Personalized evaluation of the passive myocardium in ischemic cardiomyopathy via computational modeling using Bayesian optimization.

Biomechanics-based patient-specific modeling is a promising approach that has proved invaluable for its clinical potential to assess the adversities caused by ischemic heart disease (IHD). In the present study, we propose a framework to find the passive material properties of the myocardium and the unloaded shape of cardiac ventricles simultaneously in patients diagnosed with ischemic cardiomyopathy (ICM). This was achieved by minimizing the difference between the simulated and the target end-diastolic pressure-volume relationships (EDPVRs) using black-box Bayesian optimization, based on the finite element analysis (FEA). End-diastolic (ED) biventricular geometry and the location of the ischemia were determined from cardiac magnetic resonance (CMR) imaging. We employed our pipeline to model the cardiac ventricles of three patients aged between 57 and 66 years, with and without the inclusion of valves. An excellent agreement between the simulated and the target EDPVRs has been reached. Our results revealed that the incorporation of valvular springs typically leads to lower hyperelastic parameters for both healthy and ischemic myocardium, as well as a higher fiber Green strain in the viable regions compared to models without valvular stiffness. Furthermore, the addition of valve-related effects did not result in significant changes in myofiber stress after optimization. We concluded that more accurate results could be obtained when cardiac valves were considered in modeling ventricles. The present novel and practical methodology paves the way for developing digital twins of ischemic cardiac ventricles, providing a non-invasive assessment for designing optimal personalized therapies in precision medicine.

An articulated shape model to predict paediatric lower limb bone geometry using sparse landmarks.

Creating musculoskeletal models in a paediatric population currently involves either creating an image-based model from medical imaging data or a generic model using linear scaling. Image-based models provide a high level of accuracy but are time-consuming and costly to implement, on the other hand, linear scaling of an adult template musculoskeletal model is faster and common practice, but the output errors are significantly higher. An articulated shape model incorporates pose and shape to predict geometry for use in musculoskeletal models based on existing information from a population to provide both a fast and accurate method. From a population of 333 children aged 4-18 years old, we have developed an articulated shape model of paediatric lower limb bones to predict bone geometry from eight bone landmarks commonly used for motion capture. Bone surface root mean squared errors were found to be 2.63 ± 0.90 mm, 1.97 ± 0.61 mm, and 1.72 ± 0.51 mm for the pelvis, femur, and tibia/fibula, respectively. Linear scaling produced bone surface errors of 4.79 ± 1.39 mm, 4.38 ± 0.72 mm, and 4.39 ± 0.86 mm for the pelvis, femur, and tibia/fibula, respectively. Clinical bone measurement errors were low across all bones predicted using the articulated shape model, which outperformed linear scaling for all measurements. However, the model failed to accurately capture torsional measures (femoral anteversion and tibial torsion). Overall, the articulated shape model was shown to be a fast and accurate method to predict lower limb bone geometry in a paediatric population, superior to linear scaling.

Probabilistic Finite Element Analysis of Human Rib Biomechanics: A Framework for Improved Generalizability.

In dynamic impact events, thoracic injuries often involve rib fractures, which are closely related to injury severity. Previous studies have investigated the behavior of isolated ribs under impact loading conditions, but often neglected the variability in anatomical shape and tissue material properties. In this study, we used probabilistic finite element analysis and statistical shape modeling to investigate the effect of population-wide variability in rib cortical bone tissue mechanical properties and rib shape on the biomechanical response of the rib to impact loading. Using the probabilistic finite element analysis results, a response surface model was generated to rapidly investigate the biomechanical response of an isolated rib under dynamic anterior-posterior load given the variability in rib morphometry and tissue material properties. The response surface was used to generate pre-fracture force-displacement computational corridors for the overall population and a population sub-group of older mid-sized males. When compared to the experimental data, the computational mean response had a RMSE of 4.28N (peak force 94N) and 6.11N (peak force 116N) for the overall population and sub-group respectively, whereas the normalized area metric when comparing the experimental and computational corridors ranged from 3.32% to 22.65% for the population and 10.90% to 32.81% for the sub-group. Furthermore, probabilistic sensitivities were computed in which the contribution of uncertainty and variability of the parameters of interest was quantified. The study found that rib cortical bone elastic modulus, rib morphometry and cortical thickness are the random variables that produce the largest variability in the predicted force-displacement response. The proposed framework offers a novel approach for accounting biological variability in a representative population and has the potential to improve the generalizability of findings in biomechanical studies.

