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Reports of Large Language Models (LLMs) passing board examinations have spurred medical enthusiasm for their clinical integration. Through a narrative review, we reflect upon the skill shifts necessary for clinicians to succeed in an LLM-enabled world, achieving benefits while minimizing risks. We suggest how medical education must evolve to prepare clinicians capable of navigating human-AI systems. [ABSTRACT FROM AUTHOR]

(1) Background: This study aimed to evaluate the effect of an extruded whole-grain sorghum beverage containing L. paracasei on body composition, lipid profiles, and intestinal health in overweight and obese adults. (2) Methods: A chronic, single-blind randomized controlled pilot study was conducted with 30 volunteers allocated to three groups (n = 10/group): extruded sorghum beverage (ESB), extruded sorghum beverage with L. paracasei (ESPB), and control beverage (CB) (waxy maize starch). The chemical composition of the beverages was analyzed. Volunteers consumed the beverages for ten weeks at breakfast, along with individual dietary prescriptions. Body composition, biochemical markers, gastrointestinal symptoms, stool consistency, intestinal permeability, short-chain fatty acids, fecal pH, and stool L. paracasei DNA concentration were analyzed at the beginning and end of the intervention period. (3) Results: The ESB showed better composition than the CB, particularly in terms of resistant starch content, total phenolic compounds, condensed tannins, and antioxidant capacity. Both the ESB and the ESPB had an effect on body composition (estimated total visceral fat and waist volume), biochemical markers (Castelli index I), and intestinal health (Bristol scale, diarrhea score, valeric acid, and L. paracasei DNA concentration). No changes were observed in the CB group after the intervention. (4) Conclusions: Whole-grain sorghum beverages demonstrated good nutritional value, and consumption of these beverages, with or without L. paracasei, provided health benefits, including improvements in body composition, Castelli index I scores, and intestinal health, in overweight and obese adults. [ABSTRACT FROM AUTHOR]

Photon counting computed tomography (PCCT) represents a paradigm shift from conventional CT imaging, propelled by a new generation of X-ray detectors capable of counting individual photons and measuring their energy. The first part of this narrative review is focused on the technical aspects of PCCT and describes its key advancements and benefits compared to conventional CT but also its limitations. By synthesizing the existing literature, the second part of the review seeks to elucidate the potential of PCCT as a valuable tool for assessing carotid artery disease. Thanks to the enhanced spatial resolution and image quality, PCCT allows for an accurate evaluation of carotid luminal stenosis. With its ability to finely discriminate between different tissue types, PCCT allows for detailed characterization of plaque morphology and composition, which is crucial for assessing plaque vulnerability and the risk of cerebrovascular events. [ABSTRACT FROM AUTHOR]

Beet is a nutritious and health-promoting food with important bioactive compounds in its industrial by-products. The encapsulation of antioxidants from beet by-products has been proposed for valorization. For this, an ethanol–water extract was mixed with polyvinylpyrrolidone (PVP) (used as a carrier agent) and then encapsulated. The encapsulation was performed by spray drying, where the effects of temperature (140–160 °C), extract input flow rate (10–30%), and extraction solvent (ethanol–water 50/50 v/v and ethanol) were evaluated for the total phenol content and the spray-drying yield. The yields obtained were between 60 and 89%, and total phenols were between 136 and 1026 mg gallic acid equivalents/g of encapsulated product. Both responses were affected (p < 0.05) by the extraction solvent. The optimal spray-drying conditions were determined by response surface methodology (RSM). The encapsulated product obtained at optimal conditions was characterized by infrared spectrometry, X-ray fluorescence, Ultra-High Performance Liquid Chromatography, and scanning electron microscopy analysis. The results show that the encapsulated product has a high content of total phenols and compounds such as betanin, isobetanin, and neobetanin. Considering the results of physicochemical properties and the bioactive compounds, the optimized encapsulated product could be applied in the food industry as a bioactive ingredient or natural colorant. However, the further investigation of alternative carrier agents needs to be performed to reduce caking. [ABSTRACT FROM AUTHOR]

