Endoscopic ultrasound for structured surveillance after curative treatment of esophageal cancer.

BACKGROUND: Structured surveillance after treatment of esophageal cancer is not established. Due to a paucity of data, no agreement exists on how surveillance should be performed. The main argument against intensive follow-up in esophageal cancer is that it may not lead to true survival advantage. METHODS: Structured surveillance was performed in 42 patients after multimodal therapy with peri-operative chemotherapy (29) or definitive chemoradiotherapy (13) of esophageal cancer. The surveillance protocol included gastroscopy, endoscopic ultrasound, chest X-ray, abdominal ultrasound, and CEA measurement at regular intervals of up to five years. We analyzed relapse rate, time to relapse, localization of recurrence, diagnosis within or without structured surveillance, diagnostic method providing the first evidence of a relapse, treatment of recurrence, and outcome. RESULTS: Median follow-up was 48 months; 18/42 patients suffered from tumor relapse, with 16 asymptomatic patients diagnosed within structured surveillance. Median time to recurrence was 9 months. Isolated local or locoregional recurrence occurred in 6, and isolated distant relapse in 9 patients. All patients with isolated locoregional recurrence were exclusively diagnosed with endoscopic ultrasound. Six patients received curatively intended therapy with surgery or chemoradiation, leading to long-lasting survival. CONCLUSION: Structured surveillance offers the chance to identify limited and asymptomatic tumor relapse. Especially in cases of locoregional recurrence, long-lasting survival or even a cure can be achieved. Endoscopic ultrasound is the best method for the detection of locoregional tumor recurrence and should be an integral part of structured surveillance after curative treatment of esophageal cancer.

Direct comparison of multiple computer-aided polyp detection systems.

BACKGROUND AND STUDY AIMS: Artificial intelligence (AI)-based systems for computer-aided detection (CADe) of polyps receive regular updates and occasionally offer customizable detection thresholds, both of which impact their performance, but little is known about these effects. This study aimed to compare the performance of different CADe systems on the same benchmark dataset. METHODS: 101 colonoscopy videos were used as benchmark. Each video frame with a visible polyp was manually annotated with bounding boxes, resulting in 129 705 polyp images. The videos were then analyzed by three different CADe systems, representing five conditions: two versions of GI Genius, Endo-AID with detection Types A and B, and EndoMind, a freely available system. Evaluation included an analysis of sensitivity and false-positive rate, among other metrics. RESULTS: Endo-AID detection Type A, the earlier version of GI Genius, and EndoMind detected all 93 polyps. Both the later version of GI Genius and Endo-AID Type B missed 1 polyp. The mean per-frame sensitivities were 50.63 % and 67.85 %, respectively, for the earlier and later versions of GI Genius, 65.60 % and 52.95 %, respectively, for Endo-AID Types A and B, and 60.22 % for EndoMind. CONCLUSIONS: This study compares the performance of different CADe systems, different updates, and different configuration modes. This might help clinicians to select the most appropriate system for their specific needs.

Assisted documentation as a new focus for artificial intelligence in endoscopy: the precedent of reliable withdrawal time and image reporting.

BACKGROUND : Reliable documentation is essential for maintaining quality standards in endoscopy; however, in clinical practice, report quality varies. We developed an artificial intelligence (AI)-based prototype for the measurement of withdrawal and intervention times, and automatic photodocumentation. METHOD: A multiclass deep learning algorithm distinguishing different endoscopic image content was trained with 10 557 images (1300 examinations, nine centers, four processors). Consecutively, the algorithm was used to calculate withdrawal time (AI prediction) and extract relevant images. Validation was performed on 100 colonoscopy videos (five centers). The reported and AI-predicted withdrawal times were compared with video-based measurement; photodocumentation was compared for documented polypectomies. RESULTS: Video-based measurement in 100 colonoscopies revealed a median absolute difference of 2.0 minutes between the measured and reported withdrawal times, compared with 0.4 minutes for AI predictions. The original photodocumentation represented the cecum in 88 examinations compared with 98/100 examinations for the AI-generated documentation. For 39/104 polypectomies, the examiners' photographs included the instrument, compared with 68 for the AI images. Lastly, we demonstrated real-time capability (10 colonoscopies). CONCLUSION : Our AI system calculates withdrawal time, provides an image report, and is real-time ready. After further validation, the system may improve standardized reporting, while decreasing the workload created by routine documentation.

