A clinically compatible in vitro drug-screening platform identifies therapeutic vulnerabilities in primary cultures of brain metastases.

PURPOSE: Brain metastases represent the most common intracranial tumors in adults and are associated with a poor prognosis. We used a personalized in vitro drug screening approach to characterize individual therapeutic vulnerabilities in brain metastases. METHODS: Short-term cultures of cancer cells isolated from brain metastasis patients were molecularly characterized using next-generation sequencing and functionally evaluated using high-throughput in vitro drug screening to characterize pharmacological treatment sensitivities. RESULTS: Next-generation sequencing identified matched genetic alterations in brain metastasis tissue samples and corresponding short-term cultures, suggesting that short-term cultures of brain metastases are suitable models for recapitulating the genetic profile of brain metastases that may determine their sensitivity to anti-cancer drugs. Employing a high-throughput in vitro drug screening platform, we successfully screened the cultures of five brain metastases for response to 267 anticancer compounds and related drug response to genetic data. Among others, we found that targeted treatment with JAK3, HER2, or FGFR3 inhibitors showed anti-cancer effects in individual brain metastasis cultures. CONCLUSION: Our preclinical study provides a proof-of-concept for combining molecular profiling with in vitro drug screening for predictive evaluation of therapeutic vulnerabilities in brain metastasis patients. This approach could advance the use of patient-derived cancer cells in clinical practice and might eventually facilitate decision-making for personalized drug treatment.

Potential biomarkers for multiple sclerosis stage from targeted proteomics and microRNA sequencing.

Multiple sclerosis is a chronic demyelinating disease of the central nervous system. There is a need for new circulating biomarkers for multiple sclerosis, in particular, markers that differentiate multiple sclerosis subtypes (relapsing-remitting, secondary progressive and primary progressive multiple sclerosis), as this can help in making treatment decisions. In this study, we explore two classes of potential multiple sclerosis biomarkers-proteins and microRNAs-circulating in the cerebrospinal fluid and serum. Targeted medium-throughput proteomics (92 proteins) and microRNA sequencing were performed on serum samples collected in a cross-sectional case-control cohort (cohort I, controls n = 30, multiple sclerosis n = 75) and a prospective multiple sclerosis cohort (cohort II, n = 93). For cohort I, we also made these measurements in paired cerebrospinal fluid samples. In the cohort I cerebrospinal fluid, we observed differences between multiple sclerosis and controls for 13 proteins, including some previously described to be markers for multiple sclerosis [e.g. CD27, C-X-C motif chemokine 13 (CXCL13) and interleukin-7 (IL7)]. No microRNAs were significantly differentially expressed between multiple sclerosis and controls in the cerebrospinal fluid. In serum, 10 proteins, including angiopoietin-1 receptor (TIE2), and 16 microRNAs were significantly different between relapsing-remitting multiple sclerosis and secondary progressive multiple sclerosis after performing a meta-analysis combining both cohorts. In the prospective part of the study, participants with relapsing-remitting multiple sclerosis were followed for around 3 years, during which time 12 participants converted to secondary progressive multiple sclerosis. In these longitudinally collected serum samples, we observed a peak in granzyme B, A and H proteins around the time of conversion. Single-sample enrichment analysis of serum microRNA profiles revealed that the peak in granzyme B levels around conversion coincides with enrichment for microRNAs that are enriched in CD4+, CD8+ and natural killer cells (e.g. miRNA-150). We identified several proteins and microRNAs in serum that represent potential biomarkers for relapsing-remitting and secondary progressive multiple sclerosis. Conversion to secondary progressive disease is marked by a peak in granzyme B levels and enrichment for immune-related microRNAs. This indicates that specific immune cell-driven processes may contribute to the conversion of relapsing-remitting multiple sclerosis to secondary progressive multiple sclerosis.

Preparation and evaluation of functional cocoa-free spread alternatives from different sources.

