Investigation of the Formaldehyde-Catalyzed NNitrosation of Dialkyl Amines: An Automated Experimental and Kinetic Modelling Study Using Dibutylamine

The potential for drug substances and drug products to contain low levels of N-nitrosamines is of continued interest to the pharmaceutical industry and regulatory authorities. Acid-promoted nitrosation mechanisms in solution have been investigated widely in the literature and are supported by kinetic modelling studies. Carbonyl compounds, particularly formaldehyde, which may be present as impurities in excipients and drug product packaging components or introduced during drug substance manufacturing processes are also known to catalyze nitrosation, but their impact on the risk of N-nitrosamine formation has not been systematically investigated to date. In this study, we experimentally investigated the multivariate impact of formaldehyde, nitrite and pH on N-nitrosation in aqueous solution using dibutylamine as a model amine. We augmented a published kinetic model by adding formaldehyde-catalyzed nitrosation reactions. We validated the new kinetic model vs. the experimental data and then used the model to systematically investigate the impact of formaldehyde levels on N-nitrosamine formation. Simulations of aqueous solution systems show that at low formaldehyde levels the formaldehyde-catalyzed mechanisms are insignificant in comparison to other routes. However, formaldehyde-catalyzed mechanisms can become more significant at neutral and high pH under higher formaldehyde levels. Model-based sensitivity analysis demonstrated that under high nitrite levels and low formaldehyde levels (where the rate of formaldehyde-catalyzed nitrosation is low compared to the acid-promoted pathways) the model can be used with kinetic parameters for model amines in the literature without performing additional experiments to fit amine-specific parameters. For other combinations of reaction parameters containing formaldehyde, the formaldehyde-catalyzed kinetics are non-negligible, and thus it is advised that, under such conditions, additional experiments should be conducted to reliably use the model.

Automated vehicles for older adults with cognitive impairment: a survey study

As the population is ageing, the number of older adults with cognitive impairment (CI) is increasing. Automated vehicles (AVs) can improve independence and enhance the mobility of these individuals. This study aimed to: (1) understand the perception of older adults (with and without CI) and stakeholders providing services and supports regarding care and transportation about AVs, and (2) suggest potential solutions to improve the perception of AVs for older adults with mild or moderate CI. A survey was conducted with 435 older adults with and without CI and 188 stakeholders (e.g. caregivers). The results were analysed using partial least square - structural equation modelling and multiple correspondence analysis. The findings suggested relationships between older adults' level of cognitive impairment, mobility, knowledge of AVs, and perception of AVs. The results provided recommendations to improve older adults' perception of AVs including education and adaptive driving simulation-based training.Practitioner summary: This study investigated the perception of older adults and other stakeholders regarding AVs. The findings suggested relationships between older adults' level of cognitive impairment, mobility, knowledge of AVs, and perception of AVs. The results provided guidelines to improve older adults' perception of AVs.

Novel dosimetric validation of a commercial CT scanner based deep learning automated contour solution for prostate radiotherapy

PURPOSE

OAR delineation accuracy influences: (i) a patient's optimised dose distribution (PD), (ii) the reported doses (RD) presented at approval, which represent plan quality. This study utilised a novel dosimetric validation methodology, comprehensively evaluating a new CT-scanner-based AI contouring solution in terms of PD and RD within an automated planning workflow.

METHODS

20 prostate patients were selected to evaluate AI contouring for rectum, bladder, and proximal femurs. Five planning 'pipelines' were considered; three using AI contours with differing levels of manual editing (nominally none (AIStd), minor editing in specific regions (AIMinEd), and fully corrected (AIFullEd)). Remaining pipelines were manual delineations from two observers (MDOb1, MDOb2). Automated radiotherapy plans were generated for each pipeline. Geometric and dosimetric agreement of contour sets AIStd, AIMinEd, AIFullEd and MDOb2 were evaluated against the reference set MDOb1. Non-inferiority of AI pipelines was assessed, hypothesising that compared to MDOb1, absolute deviations in metrics for AI contouring were no greater than that from MDOb2.

