AhR ligands from LGG metabolites promote piglet intestinal ILC3 activation and IL-22 secretion to inhibit PEDV infection.

In maintaining organismal homeostasis, gut immunity plays a crucial role. The coordination between the microbiota and the immune system through bidirectional interactions regulates the impact of microorganisms on the host. Our research focused on understanding the relationships between substantial changes in jejunal intestinal flora and metabolites and intestinal immunity during porcine epidemic diarrhea virus (PEDV) infection in piglets. We discovered that Lactobacillus rhamnosus GG (LGG) could effectively prevent PEDV infection in piglets. Further investigation revealed that LGG metabolites interact with type 3 innate lymphoid cells (ILC3s) in the jejunum of piglets through the aryl hydrocarbon receptor (AhR). This interaction promotes the activation of ILC3s and the production of interleukin-22 (IL-22). Subsequently, IL-22 facilitates the proliferation of IPEC-J2 cells and activates the STAT3 signaling pathway, thereby preventing PEDV infection. Moreover, the AhR receptor influences various cell types within organoids, including intestinal stem cells (ISCs), Paneth cells, and enterocytes, to promote their growth and development, suggesting that AhR has a broad impact on intestinal health. In conclusion, our study demonstrated the ability of LGG to modulate intestinal immunity and effectively prevent PEDV infection in piglets. These findings highlight the potential application of LGG as a preventive measure against viral infections in livestock.IMPORTANCEWe observed high expression of the AhR receptor on pig and human ILC3s, although its expression was negligible in mouse ILC3s. ILC3s are closely related to the gut microbiota, particularly the secretion of IL-22 stimulated by microbial signals, which plays a crucial regulatory role in intestinal immunity. In our study, we found that metabolites produced by beneficial gut bacteria interact with ILC3s through AhR, thereby maintaining intestinal immune homeostasis in pigs. Moreover, LGG feeding can enhance the activation of ILC3s and promote IL-22 secretion in the intestines of piglets, ultimately preventing PEDV infection.

PKA Activity-Driven Modulation of Bidirectional Long-Distance transport of Lysosomal vesicles During Synapse Maintenance.

The bidirectional long-distance transport of organelles is crucial for cell body-synapse communication. However, the mechanisms by which this transport is modulated for synapse formation, maintenance, and plasticity are not fully understood. Here, we demonstrate through quantitative analyses that maintaining sensory neuron-motor neuron synapses in the Aplysia gill-siphon withdrawal reflex is linked to a sustained reduction in the retrograde transport of lysosomal vesicles in sensory neurons. Interestingly, while mitochondrial transport in the anterograde direction increases within 12 hours of synapse formation, the reduction in lysosomal vesicle retrograde transport appears three days after synapse formation. Moreover, we find that formation of new synapses during learning induced by neuromodulatory neurotransmitter serotonin further reduces lysosomal vesicle transport within 24 hours, whereas mitochondrial transport increases in the anterograde direction within one hour of exposure. Pharmacological inhibition of several signaling pathways pinpoints PKA as a key regulator of retrograde transport of lysosomal vesicles during synapse maintenance. These results demonstrate that synapse formation leads to organelle-specific and direction specific enduring changes in long-distance transport, offering insights into the mechanisms underlying synapse maintenance and plasticity.

Accelerated 3D metabolite T1 mapping of the brain using variable-flip-angle SPICE.

PURPOSE: To develop a practical method to enable 3D T1 mapping of brain metabolites. THEORY AND METHODS: Due to the high dimensionality of the imaging problem underlying metabolite T1 mapping, measurement of metabolite T1 values has been currently limited to a single voxel or slice. This work achieved 3D metabolite T1 mapping by leveraging a recent ultrafast MRSI technique called SPICE (spectroscopic imaging by exploiting spatiospectral correlation). The Ernst-angle FID MRSI data acquisition used in SPICE was extended to variable flip angles, with variable-density sparse sampling for efficient encoding of metabolite T1 information. In data processing, a novel generalized series model was used to remove water and subcutaneous lipid signals; a low-rank tensor model with prelearned subspaces was used to reconstruct the variable-flip-angle metabolite signals jointly from the noisy data. RESULTS: The proposed method was evaluated using both phantom and healthy subject data. Phantom experimental results demonstrated that high-quality 3D metabolite T1 maps could be obtained and used for correction of T1 saturation effects. In vivo experimental results showed metabolite T1 maps with a large spatial coverage of 240 × 240 × 72 mm3 and good reproducibility coefficients (< 11%) in a 14.5-min scan. The metabolite T1 times obtained ranged from 0.99 to 1.44 s in gray matter and from 1.00 to 1.35 s in white matter. CONCLUSION: We successfully demonstrated the feasibility of 3D metabolite T1 mapping within a clinically acceptable scan time. The proposed method may prove useful for both T1 mapping of brain metabolites and correcting the T1-weighting effects in quantitative metabolic imaging.