Spread products have an important market share as they have high nutritional value and they are increasingly consumed, especially by children as a source of energy. The purpose of this work was to evaluate the potential use of powdered chickpea, black rice, carob, doum, date seeds, and beetroot to produce novel functional spreadable products as cocoa-free alternatives. Additionally, to avoid the side effects of cocoa-based products and to assess the cocoa replacement effects on the sensory properties, chemical composition, texture analysis, viscosity, antioxidant, peroxide stability, and microbial quality during storage periods were compared to the ones of cocoa spread. Sensory evaluation revealed that most formulated spreads were accepted as chocolate spread alternatives since there was no significant difference in overall acceptability among cocoa, chickpea, black rice, carob, and doum, while date seeds and beetroot spreads were significantly less acceptable. A variation was observed in the proximate chemical analysis of the produced functional spreads, as the alternative spreads had different characteristics to each other in their physicochemical, texture, and rheological properties. Results indicated a wide variation in the total phenolic content (TPC) of the different spread extracts. The highest amount of TPC was obtained for beetroot spread (455.84 mg GAE/100 g) followed by black rice spread (436.08 mg GAE/100 g). The obtained results indicated that the antioxidant activity of different spreads was significantly different (p < .05) while based on their microbiological analysis, they could have a shelf life of up to 9 months. According to the results, chickpea, carob, doum, black rice, date seeds, and beetroot powders could be used for the production of cocoa-free alternatives as they were highly acceptable and they showed antioxidant and antimicrobial activity.

The Loss of Estradiol by Androgen Deprivation in Prostate Cancer Patients Shows the Importance of Estrogens in Males.

The role of estradiol (E2; an estrogen) in men needs to be more appreciated. In this review, we address the clinical situations that allow the study of the clinical consequences of E2 deficiency in men and discuss the effects of restoration of levels of this reproductive steroid hormone. In men with advanced prostate cancer (PCa) undergoing androgen deprivation therapy (ADT), E2 is suppressed along with testosterone, leading to side effects affecting the quality of life. These include hot flashes, arthralgia, fatigue, mood changes, cognition problems, weight gain, bone loss, and increased risk of cardiovascular disease. Transdermal E2 alone for ADT has shown equivalent testosterone suppression compared to gonadotropin-releasing hormone (GnRH) agonists while also preventing estrogen-deficiency side effects, including hot flashes and bone loss. Co-treatment of ADT with fetal estrogen estetrol (E4) has shown significant improvements of estrogen-deficiency symptoms. These observations emphasize the need to raise awareness of the importance of estrogens in men among clinicians and the lay public.

Type 1 Myocardial Infarction in Patients With Acute Ischemic Stroke.

Importance: Elevated values of high-sensitivity cardiac troponin (hs-cTn) are common in patients with acute ischemic stroke and are associated with poor prognosis. However, diagnostic and therapeutic implications in patients with ischemic stroke remain unclear. Objective: To identify factors indicative of myocardial infarction (MI) in patients with acute ischemic stroke and hs-cTn elevation. The primary hypothesis was that a dynamic change of hs-cTn values (>50% change) in patients with acute ischemic stroke indicates MI. Design, Setting, and Participants: This cross-sectional study was a prospective, observational study with blinded end-point assessment conducted across 26 sites in Germany. Patients were included if they had acute ischemic stroke within 72 hours and either (1) highly elevated hs-cTn values on admission (>52 ng/L) or (2) hs-cTn levels above the upper limit of normal and a greater than 20% change at repeated measurements. Patients were enrolled between August 2018 and October 2020 and had 1 year of follow-up. Statistical analysis was performed between April 2022 and August 2023. Exposure: Standardized electrocardiography, echocardiography, and coronary angiography. Main Outcome and Measures: Diagnosis of MI as adjudicated by an independent end-point committee based on the findings of electrocardiography, echocardiography, and coronary angiography. Results: In total, 254 patients were included. End points were adjudicated in 247 patients (median [IQR] age, 75 [66-82] years; 117 were female [47%] and 130 male [53%]). MI was present in 126 of 247 patients (51%) and classified as type 1 MI in 50 patients (20%). Dynamic change in hs-cTn value was not associated with MI in univariable (32% vs 38%; χ2 P = .30) or adjusted comparison (odds ratio, 1.05; 95% CI, 0.31-3.33). The baseline absolute hs-cTn value was independently associated with type 1 MI. The best cutoffs for predicting type 1 MI were at hs-cTn values 5 to 10 times the upper limit normal. Conclusions and Relevance: This study found that in patients with acute ischemic stroke, a dynamic change in hs-cTn values did not identify MI, underscoring that dynamic changes do not identify the underlying pathophysiological mechanism. In exploratory analyses, very high absolute hs-cTn values were associated with a diagnosis of type 1 MI. Further studies are needed how to best identify patients with stroke who should undergo coronary angiography.

