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A synoptic review of plant disease epidemics and outbreaks published in 2023 with synthesis of trends between 2021 and 2024
No full textWe reviewed scientific literature and CABI distribution records published in 2023 to find major plant disease outbreaks and first reports of pathogens spreading in new locations or infecting new host species. This is the third in a series of studies, building on work analysing and documenting reports from 2021 and 2022. We also perform additional analyses to identify time lags between first reports of a disease in a given location and subsequent outbreaks. Pathogens with at least eight articles in the 2023 scientific literature were Xylella fastidiosa, Puccinia striiformis f. sp. tritici, Bursaphelenchus xylophilus, Candidatus Liberibacter asiaticus, Fusarium head blight pathogens (F. graminearum and F. culmorum, which we treated as a single entity), Puccinia graminis f. sp. tritici, Phytophthora infestans, cassava brown streak viruses (cassava brown streak virus and Uganda brown streak virus, which we again treated as one) and tomato leaf curl New Delhi viruses. CABI distribution data from 2023 confirmed new reports for 38 pathogens from 88 records. Pathogens with four or more reports were Meloidogyne enterolobii, Pectobacterium brasiliense, tomato brown rugose fruit virus, Colletotrichum liriopes, Khuskia oryzae, Colletotrichum truncatum, tomato fruit blotch virus, Erysiphe corylacearum, Pantoea ananatis and Ralstonia pseudosolanacearum. As previously, there was little overlap between pathogens identified by reviewing scientific literature versus CABI distribution records. However, the set of pathogens reported in the scientific literature was relatively consistent from 2022 to 2023. Considering reports of outbreaks in the scientific literature from 2020 to 2024, we identify wide variation in intervals between the first report of that pathogen in a country and subsequent disease outbreaks. In some cases, the first report was made over a century ago (for Phytophthora infestans in Ecuador, Xylella fastidiosa in California and Fusarium spp. (pokkah boeng) in China) with major outbreaks still occurring. For other outbreaks, less than a decade had passed since the first report, including Sri Lankan cassava mosaic in Thailand, and Fusarium oxysporum f. sp. cubense in Brazil. We discuss possible reasons for – and implications of – this wide variability in intervals between first report and epidemic emergence
Transient receptor potential vanilloid 4 modulates substrate stiffness mechanosensing and transcellular pore formation in human Schlemm’s canal cells
No full textPathological changes in the biomechanical environment of Schlemm’s canal (SC) inner wall cells, such as substrate stiffening and increased cellular stretch, are associated with ocular hypertension, a key risk factor for the development of glaucoma. Cell membrane stretch can trigger the activation of transient receptor potential vanilloid 4 (TRPV4) mechanosensitive ion channels, allowing calcium influx and initiating downstream signaling. However, the precise role of TRPV4 in SC cell mechanobiology remains unclear. Here, we demonstrate that sustained inhibition of TRPV4 activity modulates substrate stiffness mechanosensing to thereby affect the remodeling of the actin cytoskeleton and extracellular matrix of SC cells. This is accompanied by a reduction in cell stiffness and an increase in transcellular pore forming ability, potentially lowering outflow resistance and risk of ocular hypertension. Interestingly, acute activation of TRPV4 channels induces Ca2+ influx, increasing transcellular pore formation in SC cells. Notably, reduced TRPV4 mechanosensing is observed in glaucomatous SC cells, resulting in reduced transcellular pore forming ability. These findings suggest novel potential strategies based on targeting TRPV4 in SC cells for the treatment of ocular hypertension in glaucoma