Artificial intelligence-based polyp size measurement in gastrointestinal endoscopy using the auxiliary waterjet as a reference.

BACKGROUND: Measurement of colorectal polyp size during endoscopy is mainly performed visually. In this work, we propose a novel polyp size measurement system (Poseidon) based on artificial intelligence (AI) using the auxiliary waterjet as a measurement reference. METHODS: Visual estimation, biopsy forceps-based estimation, and Poseidon were compared using a computed tomography colonography-based silicone model with 28 polyps of defined sizes. Four experienced gastroenterologists estimated polyp sizes visually and with biopsy forceps. Furthermore, the gastroenterologists recorded images of each polyp with the waterjet in proximity for the application of Poseidon. Additionally, Poseidon's measurements of 29 colorectal polyps during routine clinical practice were compared with visual estimates. RESULTS: In the silicone model, visual estimation had the largest median percentage error of 25.1 % (95 %CI 19.1 %-30.4 %), followed by biopsy forceps-based estimation: median 20.0 % (95 %CI 14.4 %-25.6 %). Poseidon gave a significantly lower median percentage error of 7.4 % (95 %CI 5.0 %-9.4 %) compared with other methods. During routine colonoscopies, Poseidon presented a significantly lower median percentage error (7.7 %, 95 %CI 6.1 %-9.3 %) than visual estimation (22.1 %, 95 %CI 15.1 %-26.9 %). CONCLUSION: In this work, we present a novel AI-based method for measuring colorectal polyp size with significantly higher accuracy than other common sizing methods.

Automated classification of polyps using deep learning architectures and few-shot learning.

BACKGROUND: Colorectal cancer is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is a colonoscopy. However, not all colon polyps have the risk of becoming cancerous. Therefore, polyps are classified using different classification systems. After the classification, further treatment and procedures are based on the classification of the polyp. Nevertheless, classification is not easy. Therefore, we suggest two novel automated classifications system assisting gastroenterologists in classifying polyps based on the NICE and Paris classification. METHODS: We build two classification systems. One is classifying polyps based on their shape (Paris). The other classifies polyps based on their texture and surface patterns (NICE). A two-step process for the Paris classification is introduced: First, detecting and cropping the polyp on the image, and secondly, classifying the polyp based on the cropped area with a transformer network. For the NICE classification, we design a few-shot learning algorithm based on the Deep Metric Learning approach. The algorithm creates an embedding space for polyps, which allows classification from a few examples to account for the data scarcity of NICE annotated images in our database. RESULTS: For the Paris classification, we achieve an accuracy of 89.35 %, surpassing all papers in the literature and establishing a new state-of-the-art and baseline accuracy for other publications on a public data set. For the NICE classification, we achieve a competitive accuracy of 81.13 % and demonstrate thereby the viability of the few-shot learning paradigm in polyp classification in data-scarce environments. Additionally, we show different ablations of the algorithms. Finally, we further elaborate on the explainability of the system by showing heat maps of the neural network explaining neural activations. CONCLUSION: Overall we introduce two polyp classification systems to assist gastroenterologists. We achieve state-of-the-art performance in the Paris classification and demonstrate the viability of the few-shot learning paradigm in the NICE classification, addressing the prevalent data scarcity issues faced in medical machine learning.

Pollutant source or sink? Adsorption and mobilization of PFOS and PFOA from sediments in a large shallow lake with extended reed belt.

In this study, we i) assessed the occurrence of perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) in sediments, pore water, and bulk water from three different areas in Lake Neusiedl, Austria, and ii) investigated mechanisms regulating adsorption and remobilization of these substances under different conditions via multiple lab-scale experiments. The adsorption capacity was mainly influenced by sediments' organic matter content, oxide composition, and pre-loading. Results suggest that a further increase of PFAS-concentrations in the open lake can be partly buffered by sediment transport to the littoral zone and adsorption to sediments in the extended reed belt. But, under current conditions, the conducted experiments revealed a real risk for mobilization of PFOS and PFOA from reed belt sediments that may lead to their transport back into the lake. The amount of desorbed PFAS is primarily dependent on water/sediment- or pore water/water-ratios and the concentration gradient. In contrast, water matrix characteristics and oxygen levels played a minor role in partitioning. The highest risk for remobilizing PFOS and PFOA was observed in experiments with sediments taken near the only major tributary to the lake (river Wulka), which had the highest pre-loading. The following management advice for water transport between high and low polluted areas can be derived based on the results. First, to reduce emissions into Lake waters from polluted tributaries like the Wulka river, we recommend diffuse pathways through the reed belt in the lake's littoral to reduce pollutant transport into the Lake and avoid high local sediment loadings. Second, water exchange with dried-up areas with probable higher loadings should be carefully handled and monitored to avoid critical back transport in the open lake. And third, general work in the reed belt or generally in the reed should be accompanied by monitoring to prevent uncontrolled remobilization in the future.

