Effect of Surface Morphologies on the In Vitro and In Vivo Properties of Biomedical Metallic Materials.

Metallic biomaterials, including traditional bioinert materials (such as stainless steel, cobalt-chromium alloys, pure titanium, and titanium alloys), novel biodegradable metals (such as pure magnesium and magnesium alloys, pure zinc and zinc alloys, and pure iron and iron alloys), and biomedical metallic glasses, have been widely used and studied as various biomedical implants and devices. Many scientists and researchers have investigated their superior biomechanical properties, corrosion behavior, and biocompatibility. However, their surface characteristics are of extreme importance due to continuing interactions between the surface/interface of an implanted metallic biomaterial and the surrounding physiological environment. Surface morphologies on these metallic biomaterials can modulate their in vitro and in vivo biological responses. In this review, we have summarized and investigated the effect of various surface morphologies on the corrosion behavior, cellular response, antibacterial activity, and osteogenesis of biomedical metallic materials. In addition, future research directions and challenges of surface morphologies on biomedical metallic materials have been elaborated. This review can lay a theoretical and practical foundation for further research and development on biomedical metallic materials.

YOLO-PBESW: A Lightweight Deep Learning Model for the Efficient Identification of Indomethacin Crystal Morphologies in Microfluidic Droplets.

Crystallization is important to the pharmaceutical, the chemical, and the materials fields, where the morphology of crystals is one of the key factors affecting the quality of crystallization. High-throughput screening based on microfluidic droplets is a potent technique to accelerate the discovery and development of new crystal morphologies with active pharmaceutical ingredients. However, massive crystal morphologies' datum needs to be identified completely and accurately, which is time-consuming and labor-intensive. Therefore, effective morphologies' detection and small-target tracking are essential for high-efficiency experiments. In this paper, a new improved algorithm YOLOv8 (YOLO-PBESW) for detecting indomethacin crystals with different morphologies is proposed. We enhanced its capability in detecting small targets through the integration of a high-resolution feature layer P2, and the adoption of a BiFPN structure. Additionally, in this paper, adding the EMA mechanism before the P2 detection head was implemented to improve network attention towards global features. Furthermore, we utilized SimSPPF to replace SPPF to mitigate computational costs and reduce inference time. Lastly, the CIoU loss function was substituted with WIoUv3 to improve detection performance. The experimental findings indicate that the enhanced YOLOv8 model attained advancements, achieving AP metrics of 93.3%, 77.6%, 80.2%, and 99.5% for crystal wire, crystal rod, crystal sheet, and jelly-like phases, respectively. The model also achieved a precision of 85.2%, a recall of 83.8%, and an F1 score of 84.5%, with a mAP of 87.6%. In terms of computational efficiency, the model's dimensions and operational efficiency are reported as 5.46 MB, and it took 12.89 ms to process each image with a speed of 77.52 FPS. Compared with state-of-the-art lightweight small object detection models such as the FFCA-YOLO series, our proposed YOLO-PBESW model achieved improvements in detecting indomethacin crystal morphologies, particularly for crystal sheets and crystal rods. The model demonstrated AP values that exceeded L-FFCA-YOLO by 7.4% for crystal sheets and 3.9% for crystal rods, while also delivering a superior F1-score. Furthermore, YOLO-PBESW maintained a lower computational complexity, with parameters of only 11.8 GFLOPs and 2.65 M, and achieved a higher FPS. These outcomes collectively demonstrate that our method achieved a balance between precision and computational speed.

Block Copolymer-Directed Single-Diamond Hybrid Structures Derived from X-ray Nanotomography.

Block copolymers are recognized as a valuable platform for creating nanostructured materials. Morphologies formed by block copolymer self-assembly can be transferred into a wide range of inorganic materials, enabling applications including energy storage and metamaterials. However, imaging of the underlying, often complex, nanostructures in large volumes has remained a challenge, limiting progress in materials development. Taking advantage of recent advances in X-ray nanotomography, we noninvasively imaged exceptionally large volumes of nanostructured hybrid materials at high resolution, revealing a single-diamond morphology in a triblock terpolymer-gold composite network. This morphology, which is ubiquitous in nature, has so far remained elusive in block copolymer-derived materials, despite its potential to create materials with large photonic bandgaps. The discovery was made possible by the precise analysis of distortions in a large volume of the self-assembled diamond network, which are difficult to unambiguously assess using traditional characterization tools. We anticipate that high-resolution X-ray nanotomography, which allows imaging of much larger sample volumes than electron-based tomography, will become a powerful tool for the quantitative analysis of complex nanostructures and that structures such as the triblock terpolymer-directed single diamond will enable the generation of advanced multicomponent composites with hitherto unknown property profiles.

