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Constantinos Kallis,1– 3 Amit Kaura,1,3 Nathan A Samuel,4 Abdulrahim Mulla,3 Ben Glampson,3 Kevin O’Gallagher,5 Jim Davies,4 Dimitri Papadimitriou,3 Kerrie J Woods,4 Anoop D Shah,6,7 Bryan Williams,6,7 Folkert W Asselbergs,6,7 Erik K Mayer,3,8 Richard W Lee,1,9 Christopher Herbert,10 Stuart W Grant,11 Nick Curzen,12 Iain B Squire,13 Thomas Johnson,14 Ajay M Shah,15 Divaka Perera,5 Rajesh K Kharbanda,4 Riyaz S Patel,6 Keith M Channon,4 Jamil Mayet,1,3 Jennifer K Quint1– 3 1National Heart and Lung Institute, Imperial College London, London, UK; 2School of Public Health, Imperial College London, London, UK; 3NIHR Imperial Biomedical Research Centre, Imperial College London and Imperial College Healthcare NHS Trust, London, UK; 4NIHR Oxford Biomedical Research Centre, University of Oxford and Oxford University Hospitals NHS Foundation Trust, Oxford, UK; 5NIHR King’s Biomedical Research Centre, King’s College London and King’s College Hospital NHS Foundation Trust, London, UK; 6NIHR University College London Biomedical Research Centre, University College London and University College London Hospitals NHS Foundation Trust, London, UK; 7Institute of Health Informatics, University College London, London, UK; 8Imperial Clinical Analytics, Research & Evaluation (iCARE) and Department of Surgery & Cancer, Imperial College London, London, UK; 9Early Diagnosis and Detection Centre, NIHR BRC at The Royal Marsden and Institute of Cancer Research, London, UK; 10NIHR Leeds Clinical Research Facility, Leeds Teaching Hospitals Trust and University of Leeds, Leeds, UK; 11NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust and the University of Manchester, Manchester, UK; 12NIHR Southampton Clinical Research Facility and Biomedical Research Centre, Faculty of Medicine, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK; 13NIHR Leicester Biomedical Research Centre, Glenfield Hospital, and Department of Cardiovascular Sciences, University of Leicester, Leicester, UK; 14NIHR Bristol Biomedical Research Centre, University of Bristol and University Hospitals Bristol NHS Foundation Trust, Bristol, UK; 15NIHR Guys & St Thomas’ Hospital Clinical Research Facility, King’s College Hospital, and King’s College London British Heart Foundation Centre of Excellence, London, UKCorrespondence: Jennifer K Quint, School of Public Health, Imperial College London, Floor 9, Sir Michael Uren Building, 86 Wood Ln, London, W12 0BZ, United Kingdom, Email j.quint@imperial.ac.ukBackground: No single biomarker currently risk stratifies chronic obstructive pulmonary disease (COPD) patients at the time of an exacerbation, though previous studies have suggested that patients with elevated troponin at exacerbation have worse outcomes. This study evaluated the relationship between peak cardiac troponin and subsequent major adverse cardiac events (MACE) including all-cause mortality and COPD hospital readmission, among patients admitted with COPD exacerbation.Methods: Data from five cross-regional hospitals in England were analysed using the National Institute of Health Research Health Informatics Collaborative (NIHR-HIC) acute coronary syndrome database (2008– 2017). People hospitalised with a COPD exacerbation were included, and peak troponin levels were standardised relative to the 99th percentile (upper limit of normal). We used Cox Proportional Hazard models adjusting for age, sex, laboratory results and clinical risk factors, and implemented logarithmic transformation (base-10 logarithm). The primary outcome was risk of MACE within 90 days from peak troponin measurement. Secondary outcome was risk of COPD readmission within 90 days from peak troponin measurement.Results: There were 2487 patients included. Of these, 377 (15.2%) patients had a MACE event and 203 (8.2%) were readmitted within 90 days from peak troponin measurement. A total of 1107 (44.5%) patients had an elevated troponin level. Of 1107 patients with elevated troponin at exacerbation, 256 (22.8%) had a MACE event and 101 (9.0%) a COPD readmission within 90 days from peak troponin measurement. Patients with troponin above the upper limit of normal had a higher risk of MACE (adjusted HR 2.20, 95% CI 1.75– 2.77) and COPD hospital readmission (adjusted HR 1.37, 95% CI 1.02– 1.83) when compared with patients without elevated troponin.Conclusion: An elevated troponin level at the time of COPD exacerbation may be a useful tool for predicting MACE in COPD patients. The relationship between degree of troponin elevation and risk of future events is complex and requires further investigation.Keywords: COPD, CVD, exacerbation