RESULTS

Compared to MDOb1, organ delineation time was reduced by 24.9 min (96 %), 21.4 min (79 %) and 12.2 min (45 %) for AIStd, AIMinEd and AIFullEd respectively. All pipelines exhibited generally good dosimetric agreement with MDOb1. For RD, median deviations were within ± 1.8 cm3, ± 1.7 % and ± 0.6 Gy for absolute volume, relative volume and mean dose metrics respectively. For PD, respective values were within ± 0.4 cm3, ± 0.5 % and ± 0.2 Gy. Statistically (p < 0.05), AIMinEd and AIFullEd were dosimetrically non-inferior to MDOb2.

CONCLUSIONS

This novel dosimetric validation demonstrated that following targeted minor editing (AIMinEd), AI contours were dosimetrically non-inferior to manual delineations, reducing delineation time by 79 %.

Molecular architecture of the actin cytoskeleton: From single cells to whole organisms using cryo-electron tomography

Cryo-electron tomography (cryo-ET) has begun to provide intricate views of cellular architecture at unprecedented resolutions. Considerable efforts are being made to further optimize and automate the cryo-ET workflow, from sample preparation to data acquisition and analysis, to enable visual proteomics inside of cells. Here, we will discuss the latest advances in cryo-ET that go hand in hand with their application to the actin cytoskeleton. The development of deep learning tools for automated annotation of tomographic reconstructions and the serial lift-out sample preparation procedure will soon make it possible to perform high-resolution structural biology in a whole new range of samples, from multicellular organisms to organoids and tissues.

Cost analyses for malaria molecular diagnosis for research planners in India and beyond

BACKGROUND

Malaria elimination mandates early and accurate diagnosis of infection. Although malaria diagnosis is programmatically dependent on microscopy/RDTs, molecular diagnosis has much better diagnostic accuracy. Higher cost of molecular diagnoses is a recognized challenge for use at the point of care. Because funding is always a recognized constraint, we performed financial cost-analyses of available molecular platforms for better utilization of available budget.

METHODS

Two strategies were applied to deduce the cost per sample. Strategy 1 included recurring components (RC) in minimum pack size, and biologist's time whereas strategy 2 included only RC and non-recurring components and costs are calculated for sample sizes (1-1,000,000) to infer the sample size effect.

RESULTS

Spin column-based manual DNA extraction (US$ 3.93 per sample) is the lowest-cost method, followed by magnetic bead-based automated, semi-automated, and PCI-based manual method. Further, DNA extraction cost per sample via spin column-based manual method and semi-automated method decreases with an increase in sample size up to 10,000. Real-time PCRs are ~ 2-fold more economical than conventional PCR, regardless of sample size.

CONCLUSIONS

This study is the first for malaria to estimate systematic molecular diagnosis financial costs. Kit-based and automated methods may replace conventional DNA extraction and amplification methods for a frugal high-throughput diagnosis.

Recent advances in the synthesis of extensive libraries of heparan sulfate oligosaccharides for structure-activity relationship studies

Heparan sulfate (HS) is a linear, sulfated and highly negatively-charged polysaccharide that plays important roles in many biological events. As a member of the glycosaminoglycan (GAG) family, HS is commonly found on mammalian cell surfaces and within the extracellular matrix. The structural complexities of natural HS polysaccharides have hampered the comprehension of their biological functions and structure-activity relationships (SARs). Although the sulfation patterns and backbone structures of HS can be major determinants of their biological activities, obtaining significant amounts of pure HS from natural sources for comprehensive SAR studies is challenging. Chemical and enzyme-based synthesis can aid in the production of structurally well-defined HS oligosaccharides. In this review, we discuss recent innovations enabling the syntheses of large libraries of HS and how these libraries can provide insights into the structural preferences of various HS binding proteins.

