The underuse of AI in the health sector: Opportunity costs, success stories, risks and recommendations.

Purpose: This contribution explores the underuse of artificial intelligence (AI) in the health sector, what this means for practice, and how much the underuse can cost. Attention is drawn to the relevance of an issue that the European Parliament has outlined as a "major threat" in 2020. At its heart is the risk that research and development on trusted AI systems for medicine and digital health will pile up in lab centers without generating further practical relevance. Our analysis highlights why researchers, practitioners and especially policymakers, should pay attention to this phenomenon. Methods: The paper examines the ways in which governments and public agencies are addressing the underuse of AI. As governments and international organizations often acknowledge the limitations of their own initiatives, the contribution explores the causes of the current issues and suggests ways to improve initiatives for digital health. Results: Recommendations address the development of standards, models of regulatory governance, assessment of the opportunity costs of underuse of technology, and the urgency of the problem. Conclusions: The exponential pace of AI advances and innovations makes the risks of underuse of AI increasingly threatening.

AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity.

Multimorbidity refers to the coexistence of two or more chronic diseases in one person. Therefore, patients with multimorbidity have multiple and special care needs. However, in practice it is difficult to meet these needs because the organizational processes of current healthcare systems tend to be tailored to a single disease. To improve clinical decision making and patient care in multimorbidity, a radical change in the problem-solving approach to medical research and treatment is needed. In addition to the traditional reductionist approach, we propose interactive research supported by artificial intelligence (AI) and advanced big data analytics. Such research approach, when applied to data routinely collected in healthcare settings, provides an integrated platform for research tasks related to multimorbidity. This may include, for example, prediction, correlation, and classification problems based on multiple interaction factors. However, to realize the idea of this paradigm shift in multimorbidity research, the optimization, standardization, and most importantly, the integration of electronic health data into a common national and international research infrastructure is needed. Ultimately, there is a need for the integration and implementation of efficient AI approaches, particularly deep learning, into clinical routine directly within the workflows of the medical professionals.

Novel Barbiturate-Nitrate Compounds Inhibit the Upregulation of Matrix Metalloproteinase-9 Gene Expression in Intestinal Inflammation through a cGMP-Mediated Pathway.

Matrix metalloproteinase-9 is upregulated in inflammatory bowel disease. Barbiturate nitrate hybrid compounds have been designed to inhibit MMP secretion and enzyme activity. In this study, we investigated the mechanism of action of barbiturate-nitrate hybrid compounds and their component parts using models of intestinal inflammation in vitro. Cytokine-stimulated Caco-2 cells were used in all in vitro experiments. The NO donors SNAP and DETA-NONOate were used to study the effect of NO on MMP-9 mRNA. Mechanistic elucidation was carried out using the soluble guanylate cyclase (sGC) inhibitor, ODQ, and the cGMP analogue, 8-Bromo-cGMP. Further experiments were carried out to elucidate the role of NF-κB. NO donors exerted an inhibitory effect on MMP-9 mRNA in cytokine-stimulated cells. While the non-nitrate barbiturates had a limited effect on MMP-9 expression, the hybrid compounds inhibited MMP-9 expression through its NO-mimetic properties. No effect could be observed on mRNA for MMP-1 or MMP-2. The sGC inhibitior, ODQ, abolished the nitrate-barbiturate inhibition of MMP-9 gene expression, an effect which was reversed by 8-Br-cGMP. This study shows that the barbiturate scaffold is suitable for hybrid design as an MMP-9 inhibitor in cytokine-stimulated Caco-2 cells. The inhibition of MMP-9 levels was largely mediated through a reduction in its mRNA by a sGC/cGMP pathway mediated mechanism.

Influenza management with new therapies.

PURPOSE OF REVIEW: Influenza represents a significant treatment burden to critical care services. A variety of treatment strategies exist, with more and more therapeutic avenues opening up as research progresses. We examined both pharmacological and supportive treatment strategies currently available to see how they might be applied in an ICU setting. RECENT FINDINGS: Supportive care in Influenza centres around optimizing respiratory failure, particularly through well established and recognized ventilatory strategies. Noninvasive ventilation and high-flow nasal oxygen may have a limited role in selected patients under carefully monitored circumstances. Drug therapy exerts only a modest clinical effect and has been poorly studied in the critically ill, though there is some evidence to support the use of neuraminidase inhibitors (NAI) - particularly oseltamivir - as early as possible in this cohort. Newer agents have failed to demonstrate superiority over NAIs but may be useful options if the patient fails to respond or should resistant influenza strains emerge. Steroid therapy, in the absence of another indication, must be recommended against given the repeated trend towards increased mortality in this group. SUMMARY: Influenza management is an evolving field of significant interest to any critical care provider. Currently, good respiratory supportive care and early enteral oseltamivir are the best supported treatment strategies. Further study in the intensive care setting will be needed before the use of novel agents can be recommended.