Protocol for the MS-CEBA study: an observational, prospective cohort study identifying Cognitive, Energetic, Behavioural and Affective (CEBA) profiles in Multiple Sclerosis to guide neuropsychological treatment choice.

BACKGROUND: Neuropsychological symptoms in the Cognitive, Energetic, Behavioural, and Affective (CEBA) domains are common in people with multiple sclerosis (PwMS) and can negatively affect societal participation. The current study aims to investigate whether there are combinations of symptoms in the different CEBA domains that consistently occur together, that is, if there are CEBA profiles that can be identified. If so, this study aims to develop a screening instrument identifying CEBA profiles in PwMS to select the most suitable neuropsychological rehabilitation treatment for a given CEBA profile and consequently improve the societal participation of PwMS. METHODS: This study is an observational, prospective cohort study consisting of 3 phases. Phase 1 focuses on the identification of CEBA profiles in a large sample of PwMS (n = 300). Phase 2 focuses on validating these CEBA profiles through replication of results in a new sample (n = 100) and on the development of the screening instrument. Phase 3 focuses on qualitatively evaluating in a small group of PwMS whether the selected treatment is suitable for the given CEBA profile or whether existing neuropsychological treatments should be adapted to meet the needs of PwMS suffering from symptoms in multiple CEBA domains simultaneously. Primary outcome is the CEBA profile, which will be derived from performance on neuropsychological assessment consisting of tests and questionnaires regarding the CEBA domains using a latent profile analysis. Inclusion criteria include MS diagnosis, sufficient ability in the Dutch language, and an age between 18 and 70 years. DISCUSSION: The results of the current study will contribute to a more comprehensive understanding of the entire spectrum of neuropsychological symptoms in PwMS. Identification of possible CEBA profiles, and accordingly, the development of a screening instrument determining the CEBA profile of PwMS in clinical practice, contributes to the timely referral of PwMS to the most suitable neuropsychological rehabilitation treatment. If necessary, adjustments to existing treatments will be suggested in order to sufficiently meet the needs of PwMS. All of this with the ultimate aim to improve societal participation, and thereby quality of life, of PwMS. TRIAL REGISTRATION: Dutch Central Committee on Research Involving Human Subjects (CCMO) NL83954.042.23; ClinicalTrials.gov NCT06016309.

An integrated framework for improving green agricultural production sustainability in human-natural systems.

Water scarcity, land pollution, and global warming are serious challenges and crises facing the development of sustainable or green agriculture and need to be addressed using efficient and environmentally friendly management strategies. This paper proposed an integrated framework appropriate for agricultural green total factor productivity (AGTFP) assessment coupled with microscopic and mesoscopic perspectives under water-energy-food (WEF) nexus, which generated scientific and reasonable strategies for green and low-carbon agriculture from internal core factors and peripheral environmental impacts to improve green agricultural production sustainability. Taking the Lianshui irrigation district (LID) with three sub-areas as the object, internal core factors were explored by partial least squares regression (PLSR) and the external impact path through partial least squares structural equation modeling (PLS-SEM). Results indicated that AGTFP in LID was the smallest (0.818) compared to the three sub-areas and was in a fluctuating state. Meanwhile, AGTFP which was calculated considering undesirable outputs, was closer to tangible productivity. Resource endowments and technical facilities will promote agricultural production, desirable outputs will stimulate green production, and undesirable outputs can inhibit green production. The external influence pathway was shown to be primary environment - > secondary environment - > economic aspects - > social aspects - > AGTFP. The innovative perspectives presented in this study can facilitate preferable decisions and avoid unintended consequences for human-natural systems.

