Search Results (54,636)

Nickel-titanium (NiTi) alloys are attractive for functional and biomedical applications due to their shape memory effect, superelasticity, and favorable corrosion resistance and biocompatibility. In this work, the influence of strut size on the compressive response of laser-based powder bed fusion (PBF-LB/M) fabricated NiTi ortho-octahedral porous scaffolds was systematically investigated using combined experiments and finite element simulations. Four scaffold designs with identical unit-cell size (2 mm) but different strut sizes (280, 320, 360, and 400 μm) were fabricated, and their forming quality and deformation behaviors were examined. The as-built scaffolds exhibited high geometric fidelity to the CAD models and stable manufacturability across the investigated parameter range. Quasi-static compression tests revealed a typical three-stage response (linear-elastic regime, plateau/collapse regime, and densification), with both elastic modulus and compressive strength increasing markedly with strut size. Specifically, the modulus increased from 1.17 to 4.28 GPa and the compressive strength increased from 155 to 564 MPa as the strut size increased from 280 to 400 μm. A pronounced oscillatory plateau was observed for the 280 μm scaffolds, indicating progressive layer-by-layer collapse, whereas larger struts promoted a shear-band-dominated failure mode characterized by an approximately 45° fracture zone. Explicit quasi-static simulations reproduced the experimentally observed collapse sequence and demonstrated that stress preferentially concentrates at nodal junctions, with load transfer dominated by struts aligned with the loading direction. The agreement between experiments and simulations confirms the predictive capability of the proposed modeling framework and provides mechanistic insights into geometry-controlled failure. These findings establish a structure-property-failure relationship for PBF-LB/M-fabricated NiTi octahedral scaffolds and offer practical guidance for tailoring stiffness, strength, and collapse mode through strut-size design. Full article

The further development of scalable fabrication for perovskite solar cells has been considerably constrained by strong process variability and the lack of a reliable real-time predictive mechanism during the thin-film formation process. Existing machine learning-based methods are incapable of capturing the inherent multi-stage kinetic characteristics and uncertainties of the perovskite crystallization process, as they rely on deterministic point prediction models and flatten time-series signals into static features, which necessitates more advanced modeling strategies. To address these challenges, an in situ process monitoring and predictive modeling framework based on a lightweight probabilistic Transformer is proposed for the scalable preparation of perovskite thin films. The strategically designed inputs, consisting of time-resolved photoluminescence (PL) and diffuse reflectance imaging signals acquired during the vacuum quenching process, enable the model to directly learn the conditional probability distribution of the final device performance metrics. Rather than producing a single predicted value, this method enables the explicit quantification of prediction uncertainty, providing statistical support for uncertainty-aware process assessment. Leveraging its advantages over feed-forward neural networks and traditional tree-based machine learning methods, the proposed Transformer architecture effectively captures the staged and non-stationary kinetic features of thin-film formation. Consequently, it exhibits higher robustness and superior uncertainty calibration capability during the early-stage prediction phase. The results demonstrate that the probabilistic Transformer-based modeling paradigm provides a viable pathway toward uncertainty-aware, data-driven process evaluation in perovskite manufacturing. This framework extends its application beyond perovskite photovoltaic device fabrication, providing a generalizable modeling strategy for real-time predictive assessment in the preparation of other complex materials governed by irreversible stochastic dynamics. Full article

Bacterial swarms provide a tractable natural model of active matter, where their dynamics illuminate the principles of collective behavior and self-organization phenomena. In particular, the mechanistic and dynamical features of monolayer swarming are critical in driving the transition to multilayer structures at the onset of biofilm formation. Here, we investigate monolayer swarms of Serratia marcescens across varying cell body aspect ratios and area fractions. The results show that at intermediate-to-low densities, bacteria form local dynamic clusters, with the distribution of cluster sizes determined by aspect ratio and area fraction. At higher densities, elongated bacteria align into active nematic states with half-integer topological defects, which point to a potential nucleation mechanism for multilayer formation. These findings provide new physical insights into how cellular morphology and density govern bacterial swarming dynamics and drive the early transition from monolayer swarming to multilayered biofilm development. Full article