The volatile components emitted by fresh aromatic flowers of Plumeria rubra L., harvested in southern Ecuador during three different months were determined to evaluate the fluctuation of secondary metabolites. The volatile compounds were analyzed using headspace solid-phase microextraction (HS-SPME) followed by gas chromatography coupled to mass spectrometry (GC–MS) and a flame ionization detector (GC–FID) using two types of columns: a non-polar (DB-5ms) and polar column (HP-INNOWax). The principal chemical groups were hydrocarbon sesquiterpenes (43.5%; 40.0%), oxygenated sesquiterpenes (23.4%; 26.4%), oxygenated monoterpenes (14.0%; 11.2%), and hydrocarbon monoterpenes (12.7%; 9.3%). The most representative constituents were (E,E)-α-Farnesene (40.9–41.2%; 38.5–50.6%), (E)-nerolidol (21.4–32.6%; 23.2–33.0%), (E)-β-ocimene (4.2–12.5%; 4.5–9.1%), (Z)-dihydro-apofarnesol (6.5–9.9%; 7.6–8.6%), linalool (5.6–8.3%; 3.3–7.8%), and perillene (3.1–5.9%; 3.0–3.2%) in DB-5ms and HP-INNOWax, respectively. Finally, we reported for the first time the enantiomeric distribution of P. rubra flowers, where the enantiomers (1R,5R)-(+)-α-pinene, (S)-(−)-limonene, (S)-(+)-Linalool, and (1S,2R,6R,7R,8R)-(+)-α-copaene were present as enantiomerically pure substances, whereas (S)-(+)-(E)-Nerolidol and (R)-(+)-(E)-Nerolidol were observed as scalemic mixtures. This study provides the first comprehensive and comparative aroma profile of Plumeria rubra cultivated in southern Ecuador and gave us a clue to the variability of P. rubra chemotypes depending on the harvesting time, which could be used for future quality control or applications in phytopharmaceutical and food industries. [ABSTRACT FROM AUTHOR]

The presence of engineered nanoparticles (ENPs) in soil systems can modify their properties and the availability of nutrients. This study evaluated the effect of 1% CuO or ZnO ENPs on the physicochemical properties and on the phosphorus (P) adsorption–desorption processes of a volcanic ash soil (Lautaro; LAU). The dynamics of P were conducted through kinetic and isotherm batch experiments. The results showed that LAU soil with 1% CuO or ZnO ENPs increased pHH2O (from 5.67 to 6.03 and 6.82, respectively), electrical conductivity (from 0.119 to 0.143 and 0.150 dS m−1, respectively), Zn availability (597.7 times higher for LAU with 1% ZnO ENPs in relation to soil without ENPs), and Cu availability (41.8 times higher for LAU with 1% CuO ENPs in relation to soil without ENPs). Moreover, the presence of ENPs decreased Brunauer, Emmett, and Teller specific surface area. The adsorption kinetic studies of P on LAU soil without and with 1% ENPs fitted well to the Elovich model (r2 ≥ 0.923), which indicated a chemiadsorption mechanism, whereas the adsorption isotherms were described by Langmuir–Freundlich model (r2 ≥ 0.939). The desorption percentage was LAU > LAU + 1% CuO–ENPs > LAU + 1% ZnO–ENPs, demonstrating an increased stability of the P–soil surface binding with 1% ENPs. Co–existing NO3−, SeO42−, and SO42− anions did not generate a steric hindrance between P and LAU soil binding. Finally, both ENPs could alter the quality of the soil due to changes in their physicochemical properties and decrease the availability of P in volcanic ash soils. [ABSTRACT FROM AUTHOR]

Importance: Maneuvers assessing fluid responsiveness before an intravascular volume expansion may limit useless fluid administration, which in turn may improve outcomes. Objective: To describe maneuvers for assessing fluid responsiveness in mechanically ventilated patients. Registration: The protocol was registered at PROSPERO: CRD42019146781. Information sources and search: PubMed, EMBASE, CINAHL, SCOPUS, and Web of Science were search from inception to 08/08/2023. Study selection and data collection: Prospective and intervention studies were selected. Statistical analysis: Data for each maneuver were reported individually and data from the five most employed maneuvers were aggregated. A traditional and a Bayesian meta-analysis approach were performed. Results: A total of 69 studies, encompassing 3185 fluid challenges and 2711 patients were analyzed. The prevalence of fluid responsiveness was 49.9%. Pulse pressure variation (PPV) was studied in 40 studies, mean threshold with 95% confidence intervals (95% CI) = 11.5 (10.5–12.4)%, and area under the receiver operating characteristics curve (AUC) with 95% CI was 0.87 (0.84–0.90). Stroke volume variation (SVV) was studied in 24 studies, mean threshold with 95% CI = 12.1 (10.9–13.3)%, and AUC with 95% CI was 0.87 (0.84–0.91). The plethysmographic variability index (PVI) was studied in 17 studies, mean threshold = 13.8 (12.3–15.3)%, and AUC was 0.88 (0.82–0.94). Central venous pressure (CVP) was studied in 12 studies, mean threshold with 95% CI = 9.0 (7.7–10.1) mmHg, and AUC with 95% CI was 0.77 (0.69–0.87). Inferior vena cava variation (∆IVC) was studied in 8 studies, mean threshold = 15.4 (13.3–17.6)%, and AUC with 95% CI was 0.83 (0.78–0.89). Conclusions: Fluid responsiveness can be reliably assessed in adult patients under mechanical ventilation. Among the five maneuvers compared in predicting fluid responsiveness, PPV, SVV, and PVI were superior to CVP and ∆IVC. However, there is no data supporting any of the above mentioned as being the best maneuver. Additionally, other well-established tests, such as the passive leg raising test, end-expiratory occlusion test, and tidal volume challenge, are also reliable. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of migration on the export and production techniques of agri-industrial firms in the proximity of clusters of migrants. The analysis draws on an original dataset built through interviews conducted with agri-food firms in the Foggia province (southern Italy). Over the past two decades, this area has experienced a strong influx of migrants, who have concentrated in ghettos. The results do not support a pro-trade effect, but provide evidence for both a substitution and a complementarity effect of migrants on capital endowment, depending on the type of machinery used by the firm. [ABSTRACT FROM AUTHOR]

