Genetically engineered crops producing insecticidal Bacillus thuringiensis proteins are useful for managing some key insect pests, including Helicoverpa zea (corn earworm or bollworm). In the United States, widespread practical resistance to crystalline (Cry) proteins and early warning of resistance to the vegetative insecticidal protein Vip3Aa have been reported for H. zea. To test the hypothesis that resistance to Cry1Ac or Vip3Aa causes fitness costs affecting flight and related traits in H. zea, we compared lab-selected Cry1Ac-resistant and Vip3Aa-resistant strains with their susceptible parental strains, and with an unrelated standard susceptible strain. We used flight mills to analyze flight (flight propensity, total distance, distance per flight, duration, number of flights, and speed) and related traits (post-flight survival, body mass, forewing area, wing loading, flight muscle mass, and abdominal lipid mass). The results show that H. zea resistance to Cry1Ac or Vip3Aa generally did not cause fitness costs affecting flight and related traits. One notable exception is that male post-flight survival was lower in a Vip3Aa-resistant strain than its Vip3Aa-susceptible parent strain. Together with the limited fitness costs previously reported in Cry-resistant H. zea, the lack of fitness costs in Cry1Ac-resistant H. zea affecting flight and related traits reported here aligns with the rapid evolution of practical resistance of H. zea to Cry proteins. If the reduced post-flight survival of Vip3Aa-resistant males in the laboratory also occurs in the field, it could help to delay the evolution of resistance and the geographic spread of alleles conferring resistance to Vip3Aa. © 2026 Society of Chemical Industry. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
Patients with thoracic aortic disease (TAD) frequently seek advice on the safety of commercial air travel. Despite the clinical relevance of this question, robust evidence is virtually absent, and current recommendations rely largely on expert opinion. This Viewpoint discusses the physiological effects of flights, reviews the limited available evidence, and proposes a pragmatic, risk-based approach for clinicians counselling patients with TAD.
Detecting Lévy flights of cells has been a challenging problem in experiments. The challenge lies in accessing data in spatiotemporal scales across orders of magnitude, which is necessary for reliably extracting a power-law scaling. Differential dynamic microscopy has been shown to be a powerful method that allows one to acquire statistics of cell motion across scales, which is a potentially versatile method for detecting Lévy walks in biological systems. In this article, we extend the differential dynamic microscopy method to self-propelled Lévy particles, whose run-time distribution has an algebraic tail. We validate our protocol using synthetic imaging data and show that a reliable detection of active Lévy particles requires accessing length scales of an order of magnitude larger than its persistence length, if the variability in particle speed is moderate. Applying the protocol to experimental data of E. coli and E. gracilis, we find that E. coli does not exhibit a signature of Lévy walks, while E. gracilis is better described as active Lévy particles.
Variable speed generalized Lévy walks (VGLWs) are a class of spatiotemporally coupled stochastic processes that unify a broad range of previously studied models within a single parametrized framework. Their dynamics consist of discrete random steps, or flights, during which the walker's speed varies deterministically with both the elapsed time and the total duration of the flight. We investigate the anomalous diffusive behavior of VGLWs and analyze it through decomposition into the three fundamental constitutive effects that capture violations of the Central Limit Theorem (CLT): the Joseph effect, reflecting long-range increment correlations, the Noah effect, arising from heavy-tailed step-size distributions with infinite variance, and the Moses effect, associated with statistical aging and nonstationarity. Our results show that anomalous diffusion in VGLWs is typically generated by a nontrivial combination of all three effects, rather than being attributable to a single mechanism. Strikingly, we find that within the VGLW framework the Noah exponent L, which quantifies the strength of the Noah effect, is unbounded from above, revealing a richer and more extreme landscape of anomalous diffusion than in previously studied Lévy-walk-type models.
