Glioblastoma Multiforme (GBM) is an aggressive brain tumor with a high mortality rate. Direct reprogramming of glial cells to different cell lineages, such as induced neural stem cells (iNSCs) and induced neurons (iNeurons), provides genetic tools to manipulate a cell’s fate as a potential therapy for neurological diseases. NeuroD1 (ND1) is a master transcriptional factor for neurogenesis and it promotes neuronal differentiation. In the present study, we tested the hypothesis that the expression of ND1 in GBM cells can force them to differentiate toward post-mitotic neurons and halt GBM tumor progression. In cultured human GBM cell lines, including LN229, U87, and U373 as temozolomide (TMZ)-sensitive and T98G as TMZ-resistant cells, the neuronal lineage conversion was induced by an adeno-associated virus (AAV) package carrying ND1. Twenty-one days after AAV-ND1 transduction, ND1-expressing cells displayed neuronal markers MAP2, TUJ1, and NeuN. The ND1-induced transdifferentiation was regulated by Wnt signaling and markedly enhanced under a hypoxic condition (2% O₂ vs. 21% O₂). ND1-expressing GBM cultures had fewer BrdU-positive proliferating cells compared to vector control cultures. Increased cell death was visualized by TUNEL staining, and reduced migrative activity was demonstrated in the wound-healing test after ND1 reprogramming in both TMZ-sensitive and -resistant GBM cells. In a striking contrast to cancer cells, converted cells expressed the anti-tumor gene p53. In an orthotopical GBM mouse model, AAV-ND1-reprogrammed U373 cells were transplanted into the fornix of the cyclosporine-immunocompromised C57BL/6 mouse brain. Compared to control GBM cell-formed tumors, cells from ND1-reprogrammed cultures formed smaller tumors and expressed neuronal markers such as TUJ1 in the brain. Thus, reprogramming using a single-factor ND1 overcame drug resistance, converting malignant cells of heterogeneous GBM cells to normal neuron-like cells in vitro and in vivo. These novel observations warrant further research using patient-derived GBM cells and patient-derived xenograft (PDX) models as a potentially effective treatment for a deadly brain cancer and likely other astrocytoma tumors. Full article

The spindle tool is an important module of the machine tool. Its dynamic characteristics directly affect the machining performance, but it could also be affected by thermal deformation and bearing preload. However, it is difficult to detect the change in the bearing preload through sensory instruments. Therefore, this study aimed to establish a digital thermal–mechanical model to investigate the thermal-induced effects on the spindle tool system. The technologies involved include the following: Run-in experiments of the milling spindle at different speeds, the establishment of the thermal–mechanical model, identification of the thermal parameters, and prediction of the thermal-induced preload of bearings in the spindle. The speed-dependent thermal parameters were identified from thermal analysis through comparisons with transient temperature history, which were further used to model the thermal effects on the bearing preload and dynamic compliance of the milling spindle under different operating speeds. Current results of thermal–mechanical analysis also indicate that the internal temperature of the bearing can reach 40 °C, and the thermal elongation of the spindle tool is about 27 µm. At the steady state temperature of 15,000 rpm, the bearing preload is reduced by 40%, which yields a decrease in the bearing rigidity by approximately 16%. This, in turn, increases the dynamic compliance of the spindle tool by 22%. Comparisons of the experimental measurements and modeling data show that the variation in bearing preload substantially affects the modal frequency and stiffness of the spindle. These findings demonstrated that the proposed digital spindle model accurately mirrors real spindle characteristics, offering a foundation for monitoring performance changes and refining design, especially in bearing configuration and cooling systems. Full article

Recent advancements in renewable energy technologies, alongside changes in utility infrastructure and progressive government policies, have bolstered the integration of renewable-based distributed generation units within distribution systems. This paper introduces the Energy Valley Optimizer, a novel tool designed for the strategic placement of distributed generation units and capacitor banks. This placement is crucial not only for optimizing energy loss and enhancing bus voltage stability but also for promoting sustainable energy use and reducing environmental impact over the long term. By minimizing energy loss and voltage fluctuations, the optimizer contributes to a more sustainable and resilient energy system. It achieves this through the optimal allocation of resources across various load patterns within a 24 h period and is tested on the ALG-AB-Hassi-Sida 157-bus distribution network in South Algeria. Comparative analysis with existing algorithms—such as the Liver Cancer Algorithm, Walrus Optimization Algorithm, and Zebra Optimization Algorithm—demonstrates the superior performance of the Energy Valley Optimizer. It not only enhances technical and economic efficiencies but also significantly lowers the total cost of energy over 24 years, thus supporting sustainable development goals in energy management. Full article