Safety concerns surrounding skin-lightening agents have intensified following chemical leukoderma linked to rhododendrol. Here, we performed an in vitro safety and hazard profiling comparison of raspberry ketone (RK) and a total anthraquinone fraction from Fallopia multiflora var. cillinerve (Polygonum cillinerve) using an immortalized keratinocyte–melanocyte co-culture model (human HaCaT keratinocytes and murine B10.BR melanocytes, 3:1). Rhododendrol and arbutin were included as contextual references. Following viability-guided range finding, cells were exposed for 48 h and evaluated for melanocyte stress and injury, including ROS generation, UPR/ER-stress activation (PERK/eIF2α–ATF4-associated readouts: ATF4, Hmox1, GADD45a; and IRE1 phosphorylation), IL-8-related chemokine output (CXCL1/KC, a murine functional homolog of IL-8), cell-cycle perturbation, and Caspase-3-associated apoptosis. In parallel, targeted LC–MS metabolomics was performed to resolve pathway-level perturbations. High-dose RK elicited a rhododendrol-like in vitro stress/toxicity signature, characterized by elevated ROS, robust UPR engagement, inflammatory chemokine induction, cell-cycle dysregulation, and pro-apoptotic responses; under viability-adjusted conditions, these effects remained more evident than with arbutin. Metabolomics revealed convergent disturbances between RK and rhododendrol, highlighting purine metabolism as a prominent perturbed pathway and suggesting purine-related metabolites as candidate indicators associated with leukoderma-relevant cellular stress in vitro. In contrast, the anthraquinone fraction did not trigger oxidative or ER stress within the tested range and exhibited a more favorable in vitro safety profile, including reduced ROS. Full article

Background/Objectives: Gastric ulcer is a prevalent global gastrointestinal disorder influenced by multiple factors, including excessive alcohol consumption, poor dietary habits, psychological stress, smoking, and the chronic use of non-steroidal anti-inflammatory drugs. Among these, alcohol plays a critical role in gastric mucosal injury by enhancing gastric acid secretion, triggering inflammatory responses, inducing oxidative stress, and promoting epithelial cell apoptosis while simultaneously depleting key protective mediators such as nitric oxide and prostaglandin E₂. Growing interest has focused on medicinal plants as promising sources of novel therapeutic agents for the management of peptic ulcer disease. Methods: This review summarizes commonly used medicinal plants documented in both Ayurvedic and modern medical systems that exhibit ulcer-healing potential. Experimental and preclinical studies indicate that various herbal drugs and plant extracts derived from different plant parts exert significant anti-ulcer effects through multiple mechanisms, including antioxidant activity, modulation of inflammatory pathways, enhancement of mucosal defense, and inhibition of gastric acid secretion. Results: The review further highlights the gastroprotective effects of these herbal remedies as demonstrated in established experimental ulcer models. Conclusions: Exploring plant-based therapies for gastric ulcers offers valuable insights into alternative and complementary treatment strategies. Continued research aimed at identifying bioactive compounds, elucidating their molecular mechanisms, and developing improved formulations may contribute to safer, more effective, and patient-friendly therapeutic options for peptic ulcer management. Full article

Autoimmune hepatitis (AIH) is an inflammatory liver disease characterised by immune-mediated hepatic injury, often leading to liver failure. The underlying molecular mechanisms of AIH remain poorly elucidated, hindering diagnostic and therapeutic advances. This review overviews the current understanding of AIH pathogenesis, which arises from a complex interplay of genetic predisposition, environmental triggers, and immune mechanisms (loss of tolerance, regulatory T cell dysfunction). Furthermore, current technologies and models which are being used to deconvolve the molecular profiles and pathophysiology of AIH are also discussed. Although AIH has a low reported global burden, AIH research is critically skewed towards European ancestry populations. This leaves a significant knowledge gap in diverse ancestry groups, such as those of African ancestry, where emerging research suggests that these patients may experience a more aggressive disease. Collectively, this highlights the need for research in underrepresented global populations to develop tailored diagnostics and effective targeted treatments. Full article

