Automatic three-dimensional reconstruction of the oesophagus in achalasia patients undergoing POEM: an innovative approach for evaluating treatment outcomes.

BACKGROUND AND AIMS: Peroral endoscopic myotomy (POEM) is a standard treatment option for achalasia patients. Treatment response varies due to factors such as achalasia type, degree of dilatation, pressure and distensibility indices. We present an innovative approach for treatment response prediction based on an automatic three-dimensional (3-D) reconstruction of the tubular oesophagus (TE) and the lower oesophageal sphincter (LES) in patients undergoing POEM for achalasia. METHODS: A software was developed, integrating data from high-resolution manometry, timed barium oesophagogram and endoscopic images to automatically generate 3-D reconstructions of the TE and LES. Novel normative indices for TE (volume×pressure) and LES (volume/pressure) were automatically integrated, facilitating pre-POEM and post-POEM comparisons. Treatment response was evaluated by changes in volumetric and pressure indices for the TE and the LES before as well as 3 and 12 months after POEM. In addition, these values were compared with normal value indices of non-achalasia patients. RESULTS: 50 treatment-naive achalasia patients were enrolled prospectively. The mean TE index decreased significantly (p<0.0001) and the mean LES index increased significantly 3 months post-POEM (p<0.0001). In the 12-month follow-up, no further significant change of value indices between 3 and 12 months post-POEM was seen. 3 months post-POEM mean LES index approached the mean LES of the healthy control group (p=0.077). CONCLUSION: 3-D reconstruction provides an interactive, dynamic visualisation of the oesophagus, serving as a comprehensive tool for evaluating treatment response. It may contribute to refining our approach to achalasia treatment and optimising treatment outcomes. TRIAL REGISTRATION NUMBER: 22-0149.

Early medieval vernacular Celtic glosses: originals or translations? A case study on the Vienna Bede.

This study investigates the Old Irish glossing tradition on the Venerable Bede's De Temporum Ratione, a computistical work from the early eighth century. Its main source is the Vienna Bede, a fragmentary manuscript with Old Irish and Latin glosses dating from the late eighth/early ninth centuries. It focuses on parallel glosses found in the Gloss-ViBe corpus where the Vienna Bede has an Old Irish gloss and the other manuscripts feature glosses in another language (Latin or Old Breton/Welsh). Minute analysis of individual glosses is used to determine whether early medieval vernacular Celtic glosses originals or translations from Latin glosses? The heterogenic nature of early medieval gloss corpora makes this a complex question for which there is no straightforward answer: for some glosses, a translation from Latin into Irish is almost inevitable, but others suggest Irish influence on the Latin parallel glosses. Accordingly, each case is discussed individually and the results are synthesised in the final part of the article.

In 725 the English monk Bede wrote the Reckoning of Time, a book about calculating time and making a calendar. ¹ This was mainly important to solve a complicated mathematical problem: what is the date of Easter? The work was widely distributed. Early medieval scholars annotated their copies. These annotations are also called glosses and are a great source of information about contact between people in this period. Glosses appear in different languages, e.g., Latin, or the Insular Celtic languages, i.e., Old Irish, Old Breton or Old Welsh. As the manuscripts were copied the glosses were also copied and sometimes translated into a different language. This helps us to understand the history of the annotations on Bede's Reckoning of Time. This study looks at one manuscript, the Vienna Bede, which dates to the late eighth or early ninth centuries. It compares it to three other manuscripts from around the same time. The comparisons show how closely linked the four manuscripts are. Some of the parallels can even show which language the glosses were translated from. Translations can go from Latin to the Celtic languages and the other way around.

Towards Automated COVID-19 Presence and Severity Classification.