Robert J Barry,1 Quan Dong Nguyen,2 Richard W Lee,3 Philip I Murray,1 Alastair K Denniston1,4 1Academic Unit of Ophthalmology, Centre for Translational Inflammation, Research, University of Birmingham, UK; 2Stanley M Truhlsen Eye Institute, University of Nebraska Medical Center, Omaha, NE, USA; 3Inflammation and Immunotherapy Theme, National Institute for Health Research (NIHR) Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK; 4Department of Ophthalmology, Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation trust, Birmingham, UK Abstract: Uveitis, a group of conditions characterized by intraocular inflammation, is a major cause of sight loss in the working population. Most uveitis seen in Western countries is noninfectious and appears to be autoimmune or autoinflammatory in nature, requiring treatment with immunosuppressive and/or anti-inflammatory drugs. In this educational review, we outline the ideal characteristics of drugs for uveitis and review the data to support the use of current and emerging therapies in this context. It is crucial that we continue to develop new therapies for use in uveitis that aim to suppress disease activity, prevent accumulation of damage, and preserve visual function for patients with the minimum possible side effects. Keywords: clinical trials, immunomodulatory therapeutic agents, immunosuppression, inflammation, uvea

John J Kim,1,2 Nathan Buchbinder,1,† Simon Ammanuel,1,4,5,† Robert Kim,1,† Erika Moore,1 Neil O'Donnell,1 Jennifer K Lee,3 Ewa Kulikowicz,3 Soumyadipta Acharya,1 Robert H Allen,1,9 Ryan W Lee,6,7 Michael V Johnston4–81Department of Biomedical Engineering, Whiting School of Engineering, The Johns Hopkins University, 2The James Buchanan Brady Urological Institute, Department of Urology, The Johns Hopkins University School of Medicine, 3Department of Anesthesia and Critical Care Medicine, Johns Hopkins University, 4Kennedy Krieger Institute, 5Hugo W Moser Research Institute, 6Department of Neurology, 7Department of Pediatrics, 8Department of Physical Medicine and Rehabilitation Johns Hopkins University School of Medicine, Baltimore, MD; 9Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA†These authors contributed equally to this workAbstract: Despite recent advances in neonatal care and monitoring, asphyxia globally accounts for 23% of the 4 million annual deaths of newborns, and leads to hypoxic-ischemic encephalopathy (HIE). Occurring in five of 1000 live-born infants globally and even more in developing countries, HIE is a serious problem that causes death in 25%–50% of affected neonates and neurological disability to at least 25% of survivors. In order to prevent the damage caused by HIE, our invention provides an effective whole-body cooling of the neonates by utilizing evaporation and an endothermic reaction. Our device is composed of basic electronics, clay pots, sand, and urea-based instant cold pack powder. A larger clay pot, lined with nearly 5 cm of sand, contains a smaller pot, where the neonate will be placed for therapeutic treatment. When the sand is mixed with instant cold pack urea powder and wetted with water, the device can extract heat from inside to outside and maintain the inner pot at 17°C for more than 24 hours with monitoring by LED lights and thermistors. Using a piglet model, we confirmed that our device fits the specific parameters of therapeutic hypothermia, lowering the body temperature to 33.5°C with a 1°C margin of error. After the therapeutic hypothermia treatment, warming is regulated by adjusting the amount of water added and the location of baby inside the device. Our invention uniquely limits the amount of electricity required to power and operate the device compared with current expensive and high-tech devices available in the United States. Our device costs a maximum of 40 dollars and is simple enough to be used in neonatal intensive care units in developing countries.Keywords: therapeutic hypothermia, evaporative cooling, hypoxic ischemic encephalopathy, birth asphyxia, neuroprotection

