Generalized sleep decoding with basal ganglia signals in multiple movement disorders.

Sleep disturbances profoundly affect the quality of life in individuals with neurological disorders. Closed-loop deep brain stimulation (DBS) holds promise for alleviating sleep symptoms, however, this technique necessitates automated sleep stage decoding from intracranial signals. We leveraged overnight data from 121 patients with movement disorders (Parkinson's disease, Essential Tremor, Dystonia, Essential Tremor, Huntington's disease, and Tourette's syndrome) in whom synchronized polysomnograms and basal ganglia local field potentials were recorded, to develop a generalized, multi-class, sleep specific decoder - BGOOSE. This generalized model achieved 85% average accuracy across patients and across disease conditions, even in the presence of recordings from different basal ganglia targets. Furthermore, we also investigated the role of electrocorticography on decoding performances and proposed an optimal decoding map, which was shown to facilitate channel selection for optimal model performances. BGOOSE emerges as a powerful tool for generalized sleep decoding, offering exciting potentials for the precision stimulation delivery of DBS and better management of sleep disturbances in movement disorders.

Unsupervised multimodal modeling of cognitive and brain health trajectories for early dementia prediction.

Predicting the course of neurodegenerative disorders early has potential to greatly improve clinical management and patient outcomes. A key challenge for early prediction in real-world clinical settings is the lack of labeled data (i.e., clinical diagnosis). In contrast to supervised classification approaches that require labeled data, we propose an unsupervised multimodal trajectory modeling (MTM) approach based on a mixture of state space models that captures changes in longitudinal data (i.e., trajectories) and stratifies individuals without using clinical diagnosis for model training. MTM learns the relationship between states comprising expensive, invasive biomarkers (ß-amyloid, grey matter density) and readily obtainable cognitive observations. MTM training on trajectories stratifies individuals into clinically meaningful clusters more reliably than MTM training on baseline data alone and is robust to missing data (i.e., cognitive data alone or single assessments). Extracting an individualized cognitive health index (i.e., MTM-derived cluster membership index) allows us to predict progression to AD more precisely than standard clinical assessments (i.e., cognitive tests or MRI scans alone). Importantly, MTM generalizes successfully from research cohort to real-world clinical data from memory clinic patients with missing data, enhancing the clinical utility of our approach. Thus, our multimodal trajectory modeling approach provides a cost-effective and non-invasive tool for early dementia prediction without labeled data (i.e., clinical diagnosis) with strong potential for translation to clinical practice.

Thalassotalea psychrophila sp. nov., Thalassotalea nanhaiensis sp. nov. and Thalassotalea fonticola sp. nov., three psychrophilic bacteria isolated from deep-sea sediment.

Three psychrophilic bacteria, designated as strains SQ149T, SQ345T, and S1-1T, were isolated from deep-sea sediment from the South China Sea. All three strains were the most closely related to Thalassotalea atypica RZG4-3-1T based on the 16S rRNA gene sequence analysis (similarity ranged from 96.45 to 96.67 %). Phylogenetic analysis based on the 16S rRNA gene and core-genome sequences showed that three strains formed a cluster within the genus Thalassotalea. The average amino acid identity, average nucleotide identity, and digital DNA-DNA hybridization values among the three strains and closest Thalassotalea species were far below the cut-off value recommended for delineating species, indicating they each represented a novel species. All three strains were Gram-stain-negative, rod-shaped, and contained summed feature 3 (C16 : 1 ω7c and/or C16 : 1 ω6c) as the predominant fatty acid, Q-8 as the major respiratory quinone, and phosphatidylethanolamine and phosphatidylglycerol as predominant polar lipids. Based on the genomic, phylogenetic, and phenotypic characterizations, each strain is considered to represent a novel species within the genus Thalassotalea, for which the names Thalassotalea psychrophila sp. nov. (type strain SQ149T=MCCC 1K04231T=JCM 33807T), Thalassotalea nanhaiensis sp. nov. (type strain SQ345T=MCCC 1K04232T=JCM 33808T), and Thalassotalea fonticola sp. nov. (type strain S1-1T=MCCC 1K06879T=JCM 34824T) are proposed.

