Precision and Test-Retest Repeatability of Stiffness Measurement with MR Elastography: A Multicenter Phantom Study.

Background MR elastography (MRE) has been shown to have excellent performance for noninvasive liver fibrosis staging. However, there is limited knowledge regarding the precision and test-retest repeatability of stiffness measurement with MRE in the multicenter setting. Purpose To determine the precision and test-retest repeatability of stiffness measurement with MRE across multiple centers using the same phantoms. Materials and Methods In this study, three cylindrical phantoms made of polyvinyl chloride gel mimicking different degrees of liver stiffness in humans (phantoms 1-3: soft, medium, and hard stiffness, respectively) were evaluated. Between January 2021 and January 2022, phantoms were circulated between five different centers and scanned with 10 MRE-equipped clinical 1.5-T and 3-T systems from three major vendors, using two-dimensional (2D) gradient-recalled echo (GRE) imaging and/or 2D spin-echo (SE) echo-planar imaging (EPI). Similar MRE acquisition parameters, hardware, and reconstruction algorithms were used at each center. Mean stiffness was measured by a single observer for each phantom and acquisition on a single section. Stiffness measurement precision and same-session test-retest repeatability were assessed using the coefficient of variation (CV) and the repeatability coefficient (RC), respectively. Results The mean precision represented by the CV was 5.8% (95% CI: 3.8, 7.7) for all phantoms and both sequences combined. For all phantoms, 2D GRE achieved a CV of 4.5% (95% CI: 3.3, 5.7) whereas 2D SE EPI achieved a CV of 7.8% (95% CI: 3.1, 12.6). The mean RC of stiffness measurement was 5.8% (95% CI: 3.7, 7.8) for all phantoms and both sequences combined, 4.9% (95% CI: 2.7, 7.0) for 2D GRE, and 7.0% (95% CI: 2.9, 11.2) for 2D SE EPI (all phantoms). Conclusion MRE had excellent in vitro precision and same-session test-retest repeatability in the multicenter setting when similar imaging protocols, hardware, and reconstruction algorithms were used. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Tang in this issue.

Soluble CTLA-4 attenuates T cell activation and modulates anti-tumor immunity.

CTLA-4 is a crucial immune checkpoint receptor involved in the maintenance of immune homeostasis, tolerance, and tumor control. Antibodies targeting CTLA-4 have been promising treatments for numerous cancers, but the mechanistic basis of their anti-tumoral immune-boosting effects is poorly understood. Although the ctla4 gene also encodes an alternatively spliced soluble variant (sCTLA-4), preclinical/clinical evaluation of anti-CTLA-4-based immunotherapies have not considered the contribution of this isoform. Here, we explore the functional properties of sCTLA-4 and evaluate the efficacy of isoform-specific anti-sCTLA-4 antibody targeting in a murine cancer model. We show that expression of sCTLA-4 by tumor cells suppresses CD8+ T cells in vitro and accelerates growth and experimental metastasis of murine tumors in vivo. These effects were accompanied by modification of the immune infiltrate, notably restraining CD8+ T cells in a non-cytotoxic state. sCTLA-4 blockade with isoform-specific antibody reversed this restraint, enhancing intratumoral CD8+ T cell activation and cytolytic potential, correlating with therapeutic efficacy and tumor control. This previously unappreciated role of sCTLA-4 suggests that the biology and function of multi-gene products of immune checkpoint receptors need to be fully elucidated for improved mechanistic understanding of cancer immunotherapies.

Differential Regulation of the STING Pathway in Human Papillomavirus-Positive and -Negative Head and Neck Cancers.

