Abstract: Anti-allergic and anti-inflammatory activities of the extracts of rosebuds newly-crossbred in Korea were investigated in vitro and in vivo. Twenty-four candidate rosebuds were extracted with 80% ethanol, and analyzed for polyphenols, flavonoids, tannins, proanthocyanidins, and pyrogallol (1,2,3-benzenetriol). The extracts’ in vitro anti-allergic and anti-inflammatory activities were analyzed through inhibitory effects on the β-hexosaminidase release from Compound 48/80-stimulated RBL-2H3 cells and nitric oxide production from lipopolysacchrade-activated RAW 264.7 macrophages, respectively. The in vivo activity was assessed via protection against lethality and itching (scratching) symptoms in mice challenged with Compound 48/80. Among candidates, Lover Shy, Pretty Velvet, Ice Wing, Red Perfume, Onnuri, Jaemina Red, and Hanggina were found to possess high concentrations of antioxidative components. By comparison, Pretty Velvet, Red Perfume, Jaemina Red, Hanggina, Onnuri, and Ice Wing were highly effective in anti-allergic and anti-inflammatory activities in vitro, in parallel with their concentrations of pyrogallol. Their anti-allergic effects were confirmed in mice: The 6 extracts protected against Compound 48/80-induced mortality and scratching behaviors in a dose-dependent manner. The allergen-induced increases in serum IgE and histamine as well as inflammatory cytokines, tumor-necrosis factor-α and interleukin-1β, were remarkably attenuated following treatment with the rosebud extracts. Therefore, it is suggested that the extracts and active ingredients from cross-bred Korean rosebuds exert anti-allergic and anti-inflammatory activities through their high levels of antioxidants and pyrogallol, and that could be promising candidates to overcome allergic responses such as atopic dermatitis.

Abstract: .Severe early childhood caries (S ECC) in 3–4 year olds is a preventable disease with consequences that extend beyond teeth to sleep, nutrition, development, family stability, and long term health. In a high income country such as the United States, the central clinical and ethical challenge is not whether minimally invasive dentistry (MID)—including silver diamine fluoride (SDF)—can be used, but whether it is used with appropriate precision and within a system capable of delivering timely definitive care. This editorial argues for a Preservation to Precision movement that transcends “MID” as a narrow technical identity and instead prioritizes child well being as the endpoint: freedom from pain and infection, durable function, and acceptable psychosocial outcomes. Published evidence supports SDF/MID as an evi-dence based tool for lesion arrest and as an interim strategy that can alter care pathways and, in some con-texts, delay escalation to sedation/general anesthesia by weeks to months; however, real world data also show that many SDF treated primary teeth receive subsequent treatment within two years, underscoring that “buying time” is not synonymous with securing long term outcomes to exfoliation. The editorial cautions against redefining temporization as a universal protocol and calls for rights aligned, risk based precision: tooth and child specific planning, realistic appraisal of follow up feasibility, and system reforms that ensure timely access to definitive restorative care when indicated.

Abstract: Above ground storage tanks are used to store various fluids and chemicals for many industrial purposes. According to API standard 653, the structural integrity of these tanks must be regularly assessed. The U.S. EPA requires each operator to have a Spill Prevention, Control and Countermeasure Plan (SPCC) for aboveground storage con-tainers. The accepted practice for inspection of these tanks, particularly the tank bot-toms, involves removing the tank from service, emptying the tank, and inspecting di-rectly from the interior. The required inspection operations are hazardous due to the chemicals themselves as well as the requirement to operate within confined spaces. An inspection from outside the tank would have significant cost and time benefits and would provide a large reduction in the risks faced by the inspection personnel. Guided wave (GW) testing is one promising candidate for screening of storage tanks walls and bottoms from the tank exterior due to the ability of GWs to propagate long distances from a fixed probe location. The lowest order transverse-motion guided wave modes (e.g., torsional vibrations in pipes) are a good choice for long-range inspection because this mode is not dispersive; therefore, the wave packets do not spread out in time. A common weakness of guided wave inspection is the complexity of report generation in the presence of multiple geometry features in the structure, such as welds, welded plate corners, attachments and so on. In some cases, these features cause generation of non-relevant indications due to mode conversion. Common non-relevant indications are described in this paper. Another significant challenge in applying GW testing is development of probes with high enough signal amplitudes and a relatively small footprint to allow them to be mounted on relatively short tank bottom extensions. In this paper a new generation of magnetostrictive transducers will be presented. The transducers are based on a reversed Wiedemann effect and can generate shear hori-zontal mode guided waves over a wide frequency range (20 – 150 kHz) and with SNR in excess of 50 dB. The recently developed SwRI MST 8x8 probe contains an array of 8 pairs of individual magnetostrictive transducers (MsTs). The data acquisition hard-ware allows acquisition using Full Matrix Capture (FMC) and analysis software re-porting of anomalies based on Total Focusing Method (TFM) image reconstruction. This novel inspection package allows generation of reports containing high accuracy corrosion mapping information. Case studies of this technology on actual storage tanks walls and bottoms will be presented together with validation of processing methods on mockups with known anomalies and geometry features.

