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Non-targeted metabolomics reveals fatty acid and associated pathways driving resistance to whitefly and tomato leafminer in wild tomato accessions

A shout-out for AI studies that don’t make the headlines

GNSS spoofing in conflict zones disrupts wildlife tracking and hampers research and conservation efforts

Examining the mediating role of motivation in the relationships between teacher-created motivational climates and quality of engagement in secondary school physical education

Grounded in Duda’s integrated model of the motivational climate, the current study examined the hypothesized mediating role of motivation quality in the relationships between empowering and disempowering teacher-created motivational climates and indicators of quality engagement in secondary school physical education (PE). The hypothesised model was tested cross-sectionally and longitudinally in two separate samples of students. Data were collected via questionnaires measuring the motivational climate, autonomous and controlled motivation and indicators of engagement (enjoyment, concentration and boredom). Cross sectional data collected from 832 students (439 males and 386 females) while longitudinal data stemmed 299 students (166 males and 163 females). All students were from schools in Wales aged between 12 and 15 years. Structural equation modelling was used to test the hypothesised model and the mediating role of autonomous and controlled motivation. The hypothesised model was supported cross-sectionally and longitudinally, indicating that empowering climates positively predicted students’ autonomous motivation for PE, whereas disempowering motivational climates positively predicted controlled motivation. In turn, autonomous and controlled motivation positively and negatively predicted indictors of students’ engagement in PE in the hypothesised directions. Analyses revealed relationships between empowering and disempowering climates with enjoyment, concentration and boredom were indirect via autonomous and controlled motivation. In summary, results support the role of autonomous and controlled motivation in the differential relationships between empowering and disempowering motivational climates and indicators of the quality of student engagement. The findings suggest that targeted professional learning opportunities for PE teachers are needed which facilitate more empowering climates and reducing disempowering strategies.

An optimized lightweight real-time detection network model for IoT embedded devices

Pasteurisation temperatures effectively inactivate influenza A viruses in milk

Abstract In late 2023 an H5N1 lineage of high pathogenicity avian influenza virus (HPAIV) began circulating in American dairy cattle Concerningly, high titres of virus were detected in cows’ milk, raising the concern that milk could be a route of human infection. Cows’ milk is typically pasteurised to render it safe for human consumption, but the effectiveness of pasteurisation on influenza viruses in milk was uncertain. To assess this, here we evaluate heat inactivation in milk for a panel of different influenza viruses. This includes human and avian influenza A viruses (IAVs), an influenza D virus that naturally infects cattle, and recombinant IAVs carrying contemporary avian or bovine H5N1 glycoproteins. At pasteurisation temperatures of 63 °C and 72 °C, we find that viral infectivity is rapidly lost and becomes undetectable before the times recommended for pasteurisation (30 minutes and 15 seconds, respectively). We then show that an H5N1 HPAIV in milk is effectively inactivated by a comparable treatment, even though its genetic material remains detectable. We conclude that pasteurisation conditions should effectively inactivate H5N1 HPAIV in cows’ milk, but that unpasteurised milk could carry infectious influenza viruses.

Acquired hypothyroidism, iodine status and hearing impairment in adults: A pilot study

Objectives Hearing impairment can have major impacts on behavior, educational attainment, social status, and quality of life. In congenital hypothyroidism, the incidence of hearing impairment reaches 35–50%, while in acquired hypothyroidism there is a reported incidence of 25%. Despite this, knowledge of the pathogenesis, incidence and severity of hearing impairment remains greatly lacking. The aim of our study was to evaluate hearing in patients with acquired hypothyroidism. Methods 30 patients with untreated and newly diagnosed peripheral hypothyroidism (H) and a control group of 30 healthy probands (C) were enrolled in the study. Biochemical markers were measured, including median iodine urine concentrations (IUC) µg/L. The hearing examination included a subjective complaint assessment, otomicroscopy, tympanometry, transitory otoacoustic emission (TOAE), tone audiometry, and brainstem auditory evoked potential (BERA) examinations. The Mann-Whitney U test, Fisher’s Exact test and multivariate regression were used for statistical analysis. Results The H and C groups had significantly different thyroid hormone levels (medians with 95% CI) TSH mU/L 13.3 (8.1, 19.3) vs. 1.97 (1.21, 2.25) p =  0 and fT4 pmol/L 10.4 (9.51, 11.1) vs. 15 (13.8, 16.7) p =  0. The groups did not significantly differ in age 39 (34, 43) vs. 41 (36,44) p =  0.767 and IUC 142 (113, 159) vs. 123 (101, 157) p =  0.814. None of the hearing examinations showed differences between the H and C groups: otomicroscopy (p =  1), tympanometry (p =  1), TOAE (p =  1), audiometry (p =  0.179), and BERA (p =  0.505). Conclusions We did not observe any hearing impairment in adults with acquired hypothyroidism, and there were no associations found between hearing impairment and the severity of hypothyroidism or iodine status. However, some forms of hearing impairment, mostly mild, were very common in both studied groups.

