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Lindsey A George,1,2 Rodney M Camire1–3 1Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; 2Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; 3Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Abstract: Hemophilia care has improved dramatically over the past 50 years, evolving from plasma concentrates, to purified plasma proteins, to recombinant clotting factors. These collective developments allowed for home delivery of on-demand and prophylactic treatment, resulting in the reduction of hemophilia morbidity and mortality and improved quality of life. Although efficacious in treating bleeding, conventional factor products' half-lives require frequent venipuncture, which remains a significant burden to patients. Despite the remarkable advances in hemophilia care, no improvements have, until now, been made to the pharmacokinetic properties of factor products. Multiple strategies have more recently been employed to generate novel bioengineered products that, with great hope, represent the next wave of progress in hemophilia care. The use of these products will undoubtedly raise important discussion about choosing conventional factor over new long-acting factor products. Incorporation of these therapies into clinical care is accompanied by unanswered safety questions that will likely be evaluated only in postmarketing surveillance analysis. Further, these products may change current treatment paradigms with unclear cost repercussions and feasibility. This paper will review efraloctocog alfa (FVIII-Fc) and its role in the treatment of hemophilia A. Keywords: hemophilia A, factor VIII, Fc fusion, bioengineered products, efraloctocog alfa

Abstract Low Earth Orbit (LEO) has emerged as a unique environment for evaluating altered stem cell properties in microgravity. LEO has become increasingly accessible for research and development due to progress in private spaceflight. Axiom Mission 2 (Ax-2) was launched as the second all-private astronaut mission to the International Space Station (ISS). Frozen human induced pluripotent stem cells (hiPSCs) expressing green fluorescent protein (GFP) under the SOX2 promoter, as well as fibroblasts differentiated from SOX2-GFP hiPSCs, were sent to the ISS. Astronauts then thawed and seeded both cell types into commercially available 96-well plates, which provided surface tension that reduced fluid movement out of individual wells and showed that hiPSCs or hiPSC-derived fibroblasts could survive either in suspension or attached to a Matrigel substrate. Furthermore, both cell types could be transfected with red fluorescent protein (RFP)-expressing plasmid. We demonstrate that hiPSCs and hiPSC-fibroblasts can be thawed in microgravity in off-the-shelf, commercially-available cell culture hardware, can associate into 3D spheroids or grow adherently in Matrigel, and can be transfected with DNA. This lays the groundwork for future biomanufacturing experiments in space.

This paper presents DeepTSF, a comprehensive machine learning operations (MLOps) framework aiming to innovate time series forecasting through workflow automation and codeless modeling. DeepTSF automates key aspects of the machine learning (ML) lifecycle, making it an ideal tool for data scientists and MLops engineers engaged in ML and deep learning (DL)-based forecasting. DeepTSF empowers users with a robust and user-friendly solution, while it is designed to seamlessly integrate with existing data analysis workflows, providing enhanced productivity and compatibility. The framework offers a front-end user interface (UI) suitable for data scientists, as well as other higher-level stakeholders, enabling comprehensive understanding through insightful visualizations and evaluation metrics. DeepTSF also prioritizes security through identity management and access authorization mechanisms. The application of DeepTSF in real-life use cases of the I-NERGY project has already proven DeepTSF’s efficacy in DL-based load forecasting, showcasing its significant added value in the electrical power and energy systems domain.

Nowadays, numerous governments have instituted diverse regulatory frameworks aimed at fostering the assimilation of sustainable energy sources characterized by reduced environmental footprints. Solar, wind, geothermal, and ocean energies were subject to extensive scrutiny, owing to their ecological merits. However, these sources exhibit pronounced temporal fluctuations. Notably, ocean dynamics offer vast energy reservoirs, with oceanic waves containing significant amounts of energy. In the Central American Pacific context, the exploration of wave energy resources is currently underway. Accurate numerical wave models are required for applied studies such as those focused on the estimation of exploitable wave power; and even more so in Central American region of the Pacific Ocean where existing numerical models simulations have so far relied on coarse resolution and limited validation field data. This work presents a high-resolution unstructured wave hindcast over the Central American Pacific region, implemented using the third-generation spectral wave model WAVEWATCH III over the period between 1979 and 2021. The results of the significant wave height have been bias-corrected on the basis of satellite information spanning 2005 to 2015, and further validation was performed using wave buoy and acoustic Doppler current profiler (ADCP) records located in the nearshore region of the Central America Pacific coast. After correction and validation of the wave hindcast, we employed the dataset for the evaluation and assessment of wave energy and its possible exploitation using different wave energy converters (WECs). This evaluation addressed the need to diverse the energy portfolio within the exclusive economic zones of Guatemala, El Salvador, Honduras, Nicaragua, Costa Rica, Panama, Colombia, and Ecuador in a sustainable manner. Moreover, a comprehensive analysis was carried out on the advantages of harnessing wave energy, juxtaposed with the imperative of regulatory frameworks and the current dearth of economic and environmental guidelines requisite for development within the region.

This article delves into the intricate interplay among digitalization, the COVID-19 pandemic, and the business environment in the Balkans, presenting a robust framework to comprehend and navigate these intertwined influences. As digital transformation swiftly reshapes global business landscapes, its accelerated adoption during the pandemic has proven crucial in adapting to new economic realities. This study investigates how businesses across the Balkans have navigated these dual pressures, examining their adoption of digital technologies, shifts in consumer behavior, and the resilience of entrepreneurial ventures amidst uncertainties induced by the crisis. The research is guided by the question: What is the interplay between digitalization and the pandemic in restarting business activities? Insights include associations found between digitalization and the DiGiX 2022 index, and the correlation between restarting business and the annual real GDP growth rate in 2023. Moreover, the study explores how the COVID-19 pandemic has impacted the Harmonized Index of Consumer Prices (HICP), reflecting its broader economic effects. By synthesizing these elements, the framework aims to offer strategic guidance to businesses and policymakers navigating the evolving digital landscape and pandemic-induced challenges in the Balkans.

