Browse Articles

Pedigree-assisted genotype imputation enables cost-effective genomic prediction in Penaeus vannamei

Abstract Genomic selection in Penaeus vannamei has long been constrained by the high cost of dense genotyping. To address this limitation, we evaluated genotype imputation from a low-density 1 K panel to a medium-density 55 K panel of the “Yellow Sea Array No. 1” and examined its impact on genomic prediction for harvest body weight in P. vannamei . A four-generation pedigree including 30 great-grandparents, 39 grandparents, 100 parents, and 608 offspring was genotyped using the 55 K panel. A two-step experimental design was implemented to (i) assess the performance of different imputation algorithms under reference population scenarios with varying proportions of siblings, and (ii) compare six alternative reference population structures incorporating parents, ancestors, and siblings. Genotype imputation using the pedigree-based method FImpute v3.0 consistently achieved higher accuracy than the population-based method Beagle v5.5. Using this pedigree-assisted approach, imputation accuracy increased from 0.73 when only parental genotypes were used to 0.84 with the inclusion of 10% siblings, and subsequently plateaued at 0.87–0.90 when sibling representation reached 20%. Across the six reference population structures, imputation accuracy was primarily driven by the availability of parental genotypes, ranging from 0.50 to 0.56 in the absence of parents to 0.88–0.89 when both parents and ancestral generations were included. Accuracy remained high when both parents were available (0.84–0.87 with siblings; 0.73 without siblings) but declined substantially when only one parent was genotyped (0.65–0.68). Imputation accuracy was positively associated with both minor allele frequency (MAF) and linkage disequilibrium (max r 2 LD ), with LD exerting the stronger influence. Heritability estimates derived from imputed 55 K genotypes were highly consistent with those obtained from the original 55 K data (0.39 ± 0.14 vs. 0.41 ± 0.14), indicating that genotype imputation did not compromise variance component estimation. In predictive ability analyses, pedigree-based BLUP (PBLUP) achieved higher predictive ability than genomic BLUP (GBLUP) based on the 1 K panel, with predictive abilities of 0.42–0.44 for PBLUP compared with 0.34–0.35 for GBLUP. Using imputed genotypes for genomic prediction further improved predictive ability relative to the true 1 K panel, yielding values ranging from 0.35 to 0.47. Notably, when parental genotypes were included in the reference population, GBLUP based on imputed genotypes surpassed the predictive ability of PBLUP and approached that achieved with the original 55 K genotypes (0.45–0.47). Collectively, these results provide the first empirical evidence that low- to medium-density genotype imputation, combined with pedigree information, can effectively support genomic prediction in P. vannamei . This study establishes a cost-efficient and scalable framework for implementing genomic selection in P. vannamei and provides a practical reference for the application of genomic selection in other aquaculture species with constrained breeding budgets.

Cyclopropanone: Preparation, Rotational Spectroscopy, and Semi-Experimental Equilibrium ( <i>r</i> _<i>e</i> ^SE ) Structure

Engineering exosomes with iRGD for targeted RNAi therapy against pancreatic cancer mediated by long non-coding RNA PLBD1-AS1

Tumor-derived exosomes play critical roles in pancreatic ductal adenocarcinoma (PDAC) progression by mediating intercellular communication within the tumor microenvironment. This study identifies the long non-coding RNA PLBD1-AS1 as a functional oncogenic lncRNA enriched in PDAC exosomes. We demonstrate that PLBD1-AS1 promotes tumor cell proliferation, migration, and invasion by interacting with the glycolytic enzyme ALDOA and enhancing glycolytic flux. Furthermore, tumor exosomes deliver PLBD1-AS1 to pancreatic stellate cells (PSC), augmenting their glycolysis and facilitating their activation into cancer-associated fibroblasts, thereby shaping a pro-tumorigenic microenvironment. To target it, we developed an engineered exosome system modified with the tumor-penetrating peptide iRGD for specific delivery of siPLBD1-AS1 to both tumor and stromal cells. The resulting iRGD-exo-siPLBD1-AS1 construct demonstrated enhanced cellular uptake and effectively suppressed PLBD1-AS1 expression, inhibited glycolysis, impaired PSC activation, and significantly attenuated tumor growth. Our findings reveal a novel mechanism of exosome-mediated metabolic crosstalk in PDAC and establish a promising RNAi-based therapeutic strategy targeting this lethal malignancy.