Squamous cell carcinomas, which arise from the cells that line the mucosal surfaces of the head and neck, represent the most common type of head and neck cancers (HNSCC). Human papillomavirus (HPV) infection has been strongly associated with the development of oropharyngeal cancers, which are cancers that occur in the back of the throat, including the tonsils and base of the tongue. HNSCCs with and without HPV infection have distinct pathology, with HPV-positive patients having higher levels of immune infiltration, activation in the tumor microenvironment and better response to radiation and chemotherapy. It is, however, unclear whether HPV infection in HNSCCs has the potential to activate innate-immune sensing pathways and if these cancers possess intrinsic immunogenicity associated with HPV infection. Here we investigate the innate immune stimulator of interferon genes (STING) pathway and immune responses to STING activation in HNSCCs and uncover fundamental differences in the regulation of this pathway in cell lines versus primary human clinical specimens. We show that while STING is differentially expressed in HPV-positive and -negative HNSCC cell lines, they exhibit a gross functional defect in signaling through this pathway. However, STING activation in immune cell populations generated immune signatures predicted to elicit useful tumoricidal mechanisms. In contrast, IHC analysis of human tissue microarrays revealed enhanced STING expression in HPV-related tumors and high intratumoral expression of STING correlated with increased survival. SIGNIFICANCE: STING is an important innate immune sensor of cytosolic DNA, inducing essential antiviral and antitumoral responses. This research shows that STING expression is enhanced in HPV-positive HNSCC patient tissue, with high intratumoral STING expression correlating with increased survival. In addition, STING activation in immune cell populations augmented antitumoral effects against HNSCCs, suggesting patients may benefit from the use of STING agonists in combination with traditional therapies.

Understanding cancer patient cohorts in virtual reality environment for better clinical decisions: a usability study.

BACKGROUND: Visualising patient genomic data in a cohort with embedding data analytics models can provide relevant and sensible patient comparisons to assist a clinician with treatment decisions. As immersive technology is actively used around the medical world, there is a rising demand for an efficient environment that can effectively display genomic data visualisations on immersive devices such as a Virtual Reality (VR) environment. The VR technology will allow clinicians, biologists, and computer scientists to explore a cohort of individual patients within the 3D environment. However, demonstrating the feasibility of the VR prototype needs domain users' feedback for future user-centred design and a better cognitive model of human-computer interactions. There is limited research work for collecting and integrating domain knowledge into the prototype design. OBJECTIVE: A usability study for the VR prototype--Virtual Reality to Observe Oncology data Models (VROOM) was implemented. VROOM was designed based on a preliminary study among medical users. The goals of this usability study included establishing a baseline of user experience, validating user performance measures, and identifying potential design improvements that are to be addressed to improve efficiency, functionality, and end-user satisfaction. METHODS: The study was conducted with a group of domain users (10 males, 10 females) with portable VR devices and camera equipment. These domain users included medical users such as clinicians and genetic scientists and computing domain users such as bioinformatics and data analysts. Users were asked to complete routine tasks based on a clinical scenario. Sessions were recorded and analysed to identify potential areas for improvement to the data visual analytics projects in the VR environment. The one-hour usability study included learning VR interaction gestures, running visual analytics tool, and collecting before and after feedback. The feedback was analysed with different methods to measure effectiveness. The statistical method Mann-Whitney U test was used to analyse various task performances among the different participant groups, and multiple data visualisations were created to find insights from questionnaire answers. RESULTS: The usability study investigated the feasibility of using VR for genomic data analysis in domain users' daily work. From the feedback, 65% of the participants, especially clinicians (75% of them), indicated that the VR prototype is potentially helpful for domain users' daily work but needed more flexibility, such as allowing them to define their features for machine learning part, adding new patient data, and importing their datasets in a better way. We calculated the engaged time for each task and compared them among different user groups. Computing domain users spent 50% more time exploring the algorithms and datasets than medical domain users. Additionally, the medical domain users engaged in the data visual analytics parts (approximately 20%) longer than the computing domain users.

Inferring actual treatment pathways from patient records.