Abstract The relationship between ammonia and liver-related complications (LRCs) in acute-on-chronic liver failure (ACLF) patients is not clearly established. This study aimed to evaluate the association between ammonia levels and LRCs in patients with ACLF. The study also evaluated the ability of ammonia in predicting mortality and progression of LRCs. The study prospectively recruited ACLF patients based on the APASL definition from the ACLF Research Consortium (AARC) from 2009 to 2019. LRCs were a composite endpoint of bacterial infection, overt hepatic encephalopathy (HE), and ascites. A total of 3871 cases were screened. Of these, 701 ACLF patients were enrolled. Patients with LRCs had significantly higher ammonia levels than those without. Ammonia was significantly higher in patients with overt HE and ascites, but not in those with bacterial infection. Multivariate analysis found that ammonia was associated with LRCs. Additionally, baseline arterial ammonia was an independent predictor of 30-day mortality, but it was not associated with the development of new LRCs within 30 days. In summary, baseline arterial ammonia levels are associated with 30-day mortality and LRCs, mainly overt HE and ascites in ACLF patients.

BackgroundAbout 20% of on-treatment patients with chronic hepatitis B (CHB) experienced low-level viraemia (LLV), which is associated with persistent low-grade inflammation, fibrosis progression, and increased risk of hepatocellular carcinoma. We aimed to investigate the high-risk factors related to LLV.MethodsIn this retrospective study, patients receiving entecavir (ETV) treatment from January 2018 to January 2023 were enrolled, and were divided into a LLV (HBV DNA 20-2000 IU/mL) cohort and a complete virological response (CVR) (HBV DNA < 20 IU/mL) cohort according to the virological response at week 48 posttreatment. Treatment baseline characteristics were retrieved from electronic medical records. Multivariate logistic regression was performed.ResultsTotally, 1653 patients were enrolled, male patients accounted for 73.0%; the median age was 44 years; the mean HBV DNA level was 5.9 Log10 IU/ml. Among them, 472 (28.6%) experienced LLV. Multivariate analysis showed that HBeAg positivity (OR = 2.650, 95% CI: 2.000-3.511, p < 0.001), HBV DNA ≥ 6.0 Log10 IU/mL (OR = 1.370, 95% CI: 1.054-1.780, p = 0.019), qHBsAg ≥ 9000 IU/mL (OR = 4.472, 95% CI: 3.410-5.866, p < 0.001), cirrhosis (OR = 1.650, 95% CI: 1.234-2.207, P = 0.001), LSM ≥ 13.0 kPa (OR = 1.644, 95% CI: 1.203-2.246, p = 0.002), and PLT < 100×109/L (OR = 1.450, 95% CI: 1.094-1.922, p = 0.010) at baseline were related to the development of LLV.ConclusionsHigh HBV DNA/HBsAg quantification/LSM, low PLT, HBeAg positivity, and liver cirrhosis were high-risk factors associated with LLV in patients receiving entecavir treatment.

Introduction: Data regarding quality of life (QoL) of oncologic patients experiencing dermatologic immune-related adverse events (dirAEs)and their course after dermatologic intervention are scarce. Objectives To assess the impact of dirAEs on patients' QoL and to investigate the correlation between dermatologic and oncologic indexes used for estimating QoL. Methods We enrolled oncologic patients with dirAEs managed in two supportive oncodermatology outpatient clinics in Greece. Patient-reported outcomes included DLQI, EORTC-QLQ-C30 and Numerical Rating Scale for pruritus (pNRS). Results Overall, 110 patients were enrolled in the study. Mean(SD) DLQI and pNRS scores were 15.54 (5.44) and7.25 (2.95), correspondingly, while functional, symptom and summary scores of EORTC-C30 were 79.17 (2.11), 17.66 (3.60) and 80.67 (3.08), respectively. After therapeutic interventions, there was a statistically significant decrease in DLQI scores after1st intervention compared to baseline, and 2nd intervention compared to 1st [mean (SD) decrease 4.38 (2.91), p

BackgroundStarting in 2010, the epidermal growth factor receptor (EGFR) kinase inhibitors erlotinib and gefitinib were introduced into routine use in Aotearoa New Zealand (NZ) for treating advanced lung cancer, but their impact in this setting is unknown. ObjectiveThe study described in this protocol aims to understand the effectiveness and safety of these new personalized lung cancer treatments and the contributions made by concomitant medicines and other factors to adverse outcomes in the general NZ patient population. A substudy aimed to validate national electronic health databases as the data source and the methods for determining patient eligibility and identifying outcomes and variables. MethodsThis study will include all NZ patients with advanced EGFR mutation–positive lung cancer who were first dispensed erlotinib or gefitinib before October 1, 2020, and followed until death or for at least 1 year. Routinely collected health administrative and clinical data will be collated from national electronic cancer registration, hospital discharge, mortality registration, and pharmaceutical dispensing databases by deterministic data linkage using National Health Index numbers. The primary effectiveness and safety outcomes will be time to treatment discontinuation and serious adverse events, respectively. The primary variable will be high-risk concomitant medicines use with erlotinib or gefitinib. For the validation substudy (n=100), data from clinical records were compared to those from national electronic health databases and analyzed by agreement analysis for categorical data and by paired 2-tailed t tests for numerical data. ResultsIn the validation substudy, national electronic health databases and clinical records agreed in determining patient eligibility and for identifying serious adverse events, high-risk concomitant medicines use, and other categorical data with overall agreement and κ statistic of >90% and >0.8000, respectively; for example, for the determination of patient eligibility, the comparison of proxy and standard eligibility criteria applied to national electronic health databases and clinical records, respectively, showed overall agreement and κ statistic of 96% and 0.8936, respectively. Dates for estimating time to treatment discontinuation and other numerical variables and outcomes showed small differences, mostly with nonsignificant P values and 95% CIs overlapping with zero difference; for example, for the dates of the first dispensing of erlotinib or gefitinib, national electronic health databases and clinical records differed on average by approximately 4 days with a nonsignificant P value of .33 and 95% CIs overlapping with zero difference. As of May 2024, the main study is ongoing. ConclusionsA protocol is presented for a national whole-of-patient-population retrospective cohort study designed to describe the safety and effectiveness of erlotinib and gefitinib during their first decade of routine use in NZ for treating EGFR mutation–positive lung cancer. The validation substudy demonstrated the feasibility and validity of using national electronic health databases and the methods for determining patient eligibility and identifying the study outcomes and variables proposed in the study protocol. Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12615000998549; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=368928 International Registered Report Identifier (IRRID)DERR1-10.2196/51381

This survey explores the transformative role of Generative Artificial Intelligence (GenAI) in enhancing the trustworthiness, reliability, and security of autonomous systems such as Unmanned Aerial Vehicles (UAVs), self-driving cars, and robotic arms. As edge robots become increasingly integrated into daily life and critical infrastructure, the complexity and connectivity of these systems introduce formidable challenges in ensuring security, resilience, and safety. GenAI advances from mere data interpretation to autonomously generating new data, proving critical in complex, context-aware environments like edge robotics. Our survey delves into the impact of GenAI technologies—including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Transformer-based models, and Large Language Models (LLMs)—on cybersecurity, decision-making, and the development of resilient architectures. We categorize existing research to highlight how these technologies address operational challenges and innovate predictive maintenance, anomaly detection, and adaptive threat response. Our comprehensive analysis distinguishes this work from existing reviews by mapping out the applications, challenges, and technological advancements of GenAI and their impact on creating secure frameworks for autonomous systems. We discuss significant challenges and future directions for integrating these technologies within security frameworks to address the evolving landscape of cyber-physical threats, underscoring the potential of GenAI to make autonomous systems more adaptive, secure, and efficient.