Abstract: We have collected geomagnetic observations from low and equatorial latitudes during the 19th century to infer the intensity of geomagnetic storms during the years 1841-1877. Daily mean H observations during the above years in Trivandrum, Singapore and Madras is first scaled to Bombay observations and subsequently to the Dst index to infer the intensity of storms in modern units . These results are also compared with the intensity of these storms derived from mid latitudes. Extreme space weather events (ESW) are identified from the list of intense storms inferred during this period. The annual number of ESW events shows the characteristic double peak structure during the sunspot cycles 9-11. Space weather conditions during the sunspot cycle 11 (1867-1877) is found to be exceptional. A discussion on the true intensity of geomagnetic storms is also included.

Abstract: This article presents a computational model for transmission and generation expansion planning that incorporates the effects of a new booster inter-area Virtual Transmission lines model, achieved through investments in energy storage systems within the transmission network areas. This approach enables the evaluation of potential reductions and deferrals in transmission line investments, including those involving inter-area trunk lines. Furthermore, the model captures flexibility from TSO-DSO interconnections to examine their influence on overall system expansion choices. A review of state-of-the-art flexibility indicators supports the selection of a metric that effectively quantifies resources for mitigating short-term operational variabilities; this metric is integrated into the model's unit commitment module, incorporating generator ramping and flexibility constraints. Flexibility is supplied to the AC transmission network via connected distribution systems at transmission nodes, with required flexibility levels derived from expansion planning performed by the associated DSOs. The model's core objective is to minimize total system costs, encompassing operations, investments in transmission and generation, and flexibility provisions. To handle uncertainties in demand and variable renewable energy generation, a data-driven distributionally robust optimization (DDDRO) method is employed. The framework utilizes a two-level architecture based on the column-and-constraint generation algorithm and duality-free decomposition, augmented by a third level to embed unit commitment and generator ramping constraints. Validation through case studies on the IEEE RTS-GMLC network illustrates the model's efficacy, highlighting the benefits of the proposed contributions in achieving cost savings, enhanced transmission and generation efficiency, and flexibility metrics.

Abstract:

For over 50 years, Everett Rogers’ Diffusion of Innovation (DOI) theory has been a cornerstone of understanding how new ideas and technologies spread through social systems. The period of 2000-2025 has ushered in an unprecedented revolution in communication brought about by the explosion of digital media, the emergence of social networking platforms, and the proliferation of mobile connectivity, which has fundamentally altered our human communications, social systems, and behaviors. This critical literature review investigates how DOI theory has been applied, adapted, and remains relevant in the digital media age. This paper utilizes a systematic review method to collect academic literature published in this time frame while synthesizing how the basic constructs of DOI theory—such as adopter categories, innovation attributes, communication channels, and the S-shaped adoption curve—have been developed, amended, or referenced. While DOI theory's tenets are surprisingly resilient, the digital media age has shifted dynamics and introduced substantial theoretical modifications. Digital platforms have collapsed distinctions between mass and interpersonal communication, diffusion processes have rapidly increased adoption, and network effects have increased social influence's role in adoption decisions. The rise of the digital influence altered what it means to be an opinion leader, and the algorithmic curation of content can even represent a robust non-human actor in generating diffusion. This review also identifies some critical limitations of the classic DOI model relating to the digital divide, complexities of information overload, and adoption dynamics associated with purely digital innovations, such as cryptocurrencies and AI/predictive services. Additionally, this review revealed some key gaps in the respective literature establishing the relationship between algorithmic influence and human social networks, and the long-term societal implications of algorithmically driven diffusion. This review concludes that although DOI theory is useful, it needs to be combined with network theory, technology acceptance models, and critical media studies to better grasp innovation diffusion today.

