The bacterial community drive the humification and greenhouse gas emissions during plant residues composting under different aeration rates.

This study investigated the effects of different aeration intensities on organic matter (OM) degradation, greenhouse gas emissions (GHG) as well as humification during plant residue composting. Three intermittent aeration intensities of 0.084 (Tlow), 0.19 (Tmedium) and 0.34 (Thigh) L min-1kg-1 DM with 30 min on/30 min off were conducted on a lab-scale composting experiment. Results showed that OM mineralization in Thigh was more evident than Tlow and Tmedium, resulting in the highest humic acid content. Humic acid content in Tmedium and Thigh was 15.7% and 18.5% higher than that in Tlow. The average O2 concentration was 4.9%, 9.5% and 13.6% for Tlow, Tmedium and Thigh. Compared with Tmedium and Thigh, Tlow reduced CO2 and N2O emissions by 18.3%-39.6% and 72.4%-63.9%, but the CH4 emission was highest in Tlow. But the total GHG emission was the lowest in Thigh. Linear Discriminant Analysis Effect Size analysis showed that the core bacteria within Tlow mainly belonged to Anaerolineaceae, which was significantly negatively correlated to the emission of CH4. Thermostaphylospora, Unclassified_Vicinamibacteraceae and Sulfurifustis were identified as core bacteria in Tmedium and Thigh, and these genus were significantly postively correlated to CO2 and N2O emissions. Redundancy analysis showed that total orgnic carbon, O2 and electrical conductivity were the key factors affecting the evolution of bacterial community.

Sustainable design of photo-Fenton-like oxidation process in actual livestock wastewater through the highly dispersed FeCl3 anchoring on a g-C3N4 substrate.

Photocatalytic technology emerges as a promising solution for the sustainable treatment of contaminated wastewater. However, the practical implementation of designed photocatalysts often faces challenges due to the intricate 'high carbon footprint' process and limited outdoor laboratory investigations. Herein, a simple yet versatile impregnation approach is proposed to anchor highly dispersed FeCl3 on a g-C3N4 substrate (Fe-C3N4) with minimal energy consumption and post-processing. Fe-C3N4 enhances photocatalytic reactivity for antibiotic degradation via a synergistic photo-Fenton-like oxidation technique, efficiently removing antibiotic pollutants from actual livestock wastewater. The Fe-C3N4 catalyst exhibited consistent degradation performance over five cycles in laboratory conditions, maintaining a degradation efficiency exceeding 90 % for tetracycline hydrochloride (TCHCl). Furthermore, we engineered a straightforward Fe-C3N4Na2SiO3 reactor for treating livestock wastewater, achieving an 81.8 % removal of TCHCl in outdoor field tests conducted in the winter and summer in China. The Fe-C3N4 catalyst demonstrated high feasibility in treating antibiotic-contaminated livestock wastewater under year-round climatic conditions, leveraging synergistic effects. The stabilization of Fe-C3N4 for the degradation of antibiotic-containing wastewater under sunlight represents a significant advancement in the practical application of photocatalysts, marking a crucial milestone from experimental conception to implementation. Acute toxicity estimation suggested that intermediates/products generated exhibited lower toxicity compared to TCHCl, indicating their practical applicability. Density functional theory (DFT) analysis successfully predicted significant electron transfer between Fe-C3N4 and TCHCl, indicating efficient interfacial interactions on the TCHCl surface. To ensure the environmental sustainability of Fe-C3N4, a life cycle assessment (LCA) was conducted to compared this photocatalyst with other commonly used emerging photocatalysts. The results demonstrated that Fe-C3N4 exhibits a two orders of magnitude lower CO2 equivalent emission compared to the ZnO photocatalyst, indicating a cost-effective and efficient synergistic photo-Fenton-like catalytic approach. This low-cost photocatalyst, moving from the laboratory to real-world wastewater applications, provides a powerful and more sustainable solution for the efficient treatment of wastewater containing antibiotics from livestock farming.

Micro-expression recognition based on multi-scale 3D residual convolutional neural network.