The effect of preterm birth on thalamic development based on shape and structural covariance analysis.

Acting as a central hub in regulating brain functions, the thalamus plays a pivotal role in controlling high-order brain functions. Considering the impact of preterm birth on infant brain development, traditional studies focused on the overall development of thalamus other than its subregions. In this study, we compared the volumetric growth and shape development of the thalamic hemispheres between the infants born preterm and full-term (Left volume: P = 0.027, Left normalized volume: P < 0.0001; Right volume: P = 0.070, Right normalized volume: P < 0.0001). The ventral nucleus region, dorsomedial nucleus region, and posterior nucleus region of the thalamus exhibit higher vulnerability to alterations induced by preterm birth. The structural covariance (SC) between the thickness of thalamus and insula in preterm infants (Left: corrected P = 0.0091, Right: corrected P = 0.0119) showed significant increase as compared to full-term controls. Current findings suggest that preterm birth affects the development of the thalamus and has differential effects on its subregions. The ventral nucleus region, dorsomedial nucleus region, and posterior nucleus region of the thalamus are more susceptible to the impacts of preterm birth.

Hainan four-eyed turtles actively select suitable stones to masquerade according to their own morphology.

Masquerade is a form of camouflage in which animals use their body size, shape, and coloration to resemble inanimate objects in their environment to deceive predators. However, there is a lack of experimental evidence to show that animals actively choose objects that match these body parameters. To explore how the Hainan four-eyed turtle, Sacalia insulensis, masquerades using suitable stones, we used indoor video surveillance technology to study the preferences of juvenile S. insulensis for stones of different sizes, shapes, and colors. The results indicated that under normal conditions, during the day, juvenile S. insulensis preferred larger oval or round stones, while at night, they preferred oval stones that were closer to their own size, with no significant preference for stone color during either time. When disturbed (by a researcher swinging their arm back and forth above the experimental setup every hour to mimic a predator), the turtles showed a preference for brown stones that were closer to their size and oval in shape. These findings suggest that juvenile S. insulensis prefer stones that resemble their carapace size and shape to masquerade when undisturbed, and that this preference is reinforced when they masquerade to reduce the risk of predation. The preference for stones that resemble their carapace color is significant only when there is a disturbance. To the best of our knowledge, this is the first study to provide evidence that vertebrates can selectively choose objects that resemble their own morphology for masquerading to reduce predation risk.

Shaping Drosophila eggs: unveiling the roles of Arpc1 and cpb in morphogenesis.

The Drosophila egg chamber (EC) starts as a spherical tissue at the beginning. With maturation, the outer follicle cells of EC collectively migrate in a direction perpendicular to the anterior-posterior axis, to shape EC from spherical to ellipsoidal. Filamentous actin (F-actin) plays a significant role in shaping individual migratory cells to the overall EC shape, like in every cell migration. The primary focus of this article is to unveil the function of different Actin Binding Proteins (ABPs) in regulating mature Drosophila egg shape. We have screened 66 ABPs, and the genetic screening data revealed that individual knockdown of Arp2/3 complex genes and the "capping protein ß" (cpb) gene have severely altered the egg phenotype. Arpc1 and cpb RNAi mediated knockdown resulted in the formation of spherical eggs which are devoid of dorsal appendages. Studies also showed the role of Arpc1 and cpb on the number of laid eggs and follicle cell morphology. Furthermore, the depletion of Arpc1 and cpb resulted in a change in F-actin quantity. Together, the data indicate that Arpc1 and cpb regulate Drosophila egg shape, F-actin management, egg-laying characteristics and dorsal appendages formation.

