Evolving robotic surgery training and improving patient safety, with the integration of novel technologies

INTRODUCTION: Robot-assisted surgery is becoming increasingly adopted by multiple surgical specialties. There is evidence of inherent risks of utilising new technologies that are unfamiliar early in the learning curve. The development of standardised and validated training programmes is crucial to deliver safe introduction. In this review, we aim to evaluate the current evidence and opportunities to integrate novel technologies into modern digitalised robotic training curricula. METHODS: A systematic literature review of the current evidence for novel technologies in surgical training was conducted online and relevant publications and information were identified. Evaluation was made on how these technologies could further enable digitalisation of training. RESULTS: Overall, the quality of available studies was found to be low with current available evidence consisting largely of expert opinion, consensus statements and small qualitative studies. The review identified that there are several novel technologies already being utilised in robotic surgery training. There is also a trend towards standardised validated robotic training curricula. Currently, the majority of the validated curricula do not incorporate novel technologies and training is delivered with more traditional methods that includes centralisation of training services with wet laboratories that have access to cadavers and dedicated training robots. CONCLUSIONS: Improvements to training standards and understanding performance data have good potential to significantly lower complications in patients. Digitalisation automates data collection and brings data together for analysis. Machine learning has potential to develop automated performance feedback for trainees. Digitalised training aims to build on the current gold standards and to further improve the 'continuum of training' by integrating PBP training, 3D-printed models, telementoring, telemetry and machine learning

Ethical implications of AI in robotic surgical training: A Delphi consensus statement

CONTEXT: As the role of AI in healthcare continues to expand there is increasing awareness of the potential pitfalls of AI and the need for guidance to avoid them. OBJECTIVES: To provide ethical guidance on developing narrow AI applications for surgical training curricula. We define standardised approaches to developing AI driven applications in surgical training that address current recognised ethical implications of utilising AI on surgical data. We aim to describe an ethical approach based on the current evidence, understanding of AI and available technologies, by seeking consensus from an expert committee. EVIDENCE ACQUISITION: The project was carried out in 3 phases: (1) A steering group was formed to review the literature and summarize current evidence. (2) A larger expert panel convened and discussed the ethical implications of AI application based on the current evidence. A survey was created, with input from panel members. (3) Thirdly, panel-based consensus findings were determined using an online Delphi process to formulate guidance. 30 experts in AI implementation and/or training including clinicians, academics and industry contributed. The Delphi process underwent 3 rounds. Additions to the second and third-round surveys were formulated based on the answers and comments from previous rounds. Consensus opinion was defined as ≥ 80% agreement. EVIDENCE SYNTHESIS: There was 100% response from all 3 rounds. The resulting formulated guidance showed good internal consistency, with a Cronbach alpha of >0.8. There was 100% consensus that there is currently a lack of guidance on the utilisation of AI in the setting of robotic surgical training. Consensus was reached in multiple areas, including: 1. Data protection and privacy; 2. Reproducibility and transparency; 3. Predictive analytics; 4. Inherent biases; 5. Areas of training most likely to benefit from AI. CONCLUSIONS: Using the Delphi methodology, we achieved international consensus among experts to develop and reach content validation for guidance on ethical implications of AI in surgical training. Providing an ethical foundation for launching narrow AI applications in surgical training. This guidance will require further validation. PATIENT SUMMARY: As the role of AI in healthcare continues to expand there is increasing awareness of the potential pitfalls of AI and the need for guidance to avoid them.In this paper we provide guidance on ethical implications of AI in surgical training

Positional Information – a concept underpinning our understanding of developmental biology

© 2019 Wiley Periodicals, Inc.Peer reviewedPostprin

Factors influencing epiphytic bryophyte and lichen species richness at different spatial scales in managed temperate forests

The effect of management related factors on species richness of epiphytic bryophytes and lichens was studied in managed deciduous-coniferous mixed forests in Western-Hungary. At the stand level, the potential explanatory variables were tree species composition, stand structure, microclimate and light conditions, landscape and historical variables; while at tree level host tree species, tree size and light were studied. Species richness of the two epiphyte groups was positively correlated. Both for lichen and bryophyte plot level richness, the composition and diversity of tree species and the abundance of shrub layer were the most influential positive factors. Besides, for bryophytes the presence of large trees, while for lichens amount and heterogeneity of light were important. Tree level richness was mainly determined by host tree species for both groups. For bryophytes oaks, while for lichens oaks and hornbeam turned out the most favourable hosts. Tree size generally increased tree level species richness, except on pine for bryophytes and on hornbeam for lichens. The key variables for epiphytic diversity of the region were directly influenced by recent forest management; historical and landscape variables were not influential. Forest management oriented to the conservation of epiphyte s should focus on: (i) the maintenance of tree species diversity in mixed stands; (ii) increment the proportion of deciduous trees (mainly oaks); (iii) conserving large trees within the stands; (iv) providing the presence of shrub and regeneration layer; (v) creating heterogeneous light conditions. For these purposes tree selection and selective cutting management seem more appropriate than shelterwood system