COVID-19 presence classification and severity prediction via (3D) thorax computed tomography scans have become important tasks in recent times. Especially for capacity planning of intensive care units, predicting the future severity of a COVID-19 patient is crucial. The presented approach follows state-of-theart techniques to aid medical professionals in these situations. It comprises an ensemble learning strategy via 5-fold cross-validation that includes transfer learning and combines pre-trained 3D-versions of ResNet34 and DenseNet121 for COVID19 classification and severity prediction respectively. Further, domain-specific preprocessing was applied to optimize model performance. In addition, medical information like the infection-lung-ratio, patient age, and sex were included. The presented model achieves an AUC of 79.0% to predict COVID-19 severity, and 83.7% AUC to classify the presence of an infection, which is comparable with other currently popular methods. This approach is implemented using the AUCMEDI framework and relies on well-known network architectures to ensure robustness and reproducibility.

Towards automatic airborne pollen monitoring: From commercial devices to operational by mitigating class-imbalance in a deep learning approach.

Allergic diseases have been the epidemic of the century among chronic diseases. Particularly for pollen allergies, and in the context of climate change, as airborne pollen seasons have been shifting earlier and abundances have been becoming higher, pollen monitoring plays an important role in generating high-risk allergy alerts. However, this task requires labour-intensive and time-consuming manual classification via optical microscopy. Even new-generation, automatic, monitoring devices require manual pollen labelling to increase accuracy and to advance to genuinely operational devices. Deep Learning-based models have the potential to increase the accuracy of automated pollen monitoring systems. In the current research, transfer learning-based convolutional neural networks were employed to classify pollen grains from microscopic images. Given a high imbalance in the dataset, we incorporated class weighted loss, focal loss and weight vector normalisation for class balancing as well as data augmentation and weight penalties for regularisation. Airborne pollen has been routinely recorded by a Bio-Aerosol Analyzer (BAA500, Hund GmbH) located in Augsburg, Germany. Here we utilised a database referring to manually classified airborne pollen images of the whole pollen diversity throughout an annual pollen season. By using the cropped pollen images collected by this device, we achieved an unweighted average F1 score of 93.8% across 15 classes and an unweighted average F1 score of 75.9% across 31 classes. The majority of taxa (9 of 15), being also the most abundant and allergenic, showed a recall of at least 95%, reaching up to a remarkable 100% in pollen from Taxus and Urticaceae. The recent introduction of novel pollen monitoring devices worldwide has pointed to the necessity for real-time, automatic measurements of airborne pollen and fungal spores. Thus, we may improve everyday clinical practice and achieve the most efficient prophylaxis of allergic patients.

Modulating tiller formation in cereal crops by the signalling function of fertilizer nitrogen forms.

Cereal crop yield comprises interrelated components, among which the number of tillers is highly responsive to nitrogen fertilization. We addressed the hypothesis of whether the supply of different nitrogen forms can be employed to manipulate the tiller number in cereal crops. Relative to urea or ammonium, exclusive supply of nitrate increased tiller number in hydroponically-grown barley plants. Thereby, tiller number correlated positively with the root-to-shoot translocation rate of endogenous cytokinins. External supply of a synthetic cytokinin analog further stimulated tillering in nitrate-containing but not in urea-containing nutrient solution. When the cytokinin analog 6-benzylaminopurine riboside was externally supplied to roots, its translocation to shoots was 2.5 times higher in presence of nitrate than in presence of urea or ammonium, suggesting that cytokinin loading into the xylem is affected by different nitrogen forms. We then translated this finding to field scale, cultivated winter wheat in four environments, and confirmed that nitrate fertilization significantly increased tiller number in a dose-dependent manner. As assessed in 22 winter wheat cultivars, nitrogen form-dependent tiller formation was subject to substantial genotypic variation. We conclude that cytokinin-mediated signaling effects of fertilizer nitrogen forms can be employed as a management tool to regulate the tiller number in cereal crops.

Author Correction: Interspecific competition among catch crops modifies vertical root biomass distribution and nitrate scavenging in soils.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Interspecific competition among catch crops modifies vertical root biomass distribution and nitrate scavenging in soils.