Facade thermal defect diagnosis is a critical prerequisite for energy-efficiency retrofitting of old residential buildings. However, conventional infrared thermography is easily affected by environmental conditions and occupant behavior, making it difficult to distinguish persistent thermal defects from transient anomalies. To address this challenge, this study proposes an integrated diagnostic framework for old residential buildings in Wuhan, China, combining unmanned aerial vehicle (UAV) infrared thermography, multi-temporal data acquisition, 3D flight-path planning, thermal anomaly recognition, facade spatial mapping, and temporal screening. Field experiments were conducted to determine key acquisition parameters, including sensor preheating time, imaging distance, and acquisition timing. Thermal anomalies were identified through image-processing techniques and mapped onto facade representations derived from 3D models. Repeated observations across different times and days were then used to evaluate anomaly recurrence and spatial stability. The results show that preheating the sensor for at least 10 min, maintaining a UAV-to-facade distance of 8-10 m, and acquiring data around 17:00 provide more reliable thermal images. Multi-temporal screening effectively reduces false positives caused by temporary disturbances, while persistent anomalies associated with window-wall joints, floor slabs, wall surfaces, and moisture-related areas can be identified more robustly. The proposed framework provides a practical workflow for facade thermal defect diagnosis and retrofit-oriented decision support.
Bats (order Chiroptera) are among the most diverse and ecologically vital mammals, defined by powered flight, remarkable echolocation, and exceptional physiological adaptations [...].
Cancer risk estimation remains one of the main unresolved challenges in human spaceflight beyond low Earth orbit, where astronauts are exposed to galactic cosmic rays, solar particle events, and high-linear energy transfer (high-LET) secondary radiation. This narrative review summarizes the principal quantitative models used to estimate radiation-induced cancer risk in astronauts, including particle fluence-based cross-sections, mixture models, risk of exposure-induced death (REID)-based operational frameworks, uncertainty distribution approaches, and ensemble models. Early studies estimated 1-year excess cancer mortality at solar minimum as 1.3% in women and 1.1% in men under 10 g/cm2 aluminum shielding, whereas later models projected non-leukemia lifetime cancer incidence after 1 Sv dose equivalent/effective dose between 2.20% and 2.98%, depending on sex and age. Earlier REID-based models suggested that the historical 3% REID threshold could be exceeded after approximately 18 months in women and 24 months in men under unfavorable solar conditions, whereas the current NASA radiation standard uses a universal career-effective dose limit of 600 mSv, applied regardless of sex or age. More recent revisions of the NASA Space Cancer Risk model and non-targeted effect scenarios suggest that exploration mission risks may be higher than previously estimated, while uncertainty remains substantial, especially for high-LET radiobiology, mixed-field exposure, and the transfer of terrestrial epidemiological data to the spaceflight setting. Future progress may also involve exploring quantitative imaging biomarkers and tomographic assessments as complementary tools for longitudinal monitoring and early detection of radiation-related tissue changes, although these approaches are not yet validated as components of operational astronaut cancer risk models.
This paper proposes a Multi-Strategy Improved Connected Banking System Optimizer, named MICBSO, for numerical optimization and three-dimensional UAV path planning. MICBSO enhances the original CBSO through three coordinated strategies. First, a chaos-opposition learning initialization strategy is introduced to improve initial population quality and search coverage. Second, a Gaussian perturbation-based multi-elite guidance mechanism is designed to reduce dependence on a single best solution and strengthen the balance between exploration and exploitation. Third, a hybrid boundary control strategy combining reflective correction and random reinitialization is developed to improve solution feasibility and maintain population diversity. The proposed algorithm is evaluated on the CEC2017 benchmark suite and compared with 11 representative algorithms. Experimental results show that MICBSO achieves competitive convergence accuracy, stability, and robustness across different dimensional settings. In addition, MICBSO is applied to three-dimensional UAV path planning in four complex terrain scenarios. The results demonstrate that MICBSO can generate feasible and safe flight paths with lower comprehensive cost. Overall, the proposed method provides an effective optimization framework for both benchmark optimization and constrained UAV path planning tasks.
MRSA is an important antimicrobial-resistant pathogen reported in a wide range of animal species; however, information regarding its occurrence in captive large felids remains limited. This report describes the detection and characterization of MRSA associated with a dental abscess in a captive jaguar (Panthera onca) from a zoological collection in Romania. A 10-year-old male jaguar presented with clinical signs suggestive of a localized oral infection. Samples collected from the dental lesion, nasal mucosa, external ear canal, and skin surface were subjected to bacteriological examination. Bacterial isolates were identified using conventional microbiological methods and Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS). Antimicrobial susceptibility testing was performed using the VITEK® 2 system, while molecular confirmation was achieved by PCR targeting the nuc, mecA, and mecC genes. All isolates were identified as S. aureus and demonstrated a methicillin-resistant phenotype. PCR confirmed the presence of the species-specific nuc gene and the methicillin-resistance determinant mecA, while mecC was not detected. The isolates exhibited resistance to multiple antimicrobial classes, including β-lactams, fluoroquinolones, and macrolides, while remaining susceptible to linezolid, vancomycin, teicoplanin, rifampicin, and tigecycline. This case documents the occurrence of MRSA in a captive jaguar and highlights the value of integrated microbiological and molecular investigations for the diagnosis and characterization of resistant bacterial infections in zoological species.