Theory predicts that, with an ultrashort and extremely bright coherent X-ray pulse, a single diffraction pattern may be recorded from a large macromolecule, a virus or a cell before the sample explodes and turns into a plasma. Here we report the first experimental demonstration of this principle using the FLASH soft-X-ray free-electron laser. An intense 25 fs, 4×10 13 W cm -2 pulse, containing 10 12 photons at 32 nm wavelength, produced a coherent diffraction pattern from a nanostructured non-periodic object, before destroying it at 60,000 K. A novel X-ray camera assured single-photon detection sensitivity by filtering out parasitic scattering and plasma radiation. The reconstructed image, obtained directly from the coherent pattern by phase retrieval through oversampling, shows no measurable damage, and is reconstructed at the diffraction-limited resolution. A three-dimensional data set may be assembled from such images when copies of a reproducible sample are exposed to the beam one by one. © 2006 Nature Publishing Group.

The blockbuster drug paradigm is under increasing scrutiny across the biopharmaceutical industry. Intraocular inflammation poses particular challenges to this, given the heterogeneity of conditions in the uveitis spectrum, and the increasing acknowledgement of individual patient and disease variance in underlying immune responses. This need has triggered a drive towards personalised and stratified medicine, supported and enabled as a result of continued development of both experimental models and molecular biological techniques and improved clinical classification. As such we have the ability now to systematically appraise at a genomic, transcriptomic, and proteomic level individual immunophenotype, and the promise that in the eye this can be augmented by in vivo immune imaging to identify individual immunopathology. With such advances all running in parallel, we are entering an era of experimental medicine that will facilitate early diagnosis, generate biomarkers for accurate prognostication, and enable the development of individualised and targeted therapies, which can progress rapidly into clinical practice. [ABSTRACT FROM AUTHOR]

The rapid expansion in the therapeutic modalities available for the treatment of anti-neutrophil cytoplasmic antibody-associated vasculitides (AAV), with clear limitations in existing strategies, prompted us to undertake a review of novel therapies reported in MEDLINE and EMBASE. Tumour necrosis factor (TNF)-alpha antagonism with infliximab is described favourably in retrospective series and open-label trials. However, evidence from the WGET (Wegener's Granulomatosis Etanercept Trial) does not support the clinical use of etanercept, and a significantly higher malignancy rate following TNFalpha inhibition questions the role of this approach. Uncontrolled evidence alone supports remission induction with rituximab-mediated B-lymphocyte depletion and may be less effective in predominantly granulomatous AAV. Remission following T-lymphocyte depletion can be achieved with alemtuzumab and antithymocyte globulin, but it is not yet clear what the clinical role will be for these agents in AAV. In addition, these agents are associated with prolonged lymphopenia and pulmonary complications, respectively. Stem cell transplantation to support immune reconstitution following the use of such agents has been trialled in AAV, but studies included very few patients. Purine and pyrimidine antimetabolites mycophenolate mofetil and leflunomide are likely to play an important role in the treatment of AAV, but results supporting remission maintenance and induction in the former are limited to uncontrolled trials, such that their use remains experimental at this time. Similarly, 15-deoxyspergualin may provide an alternative to cyclophosphamide but awaits randomized controlled trial evidence. The MEPEX (MEthylprednisolone versus Plasma EXchange) trial supports plasma exchange in renal disease but this may be limited by pulmonary complications. Randomized controlled evidence also exists for intravenous immunoglobulin, although improvement may not be sustained. Antimicrobial therapy may be of use in Wegener's granulomatosis patients with predominantly upper respiratory tract involvement. Safety concerns, notably of infection and malignancy, were common and need to be explored in subsequent trials. In addition, concomitant immunosuppressants and non-standardized definitions were major limitations, and future studies of these and newer agents must follow agreed standards of study design and reporting to facilitate clearer interpretation of the circumstances (e.g. disease stage, severity or organ involvement) under which these agents perform optimally. Consequently, use is still limited to centres experienced in such agents and mostly in the context of clinical trials. [ABSTRACT FROM AUTHOR]

Swallow syncope is a rare disorder caused by hypersensitive vagotonic reflex in response to deglutition. A 26-year-old man complained of recurrent light-headedness and near syncope on swallowing was hospitalized for monitoring and evaluation. Continuous electrocardiographic and invasive arterial pressure monitoring showed ingestion of a solid meal evoked light-headedness and complete AV block without an escape rhythm that lasted for 5.6 seconds. This patient received a Medtronic Kappa (401B) DDDR pacemaker with the rate drop feature. The patient has remained asymptomatic on follow-up for the past 2 years. [ABSTRACT FROM AUTHOR]