Children functioning at Gross Motor Function Classification System (GMFCS) levels IV–V cannot maintain an aligned standing position or take steps without support. Upright positioning and mobility devices have psycho-social significance for these children and their families, enhancing use of vision, communication, functioning and emotional well-being. Standers and supported stepping devices facilitate opportunities for biomechanical loading, potentially helping to build and maintain muscle and bone integrity, and they promote physical development. However, families are often required to choose between these two devices for their young child. This study aims to synthesize evidence for use and benefits of both supported standing and stepping devices through the lens of two contemporary theoretical frameworks to support clinical reasoning and implementation. The F-words for childhood development (functioning, family, fitness, fun, friends, future) and the interdependence-Human Activity Assistive Technology (iHAAT) models were combined to illustrate the complex interactions between the child, family, caregivers, peers and contextual factors when implementing standing and stepping devices with children at GMFCS levels IV and V. Supported standing and stepping devices provide complementary benefits, and both may be necessary starting at 9–15 months. We propose they both be included ON-Time, along with other age-appropriate positioning and mobility devices, to promote more equitable developmental opportunities for children with non-ambulant cerebral palsy. Full article

The dim lighting and excessive dust in underground mines often result in uneven illumination, blurriness, and loss of detail in surveillance images, which hinders subsequent intelligent image recognition. To address the limitations of the existing image enhancement algorithms in terms of generalization and accuracy, this paper proposes an unsupervised method for enhancing mine images in the hue–saturation–value (HSV) color space. Inspired by the HSV color space, the method first converts RGB images to the HSV space and integrates Retinex theory into the brightness (V channel). Additionally, a random perturbation technique is designed for the brightness. Within the same scene, a U-Net-based reflectance estimation network is constructed by enforcing consistency between the original reflectance and the perturbed reflectance, incorporating ResNeSt blocks and a multi-scale channel pixel attention module to improve accuracy. Finally, an enhanced image is obtained by recombining the original hue (H channel), brightness, and saturation (S channel), and converting back to the RGB space. Importantly, this image enhancement algorithm does not require any normally illuminated images during training. Extensive experiments demonstrated that the proposed method outperformed most existing unsupervised low-light image enhancement methods, qualitatively and quantitatively, achieving a competitive performance comparable to many supervised methods. Specifically, our method achieved the highest PSNR value of 22.18, indicating significant improvements compared to the other methods, and surpassing the second-best WCDM method by 10.3%. In terms of SSIM, our method also performed exceptionally well, achieving a value of 0.807, surpassing all other methods, and improving upon the second-place WCDM method by 19.5%. These results demonstrate that our proposed method significantly enhanced image quality and similarity, far exceeding the performance of the other algorithms. Full article

In this paper, a novel experimental setup to quantify the particle deposition during a lithium-ion battery thermal runaway (TR) is proposed. The setup integrates a single prismatic battery cell into an environment representing similar conditions as found for battery modules in battery packs of electric vehicles. In total, 86 weighing plates, positioned within the flow path of the vented gas and particles, can be individually removed from the setup in order to determine the spatial mass distribution of the deposited particles. Two proof-of-concept experiments with different distances between cell vent and module cover are performed. The particle deposition on the weighing plates as well as the particle size distribution of the deposited particles are found to be dependent on the distance between cell vent and cover. In addition, the specific heat capacity of the deposited particles as well as the jelly roll remains are analyzed. Its temperature dependency is found to be comparable for both ejected particles and jelly roll remains. The results of this study help researches and engineers to gain further insights into the particle ejection process during TR. By implementing certain suggested improvements, the proposed experimental setup may be used in the future to provide necessary data for simulation model validation. Therefore, this study contributes to the improvement of battery pack design and safety. Full article