Surface-Integrating Oxygen Vacancy and CuxO Nanodots Enabling Synergistic Electric Field and Dual Catalytic Sites Boosting CO2 Photoreduction.

High carrier separation efficiency and rapid surface catalytic reaction are crucial for enhancing catalytic CO2 photoreduction reaction. Herein, integrated surface decoration strategy with oxygen vacancies (Ov) and anchoring CuxO (1 < x < 2) nanodots below 10 nm is realized on Bi2MoO6 for promoting CO2 photoreduction performance. The charge interaction between Ov and anchored CuxO enables the formation of enhanced internal electric field, which provides a strong driving force for accelerating the separation of photocharge carriers on the surface of Bi2MoO6 (ηsurf ≈71%). They can also cooperatively reduce the surface work function of Bi2MoO6, facilitating the migration of carrier to the surface. Meanwhile, surface-integrated Ov and CuxO nanodots allowing dual catalytic sites strengthens the adsorption and activation CO2 into *CO2 over Bi2MoO6, considerably boosting the progression of CO2 conversion process. In the absence of co-catalyst or sacrificial agent, Bi2MoO6 with Ov and CuxO nanodots achieves a photocatalytic CO generation rate of 12.75 µmol g-1 h-1, a remarkable increase of over ≈15 times that of the original counterpart. This work provides a new idea for governing charge movement behaviors and catalytic reaction thermodynamics on the basis of synergistic improvement of electric field and active sites by coupling of the internal defects and external species.

Salivary microbiome is associated with the response to chemoradiotherapy in initially inoperable patients with esophageal squamous cell carcinoma.

Background: The salivary microbiome may interact with chemoradiotherapy through dynamic changes in microbial composition and systemic immunity. We aimed to explore the association between the salivary microbiome and response to chemoradiotherapy in initially inoperable patients with local advanced esophageal squamous cell carcinoma (LAESCC). Methods: Salivary and peripheral blood samples were collected before and after chemoradiotherapy. The microbiome and metabolic pathways were analyzed by 16S ribosomal RNA sequencing and liquid chromatography tandem mass spectrometry/Mass spectrometry analyses. Results: The salivary microbiome exhibited characteristic variations between patients and healthy controls. A significant correlation was found between Prevotella_salivae, Saccharibacteria_TM7_G3_bacterium_HMT_351, and Veillonellaceae_G1_bacterium_HMT_129 and pathological complete response (pCR) in initially inoperable patients who underwent surgery. The PICRUSt suggested that immune diseases and cell motility were different in tumor compared to normal groups. KEGG enrichment analysis showed enriched lipid metabolism, signal transduction, and membrane transport in the tumor group. CD3+CD8 T cells, IL6, IL10, and IFNγ exhibited an increasing trend during the treatment process of chemoradiotherapy. Conclusions: Our study demonstrated that variations in specific saliva taxa associated with host immunomodulatory cells and cytokines could be promising for early efficacy prediction of chemoradiotherapy in initially inoperable patients with LAESCC.

Microstructure and interaction in aluminum hydrides@polydopamine composites and interfacial improvement with GAP adhesive.

The reduction of interfacial interaction and the deterioration of processing properties of aluminum hydrides (AlH3) is the main challenges preventing its practical application. Here, a simple and effective core-shell structure aluminum hydrides@polydopamine (AlH3@PDA) complex was constructed through in-situ polymerization. The evolution of element states on the surface of AlH3 conducted by X-ray photoelectron spectroscopy indicated the successful introduction of PDA to form the core@shell structure, the thickness of the PDA coated layer increased with the increasing PDA dosage from 0.1 to 1.6% in mass fraction, and the maximum of thickness is 50 nm in TEM testing. Py GC/MS results proved that the increase of dopamine concentration leads to higher proportions of self-assemble units, whereas lower dopamine concentrations favor higher levels of chemical bonded components. Regarding whether PDA is a covalent polymer or a noncovalent aggregate of some species, the formation of intermediates, such as dopaminechrome and 5,6-dihydroxyindole played an important role to coordination interaction with AlH3 in FTIR, Raman, and UV-Vis spectra testing. Compared with pure AlH3, the formation of organic PDA coating improved AlH3 heat resistance. The adhesion work with GAP adhesive was also improved from 107.02 J/m2 of pure AlH3 to 111.13 mJ/m2 of AlH3@PDA-5 complex. This paper provides well support for further practical application of AlH3 in solid propellants.

