Artificial intelligence and automation in endoscopy and surgery

Modern endoscopy relies on digital technology, from high-resolution imaging sensors and displays to electronics connecting configurable illumination and actuation systems for robotic articulation. In addition to enabling more effective diagnostic and therapeutic interventions, the digitization of the procedural toolset enables video data capture of the internal human anatomy at unprecedented levels. Interventional video data encapsulate functional and structural information about a patient’s anatomy as well as events, activity and action logs about the surgical process. This detailed but difficult-to-interpret record from endoscopic procedures can be linked to preoperative and postoperative records or patient imaging information. Rapid advances in artificial intelligence, especially in supervised deep learning, can utilize data from endoscopic procedures to develop systems for assisting procedures leading to computer-assisted interventions that can enable better navigation during procedures, automation of image interpretation and robotically assisted tool manipulation. In this Perspective, we summarize state-of-the-art artificial intelligence for computer-assisted interventions in gastroenterology and surgery

Winter pruning: Effect on root density, root distribution and root/canopy ratio in vitis vinifera cv. Pinot Gris

As in any other plant, the grapevine roots play a vital role in terms of anchorage, uptake of water and nutrients, as well as storage and production of chemicals. Their behaviour and development depend on various factors, namely rootstock genetics, soil physical and chemical features, and field agronomic practices. Canopy management, involving techniques such as defoliation and pruning, could greatly influence root growth. To date, most of the studies on grapevine winter pruning have focused on the effects on yield and quality of the grapes achievable through different pruning systems and techniques, while knowledge regarding root distribution, development, and growth in relation to winter pruning is still not completely understood. In this context, the purpose of our study was to investigate the effect of winter pruning on the root system of field-grown Vitis vinifera cv. Pinot Gris grafted onto rootstock SO4. We compared two pruning treatments (pruned-P and no pruned-NP) and analysed the effect on root distribution and density, the root index, and the root sugar reserve. Root data were analysed in relation to canopy growth and yield, to elucidate the effect of winter pruning on the root/yield ratio. Our data indicated that: (1) winter pruning stimulated the root growth and distribution; (2) canopy development was not negatively affected by this technique; (3) no pruned treatment produced less growth of the roots but a larger canopy. Information regarding both root growth and root canopy ratio is important as it gives us an understanding of the relationship between the aerial and subterranean parts of the plant, how they compete, and finally, offers us the possibility to ponder on the cultural practices

Initial Responses to False Positives in AI-Supported Continuous Interactions: A Colonoscopy Case Study

The use of artificial intelligence (AI) in clinical support systems is increasing. In this article, we focus on AI support for continuous interaction scenarios. A thorough understanding of end-user behaviour during these continuous human-AI interactions, in which user input is sustained over time and during which AI suggestions can appear at any time, is still missing. We present a controlled lab study involving 21 endoscopists and an AI colonoscopy support system. Using a custom-developed application and an off-the-shelf videogame controller, we record participants’ navigation behaviour and clinical assessment across 14 endoscopic videos. Each video is manually annotated to mimic an AI recommendation, being either true positive or false positive in nature. We find that time between AI recommendation and clinical assessment is significantly longer for incorrect assessments. Further, the type of medical content displayed significantly affects decision time. Finally, we discover that the participant’s clinical role plays a large part in the perception of clinical AI support systems. Our study presents a realistic assessment of the effects of imperfect and continuous AI support in a clinical scenario

MESSAGEix workshop

The aim of the workshop is to help new users of the MESSAGEix modelling framework to get started with their modeling work. The main features of the “framework” are introduced, and the use cases of some features are shown. The user can learn how to build an energy model and how to represent some policy constraints in their energy scenarios. For information about the model, its structure, mathematical formulation and much more, please see the documentation at: https://docs.messageix.org. The different lectures contain the workshop slides, videos as well as tutorials for hands-on examples