The rise in food intolerances and celiac disease, along with advanced diagnostic techniques, has prompted health professionals to seek effective and economical testing methods. This study evaluates combining genetic tests with routine carbohydrate-absorption breath tests to classify patients with chronic gastrointestinal disorders into therapeutic groups, enhancing dietary management and improving gut health and quality of life. Forty-nine patients with suspected carbohydrate intolerance underwent genetic testing for lactase non-persistence, hereditary fructose intolerance, and celiac disease risk. Simultaneously, breath tests assessed lactose and fructose absorption. The lactase non-persistence genotype appeared in 36.7% of cases, with one hereditary fructose-intolerance case in a heterozygous condition. Celiac disease risk markers (HLA-DQ2/8 haplotypes) were found in 49.0% of the population. Secondary lactose and/or fructose malabsorption was present in 67.3% of patients, with 66.1% of lactase non-persistence individuals showing secondary lactose malabsorption. Fructose malabsorption was prevalent in 45.8% of patients at risk for celiac disease. Two main treatment groups were defined based on genetic results, indicating primary and irreversible gastrointestinal disorder causes, followed by a sub-classification using breath test results. Genetic testing is a valuable tool for designing dietary management plans, avoiding unnecessary diet restrictions, and reducing recovery times. [ABSTRACT FROM AUTHOR]

Extracellular vesicles (EVs) play a pivotal role in a variety of physiologically relevant processes, including lung inflammation. Recent attention has been directed toward EV-derived microRNAs (miRNAs), such as miR-191-5p, particularly in the context of inflammation. Here, we investigated the impact of miR-191-5p-enriched EVs on the activation of NF-κB and the expression of molecules associated with inflammation such as interleukin-8 (IL-8). To this aim, cells of bronchial epithelial origin, 16HBE, were transfected with miR-191-5p mimic and inhibitor and subsequently subjected to stimulations to generate EVs. Then, bronchial epithelial cells were exposed to the obtained EVs to evaluate the activation of NF-κB and IL-8 levels. Additionally, we conducted a preliminary investigation to analyze the expression profiles of miR-191-5p in EVs isolated from the plasma of patients diagnosed with chronic obstructive pulmonary disease (COPD). Our initial findings revealed two significant observations. First, the exposure of bronchial epithelial cells to miR-191-5p-enriched EVs activated the NF-kB signaling and increased the synthesis of IL-8. Second, we discovered the presence of miR-191-5p in peripheral blood-derived EVs from COPD patients and noted a correlation between miR-191-5p levels and inflammatory and functional parameters. Collectively, these data corroborate and further expand the proinflammatory role of EVs, with a specific emphasis on miR-191-5p as a key cargo involved in this process. Consequently, we propose a model in which miR-191-5p, carried by EVs, plays a role in airway inflammation and may contribute to the pathogenesis of COPD. [ABSTRACT FROM AUTHOR]

Alternate wetting and drying (AWD) is an effective water-saving practice for rice cultivation that may however promote nitrogen (N) losses compared to continuous flooding (CF). The interaction between water, crop residue and N fertilization management can influence the contribution of different N sources to plant uptake. We hypothesized that microbial processes driving the source-differentiated N supply for rice uptake during the early growth stages will depend on the interaction between water management, the timing of straw incorporation with respect to flooding and the temporal distribution of mineral N application. Rice was grown for 60 days in mesocosm experiment involving a factorial design with (i) two water regimes (CF vs. AWD) and (ii) three straw and fertilizer managements, during which soil N, porewater chemistry, plant growth and N uptake were evaluated. Source partitioning of plant N between fertilizer-, straw- and soil-derived N was achieved by means of a dual-stable isotope 15N tracing approach. Although AWD reduced total N uptake by about 4–25% with respect to CF, this could only be partly attributed to a lower uptake of fertilizer-N (and lower fertilizer-N use efficiency), suggesting that other N sources were affected by water management. Our findings evidence how the interaction between soil redox conditions and the availability of labile C and inorganic N strongly determined the supply of soil-derived N through microbial feedback and priming responses. Although incorporated straw contributed only minimally to rice N, it represented the primary driver controlling plant N nutrition through these microbial responses. These insights may contribute to identify suitable fertilization practices that favour plant N uptake during the early stages of rice growth under AWD. [ABSTRACT FROM AUTHOR]