Operational framework and training standard requirements for AI-empowered robotic surgery.

BACKGROUND: For autonomous robot-delivered surgeries to ever become a feasible option, we recommend the combination of human-centered artificial intelligence (AI) and transparent machine learning (ML), with integrated Gross anatomy models. This can be supplemented with medical imaging data of cadavers for performance evaluation. METHODS: We reviewed technological advances and state-of-the-art documented developments. We undertook a literature search on surgical robotics and skills, tracing agent studies, relevant frameworks, and standards for AI. This embraced transparency aspects of AI. CONCLUSION: We recommend "a procedure/skill template" for teaching AI that can be used by a surgeon. Similar existing methodologies show that when such a metric-based approach is used for training surgeons, cardiologists, and anesthetists, it results in a >40% error reduction in objectively assessed intraoperative procedures. The integration of Explainable AI and ML, and novel tissue characterization sensorics to tele-operated robotic-assisted procedures with medical imaged cadavers, provides robotic guidance and refines tissue classifications at a molecular level.

Artificial intelligence and robotics: a combination that is changing the operating room.

PURPOSE: The aim of the current narrative review was to summarize the available evidence in the literature on artificial intelligence (AI) methods that have been applied during robotic surgery. METHODS: A narrative review of the literature was performed on MEDLINE/Pubmed and Scopus database on the topics of artificial intelligence, autonomous surgery, machine learning, robotic surgery, and surgical navigation, focusing on articles published between January 2015 and June 2019. All available evidences were analyzed and summarized herein after an interactive peer-review process of the panel. LITERATURE REVIEW: The preliminary results of the implementation of AI in clinical setting are encouraging. By providing a readout of the full telemetry and a sophisticated viewing console, robot-assisted surgery can be used to study and refine the application of AI in surgical practice. Machine learning approaches strengthen the feedback regarding surgical skills acquisition, efficiency of the surgical process, surgical guidance and prediction of postoperative outcomes. Tension-sensors on the robotic arms and the integration of augmented reality methods can help enhance the surgical experience and monitor organ movements. CONCLUSIONS: The use of AI in robotic surgery is expected to have a significant impact on future surgical training as well as enhance the surgical experience during a procedure. Both aim to realize precision surgery and thus to increase the quality of the surgical care. Implementation of AI in master-slave robotic surgery may allow for the careful, step-by-step consideration of autonomous robotic surgery.

Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing.

We review some emerging trends in transduction, connectivity and data analytics for Point-of-Care Testing (POCT) of infectious and non-communicable diseases. The patient need for POCT is described along with developments in portable diagnostics, specifically in respect of Lab-on-chip and microfluidic systems. We describe some novel electrochemical and photonic systems and the use of mobile phones in terms of hardware components and device connectivity for POCT. Developments in data analytics that are applicable for POCT are described with an overview of data structures and recent AI/Machine learning trends. The most important methodologies of machine learning, including deep learning methods, are summarised. The potential value of trends within POCT systems for clinical diagnostics within Lower Middle Income Countries (LMICs) and the Least Developed Countries (LDCs) are highlighted.

The role of artificial intelligence and machine learning in harmonization of high-resolution post-mortem MRI (virtopsy) with respect to brain microstructure.

