Hamilton-Jacobi Counterterms for Einstein-Gauss-Bonnet Gravity

The on-shell gravitational action and the boundary stress tensor are essential ingredients in the study of black hole thermodynamics. We employ the Hamilton-Jacobi method to calculate the boundary counterterms necessary to remove the divergences and allow the study of the thermodynamics of Einstein-Gauss-Bonnet black holes.Comment: 21 pages, LaTe

IntAct:intra-operative fluorescence angiography to prevent anastomotic leak in rectal cancer surgery: a randomized controlled trial

Aim Anastomotic leak (AL) is a major complication of rectal cancer surgery. Despite advances in surgical practice, the rates of AL have remained static, at around 10–15%. The aetiology of AL is multifactorial, but one of the most crucial risk factors, which is mostly under the control of the surgeon, is blood supply to the anastomosis. The MRC/NIHR IntAct study will determine whether assessment of anastomotic perfusion using a fluorescent dye (indocyanine green) and near‐infrared laparoscopy can minimize the rate of AL leak compared with conventional white‐light laparoscopy. Two mechanistic sub‐studies will explore the role of the rectal microbiome in AL and the predictive value of CT angiography/perfusion studies. Method IntAct is a prospective, unblinded, parallel‐group, multicentre, European, randomized controlled trial comparing surgery with intra‐operative fluorescence angiography (IFA) against standard care (surgery with no IFA). The primary end‐point is rate of clinical AL at 90 days following surgery. Secondary end‐points include all AL (clinical and radiological), change in planned anastomosis, complications and re‐interventions, use of stoma, cost‐effectiveness of the intervention and quality of life. Patients should have a diagnosis of adenocarcinoma of the rectum suitable for potentially curative surgery by anterior resection. Over 3 years, 880 patients from 25 European centres will be recruited and followed up for 90 days. Discussion IntAct will rigorously evaluate the use of IFA in rectal cancer surgery and explore the role of the microbiome in AL and the predictive value of preoperative CT angiography/perfusion scanning

Selecting the most suitable classification algorithm for supporting assistive technology adoption for people with dementia: A multicriteria framework

The number of people with dementia (PwD) is increasing dramatically. PwD exhibit impairments of reasoning, memory, and thought that require some form of self‐management intervention to support the completion of everyday activities while maintaining a level of independence. To address this need, efforts have been directed to the development of assistive technology solutions, which may provide an opportunity to alleviate the burden faced by the PwD and their carers. Nevertheless, uptake of such solutions has been limited. It is therefore necessary to use classifiers to discriminate between adopters and nonadopters of these technologies in order to avoid cost overruns and potential negative effects on quality of life. As multiple classification algorithms have been developed, choosing the most suitable classifier has become a critical step in technology adoption. To select the most appropriate classifier, a set of criteria from various domains need to be taken into account by decision makers. In addition, it is crucial to define the most appropriate multicriteria decision‐making approach for the modelling of technology adoption. Considering the above‐mentioned aspects, this paper presents the integration of a five‐phase methodology based on the Fuzzy Analytic Hierarchy Process and the Technique for Order of Preference by Similarity to Ideal Solution to determine the most suitable classifier for supporting assistive technology adoption studies. Fuzzy Analytic Hierarchy Process is used to determine the relative weights of criteria and subcriteria under uncertainty and Technique for Order of Preference by Similarity to Ideal Solution is applied to rank the classifier alternatives. A case study considering a mobile‐based self‐management and reminding solution for PwD is described to validate the proposed approach. The results revealed that the best classifier was k‐nearest‐neighbour with a closeness coefficient of 0.804, and the most important criterion when selecting classifiers is scalability. The paper also discusses the strengths and weaknesses of each algorithm that should be addressed in future research

Generalizing Galileons

The Galileons are a set of terms within four-dimensional effective field theories, obeying symmetries that can be derived from the dynamics of a 3+1-dimensional flat brane embedded in a 5-dimensional Minkowski Bulk. These theories have some intriguing properties, including freedom from ghosts and a non-renormalization theorem that hints at possible applications in both particle physics and cosmology. In this brief review article, we will summarize our attempts over the last year to extend the Galileon idea in two important ways. We will discuss the effective field theory construction arising from co-dimension greater than one flat branes embedded in a flat background - the multiGalileons - and we will then describe symmetric covariant versions of the Galileons, more suitable for general cosmological applications. While all these Galileons can be thought of as interesting four-dimensional field theories in their own rights, the work described here may also make it easier to embed them into string theory, with its multiple extra dimensions and more general gravitational backgrounds.Comment: 16 pages; invited brief review article for a special issue of Classical and Quantum Gravity. Submitted to CQ

Patient-specific mental rehearsal with three-dimensional models before low anterior resection: randomized clinical trial