The Pelargonium genus encompasses around 280 species, most of which are used for medicinal purposes. While P. graveolens, P. odoratissimum, and P. zonale are known to exhibit antimicrobial activity, there is an evident absence of studies evaluating all three species to understand their chemical differences and biological effects. Through the analysis of the hydroalcoholic extracts of P. graveolens, P. odoratissimum, and P. zonale, using HPLC-DAD-MS/MS, quercetin and kaempferol derivatives were identified in these three species. Conversely, gallotannins and anthocyanins were uniquely detected in P. zonale. P. graveolens stood out due to the various types of myricetin derivatives that were not detected in P. odoratissimum and P. zonale extracts. Evaluation of their biological activities revealed that P. zonale displayed superior antibacterial and antibiofilm activities in comparison to the other two species. The antibacterial efficacy of P. zonale was observed towards the clinically relevant strains of Staphylococcus aureus ATCC 25923, Methicillin-resistant Staphylococcus aureus (MRSA) 333, Enterococcus faecalis ATCC 29212, and the Vancomycin-resistant E. faecalis INSPI 032. Fractionation analysis of P. zonale suggested that the antibacterial activity attributed to this plant is due to the presence of quercetin derivatives and kaempferol and its derivatives, alongside their synergistic interaction with gallotannins and anthocyanins. Lastly, the three Pelargonium species exhibited notable antioxidant activity, which may be attributed to their high content of total phenolic compounds. [ABSTRACT FROM AUTHOR]

Digital health is increasingly promoting open health data. Although this open approach promises a number of benefits, it also leads to tensions with Indigenous data sovereignty movements led by Indigenous peoples around the world who are asserting control over the use of health data as a part of self-determination. Digital health has a role in improving access to services and delivering improved health outcomes for Indigenous communities. However, we argue that in order to be effective and ethical, it is essential that the field engages more with Indigenous peoples´ rights and interests. We discuss challenges and possible improvements for data acquisition, management, analysis, and integration as they pertain to the health of Indigenous communities around the world. [ABSTRACT FROM AUTHOR]

Depending on local cues, macrophages can polarize into classically activated (M1) or alternatively activated (M2) phenotypes. This study investigates the impact of polarized macrophage-derived Extracellular Vesicles (EVs) (M1 and M2) and their cargo of miRNA-19a-3p and miRNA-425-5p on TGF-β production in lung fibroblasts. EVs were isolated from supernatants of M0, M1, and M2 macrophages and quantified using nanoscale flow cytometry prior to fibroblast stimulation. The concentration of TGF-β in fibroblast supernatants was measured using ELISA assays. The expression levels of miRNA-19a-3p and miRNA-425-5p were assessed via TaqMan-qPCR. TGF-β production after stimulation with M0-derived EVs and with M1-derived EVs increased significantly compared to untreated fibroblasts. miRNA-425-5p, but not miRNA-19a-3p, was significantly upregulated in M2-derived EVs compared to M0- and M1-derived EVs. This study demonstrates that EVs derived from both M0 and M1 polarized macrophages induce the production of TGF-β in fibroblasts, with potential regulation by miRNA-425-5p. [ABSTRACT FROM AUTHOR]

Purpose: This article explores the migration intentions (MIs) embedded in population movements from rural to urban areas in Bangladesh. In this country, urban-centric development policies have made cities epicentres of commerce and industrialisation, offering significant employment and livelihood opportunities. This rapid transformation has generated several socio-psychological factors that are influencing the willingness of rural populations to migrate to cities for better jobs, lifestyles and services. Design/methodology/approach: The present study adopted the theory of planned behaviour (TPB) as a conceptual model to assess the behavioural and psychological factors underlying MIs. Findings: The results of the structural equation modelling (SEM) indicate that MIs are mainly influenced by subjective norms (SN) and, to a lesser extent, attitudes towards migration (ATM) and perceived behavioural control (PBC). Originality/value: The analysis drew on an original dataset built through interviews with migrants from rural areas employed in the ready-made garment (RMG) industry in four selective areas of the Metropolitan City of Chittagong. [ABSTRACT FROM AUTHOR]