A smartphone serves as a data logger for a fully automated lab-constructed microfluidic system

Fluorescence is an innovative technique that has captivated scholars in recent years due to its superior sensitivity and selectivity. The development of microfluidic components has added to its appeal, particularly given the technology ability to control fluid using very small quantities (microliter range) and achieve high liquid throughput. We have combined these two technologies to develop a lab-constructed simple system for measuring fluorescence, notable for the following features:•The device constructed entirely in our lab and programmed for measuring the fluorescence of liquids using microfluidic technology, delivered excellent results. The regression coefficient R² (0.9995) was obtained five points between 0.001-0.01µg .ml-1. Moreover, the reproducibility standard deviation (%) of 0.008 µg .ml-1 fluorescein dye remained at zero, for ten repeated experiments.•The device was full automated using a smartphone as a data logger, and lab-constructed programs.•The results were satisfactory with a detection limit of 1 × 10-4 µg.ml-1. This proposed system can measure over 200 samples per hour making it highly efficient and eco-friendly due to the reduced use of reagents and lower waste production. The fully automated system can effectively be used to determine fluorescein dye concentrations. Another application (micro pump view) manages all actions required in this microfluidic system, such as operating the two lab-constructed peristaltic pumps.

Sequential Treatment Application Robot (STAR) for high-replication marine experimentation

Marine organisms are often subject to numerous anthropogenic stressors, resulting in widespread ecosystem degradation. Physiological responses to these stressors, however, are complicated by high biological variability, species-specific sensitivities, nonlinear relationships, and countless permutations of stressor combinations. Nevertheless, quantification of these relationships is paramount for parameterizing predictive tools and ultimately for effective management of marine resources. Multi-level, multi-stressor experimentation is therefore key, yet the high replication required has remained a logistical challenge and a financial barrier. To overcome these issues, we created an automated system for experimentation on marine organisms, the Sequential Treatment Application Robot (STAR). The system consists of a track-mounted robotic arm that sequentially applies precision treatments to independent aquaria via syringe and peristaltic pumps. The accuracy and precision were validated with dye and spectrophotometry, and stability was demonstrated by maintaining corals under treatment conditions for more than a month. The system is open source and scalable in that additional treatments and replicates may be added without incurring multiplicative costs. While STAR was designed for investigating the combined impacts of nutrients, warming, and disease on reef-building corals, it is highly customizable and may be used for experimentation involving a diverse array of treatments and species.

A practical approach to supported liquid extraction and measurement of 18 steroids in plasma and serum by targeted liquid chromatography tandem mass spectrometry

Chromatography combined with mass spectrometry is a gold standard technique for steroid measurement, however the type of sample preparation, the dynamic range and reliability of the calibration curve, the chromatographic separation and mass spectrometry settings ultimately determine the success of the method. The steroid biosynthetic pathway is conserved in higher mammals and literature demonstrates that the concentration ranges of different steroid groups are relatively comparable across species. We sought to develop a robust and reliable multi steroid targeted analysis method for blood that would have wide application across higher mammals. The method was developed following bioanalytical method validation guidelines to standards typically applied to human clinical studies, including isotopically labelled internal standards where at all possible. Here we describe the practical approach to a 96-well supported liquid extraction (SLE) method of extraction from plasma (200 µL) using an Extrahera liquid handling robot (Biotage, Sweden), including quality control samples, followed by a comprehensive separation and targeted LC-MS/MS analysis of 18 steroids in plasma (pregnenolone, progesterone, 17α-hydroxyprogesterone, 11-deoxycorticosterone, corticosterone, 11-dehydrocorticosterone, aldosterone, 11-deoxycortisol, 21-deoxycortisol, cortisol, cortisone, androstenedione, testosterone, 5α-dihydrotestosterone, dehydroepiandrosterone, estrone, 17β-estradiol and estriol). •SLE in a 96-well format of up to 74 biological plasma samples, enriched with multiple isotopically labelled internal standards, a 12-point aqueous calibration curve, and 6 serum quality controls, designed to monitor long-term performance of the method•Chromatographic separation of multiple steroids along the gradient, with ammonium fluoride mobile phase additive to improve sensitivity, followed by electrospray ionisation and constant polarity switching•Aqueous calibration standards that cover physiologically relevant ranges - high nanomolar glucocorticoids, low nanomolar androgens and picomolar ranges for estrogens and steroid intermediates.

