Levosimendan’s calcium sensitizing effects in heart muscle cells are well established; yet, its potential impact on skeletal muscle cells has not been evidently determined. Despite controversial results, levosimendan is still expected to interact with skeletal muscle through off-target sites (further than troponin C). Adding to this debate, we investigated levosimendan’s acute impact on fast-twitch skeletal muscle biomechanics in a length-dependent activation study by submersing single muscle fibres in a levosimendan-supplemented solution. We employed our MyoRobot technology to investigate the calcium sensitivity of skinned single muscle fibres alongside their stress–strain response in the presence or absence of levosimendan (100 µM). While control data are in agreement with the theory of length-dependent activation, levosimendan appears to shift the onset of the ‘descending limb’ of active force generation to longer sarcomere lengths without notably improving myofibrillar calcium sensitivity. Passive stretches in the presence of levosimendan yielded over twice the amount of enlarged restoration stress and Young’s modulus in comparison to control single fibres. Both effects have not been described before and may point towards potential off-target sites of levosimendan. Full article

This study is based on a sample of 30 Sinitic languages spoken in the Hunan Province. Its first objective is to explore the types of dative markers, comparing the form of the dative with allative, passive, benefactive, and differential object markers in these languages. Five patterns are identified: (I) DAT = ALL (II) DAT = GIVE = OM ≠ PASS; (III) DAT = GIVE = OM = PASS; (VI) DAT = GIVE = PASS ≠ OM; (V) DAT = BEN. Then, we reveal three main possible grammaticalization pathways that motivate the five synchronic patterns: (a) Allative > Dative; (b) (TAKE >) GIVE > Dative; (c) Benefactive > Dative. It concerns two distinct developments for the second pathway. Based on the areal distribution of the various types of dative markers, we can observe how the dative markers are developed in Hunan Sinitic languages. Full article

In this study, the chemical composition, repellent, and oviposition deterrent effects of five plant essential oils (EOs) extracted from Lantana camara (Verbenaceae), Schinus terebinthifolia (Anacardiaceae), Callistemon viminalis (Myrtaceae), Helichrysum odoratissimum (Asteraceae), and Hyptis suaveolens (Lamiaceae) were evaluated against Aedes aegypti, Anopheles gambiae, and Culex quinquefasciatus. When tested at 33.3 µg/cm², L. camara, S. terebinthifolia, C. viminalis, and H. odoratissimum were effective repellents against Ae. aegypti (89%, 91%, 90%, and 51% repellency, respectively), but they were less repellent against An. gambiae (66%, 86%, 59%, and 49% repellency, respectively). Interestingly, L. camara, S. terebinthifolia, C. viminalis, and H. odoratissimum exhibited 100% repellency against Cx. quinquefasciatus at 33.3 μg/cm². In time-span bioassays performed at 333 μg/cm², the EO of L. camara exhibited 100% repellence against Ae. aegypti and An. gambiae for up to 15 min and against Cx. quinquefasciatus for 75 min. The oviposition bioassays revealed that L. camara exhibited the highest activity, showing 85%, 59%, and 89% oviposition deterrence against Ae. aegypti, An. gambiae, and Cx. quinquefasciatus, respectively. The major compounds of L. camara, S. terebinthifolia, and C. viminalis were trans-β-caryophyllene (16.7%), α-pinene (15.5%), and 1,8-cineole (38.1%), respectively. In conclusion, the L. camara and S. terebinthifolia EOs have the potential to be natural mosquito repellents. Full article