In demanding application scenarios such as clinical psychotherapy and criminal interrogation, the accurate recognition of micro-expressions is of utmost importance but poses significant challenges. One of the main difficulties lies in effectively capturing weak and fleeting facial features and improving recognition performance. To address this fundamental issue, this paper proposed a novel architecture based on a multi-scale 3D residual convolutional neural network. The algorithm leveraged a deep 3D-ResNet50 as the skeleton model and utilized the micro-expression optical flow feature map as the input for the network model. Drawing upon the complex spatial and temporal features inherent in micro-expressions, the network incorporated multi-scale convolutional modules of varying sizes to integrate both global and local information. Furthermore, an attention mechanism feature fusion module was introduced to enhance the model's contextual awareness. Finally, to optimize the model's prediction of the optimal solution, a discriminative network structure with multiple output channels was constructed. The algorithm's performance was evaluated using the public datasets SMIC, SAMM, and CASME Ⅱ. The experimental results demonstrated that the proposed algorithm achieves recognition accuracies of 74.6, 84.77 and 91.35% on these datasets, respectively. This substantial improvement in efficiency compared to existing mainstream methods for extracting micro-expression subtle features effectively enhanced micro-expression recognition performance and increased the accuracy of high-precision micro-expression recognition. Consequently, this paper served as an important reference for researchers working on high-precision micro-expression recognition.

Renewable hemicellulose-based materials for value-added applications.

The importance of renewable resources and environmentally friendly materials has grown globally in recent time. Hemicellulose is renewable lignocellulosic materials that have been the subject of substantial valorisation research. Due to its distinctive benefits, including its wide availability, low cost, renewability, biodegradability, simplicity of chemical modification, etc., it has attracted increasing interest in a number of value-added fields. In this review, a systematic summarizes of the structure, extraction method, and characterization technique for hemicellulose-based materials was carried out. Also, their most current developments in a variety of value-added adsorbents, biomedical, energy-related, 3D-printed materials, sensors, food packaging applications were discussed. Additionally, the most recent challenges and prospects of hemicellulose-based materials are emphasized and examined in-depth. It is anticipated that in the near future, persistent scientific efforts will enable the renewable hemicellulose-based products to achieve practical applications.

Research on gesture recognition algorithm based on MME-P3D.

A Multiscale-Motion Embedding Pseudo-3D (MME-P3D) gesture recognition algorithm has been proposed to tackle the issues of excessive parameters and high computational complexity encountered by existing gesture recognition algorithms deployed in mobile and embedded devices. The algorithm initially takes into account the characteristics of gesture motion information, integrating the channel attention (CE) mechanism into the pseudo-3D (P3D) module, thereby constructing a P3D-C feature extraction network that can efficiently extract spatio-temporal feature information while reducing the complexity of the algorithmic model. To further enhance the understanding and learning of the global gesture movement's dynamic information, a Multiscale Motion Embedding (MME) mechanism is subsequently designed. The experimental findings reveal that the MME-P3D model achieves recognition accuracies reaching up to 91.12% and 83.06% on the self-constructed conference gesture dataset and the publicly available Chalearn 2013 dataset, respectively. In comparison with the conventional 3D convolutional neural network, the MME-P3D model demonstrates a significant advantage in terms of parameter count and computational requirements, which are reduced by as much as 82% and 83%, respectively. This effectively addresses the limitations of the original algorithms, making them more suitable for deployment on embedded and mobile devices and providing a more effective means for the practical application of hand gesture recognition technology.

Hydrochar drives reduction in bioavailability of heavy metals during composting via promoting humification and microbial community evolution.