Differences in Albizia odoratissima genetic diversity between Hainan Island and mainland populations in China.

Background: This study aimed at exploring unique population genetic characteristics of Albizia odoratissima (Linn. f) Benth on Hainan Island to provide a scientific basis for its rational utilization and protection. Methods: It analyzed the genetic diversity and structure of 280 individuals from 10 subpopulations of A. odoratissima from Hainan Island and Baise City using 16 expression sequence markers - simple sequence repeat markers. Results: The genetic diversity of Hainan population (I = 0.7290, He = 0.4483) was lower than that of the Baise population (I = 0.8722, He = 0.5121). Compared with the Baise population (Nm = 2.0709, FST = 0.1077), the Hainan Island population (Nm = 1.7519, FST = 0.1249) exhibited lower gene flow and higher degree of genetic differentiation. Molecular variance and genetic differentiation analyses showed that the main variation originated from individuals within the subpopulation. There were significant differences in the genetic structure between Hainan and Baise populations. It grouped according to geographical distance, consistent with the Mantel test results (R2 = 0.77, p = 0.001). In conclusion, the genetic diversity of the island A. odoratissima population was lower than that distributed on land, the two populations exhibited obvious genetic structure differences. Both the degrees of inbreeding and genetic differentiation were higher in the island population than in the land population.

Shear Flow-Assembled Janus Membrane with Bifunctional Osteogenic and Antibacterial Effects for Guided Bone Regeneration.

Guided bone regeneration (GBR) membranes that reside at the interface between the bone and soft tissues for bone repair attract increasing attention, but currently developed GBR membranes suffer from relatively poor osteogenic and antibacterial effects as well as limited mechanical property and biodegradability. We present here the design and fabrication of a bifunctional Janus GBR membrane based on a shear flow-driven layer by a layer self-assembly approach. The Janus GBR membrane comprises a calcium phosphate-collagen/polyethylene glycol (CaP@COL/PEG) layer and a chitosan/poly(acrylic acid) (CHI/PAA) layer on different sides of a collagen membrane to form a sandwich structure. The membrane exhibits good mechanical stability and tailored biodegradability. It is found that the CaP@COL/PEG layer and CHI/PAA layer contribute to the osteogenic differentiation and antibacterial function, respectively. In comparison with the control group, the Janus GBR membrane displays a 2.52-time and 1.84-time enhancement in respective volume and density of newly generated bone. The greatly improved bone repair ability of the Janus GBR membrane is further confirmed through histological analysis, and it has great potential for practical applications in bone tissue engineering.

Interaction Between Hypoxia-Inducible Factor 1-alpha Gene Polymorphism and Helicobacter pylori Infection on Gastric Cancer in a Chinese Tibetan Population.