Abstract The unique physiological and genetic characteristics of individuals influence their reactions to different dietary constituents and nutrients. This notion is the foundation of personalized nutrition. The field of nutrigenetics has witnessed significant progress in understanding the impact of genetic variants on macronutrient and micronutrient levels and the individual's responsiveness to dietary intake. These variants hold significant value in facilitating the development of personalized nutritional interventions, thereby enabling the effective translation from conventional dietary guidelines to genome-guided nutrition. Nevertheless, certain obstacles could impede the extensive implementation of individualized nutrition, which is still in its infancy, such as the polygenic nature of nutrition-related pathologies. Consequently, many disorders are susceptible to the collective influence of multiple genes and environmental interplay, wherein each gene exerts a moderate to modest effect. Furthermore, it is widely accepted that diseases emerge because of the intricate interplay between genetic predisposition and external environmental influences. In the context of this specific paradigm, the utilization of advanced "omic" technologies, including epigenomics, transcriptomics, proteomics, metabolomics, and microbiome analysis, in conjunction with comprehensive phenotyping, has the potential to unveil hitherto undisclosed hereditary elements and interactions between genes and the environment. This review aims to provide up-to-date information regarding the fundamentals of personalized nutrition, specifically emphasizing the complex triangulation interplay among microbiota, dietary metabolites, and genes. Furthermore, it highlights the intestinal microbiota's unique makeup, its influence on nutrigenomics, and the tailoring of dietary suggestions. Finally, this article provides an overview of genotyping versus microbiomics, focusing on investigating the potential applications of this knowledge in the context of tailored dietary plans that aim to improve human well-being and overall health.

The research problem of this systematic review was whether green 6G networks can integrate energy-efficient Industrial Internet of Things (IIoT) in terms of distributed artificial intelligence, green 6G pervasive edge computing communication networks and big-data-based intelligent decision algorithms. We show that sensor data fusion can be carried out in energy-efficient IoT smart industrial urban environments by cooperative perception and inference tasks. Our analyses debate on 6G wireless communication, vehicular IoT intelligent and autonomous networks, and energy-efficient algorithm and green computing technologies in smart industrial equipment and manufacturing environments. Mobile edge and cloud computing task processing capabilities of decentralized network control and power grid system monitoring were thereby analyzed. Our results and contributions clarify that sustainable energy efficiency and green power generation together with IoT decision support and smart environmental systems operate efficiently in distributed artificial intelligence 6G pervasive edge computing communication networks. PRISMA was used, and with its web-based Shiny app flow design, the search outcomes and screening procedures were integrated. A quantitative literature review was performed in July 2024 on original and review research published between 2019 and 2024. Study screening, evidence map visualization, and data extraction and reporting tools, machine learning classifiers, and reference management software were harnessed for qualitative and quantitative data, collection, management, and analysis in research synthesis. Dimensions and VOSviewer were deployed for data visualization and analysis.

Coronary artery disease (CAD) constitutes a leading cause of morbidity and mortality worldwide. Percutaneous coronary intervention (PCI) is indicated in a significant proportion of CAD patients, either to improve prognosis or to relieve symptoms not responding to optimal medical therapy. Thus the annual number of patients undergoing PCI in a given geographical area could serve as a surrogate marker of the total CAD burden there. The aim of this study was to analyze the potential, spatial patterns of PCItreated CAD patients in Crete. We evaluated data from all patients subjected to PCI at the island’s sole reference centre for cardiac catheterization within a 4-year study period (2013-2016). The analysis focused on regional variations of yearly PCI rates, as well as on the effect of several clinical parameters on the severity of the coronary artery stenosis treated with PCI across Crete. A spatial database within the ArcGIS environment was created and an analysis carried out based on global and local regression using ordinary least squares (OLS) and geographically weighted regression (GWR), respectively. The results revealed significant inter-municipality variation in PCI rates and thus potentially CAD burden, while the degree and direction of correlation between key clinical factors to coronary stenosis severity demonstrated specific geographical patterns. These preliminary results could set the basis for future research, with the ultimate aim to facilitate efficient healthcare strategies planning.

Central bank digital currencies (CBDCs) have been growing in popularity since 2018, as worldwide countries explore their impact and implementation options. This article analyzes the state of research around central bank digital currencies and the evolving landscape of CBDCs, and explores emerging areas of research and trends by using the PRISMA method and VOSviewer, with the goal of showing the main opportunities and challenges related to them. AMSTAR, DistillerSR, Eppi-Reviewer, ROBIS, and SRDR were the screening and quality evaluation tools employed for study eligibility criteria, design screening and content selection, text analysis data extraction, methodological quality predictors, and reliable and reproducible evidence assessment. A total of 1024 articles on central bank digital currencies were identified in Scopus and the Web of Science, out of which 747 have been included in the review (documents which were not in English language and not categorized as journal articles were excluded). Through an analysis of the relevant literature, the study categorizes CBDC research into positive, negative and neutral research, with a particular focus on sustainability issues, and conducts a keyword co-occurrence analysis using VOSviewer, following a narrowing down of the relevant articles to be included in the study by applying the PRISMA framework. This generates an overall view for experts and researchers who can use the main analyzed features of CBDCs and adapt them accordingly, taking into account relevant macroeconomic characteristics. The study highlights the need to continue interdisciplinary research, by adapting the research and CBDC characteristics to keep up with the latest technologies and with the shift towards green finance, and explores the elaborate relationship between finance, technology and sustainability.