The BacA(SbmA) importer of symbiotically important legume nodule cysteine-rich peptides: insights into protein architecture, function, and evolutionary implications
No full textArtificial intelligence in operations management: AI-driven techniques for decision making
No full textArtificial intelligence (AI) has demonstrated substantial success across diverse fields, revolutionizing predictive and prescriptive analytics. Motivated by these advancements, this thesis explores the application of artificial intelligence within Operations Management (OM), specifically targeting challenges related to choice modeling, assortment optimization, and sequential decision-making problems. The thesis has three primary contributions. First, a neural network-based discrete choice model is introduced, tailored for single-choice scenarios, capable of accurately capturing complex customer behaviors without reliance on traditional model assumptions. This model can be used successfully for assortment optimization through integer programming methods. Second, the Transformer Choice Net is developed to handle single, sequential, and multiple-choice contexts within a unified transformer-based architecture, significantly enhancing prediction accuracy and scalability across diverse consumer decision settings. Third, an Operational Management Generative Pre-trained Transformer (OMGPT) is presented, adapting GPT-style transformer networks to general sequential decision-making problems, such as dynamic pricing, inventory management, and queuing control. OMGPT provides a robust, data-driven, model-free approach, demonstrating state-of-the-art performance and strong generalization capabilities across varying operational tasks. Collectively, this thesis underscores the transformative potential of artificial intelligence to enhance decision-making and analytics in OM, advancing both theoretical understanding and practical capabilities.Open Acces
Immunomodulatory effects of atorvastatin on peripheral blood mononuclear cells infected with Mycobacterium tuberculosis
No full textBackground: Tuberculosis (TB) remains a major global health threat, contributing substantially to high morbidity and mortality rates. This underscores the urgent need for more effective interventions. Recent studies highlight the potential of host-directed therapy approaches to enhance immune defences against TB. Atorvastatin, recognized for both its lipid-lowering properties and its immunomodulatory effects, has emerged as a compelling candidate for host-directed therapy against TB. Here, we investigated the ex vivo efficacy of atorvastatin in inducing immunomodulatory activities (phagosome maturation, autophagy, and apoptosis) and enhancing the mycobacterial killing capacity in Mycobacterium tuberculosis (Mtb)-infected peripheral blood mononuclear cells (PBMCs).
Method: Blood samples from healthy donors were collected for PBMC isolation. PBMCs were then treated overnight with or without atorvastatin, followed by infection with Mtb strains (H37Rv, HN878, and CDC1551) to evaluate intracellular mycobacterial growth by colony-forming units enumeration. Furthermore, co-localization of late endosomal marker (Rab-7), lysosomal markers (Cathepsin-D and LAMP-3), and autophagy marker (LC3B) with GFP-Mtb was investigated in infected PBMCs using laser scanning confocal microscopy. Moreover, multiple apoptotic assays were performed, including the TUNEL assay for DNA fragmentation, quantification of caspase-3 activity, and the expression levels of the pro-apoptotic gene (Bax) and anti-apoptotic gene (Bcl2).
Results: Treatment with atorvastatin significantly reduced intracellular mycobacterial replication compared to untreated controls in Mtb-infected PBMCs. Moreover, atorvastatin enhanced co-localization between Mtb and late endosomal marker (Rab-7), lysosomal markers (Cathepsin-D and LAMP-3), and autophagy marker (LC3B) in Mtb-infected PBMCs. Furthermore, atorvastatin robustly promoted apoptosis in Mtb-infected PBMCs, as demonstrated by TUNEL assay and caspase-3 activation.