This study presented the effects of hydrochar on humification, heavy metals (HMs) bioavailability and bacterial community succession during composting. Results indicated that hydrochar addition led to elevated composting temperature, 7.3% increase in humic acid (HA), and 52.9% increase in ratio of humic acid to fulvic acid. The diethylene triamine pentacetic acid extractable Zn, Cu, Pb, and Ni were reduced by 19.2%, 36.3%, 37.8%, and 27.1%, respectively, in hydrochar-involved composting system. Furthermore, main mechanisms driving the reduced HMs bioavailability by hydrochar addition were revealed. The addition of hydrochar significantly modified the microbial community structure. Correlation analysis and microbial analysis demonstrated that relative abundance of bacterial groups connected with humification and HMs passivation were increased. Consequently, the HA formation was promoted and the HMs bioavailability were reduced through bacterial bioremediation and HA complexation. This study demonstrates the addition of hydrochar as a promising strategy to mitigate the HMs bioavailability during composting.

Risk Factors for Hypoglycemia Among Neonates: A Prospective Cohort Study Among Pregnant People With Gestational Diabetes Mellitus.

OBJECTIVE: Neonatal hypoglycemia (NH) is the most frequent complication in neonates born to pregnant people with gestational diabetes mellitus (GDM) and an important cause of brain damage and death of neonates. We explored the risk factors for NH in neonates of pregnant people with GDM. METHODS: A prospective cohort study was conducted involving 322 pregnant people with GDM at the Guangzhou Women and Children's Medical Centre. Maternal sociodemographic, clinical, and biochemical data, as well as general characteristics of neonates, were collected to analyze their associations with NH in neonates of pregnant people with GDM. RESULTS: The incidence of NH among neonates of pregnant people with GDM was 19.57% (63/322). After adjustment for confounders, the factors significantly associated with an increased risk of NH were cesarean delivery (relative risk [RR] = 3.44; 95% confidence interval [CI], 1.83-6.45), red blood cell (RBC) count (RR = 2.19; 95% CI, 1.22-3.96), and 1-hour postprandial glucose (RR = 2.35; 95% CI, 1.23-4.46) during pregnancy, whereas later gestational age (RR = 0.58; 95% CI, 0.42-0.80) and multiparity (RR = 0.32; 95% CI, 0.16-0.66) were associated with a reduced risk of NH. CONCLUSION: Cesarean delivery, maternal 1-hour glucose of the oral glucose tolerance test, and increased RBC count of pregnant people with GDM are independent risk factors for NH, while later gestational age and multiparity are protective factors.

A global optimization generation method of stitching dental panorama with anti-perspective transformation.

To address the limitation of narrow field-of-view in local oral cavity images that fail to capture large-area targets at once, this paper designs a method for generating natural dental panoramas based on oral endoscopic imaging that consists of two main stages: the anti-perspective transformation feature extraction and the coarse-to-fine global optimization matching. In the first stage, we increase the number of matched pairs and improve the robustness of the algorithm to viewpoint transformation by normalizing the anti-affine transformation region extracted from the Gaussian scale space and using log-polar coordinates to compute the gradient histogram of the octagonal region to obtain the set of perspective transformation resistant feature points. In the second stage, we design a coarse-to-fine global optimization matching strategy. Initially, we incorporate motion smoothing constraints and improve the Fast Library for Approximate Nearest Neighbors (FLANN) algorithm by utilizing neighborhood information for coarse matching. Then, we eliminate mismatches via homography-guided Random Sample Consensus (RANSAC) and further refine the matching using the Levenberg-Marquardt (L-M) algorithm to reduce cumulative errors and achieve global optimization. Finally, multi-band blending is used to eliminate the ghosting due to unalignment and make the image transition more natural. Experiments show that the visual effect of dental panoramas generated by the proposed method is significantly better than that of other methods, addressing the problems of sparse splicing discontinuities caused by sparse keypoints, ghosting due to parallax, and distortion caused by the accumulation of errors in multi-image splicing in oral endoscopic image stitching.

Reduction of mobile genetic elements determines the removal of antibiotic resistance genes during pig manure composting after thermal pretreatment.