To investigate the impact of four single nucleotide polymorphisms (SNPs) of the HIF1α gene and its interaction with Helicobacter pylori (H. pylori) infection on susceptibility to gastric cancer (GC).Logistic regression was used to test the relationship between four SNPs of HIF1α gene and the susceptibility of GC. A generalized multifactor dimensionality reduction (GMDR) model was used to assess the HIF1α gene-H. pylori infection interaction.Logistic regression analysis indicated that both the rs11549465-CT genotype and the T allele were associated with an increased risk of GC, adjusted OR (95% CI) were 1.63 (1.09-2.20) (CT vs. CC) and 1.70 (1.13-2.36) (T vs. C), respectively. We also found that both the rs11549467-A allele and rs11549467-GA genotype were associated with an increased risk of GC, and adjusted OR (95% CI) were 2.21 (1.61-2.86) (GA vs. GG), 2.13 (1.65-2.65) (A vs. G), respectively. However, no statistically significant impact of rs2057482 or rs1957757 on risk of GC was found. The GMDR model indicated a statistically significant two-dimensional model combination (including rs11549467 and H. pylori infection). The selected model had testing balanced accuracy of 0.60 and the best cross-validation consistencies of 10/10 (p = 0.0107). Compared with H. pylori infection negative participants with rs11549467-GG genotype, H. pylori positive participants with the rs11549467-GA genotype had the highest GC risk, the OR (95% CI) was 3.04 (1.98-4.12).The rs11549467-A allele and rs11549467-GA genotype was associated with increased GC risk. Additionally, the gene-environment interaction between HIF-1α-rs11549467 and H. pylori infection was also correlated with an increased risk of GC.

A meta-analysis of antibiotic residues in the Beibu Gulf.

Antibiotic residue stands as a significant ongoing environmental issue, with aquaculture being a major source of annual antibiotic discharge into the ocean. Nevertheless, there is still an incomplete evaluation of antibiotic residues in the Beibu Gulf, an area encompassed by two prominent aquaculture nations, China and Vietnam. The present systematic review and meta-analysis was conducted to examine the presence antibiotic residues in the Beibu Gulf based on published studies. Data were obtained through eight databases up to December 19th, 2023, and were updated on April 15th, 2024. The pooled concentration of antibiotic residues in seawater was 5.90 (ng/L), ranging from 5.73 to 6.06 (ng/L), and was 8.03 (ng/g), ranging from 7.77 to 8.28 (ng/g) in sediments. Fluoroquinolones, tetracyclines, and macrolides were identified as the main antibiotics found in both seawater and sediment samples. The Beibu Gulf showed higher antibiotic levels in its western and northeastern areas. Additionally, the nearshore mangrove areas displayed the highest prevalence of antibiotic residues. It is strongly advised to conduct regular long-term monitoring of antibiotic residues in the Beibu Gulf. Collaborative surveys covering the entire Beibu Gulf involving China and Vietnam are recommended.

A mathematical model for the role of dopamine-D2 self-regulation in the production of ultradian rhythms.

Many self-motivated and goal-directed behaviours display highly flexible, approximately 4 hour ultradian (shorter than a day) oscillations. Despite lacking direct correspondence to physical cycles in the environment, these ultradian rhythms may be involved in optimizing functional interactions with the environment and reflect intrinsic neural dynamics. Current evidence supports a role of mesostriatal dopamine (DA) in the expression and propagation of ultradian rhythmicity, however, the biochemical processes underpinning these oscillations remain to be identified. Here, we use a mathematical model to investigate D2 autoreceptor-dependent DA self-regulation as the source of ultradian behavioural rhythms. DA concentration at the midbrain-striatal synapses is governed through a dual-negative feedback-loop structure, which naturally gives rise to rhythmicity. This model shows the propensity of striatal DA to produce an ultradian oscillation characterized by a flexible period that is highly sensitive to parameter variations. Circadian (approximately 24 hour) regulation consolidates the ultradian oscillations and alters their response to the phase-dependent, rapid-resetting effect of a transient excitatory stimulus. Within a circadian framework, the ultradian rhythm orchestrates behavioural activity and enhances responsiveness to an external stimulus. This suggests a role for the circadian-ultradian timekeeping hierarchy in governing organized behaviour and shaping daily experience through coordinating the motivation to engage in recurring, albeit not highly predictable events, such as social interactions.

Development and validation of a risk prediction model and prediction tools for post-thrombotic syndrome in patients with lower limb deep vein thrombosis.