Conclusion: Our findings highlight atorvastatin’s potential as a crucial modulator of the immune response in Mtb-infected PBMCs, supporting its role in host-directed therapy
Mitigating climate change impact on renewable energy: role of energy efficiency and diversification in sustainability
No full textEnvironmental pressures have long driven the shift toward non-fossil fuel alternatives in energy systems. However, the impact of climate change on reliability of renewable sources has received limited attention. Brazil’s energy system, dominated by hydropower (71%), faces increasing strain from prolonged dry conditions and growing peak demand. Only half of this hydro capacity is reservoir-type dispatchable, increasing reliability concerns. While expansions in wind, solar, and natural gas have been pursued, they introduce volatility and logistical complexity,
with imposed constraints of domestic reserves and imports. Biomass emerges as a flexible and viable alternative, particularly in decentralized applications. It offers emission reductions and cost savings when derived from locally sourced agricultural residues, in form of biogas and biomethane energy streams. This paper applies the extended Combined Gas and Electricity Network model to assess infrastructure interdependencies and diversification strategies under Brazil’s energy transition. Results show that small-scale biomass, paired with energy efficiency
and demand management, enhances resilience. Energy efficiency, despite higher upfront costs, provides long-term savings and emission reductions. The findings highlight the need for diversified, low-emission strategies with energy conservation as the foundation of sustainable development
An engineering approach for predicting impact damage in pressurised glass fibre reinforced pipes
No full textThis paper presents an impact testing technique in conjunction with a virtual approach for pressurised composite pipe components, focusing on high and low velocity impact (HVI and LVI) energy levels. Gas gun HVI and drop weight LVI impact tests were conducted on as-received, and pre-stressed pipe sections to validate impact damage predictions using finite element impact modelling methods. The modelling employed a statistical method to obtain the upper/mean/lower bound range of input variables for input in the impact prediction model. The study found that fibre breakage and matrix damage/delamination size due to HVI depend on the stress state at the impact surface. Comparing model predictions and HVI and LVI testing for GFRP pipe material, a simple relationship between impact energy in Joules and surface damage/fibre breakage can be derived. This approach could simplify experimental and virtual impact testing, reducing the number of pressurised pipe tests needed for validation
Will AI speed up literature reviews or derail them entirely?
No full textThe publication of ever-larger numbers of problematic papers, including fake ones generated by artificial intelligence, represents an existential crisis for the established way of doing evidence synthesis. But with a new approach, AI might also save the day
Aspergillus and Pseudomonas lung infections: that's what friends are spore
No full textAspergillus fumigatus is a significant airway pathogen in chronic suppurative lung diseases. Poore et al. demonstrate the impact of mucus composition, and the importance of competition with Pseudomonas aeruginosa that reduces fungal growth in co-infection https://bit.ly/4mdTvYQ
Impact of COVID-19 on mental health: sociodemographic differences and the moderating effect of religiosity
No full textBackground and Objectives: This research aimed to examine the impact of sociodemographic characteristics on mental health during the COVID-19 pandemic, with religiosity as a moderator. Materials and Methods: The cross-sectional study was conducted in family medicine clinics within the Primary Healthcare Center of Virovitica-Podravina County among 1131 participants, divided into 2 groups: RC (Recovered from COVID-19; N = 423) and NRC (Not Recovered from COVID-19; N = 708). To ensure clear differentiation, RC participants were defined as individuals with documented positive PCR results for SARS-CoV-2 (prior infection and clinical recovery), whereas NRC participants exhibited consistently negative PCR results and lacked any clinical history of the disease. Group allocation was rigorously based on the review of medical records and corresponding PCR documentation obtained both at the time of recruitment and retrospectively. All data were collected through a questionnaire from September 2022 to September 2023. Participants completed questionnaires measuring their sociodemographic characteristics (gender, age, education, and marital status), levels of depression, anxiety, stress, and level of religiosity. Results: Older participants were more prone to depression, whereas younger participants showed relatively better mental-health indicators. Sociodemographic characteristics were significantly associated with mental health during the pandemic. Religiosity was found to be a significant moderator in the relationship between sociodemographic characteristics and mental health. Individuals with higher levels of religiosity reported higher levels of depression and anxiety, suggesting that religiosity may act as a negative factor in times of crisis. Conclusions: Sociodemographic characteristics were significant predictors of mental health during the pandemic. Religiosity emerged as an important factor, particularly in moderating the relationship between sociodemographic characteristics and mental health. Further research is recommended to develop targeted interventions for vulnerable groups such as women, younger individuals, and those with lower incomes