Changes in lake sturgeon spawning periodicity is associated with prior reproductive effort

Site-specific substitution in atomically precise carboranethiol-protected nanoclusters and concomitant changes in electronic properties

Generating context-specific sports training plans by combining generative adversarial networks

Personalized sports training plans are essential for addressing individual athlete needs, but traditional methods often need to integrate diverse data types, limiting adaptability and effectiveness. Existing machine learning (ML) and rule-based approaches cannot dynamically generate context-specific training programs, reducing their applicability in real-world scenarios. This study aims to develop a Generative Adversarial Network (GAN)- based framework to create context-specific training plans by integrating numeric attributes (e.g., age, heart rate) and motion features from video data. The research focuses on improving context-specific efficiency and real-time adaptability while addressing the limitations of traditional methods. The proposed GAN framework combines numeric and motion features using a generator-discriminator architecture to produce tailored training plans. The model is evaluated quantitatively through metrics like mean square error (MSE) and generation time and qualitatively through subjective ratings from athletes and coaches using a five-point Likert scale for context-specific, scientificity, applicability, and feasibility. Statistical significance is analyzed using ANOVA testing. The proposed GAN model outperforms traditional ML and rule-based methods, achieving a 22% reduction in MSE and a 45% improvement in generation time. Subjective evaluations reveal significant improvements in context-specific and applicability, with ratings averaging 4.8/5 compared to 3.9/5 for baseline models. The GAN framework effectively integrates multimodal data, demonstrating dynamic adaptability and high efficiency suitable for real-world applications. The proposed GAN-based framework advances the generation of personalized sports training plans by integrating numeric and motion data, achieving superior adaptability and efficiency. These results highlight the model’s potential for practical deployment in athletic coaching systems, addressing critical gaps in existing methodologies and offering scalable solutions for individualized training.

Muscarinic acetylcholine receptor 3 localized to primary endothelial cilia regulates blood pressure and cognition

Deep mutational scanning of the Trypanosoma brucei developmental regulator RBP6 reveals an essential disordered region influenced by positive residues

Long-term engagement in smoking cessation campaign: A mixed methods randomized trial

Introduction A long-term engagement (LTE) intervention was embedded in a social marketing campaign aimed at motivating quit attempts among Canadian adult commercial tobacco users 35 to 64 years of age. The purpose of this study was to examine the effectiveness and appeal of LTE within a marketing campaign. Methods 3,199 Canadians who smoked cigarettes aged 35–64 recruited using Facebook and Instagram advertisements were randomized into Intervention and Control groups. Over the course of two years, Intervention Group participants received monthly emails connecting them to campaign news and activities, Mini Surveys to inform campaign refinement, feedback opportunities via focus groups and interviews, financial incentives, and proactive knowledge exchange presenting study findings. Both groups responded to a baseline and follow-up surveys every six months. Results LTE Intervention Group participants engaged frequently with emails (unique opens, open rates, click rates, and total clicks). Compared with Control Group members, they had significantly higher rates of: unaided and aided campaign awareness; engagement with the social marketing campaign (website visits, social media visits, likes/shares); actions towards making quit attempts; quit attempts. Many participants expressed feelings of motivation, support, and a sense of belonging. Conclusions When embedded in a social marketing campaign, meaningful long-term engagement of adults who smoke cigarettes shows promise as an intervention to promote quitting behaviors. Implications Active long-term engagement can significantly amplify the effects of social marketing campaigns aimed at promoting quit smoking behaviours among adults. The active engagement approach applied indicates that frequent long-term engagement is more effective when done in a more holistic, empathetic manner. The intervention also allows for real-time learning to support campaign development. Trial registration ISRCTN94797633.

