Maria Paraskevaidi

Adverse obstetric outcomes after local treatment for cervical preinvasive and early invasive disease according to cone depth: systematic review and meta-analysis.

Objective To assess the effect of treatment for cervical intraepithelial neoplasia (CIN) on obstetric outcomes and to correlate this with cone depth and comparison group used. Design Systematic review and meta-analysis. Data sources CENTRAL, Medline, Embase from 1948 to April 2016 were searched for studies assessing obstetric outcomes in women with or without previous local cervical treatment. Data extraction and synthesis Independent reviewers extracted the data and performed quality assessment using the Newcastle-Ottawa criteria. Studies were classified according to method and obstetric endpoint. Pooled risk ratios were calculated with a random effect model and inverse variance. Heterogeneity between studies was assessed with I2 statistics. Main outcome measures Obstetric outcomes comprised preterm birth (including spontaneous and threatened), premature rupture of the membranes, chorioamnionitis, mode of delivery, length of labour, induction of delivery, oxytocin use, haemorrhage, analgesia, cervical cerclage, and cervical stenosis. Neonatal outcomes comprised low birth weight, admission to neonatal intensive care, stillbirth, APGAR scores, and perinatal mortality. Results 71 studies were included (6 338 982 participants: 65 082 treated/6 292 563 untreated). Treatment significantly increased the risk of overall (<37 weeks; 10.7% v 5.4%; relative risk 1.78, 95% confidence interval 1.60 to 1.98), severe (<32-34 weeks; 3.5% v 1.4%; 2.40, 1.92 to 2.99), and extreme (<28-30 weeks; 1.0% v 0.3%; 2.54, 1.77 to 3.63) preterm birth. Techniques removing or ablating more tissue were associated with worse outcomes. Relative risks for delivery at <37 weeks were 2.70 (2.14 to 3.40) for cold knife conisation, 2.11 (1.26 to 3.54) for laser conisation, 2.02 (1.60 to 2.55) for excision not otherwise specified, 1.56 (1.36 to 1.79) for large loop excision of the transformation zone, and 1.46 (1.27 to 1.66) for ablation not otherwise specified. Compared with no treatment, the risk of preterm birth was higher in women who had undergone more than one treatment (13.2% v 4.1%; 3.78, 2.65 to 5.39) and with increasing cone depth (≤10-12 mm; 7.1% v 3.4%; 1.54, 1.09 to 2.18; ≥10-12 mm: 9.8% v 3.4%, 1.93, 1.62 to 2.31; ≥15-17 mm: 10.1% v 3.4%; 2.77, 1.95 to 3.93; ≥20 mm: 10.2% v 3.4%; 4.91, 2.06 to 11.68). The choice of comparison group affected the magnitude of effect. This was higher for external comparators, followed by internal comparators, and ultimately women with disease who did not undergo treatment. In women with untreated CIN and in pregnancies before treatment, the risk of preterm birth was higher than the risk in the general population (5.9% v 5.6%; 1.24, 1.14 to 1.35). Spontaneous preterm birth, premature rupture of the membranes, chorioamnionitis, low birth weight, admission to neonatal intensive care, and perinatal mortality were also significantly increased after treatment. Conclusions Women with CIN have a higher baseline risk for prematurity. Excisional and ablative treatment further increases that risk. The frequency and severity of adverse sequelae increases with increasing cone depth and is higher for excision than for ablation.