Aim Anakinra, an anti IL-1 agent targeting IL-1 alfa and beta, is available for the treatment of recurrent pericarditis in cases with corticosteroid dependence and colchicine resistance after failure of conventional therapies. However, it is unclear if the combination with colchicine, a non-specific inhibitor of the inflammasome targeting the same inflammatory pathway of IL-1, could provide additional benefit to prevent further recurrences. The aim of the present observational study is to assess whether the addition of colchicine on top of anakinra could prolong the time to first recurrence and prevent recurrences better than anakinra alone.Methods International, all-comers, multicentre, retrospective observational cohort study analysing all consecutive patients treated with anakinra for corticosteroid-dependent and colchicine-resistant recurrent pericarditis. The efficacy endpoint was recurrence rate and the time to the first recurrence.Results A total of 256 patients (mean age 45.0±15.4 years, 65.6% females, 80.9% with idiopathic/viral aetiology) were included. 64 (25.0%) were treated with anakinra as monotherapy while 192 (75.0%) with both anakinra and colchicine. After a follow-up of 12 months, 56 (21.9%) patients had recurrences. Patients treated with colchicine added to anakinra had a lower incidence of recurrences (respectively, 18.8% vs 31.3%; p=0.036) and a longer event-free survival (p=0.025). In multivariable analysis, colchicine use prevented recurrences (HR 0.52, 95% CI 0.29 to 0.91; p=0.021).Conclusions The addition of colchicine on top of anakinra treatment could be helpful to reduce recurrences and prolong the recurrence-free survival.

IntroductionHeart transplant remains the gold standard treatment for patients with advanced heart failure. However, the list of patients waiting for a heart transplant continues to increase. We have developed a portable hypothermic oxygenated machine perfusion device, the VP.S ENCORE®, to extend the allowable preservation time. The purpose of this study was to test the efficacy of the VP.S. ENCORE® using deceased donors derived hearts.MethodsHearts from brain-dead donors not utilized for transplant (n = 11) were offered for research from the Texas Organ Sharing Alliance (TOSA), South and Central Texas' Organ Procurement Organization (OPO) and were preserved in the VP.S ENCORE® for 4 (n = 2), 6 (n = 3), and 8 (n = 3) hours or were kept in static cold storage (SCS) (n = 3). After preservation, the hearts were placed in an isolated heart Langendorff model for reperfusion and evaluated for cardiac function.ResultsThe mean donor age was 37.82 ± 12.67 with the youngest donor being 19 and the oldest donor being 58 years old. SCS hearts mean weight gain (%) was −1.4 ± 2.77, while perfused at 4 h was 5.6 ± 6.04, perfused at 6 h 2.1 ± 6.04, and 8 h was 7.2 ± 10.76. Venous and arterial lactate concentrations were less than 2.0 mmol/L across all perfused hearts. Left ventricular contractility (+dPdT, mmHg/s) for 4 h (1,214 ± 1,064), 6 (1,565 ± 141.3), and 8 h (1,331 ± 403.6) were within the range of healthy human heart function. Thus, not significant as compared to the SCS group (1,597 ± 342.2). However, the left ventricular relaxation (mmHg/s) was significant in 6-hour perfused heart (p

BackgroundGiven that signage, messaging, and advertisements (ads) are the gateway to many interventions in suicide prevention, it is important that we understand what type of messaging works best for whom. ObjectiveWe investigated whether explicitly mentioning suicide increases engagement using internet ads by investigating engagement with campaigns with different categories of keywords searched, which may reflect different cognitive states. MethodsWe ran a 2-arm study Australia-wide, with or without ads featuring explicit suicide wording. We analyzed whether there were differences in engagement for campaigns with explicit and nonexplicit ads for low-risk (distressed but not explicitly suicidal), high-risk (explicitly suicidal), and help-seeking for suicide keywords. ResultsOur analyses revealed that having explicit wording has opposite effects, depending on the search terms used: explicit wording reduced the engagement rate for individuals searching for low-risk keywords but increased engagement for those using high-risk keywords. ConclusionsThe findings suggest that individuals who are aware of their suicidality respond better to campaigns that explicitly use the word “suicide.” We found that individuals who search for low-risk keywords also respond to explicit ads, suggesting that some individuals who are experiencing suicidality search for low-risk keywords.

Abstract Background Flavored e-cigarettes remain a controversial topic with regulators planning or already implementing restrictions worldwide. In this study, we examined patterns of flavor use in e-cigarettes among a convenience sample of US adult vapers. Methods Participants aged ≥ 18 years who reported ever using an e-cigarette were included in the study (N = 69,233) and responded to an online questionnaire. Their smoking status was recorded as well as patterns of flavor use at e-cigarette use initiation, at the time of the survey and at the time of smoking cessation (for participants who used to smoke and were using e-cigarettes at the time of quitting). Results The most popular flavors at e-cigarette use initiation were fruit (82.8%), followed by dessert/pastry/bakery (68.6%) and candy/chocolate/sweet (52.2%). Slightly higher prevalence of using fruit and dessert/pastry/bakery flavors was observed in those who never smoked compared to those who were currently and formerly smoking. Tobacco flavors were used by 20.8% of the participants and was by far the least prevalent among participants who never smoked. Similar patterns were observed with participants’ choices at the time of the survey, but tobacco flavor use was substantially reduced (7.7%). Only 2.1% reported tobacco as the single most often used flavor. The most prevalent flavor at the time of quitting smoking was again fruit (83.3%), followed by dessert/pastry/bakery (68.0%) and candy/chocolate/sweet (44.5%). These flavors were considered the most helpful for quitting smoking. Tobacco flavor use at the time of smoking cessation was reported by 15.0%, while 9.3% considered it helpful for quitting smoking. Conclusion Non-tobacco flavors were popular among the US adult vapers who participated in the study, and were popular choices at the time of quitting smoking for those who formerly smoked. Tobacco flavor use prevalence was low and was further reduced over time. Regulators should consider the flavor choice of adult consumers, especially those who quit smoking, when preparing legislation on flavored e-cigarettes.

