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Microglia, the resident immune cells of the central nervous system (CNS), are derived from yolk-sac macrophages that populate the developing CNS during early embryonic development. Once established, the microglia population is self-maintained throughout life by local proliferation. As a scalable source of microglia-like cells (MGLs), we here present a forward programming protocol for their generation from human pluripotent stem cells (hPSCs). The transient overexpression of PU.1 and C/EBPβ in hPSCs led to a homogenous population of mature microglia within 16 d. MGLs met microglia characteristics on a morphological, transcriptional, and functional level. MGLs facilitated the investigation of a human tauopathy model in cortical neuron–microglia cocultures, revealing a secondary dystrophic microglia phenotype. Single-cell RNA sequencing of microglia integrated into hPSC-derived cortical brain organoids demonstrated a shift of microglia signatures toward a more-developmental in vivo–like phenotype, inducing intercellular interactions promoting neurogenesis and arborization. Taken together, our microglia forward programming platform represents a tool for both reductionist studies in monocultures and complex coculture systems, including 3D brain organoids for the study of cellular interactions in healthy or diseased environments.

Cationic hydrogels have received great attention to control eutrophication and recycle phosphate. In this study, a type of La(OH)3 loaded magnetic MAPTAC-based cationic hydrogel (La(OH)3@MMCH) was developed as a potential adsorbent for enhanced phosphate removal from aqueous environment. La(OH)3@MMCH exhibited high adsorption capacity of 105.72±5.99 mg P/g, and reached equilibrium within 2 hr. La(OH)3@MMCH could perform effectively in a wide pH range from 3.0 to 9.0 and in the presence of coexisting ions (including SO42−, Cl−, NO3−, HCO3−, SiO44− and HA). The adsorption-desorption experiment indicated that La(OH)3@MMCH could be easily regenerated by using NaOH-NaCl as the desorption agent, and 73.3% adsorption capacity remained after five cycles. Moreover, La(OH)3@MMCH was employed to treat surface water with phosphate concentration of 1.90 mg/L and showed great removal efficiency of 95.21%. Actually, MMCH showed high surface charge density of 34.38-59.38 meq/kg in the pH range from 3.0 to 11.0 and great swelling ratio of 3014.57% within 24 h, indicating that MMCH could produce the enhanced Donnan membrane effect to pre-permeate phosphate. Furthermore, the bifunctional structure of La(OH)3@MMCH enabled it to capture phosphate through electrostatic attraction and ligand exchange. All the results prove that La(OH)3@MMCH is a promising adsorbent for eutrophication control and phosphate recovery.

The two-dimensional (2D) bulk photovoltaic effect (BPVE) is a cornerstone for future highly efficient 2D solar cells and optoelectronics. The ferromagnetic semiconductor 2H-FeCl2 is shown to realize a new type of BPVE in which spatial inversion (P), time reversal (T), and space-time reversal (PT) symmetries are broken (PT-broken). Using density functional theory and perturbation theory, we show that 2H-FeCl2 exhibits giant photocurrents, photo-spin-currents, and photo-orbital-currents under illumination by linearly polarized light. The injection-like and shift-like photocurrents coexist and propagate in different directions. The material also demonstrates substantial photoconductance, photo-spin-conductance, and photo-orbital-conductance, with magnitudes up to 4650 (nm{\cdot}{\mu}A/V2), 4620 (nm{\cdot}{\mu}A/V2 {\hbar}/2e), and 6450 (nm{\cdot}{\mu}A/V2 {\hbar}/e), respectively. Furthermore, the injection-currents, shift-spin-currents, and shift-orbital-currents can be readily switched via rotating the magnetizations of 2H-FeCl2. These results demonstrate the superior performance and intriguing control of a new type of BPVE in 2H-FeCl2., Comment: 12 pages, 5 figures. Accepted by Frontiers of Physics