Animal manure is a primary repository of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs). This work explored the efficiency of ARGs and MGEs removal during pig manure composting after thermal pretreatment (TPC) and the underlying mechanisms. TPC resulted in a decrease of 94.7% and 92.3% in the relative abundance of ARGs and MGEs which was 48.9% and 76.6% lower than control, respectively. Network analysis indicated that reductions of ARGs and MGEs in TPC were relevant to decrease in the amount and abundance of bacterial hosts. Furthermore, total ARGs abundance in TPC was correlated with that of intI1 and Tn916/1545 (P < 0.001). Redundancy analysis supported a leading role of MGEs in ARGs dynamics in TPC. Reduction of MGEs rather than bacterial hosts contributed mainly to ARGs removal in TPC, as revealed by structural equation modeling. In conclusion, TPC was an effective method to treat animal manure containing ARGs.

A weakly supervised learning-based segmentation network for dental diseases.

With the development of deep learning, medical image segmentation has become a promising technique for computer-aided medical diagnosis. However, the supervised training of the algorithm relies on a large amount of labeled data, and the private dataset bias generally exists in previous research, which seriously affects the algorithm's performance. In order to alleviate this problem and improve the robustness and generalization of the model, this paper proposes an end-to-end weakly supervised semantic segmentation network to learn and infer mappings. Firstly, an attention compensation mechanism (ACM) aggregating the class activation map (CAM) is designed to learn complementarily. Then the conditional random field (CRF) is introduced to prune the foreground and background regions. Finally, the obtained high-confidence regions are used as pseudo labels for the segmentation branch to train and optimize using a joint loss function. Our model achieves a Mean Intersection over Union (MIoU) score of 62.84% in the segmentation task, which is an effective improvement of 11.18% compared to the previous network for segmenting dental diseases. Moreover, we further verify that our model has higher robustness to dataset bias by improved localization mechanism (CAM). The research shows that our proposed approach improves the accuracy and robustness of dental disease identification.

Potential of hydrochar/pyrochar derived from sawdust of oriental plane tree for stimulating methanization by mitigating propionic acid inhibition in mesophilic anaerobic digestion of swine manure.

VFAs accumulation in anaerobic digestion systems can lead to disturbance of the acid base balance, which has brought major challenges for methane production. Meanwhile, less research explored the potential of biochar derived from wood wastes of oriental plane tree (Platanus orientalis L.) for stimulating methanization in mesophilic anaerobic digestion. In this study, the effects of pyrochar and hydrochar derived from sawdust of oriental plane tree on mesophilic anaerobic digestion of swine manure were compared for the first time. Fourier infrared transform analysis indicated that more functional groups existed on the surface of hydrochar, whereas higher ash content and BET specific surface area were found in pyrochar. The maximum methane production rate during anaerobic digestion was observed in the pyrochar treatment, which increased by 59.5% compared with the control without biochar. Although stimulative effects on dissolved organic carbon and volatile fatty acids production were both observed in the pyrochar and hydrochar treatments, the pyrochar treatment was much easier to trigger multipath methanogenesis and direct interspecific electron transport and subdue propionic acid accumulation compared to the hydrochar treatment. Moreover, redundancy analysis indicated that the variations in acetic acid and dissolved organic carbon were mostly associated with microbial succession. These results suggest that pyrochar has better promoting effects than HC in terms of methane generation and propionic acid inhibition alleviation owing to its special porous structures, functional groups (e.g., C=O, C-O and O-H), and physicochemical properties. These excellent properties play a greater role in recruiting functional archaea and bacteria to regulate the levels of volatile fatty acids and dissolved organic carbon to enhance the methane yield of anaerobic digestion. This study provides novel and valuable information for further engineering applications of pyrochar and hydrochar derived from sawdust of oriental plane tree in energy production and environmental waste treatment.

Shared and unique effects of ApoEε4 and pathogenic gene mutation on cognition and imaging in preclinical familial Alzheimer's disease.