Abstract: Accurate segmentation of breast cancer regions in histopathological images is critical for advancing computer-aided diagnostic systems, yet challenges persist due to heterogeneous tissue structures, staining variations, and the need to capture features across multiple scales. This study introduces MSB-UNet, a novel Multi-Scale Bifurcated U-Net architecture designed to address these challenges through a dual-pathway encoder-decoder framework that processes images at multiple resolutions simultaneously. By integrating a bifurcated encoder with a Feature Fusion Module, MSB-UNet effectively captures fine-grained cellular details and broader tissue-level patterns. Evaluated on a publicly available breast cancer histopathology dataset, MSB-UNet achieves a Dice Similarity Coefficient (DSC) of 91.3% and a mean Intersection over Union (mIoU) of 84.4%, outperforming state-of-the-art segmentation models. The architecture demonstrates superior boundary precision and reduced false positives, particularly in complex cases involving infiltrative growth patterns and intra-tumoral heterogeneity. These results highlight MSB-UNet’s potential to enhance automated diagnostic tools for breast cancer histopathology, paving the way for improved clinical decision-making and future extensions to multi-class segmentation tasks.

Abstract: Background: Clinical management of neonatal indirect hyperbilirubinemia relies on guideline-based thresholds for phototherapy and exchange transfusion. In 2022, the American Academy of Pediatrics (AAP) updated its guideline, raising treatment thresholds for neonates born at ≥35 weeks of gestation. In Türkiye, clinical practice is guided by the Turkish Neonatology Society (TNS) guideline, which applies lower treatment thresholds. Methods: This single-center, retrospective cross-sectional study included neonates born at ≥35 weeks of gestation who were admitted to a neonatal intensive care unit solely due to indirect hyperbilirubinemia. Phototherapy and exchange transfusion thresholds were calculated according to both the TNS guideline and the 2022 AAP guideline. Guideline compliance and admission indications were compared. Statistical analyses were performed using appropriate non-parametric tests. Results: A total of 344 neonates were included in the analysis. Mean phototherapy and exchange transfusion thresholds were significantly higher according to the AAP 2022 guideline compared with the TNS guideline (p < 0.001 for both). While 89.2% of admissions were compliant with the TNS guideline, only 36.6% met the admission criteria based on the AAP 2022 guideline. Approximately 64.4% of hospitalized neonates did not have an admission indication according to the AAP 2022 recommendations. Conclusions: Substantial differences exist between national and international guidelines for the management of neonatal indirect hyperbilirubinemia. These differences significantly influence treatment thresholds and hospitalization practices. Real-life comparative data may contribute to future evaluations of guideline-based management strategies.

Abstract: This study constructs a global timber trade network (2004-2023) to model underload cascading failures, assessing node-level disruptiveness and resilience. The network has grown structurally integrated, with density rising and path length shortening. Export-oriented economies (e.g., Canada, Vietnam) prove more susceptible to cascading failures than import-oriented ones (e.g., China, Japan), confirming upstream-to-downstream failure propagation. Node disruptiveness is heterogeneous: major exporters (Canada, Germany) cause the largest efficiency losses, while intermediaries (South Africa) impair connectivity. Out-strength and betweenness centrality are key determinants of disruptiveness. Resilience in 2023 varies widely; China's diversified sourcing enhances its resilience, whereas the U.S., Japan, and South Korea face higher vulnerability due to supply concentration. Overall, declining resilience among major importers underscores growing systemic risks. Although strategic diversification improves individual positions, large-scale disruptions remain a considerable threat, highlighting the imperative for optimized sourcing and robust contingency planning to stabilize global timber flows.