OBJECTIVE: Treatment pathways are step-by-step plans outlining the recommended medical care for specific diseases; they get revised when different treatments are found to improve patient outcomes. Examining health records is an important part of this revision process, but inferring patients' actual treatments from health data is challenging due to complex event-coding schemes and the absence of pathway-related annotations. The objective of this study is to develop a method for inferring actual treatment steps for a particular patient group from administrative health records - a common form of tabular healthcare data - and address several technique- and methodology-based gaps in treatment pathway-inference research. METHODS: We introduce Defrag, a method for examining health records to infer the real-world treatment steps for a particular patient group. Defrag learns the semantic and temporal meaning of healthcare event sequences, allowing it to reliably infer treatment steps from complex healthcare data. To our knowledge, Defrag is the first pathway-inference method to utilise a neural network (NN), an approach made possible by a novel, self-supervised learning objective. We also developed a testing and validation framework for pathway inference, which we use to characterise and evaluate Defrag's pathway inference ability, establish benchmarks, and compare against baselines. RESULTS: We demonstrate Defrag's effectiveness by identifying best-practice pathway fragments for breast cancer, lung cancer, and melanoma in public healthcare records. Additionally, we use synthetic data experiments to demonstrate the characteristics of the Defrag inference method, and to compare Defrag to several baselines, where it significantly outperforms non-NN-based methods. CONCLUSIONS: Defrag offers an innovative and effective approach for inferring treatment pathways from complex health data. Defrag significantly outperforms several existing pathway-inference methods, but computationally-derived treatment pathways are still difficult to compare against clinical guidelines. Furthermore, the open-source code for Defrag and the testing framework are provided to encourage further research in this area.

Neuroblastoma: an ongoing cold front for cancer immunotherapy.

Neuroblastoma is the most frequent extracranial childhood tumour but effective treatment with current immunotherapies is challenging due to its immunosuppressive microenvironment. Efforts to date have focused on using immunotherapy to increase tumour immunogenicity and enhance anticancer immune responses, including anti-GD2 antibodies; immune checkpoint inhibitors; drugs which enhance macrophage and natural killer T (NKT) cell function; modulation of the cyclic GMP-AMP synthase-stimulator of interferon genes pathway; and engineering neuroblastoma-targeting chimeric-antigen receptor-T cells. Some of these strategies have strong preclinical foundation and are being tested clinically, although none have demonstrated notable success in treating paediatric neuroblastoma to date. Recently, approaches to overcome heterogeneity of neuroblastoma tumours and treatment resistance are being explored. These include rational combination strategies with the aim of achieving synergy, such as dual targeting of GD2 and tumour-associated macrophages or natural killer cells; GD2 and the B7-H3 immune checkpoint; GD2 and enhancer of zeste-2 methyltransferase inhibitors. Such combination strategies provide opportunities to overcome primary resistance to and maximize the benefits of immunotherapy in neuroblastoma.

Machine learning for administrative health records: A systematic review of techniques and applications.

Machine learning provides many powerful and effective techniques for analysing heterogeneous electronic health records (EHR). Administrative Health Records (AHR) are a subset of EHR collected for administrative purposes, and the use of machine learning on AHRs is a growing subfield of EHR analytics. Existing reviews of EHR analytics emphasise that the data-modality of the EHR limits the breadth of suitable machine learning techniques, and pursuable healthcare applications. Despite emphasising the importance of data modality, the literature fails to analyse which techniques and applications are relevant to AHRs. AHRs contain uniquely well-structured, categorically encoded records which are distinct from other data-modalities captured by EHRs, and they can provide valuable information pertaining to how patients interact with the healthcare system. This paper systematically reviews AHR-based research, analysing 70 relevant studies and spanning multiple databases. We identify and analyse which machine learning techniques are applied to AHRs and which health informatics applications are pursued in AHR-based research. We also analyse how these techniques are applied in pursuit of each application, and identify the limitations of these approaches. We find that while AHR-based studies are disconnected from each other, the use of AHRs in health informatics research is substantial and accelerating. Our synthesis of these studies highlights the utility of AHRs for pursuing increasingly complex and diverse research objectives despite a number of pervading data- and technique-based limitations. Finally, through our findings, we propose a set of future research directions that can enhance the utility of AHR data and machine learning techniques for health informatics research.