A video based benchmark data set (ENDOTEST) to evaluate computer-aided polyp detection systems.

BACKGROUND AND AIMS: Computer-aided polyp detection (CADe) may become a standard for polyp detection during colonoscopy. Several systems are already commercially available. We report on a video-based benchmark technique for the first preclinical assessment of such systems before comparative randomized trials are to be undertaken. Additionally, we compare a commercially available CADe system with our newly developed one. METHODS: ENDOTEST consisted in the combination of two datasets. The validation dataset contained 48 video-snippets with 22,856 manually annotated images of which 53.2% contained polyps. The performance dataset contained 10 full-length screening colonoscopies with 230,898 manually annotated images of which 15.8% contained a polyp. Assessment parameters were accuracy for polyp detection and time delay to first polyp detection after polyp appearance (FDT). Two CADe systems were assessed: a commercial CADe system (GI-Genius, Medtronic), and a self-developed new system (ENDOMIND). The latter being a convolutional neuronal network trained on 194,983 manually labeled images extracted from colonoscopy videos recorded in mainly six different gastroenterologic practices. RESULTS: On the ENDOTEST, both CADe systems detected all polyps in at least one image. The per-frame sensitivity and specificity in full colonoscopies was 48.1% and 93.7%, respectively for GI-Genius; and 54% and 92.7%, respectively for ENDOMIND. Median FDT of ENDOMIND with 217 ms (Inter-Quartile Range(IQR)8-1533) was significantly faster than GI-Genius with 1050 ms (IQR 358-2767, p = 0.003). CONCLUSIONS: Our benchmark ENDOTEST may be helpful for preclinical testing of new CADe devices. There seems to be a correlation between a shorter FDT with a higher sensitivity and a lower specificity for polyp detection.

Pilot study of a new freely available computer-aided polyp detection system in clinical practice.

PURPOSE: Computer-aided polyp detection (CADe) systems for colonoscopy are already presented to increase adenoma detection rate (ADR) in randomized clinical trials. Those commercially available closed systems often do not allow for data collection and algorithm optimization, for example regarding the usage of different endoscopy processors. Here, we present the first clinical experiences of a, for research purposes publicly available, CADe system. METHODS: We developed an end-to-end data acquisition and polyp detection system named EndoMind. Examiners of four centers utilizing four different endoscopy processors used EndoMind during their clinical routine. Detected polyps, ADR, time to first detection of a polyp (TFD), and system usability were evaluated (NCT05006092). RESULTS: During 41 colonoscopies, EndoMind detected 29 of 29 adenomas in 66 of 66 polyps resulting in an ADR of 41.5%. Median TFD was 130 ms (95%-CI, 80-200 ms) while maintaining a median false positive rate of 2.2% (95%-CI, 1.7-2.8%). The four participating centers rated the system using the System Usability Scale with a median of 96.3 (95%-CI, 70-100). CONCLUSION: EndoMind's ability to acquire data, detect polyps in real-time, and high usability score indicate substantial practical value for research and clinical practice. Still, clinical benefit, measured by ADR, has to be determined in a prospective randomized controlled trial.

Fast machine learning annotation in the medical domain: a semi-automated video annotation tool for gastroenterologists.