Nowadays, technology is increasingly being adopted in different kinds of businesses to process, store, and share sensitive information in digital environments that include enormous numbers of users. However, this has also increased the likelihood of cyberattacks and misuse of information, potentially causing severe damage. One promising technology, which can provide the required security services with an improved level of efficiency, is blockchain. This research explores the use of Ethereum blockchain and smart contracts to create a secure and efficient quality assurance system (QAS) for academic programs. By utilizing blockchain and smart contracts, the proposed approach improves the integrity and reliability of sensitive information processed by the QAS, promotes transparency and governance, and reduces the time and effort required for quality operations. The current approach uses an additional access control layer to further enhance user privacy. Smart contracts automate various quality transactions and saves time and resources, and hence increases the efficiency of the QAS. The interplanetary file system (IPFS) is used to address the challenge of size limitations in blockchain. Additionally, this research investigates the use of various cryptographic schemes to provide robust security services at the application layer. The experimental results showed that the use of a hybrid cryptosystem relying on an Elliptic curve digital signature and AES encryption (AES_ECCDSA) outperforms other counterparts’ cryptosystems using an RSA digital signature and AES encryption (AES_RSADSA) and Elliptic Curve Integrated Encryption Scheme (ECIES) in terms of speed. The performance results showed that AES_ECCDSA consumes 188 ms to perform the required cryptographic operations for a standard-quality document with a size of 8088 KB, compared to the 231 ms and 739 ms consumed by the AES_RSADSA and ECIES schemes, respectively. This study presents a prototype implementation of the blockchain-based QAS, which outlines the processing model and system requirements for key QAS processes. It has been found that the cost and time required for blockchain operations vary depending on the size of the input data—a larger data size requires more time and costs more to process. The results of the current study showed that the time delay for blockchain transactions ranges from 15 to 120 s, while the cost ranges from USD 50 to USD 400. This research provides evidence that blockchain and smart contract technologies have the potential to create a secure, efficient, and trustworthy QAS environment for academic programs. Full article

This paper takes the central area of Shenzhen as an example to explore the correlation and differences between 2D and 3D green spaces on urban roads during the summer of 2023. By collecting street view image data and using convolutional neural networks for image semantic segmentation, the Green View Index (GVI) was calculated and combined with the Normalized Difference Vegetation Index (NDVI) for analysis. The results show that the road greening levels in Nanshan District, Futian District, and Luohu District of Shenzhen are relatively high, with GVI exceeding 25%. The Pearson correlation coefficient between the 2D and 3D greening data is 0.5818, indicating a moderate correlation. By analyzing four typical greening scenarios (high NDVI and high GVI, high NDVI and low GVI, low NDVI and high GVI, and low NDVI and low GVI), the study found specific reasons for the differences in green data in different dimensions; the analysis revealed that factors such as building height, density, and elevated transportation facilities significantly affect the accuracy of NDVI in urban spaces. The study suggests that in urban greening assessments, the complementarity and differences between street view data and remote sensing data should be comprehensively considered to improve the accuracy and comprehensiveness of the analysis. Full article

In this paper, a planning method based on the spatiotemporal variable-step-size A* algorithm is proposed to address the problem of safe trajectory planning for incremental, wheeled, mobile robots in complex motion scenarios with multiple robots. After constructing the known conditions, the spatiotemporal variable-step-size A* algorithm is first used to perform a collision-avoiding initial spatiotemporal trajectory search, and a variable time step is utilized to ensure that the robot completes the search at the target speed. Subsequently, the trajectory is instantiated using B-spline curves in a numerical optimization considering constraints to generate the final smooth trajectory. The results of simulation tests in a field-shaped, complex, dynamic scenario show that the proposed trajectory planning method is more applicable, and the results indicate higher efficiency compared to the traditional method in the incremental robot trajectory planning problem. Full article

Urban tree canopy (UTC) provides urban residents with numerous benefits, including positive mental and physical health, the mitigation and prevention of urban heat islands, and a sense of place. Numerous studies have shown that as the wealth of a community decreases, so does the amount of UTC found in the community; thus, wealthier communities are more likely to enjoy the benefits that urban forests provide. Emerging technologies in remote sensing and GIS are allowing for new opportunities to study and understand the relationships between urban neighborhoods and UTC. In this study, land cover data for Chattanooga, Tennessee were derived from high-resolution (50 cm) multispectral imagery to assess the previously unknown extent and distribution of UTC and to measure the extent of UTC by neighborhood and census block group level. Using exploratory regression analysis, variables representing income, population density, race, educational attainment, and urban heat islands were analyzed to investigate the influence of UTC on neighborhood characteristics. This study found that UTC represented half of the total land cover composition, the tree equity was not as profound as shown in other cities, and the lack of UTC likely influences the prevalence of urban heat islands. This study also shows the importance and utility of using high-resolution imagery and land cover to assess and understand the impact and distribution of UTC in urban environments. Full article

