Browse Articles

Life-history adaptation under climate warming magnifies the agricultural footprint of a cosmopolitan insect pest

Abstract Climate change is affecting population growth rates of ectothermic pests with potentially dire consequences for agriculture and global food security. However, current projection models of pest impact typically overlook the potential for rapid genetic adaptation, making current forecasts uncertain. Here, we predict how climate change adaptation in life-history traits of insect pests affects their growth rates and impact on agricultural yields by unifying thermodynamics with classic theory on resource acquisition and allocation trade-offs between foraging, reproduction, and maintenance. Our model predicts that warming temperatures will favour resource allocation towards maintenance coupled with increased resource acquisition through larval foraging, and the evolution of this life-history strategy results in both increased population growth rates and per capita host consumption, causing a double-blow on agricultural yields. We find support for these predictions by studying thermal adaptation in life-history traits and gene expression in the wide-spread insect pest, Callosobruchus maculatus ; with 5 years of evolution under experimental warming causing an almost two-fold increase in its predicted agricultural footprint. These results show that pest adaptation can offset current projections of agricultural impact and emphasize the need for integrating a mechanistic understanding of life-history evolution into forecasts of pest impact under climate change.

Insights into spinetail devil ray spatial ecology in the Mediterranean Sea through satellite telemetry

Non-metallic iodine single-atom catalysts with optimized electronic structures for efficient Fenton-like reactions

Crayfish optimization based pixel selection using block scrambling based encryption for secure cloud computing environment

Reverse mutational scanning of SARS-CoV-2 spike BA.2.86 identifies epitopes contributing to immune escape from polyclonal sera

Abstract The recently detected Omicron BA.2.86 lineage contains more than 30 amino acid mutations relative to BA.2. BA.2.86 and its JN.1 derivative evade neutralization by serum antibodies of fully vaccinated individuals. In this study, we elucidate epitopes driving the immune escape of BA.2.86 and JN.1 via pseudovirus neutralization. Here we generate 33 BA.2.86 mutants, each reverting a single mutation back to BA.2. We use this library in an approach that we call reverse mutational scanning to define distinct neutralization titers against each epitope. Mutations within the receptor binding domain at K356T, V483Δ, and to a lesser extent N460K, A484K, and F486P enhance immune escape. Interestingly, 16insMPLF within the spike N-terminal domain and P621S within S1/S2 also significantly contribute to antibody escape of BA.2.86. Upon XBB.1.5 booster vaccination, neutralization titers against JN.1 and BA.2.86 improve considerably, and residual immune escape is driven by 16insMPLF, N460K, E554K, and to a lesser extent P621S, and A484K.

Accelerometric assessment of fatigue-induced changes in swimming technique in high performance adolescent athletes

Abstract The present study analyzed the kinematic changes under fatigue in highly trained adolescent swimmers during a 50-m all-out front cwal test. Twenty-four girls and fourteen boys aged 12–13 participated in the study. The movement of the hip rim was analyzed using a specialized inertial device equipped with a triaxial gyroscope and accelerometer to measure changes in angular velocity and acceleration. Between the first and second lengths of the pool, the following were observed: a significant (F1.36 = 63.6; p  < 0.0001; η 2  = 0.64) increase (34%) in maximum pelvic angle, significant (F1,36 = 6.0; p  = 0.0193; η 2  = 0.14;) increase (12.10%) in angular velocity in rotational motion around a vertical axis, and a significant (F1,36 = 11.29; p  = 0.0018; η 2  = 0.24) increase (6.86%) in angular velocity in yaw rotation motion around the sagittal axis. Significant (F1,36 = 13.96; p  = 0.0006; η 2  = 0.28) differences in maximum pelvic angle were observed for lap and side. As unfavourable changes in kinematics are already observed in the second half of the distance, it is therefore suspected that performing frequent high-intensity repetitions may lead to the perpetuation of unfavourable movement patterns. Taking this into account, coaches should limit maximum-speed swimming in adolescent athletes to short distances and an appropriate interval and use training methods to reduce asymmetric work such as training snorkels.

