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Safety and efficacy of feed additives consisting of vitamin B<sub>2</sub> (98%) and vitamin B<sub>2</sub> (80%) produced with Bacillus subtilis CGMCC 7.449 for all animal species (Chifeng Pharmaceutical Co., Ltd.)
No full textFollowing a request from the European Commission, the Panel on Additives and Products or Substances used in Animal Feed (FEEDAP) of EFSA was asked to deliver a scientific opinion on the safety and efficacy of vitamin B2 98% and vitamin B2 80% in the form of riboflavin produced by fermentation with a genetically modified strain of Bacillus subtilis (CGMCC 7.449) as nutritional feed additives for all animal species. Viable cells and DNA of the production strain were not detected in the final products and therefore, the use of B. subtilis CGMCC 7.449 to produce vitamin B2 does not raise safety concerns. The use of vitamin 98% and 80% produced with B. subtilis CGMCC 7.449 in animal nutrition does not represent a safety concern for the target species, consumers and for the environment. The additives are not dermal nor eye irritants but are dermal and respiratory sensitisers. Inhalation and dermal exposure are considered a risk. The additives under assessment are effective in covering the animals' requirements of vitamin B2 when administered via feed.</p
Assessment of the feed additive neohesperidine dihydrochalcone for piglets, pigs for fattening, calves, sheep, fish and dogs for the renewal of its authorisation (HealthTech Bio Actives S.L.U.)
No full textFollowing a request from the European Commission, EFSA was asked to deliver a scientific opinion on the assessment of the application for the renewal of the authorisation of neohesperidine dihydrochalcone as a sensory feed additive for piglets and pigs for fattening, calves, sheep, fish and dogs. The additive is already authorised for use in calves, sheep, fish, dogs and certain categories of pigs (2b959). The applicant provided evidence that the additive currently in the market complies with the existing conditions of the authorisation and that the production process has not been modified. The EFSA Panel on Additives and Products or Substances used in Animal Feed (FEEDAP) concluded that the additive remains safe for the target species, consumers and the environment. Neohesperidine dihydrochalcone is not irritant to skin and eyes and is not a skin sensitiser. Exposure through inhalation is likely. The present application for renewal of the authorisation does not include any modification proposal that would have an impact on the efficacy of the additive, and therefore, there is no need for re-assessing the efficacy.</p
Assessment of the feed additive consisting of Lactiplantibacillus plantarum DSM 16627 for all animal species for the renewal of its authorisation (Microferm Ltd.)
No full textFollowing a request from the European Commission, EFSA was asked to deliver a scientific opinion on the assessment of the application for renewal of the authorisation of a preparation Lactiplantibacillus plantarum DSM 16627 as a technological additive to improve ensiling of fresh plant material for all animal species. The applicant has provided evidence that the additive currently on the market complies with the existing conditions of authorisation. There was no new evidence that would lead the EFSA Panel on Additives and Products or Substances used in Animal Feed (FEEDAP) to reconsider its previous conclusions for all animal species, consumers and the environment, for which the additive is considered to remain safe. Regarding the user safety, the additive is a preparation containing a microorganism and therefore should be considered a skin and respiratory sensitiser, and any exposure through the skin and respiratory tract is considered a risk. In the absence of data, no conclusion could be drawn on the eye irritation potential of the additive. There is no need for assessing the efficacy of the additive in the context of renewal of the authorisation.</p
Policy action for CVD prevention: a call to action for nurses globally
No full textCardiovascular disease (CVD) is the leading cause of death and disability globally, disproportionately affecting vulnerable populations, including women and infants. Despite significant preventability, Cardiovascular disease (CVD) continues to be underfunded and overshadowed by cancer in terms of policy attention, creating a significant health inequity. This article advocates for a shift in international health policy to prioritize CVD through targeted, disease-specific interventions and multilevel strategies addressing both modifiable and primordial risk factors. It highlights the crucial role of nurses and healthcare professionals in influencing CVD prevention and treatment, from individual behavior changes to policy advocacy. The article concludes that collaboration across sectors, including healthcare, policymakers, and communities, is essential to implement effective CVD strategies and reduce global mortality and morbidity. Clinically, nurses are positioned to lead in patient education, support community-based initiatives, and advocate for stronger policies to combat CVD worldwide