Endometrial cancer (EC) is one of the most prevalent gynecological malignancies worldwide. Atypical endometrial hyperplasia (AEH) is a premalignant condition with a substantial risk of progression to EC, with the endometrioid subtype (EEC) being the most common. In this study, we investigated the escape-from-senescence concept as a model for the malignant progression from AEH to EEC by bioinformatic analysis of single-cell RNA sequencing data. Unciliated epithelial cells from AEH and EEC tissues exhibited significantly higher levels of senescence compared with those from normal endometrium. Both the proportion of senescent cells (SCs) and their senescence scores remained comparable between hyperplasia and cancer. Despite pronounced genomic instability, SCs in EEC showed no evidence of cell cycle re-entry. RNA velocity analysis revealed no transcriptional trajectories indicating a transition from senescent to non-senescent states in the EEC group. While SCs in AEH and EEC shared similar senescence-associated transcriptional profiles, they demonstrated differences in immunomodulatory activities with enhanced immunosuppressive signaling in the EEC group compared to AEH. Thus, we found no evidence supporting the occurrence of large-scale senescence escape and subsequent malignant conversion of epithelial SCs during EC development. Instead, senescence appears to represent a generalized stress response that persists throughout both premalignant and malignant stages. Full article

Porphyra-334 (PPR-334) is one of the species of mycosporine-like amino acids (MAAs), known as biological UV protection ingredients. In this study, we developed a large-scale purification process to extract PPR-334 from Saccharomyces cerevisiae and confirmed the previously identified efficacy of PPR-334, while also demonstrating its efficacy under UV-independent conditions. PPR-334 scavenged reactivity oxygen species (ROS) and increased catalase (CAT) gene expression in human epidermal keratinocyte cells (HEKa). In both HEKa and normal human dermal fibroblast cells (NHDF), PPR-334 suppressed the gene expression of matrix metalloproteinase-1 (MMP-1). NHDF treated with PPR-334 showed increased collagen expression and proliferation, while advanced glycation end-product (AGE) production was decreased. It was confirmed that the efficacy in vitro was also reproduced in human artificial skin tissue models. Above all, the antioxidant efficacy mechanism of PPR-334 through nuclear factor erythroid 2-related factor 2 (NRF2) and Caspase-9 signals was identified. It was determined that the proliferation efficacy of PPR-334 was due to factors related to the cell cycle. These results demonstrate the anti-aging efficacy of PPR-334 independent of UV irradiation, while enhancing the UV-blocking and antioxidant effects. Thus, we suggest the potential of PPR-334 as a sunscreen agent as well as a dual- or multifunctional material. Full article

Chemoresistance remains a major barrier to effective colorectal cancer (CRC) therapy, yet its metabolic underpinnings are poorly defined. Here, we integrate lipidomic profiling, enzymatic analysis, and functional perturbation approaches to elucidate the contribution of phosphatidylcholine (PC) metabolism and its biosynthetic regulator Choline Phosphotransferase 1 (CHPT1) to drug response. Comparative analysis of chemosensitive and chemoresistant CRC cell lines revealed that resistant HT29 cells exhibited significantly higher PC content and altered PC/lysophosphatidylcholine (LPC)ratios relative to sensitive counterparts. Importantly, functional perturbation confirmed causality: CHPT1 overexpression in SW620 cells was sufficient to promote PC accumulation and confer a chemoresistant phenotype. These findings identify CHPT1 as a metabolic gatekeeper of chemoresistance. Consistently, Human Protein Atlas survival analyses further support its clinical relevance, as elevated CHPT1 expression correlates with poor patient outcomes in CRC. Mechanistically, CHPT1-driven PC enrichment may sustain pro-survival signaling, while reducing lysophospholipid-mediated stress pathways. To therapeutically target this vulnerability, we investigated edelfosine (Edel), an alkyl-lysophospholipid that disrupts lipid rafts and inhibits PC biosynthesis upstream of CHPT1. Notably, edelfosine-mediated disruption of the Kennedy pathway enhances chemosensitivity in the resistant CRC model. Collectively, our study identifies CHPT1 and PC metabolism as central determinants of CRC drug response and proposes edelfosine-based metabolic reprogramming as a promising strategy to overcome resistance. Full article