Immunohistochemistry and molecular detection of Helicobacter pylori infection and their virulent genes in gastric biopsies

Linker Torsional Angle Engineering in Metal–Organic Frameworks Enables Boosted O ₂ Photoactivation for Organic Synthesis

Leprosy neuropathy and demyelinating impairment: How should we interpret this neurophysiological pattern?

Introduction/Aims Leprosy neuropathy (LN) may cause demyelination that worsens during the leprosy reactions (LR). Type-1 LR (T1LR) occurs in patients with cell-mediated immune response against M. leprae, and Type-2 LR (T2LR) occurs in multibacillary cases. The patterns of nerve impairment need to be clarified, as both demyelination and axonal degeneration are commonly observed. This study aimed to describe how to interpret the demyelinating impairment in LN. Methods Retrospective observational analysis of leprosy patients in a National Reference Center in Brazil between 2014–2023. Results 494 participants were included in this study. 3952 nerves were evaluated, with an average of 5.1 (±5.4) nerves affected per patient. 23.5% (116/494) of patients showed a demyelinating pattern defined by standard criteria, and 20.7% (24/116) presented exclusively demyelinating abnormalities without evidence of secondary axonal loss. 81% (94/116) presented conduction block, and 95.7% (111/116) temporal dispersion, with both conditions concomitant in 76.7% (89/116) of patients. 83.6% (97/116) demonstrated prolonged distal motor latency, and 99.1% (115/116) reduction in conduction velocity. 46.1% had T1LR and 17.9% T2LR. The comparison between patients with and without LR showed higher bacillary load, conduction block, and temporal dispersion in LR patients. 93.1% (108/116) of patients fulfilled neurophysiological criteria for chronic inflammatory demyelinating polyneuropathy (CIDP). Among them, 46.3% presented clinical criteria for atypical CIDP. Discussion Leprosy is a spectral disease in which neural damage can manifest in different phenotypes. Demyelinating impairment is frequent and varies according to the clinical form and presence of LR. Although demyelinating impairment is common in the studied population, it does not reflect active disease. LN can also be misdiagnosed as other peripheral neuropathies, especially CIDP, in non-endemic areas.

Hybrid mechanism-data-driven modeling for power system frequency response

Hydride-Mediated Hydrogen Activation on Cobalt-Alloyed Single-Atom Palladium Catalysts for Efficient H ₂ O ₂ Synthesis

A new experimental method for evaluating the effectiveness of auditory signals under realistic background noise conditions: A randomized controlled pilot study

This study introduces a new experimental method for analyzing auditory signals in the presence of background noise and identifying sounds that are consistently easy for humans to notice in daily environments. Attention to a signal was inferred from a physiological orienting response, measured as the change in heart rate (HR) before and after the presentation of a test sound in an experimental environment designed to simulate daily life. The test sounds consisted of eight musical sounds each composed of two piano notes at different pitches, and eight complex sounds, each composed of two pure tones. Each sound interval—C + E or C + G#—was recorded at four different octaves, covering the frequency range of 130.8 Hz to 1661.4 Hz. The change in HR was calculated as the difference in the mean RR interval (RRI) over five beats before and after the test sound. The strength of the orienting response (OR) was quantified as the RRI difference normalized by the standard deviation of RRI. An absolute value greater than 2 was considered to indicate the presence of an orienting response. Twenty-two healthy young male participants participated in the experiment during a three-day, two-night stay, which was repeated after a washout period of at least one week. The results showed that OR values were reproducible for 11 of the 16 test sounds. Based on the corresponding OR values, C3 + E3 (musical sound) was identified as a suitable pre-signal due to its calming response (negative OR), whereas C6 + G#6 (complex sound) was identified as a suitable alarm signal due to its tension-inducing response (positive OR). These findings suggest that the OR metric for assessing physiological responses, provides a novel and effective approach for objectively evaluating human reactions to unexpected auditory stimuli, when combined with an experimental protocol that simulates daily life and background noise.