U shape association between triglyceride glucose index and congestive heart failure in patients with diabetes and prediabetes.

BACKGROUND: While previous population studies have shown that higher triglyceride-glucose (TyG) index values are associated with an increased risk of congestive heart failure (CHF), the relationship between TyG and CHF in patients with abnormal glucose metabolism remains understudied. This study aimed to evaluate the association between TyG and CHF in individuals with diabetes and prediabetes. METHODS: The study population was derived from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2018. The exposure variable, TyG, was calculated based on triglyceride and fasting blood glucose levels, while the outcome of interest was CHF. A multivariate logistic regression analysis was employed to assess the association between TyG and CHF. RESULTS: A total of 13,644 patients with diabetes and prediabetes were included in this study. The results from the fitting curve analysis demonstrated a non-linear U-shaped correlation between TyG and CHF. Additionally, linear logistic regression analysis showed that each additional unit of TyG was associated with a non-significant odds ratio (OR) of 1.03 (95%CI: 0.88-1.22, P = 0.697) for the prevalence of CHF. A two-piecewise logistic regression model was used to calculate the threshold effect of the TyG. The log likelihood ratio test (p < 0.05) indicated that the two-piecewise logistic regression model was superior to the single-line logistic regression model. The TyG tangent point was observed at 8.60, and on the left side of this point, there existed a negative correlation between TyG and CHF (OR: 0.54, 95%CI: 0.36-0.81). Conversely, on the right side of the inflection point, a significant 28% increase in the prevalence of CHF was observed per unit increment in TyG (OR: 1.28, 95%CI: 1.04-1.56). CONCLUSIONS: The findings from this study suggest a U-shaped correlation between TyG and CHF, indicating that both elevated and reduced levels of TyG are associated with an increased prevalence of CHF.

A Comparative Evaluation of the Efficiencies of Different Rotary File Systems in Terms of Remaining Dentin Thickness Using Cone Beam Computed Tomography: An In Vitro Study.

AIM: The aim of this study was to evaluate and compare the dentin thickness of the mesio-buccal canal of the lower first molar after canal preparation with three different rotary file systems using cone beam computed tomography (CBCT). METHODOLOGY: TruNatomy (Dentsply Sirona, USA), 2Shape (Micro-Mega, France), and One Curve (Micro-Mega, France) were the three different rotary files that were employed. A total of 45 excised human permanent first mandibular molars were divided into Groups A (TruNatomy), B (2Shape), and C (One Curve) at random. To measure the residual dentin thickness at 3 mm, 5 mm, and 7 mm from the radiographic apex, the mesial root of the tooth was removed from the tooth, and a mesio-buccal canal was taken. Samples were mounted in clear acrylic resin and were subjected to a pre-instrumentation CBCT scan. The mesio-buccal canal was cleaned and shaped while maintaining the final mesio-buccal canal preparation of Group A - 26/0.04, Group B - 25/0.04, and Group C - 25/0.04. The samples were extensively irrigated with 3% sodium hypochlorite and 17% EDTA, and a post-instrumentation scan was performed on them. Statistics were used to determine the values from CBCT scans that were recorded for pre- and post-instrumentations. RESULTS: The results showed that Group A had the greatest drop in dentin thickness, followed by Group B and Group C. The change in dentin thickness was greatest at 3 mm and 7 mm. CONCLUSION: In contrast to TruNatomy and 2Shape rotary file systems, One Curve has the advantage of maintaining a tooth's thickness at 3 and 7 millimeters from the radiological apex. Since the TruNatomy file system removes more dentin than the other two combined, it should be used cautiously. Choosing the right instrument is crucial for cleaning and shaping during root canal preparation.

Ammonium bicarbonate buffers combined with hybrid surface technology columns improve the peak shape of strongly tailing lipids.

