Innovatienetwerk hyacint zoekt oplossingen voor bolbeschadiging

Beschadigingen aan hyacenten die ontstaan tijdens de oogst en verwerking kunnen de teler veel geld kosten en uiteindelijk ook het imago van de hyacint negatief beïnvloeden. Een innovatienetwerkgroep van vijf telers werkte samen met diverse partijen om ne te gaan wat er aan beschadiging is te doe

The Importance of PRI Therapy for the Pastoral Counsellor

It is not always easy for pastoral counsellors to help people change. Often people have become stuck in their ways. Recent developments in the field of brain research help explain why change is difficult. This article discusses Past Reality Integration Therapy (PRI), a psychotherapeutic method that integrates recent findings of brain research and offers an important addition to the work of (pastoral) counsellors and psychotherapists. The use of this approach with Dutch students in their pastoral training is presented. Furthermore the importance of this new method for counsellors themselves, their clients and their work is discussed and some overall conclusions about the method and its practical application are presented

Verbetering kuubskist : Energie-efficiënt drogen in een half(1/2)-laagssysteem

Op basis van eerdere testen is het ontwerp van een alternatieve kuubskist naar een idee van Peter de Wit (bloembollenbedrijf N.N.J. de Wit/Nord Lommerse) d.m.v. CFD(modellering verbeterd. De 2 dwars op het palletkanaal ongeveer halverwege de kisthoogte geplaatste buizen van hetzelfde geperforeerde materiaal als de kistbodem zijn hierbij 10 cm hoger en 2,5 cm meer naar binnengeplaatst. Om ook tussen de buizen de luchtstroom te verbeteren zijn de perforaties in het bovenste en onderste kwadrant van de buizen gesloten. De resultaten samengevat in 6 punten op een poster ' Alternatieve kuubskist' zijn: Gelijkmatiger luchtverdeling over de kisten, kortere opstartfase van het droogproces, lagere weerstand en daardoor hoger debiet, 30% eerder sneldroog, kans op ziektes kleiner, 17 % op gas en 34% op elektra bespaard

Computer aided characterization of early cancer in Barrett's esophagus on i-scan magnification imaging - Multicenter international study

BACKGROUND AND AIMS: We aimed to develop a computer aided characterization system that can support the diagnosis of dysplasia in Barrett's esophagus (BE) on magnification endoscopy. METHODS: Videos were collected in high-definition magnification white light and virtual chromoendoscopy with i-scan (Pentax Hoya, Japan) imaging in patients with dysplastic/ non-dysplastic BE (NDBE) from 4 centres. We trained a neural network with a Resnet101 architecture to classify frames as dysplastic or non-dysplastic. The network was tested on three different scenarios: high-quality still images, all available video frames and a selected sequence within each video. RESULTS: 57 different patients each with videos of magnification areas of BE (34 dysplasia, 23 NDBE) were included. Performance was evaluated using a leave-one-patient-out cross-validation methodology. 60,174 (39,347 dysplasia, 20,827 NDBE) magnification video frames were used to train the network. The testing set included 49,726 iscan-3/optical enhancement magnification frames. On 350 high-quality still images the network achieved a sensitivity of 94%, specificity of 86% and Area under the ROC (AUROC) of 96%. On all 49,726 available video frames the network achieved a sensitivity of 92%, specificity of 82% and AUROC of 95%. On a selected sequence of frames per case (total of 11,471 frames) we used an exponentially weighted moving average of classifications on consecutive frames to characterize dysplasia. The network achieved a sensitivity of 92%, specificity of 84% and AUROC of 96% The mean assessment speed per frame was 0.0135 seconds (SD, + 0.006) CONCLUSION: Our network can characterize BE dysplasia with high accuracy and speed on high-quality magnification images and sequence of video frames moving it towards real time automated diagnosis

Endoscopic tissue sampling - Part 2 : Lower gastrointestinal tract. European Society of Gastrointestinal Endoscopy (ESGE) Guideline