Abstract: This article presents PrevOccupAI-HAR, a new publicly available dataset designed to advance smartphone-based human activity recognition (HAR) in office environments. PrevOccupAI-HAR comprises two sub-datasets: (1) a model development dataset collected under controlled conditions, featuring 20 subjects performing nine sub-activities associated to three main activity classes (sitting, standing, and walking), and (2) a real-world dataset captured in an unconstrained office setting captured from 13 subjects carrying out their daily office work for six hours continuously. Three machine learning models, namely k-nearest neighbors (KNN), support vector machine (SVM), and random forest, were trained on the model development dataset to classify the three main classes independently of sub-activity variation. The models achieved accuracies of 90.94 %, 92.33 %, and 93.02 % for the KNN, SVM, and Random Forest, respectively, on the development dataset. When deployed on the real-world dataset, the models attained mean accuracies of 69.32 %, 79.43 %, and 77.81 %, reflecting performance degradations between 21.62 % and 12.90 %. Analysis of sequential predictions revealed frequent short-duration misclassifications, predominantly between sitting and standing, resulting in unstable model outputs. The findings highlight key challenges in transitioning HAR models from controlled to real-world contexts and point to future research directions involving temporal deep learning architectures or post-processing methods to enhance prediction consistency.

Abstract:

Background/Objectives: It is of upmost importance to study environmental bacteria, as these microorganisms remain poorly characterized regarding their diversity, antimicrobial resistance, and impact on the global ecosystem. This knowledge gap is particularly pronounced for marine bacteria. In this study, we aimed to isolate marine bacteria from different sources and to gain insights into the environmental bacterial resistome, an aspect that remains largely neglected. Methods: Bacteria were isolated from several marine sources using two different culture media, and their identification was based on 16S rRNA gene analysis. Whole-genome sequencing was performed for selected isolates belonging to novel taxa. Antimicrobial susceptibility to seven antibiotics was evaluated using the disk diffusion method. Results: A total of 171 bacterial isolates belonging to the phyla Pseudomonadota, Bacteroidota, Planctomycetota, Actinomycetota, and Bacillota were obtained from diverse marine samples. The most abundant group belonged to the class Alphaproteobacteria. Thirty isolates represented novel taxa, comprising 16 new species and one new genus. Despite the challenges associated with determining antibiotic resistance profiles in environmental bacteria, only one isolate (1.8%) was pan-susceptible, whereas 54 (98.2%) showed resistance to at least one of the tested antibiotics. Moreover, 33 isolates exhibited a multidrug-resistant phenotype. Genome analysis of four novel taxa revealed the presence of an incomplete AdeFGH efflux pump. Conclusions: This study highlights the high bacterial diversity in marine environments, the striking prevalence of antibiotic resistance, and the major methodological challenges in studying environmental bacteria. Importantly, it emphasizes the relevance of culturomics-based approaches for uncovering hidden microbial diversity and characterizing environmental resistomes.

Abstract: Background: Although swallowing-related muscle function has been implicated in sarcopenia, the association between suprahyoid muscle strength, which primarily contributes to laryngeal elevation during swallowing, and sarcopenia has not been thoroughly examined. The aim of this study was to investigate this association in community-dwelling older adults. Methods: This cross-sectional study included 390 community-dwelling adults aged ≥65 years. Sarcopenia was defined as the concurrent presence of low handgrip strength and low appendicular skeletal muscle mass. Suprahyoid muscle strength was assessed by the maximum force generated during a chin-tuck maneuver using a validated and reliable device. Tongue pressure and oral diadochokinesis were measured as indicators of swallowing-related muscle function. Potential confounders included body mass index, comorbidities, number of med-ications, functional status, timed up-and-go test and trail-making test times. Results: In logistic regression analyses adjusted for potential confounders, among swallowing-related muscle functions, only suprahyoid muscle strength was significantly associated with sarcopenia; greater strength correlated inversely with sarcopenia (odds ratio = 0.70, p < 0.05). Receiver operating characteristic curve analysis demonstrated acceptable discriminative ability of suprahyoid muscle strength for identifying sarcopenia (area under the curve = 0.82, 95% confidence interval: 0.73–0.91), which was significantly higher than that for tongue pressure (AUC = 0.62, 95% CI: 0.50–0.75; p < 0.01). Conclusions: Among swallowing-related muscle functions, reduced suprahyoid muscle strength may represent an important risk factor for sarcopenia in older adults. Future studies should investigate targeted assessments and interventions focused on improving suprahyoid muscle strength as a potential strategy for sarcopenia prevention.