The potential role of AI in research priority setting exercises
No full textTo help achieve the goals of accountability and research excellence, funding organisations often utilise evidence from research priority setting exercises (RPSEs), which distil, from data gathered from relevant stakeholders, a systematic and ‘objective’ rank-order of research priorities. RPSEs are, however, costly and labour-intensive. Also, critics of RPSEs have highlighted certain limitations: insufficient representation of difficult-to-reach stakeholders, especially in low- and middle-income countries; a lack of genuine stakeholder engagement; wide variation in the extent to which exercises are documented; a lack of specificity in the identified priorities; and minimal impact of the priorities. Artificial intelligence (AI) tools such as ChatGPT may potentially help, valuably complementing conventional RPSEs. While the opacity of AI decision-making is a limitation, advantages include speed, affordability, and highly inclusive distillation of the vastness of existing human knowledge. We encourage research identifying the extent to which AI can replicate conventional RPSEs. We suggest that AI tools could complement conventional approaches either at the initial question generation stage or in generating supplementary insights for reflection at the data analysis stage. Also, under conditions of high existing stakeholder engagement and an extant prevalence of conventional RPSEs, AI-only studies may be valuable.<br/
Tackling data scarcity in machine learning-based CFRP drilling performance prediction through a Broad Learning System with Virtual Sample Generation (BLS-VSG)
No full textMachine learning (ML)-based data-driven method has emerged as a powerful tool for predicting the manufacturing performance of carbon fibre reinforced plastic (CFRP), particularly in CFRP machining where physics-based models are computationally expensive. However, the effectiveness of ML model is often constrained by limited datasets, due to the high cost and time required for experimental data acquisition. To address this, this paper presents the first study to apply virtual sample generation (VSG) techniques to enlarge the training dataset and mitigate data scarcity in the prediction of CFRP drilling performance. A novel hybrid ML framework integrating Broad Learning System (BLS) and VSG (BLS-VSG) is proposed, to combine BLS’s capability in small dataset prediction with the enlarged dataset generated by VSG. The model has been employed to predict the drilling thrust force and delamination damage under various drilling conditions (spindle speed, feed rate, point angle). Three different VSG methods (SMOTE, MD-MTD and CVT) and number of virtual samples were evaluated in detail. Results show that VSG can effectively enlarge the training dataset and improve the prediction performance of the ML model. Specifically, VSG reduced the mean square error (MSE) and mean absolute percentage error (MAPE) for thrust force prediction by 39.0% and 12.9% respectively, compared to the benchmark without VSG. For delamination factor Fda prediction, MSE and MAPE were reduced by 22.6% and 16.5%, respectively. The proposed BLS-VSG model outperforms other conventional ML models (BPNN, ELM, SVR and RT) for both scenarios (with/without VSG), providing a robust and data-efficient solution for CFRP drilling performance prediction
Air quality and healthy ageing: predictive modeling of pollutants using CNN Quantum-LSTM
No full textThe concept of healthy ageing is emerging and becoming a norm to achieve a high quality of life, reducing healthcare costs and promoting longevity. Rapid growth in global population and urbanisation requires substantial efforts to ensure healthy and supportive environments to improve the quality of life, closely aligned with the principles of healthy ageing. Access to fundamental resources which include quality healthcare services, clean air, green and blue spaces plays a pivotal role in achieving this goal. Air quality, in particular, is a critical factor in achieving healthy ageing targets. However, it necessitates a global effort to develop and implement policies aimed at reducing air pollution, which has severe implications for human health including cognitive impairment and neurodegenerative diseases, while promoting healthier environments such as high quality green and blue spaces for all age groups. Such actions inevitably depend on the current status of air pollution and better predictive models to mitigate the harmful impact of emissions on planetary health and public health. In this work, we proposed a hybrid model referred as AirVCQnet, which combines the variational mode decomposition (VMD) method with a convolutional neural network (CNN) and a quantum long short-term memory (QLSTM) network for the prediction of air pollutants. The performance of the proposed model is analysed on five key pollutants including fine Particulate Matter PM2.5, Nitrogen Dioxide (NO2), Ozone (O3), PM10, and Sulphur Dioxide (SO2), sourced from air quality monitoring station in Northern Ireland, UK. The effectiveness of the proposed model is evaluated by comparing its performance with its equivalent classical counterpart using root mean square error (RMSE), mean absolute error (MAE), and R-squared (R2). The results demonstrate the superiority of the proposed model, achieving a performance gain of up to 14% and validating its robustness, efficiency and reliability by leveraging the advantages of quantum computation.<br/