The potential of a plant species to acquire nutrients depends on its ability to explore the soil by its root system. Co-cultivation of different species is anticipated to lead to vertical root niche differentiation and thus to higher soil nutrient depletion. Using a qPCR-based method we quantified root biomass distribution of four catch crop species in vertical soil profiles in pure vs. mixed stands. Pure stands of mustard and phacelia robustly reached 70 cm soil depth, while oat preferably colonized upper soil layers, and clover developed the shallowest and smallest root system. Analysis of residual nitrate pools in different soil depths and correlation with root biomass showed that, besides rooting depth also root biomass determines soil nitrogen depletion. While occupying the same vertical niches as in pure stands, mustard and phacelia dominated total root biomass of the mix. In contrast, root biomass of clover and oat was severely suppressed in presence of the other species. Below-ground biomass profiling indicated low niche complementarity among the root systems of the examined species. Nonetheless, the mixture mostly overyielded root biomass of the pure stands and thus shows higher potential for efficient soil exploration by roots.

Computational analysis of receptor tyrosine kinase inhibitors and cancer metabolism: implications for treatment and discovery of potential therapeutic signatures.

BACKGROUND: Receptor tyrosine kinase (RTK) inhibitors are frequently used to treat cancers and the results have been mixed, some of these small molecule drugs are highly successful while others show a more modest response. A high number of studies have been conducted to investigate the signaling mechanisms and corresponding therapeutic influence of RTK inhibitors in order to explore the therapeutic potential of RTK inhibitors. However, most of these studies neglected the potential metabolic impact of RTK inhibitors, which could be highly associated with drug efficacy and adverse effects during treatment. METHODS: In order to fill these knowledge gaps and improve the therapeutic utilization of RTK inhibitors a large-scale computational simulation/analysis over multiple types of cancers with the treatment responses of RTK inhibitors was performed. The pharmacological data of all eight RTK inhibitor and gene expression profiles of 479 cell lines from The Cancer Cell Line Encyclopedia were used. RESULTS: The potential metabolic impact of RTK inhibitors on different types of cancers were analyzed resulting in cancer-specific (breast, liver, pancreas, central nervous system) metabolic signatures. Many of these are in line with results from different independent studies, thereby providing indirect verification of the obtained results. CONCLUSIONS: Our study demonstrates the potential of using a computational approach on signature-based-analysis over multiple cancer types. The results reveal the strength of multiple-cancer analysis over conventional signature-based analysis on a single cancer type.

AutoAnalyze in Systems Biology.

AutoAnalyze is a highly customizable framework for the visualization and analysis of large-scale model graphs. Originally developed for use in the automotive domain, it also supports efficient computation within molecular networks represented by reaction equations. A static analysis approach is used for efficient treatment-condition-specific simulation. The chosen method relies on the computation of a global network data-flow resulting from the evaluation of individual genetic data. The approach facilitates complex analyses of biological components from a molecular network under specific therapeutic perturbations, as demonstrated in a case study. In addition to simulating the complex networks in a stable and reproducible way, kinetic constants can also be fine-tuned using a genetic algorithm and built-in statistical tools.

Automated Classification of Airborne Pollen using Neural Networks.

Pollen allergies are considered as a global epidemic nowadays, as they influence more than a quarter of the worldwide population, with this percentage expected to rapidly increase because of ongoing climate change. To date, alerts on high-risk allergenic pollen exposure have been provided only via forecasting models and conventional monitoring methods that are laborious. The aim of this study is to develop and evaluate our own pollen classification model based on deep neural networks. Airborne allergenic pollen have been monitored in Augsburg, Bavaria, Germany, since 2015, using a novel automatic Bio-Aerosol Analyzer (BAA 500, Hund GmbH). The automatic classification system is compared and evaluated against our own, newly developed algorithm. Our model achieves an unweighted average precision of 83.0 % and an unweighted average recall of 77.1 % across 15 classes of pollen taxa. Automatic, real-time information on concentrations of airborne allergenic pollen will significantly contribute to the implementation of timely, personalized management of allergies in the future. It is already clear that new methods and sophisticated models have to be developed so as to successfully switch to novel operational pollen monitoring techniques serving the above need.

Data Integration for Future Medicine (DIFUTURE).