Precursor-Directed Biosynthesis and Biological Testing of omega-Alicyclic- and neo-Branched Tunicamycin N-Acyl Variants.

Tunicamycins (TUNs) are Streptomyces-derived natural products, widely used to block protein N-glycosylation in eukaryotes or cell wall biosynthesis in bacteria. Modified or synthetic TUN analogues that uncouple these activities have considerable potential as novel mode-of-action antibacterial agents. Chemically modified TUNs reported previously with attenuated activity on yeast have pinpointed eukaryotic-specific chemophores in the uridyl group and the N-acyl chain length and terminal branching pattern. A small molecule screen of fatty acid biosynthetic primers identified several novel alicyclic- and neo-branched TUN N-acyl variants, with primer incorporation at the terminal omega-acyl position. TUNs with unique 5- and 6-carbon ω-cycloalkane and ω-cycloalkene acyl chains are produced under fermentation and in yields comparable with the native TUN. The purification, structural assignments, and the comparable antimicrobial properties of 15 of these compounds are reported, greatly extending the structural diversity of this class of compounds for potential medicinal and agricultural applications.

A review of the machine learning datasets in mammography, their adherence to the FAIR principles and the outlook for the future.

The increasing rates of breast cancer, particularly in emerging economies, have led to interest in scalable deep learning-based solutions that improve the accuracy and cost-effectiveness of mammographic screening. However, such tools require large volumes of high-quality training data, which can be challenging to obtain. This paper combines the experience of an AI startup with an analysis of the FAIR principles of the eight available datasets. It demonstrates that the datasets vary considerably, particularly in their interoperability, as each dataset is skewed towards a particular clinical use-case. Additionally, the mix of digital captures and scanned film compounds the problem of variability, along with differences in licensing terms, ease of access, labelling reliability, and file formats. Improving interoperability through adherence to standards such as the BIRADS criteria for labelling and annotation, and a consistent file format, could markedly improve access and use of larger amounts of standardized data. This, in turn, could be increased further by GAN-based synthetic data generation, paving the way towards better health outcomes for breast cancer.

Magnetic resonance elastography for noninvasive detection of liver fibrosis: is there an added value of 3D acquisition?

PURPOSE: (1) Assess the diagnostic performance of liver 3D magnetic resonance elastography (MRE) parameters (including stiffness, storage/loss modulus and damping ratio) compared to liver stiffness measured with 2D MRE for noninvasive detection of advanced liver fibrosis (F3-F4) and cirrhosis (F4) in patients with chronic liver disease. (2) Assess the value of serum markers (FIB-4) in detecting advanced liver fibrosis and cirrhosis in the same patients. METHODS: This was a single center, prospective IRB-approved cross-sectional study that included 49 patients (M/F: 23/26, mean age 50.8 y) with chronic liver disease and concomitant liver biopsy. MRE was acquired at 1.5T using a spin echo-EPI sequence. The following parameters were measured: liver stiffness using 2D MRE (LS-2D) and 3D MRE parameters (LS-3D, liver storage, loss modulus and damping ratio). The Mann-Whitney U test, ROC curve analysis, Spearman correlation and logistic regression were performed to evaluate diagnostic performance of MRE parameters and FIB-4. RESULTS: LS-2D and LS-3D had similar diagnostic performance for diagnosis of F3-F4, with AUCs of 0.87 and 0.88, sensitivity of 0.71 and 0.81, specificity of 0.89 for both. For diagnosis of F4, LS-2D and LS-3D had similar performance with AUCs of 0.81 for both, sensitivity of 0.75 and 0.83, and specificity of 0.84 and 0.73, respectively. Additional 3D parameters (storage modulus, loss modulus, damping ratio) had variable performance, with AUC range of 0.59-0.78 for F3-F4; and 0.52-0.70 for F4. FIB-4 had lower diagnostic performance, with AUCs of 0.66 for F3-F4, and 0.68 for F4. CONCLUSION: Our study shows no added value of 3D MRE compared to 2D MRE for detection of advanced fibrosis and cirrhosis, while FIB-4 had lower diagnostic performance.

