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.

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.

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.

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.

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.

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.

Roles of TRP and PIEZO receptors in autoimmune diseases.

Autoimmune diseases are pathological autoimmune reactions in the body caused by various factors, which can lead to tissue damage and organ dysfunction. They can be divided into organ-specific and systemic autoimmune diseases. These diseases usually involve various body systems, including the blood, muscles, bones, joints and soft tissues. The transient receptor potential (TRP) and PIEZO receptors, which resulted in David Julius and Ardem Patapoutian winning the Nobel Prize in Physiology or Medicine in 2021, attracted people's attention. Most current studies on TRP and PIEZO receptors in autoimmune diseases have been carried out on animal model, only few clinical studies have been conducted. Therefore, this study aimed to review existing studies on TRP and PIEZO to understand the roles of these receptors in autoimmune diseases, which may help elucidate novel treatment strategies.

Unravelling immune microenvironment features underlying tumor progression in the single-cell era.

The relationship between the immune cell and tumor occurrence and progression remains unclear. Profiling alterations in the tumor immune microenvironment (TIME) at high resolution is crucial to identify factors influencing cancer progression and enhance the effectiveness of immunotherapy. However, traditional sequencing methods, including bulk RNA sequencing, exhibit varying degrees of masking the cellular heterogeneity and immunophenotypic changes observed in early and late-stage tumors. Single-cell RNA sequencing (scRNA-seq) has provided significant and precise TIME landscapes. Consequently, this review has highlighted TIME cellular and molecular changes in tumorigenesis and progression elucidated through recent scRNA-seq studies. Specifically, we have summarized the cellular heterogeneity of TIME at different stages, including early, late, and metastatic stages. Moreover, we have outlined the related variations that may promote tumor occurrence and metastasis in the single-cell era. The widespread applications of scRNA-seq in TIME will comprehensively redefine the understanding of tumor biology and furnish more effective immunotherapy strategies.

Recent advances in the contribution of glucosinolates degradation products to cruciferous foods odor: factors that influence degradation pathways and odor attributes.

As one of the most important vegetables and oils consumed globally, cruciferous foods are appreciated for their high nutritional value. However, there is no comprehensive knowledge to sufficiently unravel the "flavor mystery" of cruciferous foods. The present review provides a comprehensive literature on the recent advances regarding the contribution of glucosinolates (GSL) degradation products to cruciferous foods odor, which focuses on key GSL degradation products contributing to distinct odor of cruciferous foods (Brassica oleracea, Brassica rapa, Brassica napus, Brassica juncea, Raphanus sativus), and key factors affecting GSL degradation pathways (i.e., enzyme-induced degradation, thermal-induced degradation, chemical-induced degradation, microwave-induced degradation) during different processing and cooking. A total of 93 volatile GSL degradation products (i.e., 36 nitriles, 33 isothiocyanates, 3 thiocyanates, 5 epithionitriles, and 16 sulfides) and 29 GSL (i.e., 20 aliphatic, 5 aromatic, and 4 indolic) were found in generalized cruciferous foods. Remarkably, cruciferous foods have a distinctive pungent, spicy, pickled, sulfur, and vegetable odor. In general, isothiocyanates are mostly present in enzyme-induced degradation of GSL and are therefore often enriched in fresh-cut or low-temperature, short-time cooked cruciferous foods. In contrast, nitriles are mainly derived from thermal-induced degradation of GSL, and are thus often enriched in high-temperature, long-time cooked cruciferous foods.

Processing and cooking can cause degradation of glucosinolates and formation of volatiles.Structure­odor relationship of glucosinolates degradation products is discussed.Nitriles, isothiocyanates, and sulfides play an important role in cruciferous foods odor.Both enzyme- and thermal-induced degradation of glucosinolates is strongly pH-dependent.

Patterns of Cross-Peaks in Two-Dimensional Correlation Spectra to Probe Intermolecular Interactions Described by Two Reversible Reactions.

Two-dimensional correlation spectroscopy is used to investigate the intermolecular interaction between two substances dissolved in the same solutions, where the intermolecular interaction is described by two reversible reactions producing two supramolecular aggregates. The severe overlappings expected among the characteristic peaks of the original solute and aggregates make conventional one-dimensional spectra difficult to accurately reflect the physiochemical nature of the intermolecular interaction. The double asynchronous orthogonal sample design (DAOSD) approach is utilized to analyze the simulated data for proof-of-principle demonstration. The patterns of cross-peaks are much more complex compared with the intermolecular interaction described by only a single reaction. Four major groups of cross-peaks with characteristic patterns observed in the pair of DAOSD asynchronous spectra are systematically analyzed and classified. Further analysis of the spectral feature of the cross-peaks of the DAOSD asynchronous spectra is helpful to exact additional information concerning the variation of the peak position and peak width of the aggregates compared with those of the original solute. The result is important to reveal the physicochemical nature of intermolecular interaction between the solutes (e.g., changes in conformation, dynamical behavior, etc.). The pattern of cross-peaks in the corresponding 2D asynchronous spectra may become rather complex when the peak position, peak width, and peak intensity of two supramolecular aggregates change simultaneously. Further work using artificial intelligence techniques to interpret the complex cross-peaks is still being carried out.