Mapping intracellular NAD content in entire human brain using phosphorus-31 MR spectroscopic imaging at 7 Tesla.

Introduction: Nicotinamide adenine dinucleotide (NAD) is a crucial molecule in cellular metabolism and signaling. Mapping intracellular NAD content of human brain has long been of interest. However, the sub-millimolar level of cerebral NAD concentration poses significant challenges for in vivo measurement and imaging. Methods: In this study, we demonstrated the feasibility of non-invasively mapping NAD contents in entire human brain by employing a phosphorus-31 magnetic resonance spectroscopic imaging (31P-MRSI)-based NAD assay at ultrahigh field (7 Tesla), in combination with a probabilistic subspace-based processing method. Results: The processing method achieved about a 10-fold reduction in noise over raw measurements, resulting in remarkably reduced estimation errors of NAD. Quantified NAD levels, observed at approximately 0.4 mM, exhibited good reproducibility within repeated scans on the same subject and good consistency across subjects in group data (2.3 cc nominal resolution). One set of higher-resolution data (1.0 cc nominal resolution) unveiled potential for assessing tissue metabolic heterogeneity, showing similar NAD distributions in white and gray matter. Preliminary analysis of age dependence suggested that the NAD level decreases with age. Discussion: These results illustrate favorable outcomes of our first attempt to use ultrahigh field 31P-MRSI and advanced processing techniques to generate a whole-brain map of low-concentration intracellular NAD content in the human brain.

Single-neuron analysis of aging-associated changes in learning reveals impairments in transcriptional plasticity.

The molecular mechanisms underlying age-related declines in learning and long-term memory are still not fully understood. To address this gap, our study focused on investigating the transcriptional landscape of a singularly identified motor neuron L7 in Aplysia, which is pivotal in a specific type of nonassociative learning known as sensitization of the siphon-withdraw reflex. Employing total RNAseq analysis on a single isolated L7 motor neuron after short-term or long-term sensitization (LTS) training of Aplysia at 8, 10, and 12 months (representing mature, late mature, and senescent stages), we uncovered aberrant changes in transcriptional plasticity during the aging process. Our findings specifically highlight changes in the expression of messenger RNAs (mRNAs) that encode transcription factors, translation regulators, RNA methylation participants, and contributors to cytoskeletal rearrangements during learning and long noncoding RNAs (lncRNAs). Furthermore, our comparative gene expression analysis identified distinct transcriptional alterations in two other neurons, namely the motor neuron L11 and the giant cholinergic neuron R2, whose roles in LTS are not yet fully elucidated. Taken together, our analyses underscore cell type-specific impairments in the expression of key components related to learning and memory within the transcriptome as organisms age, shedding light on the complex molecular mechanisms driving cognitive decline during aging.

Evaluating annual soil carbon emissions under biochar-added farmland subjecting from freeze-thaw cycle.