Can the efficacy of a medical treatment be predicted based on the type of idiopathic premature ventricular contraction?

BACKGROUND: Premature ventricular contractions (PVCs) are common arrhythmias with diverse clinical implications. This retrospective study aimed to evaluate the efficacy of medical treatments using various clinical, imaging, and electrocardiographic parameters in patients with idiopathic PVCs. METHODS: A total of 1051 patients with idiopathic PVCs were retrospectively analyzed. Patients were categorized into three groups based on treatment response: beta-blocker (BB) responders (479 patients), calcium-channel blocker (CCB) responders (335 patients), and class 1c antiarrhythmic (AA) responders (237 patients). Clinical, imaging, and electrocardiographic data were collected and analyzed to assess the factors influencing treatment response. RESULTS: Age, left ventricular ejection fraction (LVEF), PVC QRS duration, CI variability, and multiple PVC morphologies were identified as significant factors affecting treatment response. Older age and lower LVEF were associated with better response to BB treatment, whereas CCB responders showed narrower QRS complexes. BB responders also exhibited higher CI variability, possibly linked to automaticity mechanisms. Moreover, the BB responder group had a higher frequency of multiple PVC morphologies. CONCLUSION: These findings emphasize the importance of tailored treatment approaches based on individual patient characteristics.

Wide-Field Polarimetric Second-Harmonic Imaging for Rapid and Nondestructive Investigation of Laser-Induced Crystallization Phenomena.

The selective and controlled formation of nanocrystals in glass is emerging as a versatile method to achieve functional photonics, optoelectronics, and quantum devices, such as single-photon emitters. Here, we investigate the use of wide-field polarimetric second-harmonic (SH) microscopy as a method to rapidly and nondestructively examine nanoscale crystal arrangements in laser-processed glass. As a case study, we investigate tellurite glass, where the formation of a trigonal tellurium (t-Te) nanocrystalline phase after femtosecond laser exposure was recently demonstrated. Combined with theoretical models, we show that wide-field polarimetric SH microscopy offers comprehensive information on the nanocrystals' orientation, distribution, and chirality. With its high imaging throughput and spatial resolution, this method has the potential not only to significantly accelerate investigations on laser-induced glass crystallization processes but also to provide a valuable tool for in situ process monitoring.

Optimized hybrid edible surface coating prepared with gelatin and cellulose nanofiber for cherry tomato preservation.

The use of renewable bioresources and their nanoforms in developing edible coating materials is considered a promising approach for preserving food freshness. Herein, cellulose nanofibers (CNF) with different morphologies were combined with gelatin to prepare composite preservation film following by brushing over the surface of cherry tomatoes as an edible coating. The gelatin-based composite film containing 0.3 % CNF20 (GC2-0.3) exhibited the lowest water vapor permeability (WVP, 1.97 × 10-4 barrer), lower oxygen permeability (OP, 2.54 × 10-2 barrer), higher transparency (Tr = 85.28 %) and excellent mechanical properties (σ = 47.45 MPa, E = 1.84 GPa). When coated on cherry tomatoes, it maintained good luster and freshness, significantly reducing the water loss of cherry tomatoes. The weight loss was only 16 % after 14 days of storage at 25 °C and 30 % humidity, compared to >30 % for the uncoated cherry tomatoes. This work provides a viable strategy for developing sustainable, green fresh-keeping materials that can prolong the storage time of the putrescible food.

Electrodermal Activity (EDA) Morphologies and Prediction of Engagement with Simple Moving Average Crossover: A Mixed-Method Study.

