The distribution of extracellular matrix in the human uterus

Several lines of evidence suggest that there may be a distinction between the inner and outer myometrium. Magnetic resonance imaging has shown that the uterus of women of reproductive age consists of three layers, in addition, transvaginal ultrasound has revealed that peristaltic waves, during the course of the normal menstrual cycle, emanate only from the inner myometrial muscle. Finally histological findings have suggested that there is a three-fold increase in the nuclear density of the inner compared to the outer myometrium, hi addition, trophoblast invasion is restricted to the inner third of the myometrium. Based on these lines of evidence it was postulated that there could be a difference in extracellular matrix between inner and outer myometrial smooth muscle. To test this hypothesis, the distribution of different laminin chains, collagen IV and elastin were examined in the human uterus, hi addition observations were made to determine whether there was tissue specificity of laminin type expression. Forty-four hysterectomy specimens were collected, from women undergoing hysterectomy for benign conditions, representing all phases of the menstrual cycle. These also included specimens from patients who had been treated with intrauterine levonorgestrel (MirenaRTM). Cryo- and paraffin embedded sections were prepared. Immunocytochemistry was carried out using monoclonal antibodies directed to the alpha2, beta1, beta2, and gamma1 laminin chains, collagen IV, elastin, CD31 and the 68kD neurofilament protein. Digital imaging, by microscopy and scanning, was undertaken and novel image analysis methods were developed to examine the myometrial distribution of extracellular matrix proteins. Elastin detection was confirmed by orcein staining. As predicted collagen IV and the gamma1 laminin chain were present in the basement membranes of the vascular smooth muscle, myometrial smooth muscle, vascular-endothelium and endometrial epithelium. (Abstract shortened by ProQuest.)

The influence of the hormonal milieu on functional prostaglandin and oxytocin receptors and their downstream signal pathways in isolated human myometrium.

Although prostaglandins (PG) and oxytocin are crucial mediators of uterine contractility, their receptor-mediated effects during the menstrual cycle, pregnancy and labour are not fully understood. The aim of this thesis was to elucidate the functional expression of EP, FP, TP and oxytocin receptors in isolated human myometrium relative to myocyte mRNA and signal transduction pathways. Myometrial samples were obtained from consenting non-pregnant and pregnant donors. Functional techniques were used to determine isometric muscle contractions. Primary uterine myocytes and fibroblasts were cultured at term to identify stimulated changes in calcium (Ca2+), cyclic adenosine monophosphate (cAMP) and mRNA. Myometrial strips exhibited spontaneous contractions, which were most active midcycle under oestrogenic conditions. At this time intrinsic contractility and responsiveness to uterotonins decreased towards the fundus. PGE2 produced bellshaped responses with predominant utero-relaxant effects mediated via the EP2 subtype. Although activity was partially restored by PGE2 through EP3/1 receptors, tissue excitation was more pronounced at FP, TP and oxytocin receptors. Despite high FP mRNA expression, the lower segment uterus was particularly responsive to U46619 and oxytocin at term pregnancy. Even so, Ca2+ mobilisation by oxytocin was greater via principal release from intracellular stores. Incubations with atosiban, progesterone and a rho-kinase inhibitor reduced oxytocin-stimulated Ca2+ transients. EP2 also attenuated oxytocic effects but this appeared to be mediated through cAMP rather than Ca2+ signalling pathways. With advancing labour, intrinsic myogenic activity declined in parallel with oxytocin desensitisation. However, TP-induced contractions were continued in the lower parturient uterus. These findings demonstrate that PG and oxytocin receptor expression are regulated in a hormone-dependent temporal and spatial manner. EP2-mediated cAMP formation appears to promote uterine quiescence, whilst TP receptors may control muscle tonus during parturition. These receptors and their messenger systems represent effective tocolytic targets for uterine hypercontractile disorders, such as dysmenorrhoea and preterm labour.Allergan Inc

Diseases of the Abdomen and Pelvis 2018-2021: Diagnostic Imaging - IDKD Book

Gastrointestinal disease; PET/CT; Radiology; X-ray; IDKD; Davo

Optimisation and properties of gamete transport

We consider a series of problems from the field of biological fluid mechanics, in particular the properties and optimisation of human sperm motility, and the fluid flow in the oviduct. As an initial approach, we consider and refine a sinusoidal planar model by introducing a new envelope function with parameters to specify the distal component of the beat pattern and to account for non-constant wavenumber; we investigate the properties of beat pattern configurations such as predicted cell velocity, power consumption and efficiency. The modelling of self-propelled flagellated micro-organisms at low Reynolds number is achieved using the powerful singularity method and slender-body theory. Results using the modified envelope parameter model agree qualitatively with experimental data to show that a balance between velocity, drag and power consumption is a factor in determining a beat pattern configuration. Limitations of the model are discussed including the underlying assumption that the beat pattern is a modified sinusoidal wave which limits the range of permissible patterns. A new method for specifying beat pattern configurations is developed arising from analysis of experimental data using the shear-angle. The resulting two parameter model encompasses a wide range of beat pattern observed in human sperm in vitro. The two parameter model is considered and various modes of efficient beating are illustrated. By considering the bending moment density (which scales with viscosity) we offer an explanation for the viscosity-dependent modulation of human sperm beat. Further extensions and applications of the new model are proposed