High resolution depth profile scanning of plankton organisms-VERTILICE

Knowledge of the vertical migration pattern of sea lice (Lepeophtheirus salmonis) copepodites is necessary for designing efficient measures to prevent lice infestations on farmed Atlantic salmon (Salmo Salar) in sea-cages. However, data can be challenging to acquire at a large scale under realistic circumstances without interfering with the natural behavior of the specimen. A mesocosm platform was built to help acquire this data consisting of a sensor package in an underwater housing being pulled up and down along a 11-meter-long transparent tube containing planktonic organisms while collecting image-, temperature- and spectrometer data. The platform was placed at a salmon farm and the acrylic tube was filled with L. salmonis copepodites and was pre-programmed to run a profile scan twice per hour for four consecutive days. Using a fully convolutional neural network, the copepodites were automatically counted - creating a depth profile of detected lice and measured light specter. The final results showed a diurnal migration pattern throughout the test period.•Capable of acquiring vertical density profiles of any aquatic species between 0,5 - 10 mm down to 11 m below the surface.•Fully automated and can be left unintended for weeks while collecting data.

AST: An OpenSim-based tool for the automatic scaling of generic musculoskeletal models

BACKGROUND AND OBJECTIVES

The paper introduces a tool called Automatic Scaling Tool (AST) designed for improving and expediting musculoskeletal (MSK) simulations based on generic models in OpenSim. Scaling is a crucial initial step in MSK analyses, involving the correction of virtual marker locations on a model to align with actual experimental markers.

METHODS

The AST automates this process by iteratively adjusting virtual markers using scaling and inverse kinematics on a static trial. It evaluates the root mean square error (RMSE) and maximum marker error, implementing corrective actions until achieving the desired accuracy level. The tool determines whether to scale a segment with a marker-based or constant scaling factor based on checks on RMSE and segment scaling factors.

RESULTS

Testing on three generic MSK models demonstrated that the AST significantly outperformed manual scaling by an expert operator. The RMSE for static trials was one order of magnitude lower, and for gait tasks, it was five times lower (8.5 ± 0.76 mm vs. 44.5 ± 7.5 mm). The AST consistently achieved the desired level of accuracy in less than 100 iterations, providing reliable scaled MSK models within a relatively brief timeframe, ranging from minutes to hours depending on model complexity.

CONCLUSIONS

The paper concludes that AST can greatly benefit the biomechanical community by quickly and accurately scaling generic models, a critical first step in MSK analyses. Further validation through additional experimental datasets and generic models is proposed for future tests.

Practical deployment of automation to expedite aqueous two-phase extraction

The feasibility of bioprocess development relies heavily on the successful application of primary recovery and purification techniques. Aqueous two-phase extraction (ATPE) disrupts the definition of "unit operation" by serving as an integrative and intensive technique that combines different objectives such as the removal of biomass and integrated recovery and purification of the product of interest. The relative simplicity of processing large samples renders this technique an attractive alternative for industrial bioprocessing applications. However, process development is hindered by the lack of easily predictable partition behaviours, the elucidation of which necessitates a large number of experiments to be conducted. Liquid handling devices can assist to address this problem; however, they are configured to operate using low viscosity fluids such as water and water-based solutions as opposed to highly viscous polymeric solutions, which are typically required in ATPE. In this work, an automated high throughput ATPE process development framework is presented by constructing phase diagrams and identifying the binodal curves for PEG6000, PEG3000, and PEG2000. Models were built to determine viscosity- and volume-independent transfer parameters. The framework provided an appropriate strategy to develop a very precise and accurate operation by exploiting the relationship between different liquid transfer parameters and process error. Process accuracy, measured by mean absolute error, and device precision, evaluated by the coefficient of variation, were both shown to be affected by the mechanical properties, particularly viscosity, of the fluids employed. For PEG6000, the mean absolute error improved by six-fold (from 4.82% to 0.75%) and the coefficient of variation improved by three-fold (from 0.027 to 0.008) upon optimisation of the liquid transfer parameters accounting for the viscosity effect on the PEG-salt buffer utilising ATPE operations. As demonstrated here, automated liquid handling devices can serve to streamline process development for APTE enabling wide adoption of this technique in large scale bioprocess applications.