Electrodermal Activity (EDA), which primarily indicates arousal through sympathetic nervous system activity, serves as a tool to measure constructs like engagement, cognitive load, performance, and stress. Despite its potential, empirical studies have often yielded mixed results and found it of limited use. To better understand EDA, we conducted a mixed-methods study in which quantitative EDA profiles and survey data were investigated using qualitative interviews. This study furnishes an EDA dataset measuring the engagement levels of seven participants who watched three videos for 4-10 min. The subsequent interviews revealed five EDA morphologies with varying short-term signatures and long-term trends. We used this dataset to demonstrate the moving average crossover, a novel metric for EDA analysis, in predicting engagement-disengagement dynamics in such data. Our contributions include the creation of the detailed dataset, comprising EDA profiles annotated with qualitative data, the identification of five distinct EDA morphologies, and the proposition of the moving average crossover as an indicator of the beginning of engagement or disengagement in an individual.

Numerical investigation on the impact of different coronary aneurysms morphologies on thrombus formation and hemodynamics: a comparative study.

Coronary artery aneurysms (CAAs) are morphologically classified as saccular and fusiform. There is still a great deal of clinical controversy as to which types of CAA are more likely to cause thrombosis. Therefore, the main objective of this study was to evaluate the trend of thrombus growth in CAAs with different morphologies and to assess the risk of possible long-term complications based on hemodynamic parameters. Utilizing computed tomography angiography (CTA) data from eight healthy coronary arteries, two distinct morphologies of coronary artery aneurysms (CAAs) were reconstructed. Distribution of four wall shear stress (WSS)-based indicators and three helicity indicators was analyzed in this study. Meanwhile, a thrombus growth model was introduced to analyze the thrombus formation in CAAs with different morphologies. The research results showed the distribution of most WSS indicators between saccular and fusiform CAAs was not statistically significant. However, due to the presence of a more pronounced helical flow pattern, irregular helical flow structure and longer time of flow stagnation in saccular CAAs during the cardiac cycle, the mean and maximum relative residence time (RRT) were significantly higher in saccular CAAs than in fusiform CAAs (P < 0.05). This may increase the risk of saccular coronary arteries leading to aneurysmal dilatation or even rupture. Although the two CAAs had similar rates of thrombosis, fusiform CAAs may more early cause obstruction of the main coronary flow channel where the aneurysm is located due to thrombosis growth. Thus, the risk of thrombosis in fusiform coronary aneurysms may warrant greater clinical concern.

Deep Learning Powered Identification of Differentiated Early Mesoderm Cells from Pluripotent Stem Cells.

Pluripotent stem cells can be differentiated into all three germ-layers including ecto-, endo-, and mesoderm in vitro. However, the early identification and rapid characterization of each germ-layer in response to chemical and physical induction of differentiation is limited. This is a long-standing issue for rapid and high-throughput screening to determine lineage specification efficiency. Here, we present deep learning (DL) methodologies for predicting and classifying early mesoderm cells differentiated from embryoid bodies (EBs) based on cellular and nuclear morphologies. Using a transgenic murine embryonic stem cell (mESC) line, namely OGTR1, we validated the upregulation of mesodermal genes (Brachyury (T): DsRed) in cells derived from EBs for the deep learning model training. Cells were classified into mesodermal and non-mesodermal (representing endo- and ectoderm) classes using a convolutional neural network (CNN) model called InceptionV3 which achieved a very high classification accuracy of 97% for phase images and 90% for nuclei images. In addition, we also performed image segmentation using an Attention U-Net CNN and obtained a mean intersection over union of 61% and 69% for phase-contrast and nuclear images, respectively. This work highlights the potential of integrating cell culture, imaging technologies, and deep learning methodologies in identifying lineage specification, thus contributing to the advancements in regenerative medicine. Collectively, our trained deep learning models can predict the mesoderm cells with high accuracy based on cellular and nuclear morphologies.

Functionality Modulation Toward Thianthrene-based Metal-Free Electrocatalysts for Water Splitting.