Additional file 2. Fig. S1: Screening for somatic DNA contamination of the testicular germ cell (TGC) samples. Dotplots representing the mean methylation levels of MEST and H19 (left) and XIST and DDX4 (right) measured by deep bisulfite sequencing in 24 normal controls (CTR, teal) and 10 cryptozoospermic (CZ, purple) testicular germ cell (TGC) samples. Fig. S2: DNA methylation levels in imprinting control regions. A) Methylation levels of the 50 ICRs in the CTR and CZ samples. * Not imprinted according to this data, ** Possible polymorphism. B) Box plots showing the distribution of methylation levels of the 34 oocyte DMRs in the four CTR (teal) and four CZ testicular germ cell samples (purple). C) Comparison of the distributions of the average methylation levels of the 34 oocyte DMRs in the human embryonic stem cells (ESC, n = 2), the SSEA+ spermatogonial stem cells from Guo et al. [29] (SSC, n = 2), the primordial germ cells isolated from 7–19-week-old embryos datasets from Guo et al. [6] (PGC, n = 8) and the CTR and CZ testicular germ cell samples (TGC, n = 8, black). D) Comparison of the distribution of the methylation levels of the 34 oocyte DMRs in the eight primordial germ cells samples isolated from 7–19-week-old embryos [6]. Values can be found in Additional file 1: Table S5. Box plots elements are defined as follows: center line: median; box limits: upper and lower quartiles; whiskers: 1.5× interquartile range; points: outliers. Fig. S3: Global comparison of methylomes of control testicular germ cells and control sperm. A) Box plots showing the distribution of global methylation values in control testicular germ cells (CTR, n = 4, Additional file 1: Table S4) and sperm normal control samples (SP, n = 5, [16]). Statistical analysis showed difference between the two groups (Mann-Whitney U test). Box plots elements are defined as follows: center line: median; box limits: upper and lower quartiles; whiskers: 1.5× interquartile range; points: outliers. B) Violin plots showing the distribution of the mean methylation values for various genomic features in control testicular germ cells (CTR, n = 4) and sperm normal control samples (SP, n = 5, [16]). Promoters were defined as the 2,000 bp region around TSSs. GeneHancer regions refer to the DoubleElite regulatory elements. Repeats refer to elements from RepeatMasker. C) PCA generated for 1,350,244 CpG loci where all samples show methylation values. Only loci with minimum coverage of five in all samples and minimum mapping quality of 10 are considered. ESC, embryonic stem cells; SSC, spermatogonial stem cells [29]; PGC, primordial germ cells [6][5]; TGC, control testicular germ cells; SP, sperm [16]. Fig. S4: Global comparison of methylomes from control and cryptozoospermic testicular germ cells. A) Box plots showing the distribution of the global methylation values in control testicular germ cells (CTR) and cryptozoospermic testicular germ cells (CZ) (Additional file 1: Table S4). Statistical analysis showed no difference between the two groups (Mann-Whitney U test). Box plots elements are defined as follows: center line: median; box limits: upper and lower quartiles; whiskers: 1.5× interquartile range; points: outliers. B) Violin plots showing the distribution of the mean methylation values for various genomic features in control testicular germ cells (CTR, n = 4) and cryptozoospermic testicular germ cells (CZ, n = 4). Promoters were defined as the 2000 bp region around TSSs. GeneHancer regions refer to the DoubleElite regulatory elements. Repeats refer to elements from RepeatMasker. C) Distribution of the number (left) and total genomic size (right) of unmethylated (UMR) and low-methylated regions (LMR) obtained by segmenting CTR (teal, n = 4) and CZ methylomes (purple, n = 4) with MethylSeekR. Statistical analysis showed no difference between the two groups (Mann-Whitney U test). Fig. S5: Differentially methylation regions. A) Flow chart of the discovery of differentially methylated regions (DMRs) between the testicular germ cells from controls and cryptozoospermic men. DMRs were identified with camel, metilene and bsmooth requiring coverage of at least 4 CpGs, with at least 30% difference in methylation, minimum coverage of 5 reads and a maximum q-value of 0.05. Filters on the ranges of methylation values in CTR and CZ groups were further applied. B) Scatter plots showing the relation between the range of methylation values within the CTR and the CZ group for each DMR. DMRs are shown as black dots (included) or white dots (excluded) according to filters on the range of methylation values. Left: no range filters applied. Right: CTR and CZ ranges < 0.3. Numbers of considered DMRs are shown above. C) Cluster analyses of the methylation values of the 1,329 DMRs considered without range filters applied. CTR testicular germ cell samples in teal, CZ samples in purple. Arrows indicate a CZ sample clustering together with the CTR group. D) Number of DMRs from the 271 set that overlap specific functional genomic regions. Fig. S6: scRNA seq analysis. A) UMAP plot showing the integrated CTR-CZ germ cell dataset. The cells are colour-coded according to their knot group identity. Knot group 1 includes cells from undifferentiated spermatogonia to pachytene spermatocytes; Knot group 2 includes cells from pachytene spermatocytes to meiotic divisions; Knot group 3 includes cells from meiotic divisions to late spermatids. B) Schematic representation summarizing the results of the tradeSeq and MAST differential expression analyses. Red colour indicates significant down-regulation of a gene, whereas green indicates significant up-regulation. Fig. S7: IGV browser snapshots of WGBS data from control (CTR) and cryptozoospermic (CZ) testicular germ cells showing CTR-CZ DMRs associated with differentially expressed genes. Each DMR is shown as a red region either spanning the entire width (top panels) or with the surrounding genomic regions (lower panels). Only a subset of reads is shown for each sample. Methylated CpGs are shown in red and unmethylated CpGs in blue