Background: Medical management of thyroid eye disease remains controversial due to a paucity of high quality evidence on long-term treatment outcomes. Glucocorticoids are known to be effective initially but have significant side-effects with long-term use and recrudescence can occur on cessation. Current evidence is conflicting on the efficacy of radiotherapy and non-steroid systemic immunosuppression, and the majority of previous studies have been retrospective, uncontrolled, small or poorly designed.The Combined Immunosuppression and Radiotherapy in Thyroid Eye Disease (CIRTED) trial was designed to investigate the efficacy of radiotherapy and azathioprine in combination with a standard course of oral prednisolone in patients with active thyroid eye disease.Methods/design: Patients with active thyroid eye disease will be randomised to receive (i) azathioprine or oral placebo and (ii) radiotherapy or sham-radiotherapy in this multi-centre, factorial randomised control trial. The primary outcome is improvement in disease severity (assessed using a composite binary measure) at 12 months and secondary end-points include quality of life scores and health economic measures.Discussion: The CIRTED trial is the first study to evaluate the role of radiotherapy and azathioprine as part of a long-term, combination immunosuppressive treatment regime for Thyroid Eye Disease. It will provide evidence for the role of radiotherapy and prolonged immunosuppression in the management of this condition, as well as pilot data on their use in combination. We have paid particular attention in the trial design to establishing (a) robust placebo controls and masking protocols which are effective and safe for both radiotherapy and the systemic administration of an antiproliferative drug; (b) constructing effective inclusion and exclusion criteria to select for active disease; and (c) selecting pragmatic outcome measures.Trial Registration: Current controlled trials ISRCTN22471573. [ABSTRACT FROM AUTHOR]

Introduction: Ultrasound equipment provides real-time visualization of internal organs, essential for early disease detection and diagnosis. However, poor-quality ultrasound images can compromise diagnostic accuracy and increase the risk of misdiagnosis. Quality assessments are often subjective, relying on the evaluator's experience and interpretation, which can vary., Methods: This study introduces a two-stage deep learning framework designed to objectively assess ultrasound image quality using phantom data across three key parameters: 'Dead zone', 'Axial/lateral resolution', and 'Gray scale and dynamic range'. Stage 1 automatically extracts regions of interest for each parameter, while Stage 2 employs detection or classification models to evaluate image quality within these regions. To generate an overall equipment quality score, a logistic regression model combines the weighted results from each parameter., Results: The classification model demonstrated high performance across datasets, achieving AUC scores of 98.6% for 'Dead zone', 87.7% for 'Axial/lateral resolution', and 96.0% for 'Gray scale and dynamic range'. Further analysis using guideline-compliant images of individual devices showed AUC scores of 98.2%, 92.8%, and 100%, respectively. These findings highlight deep learning's potential for quantitative and objective assessments of ultrasound image quality. Ultimately, this framework provides a streamlined approach to quality management, enabling consistent quality control and efficient scoring-based evaluation of ultrasound equipment., Competing Interests: Declaration of Competing Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Aims: Lipoprotein(a) [Lp(a)] has demonstrated its association with atherosclerosis and myocardial infarction. However, its role in the development of in-stent restenosis (ISR) after percutaneous coronary intervention (PCI) is not clearly established. The aim of this study is to investigate the association between Lp(a) and ISR., Methods and Results: A retrospective study of adult patients who underwent successful PCI between January 2006 and December 2017 at the three Mayo Clinic sites and had a preprocedural Lp(a) measurement was conducted. Patients were divided into two groups according to the serum Lp(a) concentration [high Lp(a) ≥ 50 mg/dL and low Lp(a) < 50 mg/dL]. Univariable and multivariable analyses were performed to compare risk of ISR between patients with high Lp(a) vs. those with low Lp(a). A total of 1209 patients were included, with mean age 65.9 ± 11.7 years and 71.8% were male. Median follow-up after baseline PCI was 8.8 [interquartile range (IQR) 7.4] years. Restenosis was observed in 162 (13.4%) patients. Median serum levels of Lp(a) were significantly higher in patients affected by ISR vs. non-affected cases: 27 (IQR 73.8) vs. 20 (IQR 57.5) mg/dL, P = 0.008. The rate of ISR was significantly higher among patients with high Lp(a) vs. patients with low Lp(a) values (17.0% vs. 11.6%, P = 0.010). High Lp(a) values were independently associated with ISR events (hazard ratio 1.67, 95% confidence interval 1.18-2.37, P = 0.004), and this association was more prominent after the first year following the PCI., Conclusion: Lipoprotein(a) is an independent predictor for long-term ISR and should be considered in the evaluation of patients undergoing PCI., Competing Interests: Conflict of interest: none declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Knee osteoarthritis (OA) is a prevalent degenerative joint disease significantly impacting global health. Early and accurate diagnosis is crucial for effective management, but traditional methods often rely on subjective assessments. This study evaluates the efficacy of a deep learning model implemented through a no-code AI platform for diagnosing and grading knee OA from plain radiographs. Methods: We utilized the Osteoarthritis Initiative (OAI) dataset, comprising knee X-ray data from 1526 patients. The data were split into training (47.0%), validation (26.5%), and test (26.5%) sets. We employed a ResNet101 model on the DEEP:PHI no-code AI platform for image analysis. The model was trained to classify knee OA into five grades (0-4) based on the Kellgren-Lawrence scale. Results: Our AI model demonstrated high accuracy in distinguishing between different OA grades, with particular strength in early-stage detection. The model achieved optimal performance at 20 epochs, suggesting efficient learning dynamics. Grad-CAM visualizations were used to enhance the interpretability of the model's decision-making process. Conclusions: This study demonstrates the potential of AI, implemented through a no-code platform, to accurately diagnose and grade knee OA from radiographs. The use of a no-code AI platform such as DEEP:PHI represents a step towards democratizing AI in healthcare, enabling the rapid development and deployment of sophisticated medical AI applications without extensive coding expertise. This approach could significantly enhance the early detection and management of knee OA, potentially improving patient outcomes and streamlining clinical workflows.