The development of metal-free bifunctional electrocatalysts for hydrogen and oxygen evolution reactions (HER and OER) is significant but rarely demonstrated. Porous organic polymers (POPs) with well-defined electroactive functionalities show superior performance in hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). Precise control of the active sites' local environment requires careful modulation of linkers through the judicious selection of building units. Here, a systematic strategy is introduced for modulating functionality to design and synthesize a series of thianthrene-based bifunctional sp2 C═C bonded POPs with hollow spherical morphologies exhibiting superior electrocatalytic activity. This precise structural tuning allowed to gain insight into the effects of heteroatom incorporation, hydrophilicity, and variations in linker length on electrocatalytic activity. The most efficient bifunctional electrocatalyst THT-PyDAN achieves a current density of 10 mA cm─2 at an overpotential (η10) of ≈65 mV (in 0.5 m H2SO4) and ≈283 mV (in 1 m KOH) for HER and OER, respectively. THT-PyDAN exhibits superior activity to all previously reported metal-free bifunctional electrocatalysts in the literature. Furthermore, these investigations demonstrate that THT-PyDAN maintains its performance even after 36 h of chronoamperometry and 1000 CV cycling. Post-catalytic characterization using FT-IR, XPS, and microscopic imaging techniques underscores the long-term durability of THT-PyDAN.

Quantifying morphologies of developing neuronal cells using deep learning with imperfect annotations.

The functionality of human intelligence relies on the interaction and health of neurons, hence, quantifying neuronal morphologies can be crucial for investigating the functionality of the human brain. This paper proposes a deep learning (DL) based method for segmenting and quantifying neuronal structures in fluorescence microscopy images of developing neuronal cells cultured in vitro. Compared to the majority of supervised DL-based segmentation methods that heavily rely on creating exact corresponding masks of neuronal structures for the preparation of training samples, the proposed approach allows for imperfect annotation of neurons, as it only requires tracing the centrelines of the neurites. This ability accelerates the preparation of training data by several folds. Our proposed framework is built on a modified version of PSPNet with an EfficientNet backbone pre-trained on the CityScapes dataset. To handle the imperfectness of training samples, we incorporated a weighted combination of two loss functions, namely the Dice loss and Lovász loss functions, into our network. We evaluated the proposed framework and several other state-of-the-art methods on a published dataset of approximately 900 manually quantified cultured mouse neurons. Our results indicate a close correlation between the proposed method and manual quantification in terms of neuron length and the number of branches while demonstrating improved analysis speed. Furthermore, the proposed method achieved high accuracy in neuron segmentation, as evidenced by the evaluation of the neurons' length and number of branches.

Recent advancements in bionanomaterial applications of peptide nucleic acid assemblies.

Peptide nucleic acid (PNA) is a unique combination of peptides and nucleic acids. PNA can exhibit hydrogen bonding interactions with complementary nucleobases like DNA/RNA. Also, its polyamide backbone allows easy incorporation of biomolecules like peptides and proteins to build hybrid molecular constructs. Because of chimeric structural properties, PNA has lots of potential to build diverse nanostructures. However, progress in the PNA material field is still immature compared with its massive applications in antisense oligonucleotide research. Examples of well-defined molecular assemblies have been reported with PNA amphiphiles, self-assembling guanine-PNA monomers/dimers, and PNA-decorated nucleic acids/ polymers/ peptides. All these works indicate the great potential of PNA to be used as bionanomaterials. The review summarizes the recent reports on PNA-based nanostructures and their versatile applications. Additionally, this review shares a perspective to promote a better understanding of controlling molecular assembly by the systematic structural modifications of PNA monomers.

Tethered Small-Molecule Acceptor Refines Hierarchical Morphology in Ternary Polymer Solar Cells: Enhanced Stability and 19% Efficiency.

Polymer solar cells (PSCs) are promising for efficient solar energy conversion, but achieving high efficiency and device longevity within a bulk-heterojunction (BHJ) structure remains a challenge. Traditional small-molecule acceptors (SMAs) in the BHJ blend show thermodynamic instability affecting the morphology. In contrast, tethered SMAs exhibit higher glass transition temperatures, mitigating these concerns. Yet, they might not integrate well with polymer donors, causing pronounced phase separation and overpurification of mixed domains. Herein, a novel ternary device is introduced that uses DY-P2EH, a tethered dimeric SMA with conjugated side-chains as host acceptor, and BTP-ec9, a monomeric SMA as secondary acceptor, which respectively possess hypomiscibility and hypermiscibility with the polymer donor PM6. This unique combination affords a parallel-connected ternary BHJ blend, leading to a hierarchical and stable morphology. The ternary device achieves a remarkable fill factor of 80.61% and an impressive power conversion efficiency of 19.09%. Furthermore, the ternary device exhibits exceptional stability, retaining over 85% of its initial efficiency even after enduring 1100 h of thermal stress at 85 °C. These findings highlight the potential advantage of tethered SMAs in the design of ternary devices with a refined hierarchical structure for more efficient and durable solar energy conversion technologies.