Interference of gastrointestinal barriers with antibiotic susceptibility of foodborne pathogens: an in vitro case study of ciprofloxacin and tetracycline against Salmonella enterica and Listeria monocytogenes.

Minimum inhibitory concentrations (MIC) assays are often questioned for their representativeness. Especially when foodborne pathogens are tested, it is of crucial importance to also consider parameters of the human digestive system. Hence, the current study aimed to assess the inhibitory capacity of two antibiotics, ciprofloxacin and tetracycline, against Salmonella enterica and Listeria monocytogenes, under representative environmental conditions. More specifically, aspects of the harsh environment of the human gastrointestinal tract (GIT) were gradually added to the experimental conditions starting from simple aerobic lab conditions into an in vitro simulation of the GIT. In this way, the effects of parameters including the anoxic environment, physicochemical conditions of the GIT (low gastric pH, digestive enzymes, bile acids) and the gut microbiota were evaluated. The latter was simulated by including a representative consortium of selected gut bacteria species. In this study, the MIC of the two antibiotics against the relevant foodborne pathogens were established, under the previously mentioned environmental conditions. The results of S. enterica highlighted the importance of the anaerobic environment when conducting such studies, since the pathogen thrived under such conditions. Inclusion of physicochemical barriers led to exactly opposite results for S. enterica and L. monocytogenes since the former became more susceptible to ciprofloxacin while the latter showed lower susceptibility towards tetracycline. Finally, the inclusion of gut bacteria had a bactericidal effect against L. monocytogenes even in the absence of antibiotics, while gut bacteria protected S. enterica from the effect of ciprofloxacin.

Protein kinase-D1 and downstream signaling mechanisms involved in GLUT4 translocation in cardiac muscle.

The Ser/Thr kinase protein kinase-D1 (PKD1) is involved in induction of various cell physiological processes in the heart such as myocellular hypertrophy and inflammation, which may turn maladaptive during long-term stimulation. Of special interest is a key role of PKD1 in the regulation of cardiac substrate metabolism. Glucose and fatty acids are the most important substrates for cardiac energy provision, and the ratio at which they are utilized determines the health status of the heart. Cardiac glucose uptake is mainly regulated by translocation of the glucose transporter GLUT4 from intracellular stores (endosomes) to the sarcolemma, and fatty acid uptake via a parallel translocation of fatty acid transporter CD36 from endosomes to the sarcolemma. PKD1 is involved in the regulation of GLUT4 translocation, but not CD36 translocation, giving it the ability to modulate glucose uptake without affecting fatty acid uptake, thereby altering the cardiac substrate balance. PKD1 would therefore serve as an attractive target to combat cardiac metabolic diseases with a tilted substrate balance, such as diabetic cardiomyopathy. However, PKD1 activation also elicits cardiac hypertrophy and inflammation. Therefore, identification of the events upstream and downstream of PKD1 may provide superior therapeutic targets to alter the cardiac substrate balance. Recent studies have identified the lipid kinase phosphatidylinositol 4-kinase IIIß (PI4KIIIß) as signaling hub downstream of PKD1 to selectively stimulate GLUT4-mediated myocardial glucose uptake without inducing hypertrophy. Taken together, the PKD1 signaling pathway serves a pivotal role in cardiac glucose metabolism and is a promising target to selectively modulate glucose uptake in cardiac disease.

The use of prolonged-release melatonin in circadian medicine: a systematic review.