Background: Tangeretin, a natural polymethoxyflavone compound, possesses potent anti-inflammatory activity that improves respiratory inflammation in chronic obstructive pulmonary disease (COPD). However, the molecular mechanisms underlying the anti-COPD effects of tangeretin remain unclear. In this study, we aimed to investigate the key molecular mechanisms by which tangeretin suppresses COPD-related inflammatory responses., Methods: We conducted the investigation in phorbol-12-myristate-13-acetate (PMA)-stimulated human airway epithelial cells ( in vitro ) and cigarette smoke (CS)/lipopolysaccharide (LPS)-exposed mice ( in vivo )., Results: Tangeretin decreased the release of inflammatory mediators, including tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and mucin 5AC (MUC5AC), by suppressing early growth response 1 (EGR1) expression in vitro . Tangeretin and EGR1 small interfering ribonucleic acid (siRNA) combination showed a synergistic reduction in MUC5AC and TNF-α secretion. Tangeretin administration significantly inhibited the levels of reactive oxygen species (ROS) production, elastase activity, TNF-α, IL-6, and monocyte chemoattractant protein-1 (MCP-1) secretion, and macrophage and neutrophil numbers in the bronchoalveolar lavage fluid of CS/LPS-exposed mice. Tangeretin also prevented CS/LPS-induced abnormal pathological changes and excessive MUC5AC and EGR1 expression in lung tissue., Conclusion: Comprehensively, tangeretin inhibits the lung inflammatory response associated with COPD by reducing EGR1 expression in PMA-induced human epithelial cells and in a CS/LPS-stimulated mouse model. This study shows that tangeretin has anti-COPD properties and can be a promising alternative (or complementary) treatment for inflammatory lung disease., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Background: Kidney biopsy is the standard of care for the diagnosis of various kidney diseases. In particular, chronic histopathologic lesions, such as interstitial fibrosis and tubular atrophy, can provide prognostic information regarding chronic kidney disease progression. In this study, we aimed to evaluate historadiological correlations between CT-based radiomic features and chronic histologic changes in native kidney biopsies and to construct and validate a radiomics-based prediction model for chronicity grade., Methods: We included patients aged ≥ 18 years who underwent kidney biopsy and abdominal CT scan within a week before kidney biopsy. Left kidneys were three-dimensionally segmented using a deep learning model based on the 3D Swin UNEt Transformers architecture. We additionally defined isovolumic cortical regions of interest near the lower pole of the left kidneys. Shape, first-order, and high-order texture features were extracted after resampling and kernel normalization. Correlations and diagnostic metrics between extracted features and chronic histologic lesions were examined. A machine learning-based radiomic prediction model for moderate chronicity was developed and compared according to the segmented regions of interest (ROI)., Results: Overall, moderate correlations with statistical significance (P < 0.05) were found between chronic histopathologic grade and top-ranked radiomic features. Total parenchymal features were more strongly correlated than cortical ROI features, and texture features were more highly ranked. However, conventional imaging markers, including kidney length, were poorly correlated. Top-ranked individual radiomic features had areas under receiver operating characteristic curves (AUCs) of 0.65 to 0.74. Developed radiomics models for moderate-to-severe chronicity achieved AUCs of 0.89 (95% confidence interval [CI] 0.75-0.99) and 0.74 (95% CI 0.52-0.93) for total parenchymal and cortical ROI features, respectively., Conclusion: Significant historadiological correlations were identified between CT-based radiomic features and chronic histologic changes in native kidney biopsies. Our findings underscore the potential of CT-based radiomic features and their prediction model for the non-invasive assessment of kidney fibrosis., (© 2024. The Author(s).)