PURPOSE: Our research aims to compare the predictive performance of decision tree algorithms (DT) and logistic regression analysis (LR) in constructing models, and develop a Post-Thrombotic Syndrome (PTS) risk stratification tool. METHODS: We retrospectively collected and analyzed relevant case information of 618 patients diagnosed with DVT from January 2012 to December 2021 in three different tertiary hospitals in Jiangxi Province as the modeling group. Additionally, we used the case information of 212 patients diagnosed with DVT from January 2022 to January 2023 in two tertiary hospitals in Hubei Province and Guangdong Province as the validation group. We extracted electronic medical record information including general patient data, medical history, laboratory test indicators, and treatment data for analysis. We established DT and LR models and compared their predictive performance using receiver operating characteristic (ROC) curves and confusion matrices. Internal and external validations were conducted. Additionally, we utilized LR to generate nomogram charts, calibration curves, and decision curves analysis (DCA) to assess its predictive accuracy. RESULTS: Both DT and LR models indicate that Year, Residence, Cancer, Varicose Vein Operation History, DM, and Chronic VTE are risk factors for PTS occurrence. In internal validation, DT outperforms LR (0.962 vs 0.925, z = 3.379, P < 0.001). However, in external validation, there is no significant difference in the area under the ROC curve between the two models (0.963 vs 0.949, z = 0.412, P = 0.680). The validation results of calibration curves and DCA demonstrate that LR exhibits good predictive accuracy and clinical effectiveness. A web-based calculator software of nomogram (https://sunxiaoxuan.shinyapps.io/dynnomapp/) was utilized to visualize the logistic regression model. CONCLUSIONS: The combination of decision tree and logistic regression models, along with the web-based calculator software of nomogram, can assist healthcare professionals in accurately assessing the risk of PTS occurrence in individual patients with lower limb DVT.

Enzyme-Driven LC-HRMS Approach for Specific Recognition of 12α-Hydroxy Bile Acids.

The synthesis of 12α-hydroxylated bile acids (12HBAs) and non-12α-hydroxylated bile acids (non-12HBAs) occurs via classical and alternative pathways, respectively. The composition of these BAs is a crucial index for pathophysiologic assessment. However, accurately differentiating 12HBAs and non-12HBAs is highly challenging due to the limited standard substances. Here, we innovatively introduce 12α-hydroxysteroid dehydrogenase (12α-HSDH) as an enzymatic probe synthesized by heterologous expression in Escherichia coli, which can specifically and efficiently convert 12HBAs in vitro under mild conditions. Coupled to the conversion rate determined by liquid chromatography-high resolution mass spectrometry (LC-HRMS), this enzymatic probe allows for the straightforward distinguishing of 210 12HBAs and 312 non-12HBAs from complex biological matrices, resulting in a BAs profile with a well-defined hydroxyl feature at the C12 site. Notably, this enzyme-driven LC-HRMS approach can be extended to any molecule with explicit knowledge of enzymatic transformation. We demonstrate the practicality of this BAs profile in terms of both revealing cross-species BAs heterogeneity and monitoring the alterations of 12HBAs and non-12HBAs under asthma disease. We envisage that this work will provide a novel pattern to recognize the shift of BA metabolism from classical to alternative synthesis pathways in different pathophysiological states, thereby offering valuable insights into the management of related diseases.

Highly Potent Transparent Passive Cooling Coating via Microphase-Separated Hydrogel Combining Radiative and Evaporative Cooling.

Transparent passive cooling materials can cool targets environmentally without interfering with light transmission or visual information reception. They play a prominent role in solar cells and flexible display cooling. However, achieving potent transparent cooling remains challenging, because light transmission is accompanied by thermal energy. Here we propose to realize effective passive cooling in transparent materials via a microscale phase separation hydrogel film. The poly(N-isopropylacrylamide-co-acrylamide) hydrogel presents light transmittance of >96% and infrared emissivity as high as 95%. The microphase-separated structure affords a higher enthalpy of evaporation. The film is highly adhesive. In field applications, it reduces temperatures by 9.14 °C compared to those with uncovered photovoltaic panels and 7.68 °C compared to those for bare flexible light-emitting diode screens. Simulations indicate that energy savings of 32.76-51.65 MJ m-2 year-1 can be achieved in typical tropical monsoon climates and temperate continental climates. We expect this work to contribute to energy-efficient materials and a carbon-neutral society.