A profound comprehension of friction and wear mechanisms is essential for the design and development of high-performance polymeric materials for tribological application. However, it is difficult to deeply investigate the polymer friction process in situ at the micro/mesoscopic scale by traditional research methods. In recent years, molecular dynamics (MD) simulation, as an emerging research method, has attracted more and more attention in the field of polymer tribology due to its ability to show the physicochemical evolution between the contact interfaces at the atomic scale. Herein, we review the applications of MD in recent studies of polymer tribology and their research focuses (e.g., tribological properties, distribution and conformation of polymer chains, interfacial interaction, frictional heat, and tribochemical reactions) across three perspectives: all-atom MD, reactive MD, and coarse-grained MD. Additionally, we summarize the current challenges encountered by MD simulation in polymer tribology research and present recommendations accordingly, aiming to provide several insights for researchers in related fields. Full article

Background: The aim of this review was to evaluate the effects of periodontal disease (PD) treatment in pregnant women to reduce the risk of preterm birth (PB) and low birth weight (LBW) by conducting an umbrella review. Methods: A comprehensive search for the literature up to April 2024 was conducted across multiple databases including PubMed, Cochrane Library, Scopus, EMBASE, Scielo, Web of Science, Google Scholar, Proquest Dissertations and Theses, and OpenGrey. We specifically targeted systematic reviews (SRs) with or without meta-analyses, irrespective of language or time constraints, focusing on primary studies examining the effect of PD treatment in pregnant women to reduce the risk of PB and LBW. Various types of non-systematic reviews, intervention studies, observational studies, preclinical and basic research, summaries, comments, case reports, protocols, personal opinions, letters, and posters were excluded from consideration. The quality and overall confidence of the included studies were assessed using the AMSTAR–2 tool. Results: After the initial search, 232 articles were identified, of which only 24 met the selection criteria after exclusion. The majority of these studies indicated that periodontal treatment reduces the risk of PB and LBW. Conclusions: According to the findings and conclusions drawn from the SRs with a high overall confidence level, PD treatment in pregnant women reduces the risk of PB and LBW. Full article

Protein palmitoylation, the most common and the only reversible post-translational lipid modification following protein translation, plays a pivotal role in the biochemical and physiological processes of both animals and plants. DHHC proteins, enriched with DHHC (Asp-His-His-Cys) domains, serve as catalyst for protein palmitoylation. However, research on DHHC in cotton remains scarce. This study conducted a systematic characterization and bioinformatics analysis on G. arboreum, G. raimondii, G. hirsutum, and G. barbadense, detecting 38, 37, 74, and 74 DHHC genes, respectively. Phylogenetic analysis categorized the DHHC gene family into six subgroups, consistent with previous evolutionary studies in Arabidopsis and rice. A further examination of protein structure revealed a correlation between genetic relatedness, structural similarity, and functional identity. Cis-element analysis identified elements predominantly associated with light response, stress, growth and development, and plant hormones. The integration of cotton seed development transcriptome, tissue expression pattern analysis, and population transcriptome data collectively suggests that Ghir_A05G027650 and Ghir_D05G027670 are promising candidate genes influencing seed development in upland cotton. Conversely, Gbar_A04G010750 and Gbar_A12G020520 emerge as potential candidates affecting both seed and fiber development in sea island cotton. These findings lay down a theoretical foundation for delving into the functional diversity of DHHC genes in cotton, thereby paving the way for the development of new breeding strategies and the optimization of cotton seed and fiber production, ultimately contributing to improved crop yield and quality. Full article

Effective feature extraction and selection are crucial for the accurate classification and prediction of hand gestures based on electromyographic signals. In this paper, we systematically compare six filter and wrapper feature evaluation methods and investigate their respective impacts on the accuracy of gesture recognition. The investigation is based on several benchmark datasets and one real hand gesture dataset, including 15 hand force exercises collected from 14 healthy subjects using eight commercial sEMG sensors. A total of 37 time- and frequency-domain features were extracted from each sEMG channel. The benchmark dataset revealed that the minimum Redundancy Maximum Relevance (mRMR) feature evaluation method had the poorest performance, resulting in a decrease in classification accuracy. However, the RFE method demonstrated the potential to enhance classification accuracy across most of the datasets. It selected a feature subset comprising 65 features, which led to an accuracy of 97.14%. The Mutual Information (MI) method selected 200 features to reach an accuracy of 97.38%. The Feature Importance (FI) method reached a higher accuracy of 97.62% but selected 140 features. Further investigations have shown that selecting 65 and 75 features with the RFE methods led to an identical accuracy of 97.14%. A thorough examination of the selected features revealed the potential for three additional features from three specific sensors to enhance the classification accuracy to 97.38%. These results highlight the significance of employing an appropriate feature selection method to significantly reduce the number of necessary features while maintaining classification accuracy. They also underscore the necessity for further analysis and refinement to achieve optimal solutions. Full article