BACKGROUND: Machine learning, especially deep learning, is becoming more and more relevant in research and development in the medical domain. For all the supervised deep learning applications, data is the most critical factor in securing successful implementation and sustaining the progress of the machine learning model. Especially gastroenterological data, which often involves endoscopic videos, are cumbersome to annotate. Domain experts are needed to interpret and annotate the videos. To support those domain experts, we generated a framework. With this framework, instead of annotating every frame in the video sequence, experts are just performing key annotations at the beginning and the end of sequences with pathologies, e.g., visible polyps. Subsequently, non-expert annotators supported by machine learning add the missing annotations for the frames in-between. METHODS: In our framework, an expert reviews the video and annotates a few video frames to verify the object's annotations for the non-expert. In a second step, a non-expert has visual confirmation of the given object and can annotate all following and preceding frames with AI assistance. After the expert has finished, relevant frames will be selected and passed on to an AI model. This information allows the AI model to detect and mark the desired object on all following and preceding frames with an annotation. Therefore, the non-expert can adjust and modify the AI predictions and export the results, which can then be used to train the AI model. RESULTS: Using this framework, we were able to reduce workload of domain experts on average by a factor of 20 on our data. This is primarily due to the structure of the framework, which is designed to minimize the workload of the domain expert. Pairing this framework with a state-of-the-art semi-automated AI model enhances the annotation speed further. Through a prospective study with 10 participants, we show that semi-automated annotation using our tool doubles the annotation speed of non-expert annotators compared to a well-known state-of-the-art annotation tool. CONCLUSION: In summary, we introduce a framework for fast expert annotation for gastroenterologists, which reduces the workload of the domain expert considerably while maintaining a very high annotation quality. The framework incorporates a semi-automated annotation system utilizing trained object detection models. The software and framework are open-source.

Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions.

BACKGROUND: The efficiency of artificial intelligence as computer-aided detection (CADe) systems for colorectal polyps has been demonstrated in several randomized trials. However, CADe systems generate many distracting detections, especially during interventions such as polypectomies. Those distracting CADe detections are often induced by the introduction of snares or biopsy forceps as the systems have not been trained for such situations. In addition, there are a significant number of non-false but not relevant detections, since the polyp has already been previously detected. All these detections have the potential to disturb the examiner's work. OBJECTIVES: Development and evaluation of a convolutional neuronal network that recognizes instruments in the endoscopic image, suppresses distracting CADe detections, and reliably detects endoscopic interventions. METHODS: A total of 580 different examination videos from 9 different centers using 4 different processor types were screened for instruments and represented the training dataset (519,856 images in total, 144,217 contained a visible instrument). The test dataset included 10 full-colonoscopy videos that were analyzed for the recognition of visible instruments and detections by a commercially available CADe system (GI Genius, Medtronic). RESULTS: The test dataset contained 153,623 images, 8.84% of those presented visible instruments (12 interventions, 19 instruments used). The convolutional neuronal network reached an overall accuracy in the detection of visible instruments of 98.59%. Sensitivity and specificity were 98.55% and 98.92%, respectively. A mean of 462.8 frames containing distracting CADe detections per colonoscopy were avoided using the convolutional neuronal network. This accounted for 95.6% of all distracting CADe detections. CONCLUSIONS: Detection of endoscopic instruments in colonoscopy using artificial intelligence technology is reliable and achieves high sensitivity and specificity. Accordingly, the new convolutional neuronal network could be used to reduce distracting CADe detections during endoscopic procedures. Thus, our study demonstrates the great potential of artificial intelligence technology beyond mucosal assessment.

Pooled SARS-CoV-2 antigen tests in asymptomatic children and their caregivers: Screening for SARS-CoV-2 in a pediatric emergency department.

BACKGROUND: Universal admission screening for SARS-CoV-2 in children and their caregivers (CG) is critical to prevent hospital outbreaks. We evaluated pooled SARS-CoV-2 antigen tests (AG) to identify infectious individuals while waiting for polymerase chain reaction (PCR) test results. METHODS: This single-center study was performed from November 5, 2020 to March 1, 2021. Nasal mid-turbinate and oropharyngeal swabbing for AG and PCR testing was performed in children with 2 individual swabs that were simultaneously inserted. Nasopharyngeal swabs were obtained from their CG. AG swabs were pooled in a single extraction buffer tube and PCR swabs in a single viral medium. Results from an adult population were used for comparison, as no pooled testing was performed. RESULTS: During the study period, 710 asymptomatic children and their CG were admitted. Pooled AG sensitivity and specificity was 75% and 99.4% respectively for detection of infectious individuals. Four false negatives were observed, though 3 out of 4 false negative child-CG pairs were not considered infectious at admission. Unpooled AG testing in an adult population showed a comparable sensitivity and specificity of 50% and 99.7%. AG performed significantly better in samples with lower Ct values in the corresponding PCR (32.3 vs 21, P-value < .001). CONCLUSIONS: Pooled SARS-CoV-2 AGs are an effective method to identify potentially contagious individuals prior admission, without adding additional strain to the child.