Abstract Background Combining short-acting nicotine replacement therapy with varenicline increases smoking cessation rates compared with varenicline alone, but not all people tolerate these medications or find them helpful. We aim to investigate the therapeutic potential of an analogous combination, by evaluating the effectiveness, safety, and acceptability of combining nicotine salt e-cigarettes with cytisine, compared to nicotine salt e-cigarettes or cytisine only, on smoking abstinence at six months. Methods A pragmatic, community-based, investigator-blinded, randomised superiority trial design will be utilised. Eligible participants will be people who smoke daily (N = 800, 90% power) from throughout New Zealand, who are: aged ≥ 18 years, motivated to quit in the next two weeks, able to provide online consent, willing to use e-cigarettes and/or cytisine, and have daily access to a mobile phone. Recruitment will utilise multi-media advertising. Participants will be randomised (3:3:2 ratio) to 12 weeks of: 1) e-cigarettes (closed pod system, 3% nicotine salt, tobacco flavour) plus cytisine; 2) e-cigarettes alone, or 3) cytisine alone. All groups will receive a six-month, text-message-based behavioural support programme. The primary outcome is self-reported, biochemically verified, continuous abstinence at six months post-quit date. Secondary outcomes, measured at quit date, then one, three, six, and 12 months post-quit date, include self-reported continuous abstinence, 7-day point prevalence abstinence, cigarettes smoked per day, withdrawal and urge to smoke, time to (re)lapse, treatment use and compliance, treatment crossover, dual-use, use of other cessation products, change in e-cigarette products, continuation of product use, acceptability, change in health state, health-related quality of life, change in body mass index, adverse events, and cost per quitter. Discussion Pragmatic trials are of particular value as they reflect the ‘real world’ impact of interventions. The trial will provide some of the first evidence on the effectiveness of combining nicotine salt e-cigarettes with cytisine for smoking cessation, in a country with strong tobacco control policy. Findings will be incorporated into relevant systematic reviews, informing practice and policy. Trial registration NCT05311085 ClinicalTrials.gov. Registered 5th April, 2022.

X-linked Charcot-Marie-Tooth disease type 1 (CMT1X) is a demyelinating neuropathy resulting from loss-of-function mutations affecting the GJB1/connexin 32 (Cx32) gene. We previously showed functional and morphological improvement in Gjb1-null mice following AAV9-mediated delivery of human Cx32 driven by the myelin protein zero (Mpz) promoter in Schwann cells. However, CMT1X mutants may interfere with virally delivered wild-type (WT) Cx32. To confirm the efficacy of this vector also in the presence of CMT1X mutants, we delivered AAV9-Mpz-GJB1 by lumbar intrathecal injection in R75W/Gjb1-null and N175D/Gjb1-null transgenic lines expressing Golgi-retained mutations, before and after the onset of the neuropathy. Widespread expression of virally delivered Cx32 was demonstrated in both genotypes. Re-establishment of WT Cx32 function resulted in improved muscle strength and increased sciatic nerve motor conduction velocities in all treated groups from both mutant lines when treated before as well as after the onset of the neuropathy. Furthermore, morphological analysis showed improvement of myelination and reduction of inflammation in lumbar motor roots and peripheral nerves. In conclusion, this study provides proof of principle for a clinically translatable gene therapy approach to treat CMT1X before and after the onset of the neuropathy, even in the presence of endogenously expressed Golgi-retained Cx32 mutants.

Refractory recurrent pericarditis is a troublesome condition that severely impairs the quality of life of affected patients and significantly increases healthcare spending. Until recently, therapeutic options included only a few medications and most of the patients resorted to chronic glucocorticoid treatment with steroid dependence. In the most recent decade, the introduction of interleukin-1 blockers in clinical practice has revolutionized the treatment of glucocorticoid-dependent and colchicine-resistant recurrent pericarditis due to their excellent efficacy and good safety profile. The rationale for the introduction of this class of medications in clinical practice is the autoinflammatory nature of recurrent pericarditis in a substantial rate of cases, with interleukin-1 being the main pro-inflammatory cytokine involved in this context. This review aims to discuss the contemporary available evidence from original research and real-world data on interleukin-1 blocker use in refractory recurrent pericarditis, in terms of indications, mechanism of action, efficacy, side effects, and recommended treatment protocols. Moreover, novel treatment proposals, such as hydroxychloroquine, beta blockers, and cannabidiol, which showed encouraging preliminary results, are addressed. Finally, gaps in knowledge, unmet needs, and future perspectives related to recurrent pericarditis are thoroughly discussed.

Paediatric cardiomyopathies form a heterogeneous group of disorders characterized by structural and electrical abnormalities of the heart muscle, commonly due to a gene variant of the myocardial cell structure. Mostly inherited as a dominant or occasionally recessive trait, they might be part of a syndromic disorder of underlying metabolic or neuromuscular defects or combine early developing extracardiac abnormalities (i.e., Naxos disease). The annual incidence of 1 per 100,000 children appears higher during the first two years of life. Dilated and hypertrophic cardiomyopathy phenotypes share an incidence of 60% and 25%, respectively. Arrhythmogenic right ventricular cardiomyopathy (ARVC), restrictive cardiomyopathy, and left ventricular noncompaction are less commonly diagnosed. Adverse events such as severe heart failure, heart transplantation, or death usually appear early after the initial presentation. In ARVC patients, high-intensity aerobic exercise has been associated with worse clinical outcomes and increased penetrance in at-risk genotype-positive relatives. Acute myocarditis in children has an incidence of 1.4–2.1 cases/per 100,000 children per year, with a 6–14% mortality rate during the acute phase. A genetic defect is considered responsible for the progression to dilated cardiomyopathy phenotype. Similarly, a dilated or arrhythmogenic cardiomyopathy phenotype might emerge with an episode of acute myocarditis in childhood or adolescence. This review provides an overview of childhood cardiomyopathies focusing on clinical presentation, outcome, and pathology.

Enabling education programs in Australia assist students, who would otherwise have been excluded from higher education, to transition into undergraduate study. These programs emerged independently in response to the needs of individual universities and the varying cohorts of students they serve. The exclusion of these programs from the Australian Qualifications Framework (AQF) has meant they remain unregulated, with no national framework for standards. The development of academic standards is a dynamic, consensus driven process, and benchmarking provides a method through which academics from across institutions can work in partnership to reach shared understandings and improve and align practices. This practice report outlines the results of the first comprehensive cross-institutional benchmarking project involving nine Australian universities and demonstrates there is shared understanding of the standards of enabling programs between institutions. These findings will contribute to the establishment of national standards for enabling programs in Australia.

Introduction Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved.Methods and analysis The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0–17 years only (component A), three centres conduct surveillance in young adults aged 18–44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression.Ethics and dissemination The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA.