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of Coronavirus disease 2019 (COVID-19), exploits angiotensin-converting enzyme 2 (ACE2) for cell entry, implicating the renin–angiotensin system (RAS) in disease pathogenesis. Hypertension (HT), a major comorbidity, is strongly influenced by genetic factors within RAS, including angiotensin ii receptor type 1 (AGTR1) and ACE2) polymorphisms. However, data on these variants in African populations remain scarce. This study investigated associations between AGTR1 and ACE2 single-nucleotide polymorphisms (SNPs), HT, and COVID-19 severity in patients at a Tshwane Academic Hospital. Methods: We genotyped AGTR1 and ACE2 SNPs in 94 PCR-confirmed COVID-19 patients using Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight (MALDI-TOF) mass spectrometry. Clinical data were extracted from hospital records. Ordinal logistic regression models assessed relationships between SNPs, HT, and COVID-19 severity. Results: The cohort (mean age: 53.9 years; HT prevalence: 54.9%) exhibited mild (54.9%), moderate (18.6%), and severe (26.5%) COVID-19. Although the rs2106809 A genotype appeared to be associated with lower odds of severe disease (OR = 0.39, 95% CI: 0.14–1.08, p = 0.04), this observation should be interpreted with caution given the limited sample size of this study. Other SNPs and clinical variables showed no significant associations. Conclusion: This exploratory study represents the first description of AGTR1 and ACE2 SNP patterns in COVID-19 patients from Tshwane. While the rs2106809 variant may indicate a possible protective trend, the evidence remains preliminary. Age correlated with severity. Larger, multi-ethnic studies are needed to confirm these findings. Full article

To address the challenge of rapidly selecting optimal numerical model products for weather forecasting in critical applications such as aviation route planning, this study proposes an enhanced object-based methodology comprising individual object scoring matching and a regional overall forecast selection scheme, building upon previous research. The method focuses on radar reflectivity forecasts within critical areas along air routes. Individual thunderstorm cells are evaluated using weighted scores for multiple parameters, including the Threat Score (TS), center-of-mass position, maximum radar reflectivity intensity, and shape forecasting accuracy. The regional overall score is then calculated by applying different weights to each convective cell within the area. After examining case studies of various convection types and bulk tests from June to September of 2024 and 2025, the results demonstrate that this method effectively selects the optimal convective forecasts from among the numerical models initiated at different times. The methodology shows promising applications in aviation weather forecasting. Different optimal selection schemes yield varying results: for large-scale convective weather, various test schemes generally align with TS score selection; for small-scale convective weather, schemes emphasizing radar reflectivity intensity show better performance; for scattered convection, schemes prioritizing center-of-mass position forecasting demonstrate superior results. These findings provide valuable insights for precision weather forecasting in both aviation and the agricultural–ecological sectors, in which accurate convective weather prediction is crucial for operational safety and resource management. Full article

Primary open angle glaucoma (POAG) is one of the leading causes of irreversible blindness and is associated with dysfunction of the trabecular meshwork (TM), a three-dimensional (3D) structure that regulates aqueous humor outflow and, consequently, intraocular pressure (IOP). IOP is the only modifiable factor for glaucoma. Outflow facility is the inverse of aqueous humor outflow resistance caused by the presence of the TM and adjacent tissues, and reflects the TM’s central role in IOP control, representing the most physiologically relevant measure of human trabecular meshwork (HTM) function. Therefore, development of ex vivo systems to study outflow facility and IOP regulation is critical for advancing glaucoma research. We present a comprehensive review of bioengineering approaches to generation of 3D HTM models using synthetic, natural, and hybrid hydrogels, micro- and nanofabricated synthetic substrates or porous scaffolds, and microfluidic devices. These 3D HTM systems have been designed to capture key features such as topography, stiffness, and fluid flow in the conventional outflow pathway. In particular, we highlight HTM models that recapitulate IOP regulation and allow measurement of outflow facility, which directly reflect pressure-dependent outflow resistance in dynamic HTM physiology and glaucoma pathophysiology. By integrating these bioengineering approaches with emerging stem cell technologies, this review offers an evidence-based landscape overview and framework for designing next-generation 3D human-relevant TM models for outflow physiological studies and IOP-modulating drug discovery. Full article