A state-of-the-art methodology for high-throughput in silico vaccine discovery against protozoan parasites and exemplified with discovered candidates for Toxoplasma gondii.

Vaccine discovery against eukaryotic parasites is not trivial as highlighted by the limited number of known vaccines compared to the number of protozoal diseases that need one. Only three of 17 priority diseases have commercial vaccines. Live and attenuated vaccines have proved to be more effective than subunit vaccines but adversely pose more unacceptable risks. One promising approach for subunit vaccines is in silico vaccine discovery, which predicts protein vaccine candidates given thousands of target organism protein sequences. This approach, nonetheless, is an overarching concept with no standardised guidebook on implementation. No known subunit vaccines against protozoan parasites exist as a result of this approach, and consequently none to emulate. The study goal was to combine current in silico discovery knowledge specific to protozoan parasites and develop a workflow representing a state-of-the-art approach. This approach reflectively integrates a parasite's biology, a host's immune system defences, and importantly, bioinformatics programs needed to predict vaccine candidates. To demonstrate the workflow effectiveness, every Toxoplasma gondii protein was ranked in its capacity to provide long-term protective immunity. Although testing in animal models is required to validate these predictions, most of the top ranked candidates are supported by publications reinforcing our confidence in the approach.

Transcriptome and Genome Analysis Uncovers a DMD Structural Variant: A Case Report.

Objective: Duchenne muscular dystrophy (DMD) is caused by pathogenic variants in the dystrophin gene (DMD). Hypermethylated CGG expansions within DIP2B 5' UTR are associated with an intellectual development disorder. Here, we demonstrate the diagnostic utility of genomic short-read sequencing (SRS) and transcriptome sequencing to identify a novel DMD structural variant (SV) and a DIP2B CGG expansion in a patient with DMD for whom conventional diagnostic testing failed to yield a genetic diagnosis. Methods: We performed genomic SRS, skeletal muscle transcriptome sequencing, and targeted programmable long-read sequencing (LRS). Results: The proband had a typical DMD clinical presentation, autism spectrum disorder (ASD), and dystrophinopathy on muscle biopsy. Transcriptome analysis identified 6 aberrantly expressed genes; DMD and DIP2B were the strongest underexpression and overexpression outliers, respectively. Genomic SRS identified a 216 kb paracentric inversion (NC_000023.11: g.33162217-33378800) overlapping 2 DMD promoters. ExpansionHunter indicated an expansion of 109 CGG repeats within the 5' UTR of DIP2B. Targeted genomic LRS confirmed the SV and genotyped the DIP2B repeat expansion as 270 CGG repeats. Discussion: Here, transcriptome data heavily guided genomic analysis to resolve a complex DMD inversion and a DIP2B repeat expansion. Longitudinal follow-up will be important for clarifying the clinical significance of the DIP2B genotype.

A guide to current methodology and usage of reverse vaccinology towards in silico vaccine discovery.

Reverse vaccinology (RV) was described at its inception in 2000 as an in silico process that starts from the genomic sequence of the pathogen and ends with a list of potential protein and/or peptide candidates to be experimentally validated for vaccine development. Twenty-two years later, this process has evolved from a few steps entailing a handful of bioinformatics tools to a multitude of steps with a plethora of tools. Other in silico related processes with overlapping workflow steps have also emerged with terms such as subtractive proteomics, computational vaccinology, and immunoinformatics. From the perspective of a new RV practitioner, determining the appropriate workflow steps and bioinformatics tools can be a time consuming and overwhelming task, given the number of choices. This review presents the current understanding of RV and its usage in the research community as determined by a comprehensive survey of scientific papers published in the last seven years. We believe the current mainstream workflow steps and tools presented here will be a valuable guideline for all researchers wanting to apply an up-to-date in silico vaccine discovery process.

4D flow MRI in abdominal vessels: prospective comparison of k-t accelerated free breathing acquisition to standard respiratory navigator gated acquisition.