Opposite seasonal and spatial dynamics of DWV-A and DWV-B suggest distinct transmission pathways in managed honey bees (Apis mellifera L.) colonies

Practical Multiphase Transition Kinetics in High-Energy-Density Layered Cathodes

White matter microstructure disruption associated with PET and cognitive impairment in Alzheimer’s disease

Alzheimer’s disease (AD) is associated with regional brain atrophy as well as elevated positron emission tomography (PET) markers of amyloid-beta (e.g., [¹⁸F]florbetapir (FBP)) and tau protein (e.g., [¹⁸F]flortaucipir (FTP). White matter microstructures have also been shown to be disrupted in AD, but there is limited understanding of their specific associations with FBP, FTP, and cognitive impairment. Herein, we used both voxel-based and fixel-based analyses of diffusion tensor imaging (DTI) to characterize microstructural white matter changes associated with PET and cognitive changes in AD. A retrospective study was performed using the data from 381 ADNI-3 participants (F:M = 200:181). FBP and FTP results were correlated with DTI metrics, including the apparent fiber density (AFD), complexity (CX), functional anisotropy (FA), fixel number (FN), and mean diffusivity (MD). Linear regression analysis was performed, adjusted for age, sex, education, and cognitive impairment. Greatest negative correlations were observed between FN and FBP standardized uptake value ratio (SUVR) in 15 out of 18 white matter tracts examined (beta coefficients of −0.3991 to −0.2877). No significant correlation was observed between DTI measures and FTP SUVR, independently. However, combined PET positivity (FBP + /FTP+) generally showed the greatest reductions in CX, FN, and FA of various tracts, compared to single PET-positive or PET-negative groups. Widespread changes in FA were positively associated with cognitive impairment, with stronger associations seen with the Montreal Cognitive Assessment (MoCA) than the Mini-Mental State Examination (MMSE). Only females showed significant correlations between MD and FBP/FTP levels and showed more widespread correlations between FA and MD changes and cognitive impairment. Taken together, these findings suggest specific patterns of white matter microstructure disruption in AD with underlying sex differences and support their potential role as early biomarkers.

Comparison of socioeconomic and psychosocial profiles between Brazilian and Swedish women with temporomandibular disorders

Abstract Temporomandibular disorders (TMD) are highly affected by psychological factors and may also be associated with socioeconomic disadvantages. This study aimed to investigate whether psychosocial and demographic factors of women with TMD differ between two countries with different socioeconomic development levels. 300 women with myogenous TMD in Brazil ( n  = 141) and Sweden ( n  = 159) were characterized regarding sociodemographic and psychological data and were clinically examined according to Axis I and II of the diagnostic criteria for temporomandibular disorders. The cohorts were compared regarding demographics, characteristic pain intensity, pain interference, the presence of widespread pain, oral parafunctions, limitations in jaw function, and symptoms of depression, anxiety, and non-specific physical symtoms. Data analysis included Mann-Whitney U-Test, Chi-square test, and Fisher’s exact test ( p  &lt; 0.05). Bonferroni test for multiple comparisons was also applied ( p  &lt; 0.01). Sociodemographic data revealed differences in body mass index (BMI), marital status, education level, and employment status ( p  &lt; 0.05), with higher BMI, greater frequency of single marital status, and higher education level in the Brazilian cohort. The Swedish cohort showed higher levels of pain interference, greater limitations in jaw function, and more frequent widespread pain ( p  &lt; 0.05), while anxiety levels were higher in the Brazilian cohort ( p  &lt; 0.05). Characteristic pain intensity, oral parafunctions, depression, and non-specific symptoms did not differ between cohorts ( p  &gt; 0.05). There were both differences and similarities in psychological and sociodemographic factors between the two TMD cohorts in Brazil and Sweden. The comprehensive assessment of TMD diagnoses, psychosocial and demographic characteristics may help to guide TMD care and future research in countries with different socioeconomic contexts.