1: ESGE suggests performing segmental biopsies (at least two from each segment), which should be placed in different specimen containers (ileum, cecum, ascending, transverse, descending, and sigmoid colon, and rectum) in patients with clinical and endoscopic signs of colitis.Weak recommendation, low quality of evidence. 2: ESGE recommends taking two biopsies from the right hemicolon (ascending and transverse colon) and, in a separate container, two biopsies from the left hemicolon (descending and sigmoid colon) when microscopic colitis is suspected.Strong recommendation, low quality of evidence. 3: ESGE recommends pancolonic dye-based chromoendoscopy or virtual chromoendoscopy with targeted biopsies of any visible lesions during surveillance endoscopy in patients with inflammatory bowel disease. Strong recommendation, moderate quality of evidence. 4: ESGE suggests that, in high risk patients with a history of colonic neoplasia, tubular-appearing colon, strictures, ongoing therapy-refractory inflammation, or primary sclerosing cholangitis, chromoendoscopy with targeted biopsies can be combined with four-quadrant non-targeted biopsies every 10 cm along the colon. Weak recommendation, low quality of evidence. 5: ESGE recommends that, if pouch surveillance for dysplasia is performed, visible abnormalities should be biopsied, with at least two biopsies systematically taken from each of the afferent ileal loop, the efferent blind loop, the pouch, and the anorectal cuff.Strong recommendation, low quality of evidence. 6: ESGE recommends that, in patients with known ulcerative colitis and endoscopic signs of inflammation, at least two biopsies be obtained from the worst affected areas for the assessment of activity or the presence of cytomegalovirus; for those with no evident endoscopic signs of inflammation, advanced imaging technologies may be useful in identifying areas for targeted biopsies to assess histologic remission if this would have therapeutic consequences. Strong recommendation, low quality of evidence. 7: ESGE suggests not biopsying endoscopically visible inflammation or normal-appearing mucosa to assess disease activity in known Crohn's disease.Weak recommendation, low quality of evidence. 8: ESGE recommends that adequately assessed colorectal polyps that are judged to be premalignant should be fully excised rather than biopsied.Strong recommendation, low quality of evidence. 9: ESGE recommends that, where endoscopically feasible, potentially malignant colorectal polyps should be excised en bloc rather than being biopsied. If the endoscopist cannot confidently perform en bloc excision at that time, careful representative images (rather than biopsies) should be taken of the potential focus of cancer, and the patient should be rescheduled or referred to an expert center.Strong recommendation, low quality of evidence. 10: ESGE recommends that, in malignant lesions not amenable to endoscopic excision owing to deep invasion, six carefully targeted biopsies should be taken from the potential focus of cancer.Strong recommendation, low quality of evidence

A new artificial intelligence system successfully detects and localises early neoplasia in Barrett's esophagus by using convolutional neural networks

BACKGROUND AND AIMS: Seattle protocol biopsies for Barrett's Esophagus (BE) surveillance are labour intensive with low compliance. Dysplasia detection rates vary, leading to missed lesions. This can potentially be offset with computer aided detection. We have developed convolutional neural networks (CNNs) to identify areas of dysplasia and where to target biopsy. METHODS: 119 Videos were collected in high-definition white light and optical chromoendoscopy with i-scan (Pentax Hoya, Japan) imaging in patients with dysplastic and non-dysplastic BE (NDBE). We trained an indirectly supervised CNN to classify images as dysplastic/non-dysplastic using whole video annotations to minimise selection bias and maximise accuracy. The CNN was trained using 148,936 video frames (31 dysplastic patients, 31 NDBE, two normal esophagus), validated on 25,161 images from 11 patient videos and tested on 264 iscan-1 images from 28 dysplastic and 16 NDBE patients which included expert delineations. To localise targeted biopsies/delineations, a second directly supervised CNN was generated based on expert delineations of 94 dysplastic images from 30 patients. This was tested on 86 i-scan one images from 28 dysplastic patients. FINDINGS: The indirectly supervised CNN achieved a per image sensitivity in the test set of 91%, specificity 79%, area under receiver operator curve of 93% to detect dysplasia. Per-lesion sensitivity was 100%. Mean assessment speed was 48 frames per second (fps). 97% of targeted biopsy predictions matched expert and histological assessment at 56 fps. The artificial intelligence system performed better than six endoscopists. INTERPRETATION: Our CNNs classify and localise dysplastic Barrett's Esophagus potentially supporting endoscopists during surveillance