Volumetric phase-contrast magnetic resonance imaging with three-dimensional velocity encoding (4D flow MRI) has shown utility as a non-invasive tool to examine altered blood flow in chronic liver disease. Novel 4D flow MRI pulse sequences with spatio-temporal acceleration can mitigate the long acquisition times of standard 4D flow MRI, which are an impediment to clinical adoption. The purpose of our study was to demonstrate feasibility of a free-breathing, spatio-temporal (k-t) accelerated 4D flow MRI acquisition for flow quantification in abdominal vessels and to compare its image quality, flow quantification and inter-observer reproducibility with a standard respiratory navigator-gated 4D flow MRI acquisition. Ten prospectively enrolled patients (M/F: 7/3, mean age = 58y) with suspected portal hypertension underwent both 4D flow MRI acquisitions. The k-t accelerated acquisition was approximately three times faster (3:11 min ± 0:12 min/9:17 min ± 1:41 min, p < 0.001) than the standard respiratory-triggered acquisition. Vessel identification agreement was substantial between acquisitions and observers. Average flow had substantial inter-sequence agreement in the portal vein and aorta (CV < 15%) and poorer agreement in hepatic and splenic arteries (CV = 11-38%). The k-t accelerated acquisition recorded reduced velocities in small arteries and reduced splenic vein flow. Respiratory gating combined with increased acceleration and spatial resolution are needed to improve flow measurements in these vessels.

Performance of native and gadoxetate-enhanced liver and spleen T1 mapping for noninvasive diagnosis of clinically significant portal hypertension: preliminary results.

PURPOSE: In this preliminary study, our aim was to assess the utility of quantitative native-T1 (T1-pre), iron-corrected T1 (cT1) of the liver/spleen and T1 mapping of the liver obtained during hepatobiliary phase (T1-HBP) post-gadoxetate disodium, compared to spleen size/volume and APRI (aspartate aminotransferase-to-platelet ratio index) for noninvasive diagnosis of clinically significant portal hypertension [CSPH, defined as hepatic venous pressure gradient (HVPG) ≥ 10 mm Hg]. METHODS: Forty-nine patients (M/F: 27/22, mean age 53y) with chronic liver disease, HVPG measurement and MRI were included. Breath-held T1 and cT1 measurements were obtained using an inversion recovery Look-Locker sequence and a T2* corrected modified Look-Locker sequence, respectively. Liver T1-pre (n = 49), spleen T1 (obtained pre-contrast, n = 47), liver and spleen cT1 (both obtained pre-contrast, n = 30), liver T1-HBP (obtained 20 min post gadoxetate disodium injection, n = 36) and liver T1 uptake (ΔT1, n = 36) were measured. Spleen size/volume and APRI were also obtained. Spearman correlation coefficients were used to assess the correlation between each of liver/spleen T1/cT1 parameters, spleen size/volume and APRI with HVPG. ROC analysis was performed to determine the performance of measured parameters for diagnosis of CSPH. RESULTS: There were 12/49 (24%) patients with CSPH. Liver T1-pre (r = 0.287, p = 0.045), liver T1-HBP (r = 0.543, p = 0.001), liver ΔT1 (r = - 0.437, p = 0.008), spleen T1 (r = 0.311, p = 0.033) and APRI (r = 0.394, p = 0.005) were all significantly correlated with HVPG, while liver cT1, spleen cT1 and spleen size/volume were not. The highest AUCs for the diagnosis of CSPH were achieved with liver T1-HBP, liver ΔT1 and spleen T1: 0.881 (95%CI 0.76-1.0, p = 0.001), 0.852 (0.72-0.98, p = 0.002) and 0.781 (0.60-0.95, p = 0.004), respectively. CONCLUSION: Our preliminary results demonstrate the potential of liver T1 mapping obtained during HBP post gadoxetate disodium for the diagnosis of CSPH. These results require further validation.

The serotonin receptor 3E variant is a risk factor for female IBS-D.