Straw biochar is a commonly recognized agricultural amendment that can improve soil quality and reduce carbon emissions while sequestering soil carbon. However, the mechanisms underlying biochar's effects on annual soil carbon emissions in seasonally frozen soil areas and intrinsic drivers have not been clarified. Here, a 2-y field experiment was conducted to investigate the effects of different biochar dosages (0, 15, and 30, t ha-1; B0 (CK), B15, and B30, respectively) on carbon emissions (CO2 and CH4) microbial colony count, and soil-environment factors. The study period was the full annual cycle, including the freeze-thaw period (FTP) and the crop growth period (CP). Structural equation modeling (SEM) was developed to reveal the key drivers and potential mechanisms of biochar on carbon emissions. Biochar application reduced soil carbon emissions, with the reduction rate positively related to the biochar application rate (B30 best). During FTP, the reduction rate was 11.5% for CO2 and 48.2% for CH4. During CP, the reduction rate was 17.9% for CO2 and 34.5% for CH4. Overall, compared with CK, B30 treatment had a significant effect on reducing total soil carbon emissions (P < 0.05), with an average decrease of 16.7% during the two-year test period. The study also showed that for soils with continuous annual cycles (FTP and CP), carbon emissions were best observed from 10:00-13:00. After two years of freeze-thaw cycling, biochar continued to improve soil physical and chemical properties, thereby increasing soil microbial colony count. Compared with B0, the B30 treatment significantly increased the total colony count by 74.3% and 263.8% during FTP and CP (P < 0.05). Structural equation modeling (SEM) indicated that, with or without biochar application, the soil physicochemical properties directly or indirectly affected soil CO2 and CH4 emission fluxes through microbial colony count. The total effects of biochar application on CO2 emission fluxes were 0.50 (P < 0.05) and 0.64 (P < 0.01), respectively, but there was no significant effect on CH4 emission fluxes (P > 0.05). Among them, soil water content (SWC), soil temperature (ST) and soil organic carbon (SOC) were the main environmental determinants of CO2 emission fluxes during the FTP and CP. The total effects were 0.57, 0.65, and 0.53, respectively. For CH4, SWC, soil salinity (SS) and actinomycete colony count were the main environmental factors affecting its emission. The total effects were 0.50, 0.45, 0.44, respectively. For freeze-thaw alternating soils, the application of biochar is a feasible option for addressing climate change through soil carbon sequestration and greenhouse gas emissions mitigation. Soil water-heat-salt-fertilization and microbial communities are important for soil carbon emissions as the reaction matrix and main participants of soil carbon and nitrogen biochemical transformation.

Correction: Steam turbine power prediction based on encode-decoder framework guided by the condenser vacuum degree.

[This corrects the article DOI: 10.1371/journal.pone.0275998.].

A hybrid model for enhanced forecasting of PM2.5 spatiotemporal concentrations with high resolution and accuracy.

Forecasting concentrations of PM2.5 is important due to its known impacts on public health and environment. However, PM2.5 concentrations can vary significantly over short distances and time, which can be influenced by local emissions and short-term weather patterns. This spatiotemporal variability makes accurate PM2.5 forecasting an inherently complex and challenging task. This study presented novel methodologies for short-term PM2.5 concentration forecast by combining the atmospheric chemistry transport model Community Multiscale Air Quality Modeling System (CMAQ) with data-driven machine learning methods, namely long short-term memory (LSTM) and random forest (RF) models. The combined model system forecast PM2.5 with 1 h, 1km × 1 km spatiotemporal resolution. The LSTM system forecast time-dependent PM2.5 concentrations at observation sites with a maximum root mean square error (RMSE) of 3.66 µg/m3 for 1-hr forecast and 23.75 µg/m3 for 72-hr forecast, leveraging results obtained from the atmospheric transport model with RMSE of 45.81 µg/m3. Wavelet transform in the LSTM system allowed learning and prediction of PM2.5 concentrations at different frequencies, capturing temporal variability of PM2.5 at various time scales. The RF model predicted distributions of PM2.5 concentrations by learning LSTM results and integrating crucial features such as CMAQ results, meteorological and topographical information. The feature significance of CMAQ results was the highest among the input features in RF models. Overall, the hybrid model could help with managing and mitigating the adverse effects of air pollution by enabling informed decision-making at the individual, community and policy levels.

BINOL-Based Chiral Macrocycles and Cages.

Chirality, a fundamental principle in chemistry, biology, and medicine, is prevalent in nature and in organisms. Chiral molecules, such as DNA, RNA, and proteins, are crucial in biomolecular synthesis, as well as in the development of functional materials. Among these, 1,1'-binaphthyl-2,2'-diol (BINOL) stands out for its stable chiral configuration, versatile functionality, and commercial availability. BINOL is widely employed in asymmetric catalysis and chiral materials. This review mainly focuses on recent research over the past five years concerning the use of BINOL derivatives for constructing chiral macrocycles and cages. Their contributions to chiral luminescence, enantiomeric separation, transmembrane transport, and asymmetric catalysis were examined.

Stable anode/separator interface enabled by graft modification of polypropylene separator via electron beam irradiation technique toward high-performance sodium metal batteries.