BACKGROUND: Lipids such as phosphatidic acids (PAs) and cardiolipins (CLs) present strongly tailing peaks in reversed phase liquid chromatography, which entails low detectability. They are usually analyzed by hydrophilic interaction liquid chromatography (HILIC), which hampers high-throughput lipidomics. Thus, there is a great need for improved analytical methods in order to obtain a broader coverage of the lipidome in a single chromatographic method. We investigated the effect of ammonium bicarbonate (ABC) on peak asymmetry and detectability, in comparison with ammonium formate (AFO) on both a conventional BEH C18 column and an HST-CSH C18 column. RESULTS: The combination of 2.5 mM ABC buffer pH 8 with an HST-CSH C18 column produced significantly improved results, reducing the asymmetry factor at 10 % peak height of PA 16:0/18:1 from 8.4 to 1.6. Furthermore, on average, there was up to a 54-fold enhancement in the peak height of its [M - H]- ion compared to AFO and the BEH C18 column. We confirmed this beneficial effect on other strongly tailing lipids, with accessible phosphate moieties e.g., cardiolipins, phosphatidylinositol phosphate, phosphatidylinositol bisphosphate, phosphorylated ceramide and phosphorylated sphingosine. Furthermore, we found an increased detectability of phospho- and sphingolipids up to 28 times in negative mode when using an HST-CSH C18 column. The method was successfully applied to mouse liver samples, where previously undetected endogenous phospholipids could be analyzed with improved chromatographic separation. SIGNIFICANCE: In conclusion, the use of 2.5 mM ABC substantially improved the peak shape of PAs and enhanced the detectability of the lipidome in negative mode on an RPLC-ESI-Q-TOF-MS system on both BEH C18 and HST-CSH C18 columns. This method provides a wider coverage of the lipidome with one single injection for future lipidomic applications in negative mode.

Novel approach for characterizing clinical load application of superelastic orthodontic wires.

OBJECTIVE: Current standardized in vitro bending experiments for orthodontic archwires cannot capture friction conditions and load sequencing during multi-bracket treatment. This means that clinically relevant forces exerted by superelastic wires cannot be predicted. To address these limitations, this study explored a novel test protocol that estimates clinical load range. METHODS: The correction of a labially displaced maxillary incisor was simulated using an in vitro model with three lingual brackets. Deflection force levels derived from four different protocols were designed to explore the impact of friction and wire load history. These force levels were compared in nickel-titanium (NiTi) archwires with three commonly used diameters. The unloading path varied between protocols, with single or multiple sequences and different load orders and initial conditions. RESULTS: Deflection forces from the new protocol, employing multiple continuous load/unload cycles (CCincr), consistently exceeded those from the conventional protocol using a single continuous unloading path (CUdecr). Mean differences in plateau force ranged from 0.54 N (Ø 0.014" wire) to 1.19 N (Ø 0.016" wire). The CCinr protocol also provided average force range estimates of 0.47 N (Ø 0.012" wire), 0.89 N (Ø 0.014" wire), and 1.15 N (Ø 0.016" wire). SIGNIFICANCE: Clinical orientation towards CUdecr carries a high risk of excessive therapeutic forces because clinical loading situations caused by friction and load history are underestimated. Physiological tooth mobility using NiTi wires contributes decisively to the therapeutic load situation. Therefore, only short unloading sequences starting from the maximum deflection in the load history, as in CCincr, are clinically meaningful.

4D Printed Protein-AuNR Nanocomposites with Photothermal Shape Recovery.

4D printing is the 3D printing of objects that change chemically or physically in response to an external stimulus over time. Photothermally responsive shape memory materials are attractive for their ability to undergo remote activation. While photothermal methods using gold nanorods (AuNRs) have been used for shape recovery, 3D patterning of these materials into objects with complex geometries using degradable materials has not been addressed. Here, we report on the fabrication of 3D printed shape memory bioplastics with photo-activated shape recovery. Protein-based nanocomposites based on bovine serum albumin (BSA), poly (ethylene glycol) diacrylate and gold nanorods were developed for vat photopolymerization. These 3D printed bioplastics were mechanically deformed under high loads, and the proteins served as mechanoactive elements that unfolded in an energy-dissipating mechanism that prevented fracture of the thermoset. The bioplastic object maintained its metastable shape-programmed state under ambient conditions. Subsequently, up to 99% shape recovery was achieved within 1 min of irradiation with near-infrared light. Mechanical characterization and small angle X-ray scattering (SAXS) analysis suggest that the proteins mechanically unfold during the shape programming step and may refold during shape recovery. These composites are promising materials for the fabrication of biodegradable shape-morphing devices for robotics and medicine.