Enhanced resolution of 7 T magnetic resonance imaging (MRI) scanners has considerably advanced our knowledge of structure and function in human and animal brains. Post-industrialized countries are particularly prone to an ever-increasing number of ageing individuals and ageing-associated neurodegenerative diseases. Neurodegenerative diseases are associated with volume loss in the affected brain. MRI diagnoses and monitoring of subtle volume changes in the ageing/diseased brains have the potential to become standard diagnostic tools. Even with the superior resolution of 7 T MRI scanners, the microstructural changes comprising cell types, cell numbers, and cellular processes, are still undetectable. Knowledge of origin, nature, and progression for microstructural changes are necessary to understand pathogenetic stages in the relentless neurodegenerative diseases, as well as to develop therapeutic tools that delay or stop neurodegenerative processes at their earliest stage. We illustrate the gap in resolution by comparing the identical regions of the post-mortem in situ 7 T MR images (virtual autopsy or virtopsy) with the histological observations in serial sections through the same brain. We also described the protocols and limitations associated with these comparisons, as well as the necessity of supercomputers and data management for "Big data". Analysis of neuron and/or glial number by using a body of mathematical tools and guidelines (stereology) is time-consuming, cumbersome, and still restricted to trained human investigators. Development of tools based on machine learning (ML) and artificial intelligence (AI) could considerably accelerate studies on localization, onset, and progression of neuron loss. Finally, these observations could disentangle the mechanisms of volume loss into stages of reversible atrophy and/or irreversible fatal cell death. This AI- and ML-based cooperation between virtopsy and histology could bridge the present gap between virtual reality and neuropathology. It could also culminate in the creation of an imaging-associated comprehensive database. This database would include genetic, clinical, epidemiological, and technical aspects that could help to alleviate or even stop the adverse effects of neurodegenerative diseases on affected individuals, their families, and society.

Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery.

BACKGROUND: This paper aims to move the debate forward regarding the potential for artificial intelligence (AI) and autonomous robotic surgery with a particular focus on ethics, regulation and legal aspects (such as civil law, international law, tort law, liability, medical malpractice, privacy and product/device legislation, among other aspects). METHODS: We conducted an intensive literature search on current or emerging AI and autonomous technologies (eg, vehicles), military and medical technologies (eg, surgical robots), relevant frameworks and standards, cyber security/safety- and legal-systems worldwide. We provide a discussion on unique challenges for robotic surgery faced by proposals made for AI more generally (eg, Explainable AI) and machine learning more specifically (eg, black box), as well as recommendations for developing and improving relevant frameworks or standards. CONCLUSION: We classify responsibility into the following: (1) Accountability; (2) Liability; and (3) Culpability. All three aspects were addressed when discussing responsibility for AI and autonomous surgical robots, be these civil or military patients (however, these aspects may require revision in cases where robots become citizens). The component which produces the least clarity is Culpability, since it is unthinkable in the current state of technology. We envision that in the near future a surgical robot can learn and perform routine operative tasks that can then be supervised by a human surgeon. This represents a surgical parallel to autonomously driven vehicles. Here a human remains in the 'driving seat' as a 'doctor-in-the-loop' thereby safeguarding patients undergoing operations that are supported by surgical machines with autonomous capabilities.

DISC1 regulates N-methyl-D-aspartate receptor dynamics: abnormalities induced by a Disc1 mutation modelling a translocation linked to major mental illness.

The neuromodulatory gene DISC1 is disrupted by a t(1;11) translocation that is highly penetrant for schizophrenia and affective disorders, but how this translocation affects DISC1 function is incompletely understood. N-methyl-D-aspartate receptors (NMDAR) play a central role in synaptic plasticity and cognition, and are implicated in the pathophysiology of schizophrenia through genetic and functional studies. We show that the NMDAR subunit GluN2B complexes with DISC1-associated trafficking factor TRAK1, while DISC1 interacts with the GluN1 subunit and regulates dendritic NMDAR motility in cultured mouse neurons. Moreover, in the first mutant mouse that models DISC1 disruption by the translocation, the pool of NMDAR transport vesicles and surface/synaptic NMDAR expression are increased. Since NMDAR cell surface/synaptic expression is tightly regulated to ensure correct function, these changes in the mutant mouse are likely to affect NMDAR signalling and synaptic plasticity. Consistent with these observations, RNASeq analysis of the translocation carrier-derived human neurons indicates abnormalities of excitatory synapses and vesicle dynamics. RNASeq analysis of the human neurons also identifies many differentially expressed genes previously highlighted as putative schizophrenia and/or depression risk factors through large-scale genome-wide association and copy number variant studies, indicating that the translocation triggers common disease pathways that are shared with unrelated psychiatric patients. Altogether, our findings suggest that translocation-induced disease mechanisms are likely to be relevant to mental illness in general, and that such disease mechanisms include altered NMDAR dynamics and excitatory synapse function. This could contribute to the cognitive disorders displayed by translocation carriers.