Intestinal epithelium renewal strictly depends on fine regulation between cell proliferation, differentiation, and apoptosis. While murine intestinal microbiota has been shown to modify some epithelial cell kinetics parameters, less is known about the role of the human intestinal microbiota. Here, we investigated the rate of intestinal cell proliferation in C3H/HeN germ-free mice associated with human flora (HFA, n = 8), and in germ-free (n = 15) and holoxenic mice (n = 16). One hour before sacrifice, all mice were intraperitoneally inoculated with 5-bromodeoxyuridine (BrdU), and the number of BrdU-positive cells/total cells (labelling index, LI), both in the jejunum and the colon, was evaluated by immunohistochemistry. Samples were also observed by scanning electron microscopy (SEM). Moreover, the microbiota composition in the large bowel of the HFA mice was compared to that of of human donor’s fecal sample. No differences in LI were found in the small bowels of the HFA, holoxenic, and germ-free mice. Conversely, the LI in the large bowel of the HFA mice was significantly higher than that in the germ-free and holoxenic counterparts (p = 0.017 and p = 0.048, respectively). In the holoxenic and HFA mice, the SEM analysis disclosed different types of bacteria in close contact with the intestinal epithelium. Finally, the colonic microbiota composition of the HFA mice widely overlapped with that of the human donor in terms of dominant populations, although Bifidobacteria and Lactobacilli disappeared. Despite the small sample size analyzed in this study, these preliminary findings suggest that human intestinal microbiota may promote a high proliferation rate of colonic mucosa. In light of the well-known role of uncontrolled proliferation in colorectal carcinogenesis, these results may deserve further investigation in a larger population study. Full article

In recent years, the increasing production and sales of automobiles have led to a notable rise in congestion on urban road traffic systems, particularly at ramps and intersections with traffic signals. Intelligent traffic signal control represents an effective means of addressing traffic congestion. Reinforcement learning methods have demonstrated considerable potential for addressing complex traffic signal control problems with multidimensional states and actions. In this research, the team propose Q-learning and Deep Q-Network (DQN) based signal control frameworks that use variable phase sequences and cycle times to adjust the order and the duration of signal phases to obtain a stable traffic signal control strategy. Experiments are simulated using the traffic simulator Simulation of Urban Mobility (SUMO) to test the average speed and the lane occupancy rate of vehicles entering the ramp to evaluate its safety performance and test the vehicle’s traveling time to assess its stability. The simulation results show that both reinforcement learning algorithms are able to control cars in dynamic traffic environments with higher average speed and lower lane occupancy rate than the no-control method and that the DQN control model improves the average speed by about 10% and reduces the lane occupancy rate by about 30% compared to the Q-learning control model, providing a higher safety performance. Full article

A high strength and ductile Mg-Gd-Y-Zn-Zr alloy was designed and fabricated. The local strain evolution of the alloys during plastic deformation was analyzed using high-resolution digital image correlation (DIC). The results showed that the β particles, nano-sized γ’ phases, and LPSO phases were distributed in the as-extruded alloy and a bimodal microstructure was exhibited, including elongated un-dynamic recrystallized grains and fine dynamic recrystallized grains. With increasing extrusion ratio, the grain size remained, with the volume fraction of dynamic recrystallization of the as-extruded alloy increasing from 30% to 75%, and the as-extruded alloy exhibited a high strength-ductility synergy, which is attributed to the grain refinement, extensive β particles, and elongated block-shaped LPSO phases. The strain evolution analysis showed that a strain-transfer from un-DRXed regions to adjacent DRXed regions and LPSO phases can promote uniform plastic deformation, which tends to improve the ductility of the alloy. Full article

Due to the limitations of traditional geometric error measurement, the measurement accuracy of long-stroke geometric errors is generally not high and the operation is complicated. In response to the above situation, in this study, a geometric error measurement system is built with a laser beam as the reference line and 2D position sensitive detector as the photoelectric conversion device. The single measurement range is 40 m, and the measurement range is further expanded through the principle of segmented splicing. Using an ultra-long guide rail as the measurement object for straightness measurement, the experimental results are similar to those of a laser interferometer. The uncertainty analysis model was obtained through the analysis of quantity characteristics, and based on this, the variance synthesis theorem and probability distribution propagation principle were studied to form two uncertainty synthesis methods. The measurement evaluation results showed that the two methods were basically consistent. The work provided a reference method for the uncertainty evaluation of position-sensitive detector measurement systems in the future. Full article