Fossil fuels are still widely used today, and exploring more sustainable ways of using coal is crucial. One promising approach is to develop a patented fuel with reduced harmful gas emissions during combustion. This study aims to investigate the properties of the ash produced by burning steam coal mixed with various ratios of patent fuel. The combustion process was carried out using a standard solid fuel boiler with a power output of 70 kW. The ash samples were analyzed using various analytical methods, and ash leaching tests were conducted. The study found that adding patent fuel to coal affects combustion and ash composition. Determining the thermal stability of ash samples showed that adding patent fuel to coal results in decomposition starting earlier and in stronger combustion. The ash produced by patent fuel–coal mixtures contains lower concentrations of Ba, Cr, Ga, Li, Mn, V, and Zn than pure coal combustion. Leaching tests showed that coal ash leachates had higher concentrations of environmental pollutants, such as As, Cd, Co, Mn, Mo, Sb, and U, than patent fuel leachates. Adding patent fuel to coal affects combustion, ash properties, emissions, and disposal. Understanding these implications can help to develop sustainable coal usage and reduce environmental impact. Full article

This study aimed to evaluate the effect of inoculants of endophytic bacteria producing indoleacetic acid (IAA) on the physiological quality of seeds and the production of seedlings of Corymbia citriodora (Hook.) KD Hill & LAS Johnson. In the physiological quality test of the seeds, the treatments used were individual inoculation with Priestia megaterium, Exiguobacterium sibiricum, Pantoea vagans strain 45URP4-1, and Bacillus sp.; joint effect of the four strains (mix); inoculation only with the carrier (cassava starch and activated charcoal); carrier with 1.0 μg mL⁻¹ of IAA; and non-inoculated control without IAA and without a carrier. In the production of seedlings in a greenhouse, the treatments were the same, except for the mix, which was replaced by P. vagans strain 7URP1-6 (Pvs7), as inoculation with the mix increased the number of abnormal seedlings. In the physiological quality test of seeds, seeds inoculated with the bacteria individually did not have the physiological quality impaired and the carrier created a microenvironment around the seeds, benefiting germination percentage, germination speed index, average germination time, and average germination speed. In the greenhouse, seedlings inoculated with Pvs7, P. megaterium and E. sibiricum were taller, with a larger stem diameter and dry mass of shoot, roots, and total. Seeds inoculated with E. sibiricum had higher averages for height, chlorophyll b content, and shoot and total dry mass, as well as a greater ability to colonize the rhizosphere and roots of C. citriodora, resulting in the production of higher-quality seedlings. Inoculation of seeds of C. citriodora with endophytic bacteria proved to be a promising alternative for plant development. Full article

The role of the immune system in myocarditis onset and progression involves a range of complex cellular and molecular pathways. Both innate and adaptive immunity contribute to myocarditis pathogenesis, regardless of its infectious or non-infectious nature and across different histological and clinical subtypes. The heterogeneity of myocarditis etiologies and molecular effectors is one of the determinants of its clinical variability, manifesting as a spectrum of disease phenotype and progression. This spectrum ranges from a fulminant presentation with spontaneous recovery to a slowly progressing, refractory heart failure with ventricular dysfunction, to arrhythmic storm and sudden cardiac death. In this review, we first examine the updated definition and classification of myocarditis at clinical, biomolecular and histopathological levels. We then discuss recent insights on the role of specific immune cell populations in myocarditis pathogenesis, with particular emphasis on established or potential therapeutic applications. Besides the well-known immunosuppressive agents, whose efficacy has been already demonstrated in human clinical trials, we discuss the immunomodulatory effects of other drugs commonly used in clinical practice for myocarditis management. The immunological complexity of myocarditis, while presenting a challenge to simplistic understanding, also represents an opportunity for the development of different therapeutic approaches with promising results. Full article

This research explores fluid flow speed behavior in capillary channels using additive manufacturing, focusing on stereolithography (SLA). It aims to validate microchannels fabricated through SLA for desired fluid flow characteristics, particularly capillary-driven flow. The methodology involves designing, fabricating, and characterizing microchannels via SLA, with improvements such as an air-cleaning step facilitating the production of microchannels ranging from 300 to 1000 $\mathrm{m}$. Experimental validation assesses fluid flow speed behavior across channels of varying dimensions, evaluating the impact of channel geometry, surface roughness, and manufacturing parameters. The findings affirm the feasibility and efficacy of SLA in producing microchannels with consistent and predictable fluid flow behavior between 300 to 800 $\mathrm{m}$. This study contributes insights into microfluidic device fabrication techniques and enhances the understanding of fluid dynamics in capillary-driven systems. Overall, it underscores the potential of additive manufacturing, specifically SLA, in offering cost-effective and scalable solutions for microfluidic applications. The validated fluid flow speed behavior in capillary channels suggests new avenues for developing innovative microfluidic devices with improved performance and functionality, marking a significant advancement in the field. Full article