Irritable bowel syndrome (IBS) is a gut-brain disorder of multifactorial origin. Evidence of disturbed serotonergic function in IBS accumulated for the 5-HT3 receptor family. 5-HT3Rs are encoded by HTR3 genes and control GI function, and peristalsis and secretion, in particular. Moreover, 5-HT3R antagonists are beneficial in the treatment of diarrhea predominant IBS (IBS-D). We previously reported on functionally relevant SNPs in HTR3A c.-42C > T (rs1062613), HTR3C p.N163K (rs6766410), and HTR3E c.*76G > A (rs56109847 = rs62625044) being associated with IBS-D, and the HTR3B variant p.Y129S (rs1176744) was also described within the context of IBS. We performed a multi-center study to validate previous results and provide further evidence for the relevance of HTR3 genes in IBS pathogenesis. Therefore, genotype data of 2682 IBS patients and 9650 controls from 14 cohorts (Chile, Germany (2), Greece, Ireland, Spain, Sweden (2), the UK (3), and the USA (3)) were taken into account. Subsequent meta-analysis confirmed HTR3E c.*76G > A (rs56109847 = rs62625044) to be associated with female IBS-D (OR = 1.58; 95% CI (1.18, 2.12)). Complementary expression studies of four GI regions (jejunum, ileum, colon, sigmoid colon) of 66 IBS patients and 42 controls revealed only HTR3E to be robustly expressed. On top, HTR3E transcript levels were significantly reduced in the sigma of IBS patients (p = 0.0187); more specifically, in those diagnosed with IBS-D (p = 0.0145). In conclusion, meta-analysis confirmed rs56109847 = rs62625044 as a risk factor for female IBS-D. Expression analysis revealed reduced HTR3E levels in the sigmoid colon of IBS-D patients, which underlines the relevance of HTR3E in the pathogenesis of IBS-D.

Experience of a systematic approach to care and prevention of fragility fractures in New Zealand.

This narrative review describes efforts to improve the care and prevention of fragility fractures in New Zealand from 2012 to 2022. This includes development of clinical standards and registries to benchmark provision of care, and public awareness campaigns to promote a life-course approach to bone health. PURPOSE: This review describes the development and implementation of a systematic approach to care and prevention for New Zealanders with fragility fractures, and those at high risk of first fracture. Progression of existing initiatives and introduction of new initiatives are proposed for the period 2022 to 2030. METHODS: In 2012, Osteoporosis New Zealand developed and published a strategy with objectives relating to people who sustain hip and other fragility fractures, those at high risk of first fragility fracture or falls and all older people. The strategy also advocated formation of a national fragility fracture alliance to expedite change. RESULTS: In 2017, a previously informal national alliance was formalised under the Live Stronger for Longer programme, which includes stakeholder organisations from relevant sectors, including government, healthcare professionals, charities and the health system. Outputs of this alliance include development of Australian and New Zealand clinical guidelines, clinical standards and quality indicators and a bi-national registry that underpins efforts to improve hip fracture care. All 22 hospitals in New Zealand that operate on hip fracture patients currently submit data to the registry. An analogous approach is ongoing to improve secondary fracture prevention for people who sustain fragility fractures at other sites through nationwide access to Fracture Liaison Services. CONCLUSION: Widespread participation in national registries is enabling benchmarking against clinical standards as a means to improve the care of hip and other fragility fractures in New Zealand. An ongoing quality improvement programme is focused on eliminating unwarranted variation in delivery of secondary fracture prevention.

Virtual reality for the observation of oncology models (VROOM): immersive analytics for oncology patient cohorts.