Selectively Modulating Componential Morphologies of Bulk Heterojunction Organic Solar Cells.

Achieving precise control over the nanoscale morphology of bulk heterojunction films presents a significant challenge for the conventional post-treatments employed in organic solar cells (OSCs). In this study, a near-infrared photon-assisted annealing (NPA) strategy is developed for fabricating high-performance OSCs under mild processing conditions. It is revealed a top NIR light illumination, together with the bottom heating, enables the selective tuning of the molecular arrangement and assembly of narrow bandgap acceptors in polymer networks to achieve optimal morphologies, as well as the acceptor-rich top surface of active layers. The derived OSCs exhibit a remarkable power conversion efficiency (PCE) of 19.25%, representing one of the highest PCEs for the reported binary OSCs so far. Moreover, via the NPA strategy, it has succeeded in accessing top-illuminated flexible OSCs using thermolabile polyethylene terephthalate from mineral water bottles, displaying excellent mechanical stabilities. Overall, this work will hold the potential to develop organic solar cells under mild processing with various substrates.

Morphology Tuning via Linker Modulation: Metal-Free Covalent Organic Nanostructures with Exceptional Chemical Stability for Electrocatalytic Water Splitting.

The development of synthetic routes for the formation of robust porous organic polymers (POPs) with well-defined nanoscale morphology is fundamentally significant for their practical applications. The thermodynamic characteristics that arise from reversible covalent bonding impart intrinsic chemical instability in the polymers, thereby impeding their overall potential. Herein, a unique strategy is reported to overcome the stability issue by designing robust imidazole-linked POPs via tandem reversible/irreversible bond formation. Incorporating inherent rigidity into the secondary building units leads to robust microporous polymeric nanostructures with hollow-spherical morphologies. An in-depth analysis by extensive solid-state NMR (1D and 2D) study on 1H, 13C, and 14N nuclei elucidates the bonding and reveals the high purity of the newly designed imidazole-based POPs. The nitrogen-rich polymeric nanostructures are further used as metal-free electrocatalysts for water splitting. In particular, the rigid POPs show excellent catalytic activity toward the oxygen evolution reaction (OER) with long-term durability. Among them, the most efficient OER electrocatalyst (TAT-TFBE) requires 314 mV of overpotential to drive 10 mA cm-2 current density, demonstrating its superiority over state-of-the-art catalysts (RuO2 and IrO2).

Design, Optimization and Performance Assessment of Single Port Film Bulk Acoustic Resonator through Finite Element Simulation.

In this paper, the study is supported by design, FEA simulation, and practical RF measurements on fabricated single-port-cavity-based acoustic resonator for gas sensing applications. In the FEA simulation, frequency domain analysis was performed to enhance the performance of the acoustic resonator. The structural and surface morphologies of the deposited ZnO as a piezoelectric layer have been studied using XRD and AFM. The XRD pattern of deposited bulk ZnO film indicates the perfect single crystalline nature of the film with dominant phase (002) at 2θ = 34.58°. The AFM micrograph indicates that deposited piezoelectric film has a very smooth surface and small grain size. In the fabrication process, use of bulk micro machined oxide (SiO2) for the production of a thin membrane as a support layer is adopted. A vector network analyzer (Model MS2028C, Anritsu) was used to measure the radio frequency response of the resonators from 1 GHz to 2.5 GHz. As a result, we have successfully fabricated an acoustic resonator operating at 1.84 GHz with a quality factor Q of 214 and an effective electromechanical coupling coefficient of 10.57%.

Recent and rapid reef recovery around Koh Phangan Island, Gulf of Thailand, driven by plate-like hard corals.