Accurate and timely evaluation and assessment of emission data and its impact on environmental status has been a key challenge due to the conventional manual approach utilized for independently computing most emission parameters. To resolve this long-standing issue, we proposed an Artificial Intelligence (AI)-driven Decision Tree model to adequately classify Environmental Protection Agency (EPA) status based on multiple Emission Parameters. The model's performance was systematically evaluated using multiple emission parameters obtained from a two-stroke motorcycle dataset collected in Nigeria across various metrics such as K-S Statistics, Confusion Matrix, Correlation Heat Map, Decision Tree, Validation Curve, and Threshold Plot. The K-S Statistics plot's experimental results showed a considerable correlation between HC, CO, and the target variable, with values ranging from 0.75 to 0.80. At the same time, CO2 and O2 do not correlate with the target variable with values between 0.00 and 0.09. The Confusion Matrix revealed that the proposed model has an overall accuracy of 99.9% with 481 true positive predictions and 75 true negative predictions, indicating the effectiveness of the proposed AI-driven model. In conclusion, our proposed AI-driven model can effectively classify EPA status based on multiple emission parameters with high accuracy, which may spur positive advancement in policy enhancement for proper environmental management.

Abstract We explore a variety of composite topological structures that arise from the spontaneous breaking of SO(10) to SU(3) c × U(1) em via one of its maximal subgroups SU(5) × U(1) χ , SU(4) c × SU(2) L × SU(2) R , and SU(5) × U(1) X (also known as flipped SU(5)). They include i) a network of ℤ strings which develop monopoles and turn into necklaces with the structure of ℤ2 strings, ii) dumbbells connecting two different types of monopoles, or monopoles and antimonpoles, iii) starfish-like configurations, iv) polypole configurations, and v) walls bounded by a necklace. We display these structures both before and after the electroweak breaking. The appearance of these composite structures in the early universe and their astrophysical implications including gravitational wave emission would depend on the symmetry breaking patterns and scales, and the nature of the associated phase transitions.

Strut-based or open lattice materials are a category of advanced materials used in medical and aerospace applications due to their properties, such as high strength-to-weight ratio and energy absorption capability. The most prominent method for the fabrication of lattice materials is the Laser-based Powder Bed Fusion (L-PBF) additive manufacturing (AM) process, due to its ability to produce parts of complex geometries. The current work presents an efficient meso-scale finite element (FE) modeling methodology of the L-PBF process demonstrated in the fabrication of body-centered cubic (BCC) lattice materials. The modeling efficiency is gained through an adaptive mesh refinement technique, which results in accurate and efficient prediction of the temperature field during the process evolution. To examine the efficiency of the modeling method, the computational time is compared with that of a conventional FE simulation, based on the element and birth technique. The temperature history difference between the two approaches is minor but the adaptive mesh modeling requires only a small portion of the simulation time of the conventional model. In addition, the computational results present a good correlation with the available experimental measurements for various process parameters validating the presented efficient method.

Performance measurement refers to the systematic evaluation and analysis of the performance and results of business processes, initiatives, or strategies. This study discusses the crucial role of communication using signaling theory in employer branding in the context of the social economy organization (SEO). The aim is to measure employee satisfaction in concrete terms and to determine the status quo of the communication culture of the organization under investigation in order to develop an employer branding strategy based on the results. The authors use an employee survey as a quantitative research method and limit the data collection to the EU member state of Germany considering the research background. The results provide insights into the specific communication policy in relation to employer branding. The focus here is on (digital) communication. Organizations need to understand how communication strategies directly influence the perception of the employer brand in the social economy. Furthermore, practical implications are derived in order to increase employer attractiveness. Concrete recommendations of action for SEOs should help them be successful in the competition for qualified specialists and talent.

IntroductionAutoimmune disorders (ADs) are a group of about 80 disorders that occur when self-attacking autoantibodies are produced due to failure in the self-tolerance mechanisms. ADs are polygenic disorders and associations with genes both in the human leukocyte antigen (HLA) region and outside of it have been described. Previous studies have shown that they are highly comorbid with shared genetic risk factors, while epidemiological studies revealed associations between various lifestyle and health-related phenotypes and ADs.MethodsHere, for the first time, we performed a comparative polygenic risk score (PRS) - Phenome Wide Association Study (PheWAS) for 11 different ADs (Juvenile Idiopathic Arthritis, Primary Sclerosing Cholangitis, Celiac Disease, Multiple Sclerosis, Rheumatoid Arthritis, Psoriasis, Myasthenia Gravis, Type 1 Diabetes, Systemic Lupus Erythematosus, Vitiligo Late Onset, Vitiligo Early Onset) and 3,254 phenotypes available in the UK Biobank that include a wide range of socio-demographic, lifestyle and health-related outcomes. Additionally, we investigated the genetic relationships of the studied ADs, calculating their genetic correlation and conducting cross-disorder GWAS meta-analyses for the observed AD clusters.ResultsIn total, we identified 508 phenotypes significantly associated with at least one AD PRS. 272 phenotypes were significantly associated after excluding variants in the HLA region from the PRS estimation. Through genetic correlation and genetic factor analyses, we identified four genetic factors that run across studied ADs. Cross-trait meta-analyses within each factor revealed pleiotropic genome-wide significant loci.DiscussionOverall, our study confirms the association of different factors with genetic susceptibility for ADs and reveals novel observations that need to be further explored.

Na atual fase pandêmica da COVID-19, quase todas as instituições de ensino foram forçadas a passar por uma transformação abrupta de ensino presencial para ensino remoto geralmente fundamentado na adoção e uso de novas tecnologias educacionais. Especificamente, no contexto dos estudantes com autismo, entende-se como pertinente analisar estudos relacionados a possibilidades destas tecnologias no âmbito da melhoria (ou não) da compreensão conceitual destes estudantes. Neste contexto, o presente trabalho tem como objetivo levantar, analisar e discutir práticas de uso de laboratórios remotos e seu impacto na aprendizagem de estudantes autista, à luz da Teoria da Distância Transacional. Para tal, foi feita uma revisão de narrativa de literatura. Foram examinados 32 artigos encontrados nas bases de dados Google Scholar, IEEE Xplore, Wiley InterScience e Science Direct–Elsevier. Como resultado, as evidências demonstraram que, no contexto da Teoria Transacional, os laboratórios remotos tendem a potencializar a efetividade dos métodos de ensino e melhorias na aprendizagem dos estudantes com transtorno do espectro autista.

Sporadically occurring malignant peripheral nerve sheath tumours (MPNSTs) can have a variety of genomic alterations including altered NF1, leading to activation of the RAS-RAF-MEK-ERK signalling pathway. Trametinib is an inhibitor of MEK1 and MEK2. Here we present a case of a patient diagnosed with sporadic MPNST with an identified NF1 gene treated successfully with trametinib.