Predictors of COVID-19 in an outpatient fever clinic.

BACKGROUND: The objective of this study was to identify clinical risk factors for COVID-19 in a German outpatient fever clinic that allow distinction of SARS-CoV-2 infected patients from other patients with flu-like symptoms. METHODS: This is a retrospective, single-centre cohort study. Patients were included visiting the fever clinic from 4th of April 2020 to 15th of May 2020. Symptoms, comorbidities, and socio-demographic factors were recorded in a standardized fashion. Multivariate logistic regression was used to identify risk factors of COVID-19, on the bases of those a model discrimination was assessed using area under the receiver operation curves (AUROC). RESULTS: The final analysis included 930 patients, of which 74 (8%) had COVID-19. Anosmia (OR 10.71; CI 6.07-18.9) and ageusia (OR 9.3; CI 5.36-16.12) were strongly associated with COVID-19. High-risk exposure (OR 12.20; CI 6.80-21.90), especially in the same household (OR 4.14; CI 1.28-13.33), was also correlated; the more household members, especially with flu-like symptoms, the higher the risk of COVID-19. Working in an essential workplace was also associated with COVID-19 (OR 2.35; CI 1.40-3.96), whereas smoking was inversely correlated (OR 0.19; CI 0.08-0.44). A model that considered risk factors like anosmia, ageusia, concomitant of symptomatic household members and smoking well discriminated COVID-19 patients from other patients with flu-like symptoms (AUROC 0.84). CONCLUSIONS: We report a set of four readily available clinical parameters that allow the identification of high-risk individuals of COVID-19. Our study will not replace molecular testing but will help guide containment efforts while waiting for test results.

Interpreting Cytokinin Action as Anterograde Signaling and Beyond.

Among the major phytohormones, the cytokinin exhibits unique features for its ability to positively affect the developmental status of plastids. Even early on in its research, cytokinins were known to promote plastid differentiation and to reduce the loss of chlorophyll in detached leaves. Since the discovery of the components of cytokinin perception and primary signaling, the genes involved in photosynthesis and plastid differentiation have been identified as those directly targeted by type-B response regulators. Furthermore, cytokinins are known to modulate versatile cellular processes such as promoting the division and differentiation of cells and, in concert with auxin, initiating the de novo formation of shoot apical meristem (SAM) in tissue cultures. Yet how cytokinins precisely participate in such diverse cellular phenomena, and how the associated cellular processes are coordinated as a whole, remains unclear. A plausible presumption that would account for the coordinated gene expression is the tight and reciprocal communication between the nucleus and plastid. The fact that cytokinins affect plastid developmental status via gene expression in both the nucleus and plastid is interpreted here to suggest that cytokinin functions as an initiator of anterograde (nucleus-to-plastid) signaling. Based on this viewpoint, we first summarize the physiological relevance of cytokinins to the coordination of plastid differentiation with de novo shoot organogenesis in tissue culture systems. Next, the role of endogenous cytokinins in influencing plastid differentiation within the SAM of intact plants is discussed. Finally, a presumed plastid-derived signal in response to cytokinins for coupled nuclear gene expression is proposed.

Cytokinin Signaling Downstream of the His-Asp Phosphorelay Network: Cytokinin-Regulated Genes and Their Functions.

The plant hormone cytokinin, existing in several molecular forms, is perceived by membrane-localized histidine kinases. The signal is transduced to transcription factors of the type-B response regulator family localized in the nucleus by a multi-step histidine-aspartate phosphorelay network employing histidine phosphotransmitters as shuttle proteins across the nuclear envelope. The type-B response regulators activate a number of primary response genes, some of which trigger in turn further signaling events and the expression of secondary response genes. Most genes activated in both rounds of transcription were identified with high confidence using different transcriptomic toolkits and meta analyses of multiple individual published datasets. In this review, we attempt to summarize the existing knowledge about the primary and secondary cytokinin response genes in order to try connecting gene expression with the multitude of effects that cytokinin exerts within the plant body and throughout the lifespan of a plant.