Background It was hypothesized that preparing for a surgical procedure, taking into account individual patient characteristics, may facilitate the procedure and improve surgical quality. The aim of this study was to compare different case-specific, preoperative mental rehearsal methods before minimally invasive rectal cancer surgery. Methods In this RCT, patients were allocated in a 1 : 1 : 1 : 1 ratio to four groups: systematic mental rehearsal (SMR) using MRI scans; SMR and three-dimensional (3D) virtual models; SMR and synthetic 3D printed models; and routine practice (control group). Surgeons operating on all but the control group underwent mental rehearsal with the visual aids, including axial MRI scans of the pelvis, interactive 3D virtual models reconstructed from axial MRIs, and synthetic models, manufactured by 3D printing. Operations were video-recorded and assessed by two experts blinded to allocation using two validated scores, the Competency Assessment Tool (CAT) and Objective Clinical Human Reliability Analysis (OCHRA). The primary outcome of the study was surgical performance, measured by the CAT. Results Forty-nine patients were randomized and allocated to the four groups. There were 12 participants in each of the control, MRI and SMR, and virtual and SMR groups, whereas the SMR using physical models and simulation group included 13. No difference was observed between groups in median CAT scores (control 30.50, MRI 34.25, virtual 31.75, physical 34.00; P = 0.748, partial η2 0.200, pη2 =0.052–0.088). Time spent not performing dissection was significantly shorter for the SMR with MRI group than for the control (57.5 versus 42 respectively; P < 0.001, pη2 =0.212). Conclusion Mental rehearsal did not affect CAT and OCHRA scores of consultant surgeons. Reference number: ISRCTN 75603704 (https://www.isrctn.com)

Modification of conservative treatment of heterotopic cervical pregnancy by Foley catheter balloon fixation with cerclage sutures at the level of the external cervical os: a case report

<p>Abstract</p> <p>Introduction</p> <p>Conservative treatment of a heterotopic cervical pregnancy was performed with a modification of the fixation of a Foley catheter at the level of the external cervical os, followed by the ligature of the descending cervical branches of the uterine arteries and systemic methotrexate application.</p> <p>Case presentation</p> <p>A 34-year-old Caucasian woman was diagnosed with double gestation after 6 weeks of <it>in vitro </it>fertilization treatment. A gynecological examination and color Doppler ultrasound scan revealed intra-uterine and cervical gestational sacs both containing live fetuses. A Foley catheter balloon was inserted into the cervical canal, inflated and fixed by a cerclage suture at the level of the external cervical os, followed by ligation of the descending cervical branches of the uterine arteries. Systemic methotrexate was applied. Three days after removal of the Foley catheter, an evacuation of the intra-uterine gestational sac was performed. Hemorrhage from the implantation site was controlled immediately and a pregnancy termination was successfully performed. The procedure was uneventful and our patient was discharged with a preserved uterus.</p> <p>Conclusions</p> <p>Conservative treatment of cervical pregnancy using a Foley catheter balloon is more efficacious if the Foley catheter balloon is attached in the correct position with a cerclage suture at the level of the external os, followed by ligation of the descending cervical branches of the uterine arteries, thereby exerting maximal pressure on the bleeding vessels.</p

Underwater robotics ready for oil spill, an EU project

Peer Reviewe

Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review

Background: The widespread use of immune checkpoint inhibitors (ICIs) has revolutionised treatment of multiple cancer types. However, selecting patients who may benefit from ICI remains challenging. Artificial intelligence (AI) approaches allow exploitation of high-dimension oncological data in research and development of precision immuno-oncology. Materials and methods: We conducted a systematic literature review of peer-reviewed original articles studying the ICI efficacy prediction in cancer patients across five data modalities: genomics (including genomics, transcriptomics, and epigenomics), radiomics, digital pathology (pathomics), and real-world and multimodality data. Results: A total of 90 studies were included in this systematic review, with 80% published in 2021-2022. Among them, 37 studies included genomic, 20 radiomic, 8 pathomic, 20 real-world, and 5 multimodal data. Standard machine learning (ML) methods were used in 72% of studies, deep learning (DL) methods in 22%, and both in 6%. The most frequently studied cancer type was non-small-cell lung cancer (36%), followed by melanoma (16%), while 25% included pan-cancer studies. No prospective study design incorporated AI-based methodologies from the outset; rather, all implemented AI as a post hoc analysis. Novel biomarkers for ICI in radiomics and pathomics were identified using AI approaches, and molecular biomarkers have expanded past genomics into transcriptomics and epigenomics. Finally, complex algorithms and new types of AI-based markers, such as meta-biomarkers, are emerging by integrating multimodal/multi-omics data. Conclusion: AI-based methods have expanded the horizon for biomarker discovery, demonstrating the power of integrating multimodal data from existing datasets to discover new meta-biomarkers. While most of the included studies showed promise for AI-based prediction of benefit from immunotherapy, none provided high-level evidence for immediate practice change. A priori planned prospective trial designs are needed to cover all lifecycle steps of these software biomarkers, from development and validation to integration into clinical practice