Safety evaluation of repeated application of polymeric microarray patches in miniature pigs
No full textThe safety of repeated microarray patch (MAP) application is crucial for its development as an innovative drug delivery platform. This study is the first to assess the safety of repeated applications of hydrogel-forming, dissolving, and implantable MAPs over four weeks using miniature pigs, an industry-standard dermatological model with human-like skin structure and physiological responses. Uniform MAPs are successfully manufactured, with application forces of 32 N/array resulting in less than 15% needle height reduction. ≈80% of the needle length penetrated Parafilm layers, while 40–60% penetrated excised porcine skin. Repeated MAP applications do not compromise skin barrier function, as confirmed by transepidermal water loss measurements, and caused no adverse skin reactions per modified Draize test results. Systemic safety assessments revealed no significant immune responses, allergic reactions, infections, or inflammatory markers (TNF-α, IgE, IgG, CRP, and IL-1β) between day 0 and day 28. No weight loss, infection signs, kidney toxicity, or clinically relevant hematological or biochemical changes are observed. Histopathological evaluations confirmed the absence of lesions or adverse effects. These findings establish the safety of repeated hydrogel-forming, dissolving, and implantable MAP applications, supporting their potential for safe, effective drug delivery and facilitating their translation from preclinical models to human clinical trials
The oncogene SLC35F2 is a high-specificity transporter for the micronutrients queuine and queuosine
No full textThe nucleobase queuine (q) and its nucleoside queuosine (Q) are micronutrients derived from bacteria that are acquired from the gut microbiome and/or diet in humans. Following cellular uptake, Q is incorporated at the wobble base (position 34) of tRNAs that decode histidine, tyrosine, aspartate, and asparagine codons, which is important for efficient translation. Early studies suggested that cytosolic uptake of queuine is mediated by a selective transporter that is regulated by mitogenic signals, but the identity of this transporter has remained elusive. Here, through a cross-species bioinformatic search and genetic validation, we have identified the solute carrier family member SLC35F2 as a unique transporter for both queuine and queuosine in Schizosaccharomyces pombe and Trypanosoma brucei. Furthermore, gene disruption in human HeLa cells revealed that SLC35F2 is the sole transporter for queuosine (Km 174 nM) and a high-affinity transporter for the queuine nucleobase (Km 67 nM), with the additional presence of second low-affinity queuine transporter (Km 259 nM). Ectopic expression of labeled SLC35F2 reveals localization to the cell membrane and Golgi apparatus via immunofluorescence. Competition uptake studies show that SLC35F2 is not a general transporter for other canonical ribonucleobases or ribonucleosides but selectively imports q and Q. The identification of SLC35F2, an oncogene, as the transporter of both q and Q advances our understanding of how intracellular levels of queuine and queuosine are regulated and how their deficiency contributes to a variety of pathophysiological conditions, including neurological disorders and cancer.</p
Cultural and creative crowdfunding: how project categories shape adoption and success on Kickstarter
No full textThis article contributes to the literature on cultural and creative crowdfunding (CCCF), illustrating the trends and dynamics of crowdfunding adoption amid cultural and creative industries (CCIs) from a longitudinal perspective. This paper explores the development of CCCF by examining all campaigns on Kickstarter from 2009 to 2020, taking into account the variations among CCIs, their respective success rates, and the amounts pledged. Using three different statistical tests, we find support for the hypotheses that there is an association between CCI campaign categories and campaign success, which varies over time. Our main findings reveal distinct dynamics with significant differences in the success rates and pledged amounts when treating the fifteen Kickstarter project categories as proxy for the different CCIs