Differential diagnosis of Alzheimer’s disease using spectrochemical analysis of blood

Significance Vibrational spectroscopy is an ideal technique for analysis of biofluids, as it provides a “spectral fingerprint” of all of the molecules present within a biological sample, thus generating a holistic picture of the sample’s status. Neurodegenerative diseases lack early and accurate diagnosis, and tests currently used for their detection are either invasive or expensive and time-consuming. This study used blood plasma to diagnose and differentiate various neurodegenerative diseases; the achieved sensitivities and specificities are equal to, or even higher than, the ones obtained by clinical/molecular methods. Herein, we show that spectroscopy could provide a simple and robust diagnostic test. Additional work should include asymptomatic individuals for an early screening test and exploration of neurodegenerative diseases at all stages of severity. The progressive aging of the world’s population makes a higher prevalence of neurodegenerative diseases inevitable. The necessity for an accurate, but at the same time, inexpensive and minimally invasive, diagnostic test is urgently required, not only to confirm the presence of the disease but also to discriminate between different types of dementia to provide the appropriate management and treatment. In this study, attenuated total reflection FTIR (ATR-FTIR) spectroscopy combined with chemometric techniques were used to analyze blood plasma samples from our cohort. Blood samples are easily collected by conventional venepuncture, permitting repeated measurements from the same individuals to monitor their progression throughout the years or evaluate any tested drugs. We included 549 individuals: 347 with various neurodegenerative diseases and 202 age-matched healthy individuals. Alzheimer’s disease (AD; n = 164) was identified with 70% sensitivity and specificity, which after the incorporation of apolipoprotein ε4 genotype (APOE ε4) information, increased to 86% when individuals carried one or two alleles of ε4, and to 72% sensitivity and 77% specificity when individuals did not carry ε4 alleles. Early AD cases (n = 14) were identified with 80% sensitivity and 74% specificity. Segregation of AD from dementia with Lewy bodies (DLB; n = 34) was achieved with 90% sensitivity and specificity. Other neurodegenerative diseases, such as frontotemporal dementia (FTD; n = 30), Parkinson’s disease (PD; n = 32), and progressive supranuclear palsy (PSP; n = 31), were included in our cohort for diagnostic purposes. Our method allows for both rapid and robust diagnosis of neurodegeneration and segregation between different dementias.

Personalised management of women with cervical abnormalities using a clinical decision support scoring system

OBJECTIVES To develop a clinical decision support scoring system (DSSS) based on artificial neural networks (ANN) for personalised management of women with cervical abnormalities. METHODS We recruited women with cervical abnormalities and healthy controls that attended for opportunistic screening between 2006 and 2014 in 3 University Hospitals. We prospectively collected detailed patient characteristics, the colposcopic impression and performed a series of biomarkers using a liquid-based cytology sample. These included HPV DNA typing, E6&E7 mRNA by NASBA or flow cytometry and p16INK4a immunostaining. We used ANNs to combine the cytology and biomarker results and develop a clinical DSSS with the aim to improve the diagnostic accuracy of tests and quantify the individuals risk for different histological diagnoses. We used histology as the gold standard. RESULTS We analysed data from 2267 women that had complete or partial dataset of clinical and molecular data during their initial or followup visits (N=3565). Accuracy parameters (sensitivity, specificity, positive and negative predictive values) were assessed for the cytological result and/or HPV status and for the DSSS. The ANN predicted with higher accuracy the chances of high-grade (CIN2+), low grade (HPV/CIN1) and normal histology than cytology with or without HPV test. The sensitivity for prediction of CIN2 or worse was 93.0%, specificity 99.2% with high positive (93.3%) and negative (99.2%) predictive values. CONCLUSIONS The DSSS based on an ANN of multilayer perceptron (MLP) type, can predict with the highest accuracy the histological diagnosis in women with abnormalities at cytology when compared with the use of tests alone. A user-friendly software based on this technology could be used to guide clinician decision making towards a more personalised care.

Extracting biomarkers of commitment to cancer development: potential role of vibrational spectroscopy in systems biology.

The complex processes driving cancer have so far impeded the discovery of dichotomous biomarkers associated with its initiation and progression. Reductionist approaches utilizing ‘omics’ technologies have met some success in identifying molecular alterations associated with carcinogenesis. Systems biology is an emerging science that combines high-throughput investigation techniques to define the dynamic interplay between regulatory biological systems in response to internal and external cues. Vibrational spectroscopy has the potential to play an integral role within systems biology research approaches. It is capable of examining global models of carcinogenesis by scrutinizing chemical bond alterations within molecules. The application of infrared or Raman spectroscopic approaches coupled with computational analysis under the systems biology umbrella can assist the transition of biomarker research from the molecular level to the system level. The comprehensive representation of carcinogenesis as a multilevel biological process will inevitably revolutionize cancer-related healthcare by personalizing risk prediction and prevention.