Entity alignment (EA) is a critical task in integrating diverse knowledge graph (KG) data and plays a central role in data-driven AI applications. Traditional EA approaches rely on entity embeddings, but their effectiveness is limited by scarce KG input data and representation learning techniques. Large language models have shown promise, but face challenges such as high hardware requirements, large model sizes and computational inefficiency, which limit their applicability. To overcome these limitations, we propose an entity-alignment model that compares the similarity between entities by capturing both semantic and topological information to enable the alignment of entities with high similarity. First, we analyze descriptive information to quantify semantic similarity, including individual features such as types and attributes. Then, for topological analysis, we introduce four conditions based on graph connectivity and structural patterns to determine subgraph similarity within three hops of the entity’s neighborhood, thereby improving accuracy. Finally, we integrate semantic and topological similarity using a weighted approach that considers dataset features. Our model requires no pre-training and is designed to be compact and generalizable to different datasets. Experimental results on four standard EA datasets validate the effectiveness of our proposed model. Full article

The land use change (LUC) and urbanization caused by human activities have markedly increased the occurrence of landslides, presenting significant challenges in accurately predicting landslide susceptibility despite decades of model advancements. This study, focusing on the Li River Valley (LRV) within the Yongding District, China, employs two common models, namely an analytic hierarchy process–comprehensive index (AHP-CI) model and a logistic regression (LR) model to assess landslide susceptibility (LS). The AHP-CI model is empirically based, with the advantage of being constructible and applicable at various scales without a dataset, though it remains highly subjective. The LR model is a statistical model that requires a training set. The two models represent heuristic and statistical approaches, respectively, to assessing LS. Meanwhile, the basic geological and environmental conditions are considered in the AHP-CI model, while the LR model accounts for the conditions of LUC and urbanization. The results of the multicollinearity diagnostics reflect the rationality of the predisposing factor selection (1.131 < VIF < 4.441). The findings reveal that the AHP-CI model underperforms in LUC and urbanization conditions (AUROC = 0.645, 0.628, and 0.667 for different validation datasets). However, when all the time-varying human activity predisposing factors are considered, the LR model (AUROC = 0.852) performs significantly better under the conditions of solely considering 2010 (AUROC = 0.744) and 2020 (AUROC = 0.810). The CA–Markov model was employed to project the future land use for the short-term (2025), mid-term (2030), and long-term (2040) planning periods. Based on these projections, maps of future LS were created. Importantly, this paper discussed the relationships between landslide management and regional sustainable development under the framework of the UN SDGs, which are relevant to Goal 1, Goal 11, Goal 13, and Goal 15. Finally, this study highlights the importance of integrating strategic land planning, reforestation efforts, and a thorough assessment of human impact predisposing factors with SDG-aligned LS predictions, advocating for a comprehensive, multi-stakeholder strategy to promote sustainable landslide mitigation. Full article

This paper examines the response of the ionosphere to the impact of two moderate geomagnetic storms observed on January 17 and 26–27, 2013, under conditions of strong sudden stratospheric warming. The study uses data from ground-based ionosonde measurements at the Alma-Ata ionospheric station (43.25 N, 76.92 E) combined with optical observation data (The Spectral Airglow Temperature Imager (SATI)). Ionosonde data showed that the geomagnetic storms under consideration do not generate ionospheric storms but demonstrate some unusual types of diurnal foF2 variations with large (up to 60%) deviations in foF2 from median values observed during the night/morning periods on 13–15 and 20–23 January, which do not have any relation to solar or geomagnetic activity. Wave-like disturbances in foF2, h’F, and daily averaged foF2 values with a quasi-period of 5–8 days and peak-to-peak amplitude from about 1 MHz to 2 MHz (from 20% to 40%) and ~40 km are observed during the period 9–28 January, after registration of the occurrence of the major SSW event on 6–7 January. The observed variations in the OH emission rate are found to be quite similar to those observed in the ionospheric parameters that assume a community of processes in the stratosphere/mesosphere/ionosphere system. The study shows that the F region of the ionosphere is influenced by processes in the lower ionosphere, in this case by processes associated with sudden stratospheric warming SSW-2013, which led to modification of the structure of the ionosphere and compensation of processes associated with the development of the ionospheric storms. Full article