Since their first identification in Türkiye in 2001, OXA-48-like carbapenemases have posed diagnostic challenges due to variant-specific phenotypic and resistance profiles. We investigated the distribution of OXA-48 variants and their association with antimicrobial susceptibility, carbapenem minimum inhibitory concentrations (MICs), phenotypic detection performance, and single- or dual-carbapenemase production. A total of 703 clinical carbapenem-resistant Enterobacterales isolates recovered over 5 years were included. Identification and antimicrobial susceptibility testing were performed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and an automated system; carbapenem MICs by broth microdilution; carbapenemase genes by multiplex qPCR; and OXA-48 variants by sequence analysis. CNPt-direct and mCIM were performed for OXA-48 variants. OXA-48-like, NDM, and KPC carbapenemases were detected in 52.3%, 11.7%, and 11.5% of isolates, respectively, with co-production observed in 11.7% of OXA-48-like-positive isolates. The most common OXA-48 variants were OXA-48/245 (39.1%), OXA-232 (36.4%), and OXA-181 (17.6%), while OXA-244, OXA-162, and OXA-1200 were less frequent. This study represents the first report of the OXA-1200 variant from Türkiye. OXA-48/245 was the variant most commonly co-produced with other carbapenemases, whereas OXA-244 predominated among CNPt-direct-negative isolates. Susceptibility to meropenem and imipenem among OXA-48-like producers was 31% and 39.1%, respectively, with higher carbapenem MIC50 values observed for OXA-181, OXA-232, and OXA-48/245 compared to OXA-244. In K. pneumoniae, meropenem resistance rates were higher with OXA-48/245, OXA-232, and OXA-181 than with other variants. MIC50 values of carbapenem were higher in dual carbapenemase producers compared to single carbapenemase producers. Our findings show that OXA-48 variants significantly impact resistance profiles, MIC values, and the sensitivity of phenotypic tests and detection of co-produced carbapenemases. Understanding their regional distribution is crucial for targeted prevention strategies.
In protected areas, fragmentation and artificial light at night are usually present alongside changes in land type, from natural to agricultural or urban. We explored the intensity of edge effects on light trap responses of nocturnal insects at the margin of the floodplain forest in the Donau-Auen National Park in Central Europe, Austria. Specifically, we examined the abundance and biomass of nocturnal insects and characterized the community composition and diversity of moths with respect to the local habitat. In this study, 58 species were observed, with 21 unique records on the forest edge and nine in the interior. Traps in the forest interior harbored significantly higher nocturnal insect biomass. However, moth assemblages were more diverse at edge sites due to many singletons, attributed to individuals attracted from areas with open vegetation. Nine species (15.5% of total) were recorded later than expected given their summer flight periods, potentially reflecting the effects of ongoing climate change associated with warmer autumns. Overall, we observed higher moth species diversity at the forest edge, and insect biomass and moth abundance were higher within the forest. These findings underscore the urgent need to incorporate local anthropogenic landscape and climate change as synergically evolutionary drivers in future population and community-focused research.
The ion motion within a mass spectrometer is governed by the coupling of gas dynamics and electric fields. Therefore, a comprehensive understanding of ion transport from atmospheric pressure to the high-vacuum mass analyzer is crucial. In this work, a hybrid computational fluid dynamics-direct simulation Monte Carlo (CFD-DSMC) strategy was employed to accurately resolve the cross-scale flow fields spanning from the continuum to the rarefied regime in the mass spectrometer. Subsequently, a multiphysics model integrating gas dynamics, electric fields, and ion trajectories was developed to achieve high-precision predictions of ion transport behavior. To validate the accuracy of the theoretical simulation, ion transmission efficiencies of acetone and toluene were experimentally measured using a homemade low-pressure photoionization time-of-flight mass spectrometer (LPPI-TOF-MS). The experimental results demonstrated a strong correlation with the simulation predictions, achieving a maximum Pearson correlation coefficient (r) of 0.96 for toluene and 0.90 for acetone in the radio-frequency-only quadrupole (RFQ) region, confirming the model's reliability. This study provides a robust theoretical tool for elucidating ion transport mechanisms and guiding the optimization of ion optics in mass spectrometers.