Energy collaborative optimization of power routing based on PPO and generative adversarial imitation learning

Under the general trend of global energy transformation, the proportion of renewable energy in the power sector continues to increase. Power routers are of great significance for improving energy utilization efficiency and ensuring the stable operation of power systems. However, the intermittent and uncertain nature of distributed energy makes energy management of power routers difficult, and traditional optimization methods are also difficult to adapt. Therefore, this study proposes the integration of Proximal Policy Optimization with a multi-agent framework, combined with a Generative Adversarial Imitation Learning based on a double-buffer mechanism. The double-buffer mechanism is used to improve data utilization efficiency and training stability, and to optimize communication and collaboration among multiple agents, thereby realizing energy collaborative optimization of power routers. Experimental results show that after 420 trainings, the average round reward of the improved algorithm is stable at about −410, and the strategy loss function is the first to stabilize after 500 times. In practical scenarios, the proposed model maintains a DC bus voltage fluctuation range between 728V and 732V. Additionally, its electricity cost amounts to 3846.36 yuan, and its total runtime is 53.32 seconds—both of which are lower than those of the other two models. Overall, the enhanced algorithm and model notably improve the energy collaboration optimization of power routers, offering a practical solution to energy management issues and significantly advancing the progress in this area.

Shell game: Neanderthal use of the European pond turtle (Emys orbicularis) in the Last Interglacial landscape of Neumark-Nord (Germany)

Abstract Data on palaeolithic subsistence is often obtained through studies of faunal palimpsests, containing remains of animal processing activities accumulated over non-quantifiable amounts of time. Compounding such site-specific data with evidence from other sites distributed over large areas - i.e. integrating data spanning large temporal as well as spatial scales - results in coarse-grained reconstructions of past prey diversity. In contrast, here we present prey diversity data from what is—geologically speaking—a “snapshot” of a ~ 25-hectare area frequented by Neanderthals during the Last Interglacial, with a focus on their exploitation of the pond terrapin Emys orbicularis . These data constitute the first evidence of turtle exploitation by Neanderthals north of the European mountain chains, beyond the Mediterranean basin. This Neumark-Nord record demonstrates that Last Interglacial foragers exploited a wide range of archaeologically visible resources available in this lake area, from small (~ 1 kg) pond terrapins up to and including the largest terrestrial mammals of the Pleistocene, straight-tusked elephants, with adult males weighing more than 10 tonnes. The abundance of intensively exploited medium- and large-sized mammals found alongside these Emys remains suggests that other variables than macronutrients per se played a role in the repeated harvesting of pond terrapins from these water bodies.

Surfactant-Mediated Synthesis of Twisted Cu _{2– <i>x</i>} S Nanobowties with Chirality Continuum toward Enantioselective Catalysis

Prediction of on-field rugby scrummaging contact forces from videos using artificial neural networks

Rugby is a contact sport with a high risk of injury. Scrums are a key component of the game and represent a collision event associated with serious injuries, especially to the cervical spine. Traditional methods for measuring scrum forces rely on both pressure sensors and scrum machines, but these have limitations for on-field monitoring. Thus, this study investigates the feasibility of using a machine learning approach to predict contact forces in rugby scrummaging during real-game situations, based on only anatomical landmarks of players extracted from video footage. A recurrent neural network (RNN) model was trained to predict contact forces from velocity signals. A dataset of eleven rugby teams (22 forward packs, n = 176 players) during on-field scrum engagements was used. Data augmentation techniques using a generative adversarial network and the Mixup technique were applied to increase the size of the training dataset. The RNN was trained using time-dependent data, with 2D trajectories from video landmarks as inputs and force signals from pressure sensors as outputs. The RNN´s prediction results showed good to excellent agreement between the predicted and measured time-dependent normal contact force signals, with a mean correlation of 0.95 ± 0.05. The mean normalized RMSE was 9.3 ± 4.3% and the mean normalized absolute difference in peak force was 6.7 ± 5.5%. This study demonstrated the feasibility of using RNNs to quantify contact forces in rugby scrummaging using only single-camera video, without players wearing sensors. In combination with a 2D human pose estimation model, the ANN trained in this study could support performance analysis, coaching, technique correction, and injury prediction using in-game data.