Predicting metabolite response to dietary intervention using deep learning

Association between composite dietary antioxidant index and hyperlipidemia in adults based on the NHANES

Structural studies of the IFNλ4 receptor complex using cryoEM enabled by protein engineering

Abstract IFNλ4 has posed a conundrum in human immunology since its discovery in 2013, with its expression linked to complications with viral clearance. While genetic and cellular studies revealed the detrimental effects of IFNλ4 expression, extensive structural and functional characterization has been limited by the inability to express and purify the protein, complicating explanations of its paradoxical behavior. In this work, we report a method for robust production of IFNλ4. We then use yeast surface display to affinity-mature IL10Rβ and solve the 72 kilodalton structures of IFNλ4 (3.26 Å) and IFNλ3 (3.00 Å) in complex with their receptors IFNλR1 and IL10Rβ using cryogenic electron microscopy. Comparison of the structures highlights differences in receptor engagement and reveals a distinct 12-degree rotation in overall receptor geometry, providing a potential mechanistic explanation for differences in cell signaling, downstream gene induction, and antiviral activities. Further, we perform a structural analysis using molecular modeling and simulation to identify a unique region of IFNλ4 that, when replaced, enables secretion of the protein from cells. These findings provide a structural and functional understanding of the IFNλ4 protein and enable future comprehensive studies towards correcting IFNλ4 dysfunction in large populations of affected patients.

Naturally russeted and wound russeted skins of mango (cv. ‘Apple’) show no differences in anatomy, chemical composition or gene expression

Abstract The mango cultivar ‘Apple’ is commercially important in Kenya but highly susceptible to russeting. Russeting refers to an area of fruit skin where the primary (epidermal) surface has been replaced by a secondary (peridermal) surface. The objective was to establish histologies, gene expressions and chemical compositions of a natural periderm, a wound-induced periderm and of cuticles of an un-russeted skin. Fluorescence microscopy revealed a suberized phellem in natural and wound-induced periderms. Wound-induced periderms had more cell layers and a higher mass than natural periderms. Compared with cuticles, periderms showed decreased expressions of cuticle-related genes (MiSHN1, MiGPAT6, MiCUS1, MiCER1, MiWCB11) and increased expressions of periderm-related genes (MiMYB93, MiNAC058, MiCYP86A1, MiCYP86B1, MiGPAT5, MiABCG20). Natural periderms and wound-induced periderms contained cutin and suberin monomers (C16-C28), including carboxylic, dicarboxylic, and ω-hydroxy acids and primary alcohols. Cuticles of the primary skin contained cutin monomers of similar chemistry but shorter chain lengths (C16-C22). The wax composition in natural and wound-induced periderms was similar to that in cuticles. Lignin monomers in natural and wound-induced periderms contained p-hydroxyphenyl, guaiacyl and syringyl units, but only traces of these occurred in cuticles. In ‘Apple’ mango, the histologies, gene expressions and compositions of natural and wound-induced periderms are largely the same.

Quantum magnetometry of transient signals with a time resolution of 1.1 nanoseconds

Transcriptomic analysis reinforces the implication of spatacsin in neuroinflammation and neurodevelopment

Refining potential energy surface through dynamical properties via differentiable molecular simulation

Public attitude and media governance of biometric information dissemination in the era of digital intelligence

Early attainment of 20-hydroxyecdysone threshold shapes mosquito sexual dimorphism in developmental timing

Analyzing the relationship between gene expression and phenotype in space-flown mice using a causal inference machine learning ensemble

Exercise induces dynamic changes in intra-articular metabolism and inflammation associated with remodeling of the infrapatellar fat pad in mice

DeepLabCut custom-trained model and the refinement function for gait analysis

Unlocking the Key to Photocatalytic Hydrogen Production Using Electronic Mediators for Z-Scheme Water Splitting

Explainable human-centered traits from head motion and facial expression dynamics

We explore the efficacy of multimodal behavioral cues for explainable prediction of personality and interview-specific traits. We utilize elementary head-motion units named kinemes, atomic facial movements termed action units and speech features to estimate these human-centered traits. Empirical results confirm that kinemes and action units enable discovery of multiple trait-specific behaviors while also enabling explainability in support of the predictions. For fusing cues, we explore decision and feature-level fusion, and an additive attention-based fusion strategy which quantifies the relative importance of the three modalities for trait prediction. Examining various long-short term memory (LSTM) architectures for classification and regression on the MIT Interview and First Impressions Candidate Screening (FICS) datasets, we note that: (1) Multimodal approaches outperform unimodal counterparts, achieving the highest PCC of 0.98 for Excited-Friendly traits in MIT and 0.57 for Extraversion in FICS; (2) Efficient trait predictions and plausible explanations are achieved with both unimodal and multimodal approaches, and (3) Following the thin-slice approach, effective trait prediction is achieved even from two-second behavioral snippets. Our implementation code is available at: https://github.com/deepsurbhi8/Explainable_Human_Traits_Prediction.