BACKGROUND: Neuropsychology and imaging changes have been reported in the preclinical stage of familial Alzheimer's disease (FAD). This study investigated the effects of APOEε4 and known pathogenic gene mutation on different cognitive domains and circuit imaging markers in preclinical FAD. METHODS: One hundred thirty-nine asymptomatic subjects in FAD families, including 26 APOEε4 carriers, 17 APP and 20 PS1 mutation carriers, and 76 control subjects, went through a series of neuropsychological tests and MRI scanning. Test scores and imaging measures including volumes, diffusion indices, and functional connectivity (FC) of frontostriatal and hippocampus to posterior cingulate cortex pathways were compared between groups and analyzed for correlation. RESULTS: Compared with controls, the APOEε4 group showed increased hippocampal volume and decreased FC of fronto-caudate pathway. The APP group showed increased recall scores in auditory verbal learning test, decreased fiber number, and increased radial diffusivity and FC of frontostriatal pathway. All three genetic groups showed decreased fractional anisotropy of hippocampus to posterior cingulate cortex pathway. These neuropsychological and imaging measures were able to discriminate genetic groups from controls, with areas under the curve from 0.733 to 0.837. Circuit imaging measures are differentially associated with scores in various cognitive scales in control and genetic groups. CONCLUSIONS: There are neuropsychological and imaging changes in the preclinical stage of FAD, some of which are shared by APOEε4 and known pathogenic gene mutation, while some are unique to different genetic groups. These findings are helpful for the early identification of Alzheimer's disease and for developing generalized and individualized prevention and intervention strategies.

Artificial Intelligence-Based Prediction of Individual Differences in Psychological Occupational Therapy Intervention Guided by the Realization of Occupational Values.

As the competition between enterprises intensifies, employees have witnessed a decline of psychological health year by year and severe anxiety and depression. To ensure the normal work of employees, it is important to implement psychological occupational therapy intervention (POTI). The previous studies on corporate occupational values focus on the behavioral variables and attitude variables related to occupations. The research paradigm does not suit a specific group of employees. Therefore, this paper explores the individual differences in POTI guided by the realization of occupational values. For a specific group of employees, the correlations of the psychological problems with job attitude, job involvement, and psychological health level were reasoned logically, a theoretical model was established, and the full-model map was plotted to illustrate the influence of the realization of occupational values over POTI. Then, the evaluation data on the psychological intervention effect of 2,800 employees were explored based on multikernel learning, and an individual difference prediction model was constructed through multikernel learning. Finally, the predicted results of different groups of employees were compared, revealing the effectiveness of our algorithm.

Comparative Analysis of Clinical Effects of Insulin Aspart Combined with Acarbose and Metformin in the Treatment of Diabetes Mellitus.

Objective: To investigate the clinical effect of Insulin aspart 30 combined with acarbose and metformin enteric-coated tablets in the treatment of diabetes mellitus. Methods: 90 diabetic patients admitted to our hospital from January 2019 to December 2021 were selected as the research subjects, and the patients were randomly divided into group A (n = 30, using insulin aspart 30 alone), group B (n = 30, using insulin aspart 30 combined with metformin enteric-coated tablets), and group C (n = 30, using insulin aspart 30 combined with acarbose). The blood glucose balance before meals and before going to bed was maintained in the three groups of patients, and the blood glucose fluctuations, time to target, hypoglycemia, insulin dosage, and daily consumption of the three groups were compared. Results: There was no significant difference in blood glucose and average blood glucose at each time point before treatment in the 3 groups of patients (P > 0.05); compared with the blood glucose and average blood glucose at each time point after reaching the target in the three groups, the blood glucose after dinner in group A was significantly higher than that in groups B and C; at 2 : 00, the blood glucose of group A was significantly higher than that of group B (P < 0.05); there was no significant difference in blood glucose and average blood glucose at other time points (P > 0.05). There was no significant difference in blood glucose standard deviation, LAGE, and PPGE at each point in the three groups before treatment (P > 0.05); the standard deviation of blood glucose, LAGE, and PPGE at each point of the three groups of patients after reaching the standard were compared with those in the same group before treatment, and the differences were statistically significant (P < 0.05); there were statistically significant differences in blood glucose standard deviation, LAGE, and PPGE among the 3 groups after reaching the standard (P < 0.05). Compared among the three groups, the standard deviation of blood glucose and LAGE level at each point after reaching the standard, the difference between group B, group C, and group A was statistically significant (P < 0.05); however, there was no significant difference between the patients in group B and group C (P > 0.05); the level of PPGE in group A was higher than that in group B, which was higher than group C, and between group C and group A, the difference was statistically significant (P < 0.05). The time of reaching the standard in 3 groups was statistically significant (P < 0.05); there was no significant difference in the time of reaching the standard between group B and group C (P > 0.05). There was no significant difference in the incidence of hypoglycemia among the 3 groups (P > 0.05); there were significant differences in the proportion of insulin twice a day among the three groups (P < 0.05); there were statistically significant differences in daily insulin dosage among the 3 groups after reaching the standard (P < 0.05). The daily consumption of the three groups of patients after reaching the standard was compared, the difference was statistically significant (P < 0.05), and there was no significant difference between group A and group B (P > 0.05). Conclusion: The effect of insulin aspart 30 alone in the treatment of diabetic patients is not good, it will lead to a large fluctuation of blood sugar in the patient's body, and the time required to reach the standard is relatively long; the use of insulin aspart 30 combined with metformin enteric-coated tablets or acarbose can effectively reduce the blood sugar fluctuation range of diabetic patients and reduce the number of insulin injections, and insulin aspart 30 combined with metformin en teric-coated tablets can also greatly reduce the daily insulin dosage and daily consumption cost of diabetic patients.