We describe a computational platform to predict atherosclerotic plaque onset and growth in carotids. It integrates in-vivo data, Computational Fluid Dynamics (CFD) simulations and a model for plaque growth linearly correlating the plaque progression with low values of time-averaged Wall Shear Stresses (WSS). We show that steady CFD simulations give the same averaged-WSS values as unsteady simulations. Therefore, the model for plaque growth can be coupled with steady simulations, reducing the computational costs. Finally, by comparing the numerical predictions with the in-vivo data, we show that a modification must be introduced in the plaque growth model to obtain acceptable results. [ABSTRACT FROM AUTHOR]

We present the INSPIRE dataset, a publicly available research dataset in perioperative medicine, which includes approximately 130,000 surgical operations at an academic institution in South Korea over a ten-year period between 2011 and 2020. This comprehensive dataset includes patient characteristics such as age, sex, American Society of Anesthesiologists physical status classification, diagnosis, surgical procedure code, department, and type of anaesthesia. The dataset also includes vital signs in the operating theatre, general wards, and intensive care units (ICUs), laboratory results from six months before admission to six months after discharge, and medication during hospitalisation. Complications include total hospital and ICU length of stay and in-hospital death. We hope this dataset will inspire collaborative research and development in perioperative medicine and serve as a reproducible external validation dataset to improve surgical outcomes. [ABSTRACT FROM AUTHOR]

In low- and middle-income countries, the substantial costs associated with traditional data collection pose an obstacle to facilitating decision-making in the field of public health. Satellite imagery offers a potential solution, but the image extraction and analysis can be costly and requires specialized expertise. We introduce SatelliteBench, a scalable framework for satellite image extraction and vector embeddings generation. We also propose a novel multimodal fusion pipeline that utilizes a series of satellite imagery and metadata. The framework was evaluated generating a dataset with a collection of 12,636 images and embeddings accompanied by comprehensive metadata, from 81 municipalities in Colombia between 2016 and 2018. The dataset was then evaluated in 3 tasks: including dengue case prediction, poverty assessment, and access to education. The performance showcases the versatility and practicality of SatelliteBench, offering a reproducible, accessible and open tool to enhance decision-making in public health. [ABSTRACT FROM AUTHOR]

Objective To investigate the consistency and reliability of medication recommendations provided by ChatGPT for common dermatological conditions, highlighting the potential for ChatGPT to offer second opinions in patient treatment while also delineating possible limitations. Materials and Methods In this mixed-methods study, we used survey questions in April 2023 for drug recommendations generated by ChatGPT with data from secondary databases, that is, Taiwan's National Health Insurance Research Database and an US medical center database, and validated by dermatologists. The methodology included preprocessing queries, executing them multiple times, and evaluating ChatGPT responses against the databases and dermatologists. The ChatGPT-generated responses were analyzed statistically in a disease-drug matrix, considering disease-medication associations (Q -value) and expert evaluation. Results ChatGPT achieved a high 98.87% dermatologist approval rate for common dermatological medication recommendations. We evaluated its drug suggestions using the Q -value, showing that human expert validation agreement surpassed Q -value cutoff-based agreement. Varying cutoff values for disease-medication associations, a cutoff of 3 achieved 95.14% accurate prescriptions, 5 yielded 85.42%, and 10 resulted in 72.92%. While ChatGPT offered accurate drug advice, it occasionally included incorrect ATC codes, leading to issues like incorrect drug use and type, nonexistent codes, repeated errors, and incomplete medication codes. Conclusion ChatGPT provides medication recommendations as a second opinion in dermatology treatment, but its reliability and comprehensiveness need refinement for greater accuracy. In the future, integrating a medical domain-specific knowledge base for training and ongoing optimization will enhance the precision of ChatGPT's results. [ABSTRACT FROM AUTHOR]

Trypanosomosis is a tropical disease caused by various protozoan haemoparasites, which affects wild and domestic animals, the latter ones related to worldwide livestock production systems. Species such as Trypanosoma vivax and Trypanosoma evansi have been described using serological and molecular tools in several countries from South and Central America. However, Ecuador presents a relevant knowledge gap in the associated general epidemiology and risk factors of the disease. Therefore, the objective of this study was to determine the seroprevalence of trypanosomosis in cattle from different regions of Ecuador. 745 serum samples from 7 Coastal and 3 Amazon provinces were screened for IgG anti-Trypanosoma spp. antibodies, using an in-house indirect ELISA. The seropositivity was explored and associated with several variables such as sex, age, breed, region, management, and province, using statistical tools. The general seroprevalence of trypanosomosis was 19.1% (95% CI: 16.30–22.1%). The Amazonian provinces of Sucumbíos and Napo and the Coastal province of Esmeraldas presented the highest seroprevalence values of 36.7% (95% CI: 27.67–46.47%), 23.64% (95% CI: 16.06–32.68%) and 25% (95% CI: 15.99–35.94%), respectively. Statistical significance was found for the region, province, and management variables, indicating as relevant risk factors the extensive management and Amazon location of the cattle analyzed. Specific actions should be taken to identify the exact species on reservoirs and susceptible hosts, evaluate the implication of farm management and cattle movement as risk factors, and implement surveillance and treatment plans for affected herds. [ABSTRACT FROM AUTHOR]