INTRODUCTION: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. Future medicine will be predictive, preventive, personalized, participatory and digital. Data and knowledge at comprehensive depth and breadth need to be available for research and at the point of care as a basis for targeted diagnosis and therapy. Data integration and data sharing will be essential to achieve these goals. For this purpose, the consortium Data Integration for Future Medicine (DIFUTURE) will establish Data Integration Centers (DICs) at university medical centers. OBJECTIVES: The infrastructure envisioned by DIFUTURE will provide researchers with cross-site access to data and support physicians by innovative views on integrated data as well as by decision support components for personalized treatments. The aim of our use cases is to show that this accelerates innovation, improves health care processes and results in tangible benefits for our patients. To realize our vision, numerous challenges have to be addressed. The objective of this article is to describe our concepts and solutions on the technical and the organizational level with a specific focus on data integration and sharing. GOVERNANCE AND POLICIES: Data sharing implies significant security and privacy challenges. Therefore, state-of-the-art data protection, modern IT security concepts and patient trust play a central role in our approach. We have established governance structures and policies safeguarding data use and sharing by technical and organizational measures providing highest levels of data protection. One of our central policies is that adequate methods of data sharing for each use case and project will be selected based on rigorous risk and threat analyses. Interdisciplinary groups have been installed in order to manage change. ARCHITECTURAL FRAMEWORK AND METHODOLOGY: The DIFUTURE Data Integration Centers will implement a three-step approach to integrating, harmonizing and sharing structured, unstructured and omics data as well as images from clinical and research environments. First, data is imported and technically harmonized using common data and interface standards (including various IHE profiles, DICOM and HL7 FHIR). Second, data is preprocessed, transformed, harmonized and enriched within a staging and working environment. Third, data is imported into common analytics platforms and data models (including i2b2 and tranSMART) and made accessible in a form compliant with the interoperability requirements defined on the national level. Secure data access and sharing will be implemented with innovative combinations of privacy-enhancing technologies (safe data, safe settings, safe outputs) and methods of distributed computing. USE CASES: From the perspective of health care and medical research, our approach is disease-oriented and use-case driven, i.e. following the needs of physicians and researchers and aiming at measurable benefits for our patients. We will work on early diagnosis, tailored therapies and therapy decision tools with focuses on neurology, oncology and further disease entities. Our early uses cases will serve as blueprints for the following ones, verifying that the infrastructure developed by DIFUTURE is able to support a variety of application scenarios. DISCUSSION: Own previous work, the use of internationally successful open source systems and a state-of-the-art software architecture are cornerstones of our approach. In the conceptual phase of the initiative, we have already prototypically implemented and tested the most important components of our architecture.

Computational modeling of methionine cycle-based metabolism and DNA methylation and the implications for anti-cancer drug response prediction.

The relationship between metabolism and methylation is considered to be an important aspect of cancer development and drug efficacy. However, it remains poorly defined how to apply this aspect to improve preclinical disease characterization and clinical treatment outcome. Using available molecular information from Kyoto Encyclopedia of Genes and Genomes (KEGG) and literature, we constructed a large-scale knowledge-based metabolic in silico model. For the purpose of model validation, we applied data from the Cancer Cell Line Encyclopedia (CCLE) to investigate computationally the impact of metabolism on chemotherapy efficacy. In our model, different metabolic components such as MAT2A, ATP6V0E1, NNMT involved in methionine cycle correlate with biologically measured chemotherapy outcome (IC50) that are in agreement with findings of independent studies. These proteins are potentially also involved in cellular methylation processes. In addition, several components such as 3,4-dihydoxymandelate, PAPSS2, UPP1 from metabolic pathways involved in the production of purine and pyrimidine correlate with IC50. This study clearly demonstrates that complex computational approaches can reflect findings of biological experiments. This demonstrates their high potential to grasp complex issues within systems medicine such as response prediction, biomarker identification using available data resources.

Efficacy of peginterferon plus ribavirin in patients receiving opioid substitution therapy : Final results of the Austrian PegHope study.