Foliar application of biosynthetic nano-selenium alleviates the toxicity of Cd, Pb, and Hg in Brassica chinensis by inhibiting heavy metal adsorption and improving antioxidant system in plant.

Biosynthetic nano-selenium (bio-SeNP), as a plant growth regulator, has better bioavailability and lower toxicity than selenite and selenate. This study investigated the beneficial role of bio-SeNP in mitigating the adverse effects of multiple heavy metals (HMs, e.g., Cd, Pb, and Hg) on growth and yield of pak choi (Brassica chinensis) grown in slightly or heavily polluted (SP or HP) soil by regulating metabolic and antioxidant systems. The results revealed that foliar application of bio-SeNP (5, 10, 20 mg L-1 Se) at the 6-leaf stage greatly reduced the levels of Cd, Pb, and Hg in shoots and roots of pak choi. Application of 5 mg L-1 bio-SeNP significantly (p < 0.05) decreased the translocation factor (TF) of Cd, Pb, and Hg from root to shoot by 9.83%, 44.21%, and 46.99% for SP soil, 24.17%, 56.00%, and 39.36% for HP soil, respectively. Meanwhile, all bio-SeNP treatments led to a significant improvement in plants growth by enhancing the antioxidant defense system (e.g., AsA-GSH) and promoting chlorophyll synthesis as well as suppressed the lipid peroxidation products contents (MDA) in shoots. Moreover, the enhanced levels of mineral nutrient elements (e.g., Ca, Mg, Fe, or Zn) and organic selenium (e.g., selenocystine, Se-methylselenocysteine, and selenomethionine) in the edible shoots of bio-SeNP-treated pak choi plant under multiple HMs stress indicated the positive impacts of bio-SeNP on the improvement of shoot quality and nutritional values. Collectively, our results indicated that bio-SeNP play an important role in the management of multiple HMs-induced adverse effects on pak choi. Foliar application of bio-SeNP at appropriate concentration (≤ 5 mg L-1 Se) can be considered as a promising agronomic measure for safety leafy vegetable production in multiple HMs polluted soils when bio-SeNP application.

Phosphorylated Tau 181 Serum Levels Predict Alzheimer's Disease in the Preclinical Stage.