Computational discovery of AKT serine/threonine kinase 1 inhibitors through shape screening for rheumatoid arthritis intervention.

Rheumatoid Arthritis (RA) is a chronic, symmetrical inflammatory autoimmune disorder characterized by painful, swollen synovitis and joint erosions, which can cause damage to bone and cartilage and be associated with progressive disability. Despite expanded treatment options, some patients still experience inadequate response or intolerable adverse effects. Consequently, the treatment options for RA remain quite limited. The enzyme AKT1 is crucial in designing drugs for various human diseases, supporting cellular functions like proliferation, survival, metabolism, and angiogenesis in both normal and malignant cells. Therefore, AKT serine/threonine kinase 1 is considered crucial for targeting therapeutic strategies aimed at mitigating RA mechanisms. In this context, directing efforts toward AKT1 represents an innovative approach to developing new anti-arthritis medications. The primary objective of this research is to prioritize AKT1 inhibitors using computational techniques such as molecular modeling and dynamics simulation (MDS) and shape-based virtual screening (SBVS). A combined SBVS approach was employed to predict potent inhibitors against AKT1 by screening a pool of compounds sourced from the ChemDiv and IMPPAT databases. From the SBVS results, only the top three compounds, ChemDiv_7266, ChemDiv_2796, and ChemDiv_9468, were subjected to stability analysis based on their high binding affinity and favorable ADME/Tox properties. The SBVS findings have revealed that critical residues, including Glu17, Gly37, Glu85, and Arg273, significantly contribute to the successful binding of the highest-ranked lead compounds at the active site of AKT1. This insight helps to understand the specific binding mechanism of these leads in inhibiting RA, facilitating the rational design of more effective therapeutic agents.

Exploring Phylogenetic Signal in Multivariate Phenotypes by Maximizing Blomberg's K.

Due to the hierarchical structure of the tree of life, closely related species often resemble each other more than distantly related species; a pattern termed phylogenetic signal. Numerous univariate statistics have been proposed as measures of phylogenetic signal for single phenotypic traits, but the study of phylogenetic signal for multivariate data, as is common in modern biology, remains challenging. Here we introduce a new method to explore phylogenetic signal in multivariate phenotypes. Our approach decomposes the data into linear combinations with maximal (or minimal) phylogenetic signal, as measured by Blomberg's K. The loading vectors of these phylogenetic components or K-components can be biologically interpreted, and scatterplots of the scores can be used as a low-dimensional ordination of the data that maximally (or minimally) preserves phylogenetic signal. We present algebraic and statistical properties, along with two new summary statistics, KA and KG, of phylogenetic signal in multivariate data. Simulation studies showed that KA and KG have higher statistical power than the previously suggested statistic Kmult, especially if phylogenetic signal is low or concentrated in a few trait dimensions. In two empirical applications to vertebrate cranial shape (crocodyliforms and papionins), we found statistically significant phylogenetic signal concentrated in a few trait dimensions. The finding that phylogenetic signal can be highly variable across the dimensions of multivariate phenotypes has important implications for current maximum likelihood approaches to phylogenetic signal in multivariate data.

Physiological and structural traits contribute to thermotolerance in wild Australian cotton species.