Stereoselective Epimerizations of Glycosyl Thiols.

Glycosyl thiols are widely used in stereoselective S-glycoside synthesis. Their epimerization from 1,2-trans to 1,2-cis thiols (e.g., equatorial to axial epimerization in thioglucopyranose) was attained using TiCl4, while SnCl4 promoted their axial-to-equatorial epimerization. The method included application for stereoselective ß-d-manno- and ß-l-rhamnopyranosyl thiol formation. Complex formation explains the equatorial preference when using SnCl4, whereas TiCl4 can shift the equilibrium toward the 1,2-cis thiol via 1,3-oxathiolane formation.

Inhibition of matrix metalloproteinase-9 by a barbiturate-nitrate hybrid ameliorates dextran sulphate sodium-induced colitis: effect on inflammation-related genes.

BACKGROUND AND PURPOSE: Matrix metalloproteinase-9 (MMP-9) is up-regulated in ulcerative colitis and implicated in the pathology of the disease. In this study, we have examined the effects of a barbiturate-based MMP inhibitor incorporating a nitric oxide donor/mimetic group (dinitrate-barbiturate) on the intestinal injury induced by dextran sulphate sodium (DSS). EXPERIMENTAL APPROACH: In vivo experiments were carried out using male Wistar rats given 5% DSS ad libitum in drinking water. The dinitrate-barbiturate, non-nitrate equivalent, nitrate side chains alone or vehicle were administered rectally, twice daily. MMP-9 release was measured by gelatin zymography, and analysis of gene expression was carried out using RT-qPCR. TaqMan low density arrays were used to evaluate the expression of 91 inflammatory genes in the rat colon. KEY RESULTS: The dinitrate-barbiturate inhibited the induction and activity of MMP-9 during DSS colitis in the rat. This occurred in association with significant reductions in the colitic response to DSS as assessed by an established clinical disease activity index and a pathological colitis grade score. The compound modified expression rates of numerous inflammation-related genes in the colon. CONCLUSIONS AND IMPLICATIONS: This study demonstrated the efficacy of the dinitrate-barbiturate in DSS-induced colitis. Therefore, barbiturate-nitrate hybrids may be developed as a promising anti-inflammatory approach to the treatment of inflammatory bowel disease.

NDE1 and GSK3ß Associate with TRAK1 and Regulate Axonal Mitochondrial Motility: Identification of Cyclic AMP as a Novel Modulator of Axonal Mitochondrial Trafficking.

Mitochondria are essential for neuronal function, providing the energy required to power neurotransmission, and fulfilling many important additional roles. In neurons, mitochondria must be efficiently transported to sites, including synapses, where their functions are required. Neurons, with their highly elongated morphology, are consequently extremely sensitive to defective mitochondrial trafficking which can lead to neuronal ill-health/death. We recently demonstrated that DISC1 associates with mitochondrial trafficking complexes where it associates with the core kinesin and dynein adaptor molecule TRAK1. We now show that the DISC1 interactors NDE1 and GSK3ß also associate robustly with TRAK1 and demonstrate that NDE1 promotes retrograde axonal mitochondrial movement. GSK3ß is known to modulate axonal mitochondrial motility, although reports of its actual effect are conflicting. We show that, in our system, GSK3ß promotes anterograde mitochondrial transport. Finally, we investigated the influence of cAMP elevation upon mitochondrial motility, and found a striking increase in mitochondrial motility and retrograde movement. DISC1, NDE1, and GSK3ß are implicated as risk factors for major mental illness. Our demonstration that they function together within mitochondrial trafficking complexes suggests that defective mitochondrial transport may be a contributory disease mechanism in some cases of psychiatric disorder.

Matrix metalloproteinases in inflammatory bowel disease: an update.

Matrix metalloproteinases (MMPs) are known to be upregulated in inflammatory bowel disease (IBD) and other inflammatory conditions, but while their involvement is clear, their role in many settings has yet to be determined. Studies of the involvement of MMPs in IBD since 2006 have revealed an array of immune and stromal cells which release the proteases in response to inflammatory cytokines and growth factors. Through digestion of the extracellular matrix and cleavage of bioactive proteins, a huge diversity of roles have been revealed for the MMPs in IBD, where they have been shown to regulate epithelial barrier function, immune response, angiogenesis, fibrosis, and wound healing. For this reason, MMPs have been recognised as potential biomarkers for disease activity in IBD and inhibition remains a huge area of interest. This review describes new roles of MMPs in the pathophysiology of IBD and suggests future directions for the development of treatment strategies in this condition.