Development and external validation of a model to predict complex treatment after RFA for Barrett's esophagus with early neoplasia

Background & Aims: Endoscopic eradication therapy for Barrett's esophagus (BE)-related neoplasia is safe and leads to complete eradication in the majority of patients. However, a subgroup will experience a more complex treatment course with a risk for failure or disease progression. Early identification of these patients may improve patient counseling and treatment outcomes. We aimed to develop a prognostic model for a complex treatment course. Methods: We collected data from a nationwide registry that captures outcomes for all patients undergoing endoscopic eradication therapy for early BE neoplasia. A complex treatment course was defined as neoplastic progression, treatment failure, or the need for endoscopic resection during the radiofrequency ablation treatment phase. We developed a prognostic model using logistic regression. We externally validated our model in an independent registry. Results: A total of 1386 patients were included, of whom 78 (6%) had a complex treatment course. Our model identified patients with a BE length of 9 cm or longer with a visible lesion containing high-grade dysplasia/cancer, and patients with less than 50% squamous conversion after radiofrequency ablation were identified as high risk for a complex treatment. This applied to 8% of the study population and included 93% of all treatment failures and 76% of all patients with advanced neoplastic progression. The model appeared robust in multiple sensitivity analyses and performed well in external validation (area under the curve, 0.84). Conclusions: We developed a prognostic model that identified patients with a BE length of 9 cm or longer and high-grade dysplasia/esophageal adenocarcinoma and those with poor squamous regeneration as high risk for a complex treatment course. The good performance in external validation suggests that it may be used in clinical management (Netherlands Trial Register: NL7039)

Природный и антропогенный факторы формирования и развития культурного ландшафта Форосского парка

Цель данной статьи: на примере небольшой территории Южного берега Крыма – парка в пгт. Форос и прилегающей к нему местности – показать роль и место культурного ландшафта в формировании человеком исторического геокультурного пространства

Dysplastic Recurrence After Successful Treatment for Early Barrett's Neoplasia:Development and Validation of a Prediction Model

Background & Aims: The combination of endoscopic resection and radiofrequency ablation is the treatment of choice for eradication of Barrett's esophagus (BE) with dysplasia and/or early cancer. Currently, there are no evidence-based recommendations on how to survey patients after successful treatment, and most patients undergo frequent follow-up endoscopies. We aimed to develop and externally validate a prediction model for visible dysplastic recurrence, which can be used to personalize surveillance after treatment. Methods: We collected data from the Dutch Barrett Expert Center Registry, a nationwide registry that captures outcomes from all patients with BE undergoing endoscopic treatment in the Netherlands in a centralized care setting. We used predictors related to demographics, severity of reflux, histologic status at baseline, and treatment characteristics. We built a Fine and Gray survival model with least absolute shrinkage and selection operator penalization to predict the incidence of visible dysplastic recurrence after initial successful treatment. The model was validated externally in patients with BE treated in Switzerland and Belgium. Results: A total of 1154 patients with complete BE eradication were included for model building. During a mean endoscopic follow-up of 4 years, 38 patients developed recurrent disease (1.0%/person-year). The following characteristics were independently associated with recurrence (strongest to weakest predictor): a new visible lesion during treatment phase, higher number of endoscopic resection treatments, male sex, increasing BE length, high-grade dysplasia or cancer at baseline, and younger age. External validation showed a C-statistic of 0.91 (95% confidence interval, 0.86–0.94) with good calibration. Conclusions: This is the first externally validated model to predict visible dysplastic recurrence after successful endoscopic eradication treatment of BE with dysplasia or early cancer. On external validation, our model has good discrimination and calibration. This model can help clinicians and patients to determine a personalized follow-up strategy