Grain boundary plane (GBP) orientation is a key descriptor of grain boundary character and strongly influences interfacial processes such as solute segregation, precipitation and phase transformation. Conventional two-dimensional imaging and orientation mapping based on scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD), however, provide only a grain boundary trace on a polished surface and therefore cannot uniquely determine the local three-dimensional GBP. Here we present a practical workflow that combines SEM/EBSD with site-specific focused ion beam (FIB) sectioning to reconstruct the local GBP from two experimentally accessible traces of the same grain boundary segment: the surface trace measured on the SEM/EBSD section and a second trace revealed on an FIB cross-section. After registering the two trace vectors into a common EBSD reference frame, the GBP normal is obtained from their cross product. Using a grain boundary α segment in Ti-6Al-4V as a worked example, we demonstrate how the reconstructed local GBP can be represented in the EBSD and crystal reference frames to quantify its geometric relationships with candidate habit planes and invariant-line-related directions.
Quantitative evaluation of antimicrobial peptide (AMP) activity is important for identifying promising peptide candidates and supporting their development. Here, we propose a new method for predicting and evaluating AMP activity by integrating atomic force microscopy (AFM) imaging, quantitative nanomechanical measurements, and machine learning. Using FC8-A12L (A12L) against Escherichia coli as a model system, AFM Quantitative Imaging simultaneously characterized bacterial height, adhesion force, and Young’s modulus at different peptide concentrations. A dual-channel threshold-intersection strategy combining height and Young’s modulus maps was developed to identify bacterial regions and automatically extract spatially matched measurements of all three parameters. These measurements revealed changes in bacterial morphology, a biphasic variation in adhesion, and progressive mechanical softening with increasing A12L concentration, providing complementary biophysical information for assessing antibacterial effects. Machine learning integrated the extracted parameters to establish quantitative relationships between bacterial biophysical properties and A12L treatment levels. The multilayer perceptron showed the best predictive performance in the comparison of untreated and 25 μg/mL-treated bacteria. Prediction across 0, 12.5, 25, and 50 μg/mL achieved a test R² of 0.99897 and a root mean squared error of 0.59210 μg/mL. By connecting AFM measurements with automated feature extraction and predictive modeling, this study provides a new approach to quantitative evaluation of AMP activity and a complementary tool for assessing peptide efficacy.
Peanuts (Arachis hypogaea L.) seed tissues differ in structure and function, yet their surface morphology, internal anatomy, and elemental composition during development have not been examined in a combined microscopy framework. Seeds of three runner-type cultivars, Georgia-06G (G-06), Georgia-12Y (G-12Y), and Georgia-18RU (G-18) were sampled across reproductive stages R3–R8 and analyzed using histology, scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS). SEM and histology revealed hull sclerenchyma, cotyledonary parenchyma, and distinct outer–inner surface variations in both hull and seed coat. Inner cotyledon stomata were classified as anomocytic, anisocytic, and paracytic. Elemental analysis indicated non-uniform calcium (Ca) and silicon (Si) distributions across tissues and stages. Outer hull Si ranged from 2.50 to 9.97 wt concentration percentage (wt%); inner hull Si remained below 0.5 wt%, except for G-06 at R3 (1.86 wt%). Outer hull Ca peaked early and declined with maturity; G-18 reached 4.95 wt% at R3, approximately 3.6- to 3.8-fold higher than other cultivars. Inner hull Ca reached 3.48 wt% in G-12Y at R3. Seed coat Ca and Si were consistently lower, remaining below 0.85 wt% and 0.51 wt%, respectively. EDS data are semi-quantitative and biological replication was not included; results are presented descriptively. These findings support a layered structural and elemental barrier organization in peanut reproductive tissues.
Phasmatodea is a relatively small order of polyneopteran insects, comprising over 3100 described species, the vast majority of which belong to the suborder Euphasmatodea. Although this group exhibits considerable morphological diversity and a broad geographic distribution, its internal systematics remains only partially resolved. Current knowledge of euphasmatodean spermatology is notably fragmented, as existing studies have predominantly emphasized the conservation of a general sperm model. The present study describes the male reproductive system and provides a detailed ultrastructural analysis of the spermatozoon of Hesperophasma planulum (Westwood, 1859), a species endemic to the eastern region of Hispaniola Island, whose systematic placement remains controversial. The spermatozoa of H. planulum exhibit several hallmark features of euphasmatodean sperm, including a simplified acrosomal lacking a perforatorium, a well-developed centriolar adjunct associated with a peculiar centriolar structure, two large, laminated, accessory bodies alongside the axoneme, that replace the mitochondrial derivatives, and a flattened flagellum provided with an “undulating membrane”. However, several traits, including a significant reduction in total length, a remarkably short nucleus, a substantially elongated centriolar adjunct, and exceptionally large, laminated accessory bodies, distinguish the spermatozoon of this species from all other euphasmatodeans described to date. These findings demonstrate that spermatological characters provide valuable taxonomic markers within Euphasmatodea, and integrating them with existing datasets will aid in resolving long-standing systematic uncertainties within the suborder.