Polyp detection on video colonoscopy using a hybrid 2D/3D CNN

Colonoscopy is the gold standard for early diagnosis and pre-emptive treatment of colorectal cancer by detecting and removing colonic polyps. Deep learning approaches to polyp detection have shown potential for enhancing polyp detection rates. However, the majority of these systems are developed and evaluated on static images from colonoscopies, whilst in clinical practice the treatment is performed on a real-time video feed. Non-curated video data remains a challenge, as it contains low-quality frames when compared to still, selected images often obtained from diagnostic records. Nevertheless, it also embeds temporal information that can be exploited to increase predictions stability. A hybrid 2D/3D convolutional neural network architecture for polyp segmentation is presented in this paper. The network is used to improve polyp detection by encompassing spatial and temporal correlation of the predictions while preserving real-time detections. Extensive experiments show that the hybrid method outperforms a 2D baseline. The proposed architecture is validated on videos from 46 patients and on the publicly available SUN polyp database. A higher performance and increased generalisability indicate that real-world clinical implementations of automated polyp detection can benefit from the hybrid algorithm and the inclusion of temporal information

Spatio-temporal classification for polyp diagnosis

Colonoscopy remains the gold standard investigation for colorectal cancer screening as it offers the opportunity to both detect and resect pre-cancerous polyps. Computer-aided polyp characterisation can determine which polyps need polypectomy and recent deep learning-based approaches have shown promising results as clinical decision support tools. Yet polyp appearance during a procedure can vary, making automatic predictions unstable. In this paper, we investigate the use of spatio-temporal information to improve the performance of lesions classification as adenoma or non-adenoma. Two methods are implemented showing an increase in performance and robustness during extensive experiments both on internal and openly available benchmark datasets

Exendin-4 stimulates autophagy in pancreatic β-cells via the RAPGEF/EPAC-Ca PPP3/calcineurin-TFEB axis

Macroautophagy/autophagy is critical for the regulation of pancreatic β-cell mass and its deregulation has been implicated in the pathogenesis of type 2 diabetes (T2D). We have previously shown that treatment of pancreatic β-cells with the GLP1R (glucagon like peptide 1 receptor) agonist exendin-4 stimulates autophagic flux in a setting of chronic nutrient excess. The aim of this study was to identify the underlying pathways contributing to enhanced autophagic flux.Pancreatic β-cells (INS-1E),mouse and human islets were treated with glucolipotoxic stress (0.5 mM palmitate and 25 mM glucose) in the presence of exendin-4. Consistent with our previous work, exendin-4 stimulated autophagic flux. Using chemical inhibitors and siRNA knockdown, we identified RAPGEF4/EPAC2 (Rap guanine nucleotide exchange factor 4) and downstream calcium signaling to be essential for regulation of autophagic flux by exendin-4. This pathway was independent of AMPK and MTOR signaling. Further analysis identified PPP3/calcineurin and its downstream regulator TFEB (transcription factor EB) as key proteins mediating exendin-4 induced autophagy. Importantly, inhibition of this pathway prevented exendin-4-mediated cell survival and overexpression of TFEB mimicked the cell protective effects of exendin-4 in INS-1E and human islets. Moreover, treatment of db/db mice with exendin-4 for 21 days increased the expression of lysosomal markers within the pancreatic islets. Collectively our data identify the RAPGEF4/EPAC2-calcium-PPP3/calcineurin-TFEB axis as a key mediator of autophagic flux, lysosomal function and cell survival in pancreatic β-cells. Pharmacological modulation of this axis may offer a novel therapeutic target for the treatment of T2D.Abbreviations: AKT1/protein kinase B: AKT serine/threonine kinase 1; AMPK: 5' AMP-activated protein kinase; CAMKK: calcium/calmodulin-dependent protein kinase kinase; cAMP: cyclic adenosine monophosphate; CASP3: caspase 3; CREB: cAMP response element-binding protein; CTSD: cathepsin D; Ex4: exendin-4(1-39); GLP-1: glucagon like peptide 1; GLP1R: glucagon like peptide 1 receptor; GLT: glucolipotoxicity; INS: insulin; MTOR: mechanistic target of rapamycin kinase; NFAT: nuclear factor of activated T-cells; PPP3/calcineurin: protein phosphatase 3; PRKA/PKA: protein kinase cAMP activated; RAPGEF3/EPAC1: Rap guanine nucleotide exchange factor 3; RAPGEF4/EPAC2: Rap guanine nucleotide exchange factor 4; SQSTM1/p62: sequestosome 1; T2D: type 2 diabetes; TFEB: transcription factor EB