Infrared Spectroscopy Coupled with a Dispersion Model for Quantifying the Real-Time Dynamics of Kanamycin Resistance in Artificial Microbiota

Overusage of antibiotics leads to the widespread induction of antibiotic-resistance genes (ARGs). Developing an approach to allow real-time monitoring and fast prediction of ARGs dynamics in clinical or environmental samples has become an urgent matter. Vibrational spectroscopy is potentially an ideal technique toward the characterization of the microbial composition of microbiota as it is nondestructive, high-throughput, and label-free. Herein, we employed attenuated total reflection Fourier transform infrared (ATR-FT-IR) spectroscopy and developed a spectrochemical tool to quantify the static and dynamic composition of kanamycin resistance in artificial microbiota to evaluate microbial antibiotic resistance. Second-order differentiation was introduced in identifying the spectral biomarkers, and principal component analysis followed by linear discriminant analysis (PCA-LDA) was used for the multivariate analysis of the entire spectral features employed. The calculated results of the mathematical dispersion model coupled with PCA-LDA showed high similarity to the designed microbiota structure, with no significant difference (P > 0.05) in the static treatments. Moreover, our model successfully predicted the dynamics of kanamycin resistance within artificial microbiota under kanamycin pressures. This work lends new insights into the potential role of spectrochemical analyses in investigating the existence and trends of antibiotic resistance in microbiota.

Raman spectroscopy to diagnose Alzheimer’s disease and dementia with Lewy bodies in blood

Accurate identification of Alzheimers disease (AD) is still of major clinical importance considering the current lack of noninvasive and low-cost diagnostic approaches. Detection of early stage AD is particularly desirable as it would allow early intervention or recruitment of patients into clinical trials. There is also an unmet need for discrimination of AD from dementia with Lewy bodies (DLB), as many cases of the latter are misdiagnosed as AD. Biomarkers based on a simple blood test would be useful in research and clinical practice. Raman spectroscopy has been implemented to analyze blood plasma of a cohort that consisted of early stage AD, late-stage AD, DLB, and healthy controls. Classification algorithms achieved high accuracy for the different groups: early stage AD vs healthy with 84% sensitivity, 86% specificity; late-stage AD vs healthy with 84% sensitivity, 77% specificity; DLB vs healthy with 83% sensitivity, 87% specificity; early-stage AD vs DLB with 81% sensitivity, 88% specificity; late-stage AD vs DLB with 90% sensitivity, 93% specificity; and lastly, early-stage AD vs late-stage AD 66% sensitivity and 83% specificity. G-score values were also estimated between 74% and 91%, demonstrating that the overall performance of the classification model was satisfactory. The wavenumbers responsible for differentiation were assigned to important biomolecules, which can serve as a panel of biomarkers. These results suggest a cost-effective, blood-based test for neurodegeneration in dementias.

Functional Single-Cell Approach to Probing Nitrogen-Fixing Bacteria in Soil Communities by Resonance Raman Spectroscopy with 15N2 Labeling

Nitrogen (N) fixation is the conversion of inert nitrogen gas (N2) to bioavailable N essential for all forms of life. N2-fixing microorganisms (diazotrophs), which play a key role in global N cycling, remain largely obscure because a large majority are uncultured. Direct probing of active diazotrophs in the environment is still a major challenge. Herein, a novel culture-independent single-cell approach combining resonance Raman (RR) spectroscopy with 15N2 stable isotope probing (SIP) was developed to discern N2-fixing bacteria in a complex soil community. Strong RR signals of cytochrome c (Cyt c, frequently present in diverse N2-fixing bacteria), along with a marked 15N2-induced Cyt c band shift, generated a highly distinguishable biomarker for N2 fixation. 15N2-induced shift was consistent well with 15N abundance in cell determined by isotope ratio mass spectroscopy. By applying this biomarker and Raman imaging, N2-fixing bacteria in both artificial and complex soil communities were discerned and imaged at the single-cell level. The linear band shift of Cyt c versus 15N2 percentage allowed quantification of N2 fixation extent of diverse soil bacteria. This single-cell approach will advance the exploration of hitherto uncultured diazotrophs in diverse ecosystems.