Sodium metal batteries (SMBs) are considered as strong alternatives to lithium-ion batteries (LIBs), due to the inherent merits of sodium metal anodes (SMAs) including low redox potential (-2.71 V vs. SHE), high theoretical capacity (1166 mAh g-1), and abundant resources. However, the uncontrollable Na dendrite growth has significantly impeded the practical deployment of SMBs. Separator modification has emerged as an effective strategy for substantially enhancing the performance of SMAs. Herein, for the first time, we present the successful grafting polyacrylic acid (PAA) onto polypropylene (PP) separators (denoted as PP-g-PAA) using highly efficient electron beam (EB) irradiation to improve the cyclability of SMAs. The polar carboxyl groups of PAA can facilitate the electrolyte wetting and provide ample mechanical strength to resist dendrite penetration. Consequently, the regulation of Na+ ion flux enables uniform Na+ deposition with dendrite-free morphology, facilitated by the favorable anode/separator interface. The PP-g-PAA separator significantly enhances the cyclability of fabricated cells. Notably, the lifespan of Na||Na symmetric cells can be extended up to 5519 h at 1 mA cm-2 and 1 mAh cm-2. The stable design of the anode/separator interface achieved through polyolefin separator modification presented in this study holds promise for the further advancement of next-generation advanced battery systems.

Structural modification and biomechanical analysis of lumbar disc prosthesis: A finite element study.

BACKGROUND: Most ball-in-socket artificial lumbar disc implanted in the spine result in increased hypermobility of the operative level and overloading of the facet joint. METHODS: A finite element model was established and validated for the lumbar spine (L1-L5). The structure of the Mobidisc prosthesis was modified, resulting in the development of two new intervertebral disc prostheses, Movcore and Mcopro. The prostheses were implanted into the L3/L4 level to simulate total disc replacement, and the biomechanical properties of the lumbar spine model were analyzed after the operation. FINDINGS: Following the implantation of the prostheses, the mobility of operative level, peak stress of lumbar spine models, and peak stress of facet joint increased. The performance of mobility was found to be more similar between Movcore and Mobidisc. The mobility and facet joint peak stress of the Mcopro model decreased progressively with an increase in the Young's modulus of the artificial annulus during flexion, extension, and lateral bending. Among all the models, the Mcopro50 model had the mobility closest to the intact model. It showed a 3% decrease in flexion, equal range of motion in extension, a 9% increase in left lateral bending, a 7% increase in right lateral bending, and a 3% decrease in axial rotation. INTERPRETATION: The feasibility of the new intervertebral disc prostheses, Movcore and Mcopro, has been established. The Mcopro prosthesis, which features an artificial annular structure, offers significant advantages in terms of reduced mobility of the operative level and peak stress of facet joint.

Catalytic pyrolysis and in situ carbonization of walnut shells: poly-generation and enhanced electrochemical performance of carbons.

In this study, walnut shell (WS) was used as feedstock, incorporating lithium carbonate (LC), sodium carbonate (SC), potassium carbonate (PC), and potassium hydroxide (PH) as pyrolysis catalysts and carbonization activators. A one-step method that allows catalytic pyrolysis and carbonization to be carried out consecutively under their respective optimal conditions is employed, enabling the concurrent production of high-quality pyrolysis oil, pyrolysis gas, and carbon materials from biomass conversion. The effects of LC, SC, PC, and PH on the yield and properties of products derived from WS pyrolysis as well as on the properties and performance of the resulting carbon materials were examined. The results indicated that the addition of LC, SC, PC, and PH enhanced the secondary cracking of tar, leading to increased solid and gas yields from WS. Additionally, it increased the production of phenolic compounds in bio-oil and H2 in syngas, concurrently yielding a walnut shell-based carbon material exhibiting excellent electrochemical performance. Specifically, when PC was used as an additive, the phenolic content in the pyrolysis oil increased by 27.64% compared to that without PC, reaching 74.9%, but the content of ketones, acids, aldehydes, and amines decreased. The hydrogen content increased from 2.5% (without the addition of PC) to 12.75%. The resulting carbon (WSC-PC) displayed a specific surface area of 598.6 m2 g-1 and achieved a specific capacitance of 245.18 F g-1 at a current density of 0.5 A g-1. Even after 5000 charge and discharge cycles at a current density of 2 A g-1, the capacitance retention rate remained at 98.16%. This method effectively enhances the quality of the biomass pyrolysis oil, gas, and char, contributing to the efficient and clean utilization of biomass in industrial applications.

Bis-tridentate Iridium(III) Complex with the N-Heterocyclic Carbene Ligand as a Novel Efficient Electrochemiluminescence Emitter for the Sandwich Immunoassay of the HHV-6A Virus.