In the paper, a new method of phase measurement error suppression in a phase-sensitive optical time domain reflectometer is proposed and experimentally proved. The main causes of phase measurement errors are identified and considered, such as the influence of the recording interferometer instabilities and laser wavelength instability, which can cause inaccuracies in phase unwrapping. The use of a Mach–Zender interferometer made by 3 × 3 fiber couplers is proposed and tested to provide insensitivity to the recording interferometer and laser source instabilities. It is shown that using all three available photodetectors of the interferometer, instead of just one pair, achieves significantly better accuracy in the phase unwrapping. A novel compensation scheme for accurate phase measurements in a phase-sensitive optical time domain reflectometer is proposed, and a comparison of the measurement signals with or without such compensation is shown and discussed. The proposed method, using three photodetectors, allows for very good compensation of the phase measurement errors arising from common-mode noise from the interferometer and laser source, providing a significant improvement in signal detection. In addition, the method allows the tracking of slow temperature changes in the monitored fiber/object, which is not obtainable when using a simple low-pass filter for phase unwrapping error reduction, as is customary in several systems of this kind. Full article

Deployable hind wings of beetles led to a bio-inspired idea to design deployable micro aerial vehicles (MAVs) to meet the requirement of miniaturization. In this paper, a bionic deployable wing (BD-W) model is designed based on the folding mechanism and elliptical wing vein structure of the Protaetia brevitarsis hindwing, and its structural static and aerodynamic characteristics are analyzed by using ANSYS Workbench. Finally, the 3D-printed bionic deployable wing was tested in a wind tunnel and compared with simulation experiments to explore the effects of different incoming velocity, flapping frequency, and angle of attack on its aerodynamic characteristics, which resulted in the optimal combination of the tested parameters, among which, the incoming velocity is 3 m/s, the flapping frequency is 10 Hz, the angle of attack is 15°, and the lift-to-drag ratio of this parameter combination is 4.91. The results provide a theoretical basis and technical reference for the further development of bionic flapping wing for MAV applications. Full article

In this study, we leverage a comprehensive dataset of over 3.8 million bid entries from institutional investors participating in China’s capital market to investigate the determinants of heterogeneous bidding behavior among these investors and the subsequent economic outcomes. We evaluate the sustainability of initial public offering (IPO) performance through three interrelated metrics: post-IPO stock price performance, financial accounting performance, and environmental, social, and governance (ESG) performance. Our analysis reveals a pronounced positive association between the quality of firms’ pre-IPO and the recent reforms to the bookbuilding mechanism in China’s capital market, as well as the level of diversity in institutional investors’ bidding opinions. After accounting for these factors, we focus on the nexus between the diversity of bidding opinions and the sustainability of IPO performance. The empirical evidence indicates that a higher degree of diversity in bidding opinions is inversely related to firms’ post-IPO stock price performance, financial accounting performance, and ESG performance. Further mechanism tests suggest that this diversity leads to a depletion of medium- to long-term share price performance by intensifying market sentiment; impedes the enhancement of financial accounting performance by reducing the capital raised during the IPO; and negatively impacts ESG performance by constraining the firm’s ability to fulfill its corporate social responsibilities. These findings challenge the assumption that diversity of opinion is always beneficial. The insights gained from this research have significant implications for the sustainable growth strategies of listed companies in emerging markets. Full article

The current paper presents helical gearbox defect detection models built from raw vibration signals measured using a triaxial accelerometer. Gear faults, such as localized pitting, localized wear on helical pinion tooth flanks, and low lubricant level, are under observation for three rotating velocities of the actuator and three load levels at the speed reducer output. The emphasis is on the strong connection between the gear faults and the fundamental meshing frequency GMF, its harmonics, and the sidebands found in the vibration spectrum as an effect of the amplitude modulation (AM) and phase modulation (PM). Several sets of features representing powers on selected frequency bands or/and associated peak amplitudes from the vibration spectrum, and also, for comparison, time-domain and frequency-domain statistical feature sets, are proposed as predictors in the defect detection task. The best performing detection model, with a testing accuracy of 99.73%, is based on SVM (Support Vector Machine) with a cubic kernel, and the features used are the band powers associated with six GMF harmonics and two sideband pairs for all three accelerometer axes, regardless of the rotation velocities and the load levels. Full article