Underlying role of mitochondrial mutagenesis in the pathogenesis of a disease and current approaches for translational research

Mitochondrial diseases have been extensively investigated over the last three decades, but many questions regarding their underlying aetiologies remain unanswered. Mitochondrial dysfunction is not only responsible for a range of neurological and myopathy diseases but also considered pivotal in a broader spectrum of common diseases such as epilepsy, autism and bipolar disorder. These disorders are a challenge to diagnose and treat, as their aetiology might be multifactorial. In this review, the focus is placed on potential mechanisms capable of introducing defects in mitochondria resulting in disease. Special attention is given to the influence of xenobiotics on mitochondria; environmental factors inducing mutations or epigenetic changes in the mitochondrial genome can alter its expression and impair the whole cells functionality. Specifically, we suggest that environmental agents can cause damage in mitochondrial DNA and consequently lead to mutagenesis. Moreover, we describe current approaches for handling mitochondrial diseases, as well as available prenatal diagnostic tests, towards eliminating these maternally inherited diseases. Undoubtedly, more research is required, as current therapeutic approaches mostly employ palliative therapies rather than targeting primary mechanisms or prophylactic approaches. Much effort is needed into further unravelling the relationship between xenobiotics and mitochondria, as the extent of influence in mitochondrial pathogenesis is increasingly recognised.

Vibrational spectroscopy: a promising approach to discriminate neurodegenerative disorders

Neurodegenerative diseases are a growing burden in modern society, thus crucially calling for the development of accurate diagnostic strategies. These diseases are currently incurable, a fact which has been attributed to their late diagnosis, after brain damage has already become widespread. An earlier and improved diagnosis is necessary for the enrolment of patients into clinical trials and can pave the way for the development of therapeutic tactics. Novel analytical techniques, such as mass spectrometry and vibrational spectroscopy, have been able to successfully detect and characterise neurodegenerative disorders. It is critical to globally support and make use of innovative basic research and techniques, which could ultimately lead to the creation of a cost-effective diagnostic test. Minimally invasive samples, such as biological fluids, have also been shown to reveal information for these diseases; utilising them could simplify sample collection/analysis and be more preferable to patients.

Aluminium foil as an alternative substrate for the spectroscopic interrogation of endometrial cancer

Biospectroscopy has the potential to investigate and characterize biological samples and could, therefore, be utilized to diagnose various diseases in a clinical environment. An important consideration in spectrochemical studies is the cost-effectiveness of the substrate used to support the sample, as high expense would limit their translation into clinic. In this paper, the performance of low-cost aluminium (Al) foil substrates was compared with the commonly used low-emissivity (low-E) slides. Attenuated total reflection-Fourier transform infrared spectroscopy was used to analyse blood plasma and serum samples from women with endometrial cancer and healthy controls. The 2 populations were differentiated using principal component analysis with support vector machines with 100% sensitivity in plasma samples (endometrial cancer = 70; healthy controls = 15) using both Al foil and low-E slides as substrates. The same sensitivity results (100%) were achieved for serum samples (endometrial cancer = 60; healthy controls = 15). Specificity was found higher using Al foil (90%) in comparison to low-E slides (85%) and lower using Al foil (70%) in comparison to low-E slides in serum samples. The establishment of Al foil as low-cost and highly performing substrate would pave the way for large-scale, multicentre studies and potentially for routine clinical use.