Design and mechanical analysis of a novel modular bionic earthworm robot with upright functionality

Enhanced energy storage in antiferroelectrics via antipolar frustration

Mitochondrial KMT9 methylates DLAT to control pyruvate dehydrogenase activity and prostate cancer growth

Abstract Prostate cancer (PCa) growth depends on de novo lipogenesis controlled by the mitochondrial pyruvate dehydrogenase complex (PDC). In this study, we identify lysine methyltransferase (KMT)9 as a regulator of PDC activity. KMT9 is localized in mitochondria of PCa cells, but not in mitochondria of other tumor cell types. Mitochondrial KMT9 regulates PDC activity by monomethylation of its subunit dihydrolipoamide transacetylase (DLAT) at lysine 596. Depletion of KMT9 compromises PDC activity, de novo lipogenesis, and PCa cell proliferation, both in vitro and in a PCa mouse model. Finally, in human patients, levels of mitochondrial KMT9 and DLAT K596me1 correlate with Gleason grade. Together, we present a mechanism of PDC regulation and an example of a histone methyltransferase with nuclear and mitochondrial functions. The dependency of PCa cells on mitochondrial KMT9 allows to develop therapeutic strategies to selectively fight PCa.

Signals of propaganda—Detecting and estimating political influences in information spread in social networks

Social networks are a battlefield for political propaganda. Protected by the anonymity of the internet, political actors use computational propaganda to influence the masses. Their methods include the use of synchronized or individual bots, multiple accounts operated by one social media management tool, or different manipulations of search engines and social network algorithms, all aiming to promote their ideology. While computational propaganda influences modern society, it is hard to measure or detect it. Furthermore, with the recent exponential growth in large language models (L.L.M), and the growing concerns about information overload, which makes the alternative truth spheres more noisy than ever before, the complexity and magnitude of computational propaganda is also expected to increase, making their detection even harder. Propaganda in social networks is disguised as legitimate news sent from authentic users. It smartly blended real users with fake accounts. We seek here to detect efforts to manipulate the spread of information in social networks, by one of the fundamental macro-scale properties of rhetoric—repetitiveness. We use 16 data sets of a total size of 13 GB, 10 related to political topics and 6 related to non-political ones (large-scale disasters), each ranging from tens of thousands to a few million of tweets. We compare them and identify statistical and network properties that distinguish between these two types of information cascades. These features are based on both the repetition distribution of hashtags and the mentions of users, as well as the network structure. Together, they enable us to distinguish (p − value = 0.0001) between the two different classes of information cascades. In addition to constructing a bipartite graph connecting words and tweets to each cascade, we develop a quantitative measure and show how it can be used to distinguish between political and non-political discussions. Our method is indifferent to the cascade’s country of origin, language, or cultural background since it is only based on the statistical properties of repetitiveness and the word appearance in tweets bipartite network structures.

Sympathetic innervation induced by nerve growth factor promotes malignant transformation in gastric cancer

Valley charge-transfer insulator in twisted double bilayer WSe2

Tailoring anaesthetic strategies for diabetes research: Acepromazine vs. medetomidine in Aachen minipigs

Pre-established anaesthetic protocols in animal models might unexpectedly interfere with the main outcome of scientific projects and therefore they need to account for the specific research goals. We aimed to optimize the anaesthetic protocol and animal handling strategies in a diabetes-related-study exemplifying how the anaesthetic approach must be adjusted for individual research targets. Aachen minipigs were used as a model to test long-lasting skin glucose sensors for diabetic human patients. A total of 6 animals participated in two or three rounds of experiments. Each round lasted 2 months, with a maximum of 2 rounds per year. In each round, animals were anaesthetised 4 times: for glucose sensors insertion, twice for glucagon stress tests (GST), and a last time for removal of sensors. Acepromazine (ACE) was compared to medetomidine (MED) in association with butorphanol (BUT) and Ketamine (KET) and 4 parameters were analysed to define the optimum anaesthetic protocol including: sedation level, anaesthesia duration, effects on blood glucose and safety. ACE-BUT demonstrated a weaker sedative effect but reduced overall experimental time, minimized anaesthetic risk and minimally interfered with the glucose metabolism. The improvement obtained by animal conditioning and handling strategies applied in this study were not objectively estimated, although the aversion behavior was completely abolished. Based on the analysed parameters, the use of acepromazine is proposed to be superior when Aachen Minipigs are used specifically as a model for diabetes-related studies, albeit the recommendations for the anaesthesia of minipigs suggest otherwise.