A fast and high precision multi-robot environment modeling based on M-BFSI: Bidirectional filtering and scene identification method

This article designs and implements a fast and high-precision multi-robot environment modeling method based on bidirectional filtering and scene identification. To solve the problem of feature tracking failure caused by large angle rotation, a bidirectional filtering mechanism is introduced to improve the error-matching elimination algorithm. A global key frame database for multiple robots is proposed based on a pretraining dictionary to convert images into a bag of words vectors. The images captured by different sub-robots are compared with the database for similarity score calculation, so as to realize fast identification and search of similar scenes. The coordinate transformation from local map to global map and the cooperative SLAM exploration of multiple robots is completed by the best matching image and the transformation matrix. The experimental results show that the proposed algorithm can effectively close the predicted trajectory of the sub-robot, thus achieving high-precision collaborative environment modeling.

A qualitative interview study to determine barriers and facilitators of implementing automated decision support tools for genomic data access

Data access committees (DAC) gatekeep access to secured genomic and related health datasets yet are challenged to keep pace with the rising volume and complexity of data generation. Automated decision support (ADS) systems have been shown to support consistency, compliance, and coordination of data access review decisions. However, we lack understanding of how DAC members perceive the value add of ADS, if any, on the quality and effectiveness of their reviews. In this qualitative study, we report findings from 13 semi-structured interviews with DAC members from around the world to identify relevant barriers and facilitators to implementing ADS for genomic data access management. Participants generally supported pilot studies that test ADS performance, for example in cataloging data types, verifying user credentials and tagging datasets for use terms. Concerns related to over-automation, lack of human oversight, low prioritization, and misalignment with institutional missions tempered enthusiasm for ADS among the DAC members we engaged. Tensions for change in institutional settings within which DACs operated was a powerful motivator for why DAC members considered the implementation of ADS into their access workflows, as well as perceptions of the relative advantage of ADS over the status quo. Future research is needed to build the evidence base around the comparative effectiveness and decisional outcomes of institutions that do/not use ADS into their workflows.

GMP production of [18F]FE-PE2I on a TRACERLab FX2 N synthesis module, a radiotracer for in vivo PET imaging of the dopamine transport

BACKGROUND

Parkinson's disease is a neurodegenerative disorder that is characterized by a degeneration of the dopaminergic system. Dopamine transporter (DAT) positron emission tomography (PET) imaging has emerged as a powerful and non-invasive method to quantify dopaminergic function in the living brain. The PET radioligand, [18F]FE-PE2I, a cocaine chemical derivative, has shown promising properties for in vivo PET imaging of DAT, including high affinity and selectivity for DAT, excellent brain permeability, and favorable metabolism. The aim of the current study was to scale up the production of [18F]FE-PE2I to fulfil the increasing clinical demand for this tracer.

RESULTS

Thus, a fully automated and GMP-compliant production procedure has been developed using a commercially available radiosynthesis module GE TRACERLab FX2 N. [18F]FE-PE2I was produced with a radiochemical yield of 39 ± 8% (n = 4, relative [18F]F- delivered to the module). The synthesis time was 70 min, and the molar activity was 925.3 ± 763 GBq/µmol (250 ± 20 Ci/µmol). The produced [18F]FE-PE2I was stable over 6 h at room temperature.

CONCLUSION

The protocol reliably provides a sterile and pyrogen-free GMP-compliant product.

Automatic center identification of electron diffraction with multi-scale transformer networks

Selected area electron diffraction (SAED) is a widely used technique for characterizing the structure and measuring lattice parameters of materials. An autonomous analytic method has become an urgent demand for the large-scale SAED data produced from in-situ experiments. In this work, we realize the automatic processing for center identification with a proposed deep segmentation model named the multi-scale Transformer (MS-Trans) network. This algorithm enables robust segmentation of the central spots by combining a novel gated axial-attention module and multi-scale feature fusion. The proposed MS-Trans model shows high precision and robustness, enabling autonomous processing of SAED patterns without any prior knowledge. The application on in-situ SAED data of the oxidation process of FeNi alloy demonstrates its capability of implementing autonomous quantitative processing. © 2017 Elsevier Inc. All rights reserved.