Additional file 1: Table s1. Baseline characteristics comparison of patients with (n = 4805 ) and without (n = 9341 ) waist circumference measurements. Table s2. Age-stratified analysis of BMI and 1-year all-cause mortality. Table s3. Sex-stratified analysis of BMI and 1-year all-cause mortality. Table s4. Baseline characteristics and outcomes by BMI groups (BMI categories according to Chinese obesity working group). Table s5. Association of BMI with 1-year all-cause mortality in the entire cohort (BMI categories according to Chinese obesity working group).

Board localization within logs using image analysis approaches for traceability and quality assessment in sawmills EffiQuAss project ANR‐21‐CE10‐0002‐01

In many scenarios, 1) data streams are generated in real time; 2) labeled data are expensive and only limited labels are available in the beginning; 3) real-world data is not always i.i.d. and data drift over time gradually; 4) the storage of historical streams is limited and model updating can only be achieved based on a very short lookback window. This learning setting limits the applicability and availability of many Machine Learning (ML) algorithms. We generalize the learning task under such setting as a semi-supervised drifted stream learning with short lookback problem (SDSL). SDSL imposes two under-addressed challenges on existing methods in semi-supervised learning, continuous learning, and domain adaptation: 1) robust pseudo-labeling under gradual shifts and 2) anti-forgetting adaptation with short lookback. To tackle these challenges, we propose a principled and generic generation-replay framework to solve SDSL. The framework is able to accomplish: 1) robust pseudo-labeling in the generation step; 2) anti-forgetting adaption in the replay step. To achieve robust pseudo-labeling, we develop a novel pseudo-label classification model to leverage supervised knowledge of previously labeled data, unsupervised knowledge of new data, and, structure knowledge of invariant label semantics. To achieve adaptive anti-forgetting model replay, we propose to view the anti-forgetting adaptation task as a flat region search problem. We propose a novel minimax game-based replay objective function to solve the flat region search problem and develop an effective optimization solver. Finally, we present extensive experiments to demonstrate our framework can effectively address the task of anti-forgetting learning in drifted streams with short lookback., Comment: To appear in KDD 2022