Ensuring the integrity of the world’s forests is indispensable for mitigating climate change, combatting biodiversity loss, and protecting the livelihoods of rural communities. While many strategies have been developed to address deforestation across different geographic scales, measuring their impact against a fluctuating background of market-driven forest loss is notoriously challenging. In this article, we (1) asses deforestation in Ecuador using a dynamic, counterfactual baseline that excludes non-market factors, (2) identify periods of reduced and excess deforestation, and (3) assess the economic consequences of associated CO2 emissions using the social cost of carbon metric. We construct a counterfactual market-forces-only reference scenario by simulating heterogeneous profit-seeking agents making satisficing land-use allocation decisions under uncertainty. The model simulates a reference scenario for 2001–2022, a period encompassing dollarization, the beginning of a constitution granting inalienable rights to nature, and the launch of the largest payments for ecosystem services program in Ecuador’s history. On this period, total deforestation was approximately 20% lower than expected in a market-forces-only scenario (9540 vs.12,000 km2). The largest deviation occurred in 2001–2009, when observed deforestation was 43.6% lower than expected (3720 vs 6590 km2). From 2010 onwards, deforestation appears to be market-driven. We assess the economic value of avoided CO2 emissions at US $5.7 billion if the reduction is permanent, or US $3.1 billion considering a 1% risk of loss from 2022 onwards. We discuss contributing factors that likely shaped periods of reduced and excess deforestation and stress the need to use realistic baselines. [ABSTRACT FROM AUTHOR]

Pulse oximeters measure peripheral arterial oxygen saturation (SpO2) noninvasively, while the gold standard (SaO2) involves arterial blood gas measurement. There are known racial and ethnic disparities in their performance. BOLD is a dataset that aims to underscore the importance of addressing biases in pulse oximetry accuracy, which disproportionately affect darker-skinned patients. The dataset was created by harmonizing three Electronic Health Record databases (MIMIC-III, MIMIC-IV, eICU-CRD) comprising Intensive Care Unit stays of US patients. Paired SpO2 and SaO2 measurements were time-aligned and combined with various other sociodemographic and parameters to provide a detailed representation of each patient. BOLD includes 49,099 paired measurements, within a 5-minute window and with oxygen saturation levels between 70–100%. Minority racial and ethnic groups account for ~25% of the data – a proportion seldom achieved in previous studies. The codebase is publicly available. Given the prevalent use of pulse oximeters in the hospital and at home, we hope that BOLD will be leveraged to develop debiasing algorithms that can result in more equitable healthcare solutions. [ABSTRACT FROM AUTHOR]

This new editorial discusses the promise and challenges of successful integration of natural language processing methods into electronic health records for timely, robust, and fair oncology pharmacovigilance. [ABSTRACT FROM AUTHOR]

The concept of synthetic dimensions works particularly well in atomic physics, quantum optics, and photonics, where the internal degrees of freedom (Zeeman sublevels of the ground state, metastable excited states, or motional states for atoms, and angular momentum states or transverse modes for photons) provide the synthetic space. In this Perspective article we report on recent progress on studies of synthetic dimensions, mostly, but not only, based on the research realized around the Barcelona groups (ICFO, UAB), Donostia (DIPC), Poznan (UAM), Kraków (UJ), and Allahabad (HRI). We describe our attempts to design quantum simulators with synthetic dimensions, to mimic curved spaces, artificial gauge fields, lattice gauge theories, twistronics, quantum random walks, and more. Quantum simulators study important models of condensed matter and high-energy physics. Research on synthetic dimensions has paved the way for studying exotic phenomena, such as curved space-times, topological phases of matter, lattice gauge theories, twistronics without a twist, and more [ABSTRACT FROM AUTHOR]