In this article we present the first investigation of the stable isotope composition of groundwater in Romania, East-Central Europe, with a focus on the karst areas. Our aim is twofold: (1) to provide a countrywide map with the distribution of stable oxygen and hydrogen isotope ratios in groundwater, and (2) to assess the recharge patterns of karst water. We collected more than 600 water samples from springs and wells across Romania for stable isotope analyses and monitored in detail the stable isotope composition of the waters as they pass through five cave systems. Our data show a spatial distribution of the stable isotope composition of the groundwater with low values in the mountainous area and high values in the surrounding lowlands and the central Transylvanian Depression. However, waters in karst areas induce departures from this distribution, resulting from the fast (hours to days) transfer of waters from high (ponor) to low (spring) altitudes. Water emerging from the karst springs has generally lower δ values than before sinking through the ponors, thus indicating a substantial contribution of winter recharge through diffuse infiltration and seepage. This contribution results in overall dilution of the water entering through ponors, likely resulting in changes in the chemical composition of the water and diluting potential pollutants. Our data call for careful separation between karst and non-karst spring/well waters, as indiscriminate common treatment might lead to erroneous interpretations. Full article

Thin-Plate Spline Generalized Linear Models (TPS-GLMs) are an extension of Semiparametric Generalized Linear Models (SGLMs), because they allow a smoothing spline to be extended to two or more dimensions. This class of models allows modeling a set of data in which it is desired to incorporate the non-linear joint effects of some covariates to explain the variability of a certain variable of interest. In the spatial context, these models are quite useful, since they allow the effects of locations to be included, both in trend and dispersion, using a smooth surface. In this work, we extend the local influence technique for the TPS-GLM model in order to evaluate the sensitivity of the maximum penalized likelihood estimators against small perturbations in the model and data. We fit our model through a joint iterative process based on Fisher Scoring and weighted backfitting algorithms. In addition, we obtained the normal curvature for the case-weight perturbation and response variable additive perturbation schemes, in order to detect influential observations on the model fit. Finally, two data sets from different areas (agronomy and environment) were used to illustrate the methodology proposed here. Full article

A novel method for finding the eigenvalues of a Sturm–Liouville problem is developed. Following the minimalist approach, the problem is transformed to a single first-order differential equation with appropriate boundary conditions. Although the resulting equation is nonlinear, its form allows us to find the general solution by adding a second part to a particular solution. This splitting of the general solution into two parts involves the Schwarzian derivative: hence, the name of the approach. The eigenvalues that correspond to acceptable solutions can be found by requiring the second part to correct the asymptotically diverging behavior of the particular solution. The method can be applied to many different areas of physics, such as the Schrödinger equation in quantum mechanics and stability problems in fluid dynamics. Examples are presented. Full article

The reduction in the rheological parameters and dissolution rate of precursors in geopolymer coatings during early hydration significantly contributes to sagging. This study aims to improve the sag resistance of these coatings by incorporating diatomite filler. Rheological testing was conducted to assess the impact of diatomite and its concentration on the yield stress, plastic viscosity, and thixotropy of the geopolymer coatings. The results indicated that diatomite’s large specific surface area and high reactivity have a significant influence on the rheological parameters and early dissolution rate of precursors. With a diatomite concentration of 1.1%, the coating exhibited a yield stress of 2.749 Pa and a plastic viscosity of 0.921 Pa·s, maintaining stability, homogeneity, and no sagging at a thickness of 600 μm. Furthermore, the highly active SiO₂ in diatomite participates in the secondary hydration reaction of the geopolymer materials led to the formation of substantial C-(A)-S-H gel. This gel enhances internal interconnectivity within the coating, thereby improving its rheological and mechanical properties. Full article

Depression is a chronic, severe, and often life-threatening neurological disorder. It not only causes depression in patients and affects daily life but, in severe cases, may lead to suicidal behavior and have adverse effects on families and society. In recent years, it has been found that sub-anesthetic doses of ketamine have a rapid antidepressant effect on patients with treatment-resistant depression and can significantly reduce the suicidal tendencies of patients with major depressive disorder. Current studies suggest that ketamine may exert antidepressant effects by blocking NMDAR ion channels, but its anesthetic and psychotomimetic side effects limit its application. Here, we report efforts to design and synthesize a novel series of ketamine derivatives of NMDAR antagonists, among which compounds 23 and 24 have improved activity compared with ketamine, introducing a new direction for the development of rapid-acting antidepressant drugs. Full article