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.

[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.

Mulberry and Hippophae-based solid beverage promotes weight loss in rats by antagonizing white adipose tissue PPARγ and FGFR1 signaling.

Obesity, a multifactorial disease with many complications, has become a global epidemic. Weight management, including dietary supplementation, has been confirmed to provide relevant health benefits. However, experimental evidence and mechanistic elucidation of dietary supplements in this regard are limited. Here, the weight loss efficacy of MHP, a commercial solid beverage consisting of mulberry leaf aqueous extract and Hippophae protein peptides, was evaluated in a high-fat high-fructose (HFF) diet-induced rat model of obesity. Body component analysis and histopathologic examination confirmed that MHP was effective to facilitate weight loss and adiposity decrease. Pathway enrichment analysis with differential metabolites generated by serum metabolomic profiling suggests that PPAR signal pathway was significantly altered when the rats were challenged by HFF diet but it was rectified after MHP intervention. RNA-Seq based transcriptome data also indicates that MHP intervention rectified the alterations of white adipose tissue mRNA expressions in HFF-induced obese rats. Integrated omics reveals that the efficacy of MHP against obesogenic adipogenesis was potentially associated with its regulation of PPARγ and FGFR1 signaling pathway. Collectively, our findings suggest that MHP could improve obesity, providing an insight into the use of MHP in body weight management.

Clinical characteristic, common sites, and geographical distribution of pediatric tuberculosis patients in Southwest China.

Background: The data report of a large sample, dynamic epidemiology, and characteristic analysis of pediatric tuberculosis (TB) in Southwest China is not clear. Herein, we conducted descriptive dynamic epidemiology, characteristic analysis and geographical distribution study of pediatric TB inpatients in Southwest China for more than 20 years. Methods: Patients with pediatric TB were recruited from October 2002 to September 2022 in Southwest of China based on etiology or clinical confirmation. Extract hospitalization medical record information for each patient. The geographical distribution chart of cases is used to display the trend of case flow segmented every 5 years. Results: Among 3,024 pediatric TB patients with an average age of 9.11 ± 4.39, 17.49% (529) had pulmonary tuberculosis (PTB), 9.06% (274) had extrapulmonary tuberculosis (EPTB), and 73.45% (2,221) had combined TB. The most common form of EPTB is disseminated TB (28.98%), followed by TB lymphadenitis (20.56%), pleural TB (19.72%), and TB meningitis (19.68%). Children aged 0-4 years had a high risk of TB meningitis and a severe symptoms, while children in the elderly age group had a high risk of pleural TB. In the past 20 years, hospitalized TB pediatric cases mainly came from Sichuan, Tibet, Qinghai, Yunnan and other places. The number of patients from ethnic minorities, especially Tibetans, showed an upward trend on a yearly basis (χ2 = 401.43, P < 0.001). Conclusions: Public health investment and effective management in pediatric TB should be further strengthened.

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.

Phylogeny and Taxonomic Revision of the Genus Melanosciadium (Apiaceae), Based on Plastid Genomes and Morphological Evidence.

Melanosciadium is considered a monotypic genus and is also endemic to the southwest of China. No detailed phylogenetic studies or plastid genomes have been identified in Melanosciadium. In this study, the plastid genome sequence and nrDNA sequence were used for the phylogenetic analysis of Melanosciadium and its related groups. Angelica tsinlingensis was previously considered a synonym of Hansenia forbesii. Similarly, Ligusticum angelicifolium was previously thought to be the genus Angelica or Ligusticopsis. Through field observations and morphological evidence, we believe that the two species are more similar to M. pimpinelloideum in leaves, umbel rays, and fruits. Meanwhile, we found a new species from Anhui Province (eastern China) that is similar to M. pimpinelloideum and have named it M. Jinzhaiensis. We sequenced and assembled the complete plastid genomes of these species and another three Angelica species. The genome comparison results show that M. pimpinelloideum, A. tsinlingensis, Ligusticum angelicifolium, and M. jinzhaiensis have similarities to each other in the plastid genome size, gene number, and length of the LSC and IR regions; the plastid genomes of these species are distinct from those of the Angelica species. In addition, we reconstruct the phylogenetic relationships using both plastid genome sequences and nrDNA sequences. The phylogenetic analysis revealed that A. tsinlingensis, M. pimpinelloideum, L. angelicifolium, and M. jinzhaiensis are closely related to each other and form a monophyletic group with strong support within the Selineae clade. Consequently, A. tsinlingensis and L. angelicifolium should be classified as members of the genus Melanosciadium, and suitable taxonomical treatments have been proposed. Meanwhile, a comprehensive description of the new species, M. jinzhaiensis, is presented, encompassing its habitat environment and detailed morphological traits.

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.