Abstract: Finite element analysis (FEA) remains the gold standard for simulating piezoelectric microactuators because it resolves coupled electromechanical fields with high fidelity. However, transient FEA becomes prohibitively expensive when thousands of actuators must be simulated. This work presents a data-driven surrogate modeling framework for tileable, PZT-5H microactuators enabling fast, dynamic, and parallel predictions of actuator displacement over multi-step horizons from short displacement history windows, augmented with the corresponding prescribed voltage and traction samples over that same history window. High-fidelity COMSOL simulations are used to generate a dataset aiming to encompass the full operational envelope of our actuator under stochastically sampled and procedurally generated input waveform families. From these families, we construct a supervised learning dataset of time histories, displacement, and applied loads, then we train a recurrent sequence-to-sequence neural network that predicts a multi-step open-loop displacement rollout conditioned on the most recent electromechanical history. The resulting model can be leveraged to perform batched inference for millions of actuators on GPU hardware, opening up a wide range of new applications such as reinforcement learning via digital twins, scalable design for piezoelectric artificial-muscle systems, and accelerated optimization.

Abstract: Study design: A series of 26 patients, submitted to decompressive craniectomy for su-pratentorial cerebral ischemia was retrospectively analyzed. Objectives: The aim of this study is to highlight the experience with this surgical tech-nique in our Institution and to analyze comparatively the preoperative and postoperative clinical and radiological data, as well as the prognostic factors verifying the agreement between our findings and the relevant literature data. Methods: From January 2018 to January 2023, we recruited 26 patients that underwent decompressive craniectomy for supratentorial cerebral ischemia. Demographic, medical history, clinical, laboratory, radiological and surgical data were collected. Statistical analysis was also performed to determine if any variable had a significant impact pre-viously and post-operatively or if they were predictive of favorable outcome. Results: The average age of the patients was 56.55 y, range between 26-80 y. Patients under 60 y were 51.8% and 59,25% of the whole sample were male. The outcome score calculated with the Modified Ranking Scale after about 1 year was < =4 in 11 patient; it distributed as follows: 2 pts with MRS 2, 5 pts with MRS 3 and 4 pts with MRS 4. The remaining were dead or in a vegetative state. Univariate statistical analysis was focused on neuroradiological parameters, studied both in pre- and post-operative CT scans. The variables that proved to be statistically significant were the presence or absence of visible cortical sulci, basal cisterns compression (cisterna ambiens in particular), quadrigeminal and sylvian cisterns. Of these parameters, the only one that maintained statistical sig-nificance even in the multivariate analysis was the presence of visible cisterna ambiens in post-operative radiological studies proving to be associated with a favorable outcome. Conclusions: Our study confirmed that decompressive craniectomy in cerebral ischemic stroke is an effective life-saving treatment in a subgroup of patients with intracranial hypertension. Standardization of the surgical indication remains a challenge and our analysis could suggest potentially useful work patterns in daily clinical practice, eventough our expe-rience had the important limitation of measuring only physical disability; further studies considering psychosocial, financial and caregiving aspects are needed. Moreover, sur-gical management remains in our opinion a tailored choice based on the experience of the surgeon and on the expectations of the patient and family.

Abstract: The chili pepper (Capsicum annuum) is among the most widely consumed vegetables worldwide, valued for its sensory and nutritional properties. Still, it is highly vulnera-ble to deterioration due to its elevated moisture content. Effective preservation strate-gies, such as the addition of salt combined with drying, are therefore crucial to main-taining quality and extending shelf life. This study employed a modified Reaction En-gineering Approach (REA) to model the drying kinetics and temperature behavior of chili paste under continuous and intermittent conductive hydro-drying conditions. Thirty experiments were conducted, considering various salt concentrations (0, 7.5 y 15 g salt/100 g paste) , water temperatures in the hydro-dryer, and heating intermit-tency through on/off cycles. The modified REA model accurately predicted both mois-ture and temperature profiles, with determination coefficients of 0.9463 and 0.8820, respectively. In addition to direct validation with the complete dataset, cross-validation between cayenne and jalapeño varieties demonstrated the ability of the model to generalize across different formulations and structural characteristics. These results confirm the robustness of the proposed framework and its suitability as a predictive tool for heterogeneous food matrices. Overall, the model provides a reliable platform for analyzing, designing, optimizing, and controlling hydro-drying processes in semi-solid foods, supporting the development of more efficient and sustainable preservation strategies.