Background: There is an urgent need for cost-effective, easy-to-measure biomarkers to identify subjects who will develop Alzheimer's disease (AD), especially at the pre-symptomatic stage. This stage can be determined in autosomal dominant AD (ADAD) which offers the opportunity to observe the dynamic biomarker changes during the life-course of AD stages. This study aimed to investigate serum biomarkers during different AD stages and potential novel protein biomarkers of presymptomatic AD. Methods: In the first stage, 32 individuals [20 mutation carriers including 10 with AD, and 10 with mild cognitive impairment (MCI), and 12 healthy controls] from ADAD families were analyzed. All subjects underwent a complete clinical evaluation and a comprehensive neuropsychological battery. Serum samples were collected from all subjects, and antibody arrays were used to analyze 170 proteins in these samples. The most promising biomarkers were identified during this screening and were then measured in serum samples of 12 subjects with pre-MCI and 20 controls. Results: The serum levels of 13 proteins were significantly different in patients with AD or MCI compared to controls. Of the 13 proteins, cathepsin D, immunoglobulin E, epidermal growth factor receptor (EGFR), matrix metalloproteinase-9 (MMP-9), von Willebrand factor (vWF), haptoglobin, and phosphorylated Tau-181 (p-Tau181) correlated with all cognitive measures (R2 = -0.69-0.76). The areas under the receiver operating characteristic curve of these seven proteins were 0.71-0.93 for the classification of AD and 0.57-0.95 for the classification of MCI. Higher levels of p-Tau181 were found in the serum of pre-MCI subjects than in the serum of controls. The p-Tau181 serum level might detect AD before symptoms occur (area under the curve 0.85, sensitivity 75%, specificity 81.67%). Conclusions: A total of 13 serum proteins showed significant differences between subjects with AD and MCI and healthy controls. The p-Tau181 serum level might be a broadly available and cost-effective biomarker to identify individuals with preclinical AD and assess the severity of AD.

Culture Effects on the Chinese Version Boston Naming Test Performance and the Normative Data in the Native Chinese-Speaking Elders in Mainland China.

Background: The Chinese version of Boston Naming Test (BNT-C) is administered in China widely. However, the neuropsychological parameter of BNT-C in native Chinese-speaking elders in mainland China has not been explored systematically. The aim of this study was to explore cultural influences on BNT-C performance and establish norms among native Chinese-speaking elders in Beijing. Methods: A total of 161 native, Chinese-speaking, cognitively normal elders aged ≥55 years were enrolled from various communities in Beijing. The BNT-C was conducted on all the participants. The internal consistency, participants' familiarity, and naming accuracy were analyzed and compared with data from Chinese areas outside the mainland and from American published previously. The influencing factors and stratified norms for BNT-C were established. Results: The BNT-C showed good internal consistency (α = 0.738). Strong correlation between naming accuracy and object familiarity was found (r = 0.962, P < 0.001). Participants' familiarity and correct naming rate for many items were notably different between the Chinese-speaking elders and English-speaking elders in America. The difference in some items' correct naming rate also existed between Beijing, Taiwan, and Hongkong. Higher education was associated with higher scores, whereas age and gender had no effect on BNT-C performance. The recommended norms of total naming scores for elders with education ≤ 9 and >9 years were 16 and 23, respectively. Conclusion: The participants' familiarity with BNT items differed between different cultures, which further affected the naming accuracy and total scores. The education stratified norms established here are helpful for the better application of BNT-C in mainland China.

Mediating effects of gut microbiota in the associations of air pollutants exposure with adverse pregnancy outcomes.

BACKGROUND: The aim of this study was to investigate alterations in gut microbiota after exposure to air pollutants during pregnancy and its mediation effect in inducing adverse pregnancy outcomes (APOs). METHODS: Participants (n = 916) were enrolled between 2017 and 2018 from a prospective cohort study of pregnant women in Guangzhou, China. The relative abundance of fecal microbiota was profiled using 16SrRNA V4 region sequencing. Exposure to air pollutants in each trimester of pregnancy was assessed using measurements from the nearest monitoring station. APOs including pre-term birth (PTB), post-term birth (POTB), low birth weight (LBW), macrosomia fetus (MF), birth defects (BDs), pathological cesarean section (PCS) and postpartum hemorrhage (PPH)) were determined by referring to reliable clinical records and diagnostic criteria. Univariate analysis, multivariate analysis and mediation analysis were performed to estimate the association among air pollutants, gut microbiota and APOs. RESULTS: Air pollutants exposure during pregnancy was significantly correlated with the alterations in the gut microbiota, and increased risks of various APOs by 1.07-1.36-fold (P < 0.05). The mediation analyses indicated that alterations in Eggerthella, Phascolarctobacterium and Clostridium partially mediated the effects of air pollutants exposure (PM2.5, PM10, O3, NO2 and SO2) on APOs. The relative abundance of f_Micrococcaceae explained 11.39%, 64.90% and 54.80% of the correlation between SO2, PM2.5, PM10 and POTB, respectively; whereas g_Rothia explained 11.97%, 67.80% and 54.50%, respectively. g_Parabacteroides explained 53.0% of the correlation between PM2.5 and PTB. CONCLUSIONS: Increased air pollutants exposure during pregnancy may induce adverse pregnancy outcomes via alteration of the gut microbiota.