Should automated electronic hand-hygiene monitoring systems be implemented in routine patient care? Systematic review and appraisal with Medical Research Council Framework for Complex Interventions

Manual hand-hygiene audit is time-consuming, labour-intensive and inaccurate. Automated hand-hygiene monitoring systems (AHHMSs) offer advantages (generation of standardized data, avoidance of the Hawthorne effect). World Health Organization Guidelines for Hand Hygiene published in 2009 suggest that AHHMSs are a possible alternative. The objective of this review was to assess the current state of the literature for AHHMSs and offer recommendations for use in real-world settings. This was a systematic literature review, and publications included were from the time that PubMed commenced until 19th November 2023. Forty-three publications met the criteria. Using the Medical Research Council's Framework for Developing and Evaluating Complex Interventions, two were categorized as intervention development studies. Thirty-nine were evaluations. Two described implementation in real-world settings. Most were small scale and short duration. AHHMSs in conjunction with additional intervention (visual or auditory cue, performance feedback) could increase hand hygiene compliance in the short term. Impact on infection rates was difficult to determine. In the few publications where costs and resources were considered, time devoted to improving hand hygiene compliance increased when an AHHMS was in use. Health workers' opinions about AHHMSs were mixed. In conclusion, at present too little is known about the longer-term advantages of AHHMSs to recommend uptake in routine patient care. Until more longer-term accounts of implementation (over 12 months) become available, efforts should be made to improve direct observation of hand hygiene compliance to improve its accuracy and credibility. The Medical Research Council Framework could be used to categorize other complex interventions involving use of technology to prevent infection to help establish readiness for implementation.

Handling of problematic ion chromatograms with the Automated Target Screening (ATS) workflow for unsupervised analysis of high-resolution mass spectrometry data

Liquid chromatography (LC) or gas chromatography (GC) coupled to high-resolution mass spectrometry (HRMS) is a versatile analytical method for the analysis of thousands of chemical pollutants that can be found in environmental and biological samples. While the tools for handling such complex datasets have improved, there are still no fully automated workflows for targeted screening analysis. Here we present an R-based workflow that is able to cope with challenging data like noisy ion chromatograms, retention time shifts, and multiple peak patterns. The workflow can be applied to batches of HRMS data recorded after GC with electron ionization (GC-EI) and LC coupled to electrospray ionization in both negative and positive mode (LC-ESIneg/LC-ESIpos) to perform peak annotation and quantitation fully unsupervised. We used Orbitrap HRMS data of surface water extracts to compare the Automated Target Screening (ATS) workflow with data evaluations performed with the vendor software TraceFinder and the established semi-automated analysis workflow in the MZmine software. The ATS approach increased the overall evaluation performance of the peak annotation compared to the established MZmine module without the need for any post-hoc corrections. The overall accuracy increased from 0.80 to 0.86 (LC-ESIpos), from 0.77 to 0.83 (LC-ESIneg), and from 0.67 to 0.76 (GC-EI). The mean average percentage errors for quantification of ATS were around 30% compared to the manual quantification with TraceFinder. The ATS workflow enables time-efficient analysis of GC- and LC-HRMS data and accelerates and improves the applicability of target screening in studies with a large number of analytes and sample sizes without the need for manual intervention.

Automated molecular detection of West Nile Virus in mosquito pools using the Panther Fusion system

West Nile Virus (WNV) is an arthropod-borne virus that is spread through mosquito vectors. WNV emerged in the US in 1999 and has since become endemic in the US, causing the most domestically acquired arboviral disease in the country. Mosquito surveillance for WNV is useful to monitor arboviral disease burden over time and across different locations. RT-qPCR is the preferred method for WNV surveillance, but these methods are labor-intensive. The Panther Fusion System has an Open Access feature that allows for laboratory-developed tests (LDTs) to run on a fully automated system for nucleic acid extraction, RT-qPCR, and result generation. This study demonstrates the successful optimization of a WNV multiplex LDT (assay targets: ENV and NS1 genes) for high-throughput environmental surveillance testing of mosquito pool homogenates on the Panther Fusion System. Analytical sensitivity of the assay was 186 and 744 copies/PCR reaction for the ENV and NS1 targets, respectively. To assess the performance of this assay, a total of 80 mosquito pools were tested, including 60 previously tested pools and 20 spiked negative mosquito pools. Among the 60 previously tested specimens, the Panther Fusion WNV LDT demonstrated 100% positive and negative agreement with the CDC West Nile RT-qPCR assay. The Panther Fusion WNV LDT also detected all 20 spiked specimens. The Panther Fusion WNV LDT assay was successfully developed and optimized for high throughput testing with similar performance to the previously used CDC West Nile RT-qPCR assay.