The significant advancement of inexpensive and portable virtual reality (VR) and augmented reality devices has re-energised the research in the immersive analytics field. The immersive environment is different from a traditional 2D display used to analyse 3D data as it provides a unified environment that supports immersion in a 3D scene, gestural interaction, haptic feedback and spatial audio. Genomic data analysis has been used in oncology to understand better the relationship between genetic profile, cancer type, and treatment option. This paper proposes a novel immersive analytics tool for cancer patient cohorts in a virtual reality environment, virtual reality to observe oncology data models. We utilise immersive technologies to analyse the gene expression and clinical data of a cohort of cancer patients. Various machine learning algorithms and visualisation methods have also been deployed in VR to enhance the data interrogation process. This is supported with established 2D visual analytics and graphical methods in bioinformatics, such as scatter plots, descriptive statistical information, linear regression, box plot and heatmap into our visualisation. Our approach allows the clinician to interrogate the information that is familiar and meaningful to them while providing them immersive analytics capabilities to make new discoveries toward personalised medicine.

Compilation of parasitic immunogenic proteins from 30 years of published research using machine learning and natural language processing.

The World Health Organisation reported in 2020 that six of the top 10 sources of death in low-income countries are parasites. Parasites are microorganisms in a relationship with a larger organism, the host. They acquire all benefits at the host's expense. A disease develops if the parasitic infection disrupts normal functioning of the host. This disruption can range from mild to severe, including death. Humans and livestock continue to be challenged by established and emerging infectious disease threats. Vaccination is the most efficient tool for preventing current and future threats. Immunogenic proteins sourced from the disease-causing parasite are worthwhile vaccine components (subunits) due to reliable safety and manufacturing capacity. Publications with 'subunit vaccine' in their title have accumulated to thousands over the last three decades. However, there are possibly thousands more reporting immunogenicity results without mentioning 'subunit' and/or 'vaccine'. The exact number is unclear given the non-standardised keywords in publications. The study aim is to identify parasite proteins that induce a protective response in an animal model as reported in the scientific literature within the last 30 years using machine learning and natural language processing. Source code to fulfil this aim and the vaccine candidate list obtained is made available.

MR elastography outperforms shear wave elastography for the diagnosis of clinically significant portal hypertension.

OBJECTIVES: Portal hypertension (PH) is associated with complications such as ascites and esophageal varices and is typically diagnosed through invasive hepatic venous pressure gradient (HVPG) measurement, which is not widely available. In this study, we aim to assess the diagnostic performance of 2D/3D MR elastography (MRE) and shear wave elastography (SWE) measures of liver and spleen stiffness (LS and SS) and spleen volume, to noninvasively diagnose clinically significant portal hypertension (CSPH) using HVPG measurement as the reference. METHODS: In this prospective study, patients with liver disease underwent 2D/3D MRE and SWE of the liver and spleen, as well as HVPG measurement. The correlation between MRE/SWE measures of LS/SS and spleen volume with HVPG was assessed. ROC analysis was used to determine the utility of MRE, SWE, and spleen volume for diagnosing CSPH. RESULTS: Thirty-six patients (M/F 22/14, mean age 55 ± 14 years) were included. Of the evaluated parameters, 3D MRE SS had the strongest correlation with HVPG (r = 0.686, p < 0.001), followed by 2D MRE SS (r = 0.476, p = 0.004). 3D MRE SS displayed the best performance for diagnosis of CSPH (AUC = 0.911) followed by 2D MRE SS (AUC = 0.845) and 3D MRE LS (AUC = 0.804). SWE SS showed poor performance for diagnosis of CSPH (AUC = 0.583) while spleen volume was a fair predictor (AUC = 0.738). 3D MRE SS was significantly superior to SWE LS/SS (p ≤ 0.021) for the diagnosis of CSPH. CONCLUSION: SS measured with 3D MRE outperforms SWE for the diagnosis of CSPH. SS appears to be a useful biomarker for assessing PH severity. These results need further validation. KEY POINTS: • Spleen stiffness measured with 2D and 3D MR elastography correlates significantly with hepatic venous pressure gradient measurement. • Spleen stiffness measured with 3D MR elastography demonstrates excellent performance for the diagnosis of clinically significant portal hypertension (AUC 0.911). • Spleen stiffness measured with 3D MR elastography outperforms liver and spleen stiffness measured with shear wave elastography for diagnosis of clinically significant portal hypertension.