Introduction: Acute kidney injury (AKI) requiring treatment with renal replacement therapy (RRT) is a common complication after admission to an intensive care unit (ICU) and is associated with significant morbidity and mortality. However, the prevalence of RRT use and the associated outcomes in critically patients across the globe are not well described. Therefore, we describe the epidemiology and outcomes of patients receiving RRT for AKI in ICUs across several large health system jurisdictions. Methods: Retrospective cohort analysis using nationally representative and comparable databases from seven health jurisdictions in Australia, Brazil, Canada, Denmark, New Zealand, Scotland, and the USA between 2006 and 2023, depending on data availability of each dataset. Patients with a history of end-stage kidney disease receiving chronic RRT and patients with a history of renal transplant were excluded. Results: A total of 4,104,480 patients in the ICU cohort and 3,520,516 patients in the mechanical ventilation cohort were included. Overall, 156,403 (3.8%) patients in the ICU cohort and 240,824 (6.8%) patients in the mechanical ventilation cohort were treated with RRT for AKI. In the ICU cohort, the proportion of patients treated with RRT was lowest in Australia and Brazil (3.3%) and highest in Scotland (9.2%). The in-hospital mortality for critically ill patients treated with RRT was almost fourfold higher (57.1%) than those not receiving RRT (16.8%). The mortality of patients treated with RRT varied across the health jurisdictions from 37 to 65%. Conclusion: The outcomes of patients who receive RRT in ICUs throughout the world vary widely. Our research suggests that differences in access to and provision of this therapy are contributing factors. Plain Language Summary: Renal replacement therapy (RRT) is a common treatment in critically ill patients with acute kidney injury. However, there are limited data on the epidemiology and outcomes associated with RRT use in patients in the intensive care unit (ICU) across the globe. In this study, we used data from ICU databases in seven different health jurisdictions from 2006 to 2023 to report the prevalence and the mortality of RRT in critically ill patients and in patients who are receiving mechanical ventilation. We found that 3.8% (n = 156,403) of included critically ill patients and 6.8% (n = 240,824) of mechanically ventilated patients were treated with RRT. The overall mortality in patients treated with RRT was 57.1% and mortality varied significant across the included datasets, ranging from 37 to 65%. Our results show that there are differences in RRT use and outcomes across different health jurisdictions. Further studies should be undertaken to determine why these differences in care exist. [ABSTRACT FROM AUTHOR]

Left atrial appendage occlusion (LAAO) is a percutaneous procedure to prevent thromboembolism in patients affected by atrial fibrillation. Despite its demonstrated efficacy, the LAA morphological complexity hinders the procedure, resulting in postprocedural drawbacks (device‐related thrombus and peri‐device leakage). Local anatomical features may cause difficulties in the device's positioning and affect the effectiveness of the device's implant. The current work proposes a detailed FE model of the LAAO useful to investigate implant scenarios and derive clinical indications. A high‐fidelity model of the Watchman FLX device and simplified parametric conduits mimicking the zone of the LAA where the device is deployed were developed. Device‐conduit interactions were evaluated by looking at clinical indicators such as device‐wall gap, possible cause of leakage, and device protrusion. As expected, the positioning of the crimped device before the deployment was found to significantly affect the implant outcomes: clinician's choices can be improved if FE models are used to optimize the pre‐operative planning. Remarkably, also the wall mechanical stiffness plays an important role. However, this parameter value is unknown for a specific LAA, a crucial point that must be correctly defined for developing an accurate FE model. Finally, numerical simulations outlined how the device's configuration on which the clinician relies to assess the implant success (i.e., the deployed configuration with the device still attached to the catheter) may differ from the actual final device's configuration, relevant for achieving a safe intervention. [ABSTRACT FROM AUTHOR]

Healthcare AI faces an ethical dilemma between selective and equitable deployment, exacerbated by flawed performance metrics. These metrics inadequately capture real-world complexities and biases, leading to premature assertions of effectiveness. Improved evaluation practices, including continuous monitoring and silent evaluation periods, are crucial. To address these fundamental shortcomings, a paradigm shift in AI assessment is needed, prioritizing actual patient outcomes over conventional benchmarking. [ABSTRACT FROM AUTHOR]

The comment discusses the potential of federated learning in intensive care medicine and its ability to address biases in clinical care practice. While the use of diverse and inclusive health datasets is seen as a necessary step in building fair machine learning algorithms, the comment argues that it may not be sufficient to overcome deeply embedded biases in medicine. The authors highlight various data issues that can contribute to disparities in care and patient outcomes, emphasizing the need for interdisciplinary collaboration to understand and address these biases. They caution against relying solely on federated learning, as it may lead to undiscovered data issues and spurious associations. The comment concludes by advocating for an equity-focused approach to data curation and analytics in intensive care. [Extracted from the article]