Pre-pubertal females produce more oocytes than adult individuals, but the ability of oocytes to undergo embryonic development and produce viable offspring is less in pre-pubertal animals than in adult animals. Oocyte quality is associated with abnormal gene expression. To date, the transcriptome profiles of 1-month-old lamb oocytes after in vitro maturation (IVM) are poorly reported. This study aimed to identify differentially expressed genes (DEGs) in lamb oocytes with varying competencies, affecting oocyte competence. Using RNA sequencing (RNA developmental -seq) technology, the transcriptome profiles of 1-month-old lamb oocytes after IVM were assessed, and oocytes from adult sheep large follicles were used as controls. We found 11 up-regulated and 39 down-regulated DEGs in lamb oocytes. Gene Ontology analysis of DEGs showed that molecular functions were clustered in catalytic and binding activities, while biological processes were clustered in metabolic process, cellular process, single-organism process and biological regulation. Kyoto Encyclopedia of Genes and Genomes analysis showed that the DEGs were involved in oxidative phosphorylation, transforming growth factor-beta signalling pathway, or DNA replication. In lamb MII oocytes, down-regulation of oxidative phosphorylation genes (ATP5E, NDUFA7 and COX6C), thiol protease inhibitor (CSTB) and 26S proteasome component (SHFM1) and up-regulation of CUL1, MARCH7 and TRIM17 might cause low competence of lamb embryos. In conclusion, this study provided detailed information on mRNA transcriptomes in lamb oocytes after IVM, which offers insights into the reduced developmental potential of lamb oocytes.

The growth of the well-known fungus Ganoderma lucidum is influenced by temperature, which has an impact on the associated microbial structure in the substrate. In this study, we analyzed the bacterial diversity of the substrate at different temperatures using next-generation sequencing technology. A total of 513 733 sequences from 15 samples were assigned to 19 bacterial phyla. The samples were dominated by Proteobacteria, followed by Firmicutes; the 2 phyla exhibited opposite changes with elevated temperature. Bacterial genera showed different abundances at different temperatures, in which Sediminibacterium maintained a stable abundance below 40 °C, while Ochrobactrum and Rhodococcus were enriched with elevated temperature and both showed their highest abundances at 40 °C. Functional prediction uncovered 39 identified KEGG pathways, and bacterial genes involved in the membrane transport pathway exhibited the highest abundance subject to heat (40 °C) during the growth of G. lucidum. In general, our findings illustrated the influence of temperatures on G. lucidum mycelial morphology and the bacterial community in the substrate, and the results will facilitate cultivation of this fungus.

Herein, a type of syntactic foam, consisting of silicone-modified resin and hollow polymer microspheres, is developed and tested for the application of a composite cross-arm. The physical properties, electrical properties, and hydrolysis-resistance are tested and analyzed. Suitable microspheres can reduce the density of the syntactic foam to 46.63% of the resin. The dielectric strength of the syntactic foam decreases from 37.9 to 26.1 kV/mm with increasing microsphere content, which is still much higher than the operational requirement of 3 kV/mm. The water-absorption rate (

BackgroundSelf-management plays an important role in promoting and restoring mental health for individuals with mental health issues. However, there is no valid and reliable Chinese tool assessing the self-management behaviors of people with mood and anxiety disorders. This study aimed to develop a Chinese version of the Mental Health Self-management Questionnaire (MHSQ-C) and to verify its psychometric properties.MethodsA total of 440 potential participants were recruited by convenience sampling from June to August 2020. Item analysis and analyses of internal consistency, test-retest reliability, content validity, construct validity and criterion validity were performed.ResultsData from 326 participants were used. Three factors obtained via principal component analysis and varimax rotation explained 53.68% of the total variance. The average content validity index was 0.99. The Cronbach’s α coefficient (total: 0.874, clinical: 0.706, empowerment: 0.818, vitality: 0.830) and test-retest reliability (ICC: total: 0.783, 95% confidence interval (CI) [0.616, 0.882], clinical: 0.525, 95% CI [0.240, 0.725], empowerment: 0.786, 95% CI [0.622, 0.884], vitality: 0.748, 95% CI [0.564, 0.862]) were good. The MHSQ-C was well correlated with the Partners in Health scale and showed no floor or ceiling effect.DiscussionThe MHSQ-C is a reliable and valid tool to evaluate the self-management strategies of patients with mood and anxiety disorders.