[Artificial intelligence for pathology-how, where, and why?]

Artificial intelligence promises many innovations and simplifications in pathology, but also raises just as many questions and uncertainties. In this article, we provide a brief overview of the current status, the goals already achieved by existing algorithms, and the remaining challenges.

Unlocking human-like conversations: Scoping review of automation techniques for personalized healthcare interventions using conversational agents

BACKGROUND

Conversational agents (CAs) offer a sustainable approach to deliver personalized interventions and improve health outcomes.

OBJECTIVES

To review how human-like communication and automation techniques of CAs in personalized healthcare interventions have been implemented. It is intended for designers and developers, computational scientists, behavior scientists, and biomedical engineers who aim at developing CAs for healthcare interventions.

METHODOLOGY

A scoping review was conducted in accordance with PRISMA Extension for Scoping Review. A search was performed in May 2023 in Web of Science, Pubmed, Scopus and IEEE databases. Search results were extracted, duplicates removed, and the remaining results were screened. Studies that contained personalized and automated CAs within the healthcare domain were included. Information regarding study characterization, and human-like communication and automation techniques was extracted from articles that met the eligibility criteria.

RESULTS

Twenty-three studies were selected. These articles described the development of CAs designed for patients to either self-manage their diseases (such as diabetes, mental health issues, cancer, asthma, COVID-19, and other chronic conditions) or to enhance healthy habits. The human-like communication characteristics studied encompassed aspects like system flexibility, personalization, and affective characteristics. Seven studies used rule-based models, eleven applied retrieval-based techniques for content delivery, five used AI models, and six integrated affective computing.

CONCLUSIONS

The increasing interest in employing CAs for personalized healthcare interventions is noteworthy. The adaptability of dialogue structures and personalization features is still limited. Unlocking human-like conversations may encompass the use of affective computing and generative AI to help improve user engagement. Future research should focus on the integration of holistic methods to describe the end-user, and the safe use of generative models.

Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement From the ACR, CAR, ESR, RANZCR & RSNA

Artificial Intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing diagnosis, quantification, and management of multiple medical conditions. Nevertheless, the ever‑growing availability of AI tools in radiology highlights an increasing need to critically evaluate claims for its utility and to differentiate safe product offerings from potentially harmful, or fundamentally unhelpful ones. This multi‑society paper, presenting the views of Radiology Societies in the USA, Canada, Europe, Australia, and New Zealand, defines the potential practical problems and ethical issues surrounding the incorporation of AI into radiological practice. In addition to delineating the main points of concern that developers, regulators, and purchasers of AI tools should consider prior to their introduction into clinical practice, this statement also suggests methods to monitor their stability and safety in clinical use, and their suitability for possible autonomous function. This statement is intended to serve as a useful summary of the practical issues which should be considered by all parties involved in the development of radiology AI resources, and their implementation as clinical tools.

Radiosynthesis automation, non-human primate biodistribution and dosimetry of K+ channel tracer [11C]3MeO4AP

BACKGROUND

4-Aminopyridine (4AP) is a medication for the symptomatic treatment of multiple sclerosis. Several 4AP-based PET tracers have been developed for imaging demyelination. In preclinical studies, [11C]3MeO4AP has shown promise due to its high brain permeability, high metabolic stability, high plasma availability, and high in vivo binding affinity. To prepare for the translation to human studies, we developed a cGMP-compatible automated radiosynthesis protocol and evaluated the whole-body biodistribution and radiation dosimetry of [11C]3MeO4AP in non-human primates (NHPs).