There is a critical need for widespread information dissemination of agricultural best practices in Africa. Literacy, language and resource barriers often impede such information dissemination. Culturally and linguistically localized, computer-animated training videos placed on YouTube and promoted through paid advertising is a potential tool to help overcome these barriers. The goal of this study is to assess the feasibility of reaching language-diverse populations in Africa using this new type of information dissemination channel. As a case study, cost estimates were obtained for YouTube ad campaigns of a video to prevent post-harvest loss through safe food storage using sanitized jerrycan containers. Seventy-three video variants were created for the most common 16 languages in Ghana, 35 languages in Kenya, and 22 languages in Nigeria. Using these videos, campaigns were deployed country wide or focused on zones of influence that represent economically underdeveloped regions known to produce beans suitable for jerrycan storage. Using data collected from YouTube ad campaigns, language-specific models were created for each country to estimate how many viewers could be reached per US dollar spent. Separate models were created to estimate the number of viewers who watched 25% and 75% of the video (most of video without end credits), reflecting different levels of engagement. For language campaigns with both country wide and zone of influence areas of deployment, separate region-specific models were created. Models showed that the estimated number of viewers per dollar spent varied considerably amongst countries and languages. On average, the expected number of viewers per dollar spent were 1.8 (Range = 0.2–7.3) for 25% watched and 0.8 (Range = 0.1–3.2) for 75% watched in Ghana, 1.2 (0.2–4.8) for 25% watched and 0.5 (Range = 0.1–2.0) for 75% watched in Kenya, and 0.4 (Range = 0.2–1.3) for 25% watched and 0.2 (Range = 0.1–0.5) for 75% watched in Nigeria. English versions of the video were the most cost-effective in reaching viewers in Ghana and Nigeria. In Kenya, English language campaigns ranked 28 (country wide) and 36 (zones of influence) out of 37 analyzed campaigns. Results also showed that many local language campaigns performed well, opening the possibility that targeted knowledge dissemination on topics of importance to local populations, is potentially cost effective. In addition, such targeted information dissemination appears feasible, even during regional and global crises when in-person training may not be possible. In summary, leveraging multilingual computer-animations and digital platforms such as YouTube shows promise for conducting large-scale agricultural education campaigns. The findings of the current study provides the justification to pursue a more rigorous prospective study to verify the efficacy of knowledge exchange and societal impact through this form of information dissemination channel. [ABSTRACT FROM AUTHOR]

Spectral Photon-Counting Computed Tomography (SPCCT) represents a groundbreaking advancement in X-ray imaging technology. The core innovation of SPCCT lies in its photon-counting detectors, which can count the exact number of incoming x-ray photons and individually measure their energy. The first part of this review summarizes the key elements of SPCCT technology, such as energy binning, energy weighting, and material decomposition. Its energy-discriminating ability represents the key to the increase in the contrast between different tissues, the elimination of the electronic noise, and the correction of beam-hardening artifacts. Material decomposition provides valuable insights into specific elements' composition, concentration, and distribution. The capability of SPCCT to operate in three or more energy regimes allows for the differentiation of several contrast agents, facilitating quantitative assessments of elements with specific energy thresholds within the diagnostic energy range. The second part of this review provides a brief overview of the applications of SPCCT in the assessment of various cardiovascular disease processes. SPCCT can support the study of myocardial blood perfusion and enable enhanced tissue characterization and the identification of contrast agents, in a manner that was previously unattainable. [ABSTRACT FROM AUTHOR]

Background: Perhaps nowhere else in the healthcare system than in the intensive care unit environment are the challenges to create useful models with direct time-critical clinical applications more relevant and the obstacles to achieving those goals more massive. Machine learning-based artificial intelligence (AI) techniques to define states and predict future events are commonplace activities of modern life. However, their penetration into acute care medicine has been slow, stuttering and uneven. Major obstacles to widespread effective application of AI approaches to the real-time care of the critically ill patient exist and need to be addressed. Main body: Clinical decision support systems (CDSSs) in acute and critical care environments support clinicians, not replace them at the bedside. As will be discussed in this review, the reasons are many and include the immaturity of AI-based systems to have situational awareness, the fundamental bias in many large databases that do not reflect the target population of patient being treated making fairness an important issue to address and technical barriers to the timely access to valid data and its display in a fashion useful for clinical workflow. The inherent "black-box" nature of many predictive algorithms and CDSS makes trustworthiness and acceptance by the medical community difficult. Logistically, collating and curating in real-time multidimensional data streams of various sources needed to inform the algorithms and ultimately display relevant clinical decisions support format that adapt to individual patient responses and signatures represent the efferent limb of these systems and is often ignored during initial validation efforts. Similarly, legal and commercial barriers to the access to many existing clinical databases limit studies to address fairness and generalizability of predictive models and management tools. Conclusions: AI-based CDSS are evolving and are here to stay. It is our obligation to be good shepherds of their use and further development. [ABSTRACT FROM AUTHOR]