Background: The collaboration between pharmacists and veterinarians plays a crucial role in ensuring optimal animal healthcare. Understanding the willingness of veterinarians to collaborate with pharmacists and analyzing the prescribing trends by veterinarians are essential factors in improving the quality of veterinary care. By analyzing these aspects, valuable insights can be gained to enhance interprofessional collaboration and optimize medication management in veterinary practice., Objectives: To examine the willingness of veterinarians towards interprofessional collaboration with community pharmacist., Methods: A cross-sectional study was conducted among 40 veterinary clinics in Klang Valley, Malaysia. Data was collected via online using Google Forms from registered veterinarians working in private veterinary clinics in Klang Valley, Malaysia. Descriptive statistics and statistical analysis were performed using SPSS version 27., Results: The overall willingness of veterinarians to collaborate with community pharmacists was measured with a median score of 51 out of 75. The results indicated that 55 % of veterinarians demonstrated high willingness to collaborate. Specifically, 52.5 % of veterinarians had a positive attitude towards collaboration, 55 % recognized the roles of pharmacists positively, and 57.5 % identified barriers to collaboration. These findings highlight a generally positive inclination towards interprofessional collaboration among veterinarians., Conclusion: More veterinarians demonstrated a positive willingness to collaborate with pharmacists for optimal patient care. However, several constraints were identified, including a lack of face-to-face communication, concerns about pharmacists' knowledge or skills in veterinary medicine, and financial interests. Addressing these issues could further enhance collaboration between veterinarians and pharmacist., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Background: In Alzheimer's disease (AD), microglia surround extracellular plaques and mount a sustained inflammatory response, contributing to the pathogenesis of the disease. Identifying approaches to specifically target plaque-associated microglia (PAMs) without interfering in the homeostatic functions of non-plaque associated microglia would afford a powerful tool and potential therapeutic avenue., Methods: Here, we demonstrated that a systemically administered nanomedicine, hydroxyl dendrimers (HDs), can cross the blood brain barrier and are preferentially taken up by PAMs in a mouse model of AD. As proof of principle, to demonstrate biological effects in PAM function, we treated the 5xFAD mouse model of amyloidosis for 4 weeks via systemic administration (ip, 2x weekly) of HDs conjugated to a colony stimulating factor-1 receptor (CSF1R) inhibitor (D-45113)., Results: Treatment resulted in significant reductions in amyloid-beta (Aβ) and a stark reduction in the number of microglia and microglia-plaque association in the subiculum and somatosensory cortex, as well as a downregulation in microglial, inflammatory, and synaptic gene expression compared to vehicle treated 5xFAD mice., Conclusions: This study demonstrates that systemic administration of a dendranib may be utilized to target and modulate PAMs., (© 2024. The Author(s).)

