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A novel PLpro inhibitor improves outcomes in a pre-clinical model of long COVID
Abstract The COVID-19 pandemic caused by the coronavirus SARS-CoV-2 has highlighted the vulnerability of a globally connected population to zoonotic viruses. The FDA-approved coronavirus antiviral Paxlovid targets the essential SARS-CoV-2 main protease, Mpro. Whilst effective in the acute phase of a COVID infection, Paxlovid cannot be used by all patients, can lead to viral recurrence, and does not protect against post-acute sequelae of COVID-19 (PASC), commonly known as long COVID, an emerging significant health burden that remains poorly understood and untreated. Alternative antivirals that are addressing broader patient needs are urgently required. We here report our drug discovery efforts to target PLpro, a further essential coronaviral protease, for which we report a novel chemical scaffold that targets SARS-CoV-2 PLpro with low nanomolar activity, and which exhibits activity against PLpro of other pathogenic coronaviruses. Our lead compound shows excellent in vivo efficacy in a mouse model of severe acute disease. Importantly, our mouse model recapitulates long-term pathologies matching closely those seen in PASC patients. Our lead compound offers protection against a range of PASC symptoms in this model, prevents lung pathology and reduces brain dysfunction. This provides proof-of-principle that PLpro inhibition may have clinical relevance for PASC prevention and treatment going forward.
An experimental study on the susceptibility of purchasing managers to greenwashing
Abstract Greenwashing—the deliberate exaggeration or fabrication of environmental claims—undermines trust, disrupts transparency, and poses a significant barrier to genuine progress toward sustainability. This scenario-based experimental study examines whether purchasing managers, key stakeholders in organizational procurement, can reliably differentiate between greenwashed and certified sustainable products. Using three carefully designed purchasing scenarios—laptops, safety gloves, and copy paper—responses were collected from 465 purchasing managers across the EU, a region notable for its regulatory emphasis on eco-certifications. The findings reveal no statistically significant differences in willingness to pay (WTP) for products with greenwashed claims versus those backed by stringent certifications, with average WTP values varying only slightly between groups. These findings highlight a critical vulnerability to greenwashing, even among experienced professionals, raising concerns about the credibility of sustainability claims in influencing procurement decisions. The study underscores the need for systemic reforms, including the standardization of certification systems and enhanced decision-making tools, to mitigate greenwashing’s pervasive impact and foster authentic corporate sustainability.
Polycystins recruit cargo to distinct ciliary extracellular vesicle subtypes in C. elegans
Preclinical assessment of anti-arthritic activity of methanolic extract from processed Plumbago zeylanica roots
Research on the mining of candidate genes for pepper fruit color and development of SNP markers based on SLAF-seq technology
Quantum phase constraints as the origin of zero-field splitting: the case of [Ni(Me6tren)Cl](ClO4)
Genus-wide plant pangenome could inform next-generation crop design
Learning produces an orthogonalized state machine in the hippocampus
Abstract Cognitive maps confer animals with flexible intelligence by representing spatial, temporal and abstract relationships that can be used to shape thought, planning and behaviour. Cognitive maps have been observed in the hippocampus1, but their algorithmic form and learning mechanisms remain obscure. Here we used large-scale, longitudinal two-photon calcium imaging to record activity from thousands of neurons in the CA1 region of the hippocampus while mice learned to efficiently collect rewards from two subtly different linear tracks in virtual reality. Throughout learning, both animal behaviour and hippocampal neural activity progressed through multiple stages, gradually revealing improved task representation that mirrored improved behavioural efficiency. The learning process involved progressive decorrelations in initially similar hippocampal neural activity within and across tracks, ultimately resulting in orthogonalized representations resembling a state machine capturing the inherent structure of the task. This decorrelation process was driven by individual neurons acquiring task-state-specific responses (that is, ‘state cells’). Although various standard artificial neural networks did not naturally capture these dynamics, the clone-structured causal graph, a hidden Markov model variant, uniquely reproduced both the final orthogonalized states and the learning trajectory seen in animals. The observed cellular and population dynamics constrain the mechanisms underlying cognitive map formation in the hippocampus, pointing to hidden state inference as a fundamental computational principle, with implications for both biological and artificial intelligence.