Burden of disease in Gabon caused by loiasis: a cross-sectional survey.

BACKGROUND: Loiasis is a highly prevalent helminth infection found in distinct regions of sub-Saharan Africa. The disease has been considered to be of minor clinical significance, but this belief is being increasingly challenged by recent evidence. We aimed to prospectively quantify the overall burden of disease caused by loiasis in an endemic region of Gabon, using disability-adjusted life years (DALYs). METHODS: We did a cross-sectional survey during 2017 and 2018 in rural Gabon. Volunteers underwent diagnostic tests for loiasis and were given a standardised questionnaire on symptoms. Participants reporting eye worm migration or harbouring Loa loa microfilariae were defined as loiasis positive. Morbidity-based DALYs associated with loiasis were estimated for the rural population of Gabon. FINDINGS: Between Sept 1, 2017 and May 31, 2018, 1235 participants residing in 38 villages in the Gabonese departments of Tsamba-Magotsi and Ogooué et des Lacs were screened. 626 (50·8%) of 1232 eligible participants had loiasis. 520 (42·2%) of 1232 participants reported eye worm migration. 478 (93·9%) of 509 individuals with eye worm migration also reported associated pain, and 397 (78·6%) of 505 reported vision disturbances. After correcting for age and sex, loiasis was significantly associated with a variety of symptoms, including transient painful oedema (adjusted odds ratio 1·76 [95% CI 1·37-2·26]) and arthralgia (1·30 [1·01-1·69]). Application of attributable fractions of correlating symptoms resulted in 412·9 (95% CI 273·9-567·7) morbidity-based DALYs per 100 000 people in rural Gabon. INTERPRETATION: Loiasis, with the pathognomonic sign of eye worm migration, appears to not be benign, but severely impeding to affected individuals. Furthermore, loiasis is associated with substantial morbidity, comparable to that of other neglected tropical parasitic diseases. These findings call for reconsideration of L loa as a relevant pathogen in affected populations, with a need for more concerted research and control of these infections. FUNDING: Federal Ministry of Science, Research and Economy of Austria, and the European Union.

Predictors for Treatment Failure of Self-Expandable Metal Stents for Anastomotic Leak after Gastro-Esophageal Resection.

BACKGROUND AND AIMS: Self-expandable metal stents are used for the treatment of anastomotic leaks after gastro- esophageal surgery. Predictors for treatment failure and complications are unknown. In this observational retrospective study, we summarize our experience with self-expandable metal stents for the treatment of anastomotic leaks, in order to determine the predictors of treatment failure. METHODS: Between 2009 and 2015, 34 patients with anastomotic leak after curative resection of gastro- esophageal cancer were treated with self-expandable metal stents. Gender, histology, comorbidity, body mass index, neoadjuvant therapy, previous surgery, leak size, and stent diameter were analyzed for their predictive value according to treatment success and complication rate. RESULTS: Leak closure rate was 76%. Risk factors for treatment failure were neoadjuvant chemo-radiotherapy, squamous cell histology, and esophageal tumor location. Gender, comorbidity, body mass index, neoadjuvant chemotherapy, and previous surgery were not correlated with outcome. Mortality rate was 20%, most often due to uncontrolled leak. Severe stent-related complications occurred in 15% of patients, most of them following insertion of a large-sized stent. CONCLUSION: Squamous cell histology, neoadjuvant chemo-radiotherapy, and esophageal tumor location are predictors for treatment failure. Severe stent-related complications seem to be preferentially associated with the use of large-sized stents.

The emergence of small-scale self-affine surface roughness from deformation.

Most natural and man-made surfaces appear to be rough on many length scales. There is presently no unifying theory of the origin of roughness or the self-affine nature of surface topography. One likely contributor to the formation of roughness is deformation, which underlies many processes that shape surfaces such as machining, fracture, and wear. Using molecular dynamics, we simulate the biaxial compression of single-crystal Au, the high-entropy alloy Ni36.67Co30Fe16.67Ti16.67, and amorphous Cu50Zr50 and show that even surfaces of homogeneous materials develop a self-affine structure. By characterizing subsurface deformation, we connect the self-affinity of the surface to the spatial correlation of deformation events occurring within the bulk and present scaling relations for the evolution of roughness with strain. These results open routes toward interpreting and engineering roughness profiles.

