particle counting and single particle sensing in a fluidic system. The sensing principle is based on capacitance variation of an interdigitated electrode (IDE) structure embedded in an oscillator circuit. The capacitance scaling of the IDE results in frequency modulation of the oscillator. A demodulator architecture is employed to provide a read-out of the frequency modulation caused by the capacitance change. A self-calibrating technique is employed at the read-out amplifier stage. The capacitance variation of the IDE due to particle flow causing frequency modulation and the corresponding demodulator read-out has been analytically modelled. Experimental verification of the established model and the functionality of the sensor chip were shown using a modulating capacitor independent of fluidic integration. The initial results show that the sensor is capable of detecting frequency changes of the order of 100 parts per million (PPM), which translates to a shift of 1.43 MHz at 14.3 GHz operating frequency. It is also shown that a capacitance change every 3 µs can be accurately detected.

Label free sensing of creatinine using a 6 GHz CMOS near-field dielectric immunosensor.

In this work we present a CMOS high frequency direct immunosensor operating at 6 GHz (C-band) for label free determination of creatinine. The sensor is fabricated in standard 0.13 µm SiGe:C BiCMOS process. The report also demonstrates the ability to immobilize creatinine molecules on a Si3N4 passivation layer of the standard BiCMOS/CMOS process, therefore, evading any further need of cumbersome post processing of the fabricated sensor chip. The sensor is based on capacitive detection of the amount of non-creatinine bound antibodies binding to an immobilized creatinine layer on the passivated sensor. The chip bound antibody amount in turn corresponds indirectly to the creatinine concentration used in the incubation phase. The determination of creatinine in the concentration range of 0.88-880 µM is successfully demonstrated in this work. A sensitivity of 35 MHz/10 fold increase in creatinine concentration (during incubation) at the centre frequency of 6 GHz is gained by the immunosensor. The results are compared with a standard optical measurement technique and the dynamic range and sensitivity is of the order of the established optical indication technique. The C-band immunosensor chip comprising an area of 0.3 mm(2) reduces the sensing area considerably, therefore, requiring a sample volume as low as 2 µl. The small analyte sample volume and label free approach also reduce the experimental costs in addition to the low fabrication costs offered by the batch fabrication technique of CMOS/BiCMOS process.

Serum lipoprotein ratios as markers of insulin resistance: a study among non-diabetic acute coronary syndrome patients with impaired fasting glucose.

BACKGROUND & OBJECTIVES: Recent data suggest that insulin resistance can predict cardiovascular disease independently of the other risk factors, such as hypertension, visceral obesity or dyslipidaemia. However, the majority of available methods to evaluate insulin resistance are complicated to operate, expensive, and time consuming. This study was undertaken to assess whether serum lipoprotein ratios could predict insulin resistance in non-diabetic acute coronary syndrome (ACS) patients. METHODS: Ninety non-diabetic patients with impaired fasting glucose admitted with a diagnosis of ACS were included in the study. At the time of admission fasting glucose and insulin concentrations were measured. The homeostatic model assessment-insulin resistance (HOMA-IR) was used for insulin resistance. The fasting serum total cholesterol (TC), triglycerides (TG) and high density lipoprotein cholesterol (HDL-C) levels were checked, and then TC/HDL-C and TG/HDL-C ratios were calculated. The areas under the curves (AUC) of the receiver operating characteristic (ROC) curves were used to compare the power of these serum lipoprotein ratios as markers. RESULTS: Lipoprotein ratios were significantly higher in patients with HOMA-IR index > 2.5 as compared to patients with index <2.5 (P < 0.05). Both TG/HDL-C and TC/HDL-C ratios were significantly correlated with HOMA-IR (P<0.05). The area under the ROC curve of the TG/HDL-C and TC/HDL-C ratio for predicting insulin resistance was 0.80 (95% CI, 0.67 to 0.93), 0.78 (95% CI, 0.65 to 0.91), respectively. INTERPRETATION & CONCLUSIONS: The findings of this study demonstrate that serum lipoprotein ratios can provide a simple means of identifying insulin resistance and can be used as markers of insulin resistance and cardiovascular diseases risk in adult non-diabetic patients.

Bionanoparticles as candidate reference materials for mobility analysis of nanoparticles.

We propose bionanoparticles as a candidate reference material for determining the mobility of nanoparticles over the range of 6 × 10(-8)-5 × 10(-6) m(2)V(-1)s(-1). Using an electrospray differential mobility analyzer (ES-DMA), we measured the empirical distribution of several bionanoparticles. All of them show monomodal distributions that are more than two times narrower than the currently used calibration particles for mobility larger than 6 × 10(-8) m(2)V(-1)s(-1) (diameters less than 60 nm). We also present a numerical method to calculate corrected distributions of bionanoparticles by separating the contribution of the diffusive transfer function. The corrected distribution is about 20% narrower than the empirical distributions. Even with the correction, the reduced width of the mobility distribution is about a factor of 2 larger than the diffusive transfer function. The additional broadening could result from the nonuniform conformation of bionanoparticles and from the presence of volatile impurities or solvent adducts. The mobilities of these investigated bionanoparticle are stable over a range of buffer concentration and molarity, with no evidence of temporal degradation over several weeks.