BACKGROUND AND AIMS: Five species of cotton (Gossypium) were exposed to 38°C days during early vegetative development. Commercial cotton (Gossypium hirsutum) was contrasted with four wild cotton species (G. australe, G. bickii, G. robinsonii and G. sturtianum) that are endemic to central and northern Australia. METHODS: Plants were grown at daytime maxima of 30°C or 38°C for 25 d, commencing at the four-leaf stage. Leaf areas and shoot biomass were used to calculate relative rates of growth and specific leaf areas. Leaf gas exchange measurements revealed assimilation and transpiration rates, as well as electron transport rates (ETR) and carboxylation efficiency (CE) in steady-state conditions. Finally, leaf morphological traits (mean leaf area and leaf shape were quantified), along with leaf surface decorations, imaged using scanning electron microscopy. KEY RESULTS: Shoot morphology was differentially affected by heat, with three of the four wild species growing faster at 38°C than at 30°C, whereas early growth in G. hirsutum was severely inhibited by heat. Areas of individual leaves and leaf numbers both contributed to these contrasting growth responses, with fewer, smaller leaves at 38°C in G. hirsutum. CO2 assimilation and transpiration rates of G. hirsutum were also dramatically reduced by heat. Cultivated cotton failed to achieve evaporative cooling, contrasting with the transpiration-driven cooling in the wild species. Heat substantially reduced ETR and CE in G. hirsutum, with much smaller effects in the wild species. We speculate that leaf shape, as assessed by invaginations of leaf margins, and leaf size contributed to heat dispersal differentially among the five species. Similarly, reflectance of light radiation was also highly distinctive for each species. CONCLUSIONS: These four wild Australian relatives of cotton have adapted to hot days that are inhibitory to commercial cotton, deploying a range of physiological and structural adaptations to achieve accelerated growth at 38°C.

Polyhedral Vinyl Polymer Particles Synthesized Via Solvent-Free Radical Polymerization.

Liquid marbles (LMs) with a cubic shape are created by using various vinyl monomers as an inner liquid and polymer plates with mm size as a stabilizer. The relationship between the surface tension of the vinyl monomers and formability of the LMs is investigated. LMs can be fabricated using vinyl monomers with surface tensions of 42.7-40.3 mN m-1. The cubic polymer particles are successively synthesized via free-radical polymerizations by irradiation of the cubic LMs with UV light in a solvent-free manner. In addition, controlling the number of polymer plates per one LM, the shape of the plate or the coalescence of the LMs can lead to production of polymer particles with desired forms (e.g., Platonic and rectangular solids) that correspond to the shapes of the original LMs.

Domain adaptation using AdaBN and AdaIN for high-resolution IVD mesh reconstruction from clinical MRI.

PURPOSE: Deep learning has firmly established its dominance in medical imaging applications. However, careful consideration must be exercised when transitioning a trained source model to adapt to an entirely distinct environment that deviates significantly from the training set. The majority of the efforts to mitigate this issue have predominantly focused on classification and segmentation tasks. In this work, we perform a domain adaptation of a trained source model to reconstruct high-resolution intervertebral disc meshes from low-resolution MRI. METHODS: To address the outlined challenges, we use MRI2Mesh as the shape reconstruction network. It incorporates three major modules: image encoder, mesh deformation, and cross-level feature fusion. This feature fusion module is used to encapsulate local and global disc features. We evaluate two major domain adaptation techniques: adaptive batch normalization (AdaBN) and adaptive instance normalization (AdaIN) for the task of shape reconstruction. RESULTS: Experiments conducted on distinct datasets, including data from different populations, machines, and test sites demonstrate the effectiveness of MRI2Mesh for domain adaptation. MRI2Mesh achieved up to a 14% decrease in Hausdorff distance (HD) and a 19% decrease in the point-to-surface (P2S) metric for both AdaBN and AdaIN experiments, indicating improved performance. CONCLUSION: MRI2Mesh has demonstrated consistent superiority to the state-of-the-art Voxel2Mesh network across a diverse range of datasets, populations, and scanning protocols, highlighting its versatility. Additionally, AdaBN has emerged as a robust method compared to the AdaIN technique. Further experiments show that MRI2Mesh, when combined with AdaBN, holds immense promise for enhancing the precision of anatomical shape reconstruction in domain adaptation.

Establishment of Physalis alkekengi cell suspension culture: time-dependent behavior of genes related to the steroidal compounds, key enzymes, and physalins under static magnetic field.