Multiple myeloma (MM) is a hematologic malignancy caused by the clonal expansion of immunoglobulin-producing plasma cells in the bone marrow and/or extramedullary sites. Common manifestations of MM include anemia, renal dysfunction, infection, bone pain, hypercalcemia, and fatigue. Despite numerous recent advancements in the MM treatment paradigm, current therapies demonstrate limited long-term effectiveness and eventual disease relapse remains exceedingly common. Myeloma cells often develop drug resistance through clonal evolution and alterations of cellular signaling pathways. Therefore, continued research of new targets in MM is crucial to circumvent cumulative drug resistance, overcome treatment-limiting toxicities, and improve outcomes in this incurable disease. This article provides a comprehensive overview of the landscape of novel treatments and emerging therapies for MM grouped by molecular target. Molecular targets outlined include BCMA, GPRC5D, FcRH5, CD38, SLAMF7, BCL-2, kinesin spindle protein, protein disulfide isomerase 1, peptidylprolyl isomerase A, Sec61 translocon, and cyclin-dependent kinase 6. Immunomodulatory drugs, NK cell therapy, and proteolysis-targeting chimera are described as well. Full article

The objectives of the present study were to describe specific anatomical structures of the dromedary udder. Eighty-six dromedary udders were examined, taking morphological measurements and producing injection casts using resin, gelatin, and paraffin. The udder of the dromedaries consists of four quarters. The shape of the udders and teats varies considerably between animals and is influenced by age, breeding, and lactation status. The most frequently found udder form was the globular udder (48.8%) and the most common teat form in this study was the funnel teat (44.2%). The most common teat tip shape was a smooth or a slightly rough ring teat (61.6%). Injection casts showed a complete separation of the teat canals. There is also no communication between tributary mammary complexes. Resin injections of the glandular tissue adjacent to the teat cistern showed an extensive branching into large, medium, and small milk ducts. Frozen sections of the udder revealed complete separation of the right and left mammary complex through the Sulcus intermammarius. The teat sections showed longitudinal folds from the tip of the teat to the base of the teat. A ring fold at the transition from the Ductus papillaris to the teat cistern was present. The results of this study increase the knowledge of the anatomical structures of the dromedary udder, which may be useful for breeding a selection of dairy dromedaries. Full article

The spatial-temporal distribution of underwater sound speed plays a critical role in determining the propagation mode of underwater acoustic signals. Therefore, rapid estimation and prediction of sound speed distribution are imperative for facilitating underwater positioning, navigation, and timing (PNT) services. While sound speed profile (SSP) inversion methods offer quicker response times compared to direct measurement methods, these methods often focus on constructing spatial sound velocity fields and heavily rely on sonar observation data, thus imposing stringent requirements on data sources. To delve into the temporal distribution pattern of sound speed and achieve SSP prediction without relying on sonar observation data, we introduce the hierarchical long short-term memory (H-LSTM) neural network for SSP prediction. Our method enables the estimation of sound speed distribution without the need for on-site data measurement, significantly enhancing time efficiency. Compared to other state-of-the-art approaches, the H-LSTM model achieves a root mean square error (RMSE) of less than 1 m/s in predicting monthly average sound speed distribution. Its prediction accuracy has improved several-fold over alternative methods, which validates the robust capability of our proposed model in predicting SSP. Full article

Over the past few decades, the worldwide incidence of cutaneous melanoma, a malignant neoplasm arising from melanocytes, has been increasing markedly, leading to the highest rate of skin cancer-related deaths. While localized tumors are easily removed by excision surgery, late-stage metastatic melanomas are refractory to treatment and exhibit a poor prognosis. Consequently, unraveling the molecular mechanisms underlying melanoma tumorigenesis and metastasis is crucial for developing novel targeted therapies. We found that the multiple endocrine neoplasia type 1 (MEN1) gene product Menin is required for the transforming growth factor beta (TGFβ) signaling pathway to induce cell growth arrest and apoptosis in vitro and prevent tumorigenesis in vivo in preclinical xenograft models of melanoma. We further identified point mutations in two MEN1 family members affected by melanoma that led to proteasomal degradation of the MEN1 gene product and to a loss of TGFβ signaling. Interestingly, blocking the proteasome degradation pathway using an FDA-approved drug and RNAi targeting could efficiently restore MEN1 expression and TGFβ transcriptional responses. Together, these results provide new potential therapeutic strategies and patient stratification for the treatment of cutaneous melanoma. Full article