This study aimed to investigate the dimensions and types of the os trigonum and evaluate their relationship with various pathologic conditions on the posterior ankle using ankle MRI images. A total of 124 non-contrast-enhanced ankle and foot MR images of 123 consecutive patients were included in this retrospective study. The images were presented randomly, and they contained no patient information. The MR images were retrospectively and independently reviewed by two reviewers with a fellowship-trained musculoskeletal radiologist. The images were classified as type I and II based on the ossicle's medial border overlying the talus's posterior process and the groove for the flexor hallucis longus tendon (FHL). The study revealed that patients with type II os trigonum had a longer transverse diameter of the ossicle than type I, and there were statistically significant differences. Detachment status tended to be less in type I than in type II os trigonum, and the differences between the groups were statistically significant. There were no significant differences between type I and II os trigonum regarding posterior talofibular ligament (PTFL) abnormality, bone marrow edema, FHL tenosynovitis, and posterior synovitis. The study concluded that the os trigonum is a common cause of posterior ankle impingement, and type II os trigonum has a longer transverse diameter of the ossicle than type I.

Our study aimed to assess the accuracy and limitations of ChatGPT in the domain of MRI, focused on evaluating ChatGPT's performance in answering simple knowledge questions and specialized multiple-choice questions related to MRI. A two-step approach was used to evaluate ChatGPT. In the first step, 50 simple MRI-related questions were asked, and ChatGPT's answers were categorized as correct, partially correct, or incorrect by independent researchers. In the second step, 75 multiple-choice questions covering various MRI topics were posed, and the answers were similarly categorized. The study utilized Cohen's kappa coefficient for assessing interobserver agreement. ChatGPT demonstrated high accuracy in answering straightforward MRI questions, with over 85% classified as correct. However, its performance varied significantly across multiple-choice questions, with accuracy rates ranging from 40% to 66.7%, depending on the topic. This indicated a notable gap in its ability to handle more complex, specialized questions requiring deeper understanding and context. In conclusion, this study critically evaluates the accuracy of ChatGPT in addressing questions related to Magnetic Resonance Imaging (MRI), highlighting its potential and limitations in the healthcare sector, particularly in radiology. Our findings demonstrate that ChatGPT, while proficient in responding to straightforward MRI-related questions, exhibits variability in its ability to accurately answer complex multiple-choice questions that require more profound, specialized knowledge of MRI. This discrepancy underscores the nuanced role AI can play in medical education and healthcare decision-making, necessitating a balanced approach to its application.

This study evaluates the diagnostic accuracy and clinical utility of two artificial intelligence (AI) techniques: Kakao Brain Artificial Neural Network for Chest X-ray Reading (KARA-CXR), an assistive technology developed using large-scale AI and large language models (LLMs), and ChatGPT, a well-known LLM. The study was conducted to validate the performance of the two technologies in chest X-ray reading and explore their potential applications in the medical imaging diagnosis domain. The study methodology consisted of randomly selecting 2000 chest X-ray images from a single institution's patient database, and two radiologists evaluated the readings provided by KARA-CXR and ChatGPT. The study used five qualitative factors to evaluate the readings generated by each model: accuracy, false findings, location inaccuracies, count inaccuracies, and hallucinations. Statistical analysis showed that KARA-CXR achieved significantly higher diagnostic accuracy compared to ChatGPT. In the 'Acceptable' accuracy category, KARA-CXR was rated at 70.50% and 68.00% by two observers, while ChatGPT achieved 40.50% and 47.00%. Interobserver agreement was moderate for both systems, with KARA at 0.74 and GPT4 at 0.73. For 'False Findings', KARA-CXR scored 68.00% and 68.50%, while ChatGPT scored 37.00% for both observers, with high interobserver agreements of 0.96 for KARA and 0.97 for GPT4. In 'Location Inaccuracy' and 'Hallucinations', KARA-CXR outperformed ChatGPT with significant margins. KARA-CXR demonstrated a non-hallucination rate of 75%, which is significantly higher than ChatGPT's 38%. The interobserver agreement was high for KARA (0.91) and moderate to high for GPT4 (0.85) in the hallucination category. In conclusion, this study demonstrates the potential of AI and large-scale language models in medical imaging and diagnostics. It also shows that in the chest X-ray domain, KARA-CXR has relatively higher accuracy than ChatGPT.