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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Incidence and Prediction of Unrelated Mortality After Successful Endoscopic Eradication Therapy for Barrett's Neoplasia.

BACKGROUND & AIMS: Follow-up (FU) strategies after endoscopic eradication therapy (EET) for Barrett's neoplasia do not consider the risk of mortality from causes other than esophageal adenocarcinoma (EAC). We aimed to evaluate this risk during long-term FU, and to assess whether the Charlson Comorbidity Index (CCI) can predict mortality. METHODS: We included all patients with successful EET from the nationwide Barrett registry in the Netherlands. Data were merged with National Statistics for accurate mortality data. We evaluated annual mortality rates (AMRs, per 1000 person-years) and standardized mortality ratio for other-cause mortality. Performance of the CCI was evaluated by discrimination and calibration. RESULTS: We included 1154 patients with a mean age of 64 years (±9). During median 59 months (p25-p75 37-91; total 6375 person-years), 154 patients (13%) died from other causes than EAC (AMR, 24.1; 95% CI, 20.5-28.2), most commonly non-EAC cancers (n = 58), cardiovascular (n = 31), or pulmonary diseases (n = 26). Four patients died from recurrent EAC (AMR, 0.5; 95% CI, 0.1-1.4). Compared with the general Dutch population, mortality was significantly increased for patients in the lowest 3 age quartiles (ie, age <71 years). Validation of CCI in our population showed good discrimination (Concordance statistic, 0.78; 95% CI, 0.72-0.84) and fair calibration. CONCLUSION: The other-cause mortality risk after successful EET was more than 40 times higher (48; 95% CI, 15-99) than the risk of EAC-related mortality. Our findings reveal that younger post-EET patients exhibit a significantly reduced life expectancy when compared with the general population. Furthermore, they emphasize the strong predictive ability of CCI for long-term mortality after EET. This straightforward scoring system can inform decisions regarding personalized FU, including appropriate cessation timing. (NL7039).

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.

Post-Coronavirus Disease 2019 Pandemic Antimicrobial Resistance.

BACKGROUND AND AIM: Antimicrobial resistance (AMR) is a chronic issue of our Westernized society, mainly because of the uncontrolled and improper use of antimicrobials. The coronavirus disease 2019 (COVID-19) pandemic has triggered and expanded AMR diffusion all over the world, and its clinical and therapeutic features have changed. Thus, we aimed to review evidence from the literature on the definition and causative agents of AMR in the frame of the COVID-19 post-pandemic era. METHODS: We conducted a search on PubMed and Medline for original articles, reviews, meta-analyses, and case series using the following keywords, their acronyms, and their associations: antibiotics, antimicrobial resistance, severe acute respiratory syndrome coronavirus 2 (SARS-CoV2), COVID-19 pandemic, personal protective equipment. RESULTS: AMR had a significant rise in incidence both in in-hospital and outpatient populations (ranging from 5 up to 50%) worldwide, but with a variegated profile according to the germ and microorganism considered. Not only bacteria but also fungi have developed more frequent and diffuse AMR. These findings are explained by the increased use and misuse of antibiotics and preventive measures during the first waves of the SARS-CoV2 pandemic, especially in hospitalized patients. Subsequently, the reduction in and end of the lockdown and the use of personal protective equipment have allowed for the indiscriminate circulation of resistant microorganisms from low-income countries to the rest of the world with the emergence of new multi- and polyresistant organisms. However, there is not a clear association between COVID-19 and AMR changes in the post-pandemic period. CONCLUSIONS: AMR in some microorganisms has significantly increased and changed its characteristics during and after the end of the pandemic phase of COVID-19. An integrated supranational monitoring approach to this challenge is warranted in the years to come. In detail, a rational, personalized, and regulated use of antibiotics and antimicrobials is needed.

Can I trust my fake data - A comprehensive quality assessment framework for synthetic tabular data in healthcare.

BACKGROUND: Ensuring safe adoption of AI tools in healthcare hinges on access to sufficient data for training, testing and validation. Synthetic data has been suggested in response to privacy concerns and regulatory requirements and can be created by training a generator on real data to produce a dataset with similar statistical properties. Competing metrics with differing taxonomies for quality evaluation have been proposed, resulting in a complex landscape. Optimising quality entails balancing considerations that make the data fit for use, yet relevant dimensions are left out of existing frameworks. METHOD: We performed a comprehensive literature review on the use of quality evaluation metrics on synthetic data within the scope of synthetic tabular healthcare data using deep generative methods. Based on this and the collective team experiences, we developed a conceptual framework for quality assurance. The applicability was benchmarked against a practical case from the Dutch National Cancer Registry. CONCLUSION: We present a conceptual framework for quality assuranceof synthetic data for AI applications in healthcare that aligns diverging taxonomies, expands on common quality dimensions to include the dimensions of Fairness and Carbon footprint, and proposes stages necessary to support real-life applications. Building trust in synthetic data by increasing transparency and reducing the safety risk will accelerate the development and uptake of trustworthy AI tools for the benefit of patients. DISCUSSION: Despite the growing emphasis on algorithmic fairness and carbon footprint, these metrics were scarce in the literature review. The overwhelming focus was on statistical similarity using distance metrics while sequential logic detection was scarce. A consensus-backed framework that includes all relevant quality dimensions can provide assurance for safe and responsible real-life applications of synthetic data. As the choice of appropriate metrics are highly context dependent, further research is needed on validation studies to guide metric choices and support the development of technical standards.

Health benefits of combined oral contraceptives - a narrative review.

PURPOSE: This review presents an update of the non-contraceptive health benefits of the combined oral contraceptive pill. METHODS: We conducted a literature search for (review) articles that discussed the health benefits of combined oral contraceptives (COCs), in the period from 1980 to 2023. RESULTS: We identified 21 subjective and/or objective health benefits of COCs related to (i) the reproductive tract, (ii) non-gynaecological benign disorders and (iii) malignancies. Reproductive tract benefits are related to menstrual bleeding(including anaemia and toxic shock syndrome), dysmenorrhoea, migraine, premenstrual syndrome (PMS), ovarian cysts, Polycystic Ovary Syndrome (PCOS), androgen related symptoms, ectopic pregnancy, hypoestrogenism, endometriosis and adenomyosis, uterine fibroids and pelvic inflammatory disease (PID). Non-gynaecological benefits are related to benign breast disease, osteoporosis, rheumatoid arthritis, multiple sclerosis, asthma and porphyria. Health benefits of COCs related to cancer are lower risks of endometrial cancer, ovarian cancer and colorectal cancer. CONCLUSIONS: The use of combined oral contraceptives is accompanied with a range of health benefits, to be balanced against its side-effects and risks. Several health benefits of COCs are a reason for non-contraceptive COC prescription.