[Betulinic acid inhibits non-small cell lung cancer by repolarizing tumor-associated macrophages via mTOR signaling pathway].

The abnormal activation of the mammalian target of rapamycin(mTOR) signaling pathway in non-small cell lung cancer(NSCLC) is closely associated with distant metastasis, drug resistance, tumor immune escape, and low overall survival. The present study reported that betulinic acid(BA), a potent inhibitor of mTOR signaling pathway, exhibited an inhibitory activity against NSCLC in vitro and in vivo. CCK-8 and colony formation results demonstrated that BA significantly inhibited the viability and clonogenic ability of H1299, A549, and LLC cells. Additionally, the treatment with BA induced mitochondrion-mediated apoptosis of H1299 and LLC cells. Furthermore, BA inhibited the mobility and invasion of H1299 and LLC cells by down-regulating the expression level of matrix metalloproteinase 2(MMP2) and impairing epithelial-mesenchymal transition. The results demonstrated that the inhibition of mTOR signaling pathway by BA decreased the proportion of M2 phenotype(CD206 positive) cells in total macrophages. Furthermore, a mouse model of subcutaneous tumor was established with LLC cells to evaluate the anti-tumor efficiency of BA in vivo. The results revealed that the administration of BA dramatically retarded the tumor growth and inhibited the proliferation of tumor cells. More importantly, BA increased the ratio of M1/M2 macrophages in the tumor tissue, which implied the enhancement of anti-tumor immunity. In conclusion, BA demonstrated the inhibitory effect on NSCLC by repolarizing tumor-associated macrophages via the mTOR signaling pathway.

Types of Septic Cardiomyopathy: Prognosis and Influencing Factors - A Clinical Study.

Objective: To explore the prognostic outcomes associated with different types of septic cardiomyopathy and analyze the factors that exert an influence on these outcomes. Methods: The data collected within 24 hours of ICU admission included cardiac troponin I (cTnI), N-terminal pro-Brain Natriuretic Peptide (NT-proBNP); SOFA (sequential organ failure assessment) scores, and the proportion of vasopressor use. Based on echocardiographic outcomes, septic cardiomyopathy was categorized into left ventricular (LV) systolic dysfunction, LV diastolic dysfunction, and right ventricular (RV) systolic dysfunction. Differences between the mortality and survival groups, as well as between each cardiomyopathy subgroup and the non-cardiomyopathy group were compared, to explore the influencing factors of cardiomyopathy. Results: A cohort of 184 patients were included in this study, with LV diastolic dysfunction having the highest incidence rate (43.5%). The mortality group had significantly higher SOFA scores, vasopressor use, and cTnI levels compared to the survival group; the survival group had better LV diastolic function than the mortality group (p < 0.05 for all). In contrast to the non-cardiomyopathy group, each subgroup within the cardiomyopathy category exhibited elevated levels of cTnI. The subgroup with left ventricular diastolic dysfunction demonstrated a higher prevalence of advanced age, hypertension, diabetes mellitus, coronary artery disease, and an increased mortality rate; the RV systolic dysfunction subgroup had higher SOFA scores and NT-proBNP levels, and a higher mortality rate (P < 0.05 for all); the LV systolic dysfunction subgroup had a similar mortality rate (P > 0.05). Conclusion: Patients with advanced age, hypertension, diabetes mellitus, or coronary artery disease are more prone to develop LV diastolic dysfunction type of cardiomyopathy; cardiomyopathy subgroups had higher levels of cTnI. The RV systolic dysfunction cardiomyopathy subgroup had higher SOFA scores and NT-proBNP levels. The occurrence of RV systolic dysfunction in patients with sepsis significantly increased the mortality rate.

[Advances in the Effects of Microplastics on Soil N2O Emissions and Nitrogen Transformation].