The effect of the active element yttrium and its content on the oxidation behavior of GH4169 Ni-based superalloy at extreme temperature was studied by isothermal oxidation experiments. The results show that the oxide scale of GH4169 alloy presents a multi-layer structure, in which the continuous and dense Cr₂O₃ oxide layer is located in the subouter layer (II layer) and the continuous Nb-rich layer is in the subinner layer (III layer). These layers can inhibit the diffusion of oxygen and alloying elements, preventing the further oxidation of the alloy. The appropriate addition of yttrium can promote the selective oxidation of Cr element, reduce the thickness of the oxide scale and the oxidation rate of the alloy, inhibit the formation of voids at the interface of the oxide scale/alloy matrix, improve the resistance of the alloy to spalling as well as the adhesion of the oxide scale, and improve the high-temperature oxidation resistance of the alloy. Of those tested, the alloy containing 0.04 wt.%Y has the lowest oxidation weight gain, the slowest oxidation rate, and less oxide scale spalling. Based on this, the effect of yttrium on the high-temperature oxidation behavior of GH4169 Ni-based superalloy and its mechanism were revealed. Full article

Patient safety culture is relevant both in the delivery of care and in the training of nursing staff, its purpose being to prevent and reduce risks associated with health care. This research aims to evaluate patient safety culture from the perspective of the nursing teams in a highly complex public hospital in the city of Valparaíso, Chile. A cross-sectional study with a quantitative approach applying descriptive, bivariate, and inferential statistical analysis was conducted on 259 nurses and nursing assistants from 13 adult medical–surgical units of the Carlos Van Buren hospital. The participants were obtained through a non-probabilistic convenience sample, answering the hospital survey on Patient Safety Culture version 2.0 (HSOPS 2.0), adapted to the Chilean population. The best-evaluated dimension was communication and receptivity; the worst was the support administrators provide for patient safety. This study identified the weaknesses and strengths of the hospital, the most worrying weakness being the shortage of human capital, material, and financial resources necessary to improve patient safety. This study was not registered. Full article

Background: The use of standardized patient simulation in psychiatric nursing education addresses the unique challenges presented by mental healthcare settings. Students’ attitudes toward clinical simulation remain predominantly favorable, with many expressing enthusiasm for the opportunities it provides in terms of embracing challenges, enhancing realism, and promoting critical thinking through problem solving, decision-making, and adaptability. Methods: This quantitative study used a cross-sectional, descriptive, correlation design to investigate the effectiveness of standardized patient simulation as a teaching method in the Psychiatric and Mental Health nursing course in a university setting. A total of 84 nursing students were recruited for the convenience sample. Data were collected using a three-part questionnaire survey which included the following: a demographic data sheet, the Student Satisfaction and Self-confidence in Learning Scale, and a narrative open-ended question asking the participants to write the advantages and disadvantages of their simulation experience. Data were analyzed using the statistical software JMP pro17. Results: The total satisfaction with learning subscale score ranged between 5 and 25 with a mean score of 19.36 ± 6.32. The total self-confidence subscale score ranged between 8 and 40 with a mean score of 30.87 ± 9.1. Pearson’s correlation coefficient r revealed a statistically significant positive relationship between the participants’ satisfaction with the learning experience and their self-confidence (t = 0.923, p < 0.0001). Approximately 91.7% of the students recommended using simulation. The results confirmed the students’ recommendations of simulation use in teaching psychiatric and mental health courses; furthermore, the results showed a statistically significant positive correlation with the total SSLS (p = 0.01) and satisfaction with learning subscale (0.003). Participants reported that authentic, practical, comfortable, and safe learning environments contributed to an enriched learning experience. Additionally, factors such as timesaving, access to information, cost-effectiveness, standardized teaching, varied exposure, skill development, and immediate feedback also enhanced the learning experience through patient simulation in psychiatric and mental health nursing. Conclusion: Simulations can contribute efficiently and positively to psychiatric and mental health nursing education in a manner that optimizes the learning experience while ensuring the consistency of student learning in a safe learning environment. Full article