To report on the experience of developing a care protocol for pediatric patients fixation for the transflight in rotary-wing aircrafts. Professional experience report. The protocol was developed within the aeromedical urgency and emergency service of Santa Catarina, guided by the Guide for the Construction of Care Protocols of Coren/São Paulo. The theoretical framework was based on an integrative review and consultation of documents from national and international official agencies, as well as the Brazilian Federal Nursing Council. Internal validation was carried out with eight flight nurses from the service. The protocol structured the care for securing the pediatric patient into three care phases: preflight, transflight, and postflight, supporting clinical decision-making and safety during transport. The developed protocol standardized the practices for pediatric patients fixation in aeromedical services, promoting safety and supporting clinical decision-making during transflight, minimizing the risk of complications during transport, and strengthening professional practice in the field of aeromedical services.
Ginseng radix et rhizoma (GRER) is widely used in China and around the world. Due to the shortages, high prices, and profitability, the market is also full of its confused varieties. Notoginseng radix et rhizoma, panacis quinquefolii radix, ginseng folium, and ginseng radix et rhizoma rubra are GRER's common confused varieties, which affected the market order and drug safety in the case of incorrect use. Therefore, it is very important to realize the recognition analysis of GRER and its confused varieties. GRER and its confused varieties were studied using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry to convert the data matrix. Then, the data matrix was used to conduct principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). At the same time, the data matrix was also used to construct data identification models based on machine learning, and the best model was screened for external appraisal and verification analysis. Moreover, the differential chemical components were analyzed on the basis of feature screening. the data matrices contained 1971 chemical components and PCA and PLS-DA results showed that GRER cannot be clearly distinguished from confused varieties. However, all the identification models based on K-nearest neighbor, artificial neural network, support vector machine, naive bayes, and random forest (RF) had an excellent identification effect with area under the curve (AUC) ≥0.980, accuracy ≥0.800, and precision ≥0.870 in which the RF model showed the best recognition effect with AUC = 1.000, accuracy = 1.000, and precision = 1.000. Twenty batches of test samples were accurately identified by external verification, and the correct rate was 100%. Pseudoginsenoside F11, ginsenoside Rb2, ginsenoside Ro, and so on were the important distinguishing chemical markers. compared with chemometrics, machine learning presented better identification results. Moreover, the RF model has the best recognition effect, which helps to identify the GRER and its confused varieties. In addition, the characteristic components based on feature screening also contributed to the discrimination of the GRER and its confused varieties.
Fatigue detection in remote tower air traffic controllers is important for maintaining operational safety under sustained visual monitoring and high cognitive workload. This study proposes MFD-Net, a dual-stream multimodal fusion framework using eye-tracking and electrocardiogram (ECG) signals. The model separately encodes eye-tracking and ECG-derived temporal inputs, incorporates an ECG-derived RMSSD expert feature, and performs lightweight late fusion for fatigue-state classification. Under the mixed-subject random-window protocol, MFD-Net achieved an Accuracy of 85.20%, a Recall of 83.33%, and an AUC of 0.9337. Because overlapping windows from the same participant and scenario could appear in both training and test sets, this result should be interpreted as a potentially optimistic within-distribution estimate. Under the stricter zero-shot leave-one-subject-out (LOSO) protocol, performance decreased substantially, with an Accuracy of 70.95±21.59%, a Recall of 22.98±36.30%, and an AUC of 0.6025±0.2984. This low zero-shot Recall indicates limited subject-independent fatigue-detection capability. Lightweight target-subject calibration and sequential probability aggregation improved adaptation and temporal stability, although the calibration results should be interpreted cautiously because random target-subject windows were used for fine-tuning. These findings suggest that eye-tracking and ECG fusion are promising under controlled conditions, while practical deployment requires deployment-oriented calibration protocols, recall-oriented optimization, and further real-world validation.