METHODS

Automated radiosynthesis was carried out using a GE TRACERlab FX-C Pro synthesis module. One male and one female adult rhesus macaques were used in the study. A high-resolution CT from cranial vertex to knee was acquired. PET data were collected using a dynamic acquisition protocol with four bed positions and 13 passes over a total scan time of ~ 150 min. Based on the CT and PET images, volumes of interest (VOIs) were manually drawn for selected organs. Non-decay corrected time-activity curves (TACs) were extracted for each VOI. Radiation dosimetry and effective dose were calculated from the integrated TACs using OLINDA software.

RESULTS

Fully automated radiosynthesis of [11C]3MeO4AP was achieved with 7.3 ± 1.2% (n = 4) of non-decay corrected radiochemical yield within 38 min of synthesis and purification time. [11C]3MeO4AP distributed quickly throughout the body and into the brain. The organs with highest dose were the kidneys. The average effective dose of [11C]3MeO4AP was 4.0 ± 0.6 μSv/MBq. No significant changes in vital signs were observed during the scan.

CONCLUSION

A cGMP-compatible automated radiosynthesis of [11C]3MeO4AP was developed. The whole-body biodistribution and radiation dosimetry of [11C]3MeO4AP was successfully evaluated in NHPs. [11C]3MeO4AP shows lower average effective dose than [18F]3F4AP and similar average effective dose as other carbon-11 tracers.

Automation of MKID Simulations for Array Building with AEM (Automated Electromagnetic MKID Simulations)

Microwave Kinetic Inductance Detectors (MKIDs) are photon detectors comprised of superconducting LC resonators with unique resonant frequencies corresponding to their geometrical structure. As each pixel has its own geometry, electromagnetic simulations by hand of every pixel in a kilo-pixel array are impractical. Simulating fewer pixels and interpolating in between risks reduced pixel yield in arrays due to overlapping resonant frequencies. We introduce a new software called AEM (Automated Electromagnetic MKID simulations) that automates the construction and simulation of every simulated MKID pixel in an array according to specified resonant frequencies and a Q c range. We show automated designs to have an increased pixel yield (avoiding loses due to interpolation completely), increased accuracy in resonance frequency and Q c values when compared to interpolated structures. We also demonstrate a simulated trial of AEM for 100 MKIDs between 4 and 8 GHz to produce MKIDs with accuracies of ± 0.2 MHz with a runtime of 10 h 45 min.

A novel automated multi-cycle magnetic solid-phase extraction coupled to LC-MS/MS to study the disorders of six functional B vitamins in patients with gastroenterology and hyperhomocysteinemia

B vitamins are essential for human life and their disorders can cause a variety of diseases. Solid-phase extraction (SPE) coupled to LC-MS/MS is a preferred technique for determining multiple B vitamins, however, their complexity in real biological matrices makes it hard to achieve satisfactory recovery and accuracy when simultaneous detection. In this study, a novel automated multi-cycle magnetic SPE (MSPE) coupled to the LC-MS/MS method was established using a mixed-mode anion exchange magnetic adsorbent for the simultaneous extraction of six functional B vitamins, including methylmalonic acid, riboflavin, pantothenic acid, 4-pyridoxic acid, folic acid, and 5-methyltetrahydrofolate. After three consecutive MSPE cycles, the recoveries of all analytes were between 51.5% and 89.6%. The method exhibited excellent sensitivity and linearity, with a dynamic range of 200-fold (R > 0.99 for all analytes), exceptional accuracy (ranging between 95.4% and 105.6%) and precision (with RSDs ≤ 6.2%) without significant matrix effects or interferences. Compared to manual SPE method, the automated multi-cycle MSPE method has better feasibility and greater vitamin coverage. It shows a high correlation with the manual method for the detection of 5-methyltetrahydrofolate and folate (R > 0.99). A study of patients from the gastroenterology department showed that those undergoing surgery and those with malignancies may be at risk of folate deficiency. In addition, patients with hyperhomocystinemia had higher levels of methylmalonic acid and lower levels of 5-methyltetrahydrofolate, which correlated with homocysteine levels (R = 0.404 and -0.311, respectively) and showed dose-response relationships. This method is highly automated and cost-effective, with minimal systematic error, making it suitable for the analysis of clinical samples.