Gastrodia elata is an entirely heterotrophic plant, the growth of which is completely reliant on Armillaria gallica, an orchid mycorrhizal fungus. To avoid damaging ecosystems, G. elata cultivation is shifting from woodland to farmland. However, whether the microbial community structure remains stable during this conversation is unknown. Here, we cultivated G. elata in woodland or farmland and found that woodland-cultivated G. elata produced a greater yield and larger tuber size. The relative abundance of Rahnella was 22.84- and 122.25-fold higher in woodland- and farmland-cultivated soil samples, respectively, than that in uncultivated soil samples. To investigate how Rahnella impacts the growth of G. elata and establishes symbiosis with Armillaria gallica, three Rahnella spp. strains (HPDA25, SBD3, and SBD11) were isolated from mycorrhizosphere soil samples. It was found that these strains, especially HPDA25, promoted the growth of A. gallica. Ultra-performance liquid chromatography coupled to a triple quadrupole mass spectrometry analysis detected the indole-3-acetic acid with 16.24 ng/ml in HPDA25 fermentation solution. Co-culturing with the strain HPDA25 or exogenous indole-3-acetic acid increased the branching and fresh weight of rhizomorphs and the growth rate and extracellular laccase activity of A. gallica, compared with A. gallica cultured alone. The results of RNA-seq and quantitative real-time polymerase chain reaction analysis showed that co-culturing A. gallica with HPDA25 increased the expression level of the genes including hydrophobin, SUR7/PalI family, and pectin methylesterase, whereas decreased the expression levels of glycolysis-related genes. Furthermore, co-culturing with the strain HPDA25, A. gallica promotes the growth of G. elata and enhances the tuber size of G. elata. These results provide new insights into an orchid mycorrhizal symbiosis and the cultivation of G. elata.

The superhydrophobic flower-like OTS-SiO2 particles with tunable size were synthesized for application in anti-icing technology, in which the nanosilica fibers were grown on surface of SiO2 sphere. Furthermore, the anti-icing process of flower-like OTS-SiO2 particles was investigated by a high speed video and thermal infrared imaging equipment. It was found that the flower-like OTS-SiO2 particles with a diameter of 300.0 nm showed best anti-icing ability, in which the frozen time of water droplets could be prolonged to 564.0 s at −25.0℃. The good anti-icing ability was attributed to micro-nano hierarchical structure and surface modification of flower-like OTS-SiO2 particles. The work has an important guiding implication for the subsequent design and preparation of superhydrophobic particles for application in anti-icing technology.

Objective To explore whether the red blood cell count multiplied by hematocrit index (RBCHct) in blood routine parameters can indicate the risk of impaired fasting blood glucose (IFG), and whether it is related to insulin resistance and inflammation. Methods In this cross-sectional study, previous history of diabetes was excluded, and people with normal and impaired IFG were included. We use Spearman analysis to evaluate the correlation between RBCHct index and fasting plasma glucose, insulin resistance homeostasis model assessment (HOMA-IR), and hypersensitive C-reactive protein (hs-CRP). Binary logistic regression analysis was used to evaluate the RBCHct index for assessing the potential risk of IFG, and the receiver operating characteristic (ROC) curve was used to evaluate the RBCHct index for diagnosing insulin resistance and chronic low-grade inflammatory efficacy among those with IFG. Results Correlation analysis showed that the RBCHct index and fasting plasma glucose (r=0.088, P=0.003); HOMA-IR (r=0.199, P

Thrombospondin (TSP1) plays an important role as an antiangiogenic factor in the reproductive system of female mammals. However, its expression and function in sheep are still unclear. In the present research, the Altay sheep (a native Chinese breed) was used to analyze the expression of TSP1 in the ovary and its potential function in granulosa cells. TSP1 was widely expressed in most tissues, as shown by qPCR. In the ovary, TSP1 mRNA expression decreased during follicular to luteal growth. The TSP1 protein was expressed in a wide variety of follicles of different diameters and localized to the cytoplasm and nucleus of granulosa cells. In