The rapid development of intelligent systems has introduced increasingly sophisticated optimization problems across diverse domains. While contemporary metaheuristic algorithms, including the recent Artificial Lemming Algorithm (ALA), have shown considerable promise, they frequently encounter difficulties such as premature convergence, inadequate local refinement, and diminished performance in high-dimensional multimodal environments. To overcome these issues, this study presents HALA, a new hybrid dual-subpopulation optimizer that effectively integrates an enhanced ALA with the SHADE algorithm. HALA employs two interacting subpopulations: one leverages an improved ALA with hybrid t-distribution and Levy flight perturbations to promote persistent long-range exploration and diversity preservation; the other applies SHADE's success-history adaptation and external archive for accurate local exploitation. Periodic bidirectional elite migration facilitates knowledge transfer between the subpopulations, reducing early stagnation in the enhanced ALA and strengthening SHADE's global search capability. HALA is thoroughly benchmarked against 17 advanced metaheuristics, including ALA, LSHADE, LSHADE-SPACMA, AOOA, BAEO, BPBO, CCO, CEO, CQALA, DFL, DMOA, DHOA, FGO, KLA, PGA, SO, and SOO, using the IEEE CEC2017 suite in 10, 30, 50, and 100 dimensions and the IEEE CEC2022 suite in 10 dimensions. Comprehensive analyses involving qualitative visualization, convergence curves, boxplots, and statistical tests indicate that HALA achieves competitive or superior solution quality, comparable or faster convergence, and robust stability on a substantial proportion of the test instances. In particular, HALA obtains the most favorable Friedman average ranking values among the compared algorithms, which are 2.55, 2.38, 2.34, and 2.55 for the 10-, 30-, 50-, and 100-dimensional CEC2017 functions, respectively, and 2.58 for the 12 10-dimensional CEC2022 functions. Moreover, HALA is successfully applied to five well-known constrained engineering design problems-pressure vessel, rolling element bearing, tension/compression spring, cantilever beam, and gear train-where it reliably achieves optimal or near-optimal results that match or surpass the compared methods. These findings underscore HALA's competitive strength and broad potential for practical engineering optimization.
Bacterial biofilms are complex bacterial communities embedded within an extracellular polymeric substance (EPS) that protects the cells and increases survival. Once established on an orthopaedic implant, a biofilm can cause difficult-to-treat and severe infections. Pseudomonas aeruginosa is of particular concern due to its strong biofilm-forming capability. Within biofilm communities, quorum sensing (QS) networks regulate biofilm formation, virulence, and intercellular communication. This is achieved through the production of signalling molecules, QS metabolites. In P. aeruginosa, quinolones such as the Pseudomonas quinolone signal (PQS) and its precursor 2-heptyl-4-quinolone (HHQ) are among the key regulators. However, although these signalling molecules regulate essential functions such as biofilm development, virulence regulation, and population-level communication, our understanding of their spatial distribution within P. aeruginosa biofilms is still limited. QS metabolites, also referred to as autoinducers, help in the regulation of biofilm formation and dispersion. These small molecules, including quinolones, often have an isomeric counter partner which is not involved as autoinducer. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) offers a label-free approach for the spatial detection of these metabolites directly within biofilms. To differentiate isomeric quinolones, such as PQS and 2-heptyl-4-hydroxyquinoline-N-oxide (HQNO), tandem MS (MS/MS) and trapped ion mobility spectrometry (TIMS) coupled to time-of-flight (TOF) mass spectrometry are employed in this study, with the addition of salt, sodium chloride, to enhance sodium adduct formation. This integrated approach provides spatially resolved insights into QS metabolite organisation, demonstrating an improved strategy for distinguishing isomeric species within bacterial biofilms and advancing our understanding of bacterial communication and potential anti-biofilm targets.