Background: The development of plasmonic photothermal therapy (PPTT) to trigger cancer cells is often hindered by uncontrolled overheating and the lack of real-time feedback. Methods: In this study, we report the synthesis of gold nanorod-embedded mesoporous silica nanoshells (AuNR@Si) as a multifunctional theranostic platform designed for controlled hyperthermia and surface-enhanced Raman spectroscopy (SERS) monitoring. Using a layer-by-layer templating strategy, AuNRs were successfully obtained within a hollow silica architecture. Results: While AuNRs alone exhibited rapid photothermal spikes reaching 64 °C, the AuNR@Si platform moderated the photothermal response, maintaining a stable therapeutic window (41–45 °C). In vitro assays using T47D breast cancer cells demonstrated a 33% reduction in viability following irradiation. Furthermore, the structural stability of the AuNR@Si platform enabled SERS monitoring of cellular damage, identifying specific biochemical fingerprints of protein denaturation, cytochrome c release and DNA fragmentation. Conclusions: These results suggest that AuNR@Si nanoshells provide a safer, regulated approach to photothermal ablation with the added benefit of molecular detection, demonstrating proof-of-concept theranostic functionality in a luminal breast cancer model. Full article

Oral squamous cell carcinoma (OSCC) cytology involves extracting a cell sample consisting of single cells or small clusters of cells from patients’ head and neck area in order to identify abnormal morphological characteristics after staining it. This method is used to screen for early cancer and the formation of metastases within the oral cavity. OSCC diagnosis partly depends on pathologists’ skills and also laboratories’ instrumentation. The use of Raman spectroscopy could support diagnoses performed using traditional methods, providing information based on the cellular biochemical environment. Technical drawbacks related to low signal-to-noise ratios of Raman spectroscopy and the need to obtain diagnostic information within a reasonable time frame have recently led to the analysis of Raman spectra using machine learning (ML) methods in order to obtain reliable information about the correct attribution of unknown cellular spectra. So, we used Raman micro-spectroscopy combined with machine learning methods to build classification models, which allow the diagnosis of different grades of OSCC in cell samples. The Raman spectra were analysed in the 980–1800 cm⁻¹ range by focusing the laser beam onto the nucleus and the cytoplasm regions of single cells from different cell lines modelling healthy (HaCaT) and cancer (Cal-27, SAS and HSC-3) cytological samples. We considered six classification algorithms (k-Nearest Neighbours, Logistic Regression, Naïve Bayes, artificial Neural Network, Random Forest and Support Vector Machine) to classify unknown Raman spectra. We report two classification tasks: a 4-level classification, which encompasses healthy cells, two different types of cancer cells, and one type of metastatic cells, and a 3-level classification, which includes healthy cells, non-metastatic cancer cells, and metastatic cancer cells. Our findings show that both Neural Network and Support Vector Machine algorithms applied to Raman spectra measured in the cytoplasm region can achieve sensitivity, precision and F1-score values larger than 90% in the 3-groups classifications, whereas Support Vector Machine performs better in the 4-groups classification with respect to a Neural Network. These results contribute to increasing confidence in the clinical translation of ML-assisted Raman spectroscopy as a tool to support conventional cytological techniques. Full article

Alzheimer’s disease (AD) is a catastrophic neurodegenerative disorder marked by progressive decline of cognitive function, memory loss, and neuronal death. Its pathology is characterized by the formation of extracellular amyloid-beta (Aβ) plaques and intracellular neurofibrillary tangles from tau hyperphosphorylation. Despite extensive research, current treatments are limited to symptomatic relief and are associated with significant side effects. This accentuates the critical need for alternative therapeutic strategies with potent neuroprotective effects and minimal toxicity. This study investigates the neuroprotective potential of glycyrrhizic acid, as the precise molecular mechanisms by which it might improve AD pathology remain poorly understood. Using an Aβ₄₂-induced IMR-32 cell model of AD, our research revealed that Aβ₄₂ treatment caused significant protein alterations associated with AD pathology, mitochondrial dysfunction, cell cycle re-entry, and synaptic activity. Co-treatment with glycyrrhizic acid not only restored these protein levels, but also mitigated the hyperactivation of several key signaling pathways and rescued neurons from apoptosis. These findings suggest that glycyrrhizic acid exerts neuroprotective effects by preventing mitochondrial dysfunction and apoptosis via modulation of critical signaling pathways. This study provides strong evidence for glycyrrhizic acid’s neuroprotective properties in AD, paving the way for further research into its potential as a promising therapeutic agent for Alzheimer’s disease. Full article