INTRODUCTION: Melatonin, a hormone produced by the pineal gland, regulates the sleep-wake cycle and is effective in restoring biological rhythms. Prolonged-release melatonin (PRM) is designed to mimic the natural physiological pattern of melatonin release. In circadian medicine, PRM can be used to treat sleep and circadian rhythm disorders, as well as numerous organic diseases associated with sleep disorders. EVIDENCE ACQUISITION: This systematic review analyzed 62 studies and adhered to the PRISMA guidelines, examining the effectiveness of PRM in organic pathologies and mental disorders. EVIDENCE SYNTHESIS: The main evidence concerns primary insomnia in subjects over the age of 55, showing significant improvements in sleep quality. In neurodevelopmental disorders, there is evidence of a positive impact on sleep quality and quality of life for patients and their caregivers. PRM shows efficacy in the treatment of sleep disorders in mood disorders, schizophrenia, and neurocognitive disorders, but requires further confirmation. The additional use of PRM is supported for the withdrawal of chronic benzodiazepine therapies. The tolerability and safety of PRM are excellent, with ample evidence supporting the absence of tolerance and dependence. CONCLUSIONS: Overall, PRM in circadian medicine is an effective chronopharmaceutical for restoring the sleep-wake rhythm in patients with insomnia disorder. This efficacy may also extend to sleep disorders associated with mood, neurodevelopmental and neurocognitive disorders, suggesting a further potential role in insomnia associated with various organic diseases.

A model for the noninvasive, habitat-inclusive estimation of upper limit abundance for synanthropes, exemplified by M. fascicularis.

Accurately estimating population sizes for free-ranging animals through noninvasive methods, such as camera trap images, remains particularly limited by small datasets. To overcome this, we developed a flexible model for estimating upper limit populations and exemplified it by studying a group-living synanthrope, the long-tailed macaque (Macaca fascicularis). Habitat preference maps, based on environmental and GPS data, were generated with a maximum entropy model and combined with data obtained from camera traps, line transect distance sampling, and direct sightings to produce an expected number of individuals. The mapping between habitat preference and number of individuals was optimized through a tunable parameter ρ (inquisitiveness) that accounts for repeated observations of individuals. Benchmarking against published data highlights the high accuracy of the model. Overall, this approach combines citizen science with scientific observations and reveals the long-tailed macaque populations to be (up to 80%) smaller than expected. The model's flexibility makes it suitable for many species, providing a scalable, noninvasive tool for wildlife conservation.

Enhancing volleyball training: empowering athletes and coaches through advanced sensing and analysis.

Modern sensing technologies and data analysis methods usher in a new era for sports training and practice. Hidden insights can be uncovered and interactive training environments can be created by means of data analysis. We present a system to support volleyball training which makes use of Inertial Measurement Units, a pressure sensitive display floor, and machine learning techniques to automatically detect relevant behaviours and provides the user with the appropriate information. While working with trainers and amateur athletes, we also explore potential applications that are driven by automatic action recognition, that contribute various requirements to the platform. The first application is an automatic video-tagging protocol that marks key events (captured on video) based on the automatic recognition of volleyball-specific actions with an unweighted average recall of 78.71% in the 10-fold cross-validation setting with convolution neural network and 73.84% in leave-one-subject-out cross-validation setting with active data representation method using wearable sensors, as an exemplification of how dashboard and retrieval systems would work with the platform. In the context of action recognition, we have evaluated statistical functions and their transformation using active data representation besides raw signal of IMUs sensor. The second application is the "bump-set-spike" trainer, which uses automatic action recognition to provide real-time feedback about performance to steer player behaviour in volleyball, as an example of rich learning environments enabled by live action detection. In addition to describing these applications, we detail the system components and architecture and discuss the implications that our system might have for sports in general and for volleyball in particular.

Enhancing functional buffalo yogurt: Improving physicochemical properties, biological activities, and shelf life using Marjoram and Geranium essential oils.