Targeting homeostatic mechanisms of endoplasmic reticulum stress to increase susceptibility of cancer cells to fenretinide-induced apoptosis: the role of stress proteins ERdj5 and ERp57

Endoplasmic reticulum (ER) malfunction, leading to ER stress, can be a consequence of genome instability and hypoxic tissue environments. Cancer cells survive by acquiring or enhancing survival mechanisms to counter the effects of ER stress and these homeostatic responses may be new therapeutic targets. Understanding the links between ER stress and apoptosis may be approached using drugs specifically to target ER stress responses in cancer cells. The retinoid analogue fenretinide [N-(4-hydroxyphenyl) retinamide] is a new cancer preventive and chemotherapeutic drug, that induces apoptosis of some cancer cell types via oxidative stress, accompanied by induction of an ER stress-related transcription factor, GADD153. The aim of this study was to test the hypothesis that fenretinide induces ER stress in neuroectodermal tumour cells, and to elucidate the role of ER stress responses in fenretinide-induced apoptosis. The ER stress genes ERdj5, ERp57, GRP78, calreticulin and calnexin were induced in neuroectodermal tumour cells by fenretinide. In contrast to the apoptosis-inducing chemotherapeutic drugs vincristine and temozolomide, fenretinide induced the phosphorylation of eIF2α, expression of ATF4 and splicing of XBP-1 mRNA, events that define ER stress. In these respects, fenretinide displayed properties similar to the ER stress inducer thapsigargin. ER stress responses were inhibited by antioxidant treatment. Knockdown of ERp57 or ERdj5 by RNA interference in these cells increased the apoptotic response to fenretinide. These data suggest that downregulating homeostatic ER stress responses may enhance apoptosis induced by oxidative stress-inducing drugs acting through the ER stress pathway. Therefore, ER-resident proteins such as ERdj5 and ERp57 may represent novel chemotherapeutic targets

Urea-Doped Calcium Phosphate Nanoparticles as Sustainable Nitrogen Nanofertilizers for Viticulture: Implications on Yield and Quality of Pinot Gris Grapevines

In recent years, the application of nanotechnology for the development of new “smart fertilizers” is regarded as one of the most promising solutions for boosting a more sustainable and modern grapevine cultivation. Despite showing interesting potential benefits over conventional fertilization practices, the use of nanofertilizers in viticulture is still underexplored. In this work, we investigated the effectiveness of non-toxic calcium phosphate nanoparticles (Ca3(PO4)2∙nH2O) doped with urea (U-ACP) as a nitrogen source for grapevine fertilization. Plant tests were performed for two years (2019–2020) on potted adult Pinot gris cv. vines grown under semi-controlled conditions. Four fertilization treatments were compared: N1: commercial granular fertilization (45 kg N ha−1); N2: U-ACP applied in fertigation (36 kg N ha−1); N3: foliar application of U-ACP (36 kg N ha−1); C: control, receiving no N fertilization. Plant nitrogen status (SPAD), yield parameters as well as those of berry quality were analyzed. Results here presented clearly show the capability of vine plants to recognize and use the nitrogen supplied with U-ACP nanoparticles either when applied foliarly or to the soil. Moreover, all of the quali–quantitative parameters measured in vine plants fed with nanoparticles were perfectly comparable to those of plants grown in conventional condition, despite the restrained dosage of nitrogen applied with the nanoparticles. Therefore, these results provide both clear evidence of the efficacy of U-ACP nanoparticles as a nitrogen source and the basis for the development of alternative nitrogen fertilization strategies, optimizing the dosage/benefit ratio and being particularly interesting in a context of a more sustainable and modern viticulture.PSR 2014/2020 Regione Autonoma Friuli Venezia Giulia—Misure 16.1.1, DGR 1313/2018, DC 398/AGFOR 2020—GESOVIT PROJECTFondazione Cariplo, Italy, Grant n. 2016-0648, project: Romancing the stone: size controlled HYdroxyaPATItes for sustainable Agriculture (HYPATIA