Comprehensive germline and somatic profiling of high-risk Thai breast cancer via next-generation sequencing
Strength and water retention behavior of loess stabilized with guar gum and fiber under dry and wet cycles
Abstract To improve the mechanical and water-retention behavior of loess and reduce the erosion failure caused by dry–wet cycles, the applicability of guar gum (GG) biopolymer and basalt fiber in the solidification of loess is investigated. The addition of GG can enhance the compressive strength and disintegration resistance of loess. When the GG content is 0.5%, 1.0%, and 2.0%, the compressive strength of stabilized loess increased by 30.15%, 67.85%, and 124.8%, respectively. The shear strength of GG–fiber stabilized loess is obviously higher than that of specimens without GG, and the higher the GG content, the stronger the shear resistance. The dry–wet cycles have a significant degradation effect on untreated and GG–fiber stabilized loess. After 8 dry–wet cycles, the cohesion and internal friction angle of the specimen containing 2.0% GG decreased by 45.90% and 10.74%, respectively. As the GG content increases, the water-retention capacity of stabilized is enhanced, but the dry–wet cycles have a significant deterioration effect. Furthermore, the soil water characteristic curves prediction model for GG–fiber stabilized loess is established by considering the effect of dry–wet cycles and GG content, and the prediction results are basically consistent with the measured data (R 2 = 0.92). This study confirmed the feasibility of applying guar gum and basalt fiber to improve soil strength, water stability, and water-retention capacity, and provided a basis for engineering construction and soil erosion control in the loess area.
Exploring the impact of pretreatment and particle size variation on properties of rubberized concrete
Abstract This study comprises the influence of particle sizes of discarded tire rubber with and without pre-treatment to check the hardened properties of rubberized concrete (RC) in analogy to control concrete. Fine aggregates from concrete are volumetrically substituted using untreated and pre-treated rubber particles of three different sizes up to 20% in part, with an increment of 5%. Pre-treatment using two different pre-treatment methods i.e., sodium hydroxide (NaOH) and silica fume and NaOH was adopted. Properties of fresh concrete-i.e., density, workability, and toughened concrete strengths as compressive, flexural, and indirect tensile strengths were assessed with the control concrete. Along with these, unconventional properties like cylindrical compressive strength and abrasion, resistance to impact, and water absorption are compared. The mechanical properties of RC were found to be similar to conventional concrete, as the compressive strength for RC with pretreated rubber fibers up to 10% obtained was 61.5 MPa while flexural and split tensile strength was above 5.6 MPa. The abrasion resistance was obtained for RC with rubber fibers from 0.98 to 1.46 mm up to 20% substitution against 1.34 mm of control concrete. Modified concrete with pre-treated rubber particles showed better performance than concrete with untreated rubber particles with coarser sizes.
Increased fat accumulation may be associated with severe muscle wasting in critically ill patients: a prospective observational study
A novel Ti/TiAl laminated composite with excellent shear properties
A novel extraction model optimization with effective separation coefficient for rare earth extraction process using improve differential evolution
Optimizing cultivation practices to enhance growth and yield of Indian mustard
Abstract Since mustard is a significant oilseed crop in India, improving cultivation practises is essential for enhancing the productivity. The experiment was laid out in randomized block design with three replications at the farm of Department of Agronomy, Lovely Professional University, Phagwara during the rabi season. The work was carried out for two years to analyse the pooled data (2022–2023; 2023–2024) of Indian mustard. A total of 11 treatments were utilized with various sowing techniques, sulphur use, and mulching for enhanced yield on mustard growth and yield traits. With an increase in doses of sulphur, mulching with paddy straw and sowing techniques including flat bed and ridge sowing the growth characteristics such as plant height, number of leaves per plant, number of branches per plant increased and enhanced yield traits. Results from the study revealed that among the various treatments, the application of Treatment T9 = Ridge sowing + recommended NP (100:75 kg/ha) + recommended S (20 kg/ha) + mulching (Paddy straw) had more growth and improved yield as compared to other treatments of Indian mustard. The pooled analysis of data from 2022 to 23 and 2023-24 revealed that treatment T9 achieved the maximum plant heights, measuring 14.8 cm, 80.8 cm, and 131.2 cm at 30, 60, and 90 DAS, number leaves per plant (6.0, 38.8, 83.2) at 30, 60, 90 DAS and number of branches (3.2, 6.7) at 60, 90 DAS. In yield analysis, the greatest number of siliquae per plant (73.6), the longest siliquae length (4.3), seeds per siliquae (23.1), 1000 seed weight peaked at 3.5, seed yield was 1.6 t/ha, stover yield was 4.1 t/ha, and harvest index was 29.6% in 2022-23 analysis. Overall, from pooled analysis the 2022-23 mustard crop had more growth and yield as compared to 2023-24 mustard crop.