The use of essential oils (EOs) has attracted interest in the food industry due to their wide range of beneficial properties. In this study, a new functional yogurt was developed using 2 essential oils [Marjoram (M) and Geranium (G)], at 3 different concentrations (0.2%, 0.4%, and 0.6% vol/vol). The physicochemical properties (syneresis, viscosity, pH, and chemical composition), bioactivities (antioxidant activity, anticancer and antibacterial effects, total phenolic content (TPC), and total flavonoid content (TFC)), and sensory characteristics of the developed yogurt were evaluated. The findings indicated that the yogurts fortified with 0.6% M or G exhibited higher viscosity and lower syneresis compared with other treatments. The yogurt supplemented with 0.6% M displayed significant antibacterial activity against Listeria monocytogenes, Staphylococcus aureus, Salmonella typhimurium, and Escherichia coli. In addition, the yogurt enriched with Geranium and Marjoram oils at a concentration of 0.6% had notably significant (P < 0.05) higher TFC levels compared with the control sample and other concentrations. In the same context, in terms of TPC, yogurt supplemented with 0.6% Marjoram oil displayed significantly (P < 0.05) elevated levels in comparison to the other samples tested. Yogurt enriched with Marjoram oil exhibited noteworthy antioxidant activity, followed by Geranium oil compared with the control samples. The yogurt supplemented with 0.6% M demonstrated strong radical scavenging activity, while the yogurt fortified with 0.6% G showed higher anticancer activity against HepG2 human liver carcinoma cells and oxidative stress enzyme activities. Among the various concentrations of EOs tested, the yogurts fortified with 0.6% M or G EOs exhibited the most favorable outcomes, followed by 0.4% M or G. To summarize, G and M EOs can be used as a potential nutritious ingredient and as a natural preservative for milk and related products.

Estimation of Kinetics Using IMUs to Monitor and Aid in Clinical Decision-Making during ACL Rehabilitation: A Systematic Review.

After an ACL injury, rehabilitation consists of multiple phases, and progress between these phases is guided by subjective visual assessments of activities such as running, hopping, jump landing, etc. Estimation of objective kinetic measures like knee joint moments and GRF during assessment can help physiotherapists gain insights on knee loading and tailor rehabilitation protocols. Conventional methods deployed to estimate kinetics require complex, expensive systems and are limited to laboratory settings. Alternatively, multiple algorithms have been proposed in the literature to estimate kinetics from kinematics measured using only IMUs. However, the knowledge about their accuracy and generalizability for patient populations is still limited. Therefore, this article aims to identify the available algorithms for the estimation of kinetic parameters using kinematics measured only from IMUs and to evaluate their applicability in ACL rehabilitation through a comprehensive systematic review. The papers identified through the search were categorized based on the modelling techniques and kinetic parameters of interest, and subsequently compared based on the accuracies achieved and applicability for ACL patients during rehabilitation. IMUs have exhibited potential in estimating kinetic parameters with good accuracy, particularly for sagittal movements in healthy cohorts. However, several shortcomings were identified and future directions for improvement have been proposed, including extension of proposed algorithms to accommodate multiplanar movements and validation of the proposed techniques in diverse patient populations and in particular the ACL population.

Novel methods to monitor the biodegradation of polylactic acid (PLA) by Amycolatopsis orientalis and Amycolatopsis thailandensis.

Plastics are essential in modern life, but their conventional production is problematic due to environmental pollution and waste management issues. Polylactic acid (PLA) is a widely used bioplastic that is bio-based and biodegradable, making it a key player in the bioeconomy. PLA has been proven to be degradable in various settings, including aqueous, soil, and compost environments. However, monitoring and optimizing PLA biodegradation remains challenging. This study proposes methods to improve the quantification of PLA biodegradation by Amycolatopsis spp. Ultrasound treatments (10 s) significantly improved the enumeration of viable Amycolatopsis cells by breaking the pellets into quantifiable individual cells. A separation technique combining ultrasound (120 s) and 40 µm cell strainers effectively isolated PLA particles from biomass to quantify PLA weight loss. This enabled the monitoring of PLA biofragmentation. Finally, CO2 production was measured according to ISO 14852 to quantify mineralization. Integrating these methods provides an improved quantification for PLA biodegradation along its different stages. In a case study, this led to the construction of a carbon balance where 85.1% of initial carbon content was successfully tracked. The developed techniques for monitoring of PLA biodegradation are essential to design future waste management strategies for biodegradable plastics.