Human herpesvirus type 6A (HHV-6A) can cause a series of immune and neurological diseases, and the establishment of a sensitive biosensor for the rapid detection of HHV-6A is of great significance for public health and safety. Herein, a bis-tridentate iridium complex (BisLT-Ir-NHC) comprising the N-heterocyclic carbene (NHC) ligand as a novel kind of efficient ECL luminophore has been unprecedently reported. Based on its excellent ECL properties, a new sensitive ECL-based sandwich immunosensor to detect the HHV-6A virus was successfully constructed by encapsulating BisLT-Ir-NHC into silica nanoparticles and embellishing ECL sensing interface with MXene@Au-CS. Notably, the immunosensor illustrated in this work not only had a wide linear range of 102 to 107 cps/µL but also showed outstanding recoveries (98.33-105.11%) in real human serum with an RSD of 0.85-3.56%. Undoubtedly, these results demonstrated the significant potential of the bis-tridentate iridium(III) complex containing an NHC ligand in developing ECL-based sensitive analytical methods for virus detection and exploring novel kinds of efficient iridium-based ECL luminophores in the future.

The Impact of College Students' Academic Stress on Student Satisfaction from a Typological Perspective: A Latent Profile Analysis Based on Academic Self-Efficacy and Positive Coping Strategies for Stress.

This investigation employs Latent Profile Analysis (LPA) to analyze data from 1298 Chinese university students, aiming to clarify the mechanisms through which individual psychological resources, primarily academic self-efficacy and positive coping strategies, affect student satisfaction in the context of academic stress. Four distinct profiles emerged based on levels of academic self-efficacy and positive coping strategies: Low-Spirited, General Copers, Capable but Passive, and Optimistic and Confident. These profiles demonstrate significant variances in the sources of academic stress, student engagement, and student satisfaction, with a ranking order from most to least satisfied as follows: Optimistic and Confident, Capable but Passive, General Copers, and Low-spirited. While academic stress uniformly augments engagement across all profiles, its effect on student satisfaction diverges-negatively for Low-spirited and General Copers, and positively for Capable but Passive and Optimistic and Confident. The analysis reveals varying levels of academic stress-tolerance among profiles, highlighting the critical role of academic self-efficacy and indicating a possible nonlinear relationship between student engagement and satisfaction. These findings enhance our comprehension of student satisfaction's intricate dynamics and suggest strategies to alleviate academic stress and improve psychological well-being.

Influence of academic involution atmosphere on college students' stress response: the chain mediating effect of relative deprivation and academic involution.

BACKGROUND: In recent years, the phenomenon of academic involution atmosphere among college students has gradually attracted the focus of education and social circles. Thus, this study targets college students as the research object and constructs a hypothetical model to explore the relationship between academic involution atmosphere and college students' stress response, as well as the mediating role of relative deprivation and academic involution. METHODS: A survey was conducted on 1090 college students using the Academic Involution Atmosphere Scale, Relative Deprivation Scale, Personal Academic Involution Scale, and Stress Response Scale. RESULTS: The results show that: (1) Academic involution atmosphere, relative deprivation, and academic involution are significantly and positively correlated with stress response; (2) Academic involution atmosphere not only directly predicts college students' stress response, but also indirectly predicts them through relative deprivation and academic involution, respectively; (3) Relative deprivation and academic involution have a chain mediating effect between academic involution atmosphere and stress response. CONCLUSIONS: The findings of this study reveal the influence of academic involution atmosphere on college students' stress response and the mechanism, providing beneficial insights for reducing college students' stress response and maintaining their psychological well-being.

Bimetal doped Cu-Fe-ZIF-8/g-C3N4 nanocomposites for the adsorption of tetracycline hydrochloride from water.

Bimetal doped Cu-Fe-zeolitic imidazole framework-8 (ZIF-8)/graphitic carbon nitride (GCN) (Cu-Fe-ZIF-8/GCN) nanocomposites were prepared via one-pot and ion-exchange methods. The main influencing factors, such as adsorbent concentration, TC concentration, initial pH, and coexisting ions, were evaluated in detail. Due to the suitable pore structures and the presence of multiple interactions on the surface, the nanocomposite showed a high adsorption capacity up to 932 mg g-1 for tetracycline hydrochloride (TC), outperforming ZIF-8 by 4.8 times. The adsorption kinetics and adsorption isotherm were depicted in good detail using pseudo-second-order kinetic and Langmuir models, respectively. Thermodynamic calculation revealed that the adsorption of the nanocomposite under experimental conditions was a spontaneous heat absorption process, and was primarily driven by chemisorption. After four cycles of use, the nanocomposite retained 87.2% of its initial adsorption capacity, confirming its high reusability and broad application prospects in removing tetracycline-type pollutants from wastewater.