Metabolic reprogramming is a hallmark of cancer, enabling tumor cells to meet their increased biosynthetic and energetic demands. Although cells possess the capacity for de novo serine biosynthesis, most transformed cancer cells preferentially rely on exogenous serine uptake to sustain their growth, yet the regulatory mechanisms driving this metabolic dependency remain poorly understood. Here, we uncover a mechanism by which Polo-like kinase 1 (PLK1), frequently overexpressed in prostate cancer, orchestrates a metabolic shift in serine and sphingolipid metabolism through phosphorylation of phosphoglycerate dehydrogenase (PHGDH), the rate-limiting enzyme of the serine synthesis pathway (SSP). Specifically, PLK1 directly phosphorylates PHGDH at S512, S513, and S517, leading to a marked reduction in its protein level and enzymatic activity. This downregulation of de novo serine biosynthesis forces cancer cells to increase their reliance on exogenous serine uptake via the ASCT2 transporter, which in turn fuels the biosynthesis of lipids, including sphingolipids essential for tumor growth and survival. Our findings suggest that targeting the SSP, serine uptake, or downstream lipid biosynthesis pathways may represent promising therapeutic strategies in advanced cancers characterized by PLK1 dysregulation.
The hovering performance of membrane flapping-wing micro air vehicles (FWMAVs) is governed by numerous coupled parameters, making rapid forward optimization difficult via traditional empirical trials or localized fluid-structure interaction (FSI) analysis. This paper proposes a systematic design framework based on a decoupled parametric configuration and an explicit twist formula. First, a novel wing configuration capable of decoupling vein layouts from torsional deformation was identified and verified through baseline experiments, significantly simplifying the design space. Leveraging this parametric modeling, the study successfully derived an explicit analytical formula reflecting the quantitative relationship between spanwise twist and veins by performing high-fidelity FSI simulations on only a minimal set of key parameter points. This facilitates a transition from costly physical simulations to efficient mathematical expressions. Subsequently, this formula was integrated into the quasi-steady blade element method (BEM) alongside electromechanical constraints, such as motor torque saturation, to construct a fully coupled system optimization model. The optimized wing, identified via global search, achieved an 11% efficiency improvement and a lift-to-weight ratio exceeding 1.3, as validated by bench and guide-rail flight tests. This research transforms complex empirical design into deterministic analytical optimization, providing an efficient design tool for high-payload, high-efficiency FWMAVs.
Canine mammary cancer (CMC) is one of the most common malignant neoplasms in female dogs, with high metastatic potential and limited therapeutic options. Natural bioactive compounds derived from medicinal mushrooms have gained increasing attention because of their anticancer properties and low toxicity. Hericium erinaceus (HE) is a medicinal mushroom known for its antioxidant and antitumor activities; however, its anticancer effects in CMC remain poorly understood. Therefore, this study investigated the in vitro antiproliferative, pro-apoptotic, and epithelial-mesenchymal transition (EMT)-inhibitory effects of HE methanolic extract in two CMC cell lines, CHMp-13a and CHMp-5b. The anticancer activity of HE methanolic extract was evaluated using CHMp-13a and CHMp-5b CMC cell lines, while Madin-Darby canine kidney cells were used as normal controls. Cell viability was assessed using the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide assay. Cell migration and invasion were evaluated using wound healing and Transwell assays, respectively. Apoptosis was analyzed using Annexin V-fluorescein isothiocyanate/propidium iodide flow cytometry. Relative mRNA and protein expression levels of apoptosis- and EMT-related markers were determined using quantitative real-time polymerase chain reaction and western blotting. The phytochemical profile of the extract was characterized using liquid chromatography quadrupole time-of-flight mass spectrometry. HE extract significantly inhibited proliferation of both CMC cell lines in a dose- and time-dependent manner, with greater selectivity toward CHMp-13a cells and minimal cytotoxicity in normal cells. Morphological analysis revealed apoptotic features, including cell shrinkage, detachment, and cytoplasmic vacuolization. The extract significantly suppressed migration and invasion capacities of both CMC cell lines. Flow cytometric analysis demonstrated increased apoptotic cell populations following treatment. Molecular analyses showed upregulation of the pro-apoptotic marker BAX and downregulation of the anti-apoptotic marker BCL-2. Furthermore, HE extract suppressed EMT progression by increasing E-cadherin expression while reducing N-cadherin expression. Phytochemical screening identified 17 bioactive compounds, including erinacines, hericenones, hericene derivatives, and phenolic compounds, which may contribute to the observed anticancer activities. HE extract demonstrated potent in vitro anticancer activity against CMC cells through synergistic induction of apoptosis and suppression of EMT-associated metastatic behavior. These findings suggest that HE extract may serve as a promising natural adjuvant candidate for the management of CMC and warrants further in vivo and mechanistic investigations.