Epicardial cavernous haemangioma; A case report of a unique incidental finding.

Background: Primary cardiac tumours are rare, accounting for only 0.002-0.03% at autopsy. Cardiac haemangiomas are benign vascular tumours and constitute for 0.28% of all primary cardiac tumours. Cavernous haemangiomas, capillary haemangiomas, and arteriovenous haemangiomas are three distinct types. Cardiac haemangiomas are often misdiagnosed as myxomas and must be differentiated from malignant angiosarcomas. Case summary: We present a 44-year-old Mediterranean male patient with a cavernous haemangioma in the inferior vena cava and right atrium, detected on transthoracic echocardiography. The patient experienced palpitations and dyspnoea on exertion. Computed tomography (CT) angiography revealed a 7.5 × 6 × 5 cm mass suspected to be perfused by the distal right coronary artery. A watch-and-wait approach was suggested, leading to a cardiac magnetic resonance imaging (MRI) with contrast 6 months later. T1 mapping exhibited a prolonged relaxation time and isointensity to the myocardium. T2 mapping revealed a homogenous hyperintense mass with heterogenous late enhancement. Surgical excision was performed using a bicaval cannulation technique on cardiopulmonary bypass. Intraoperatively, no connection to the coronaries was noted. At 1 year follow-up, the patient reported restored physical resilience, with no evidence of tumour recurrence. Discussion: Clinical symptoms of cardiac cavernous haemangiomas are unspecific and become evident once the tumour grows. To investigate the nature and vascular involvement of the tumour, a contrast-enhanced CT angiography or MRI can be performed. Cardiac haemangiomas are often misdiagnosed and must be differentiated from malignant angiosarcomas. Clear guidelines for the treatment of cardiac haemangiomas in adult patients are lacking. Primary cardiac tumours require thorough investigation, and surgical intervention should be tailored to the individual's case.

Impact of long-term transmural plastic stents on recurrence after endoscopic treatment of walled-off pancreatic necrosis.

BACKGROUND: Endoscopic transmural drainage (ETD) using double-pigtail stents (DPSs) is a well-established treatment for walled-off pancreatic necrosis (WON). This study aimed to compare outcomes in patients undergoing ETD with DPSs left indwelling versus those where stents were removed or migrated. METHODS: This retrospective multicenter cohort study included patients with WON who underwent ETD using DPSs between July 2001 and December 2019. The primary outcome was recurrence of a pancreatic fluid collection (PFC). Secondary outcomes were long-term complications and recurrence-associated factors. Competing risk regression analysis considered DPS removal or migration as time-varying covariates. RESULTS: Among 320 patients (median age 58; 36% women), DPSs were removed in 153 (47.8%), migrated spontaneously in 27 (8.4%), and remained indwelling in 140 (43.8%). PFC recurrence was observed in 57 patients (17.8%): after removal (n = 39; 25.5%); after migration (n = 4; 14.8%); in patients with indwelling DPSs (n = 14; 10.0%). In 25 patients (7.8%), drainage of recurrent PFC was indicated. Risk factors for recurrence were DPS removal or migration (hazard ratio [HR] 3.45, 95%CI 1.37-8.70) and presence of a disconnected pancreatic duct (HR 5.08, 95%CI 1.84-14.0). CONCLUSIONS: Among patients who undergo ETD of WON, leaving DPSs in situ seems to lower the risk of recurrent fluid collections, without any long-term DPS-related complications. These results suggest that DPSs should not be routinely removed and can be safely left indwelling indefinitely.