Embryo cryopreservation is an important tool to preserve endangered species. As a cryoprotectant for mouse oocytes, antifreeze protein from Anatolica polita (ApAFP914) has demonstrated utility. In the present study, the effects of controlled slow freezing and vitrification methods on the survival rate of sheep oocytes fertilized in vitro after freezing-thawing were compared. Different ApAFP914 concentrations were added to the vitrification liquid for exploring the effect of antifreeze protein on the warmed embryos. The results showed that the survival and hatching rates of in vitro derived embryos were significantly higher than that of the slow freezing method. Furthermore, among the cryopreserved embryos at different developmental stages, the survival and hatching rates of the expanded blastocyst were significantly higher than those of the blastocysts, early blastocysts and morula. The survival and the hatching rates of the fast-growing embryos were both significantly higher than that of the slow-growing embryos. Additionally, treatment of ApAFP914 (5–30 μg/mL) did not increase the freezing efficiency of the 6–6.5 d embryos. However, addition of 10 μg/mL of ApAFP914 significantly increased the hatching rate of slow-growing embryos. In conclusion, our study suggests that the vitrification is better than the slow freezing method for the conservation of in vitro sheep embryos, and supplementation of ApAFP914 (10 μg/mL) significantly increased the hatching rate of slow-growing embryos after cryopreservation.

Objective To investigate which plasma lipid parameters are useful for detecting chronic kidney disease (CKD) in a Chinese population without known CKD or renal impairment. Methods This was a prospective study. In southern Chinese cities from 2012 to 2013, a total of 1037 subjects aged ≥ 18 years old received a survey. Logistic regression and multiple linear regression analyses were performed. The lipid parameters studied included total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), non-high-density lipoprotein cholesterol (nHDL-C), TG/HDL-C ratio, TC/HDL-C ratio and nHDL-C/HDL-C ratio. Results After adjusting for confounding factors, the fourth percentile of logTG/HDL-C was observed to be an independent risk factor for CKD (OR = 2.453, P < 0.001), and the highest quantile of the logTG/HDL-C ratio was associated with a higher prevalence of CKD (P < 0.05). This risk was reduced when the model was adjusted with Insulin resistance (IR) (OR = 2.034, P < 0.05). In the group of women, glucose metabolism disorders, high uric acid, and obesity, this risk was increased. Multiple regression models showed that log TG and nonHDL-C/HDL-C were negatively correlated with eGFR (P < 0.05), while log TG and TC were positively correlated with logACR (P < 0.05). The area under the curve (ROC) of lgTG/HDL was 0.623 (p < 0.001). Conclusion The serum logTG/HDL-C ratio is the only suitable predictor of CKD, and IR may be the mechanism. This risk needs to be controlled in a specific population. Log TG and nonHDL-C/HDL-C were negatively correlated with eGFR, while log TG and TC were positively correlated with logACR.

Purpose To investigate the correlation between visceral obesity and pathogenesis of chronic kidney disease (CKD) among non-diabetic individuals, and to evaluate the potential of visceral adiposity index (VAI) as a predictor of CKD. Patients and Methods From December 2017 to March 2018, 1877 non-diabetic participants (male n=699, female n=1208) in southern China were recruited for a cross-sectional survey. Males and females were divided into four groups according to gender-specific quartiles of VAI scores. A logistic regression model was established to analyze the correlation between visceral adiposity index and CKD. Results Visceral adiposity index was positively correlated with CKD and was negatively associated with estimated glomerular filtration rate (eGFR). Using group one as the control, odds ratios (ORs) were calculated to determine the risk of developing CKD as VAI increased (male: group four 2.73 [P