CRISPR-Cas12a based target recognition initiated duplex-specific nuclease enhanced fluorescence and colorimetric analysis of cell-free DNA (cfDNA).

The significant role of cell-free DNA (cfDNA) for disease diagnosis, including cancer, has garnered a lot of attention. The challenges of creating target-specific primers and the possibility of false-positive signals make amplification-based detection methods problematic. Fluorescent biosensors based on CRISPR-Cas have been widely established, however they still require an amplification step before they can be used for detection. To detect cfDNA, researchers have created a CRISPR-Cas12a-based nucleic acid amplification-free fluorescent biosensor that uses a combination of fluorescence and colorimetric signaling improved by duplex-specific nuclease (DSN). DSN-assisted signal recycling is initiated in H1@MBs when the target cfDNA activates the CRISPR-Cas12a complex, leading to the degradation of single-strand DNA (ssDNA) sequences. This method has an extremely high detection limit for the BRCA-1 breast cancer gene. In addition to measuring viral DNA in a field-deployable and point-of-care testing (POCT) platform, this fast and highly selective sensor can be used to evaluate additional nucleic acid biomarkers.

Ultrasensitive Electrochemiluminescence Biosensor to Detect Ampicillin Resistance Gene (ARGAMP) Based on a Novel Near-Infrared Ruthenium Carbene Complex/TPrA/PEI Ternary ECL System.

The establishment of rapid target identification and analysis methods for antibiotic resistance genes (ARGs) is urgently needed. In this study, we unprecedently designed a target-catalyzed hairpin assembly (CHA) electrochemiluminescent (ECL) biosensor for the ultrasensitive detection of ampicillin resistance genes (ARGAMP) based on a novel, efficient near-infrared ruthenium carbene complex/TPrA/PEI ternary ECL system with low oxidation potential. The ternary NIR-ECL system illustrated in this work displayed double ECL intensity in comparison with their corresponding traditional binary ECL system. The as-prepared ECL biosensor illustrated in this work demonstrates highly selective and sensitive determination of ARGAMP from 1 fM to 1 nM and a low detection limit of 0.23 fM. Importantly, it also exhibits good accuracy and stabilities to identify ARGAMP in plasmid and bacterial genome DNA, which demonstrates its excellent reliability and great potential in detecting ARGAMP in real environmental samples.

A model for the diagnosis of anxiety in patients with epilepsy based on phase locking value and Lempel-Ziv complexity features of the electroencephalogram.

OBJECTIVE: Anxiety disorders (AD) are critical factors that significantly (about one-fifth) impact the quality of life (QoL) in patients with epilepsy (PWE). Objective diagnostic methods have contributed to the identification of PWE susceptible to AD. This study aimed to identify AD in PWE by constructing a diagnostic model based on the phase locking value (PLV) and Lempel-Ziv Complexity (LZC) features of the electroencephalogram (EEG). METHODS: EEG data from 131 patients with epilepsy (PWE) were enrolled in this study. Patients were divided into two groups, anxiety disorder (AD, n = 61) and non-anxiety disorder (NAD, n = 70), according to the Hamilton Rating Scale for Anxiety (HAM-A). Support vector machine (SVM) and K-Nearest-Neighbor(KNN) algorithms were used to construct three models - the PLVEEG, LZCEEG, and PLVEEG + LZCEEG feature models. Finally, the area under the receiver operating characteristic curve (AUC) and statistical analyses were performed to evaluate the model performance. RESULTS: The efficiency of the KNN-based PLCEEG + LZCEEG feature model was the best, and the accuracy, precision, recall, F1-score, and AUC of the model after five-fold cross-validations scores were 87.89 %, 82.27 %, 98.33 %, 88.95 %, and 0.89, respectively. When the model efficiency was optimal, 29 EEG features were suggested. Further analysis of these features indicated 22 EEG features that were significantly different between the two groups, including 50 % features of the alpha (α)-band. CONCLUSIONS: The PLVEEG + LZCEEG model features can identify AD in PWE. The PLVEEG and LZCEEG characteristics of the α-band may further be explored as potential biomarkers for AD in PWE.