Geometric close-packing mechanism for predicting short-range correlations in nuclei

Abstract A geometric close-packing framework for nuclear structure is introduced, delivering parameter-free predictions for neutron–proton ( np ) short-range correlation (SRC) pair counts across the nuclear chart. Motivated by QCD-inspired parton flux tubes and electromagnetic resonance phenomena observed in BESIII measurements, each nucleon is represented by a closed double-helix parton flux tube configuration following a toroidal trefoil-knot trajectory and assembling into concentric toroidal shells sharing a common centroid. Within this framework, SRCs arise naturally as nearest-neighbor contacts between adjacent flux tube segments, converting SRC counting into a deterministic consequence of spatial organization rather than a phenomenological input. The resulting np -SRC counts quantitatively reproduce CLAS measurements for C, Al, Fe, and Pb and are consistent with established experimental systematics. The geometry further indicates a set of correlated features of np -SRC dynamics: (i) each nucleon participates in at least one np -SRC pair; (ii) adding neutrons increases the fraction of high-momentum protons; and (iii) adding protons increases the fraction of high-momentum neutrons. These results suggest that short-range nuclear dynamics is governed by an underlying geometric organizing principle, offering a physically transparent mechanism for the emergence of SRCs in nuclei.

Promoting energy conservation through attention control and construct activation: A field test at a campus laundry

Increasing the frequency of laundering in cold water has been demonstrated to reduce energy consumption, but heated water laundering rates remain high. This is particularly true in wealthy, western nations. This paper describes an individual-level, situated intervention utilizing attentional control and construct activation to motivate cold water laundering. In Study 1, we report the first direct observational study of laundering in a field setting, finding that (a) only 21% of laundry loads were washed with cold water, and (b) behavioral, normative, and control beliefs were associated with laundering in cold water. In Study 2, we report an experimental field test of an intervention designed to increase rates of cold-water laundering. The intervention significantly increased cold water laundering (57%) compared to a control condition (25%). We also tested mediators of the intervention and laundering behavior association and observed that control beliefs fully mediated the relationship. We discuss the theoretical and practical contribution of these studies to the environmental psychology and motivational science literatures.

Artificial intelligence assimilation shapes sustainable performance through dynamic capabilities

Abstract Beyond the hype of disruptive technologies, achieving sustainability requires assimilating artificial intelligence (AI) into organizational dynamic capabilities. Yet conflicting evidence on the sustainability outcomes of AI assimilation (AIA) motivates this study to unveil its underlying capability logic. Grounded in the Natural Resource-Based View and Dynamic Capabilities Theory, this study employs meta-analytic structural equation modeling (MASEM) to systematically investigate the intrinsic mechanisms through which AIA affects firms’ sustainable performance (SP). The findings reveal several key insights. First, AIA directly enhances SP and exerts indirect effects through the multiple mediating pathways of organizational agility (OA), green innovation (GI), and organizational resilience (OR). Second, GI serves as a core mediating pathway, playing a pivotal role in connecting AIA with sustainable development goals. Third, OA generates performance gains through short-cycle resource reconfiguration, whereas OR provides stable support in uncertain environments; these two capabilities exhibit complementary characteristics across different time scales. Finally, the research elucidates the complete pathway wherein AIA influences SP through the serial mediation of OA, GI, and OR. This reveals the underlying logic of how AI drives sustainable development through the evolution of dynamic capabilities. By integrating findings across existing studies, this research helps to reconcile discrepancies in prior conclusions. It provides a novel theoretical explanation for understanding the complex mechanisms of AI-enabled corporate sustainable development and also offers practical implications for businesses advancing digital and intelligent transformation.