Cell suspension culture has the potential to be a valuable source for the bioactive compound productions. In this study, an optimized procedure was established for callus and cell suspension culture of Physalis alkekengi for the first time, and the impact of static magnetic field (SMF, 6 mT) was studied on the high-value metabolic compounds through investigation of signaling molecules and gene expressions at the late log-to-stationary phase. Results showed that the growth regulators of 6-benzyl amino purine (BAP, 1.5 mg-1 L) and 1-naphthaleneacetic acid (NAA, 0.4 mg-1 L) induced the highest fresh weight, callus rate, callus index, and total withanolides. Cell suspension culture was established in the liquid MS medium supplied with BAP (1.5 mg-1 L) and NAA (0.1 mg-1 L). SMF application decreased slightly the cell growth and viability and enhanced the number of round-shaped cells. The hydrogen peroxide (H2O2) and nitric oxide (NO) levels increased at an all-time series after SMF exposure, and their maximum contents were observed after 12 h. A significant alteration of malondialdehyde content was also identified after 12 h of SMF exposure. The expression of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR), 1-deoxyD-xylulose 5-phosphate synthase (DXS), squalene synthase (SQS), sterol Δ7-reductase (DWF5), and C-7,8 sterol isomerase (HYD1) genes was upregulated significantly after 24 and 48 h. An increase in the total withanolides was related to more activity of HMGR and DXS enzymes in SMF-exposed cells and the maximum physalin A (12.8 mg g-1 DW) and physalin B (1.92 mg g-1 DW) obtained after 24 h compared to controls. Findings suggest that SMF can play a supportive factor in inducing steroidal compounds in P. alkekengi through modulating H2O2 and NO levels and the related-gene expressions.

Research on FBG Tactile Sensing Shape Recognition Based on Convolutional Neural Network.

Shape recognition plays a significant role in the field of robot perception. In view of the low efficiency and few types of shape recognition of the fiber tactile sensor applied to flexible skin, a convolutional-neural-network-based FBG tactile sensing array shape recognition method was proposed. Firstly, a sensing array was fabricated using flexible resin and 3D printing technology. Secondly, a shape recognition system based on the tactile sensing array was constructed to collect shape data. Finally, shape classification recognition was performed using convolutional neural network, random forest, support vector machine, and k-nearest neighbor. The results indicate that the tactile sensing array exhibits good sensitivity and perception capability. The shape recognition accuracy of convolutional neural network is 96.58%, which is 6.11%, 9.44%, and 12.01% higher than that of random forest, k-nearest neighbor, and support vector machine. Its F1 is 96.95%, which is 6.3%, 8.73%, and 11.94% higher than random forest, k-nearest neighbor, and support vector machine. The research of FBG shape sensing array based on convolutional neural network provides an experimental basis for shape perception of flexible tactile sensing.

When Trustworthiness Meets Face: Facial Design for Social Robots.

As a technical application in artificial intelligence, a social robot is one of the branches of robotic studies that emphasizes socially communicating and interacting with human beings. Although both robot and behavior research have realized the significance of social robot design for its market success and related emotional benefit to users, the specific design of the eye and mouth shape of a social robot in eliciting trustworthiness has received only limited attention. In order to address this research gap, our study conducted a 2 (eye shape) × 3 (mouth shape) full factorial between-subject experiment. A total of 211 participants were recruited and randomly assigned to the six scenarios in the study. After exposure to the stimuli, perceived trustworthiness and robot attitude were measured accordingly. The results showed that round eyes (vs. narrow eyes) and an upturned-shape mouth or neutral mouth (vs. downturned-shape mouth) for social robots could significantly improve people's trustworthiness and attitude towards social robots. The effect of eye and mouth shape on robot attitude are all mediated by the perceived trustworthiness. Trustworthy human facial features could be applied to the robot's face, eliciting a similar trustworthiness perception and attitude. In addition to empirical contributions to HRI, this finding could shed light on the design practice for a trustworthy-looking social robot.