Bi- to tetravalent glycoclusters presenting GlcNAc/GalNAc as inhibitors: from plant agglutinins to human macrophage galactose-type lectin (CD301) and galectins.

Emerging insights into the functional spectrum of tissue lectins leads to identification of new targets for the custom-made design of potent inhibitors, providing a challenge for synthetic chemistry. The affinity and selectivity of a carbohydrate ligand for a lectin may immensely be increased by a number of approaches, which includes varying geometrical or topological features. This perspective leads to the design and synthesis of glycoclusters and their testing using assays of physiological relevance. Herein, hydroquinone, resorcinol, benzene-1,3,5-triol and tetra(4-hydroxyphenyl)ethene have been employed as scaffolds and propargyl derivatives obtained. The triazole-containing linker to the α/ß-O/S-glycosides of GlcNAc/GalNAc presented on these scaffolds was generated by copper-catalysed azide-alkyne cycloaddition. This strategy was used to give a panel of nine glycoclusters with bi-, tri- and tetravalency. Maintained activity for lectin binding after conjugation was ascertained for both sugars in solid-phase assays with the plant agglutinins WGA (GlcNAc) and DBA (GalNAc). Absence of cross-reactivity excluded any carbohydrate-independent reactivity of the bivalent compounds, allowing us to proceed to further testing with a biomedically relevant lectin specific for GalNAc. Macrophage galactose(-binding C)-type lectin, involved in immune defence by dendritic cells and in virus uptake, was produced as a soluble protein without/with its α-helical coiled-coil stalk region. Binding to ligands presented on a matrix and on cell surfaces was highly susceptible to the presence of the tetravalent inhibitor derived from the tetraphenylethene-containing scaffold, and presentation of GalNAc with an α-thioglycosidic linkage proved favorable. Cross-reactivity of this glycocluster to human galectins-3 and -4, which interact with Tn-antigen-presenting mucins, was rather small. Evidently, the valency and spatial display of α-GalNAc residues is a key factor to design potent and selective inhibitors for this lectin.

Mechanisms of platelet-stimulated colon cancer invasion: role of clusterin and thrombospondin 1 in regulation of the P38MAPK-MMP-9 pathway.

Platelets have been implicated in colon cancer metastasis and prognosis but the underlying molecular mechanisms remain unclear. We evaluated the role of the different mitogen-activated protein kinase (MAPK) pathways in platelet-stimulated matrix metalloproteinase-9 (MMP-9) generation and colon cancer invasion. In addition, proteins released during platelet-tumour cell interactions were studied. For this purpose, interactions of Caco-2 and HT29 cells with platelets were studied using scanning electron microscopy, aggregometry, flow cytometry and cell invasion chambers. Quantitative PCR and zymography were used to study MMP-9 gene expression and activity, respectively, whereas western blot was used to study p38MAPK. Finally, the origin of proteins during platelet-cancer cell interactions was investigated using stable isotope labelling by amino acids in cell culture (SILAC)-based proteomics. We found that platelets promoted p38MAPK phosphorylation and MMP-9 up-regulation in both cell lines, with the subsequent cell-invasion-promoting effects. Pharmacological inhibition of p38MAPK led to a significant down-regulation of MMP-9 and colon cancer cell invasiveness. Also, p38MAPK-small interfering RNA abolished the induction of platelet-stimulated MMP-9. SILAC experiments demonstrated that thrombospondin 1 (TSP1) was released mainly from platelets and clusterin by both platelets and cancer cells. Finally, inhibition of TSP1 and clusterin abolished p38MAPK phosphorylation, MMP-9 activity and platelet-stimulated colon cancer invasion. Our results indicate that platelet-secreted TSP1 and clusterin promote the signal regulation of MMP-9 in platelet-induced colonic cancer invasion via a P38MAPK-regulated pathway. These findings are relevant to the development of therapeutic approaches to preventing and reducing tumour cell metastasis induced by colon adenocarcinoma.