Myometrial cyclic AMP function

Background Uncovering the processes that drive labour onset is essential to reduce the adverse consequences of dysfunctional labour. Myometrial cAMP signalling is upregulated during pregnancy promoting uterine quiescence. Changes in its components and effectors have been identified at the onset of term labour. Preterm labour (PTL) treatments targeting this pathway have limited effectiveness and serious maternal effects. In this study, real-time FRET imaging was used to investigate compartmentalised cAMP signals at distinct cellular sites. Methods Myometrial biopsies were obtained from women at term or in distinct causes of PTL. Tissues were processed for mRNA and protein extraction or cell isolation. Primary myometrial cells (HPMCs) and an hTERT-HM cell line expressed either a cytosolic (EPAC-SH187) or plasmalemma (AKAP79-CUTie) genetically encoded FRET sensor. The florescence emission changes were monitored following isoproterenol and PGE2 treatment to determine intracellular cAMP concentrations. Results Differences in cAMP signalling components were detected in PTL compared to term with variations in effector predominance and an associated increase in OTR expression in twin-PTL. Stimulus-specific subcellular compartmentalisation of cAMP was identified in both cell types with differential regulation by phosphodiesterases (PDEs). Significant disparities were detected in the amplitude, kinetics, and regulation of cAMP signals between the two cell types. For the HPMCs, a prolonged time in culture was associated with a reduction in PDE activity and altered cell phenotype. Conclusion The cAMP signalling system is influential in the final pathway of labour, primarily regulating OTR expression. This study established the technique of FRET imaging in human myometrial cells, determining the cell model of choice and culture conditions to explore localised cAMP signalling. The findings provide new insights into the spatial and temporal dynamics of cAMP in the human myometrium and pave the way for unravelling the details of how this fundamental pathway operates and its role in pregnancy and labour.Open Acces

Lycium barbarum (wolfberry) polysaccharide facilitates ejaculatory behaviour in male rats

Poster Session AOBJECTIVE: Lycium barbarum (wolfberry) is a traditional Chinese medicine, which has been considered to have therapeutic effect on male infertility. However, there is a lack of studies support the claims. We thus investigated the effect of Lycium barbarum polysaccharide (LBP), a major component of wolfberry, on male rat copulatory behavior. METHOD: Sprague-Dawley rats were divided into two groups (n=8 for each group). The first group received oral feeding of LBP at dosage of 1mg/kg daily. The control group received vehicle (0.01M phosphate-buffered saline, served as control) feeding daily for 21 days. Copulatory tests were conducted at 7, 14 and 21 days after initiation of treatment. RESULTS: Compared to control animals, animals fed with 1mg/kg LBP showed improved copulatory behavior in terms of: 1. Higher copulatory efficiency (i.e. higher frequency to show intromission rather than mounting during the test), 2. higher ejaculation frequency and 3. Shorter ejaculation latency. The differences were found at all time points (Analyzed with two-tailed student’s t-test, p<0.05). There is no significant difference found between the two groups in terms of mount/intromission latency, which indicates no difference in time required for initiation of sexual activity. Additionally, no difference in mount frequency and intromission frequency was found. CONCLUSION: The present study provides scientific evidence for the traditional use of Lycium barbarum on male sexual behavior. The result provides basis for further study of wolfberry on sexual functioning and its use as an alternative treatment in reproductive medicine.postprintThe 30th Annual Meeting of the Australian Neuroscience Society, in conjunction with the 50th Anniversary Meeting of the Australian Physiological Society (ANS/AuPS 2010), Sydney, Australia, 31 January-3 February 2010. In Abstract Book of ANS/AuPS, 2010, p. 177, abstract no. POS-TUE-19

Anwendungen maschinellen Lernens für datengetriebene Prävention auf Populationsebene