Abstract: Automated plant leaf disease detection using deep learning has achieved high accuracy on benchmark datasets; however, its performance often degrades when applied to real-world agricultural images affected by background clutter, illumination variability, and partial occlusions. These factors limit the reliability of conventional convolutional neural network (CNN)–based models trained under controlled conditions. To address this limitation, this paper proposes a Region-Aware and Enhanced Attention Convolutional Neural Network (REA-CNN) for robust classification of plant leaf diseases. The proposed framework integrates explicit region-aware pre-processing for background suppression with an attention-enhanced CNN backbone, enabling the model to focus on disease-relevant visual patterns. Unlike conventional two-stage CNN–SVM pipelines, REA-CNN is trained in a fully end-to-end manner, allowing joint optimization of feature extraction, attention refinement, and classification. Experimental results show that the proposed approach achieves higher classification accuracy and improved generalization on heterogeneous and real-world images compared to existing methods. These results demonstrate the effectiveness of combining region awareness and attention-guided learning for developing practical and deployable decision-support systems in precision agriculture.

Abstract: Architecture viewpoints play a central role as an abstraction mechanism for structuring, communicating, and reviewing software architectures by separating concerns and addressing diverse stakeholder needs [1] [8] [9] [11]. However, in both industrial practice and academic research, viewpoint definitions are often fragmented, inconsistently expressed, or narrowly scoped, which limits comparability, reuse, and long-term architectural evolution [10] [14] [15]. Existing architecture frameworks and standards, including TOGAF, C4, and ISO/IEC/IEEE 42010, either emphasize processes and notations or deliberately avoid prescribing concrete viewpoint sets [1] [4] [33]. While this flexibility supports broad applicability, it also leaves practitioners without a reusable reference taxonomy that systematically consolidates architectural concerns encountered in modern software-intensive systems [8] [10] [11]. This paper introduces PACT (Practical Architecture Viewpoint Taxonomy), a reference-level taxonomy of architecture viewpoints that consolidates recurring architectural concerns observed across standards, established viewpoint models, and industrial practice. PACT defines 52 viewpoints spanning business, application, integration, data, security, infrastructure, governance, and operations concerns. Each viewpoint is specified using a unified definition template that captures its primary concern, key questions, stakeholders, abstraction focus, and scope, enabling systematic comparison, selection, and reuse [1] [11]. PACT is explicitly aligned with the conceptual model of ISO/IEC/IEEE 42010, while remaining method-, notation-, and tool-independent, enabling reuse across heterogeneous architectural practices without imposing process or documentation lock-in [1]. It is intended as a reference taxonomy rather than a prescriptive framework, supporting enterprise architecture governance and system design practices [6] [7], as well as academic analysis of architectural knowledge and viewpoints [15] [18]. A case-based evaluation and industrial illustrations illustrate how PACT supports more systematic concern coverage, improved clarity, and structured architecture reviews across heterogeneous systems. The taxonomy is designed to be extensible, providing a stable reference for future research and evolving architectural practices [10] [32].

Abstract: Forensic human identification relies on length-based differences in short tandem repeats (STRs) across autosomal and Y chromosomes, which require separate reactions and provide limited resolution. While next-generation sequencing offers greater discriminatory power, most platforms are expensive and restricted to traditional lab settings. Nanopore sequencing has the potential to change this with the real-time, portable MinION sequencer. However, forensic-specific tools that generate STR profiles compatible with established length-based databases are lacking. To address this, we developed STRspy2.0, which simultaneously profiles autosomal and Y-STRs using nanopore reads. STRspy2.0 produced accurate profiles for 54 multiplexed control libraries and 41 mock casework samples (blood, swab, bone), achieving overall F1-scores of 100% and 99.75%, respectively. It maintains compatibility with existing forensic databases while providing higher resolution than traditional profiles. Our updated method and comprehensive database, along with the MinION's small size and price, make sequence-based STR profiling more accessible to forensic laboratories and resource-limited settings.