BACKGROUND: Patients with a history of intravenous drug abuse included in an official opioid substitution program represent an important subgroup of patients with chronic hepatitis C. The objective of this study was to assess the efficacy of and adherence to treatment with peginterferon and ribavirin in Austrian patients on stable opioid substitution therapy (OST). METHODS: This prospective, multicenter, observational, non-interventional trial (clinicaltrials.gov identifier, NCT01416610) included treatment-naïve patients with chronic hepatitis C on OST. Treatment consisted of peginterferon alpha-2a (PEGASYS®, 180 µg/week) plus ribavirin (COPEGUS®, 1000/1200 mg/day in genotypes (GT) 1/4 and 800 mg/day in GT 2/3) for 24-72 weeks, according to GT and viral response. RESULTS: The intention-to-treat (ITT) population comprised 88 patients. Mean duration of therapy was 6.0 ± 2.8 months. Treatment was discontinued earlier than planned in 34 out of 88 patients (39%), mainly because of poor adherence or side effects of treatment. At the end of treatment 65/88 patients (74%) were PCR negative. During follow-up, 5 patients relapsed. Only 44/88 patients (50%) could be evaluated 24 weeks after the end of treatment. Sustained virologic response 24 weeks after end of therapy (SVR24) was documented in 39/88 patients (44%). If only patients were considered who finished treatment as planned and for whom results at follow-up week 24 were available, the SVR24 rate was 89% (32/36). CONCLUSION: Despite favorable prognostic factors, such as young age and a high proportion of GT3, SVR rates were low in this cohort of patients receiving OST, the main reason being poor adherence; however, in those patients completing treatment, the SVR rate was high.

Semantic representation of reported measurements in radiology.

BACKGROUND: In radiology, a vast amount of diverse data is generated, and unstructured reporting is standard. Hence, much useful information is trapped in free-text form, and often lost in translation and transmission. One relevant source of free-text data consists of reports covering the assessment of changes in tumor burden, which are needed for the evaluation of cancer treatment success. Any change of lesion size is a critical factor in follow-up examinations. It is difficult to retrieve specific information from unstructured reports and to compare them over time. Therefore, a prototype was implemented that demonstrates the structured representation of findings, allowing selective review in consecutive examinations and thus more efficient comparison over time. METHODS: We developed a semantic Model for Clinical Information (MCI) based on existing ontologies from the Open Biological and Biomedical Ontologies (OBO) library. MCI is used for the integrated representation of measured image findings and medical knowledge about the normal size of anatomical entities. An integrated view of the radiology findings is realized by a prototype implementation of a ReportViewer. Further, RECIST (Response Evaluation Criteria In Solid Tumors) guidelines are implemented by SPARQL queries on MCI. The evaluation is based on two data sets of German radiology reports: An oncologic data set consisting of 2584 reports on 377 lymphoma patients and a mixed data set consisting of 6007 reports on diverse medical and surgical patients. All measurement findings were automatically classified as abnormal/normal using formalized medical background knowledge, i.e., knowledge that has been encoded into an ontology. A radiologist evaluated 813 classifications as correct or incorrect. All unclassified findings were evaluated as incorrect. RESULTS: The proposed approach allows the automatic classification of findings with an accuracy of 96.4 % for oncologic reports and 92.9 % for mixed reports. The ReportViewer permits efficient comparison of measured findings from consecutive examinations. The implementation of RECIST guidelines with SPARQL enhances the quality of the selection and comparison of target lesions as well as the corresponding treatment response evaluation. CONCLUSIONS: The developed MCI enables an accurate integrated representation of reported measurements and medical knowledge. Thus, measurements can be automatically classified and integrated in different decision processes. The structured representation is suitable for improved integration of clinical findings during decision-making. The proposed ReportViewer provides a longitudinal overview of the measurements.

The influence of inorganic nitrogen fertilizer forms on micronutrient retranslocation and accumulation in grains of winter wheat.