Performance of an Artificial Intelligence System for Breast Cancer Detection on Screening Mammograms from BreastScreen Norway.

Purpose To explore the stand-alone breast cancer detection performance, at different risk score thresholds, of a commercially available artificial intelligence (AI) system. Materials and Methods This retrospective study included information from 661 695 digital mammographic examinations performed among 242 629 female individuals screened as a part of BreastScreen Norway, 2004-2018. The study sample included 3807 screen-detected cancers and 1110 interval breast cancers. A continuous examination-level risk score by the AI system was used to measure performance as the area under the receiver operating characteristic curve (AUC) with 95% CIs and cancer detection at different AI risk score thresholds. Results The AUC of the AI system was 0.93 (95% CI: 0.92, 0.93) for screen-detected cancers and interval breast cancers combined and 0.97 (95% CI: 0.97, 0.97) for screen-detected cancers. In a setting where 10% of the examinations with the highest AI risk scores were defined as positive and 90% with the lowest scores as negative, 92.0% (3502 of 3807) of the screen-detected cancers and 44.6% (495 of 1110) of the interval breast cancers were identified with AI. In this scenario, 68.5% (10 987 of 16 040) of false-positive screening results (negative recall assessment) were considered negative by AI. When 50% was used as the cutoff, 99.3% (3781 of 3807) of the screen-detected cancers and 85.2% (946 of 1110) of the interval breast cancers were identified as positive by AI, whereas 17.0% (2725 of 16 040) of the false-positive results were considered negative. Conclusion The AI system showed high performance in detecting breast cancers within 2 years of screening mammography and a potential for use to triage low-risk mammograms to reduce radiologist workload. Keywords: Mammography, Breast, Screening, Convolutional Neural Network (CNN), Deep Learning Algorithms Supplemental material is available for this article. © RSNA, 2024 See also commentary by Bahl and Do in this issue.

A supervised, externally validated machine learning model for artifact and drainage detection in high-resolution intracranial pressure monitoring data.

OBJECTIVE: In neurocritical care, data from multiple biosensors are continuously measured, but only sporadically acknowledged by the attending physicians. In contrast, machine learning (ML) tools can analyze large amounts of data continuously, taking advantage of underlying information. However, the performance of such ML-based solutions is limited by different factors, for example, by patient motion, manipulation, or, as in the case of external ventricular drains (EVDs), the drainage of CSF to control intracranial pressure (ICP). The authors aimed to develop an ML-based algorithm that automatically classifies normal signals, artifacts, and drainages in high-resolution ICP monitoring data from EVDs, making the data suitable for real-time artifact removal and for future ML applications. METHODS: In their 2-center retrospective cohort study, the authors used labeled ICP data from 40 patients in the first neurocritical care unit (University Hospital Zurich) for model development. The authors created 94 descriptive features that were used to train the model. They compared histogram-based gradient boosting with extremely randomized trees after building pipelines with principal component analysis, hyperparameter optimization via grid search, and sequential feature selection. Performance was measured with nested 5-fold cross-validation and multiclass area under the receiver operating characteristic curve (AUROC). Data from 20 patients in a second, independent neurocritical care unit (Charité - Universitätsmedizin Berlin) were used for external validation with bootstrapping technique and AUROC. RESULTS: In cross-validation, the best-performing model achieved a mean AUROC of 0.945 (95% CI 0.92-0.969) on the development dataset. On the external validation dataset, the model performed with a mean AUROC of 0.928 (95% CI 0.908-0.946) in 100 bootstrapping validation cycles to classify normal signals, artifacts, and drainages. CONCLUSIONS: Here, the authors developed a well-performing supervised model with external validation that can detect normal signals, artifacts, and drainages in ICP signals from patients in neurocritical care units. For future analyses, this is a powerful tool to discard artifacts or to detect drainage events in ICP monitoring signals.