Healthcare costs are systematically rising, and current therapy-focused healthcare systems are not sustainable in the long run. While disease prevention is a viable instrument for reducing costs and suffering, it requires risk modeling to stratify populations, identify high- risk individuals and enable personalized interventions. In current clinical practice, however, systematic risk stratification is limited: on the one hand, for the vast majority of endpoints, no risk models exist. On the other hand, available models focus on predicting a single disease at a time, rendering predictor collection burdensome. At the same time, the den- sity of individual patient data is constantly increasing. Especially complex data modalities, such as -omics measurements or images, may contain systemic information on future health trajectories relevant for multiple endpoints simultaneously. However, to date, this data is inaccessible for risk modeling as no dedicated methods exist to extract clinically relevant information. This study built on recent advances in machine learning to investigate the ap- plicability of four distinct data modalities not yet leveraged for risk modeling in primary prevention. For each data modality, a neural network-based survival model was developed to extract predictive information, scrutinize performance gains over commonly collected covariates, and pinpoint potential clinical utility. Notably, the developed methodology was able to integrate polygenic risk scores for cardiovascular prevention, outperforming existing approaches and identifying benefiting subpopulations. Investigating NMR metabolomics, the developed methodology allowed the prediction of future disease onset for many common diseases at once, indicating potential applicability as a drop-in replacement for commonly collected covariates. Extending the methodology to phenome-wide risk modeling, elec- tronic health records were found to be a general source of predictive information with high systemic relevance for thousands of endpoints. Assessing retinal fundus photographs, the developed methodology identified diseases where retinal information most impacted health trajectories. In summary, the results demonstrate the capability of neural survival models to integrate complex data modalities for multi-disease risk modeling in primary prevention and illustrate the tremendous potential of machine learning models to disrupt medical practice toward data-driven prevention at population scale.Die Kosten im Gesundheitswesen steigen systematisch und derzeitige therapieorientierte Gesundheitssysteme sind nicht nachhaltig. Angesichts vieler verhinderbarer Krankheiten stellt die Prävention ein veritables Instrument zur Verringerung von Kosten und Leiden dar. Risikostratifizierung ist die grundlegende Voraussetzung für ein präventionszentri- ertes Gesundheitswesen um Personen mit hohem Risiko zu identifizieren und Maßnah- men einzuleiten. Heute ist eine systematische Risikostratifizierung jedoch nur begrenzt möglich, da für die meisten Krankheiten keine Risikomodelle existieren und sich verfüg- bare Modelle auf einzelne Krankheiten beschränken. Weil für deren Berechnung jeweils spezielle Sets an Prädiktoren zu erheben sind werden in Praxis oft nur wenige Modelle angewandt. Gleichzeitig versprechen komplexe Datenmodalitäten, wie Bilder oder -omics- Messungen, systemische Informationen über zukünftige Gesundheitsverläufe, mit poten- tieller Relevanz für viele Endpunkte gleichzeitig. Da es an dedizierten Methoden zur Ex- traktion klinisch relevanter Informationen fehlt, sind diese Daten jedoch für die Risikomod- ellierung unzugänglich, und ihr Potenzial blieb bislang unbewertet. Diese Studie nutzt ma- chinelles Lernen, um die Anwendbarkeit von vier Datenmodalitäten in der Primärpräven- tion zu untersuchen: polygene Risikoscores für die kardiovaskuläre Prävention, NMR Meta- bolomicsdaten, elektronische Gesundheitsakten und Netzhautfundusfotos. Pro Datenmodal- ität wurde ein neuronales Risikomodell entwickelt, um relevante Informationen zu extra- hieren, additive Information gegenüber üblicherweise erfassten Kovariaten zu quantifizieren und den potenziellen klinischen Nutzen der Datenmodalität zu ermitteln. Die entwickelte Me-thodik konnte polygene Risikoscores für die kardiovaskuläre Prävention integrieren. Im Falle der NMR-Metabolomik erschloss die entwickelte Methodik wertvolle Informa- tionen über den zukünftigen Ausbruch von Krankheiten. Unter Einsatz einer phänomen- weiten Risikomodellierung erwiesen sich elektronische Gesundheitsakten als Quelle prädik- tiver Information mit hoher systemischer Relevanz. Bei der Analyse von Fundusfotografien der Netzhaut wurden Krankheiten identifiziert für deren Vorhersage Netzhautinformationen genutzt werden könnten. Zusammengefasst zeigten die Ergebnisse das Potential neuronaler Risikomodelle die medizinische Praxis in Richtung einer datengesteuerten, präventionsori- entierten Medizin zu verändern

Recent Advances in Minimally Invasive Surgery

Minimally invasive surgery has become a common term in visceral as well as gynecologic surgery. It has almost evolved into its own surgical speciality over the past 20 years. Today, being firmly established in every subspeciality of visceral surgery, it is now no longer a distinct skillset, but a fixed part of the armamentarium of surgical options available. In every indication, the advantages of a minimally invasive approach include reduced intraoperative blood loss, less postoperative pain, and shorter rehabilitation times, as well as a marked reduction of overall and surgical postoperative morbidity. In the advent of modern oncologic treatment algorithms, these effects not only lower the immediate impact that an operation has on the patient, but also become important key steps in reducing the side-effects of surgery. Thus, they enable surgery to become a module in modern multi-disciplinary cancer treatment, which blends into multimodular treatment options at different times and prolongs and widens the possibilities available to cancer patients. In this quickly changing environment, the requirement to learn and refine not only open surgical but also different minimally invasive techniques on high levels deeply impact modern surgical training pathways. The use of modern elearning tools and new and praxis-based surgical training possibilities have been readily integrated into modern surgical education,which persists throughout the whole surgical career of modern gynecologic and visceral surgery specialists

Deep Learning and Quantum-computing Based Optimization in Medical Imaging and Power Dispatcing

兵庫県立大学大学院202