Objective We sought to compare the incidence of early-onset sepsis (EOS) in infants ≥34 weeks’ gestation identified >24 hours after birth, in hospitals using the Kaiser Permanente Sepsis Risk Calculator (SRC) with hospitals using the National Institute for Health and Care Excellence (NICE) guidance.Design and setting Prospective observational population-wide cohort study involving all 26 hospitals with neonatal units colocated with maternity services across London (10 using SRC, 16 using NICE).Participants All live births ≥34 weeks’ gestation between September 2020 and August 2021.Outcome measures EOS was defined as isolation of a bacterial pathogen in the blood or cerebrospinal fluid (CSF) culture from birth to 7 days of age. We evaluated the incidence of EOS identified by culture obtained >24 hours to 7 days after birth. We also evaluated the rate empiric antibiotics were commenced >24 hours to 7 days after birth, for a duration of ≥5 days, with negative blood or CSF cultures.Results Of 99 683 live births, 42 952 (43%) were born in SRC hospitals and 56 731 (57%) in NICE hospitals. The overall incidence of EOS (24 hours was 2.3/100 000 (n=1) for SRC vs 7.1/100 000 (n=4) for NICE (OR 0.5, 95% CI (0.1 to 2.7)). This corresponded to (1/20) 5% (SRC) vs (4/45) 8.9% (NICE) of EOS cases (χ=0.3, p=0.59). Empiric antibiotics were commenced >24 hours to 7 days after birth in 4.4/1000 (n=187) for SRC vs 2.9/1000 (n=158) for NICE (OR 1.5, 95% CI (1.2 to 1.9)). 3111 (7%) infants received antibiotics in the first 24 hours in SRC hospitals vs 8428 (15%) in NICE hospitals.Conclusion There was no significant difference in the incidence of EOS identified >24 hours after birth between SRC and NICE hospitals. SRC use was associated with 50% fewer infants receiving antibiotics in the first 24 hours of life.

Recurrent pericarditis is a problematic clinical condition that impairs the quality of life of the affected patients due to the need for repeated hospital admissions, emergency department visits, and complications from medications, especially glucocorticoids. Unfortunately, available treatments for recurrent pericarditis are very limited, including only a handful of medications such as aspirin/NSAIDs, glucocorticoids, colchicine, and immunosuppressants (such as interleukin-1 (IL-1) blockers, azathioprine, and intravenous human immunoglobulins). Until recently, the clinical experience with the latter class of medications was very limited. Nevertheless, in the last decade, experience with IL-1 blockers has consistently grown, and valid clinical data have emerged from randomized clinical trials. Accordingly, IL-1 blockers are a typical paradigm shift in the treatment of refractory recurrent pericarditis with a clearly positive cost/benefit ratio for those unfortunate patients with multiple recurrences. A drawback related to the above-mentioned medications is the absence of universally accepted and established treatment protocols regarding the full dose administration period and the need for a tapering protocol for individual medications. Another concern is the need for long-standing treatments, which should be discussed with the patients. The above-mentioned unmet needs are expected to be addressed in the near future, such as further insights into pathophysiology and an individualized approach to affected patients.

Future liquid hydrogen-powered aircraft requires the design and optimization of a large number of systems and subsystems, with cryogenic tanks being one of the largest and most critical. Considering previous space applications, these tanks are usually stiffened by internal members such as stringers, frames, and stiffeners resulting in a complex geometry that leads to an eventual reduction in weight. Cryogenic tanks experience a variety of mechanical and thermal loading conditions and are usually constructed out of several different materials. The complexity of the geometry and the loads highlights the necessity for a computational tool in order to conduct analysis. In this direction, the present work describes the development of a multi-physics finite element digital simulation, conducting heat transfer and structural analysis in a fully parametric manner in order to be able to support the investigation of different design concepts, materials, geometries, etc. The capabilities of the developed model are demonstrated by the design process of an independent-type aluminum 2219 cryogenic tank for commuter aircraft applications. The designed tank indicates a potential maximum take-off weight reduction of about 8% for the commuter category and demonstrates that aluminum alloys are serious candidate materials for future aircraft.

The European DEMO (EU-DEMO) reactor studies within EUROfusion aim to develop a fusion power plant concept. The large tokamak device needs an auxiliary heating power which, at the present stage, is provided by the Electron Cyclotron (EC) heating system with up to 130 MW foreseen to reach different regions of plasma for heating, suppression of instabilities and the possibility to support ramp-up and ramp-down phases. The present conceptual design of the system is based on 2 MW coaxial-cavity gyrotron sources, a transmission line (TL) using both circular corrugated waveguides and quasi-optical evacuated multi-beam TLs, and mirror antennas located in the Equatorial Port. In order to create a modular system, the sources are grouped in ‘clusters’, whose powers are combined in the quasi-optical TL, up to the tokamak building, where they are split and routed as single waveguides. In the launcher, they are combined together again on the launching mirrors, to save space for the apertures in the Breeding Blanket. The present EC heating system has a certain flexibility to adapt to changing design guidelines. The development status of the system is presented.

The processing and transformation of natural resources into completed and semi-finished products is the primary function of industry in each nation’s economy. There is no denying the significance of industry and sectoral classification of the economy, but the slow development and extension of one industry could have resulted in the advancement of other sectors that are now a part of contemporary communities. Since there are statistically significant differences between various industries, numerous authors are currently investigating the impact of the industry on the financial structure of firms, revealing the industry as a crucial determinant of corporate indebtedness. Thus, the main aim of this study is to determine the debt level of a sample of 4237 enterprises operating in the market in the period of 2018–2021 from various sectors using eight debt indicators, as well as to identify relationships between them, which may help to reveal sectors with homogeneous patterns of indebtedness (using the cluster analysis) and thus understand which sectors are the most stable and independent. The Kruskal–Wallis test is then used to determine if there are statistically significant differences between the calculated ratios related to the economic sector. Based on the results, it can be concluded that the choice of financial structure is significantly influenced by the industry. Financial performance and indebtedness indicators are quantitative statistics used to assess, monitor, and forecast company or sectoral financial health. They act as instruments for business insiders and outsiders to assess a company’s performance, particularly in comparison to competitors, and to pinpoint its strengths and weaknesses, making the outputs of this study important for all types of stakeholders.