Abstract: Background: Medicinal plants used in traditional Mexican medicine represent a valu-able source of bioactive compounds with potential anticancer activity. Beyond cyto-toxic potency, selectivity toward cancer cells over normal cells is a critical toxicologi-cal parameter for identifying safer therapeutic candidates.. This study aimed to evalu-ate the selective cytotoxic and antiproliferative effects of extracts from four Mexican medicinal plants across human cancerous and non-cancerous cell lines. Methods: Hexane, acetone, and methanolic extracts from Semialarium mexicanum, Eryngium heterophyllum, Piper auritum, and Cochlospermum vitifolium were evaluated in a panel of human cancer cell lines and non-tumoral models, including primary human uterine fibroblasts (HUF). Cytotoxicity was assessed after 48 h of treatment using in-creasing extract concentrations, and selectivity indices were calculated. Cell cycle dis-tribution and nuclear morphology analyses were performed to explore antiprolifera-tive effects. Additionally, GC–MS-based chemical profiling was conducted on selected extracts to obtain a tentative characterization of major bioactive constituents. Results: The extracts exhibited differential cytotoxic profiles depending on plant spe-cies and solvent polarity. Semialarium mexicanum, particularly its hexane extract, showed the highest cytotoxic potency and selectivity toward HeLa cervical cancer cells, achieving selectivity indices higher than those observed for paclitaxel when compared with HUF cells. Hexane extracts of Semialarium mexicanum and Eryngium heterophyllum, were generally more active than polar extracts, whereas Piper auritum displayed limited cytotoxicity and Cochlospermum vitifolium showed moderate, sol-vent-dependent effects. Cell cycle perturbations and nuclear alterations supported an antiproliferative response. Chemical profiling suggested the presence of lipophilic triterpenoid-related compounds in non-polar extracts and phenolic constituents in polar fractions. Conclusions: These findings provide in vitro evidence of selective anticancer activity of Mexican medicinal plant extracts and establish a basis for future mechanistic stud-ies medicinal plant extracts and lay the groundwork for future mechanistic investigations.

Abstract: Background: Accurate and consistent measurement of physical activity (PA) is essential for evaluating interventions, informing clinical and public health decision-making, and enabling comparisons across populations. Wearable device–based measures are increasingly used to quantify PA, but the extent to which populations at risk of health inequity, as defined by established equity frameworks, are represented in wearable-based PA studies, and whether measurement protocols are appropriate and comparable across these groups, remains insufficiently characterised. Aim: To synthesise evidence on the use of wearable devices for measuring PA in populations at risk of health inequity, as defined by the PROGRESS-Plus and CORE20PLUS5 frameworks, and to identify methodological features relevant to equity in PA measurement. Methods: A scoping review was conducted in accordance with PRISMA-ScR guidelines. PubMed, Scopus, Web of Science, and grey literature were searched for peer-reviewed randomised controlled trials published between January 2020 and October 2025. Eligible studies quantitatively measured PA using pedometers, accelerometers, or smartwatches in populations at risk of health inequity. Data were extracted on study design, population characteristics, device type and placement, monitoring protocols, and equity-related considerations. Results: Of 1,027 records screened, 13 studies met inclusion criteria. Wrist-worn pedometers and hip-worn accelerometers were most common. Adaptations were minimal and largely limited to language translation. Several high-risk equity groups according to the frameworks used including LGBTQ+, people experiencing homelessness, those with learning difficulties, substance misuse, and justice system involvement were absent. Conclusions: This review demonstrates that wearable-based PA measurement has been applied to only a narrow subset of populations at risk of health inequity, with notable gaps across several key PROGRESS-Plus and CORE20PLUS5 groups. Methodological adaptations to support equitable measurement were uncommon and largely superficial, raising concerns about the appropriateness, acceptability, and comparability of PA data generated in these contexts. Addressing these methodological and reporting deficiencies is essential to strengthen the evidence base and prevent the widening of inequities in PA surveillance and intervention evaluation.