Ivermectin for causal malaria prophylaxis: a randomised controlled human infection trial.

OBJECTIVE: Ivermectin is safe and widely used for treating helminth infections. It also kills arthropods feeding on treated subjects, including malaria vectors. Thus, ivermectin mass drug administration as an additional tool for malaria control is being evaluated by WHO. As in vitro data, animal experiments and epidemiological observations suggest that ivermectin has a direct effect on the liver stages of the malaria parasite, this study was designed to assess the prophylactic effect of ivermectin on Plasmodium falciparum controlled human malaria infection. METHODS: A total of 4 volunteers were randomised to placebo, and 8 volunteers were randomised to receive ivermectin 0.4 mg/kg, orally, once 2 h before being experimentally infected intravenously with 3200 P. falciparum sporozoites. The primary endpoint was time to parasitaemia detected by positive thick blood smear; RT-qPCR was performed in parallel. RESULTS: All but one volunteer became thick blood smear positive between day 11 and day 12 after infection, and there was no significant effect of ivermectin on parasitaemia. CONCLUSION: Ivermectin - at the dose used - has no clinically relevant activity against the pre-erythrocytic stages of P. falciparum.

OBJECTIF: L'ivermectine est sûr et largement utilisé pour traiter les helminthiases. Il tue également les arthropodes se nourrissant sur les sujets traités, y compris les vecteurs du paludisme. Ainsi, l'administration en masse d'ivermectine en tant qu'outil supplémentaire de lutte contre le paludisme est actuellement évaluée par l'OMS. Comme les données in vitro, les expériences sur animaux et les observations épidémiologiques suggèrent que l'ivermectine a un effet direct sur les stades hépatiques du parasite du paludisme, cette étude a été conçue pour évaluer l'effet prophylactique de l'ivermectine sur l'infection paludéenne humaine par Plasmodium falciparum contrôlée. MÉTHODES: Quatre volontaires ont été randomisés pour un placebo et 8 volontaires ont été randomisés pour recevoir de l'ivermectine à 0,4 mg/kg en une fois par voie orale, 2 heures avant d'être expérimentalement infectés par voie intraveineuse avec 3.200 sporozoïtes de P. falciparum. Le critère d'évaluation principal était le temps à la parasitémie détectée par un frottis sanguin épais positif. Une RT-qPCR a été réalisée en parallèle. RÉSULTATS: Tous les volontaires sauf un sont devenus positifs pour les frottis sanguins épais entre le jour 11 et le jour 12 après l'infection et il n'y avait aucun effet significatif de l'ivermectine sur la parasitémie. CONCLUSION: L'ivermectine - à la dose utilisée - n'a aucune activité cliniquement pertinente contre les stades pré-érythrocytaires de P. falciparum.

Efficacy of palliative chemotherapy in elderly patients with colorectal cancer.

BACKGROUND: The number of old patients suffering from colorectal cancer rises. In clinical trials, old patients are underrepresented, and chemotherapy is significantly less often performed in elderly patients. We analyzed the impact of elder age for palliative chemotherapy in patients suffering from metastatic colorectal cancer, according to therapeutic drugs used, intensity of treatment performed, and therapeutic results. MATERIALS AND METHODS: We analyzed consecutive patients with metastatic colorectal cancer treated in palliative intention in our department. Assessed data included age ( 75 years), sex, comorbidity, site of primary tumor, k-ras-status, site and amount of metastasis, number and kind of chemotherapeutic agents used, number of consecutive therapy lines performed, dose intensity, toxicity, time between start and end of palliative chemotherapy, and overall survival. Prognostic variables were tested in uni- and multivariate analysis. RESULTS: Ninety-seven patients (69 < 75, 18 > 75 years) were included. Age groups were well balanced according to site of primary tumor, k-ras-mutational status, localization, and number of metastatic sites. Cardial and renal comorbidity was more frequent in elderly patients. The median number of chemotherapeutic drugs used and lines of therapy performed did not differ between age groups, except of oxaliplatin, which was significantly less often used in old patients. Median survival did not differ between age groups (23.4 vs. 23.5 months). In multivariate analysis, only left-sided primary tumor and more than 3 lines of therapy performed were prognostic positive variables. CONCLUSION: Old patients can profit from palliative chemotherapy to the same extent as younger ones.