The fortification of cereal grains with metal micronutrients is a major target to combat human malnutrition of Fe and Zn. Based on recent studies showing that N fertilization can promote Fe and Zn accumulation in cereal grains, we investigated here the influence of nitrate- or ammonium-based N fertilization on the accumulation of Fe, Zn, and Cu as well as metal chelator pools in flag leaves and grains of winter wheat. Fertilization with either N form increased the concentrations of N and of the metal chelator nicotianamine (NA) in green leaves, while 2'-deoxymugineic acid (DMA) remained unaffected. Despite the differential response to N fertilization of NA and DMA levels in flag leaves, N fertilization remained without any significant effect on the net export of these metals during flag leaf senescence, which accounted for approximately one third of the total Fe, Zn, or Cu content in leaves. The significant increase in the accumulation of Fe, Zn, and Cu found in the grains of primarily ammonium-fertilized plants was unrelated to the extent of metal retranslocation from flag leaves. These results indicate that an increased N nutritional status of flag leaves promotes the accumulation of Fe, Zn, and Cu in flag leaves, which is accompanied by an increased pool of NA but not of DMA. With regard to the far higher concentrations of DMA relative to NA in leaves and leaf exudates, DMA may be more relevant for the mobilization and retranslocation of these metals in high-yielding wheat production.

Tumor development in murine ulcerative colitis depends on MyD88 signaling of colonic F4/80+CD11b(high)Gr1(low) macrophages.

Patients with prolonged ulcerative colitis (UC) frequently develop colorectal adenocarcinoma for reasons that are not fully clear. To analyze inflammation-associated colonic tumorigenesis, we developed a chronic form of oxazolone-induced colitis in mice that, similar to UC, was distinguished by the presence of IL-13-producing NKT cells. In this model, the induction of tumors using azoxymethane was accompanied by the coappearance of F4/80+CD11b(high)Gr1(low) M2 macrophages, cells that undergo polarization by IL-13 and are absent in tumors that lack high level IL-13 production. Importantly, this subset of macrophages was a source of tumor-promoting factors, including IL-6. Similar to dextran sodium sulfate-induced colitis, F4/80+CD11b(high)Gr1(intermediate) macrophages were present in the mouse model of chronic oxazolone-induced colitis and may influence tumor development through production of TGF-ß1, a cytokine that inhibits tumor immunosurveillance. Finally, while robust chronic oxazolone-induced colitis developed in myeloid differentiation primary response gene 88-deficient (Myd88-/-) mice, these mice did not support tumor development. The inhibition of tumor development in Myd88-/- mice correlated with cessation of IL-6 and TGF-ß1 production by M2 and F4/80+CD11b(high)Gr1(intermediate) macrophages, respectively, and was reversed by exogenous IL-6. These data show that an UC-like inflammation may facilitate tumor development by providing a milieu favoring development of MyD88-dependent tumor-supporting macrophages.

Neuroendoscopic treatment for colloid cysts of the third ventricle: the experience of a decade.

OBJECTIVE: Microsurgical resection or ventriculoperitoneal shunt placement was for a long time the only means of treatment for patients with colloid cysts. In the past few years, however, endoscopic procedures have gained increasing significance and have been used more widely. Long-term results are now available for the first time, which enabled us to evaluate this method and assess its future relevance. METHODS: Twenty patients with symptomatic colloid cysts of the third ventricle have been treated endoscopically in our department during the past 10 years. Retrospective analysis and follow-up of the patients' clinical and radiological outcomes were performed. RESULTS: In the early postoperative period, 18 patients had excellent outcomes, with clinical signs improving immediately. One patient experienced intraoperative hemorrhage followed by temporary postoperative psychosis and IIIrd cranial nerve palsy. Another patient remained shunt-dependent because of aseptic meningitis after the endoscopic procedure. In the long-term follow-up, one patient had to be reoperated to treat cyst recurrence. The operative time was strongly dependent on the cyst material as well as on the surgeon's experience with endoscopic techniques; it varied between 60 and 300 minutes (mean operative time, 200 min). The average hospitalization time was 9 days. Long-term follow-up ranging from 1 to 10 years showed a clear benefit in each patient. In three individuals with pre- and postoperative short-term memory deficits and in one patient who complained of headaches, symptoms resolved gradually during the first few months after surgery. The patient with intraoperative hemorrhage complained of slight permanent short-time memory deficit. The analysis of postoperative computed tomographic and magnetic resonance imaging scans revealed a remaining cyst wall in the majority of patients and an inconsistent decrease in ventricular size. Postoperative cine magnetic resonance imaging studies showed normalization of cerebrospinal fluid flow in 17 patients. CONCLUSION: Continued improvement of endoscopic techniques and instruments, together with good long-term results in endoscopically treated patients, have established this method as an alternative to microsurgical techniques and might even set a new standard for treatment.