Statistical Modeling of Single Target Cell Encapsulation

High throughput drop-on-demand systems for separation and encapsulation of individual target cells from heterogeneous mixtures of multiple cell types is an emerging method in biotechnology that has broad applications in tissue engineering and regenerative medicine, genomics, and cryobiology. However, cell encapsulation in droplets is a random process that is hard to control. Statistical models can provide an understanding of the underlying processes and estimation of the relevant parameters, and enable reliable and repeatable control over the encapsulation of cells in droplets during the isolation process with high confidence level. We have modeled and experimentally verified a microdroplet-based cell encapsulation process for various combinations of cell loading and target cell concentrations. Here, we explain theoretically and validate experimentally a model to isolate and pattern single target cells from heterogeneous mixtures without using complex peripheral systems.Wallace H. Coulter Foundation (Young Investigator in Bioengineering Award)National Institutes of Health (U.S.) (Grant R01AI081534)National Institutes of Health (U.S.) (Grant R21AI087107

Ultra-diffuse hydrothermal venting supports Fe-oxidizing bacteria and massive umber deposition at 5000 m off Hawaii

© International Society for Microbial Ecology, 2011. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in The ISME Journal 5 (2011): 1748–1758, doi:10.1038/ismej.2011.48.A novel hydrothermal field has been discovered at the base of Lōihi Seamount, Hawaii, at 5000 mbsl. Geochemical analyses demonstrate that ‘FeMO Deep’, while only 0.2 °C above ambient seawater temperature, derives from a distal, ultra-diffuse hydrothermal source. FeMO Deep is expressed as regional seafloor seepage of gelatinous iron- and silica-rich deposits, pooling between and over basalt pillows, in places over a meter thick. The system is capped by mm to cm thick hydrothermally derived iron-oxyhydroxide- and manganese-oxide-layered crusts. We use molecular analyses (16S rDNA-based) of extant communities combined with fluorescent in situ hybridizations to demonstrate that FeMO Deep deposits contain living iron-oxidizing Zetaproteobacteria related to the recently isolated strain Mariprofundus ferroxydans. Bioenergetic calculations, based on in-situ electrochemical measurements and cell counts, indicate that reactions between iron and oxygen are important in supporting chemosynthesis in the mats, which we infer forms a trophic base of the mat ecosystem. We suggest that the biogenic FeMO Deep hydrothermal deposit represents a modern analog for one class of geological iron deposits known as ‘umbers’ (for example, Troodos ophilolites, Cyprus) because of striking similarities in size, setting and internal structures.Funding has been provided by the NSF Microbial Observatories Program (KJE, DE, BT, HS and CM), by the Gordon and Betty Moore Foundation (KJE), the College of Letters, Arts, and Sciences at the University of Southern California (KJE) and by the NASA Astrobiology Institute (KJE, DE)

Electrotransfer of Single-Stranded or Double-Stranded DNA Induces Complete Regression of Palpable B16.F10 Mouse Melanomas

Enhanced tumor delivery of plasmid DNA with electric pulses in vivo has been confirmed in many preclinical models. Intratumor electrotransfer of plasmids encoding therapeutic molecules has reached Phase II clinical trials. In multiple preclinical studies, a reduction in tumor growth, increased survival or complete tumor regression have been observed in control groups in which vector or backbone plasmid DNA electrotransfer was performed. This study explores factors that could produce this antitumor effect. The specific electrotransfer pulse protocol employed significantly potentiated the regression. Tumor regression was observed after delivery of single-stranded or double-stranded DNA with or without CpG motifs in both immunocompetent and immunodeficient mice, indicating the involvement of the innate immune system in response to DNA. In conclusion, this study demonstrated that the observed antitumor effects are not due to a single factor, but to a combination of factors

c-Myc Regulates Self-Renewal in Bronchoalveolar Stem Cells

BACKGROUND: Bronchoalveolar stem cells (BASCs) located in the bronchoalveolar duct junction are thought to regenerate both bronchiolar and alveolar epithelium during homeostatic turnover and in response to injury. The mechanisms directing self-renewal in BASCs are poorly understood. METHODS: BASCs (Sca-1(+), CD34(+), CD31(-) and, CD45(-)) were isolated from adult mouse lung using FACS, and their capacity for self-renewal and differentiation were demonstrated by immunostaining. A transcription factor network of 53 genes required for pluripotency in embryonic stem cells was assessed in BASCs, Kras-initiated lung tumor tissue, and lung organogenesis by real-time PCR. c-Myc was knocked down in BASCs by infection with c-Myc shRNA lentivirus. Comprehensive miRNA and mRNA profiling for BASCs was performed, and significant miRNAs and mRNAs potentially regulated by c-Myc were identified. We explored a c-Myc regulatory network in BASCs using a number of statistical and computational approaches through two different strategies; 1) c-Myc/Max binding sites within individual gene promoters, and 2) miRNA-regulated target genes. RESULTS: c-Myc expression was upregulated in BASCs and downregulated over the time course of lung organogenesis in vivo. The depletion of c-Myc in BASCs resulted in decreased proliferation and cell death. Multiple mRNAs and miRNAs were dynamically regulated in c-Myc depleted BASCs. Among a total of 250 dynamically regulated genes in c-Myc depleted BASCs, 57 genes were identified as potential targets of miRNAs through miRBase and TargetScan-based computational mapping. A further 88 genes were identified as potential downstream targets through their c-Myc binding motif. CONCLUSION: c-Myc plays a critical role in maintaining the self-renewal capacity of lung bronchoalveolar stem cells through a combination of miRNA and transcription factor regulatory networks