Transcatheter aortic valve implantation (TAVI) has been established as a safe and efficacious treatment for patients with severe symptomatic aortic stenosis (AS). Despite being initially developed and indicated for high-surgical-risk patients, it is now offered to low-risk populations based on the results of large randomized controlled trials. The most common access sites in the vast majority of patients undergoing TAVI are the common femoral arteries; however, 10–20% of the patients treated with TAVI require an alternative access route, mainly due to peripheral atherosclerotic disease or complex anatomy. Hence, to achieve successful delivery and implantation of the valve, several arterial approaches have been studied, including transcarotid (TCr), axillary/subclavian (A/Sc), transapical (TAp), transaortic (TAo), suprasternal-brachiocephalic (S-B), and transcaval (TCv). This review aims to concisely summarize the most recent literature data and current guidelines as well as evaluate the various access routes for TAVI, focusing on the indications, the various special patient groups, and the advantages and disadvantages of each technique, as well as their adverse events.

BackgroundStudies have shown that individuals may search for suicide-related terms on the internet prior to an attempt. ObjectiveThus, across 2 studies, we investigated engagement with an advertisement campaign designed to reach individuals contemplating suicide. MethodsFirst, we designed the campaign to focus on crisis, running a campaign for 16 days in which crisis-related keywords would trigger an ad and landing page to help individuals find the national suicide hotline number. Second, we expanded the campaign to also help individuals contemplating suicide, running the campaign for 19 days with a wider range of keywords through a co-designed website with a wider range of offerings (eg, lived experience stories). ResultsIn the first study, the ad was shown 16,505 times and was clicked 664 times (4.02% click rate). There were 101 calls to the hotline. In the second study, the ad was shown 120,881 times and clicked 6227 times (5.15% click rate); of these 6227 clicks, there were 1419 (22.79%) engagements with the site, a substantially higher rate than the industry average of 3%. The number of clicks on the ad was high despite a suicide hotline banner likely being present. ConclusionsSearch advertisements are a quick, far-reaching, and cost-efficient way of reaching those contemplating suicide and are needed despite suicide hotline banners being present. Trial RegistrationAustralian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12623000084684; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=385209

Introduction Mining of electronic health record (EHRs) data is increasingly being implemented all over the world but mainly focuses on structured data. The capabilities of artificial intelligence (AI) could reverse the underusage of unstructured EHR data and enhance the quality of medical research and clinical care. This study aims to develop an AI-based model to transform unstructured EHR data into an organised, interpretable dataset and form a national dataset of cardiac patients.Methods and analysis CardioMining is a retrospective, multicentre study based on large, longitudinal data obtained from unstructured EHRs of the largest tertiary hospitals in Greece. Demographics, hospital administrative data, medical history, medications, laboratory examinations, imaging reports, therapeutic interventions, in-hospital management and postdischarge instructions will be collected, coupled with structured prognostic data from the National Institute of Health. The target number of included patients is 100 000. Natural language processing techniques will facilitate data mining from the unstructured EHRs. The accuracy of the automated model will be compared with the manual data extraction by study investigators. Machine learning tools will provide data analytics. CardioMining aims to cultivate the digital transformation of the national cardiovascular system and fill the gap in medical recording and big data analysis using validated AI techniques.Ethics and dissemination This study will be conducted in keeping with the International Conference on Harmonisation Good Clinical Practice guidelines, the Declaration of Helsinki, the Data Protection Code of the European Data Protection Authority and the European General Data Protection Regulation. The Research Ethics Committee of the Aristotle University of Thessaloniki and Scientific and Ethics Council of the AHEPA University Hospital have approved this study. Study findings will be disseminated through peer-reviewed medical journals and international conferences. International collaborations with other cardiovascular registries will be attempted.Trial registration number NCT05176769.

Environmental pollution is a growing threat to natural ecosystems and one of the world’s most pressing concerns. The increasing worldwide use of pharmaceuticals has elevated their status as significant emerging contaminants. Pharmaceuticals enter aquatic environments through multiple pathways related to anthropogenic activity. Their high consumption, insufficient waste treatment, and the incapacity of organisms to completely metabolize them contribute to their accumulation in aquatic environments, posing a threat to all life forms. Various analytical methods have been used to quantify pharmaceuticals. Biotechnology advancements based on next-generation sequencing (NGS) techniques, like eDNA metabarcoding, have enabled the development of new methods for assessing and monitoring the ecotoxicological effects of pharmaceuticals. eDNA metabarcoding is a valuable biomonitoring tool for pharmaceutical pollution because it (a) provides an efficient method to assess and predict pollution status, (b) identifies pollution sources, (c) tracks changes in pharmaceutical pollution levels over time, (d) assesses the ecological impact of pharmaceutical pollution, (e) helps prioritize cleanup and mitigation efforts, and (f) offers insights into the diversity and composition of microbial and other bioindicator communities. This review highlights the issue of aquatic pharmaceutical pollution while emphasizing the importance of using modern NGS-based biomonitoring actions to assess its environmental effects more consistently and effectively.

While cells in the human body function in an environment where the blood supply constantly delivers nutrients and removes waste, cells in conventional tissue culture well platforms are grown with a static pool of media above them and often lack maturity, limiting their utility to study cell biology in health and disease. In contrast, organ-chip microfluidic systems allow the growth of cells under constant flow, more akin to the in vivo situation. Here, we differentiated human induced pluripotent stem cells into dopamine neurons and assessed cellular properties in conventional multi-well cultures and organ-chips. We show that organ-chip cultures, compared to multi-well cultures, provide an overall greater proportion and homogeneity of dopaminergic neurons as well as increased levels of maturation markers. These organ-chips are an ideal platform to study mature dopamine neurons to better understand their biology in health and ultimately in neurological disorders.

The aim of this systematic review was to identify the correlations between spectrum sensing, clustering algorithms, and energy-harvesting technology for cognitive-radio-based internet of things (IoT) networks in terms of deep-learning-based, nonorthogonal, multiple-access techniques. The search results and screening procedures were configured with the use of a web-based Shiny app in the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) flow design. AMSTAR, DistillerSR, Eppi-Reviewer, PICO Portal, Rayyan, and ROBIS were the review software systems harnessed for screening and quality assessment, while bibliometric mapping (dimensions) and layout algorithms (VOSviewer) configured data visualization and analysis. Cognitive radio is pivotal in the utilization of an adequate radio spectrum source, with spectrum sensing optimizing cognitive radio network operations, opportunistic spectrum access and sensing able to boost the efficiency of cognitive radio networks, and cooperative spectrum sharing together with simultaneous wireless information and power transfer able increase spectrum and energy efficiency in 6G wireless communication networks and across IoT devices for efficient data exchange.