Peginterferon alfa-2a and ribavirin for 24 weeks in hepatitis C type 1 and 4 patients with rapid virological response.

BACKGROUND & AIMS: This analysis reports the rate of sustained virological response (SVR) in patients infected with hepatitis C virus (HCV) genotype 1 or 4 who were assigned to 24 weeks of treatment with pegylated interferon (peginterferon) alfa-2a 180 mug/wk plus ribavirin 1000/1200 mg/day after achieving a rapid virological response (RVR; HCV RNA level <50 IU/mL) at week 4 in a prospective trial investigating response-guided therapy. METHODS: Non-RVR patients with an early virological response were randomized to 48 or 72 weeks of therapy (this is a still-ongoing trial). RESULTS: A total of 150 of 516 patients (29%) had an RVR, 143 of whom completed 24 weeks of treatment. Younger patients, leaner patients, and those with an HCV RNA level

Polymorphisms of the interleukin-18 gene in periodontitis patients.

BACKGROUND: Interleukin (IL)-18 regulates the expression of the proinflammatory cytokine interferon (IFN)-gamma. The present study sought to test the putative involvement of six different IL-18 gene polymorphisms in pre-disposition to destructive periodontal disease. METHODS: A total of 123 patients with periodontitis and 121 healthy controls were genotyped for six IL-18 polymorphisms at position -656, -607, -137, +113, +127 and codon 35/3. Genotyping has been performed by PCR and restriction fragment length polymorphism analysis. The frequencies of alleles and genotypes as well of haplotypes within both study groups were compared using the Pearson Chi-square test at a level of significance of 5% (p<0.05). RESULTS: Coseggregation was found to be 100% for the two polymorphisms at position -656 and -607 as well as for the polymorphisms at position -137, +113, and +127. The distribution of genotypes for the IL-18 gene polymorphism at position -656/-607 (p=0.854), at position -137/+113/+127 (p=0.320), and at codon 35/3 (p=0.481) was not significantly different among periodontitis patients if compared with healthy control subjects. The distribution of haplotype combinations for the -607 and -137 polymorphism also showed not significant difference between the both study groups (p=0.545). CONCLUSION: Herein the six different IL-18 gene polymorphisms were not associated with destructive periodontal disease.

Endoscopic third ventriculostomy for obstructive hydrocephalus.

The indications for neuroendoscopy are not only constantly increasing, but even the currently accepted indications are constantly being adjusted and tailored. This is also true for one of the most frequently used neuroendoscopic procedures, the endoscopic 3rd ventriculostomy (ETV) for obstructive hydrocephalus. ETV has gained popularity and widespread acceptance during the past few years, but little attention has been paid to the techniques of the procedure. After a short introduction describing the history of ETV, an overview is given of all the different techniques that have been and still are employed to open the floor of the 3rd ventricle. The spectrum of indications for ETV has been widely enlarged over the last years. Initially, the use of this procedure was restricted to patients older than 2 years, to patients with an obvious triventricular hydrocephalus, and to those with a bulging, translucent floor of the 3rd ventricle. Nowadays, indications include all kinds of obstructive hydrocephalus but also communicating forms of hydrocephalus. The results of endoscopic procedures in treating these pathologies are given under special consideration of shunt technologies. In summary, from the review of the publications since the first ETV performed by Mixter in 1923, this technique is the treatment of choice for obstructive hydrocephalus caused by different etiologies and is an alternative to cerebrospinal fluid shunt application.