Research on microplastics (MPs) is gaining more attention in the soil environment, but their impact on soil microbiota and related nitrogen processes remains poorly understood. Nitrous oxide (N2O) is one of the important greenhouse gases of the nitrogen cycle in agricultural soil, which mainly originates from microbial-mediated nitrogen (N) transformation processes. Microplastics can influence soil nitrogen transformation, as well as nitrogen-related functional enzymes and genes, and its enrichment may profoundly affect the N2O emissions in soil. However, because of the complexity of the properties of MPs, variations in experimental conditions, and spatial-temporal scales, the results on the effects of MPs on soil N2O emissions, nitrogen content, enzymes activities, and nitrogen functional genes remain inconsistent. Additionally, there is a lack of research conducted at broader experimental scales (e.g., pot scale), from diverse perspectives (e.g., denitrification or DNRA), and using advanced techniques (e.g., stable isotope approaches) to elucidate the underlying mechanisms. Therefore, to comprehend the environmental risk of MPs on soil from multiple perspectives, this review summarized the impact of MPs on soil N cycling from previous published research to provide a knowledge basis and gain holistic insights into the potential impact of soil microplastic enrichment on N2O emission patterns in agricultural soils under climate change conditions.

Insights into Lithium Sulfide Glass Electrolyte Structures and Ionic Conductivity via Machine Learning Force Field Simulations.

Sulfide-based solid electrolytes (SEs) are important for advancing all-solid-state batteries (ASSBs), primarily due to their high ionic conductivities and robust mechanical stability. Glassy SEs (GSEs) comprising mixed Si and P glass formers are particularly promising for their synthesis process and their ability to prevent lithium dendrite growth. However, to date, the complexity of their glassy structures hinders a complete understanding of the relationships between their structures and properties. This study introduces a new machine learning force field (ML-FF) tailored for lithium sulfide-based GSEs, enabling the exploration of their structural characteristics, mechanical properties, and lithium ionic conductivities. Using molecular dynamic (MD) simulations with this ML-FF, we explore the glass structures in varying compositions, including binary Li2S-SiS2 and Li2S-P2S5 as well as ternary Li2S-SiS2-P2S5. Our simulations yielded consistent results in terms of density, elastic modulus, radial distribution functions, and neutron structure factors compared to DFT and experimental work. Our findings reveal distinct local environments for Si and P within these glasses, with most Si atoms in edge-sharing configurations in Li2S-SiS2 and a mix of corner- and edge-sharing tetrahedra in the ternary Li2S-SiS2-P2S5 composition. For lithium ionic conductivity at 300 K, the 50Li2S-50SiS2 glass displayed the lowest conductivity at 2.1 mS/cm, while the 75Li2S-25P2S5 composition exhibited the highest conductivity at 3.6 mS/cm. The ternary glass showed a conductivity of 2.6 mS/cm, sitting between the two. Moreover, an in-depth analysis of lithium ion diffusion over the MD trajectory in the ternary glass demonstrated a significant correlation between diffusion pathways and the rotational dynamics of nearby SiS4 or PS4 tetrahedra. The ML-FF developed in this study provides an important tool for exploring a broad spectrum of solid-state and mixed former sulfide-based electrolytes.

The mechanism of intrinsic peroxidase (POD)-like activity of attapulgite.

Natural attapulgite (ATP) is a promising substitute for existing artificial nanozymes due to its intrinsic enzymatic activity. However, the active center of ATP's inherent enzymatic activity has not yet been revealed, which limits its further design and activity optimization. Studying the active center of mineral materials can be extremely challenging due to their complexity. Here, we demonstrated that Fe is the primary element in ATP responsible for peroxidase (POD)-like activity through theoretical speculation and experimental verification. More importantly, we found that the ratio of Fe2+/Fe3+ is responsible for the district POD-like activity of ATP from different regions with the same Fe content. Additionally, three facile strategies, including grinding, heat treatment, and acid treatment, were demonstrated to increase the relative Fe content and thus optimize the POD-like activity of ATP. Finally, ATP was used to detect the concentration of H2O2, enabling the detection of low concentrations (0.11-1.76 mM) of H2O2. This study serves as a novel reference for the future design and performance optimization of nanozymes that are based on ATP and clay minerals.