Tensile Ge microstructures for lasing fabricated by means of a silicon complementary metal-oxide-semiconductor process.

In this work we study, using experiments and theoretical modeling, the mechanical and optical properties of tensile strained Ge microstructures directly fabricated in a state-of-the art complementary metal-oxide-semiconductor fabrication line, using fully qualified materials and methods. We show that these microstructures can be used as active lasing materials in mm-long Fabry-Perot cavities, taking advantage of strain-enhanced direct band gap recombination. The results of our study can be realistically applied to the fabrication of a prototype platform for monolithic integration of near infrared laser sources for silicon photonics.

Triaging pregnancies of unknown location: the performance of protocols based on single serum progesterone or repeated serum hCG levels.

STUDY QUESTION: How does a protocol based on a single serum progesterone measurement perform as a triage tool in women with pregnancy of unknown location (PUL) in comparison to protocols based on serial hCG measurement? SUMMARY ANSWER: Triage based on the logistic regression model M4 (using initial hCG and hCG ratio (48 h/0 h)) classifies the majority of PUL into low and high risk groups, in contrast to a progesterone protocol based on a serum level threshold of 10 nmol/l. WHAT IS KNOWN ALREADY: Low progesterone has been shown to identify failing pregnancies and those at low risk of complications. A prediction model (M4) based on the initial hCG and the hCG ratio at 0 and 48 h can successfully classify PUL into low and high risk groups. STUDY DESIGN, SIZE AND DURATION: A multi-centre diagnostic accuracy study of 1271 women was performed retrospectively on data from women at St. George's Hospital (SGH, London, UK) between February 2005 and 2006, Queen Charlottes & Chelsea Hospital (QCCH, London, UK) between April 2009 and August 2012, and the Royal Prince Alfred Hospital (RPAH, Sydney, Australia) between February 2008 and October 2011. The end-points were the final observed outcome for each pregnancy as a failed PUL (low risk), intrauterine pregnancy (IUP, low risk), or ectopic pregnancy (EP, high risk), and any interventions or complications for EP during the follow-up period. PARTICIPANTS/MATERIALS, SETTING AND METHODS: Complete data were available for initial progesterone, 0/48 h hCG and final outcome in 431 of 534 women (81%) at SGH, 396/585 (68%) at QCCH and 96/152 (63%) at RPAH. Missing values were handled using multiple imputation. Three diagnostic approaches were used to classify PUL as high risk: a range of serum progesterone levels were evaluated (>10, 16 and 20 nmol/l) for the progesterone protocol, risk of EP given by the M4 model ≥5% for the M4-based protocol, and hCG ratio was between 0.87 and 1.66 for hCG cut-offs as previously published. Results were analysed using random intercept models or stratified analysis to account for variability between centres. MAIN RESULTS AND THE ROLE OF CHANCE: The progesterone protocol based on levels of >10 nmol/l classified 24% (95% confidence interval 20-28%) of failed PUL, 95% (92-97%) of IUP and 76% (67-83%) of EP as high risk. The M4 protocol classified 14% (11-17%) of failed PUL, 37% (31-43%) of IUP and 84% (76-90%) of EP as high risk. The hCG ratio cut-offs classified 10% (8-12%) of failed PUL, 15% (11-20%) of IUP and 63% (53-71%) of EP as high risk. Using complete cases only, 67% of EP treated with methotrexate (n = 48) and 89% surgically managed (n = 37) were correctly classified by the progesterone protocol, 96 and 81% by M4 protocol and 75 and 65% by hCG ratio cut offs, respectively. LIMITATIONS, REASONS FOR CAUTION: Data were incomplete for 103 (19%), 189 (32%) and 56 (37%) patients at SGH, QCCH and RPAH, respectively; however, we are reassured by the minimal differences seen between the results of complete cases and those following imputation of missing values. The variation in the inclusion criteria between the three centres is also a potential limitation of this study; however, it reflects real clinical practice. Furthermore, the hCG ratio cut-offs were not originally developed to optimize triage. WIDER IMPLICATIONS OF THE FINDINGS: The results show that serum progesterone is less efficient for triage than serial hCG measurements assessed using the M4 model, the striking difference being serum progesterone places nearly all IUP in the high-risk category. A two-step strategy combining single-visit and two-visit approaches should be investigated. STUDY FUNDING/COMPETING INTERESTS: Funding was from Research Foundation-Flanders (FWO). There are no competing interests.

Caenorhabditis elegans RAC1/ced-10 mutants as a new animal model to study very early stages of Parkinson's disease.