Mass bleaching events and local anthropogenic influences have changed the benthic communities of many coral reefs with pronounced spatial differences that are linked to resilience patterns. The Gulf of Thailand is an under-investigated region with only few existing datasets containing long-term developments of coral reef communities using the same method at fixed sites. We thus analyzed benthic community data from seven reefs surrounding the island of Koh Phangan collected between 2014 and 2022. Findings revealed that the average live hard coral cover around Koh Phangan increased from 37% to 55% over the observation period, while turf algae cover decreased from 52% to 29%, indicating some recovery of local reefs. This corresponds to a mean increased rate of coral cover by 2.2% per year. The increase in live hard coral cover was mainly driven by plate-like corals, which quadrupled in proportion over the last decade from 7% to 28% while branching corals decreased in proportion from 9% to 2%. Furthermore, the hard coral genus richness increased, indicating an increased hard coral diversity. While in other reefs, increasing live hard coral cover is often attributed to fast-growing, branching coral species, considered more susceptible to bleaching and other disturbances, the reefs around Koh Phangan recovered mainly via growth of plate-like corals, particularly of the genus Montipora. Although plate-like morphologies are not necessarily more bleaching tolerant, they are important for supporting reef fish abundance and structural complexity on reefs, aiding reef recovery and sturdiness. Hence, our findings indicate that the intensity of local stressors around Kho Phangan allows reef recovery driven by some hard coral species.

The Influence of TiO2 Nanoparticles Morphologies on the Performance of Lithium-Ion Batteries.

Anode materials based on the TiO2 nanoparticles of different morphologies were prepared using the hydrothermal method and characterized by various techniques, such as X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), and N2 absorption. The TiO2 nanoparticles prepared were used as anode materials for lithium-ion batteries (LIBs), and their electrochemical properties were tested using discharging/charging measurements. The results showed that the initial morphology of the nanoparticles plays a minor role in battery performance after the first few cycles and that better capacity was achieved for TiO2 nanobelt morphology. The sharp drop in the specific capacity of LIB during their first cycles is examined by considering changes in the morphology of TiO2 particles and their porosity properties in terms of size and connectivity. The performance of TiO2 anode materials has also been assessed by considering their phase.

Recent advances and progress in biotemplate catalysts for electrochemical energy storage and conversion.

Complex structures and morphologies in nature endow materials with unexpected properties and extraordinary functions. Biotemplating is an emerging strategy for replicating nature structures to obtain materials with unique morphologies and improved properties. Recently, efforts have been made to use bio-inspired species as a template for producing morphology-controllable catalysts. Fundamental information, along with recent advances in biotemplate metal-based catalysts are presented in this review through discussions of various structures and biotemplates employed for catalyst preparation. This review also outlines the recent progress on preparation routes of biotemplate catalysts and discusses how the properties and structures of these templates play a crucial role in the final performance of metal-based catalysts. Additionally, the application of bio-based metal and metal oxide catalysts is highlighted for various key energy and environmental technologies, including photocatalysis, fuel cells, and lithium batteries. Biotemplate metal-based catalysts display high efficiency in several energy and environmental systems. Note that this review provides guidance for further research in this direction.

Mechanistic insights into the cinnamaldehyde modification of lignin for sustainable anti-fungal reagent.

The limited anti-fungal activity of enzymatic hydrolysis lignin (EHL) has been a challenge in its direct application as a bamboo preservative. To address this issue, the cinnamaldehyde modification of EHL was carried out to introduce anti-fungal structures into the lignin matrix, effectively enhancing its anti-fungal activity. The results demonstrated that the minimal inhibitory concentrations of the modified lignin (EHL-DC) against Aspergillus niger significantly improved from 16 mg/mL to 1 mg/mL, with comparable enhancements in anti-fungal activity against other fungi. As a result of the modification, the EHL-DC is more prone to interact with fungal cell membranes, contributing to a roughened, shrunken hyphal surface and a decrease in mycelial biomass. Multiple characterization methods were employed to better grapple with the EHL-DC chemical changes. The nitrogen content increased from 2.3 % to 8.3 %, and alterations in elemental compositions further support the proposed reaction mechanism and its role in enhancing EHL's anti-fungal activity. This study offers novel insights into the high-value utilization of enzymatic hydrolysis lignin based on green chemistry principles.