Good Performance of the Chinese Version of Mini Social Cognition and Emotional Assessment in the Early Diagnosis of Behavioral Variant Frontotemporal Dementia.

Social cognition impairment has been recognized as an early and characteristic change in behavioral variant frontotemporal dementia (bvFTD). The Mini Social Cognition and Emotional Assessment (mini-SEA) is a clinical tool to rapidly evaluate social cognition. In this study, we explored the diagnostic value of social cognition by assessing the Chinese version of the mini-SEA and other standard neuropsychological tests in 22 patients with mild bvFTD, 26 patients with mild Alzheimer's disease (AD), including mild cognitive impairment (MCI) and mild dementia, and 30 control subjects. The discriminatory powers of these tests were evaluated and compared using the receiver operating characteristic curve (ROC). The mini-SEA scores of the bvFTD patients were significantly lower than those of the controls (Z = -6.850, adjusted P < 0.001) and AD patients (Z = -3.737, adjusted P = 0.001). ROC analysis showed that the mini-SEA had a high discriminatory power for differentiating bvFTD from the controls, with an area under the curve (AUC) value of 0.989 (95% CI = 0.905-1.000, P < 0.001). The AUC value of the mini-SEA for differentiating bvFTD from AD was 0.899 (95% CI = 0.777-0.967, P < 0.001), higher than that of the Auditory Verbal Learning Test Delayed Recall (AUC = 0.793), Boston Naming Test (AUC = 0.685) or Frontal Assessment Battery (AUC = 0.691). The Chinese version of mini-SEA is a good clinical tool for the early diagnosis of bvFTD, and has a high sensitivity and specificity to discriminate bvFTD from AD.

N4-acetyldeoxycytosine DNA modification marks euchromatin regions in Arabidopsis thaliana.

BACKGROUND: Direct analogs of chemically modified bases that carry important epigenetic information, such as 5-methylcytosine (m5C)/5-methyldeoxycytosine (5mC), 5-hydroxymethylcytosine (hm5C)/5-hydroxymethyldeoxycytosine (5hmC), and N6-methyladenosine (m6A)/N6-methyldeoxyadenosine (6mA), are detected in both RNA and DNA, respectively. The modified base N4-acetylcytosine (ac4C) is well studied in RNAs, but its presence and epigenetic roles in cellular DNA have not been explored. RESULTS: Here, we demonstrate the existence of N4-acetyldeoxycytosine (4acC) in genomic DNA of Arabidopsis with multiple detection methods. Genome-wide profiling of 4acC modification reveals that 4acC peaks are mostly distributed in euchromatin regions and present in nearly half of the expressed protein-coding genes in Arabidopsis. 4acC is mainly located around transcription start sites and positively correlates with gene expression levels. Imbalance of 5mC does not directly affect 4acC modification. We also characterize the associations of 4acC with 5mC and histone modifications that cooperatively regulate gene expression. Moreover, 4acC is also detected in genomic DNA of rice, maize, mouse, and human by mass spectrometry. CONCLUSIONS: Our findings reveal 4acC as a hitherto unknown DNA modification in higher eukaryotes. We identify potential interactions of this mark with other epigenetic marks in gene expression regulation.