Patients with Parkinson's disease (PD) display non-motor symptoms arising prior to the appearance of motor signs and before a clear diagnosis. Motor and non-motor symptoms correlate with progressive deposition of the protein alpha-synuclein (Asyn) both within and outside of the central nervous system, and its accumulation parallels neurodegeneration. The genome of Caenorhabditis elegans does not encode a homolog of Asyn, thus rendering this nematode an invaluable system with which to investigate PD-related mechanisms in the absence of interference from endogenous Asyn aggregation. CED-10 is the nematode homolog of human RAC1, a small GTPase needed to maintain the function and survival of dopaminergic neurons against human Asyn-induced toxicity in C. elegans. Here, we introduce C. elegans RAC1/ced-10 mutants as a predictive tool to investigate early PD symptoms before neurodegeneration occurs. Deep phenotyping of these animals reveals that, early in development, they displayed altered defecation cycles, GABAergic abnormalities and an increased oxidation index. Moreover, they exhibited altered lipid metabolism evidenced by the accumulation of lipid droplets. Lipidomic fingerprinting indicates that phosphatidylcholine and sphingomyelin, but not phosphatidylethanolamine or phosphatidylserine, were elevated in RAC1/ced-10 mutant nematodes. These collective characteristics reflect the non-motor dysfunction, GABAergic neurotransmission defects, upregulation of stress response mechanisms, and metabolic changes associated with early-onset PD. Thus, we put forward an easy-to-manipulate preclinical animal model to deepen our understanding of early-stage PD and accelerate the translational path for therapeutic target discovery.

External validation of models and simple scoring systems to predict miscarriage in intrauterine pregnancies of uncertain viability.

STUDY QUESTION: Does a logistic regression model and scoring system to predict viability of an intrauterine pregnancy of uncertain viability (PUV) perform as well in an independent patient group as the original patient group? SUMMARY ANSWER: The model and scoring system showed good performance on external validation confirming their value for the prediction of miscarriage/viability in PUV patients up to 11-14 weeks of gestation. WHAT IS KNOWN ALREADY: Several individual ultrasound and demographic factors have been described as predictors for miscarriage. A logistic regression model and simple scoring system using basic clinical and ultrasound features, such as maternal age, bleeding score, mean gestational sac diameter (MSD) and presence or absence of yolk sac, have been developed to allow patient-specific prediction of viability of PUV beyond the first trimester. STUDY DESIGN, SIZE, DURATION: Prospective observational external validation cohort study in two inner city early pregnancy assessment units over a period of 18 months. PARTICIPANTS/MATERIALS, SETTING, METHODS: All consecutive women with a PUV were recruited. Ultrasound (mean sac diameter and presence of yolk sac) and demographic variables (maternal age, bleeding score and gestational age) were noted. The outcome measure was first trimester (11-14 week) viability. Women with unknown first trimester outcome were excluded. Receiver operating characteristic (ROC) curves and calibration plots were constructed. Test performance was compared with the original development data set. A new model and scoring system, which did not include gestational age, was built and evaluated. MAIN RESULTS AND THE ROLE OF CHANCE: Of the 575 women who were recruited, first trimester outcome was known for 89.2% (n = 513). The model could only be validated in 400 patients, due to missing values in model variables and outcome. The model predicted viability with an area under the ROC curve (AUC) of 0.845 [95% confidence interval (CI), 0.806-0.884] compared with 0.774 (95% CI, 0.701-0.848) in the original study. The AUC for the scoring system was 0.832 (95% CI, 0.792-0.872) compared with 0.771 (95% CI, 0.698-0.844) from the original study data set. The new model and the scoring system, excluding gestational age, could be evaluated on 503 patients and resulted in an AUC of 0.801 (95% CI, 0.765-0.841) for the model and 0.773 (95% CI, 0.733-0.812) for the scoring system. LIMITATIONS, REASONS FOR CAUTION: Approximately 22% of patients could not be validated due to missing variables and for 11% of patients the first trimester outcome was unknown. WIDER IMPLICATIONS OF THE FINDINGS: Both the model and the scoring system showed excellent performance on external validation confirming their generalizability and utility in prediction of viability beyond the first trimester in clinical practice. An advantage of the mathematical models original Mo and new Mn and scoring systems original SSo and new SSn is that they can provide women with an individualized probability of the viability of their pregnancy using only demographic information, symptoms and TVS findings. Furthermore, the risk of miscarriage can be given immediately following examination. STUDY FUNDING/COMPETING INTEREST(S): T.B. is supported by the Imperial Healthcare NHS Trust NIHR Biomedical Research Centre. This research is supported by Research Council KUL GOA MaNet, iMinds 2012, Belgian Federal Science Policy Office IUAP P719. VVB is a postdoctoral fellow of the Research Foundation - Flanders (FWO). There are no conflicts of interest.