Inflammation triggers secondary brain damage after stroke. The meninges and other CNS border compartments serve as invasion sites for leukocyte influx into the brain thus promoting tissue damage after stroke. However, the post-ischemic immune response of border compartments compared to brain parenchyma remains poorly characterized. Here, we deeply characterize tissue-resident leukocytes in meninges and brain parenchyma and discover that leukocytes respond differently to stroke depending on their site of residence. We thereby discover a unique phenotype of myeloid cells exclusive to the brain after stroke. These stroke-associated myeloid cells partially resemble neurodegenerative disease-associated microglia. They are mainly of resident microglial origin, partially conserved in humans and exhibit a lipid-phagocytosing phenotype. Blocking markers specific for these cells partially ameliorates stroke outcome thus providing a potential therapeutic target. The injury-response of myeloid cells in the CNS is thus compartmentalized, adjusted to the type of injury and may represent a therapeutic target. CA extern

Although substantial efforts have been made using graph neural networks (GNNs) for AI-driven drug discovery (AIDD), effective molecular representation learning remains an open challenge, especially in the case of insufficient labeled molecules. Recent studies suggest that big GNN models pre-trained by self-supervised learning on unlabeled datasets enable better transfer performance in downstream molecular property prediction tasks. However, they often require large-scale datasets and considerable computational resources, which is time-consuming, computationally expensive, and environmentally unfriendly. To alleviate these limitations, we propose a novel pre-training model for molecular representation learning, Bi-branch Masked Graph Transformer Autoencoder (BatmanNet). BatmanNet features two tailored and complementary graph autoencoders to reconstruct the missing nodes and edges from a masked molecular graph. To our surprise, BatmanNet discovered that the highly masked proportion (60%) of the atoms and bonds achieved the best performance. We further propose an asymmetric graph-based encoder-decoder architecture for either nodes and edges, where a transformer-based encoder only takes the visible subset of nodes or edges, and a lightweight decoder reconstructs the original molecule from the latent representation and mask tokens. With this simple yet effective asymmetrical design, our BatmanNet can learn efficiently even from a much smaller-scale unlabeled molecular dataset to capture the underlying structural and semantic information, overcoming a major limitation of current deep neural networks for molecular representation learning. For instance, using only 250K unlabelled molecules as pre-training data, our BatmanNet with 2.575M parameters achieves a 0.5% improvement on the average AUC compared with the current state-of-the-art method with 100M parameters pre-trained on 11M molecules., Comment: 11 pages, 3 figures

Additional file 2: Supplementary Methods.

Deep neural networks (DNN) are a promising tool in medical applications. However, the implementation of complex DNNs on battery-powered devices is challenging due to high energy costs for communication. In this work, a convolutional neural network model is developed for detecting atrial fibrillation from electrocardiogram (ECG) signals. The model demonstrates high performance despite being trained on limited, variable-length input data. Weight pruning and logarithmic quantisation are combined to introduce sparsity and reduce model size, which can be exploited for reduced data movement and lower computational complexity. The final model achieved a 91.1% model compression ratio while maintaining high model accuracy of 91.7% and less than 1% loss.

Additional file 4: Figure S1. Flow cytometry of B cells. Figure S2. Flow cytometry of T cells. Figure S3. Flow cytometry of T cell exhaustion markers. Figure S4. Histologies of PCNSL and glioblastoma biopsies. Figure S5. Patient characteristics of patient 1. Figure S6. Chemokines in DLBCL and PCNSL. Figure S7. Spatial transcriptomics in PCNSL

Using smart wearable devices to monitor patients electrocardiogram (ECG) for real-time detection of arrhythmias can significantly improve healthcare outcomes. Convolutional neural network (CNN) based deep learning has been used successfully to detect anomalous beats in ECG. However, the computational complexity of existing CNN models prohibits them from being implemented in low-powered edge devices. Usually, such models are complex with lots of model parameters which results in large number of computations, memory, and power usage in edge devices. Network pruning techniques can reduce model complexity at the expense of performance in CNN models. This paper presents a novel multistage pruning technique that reduces CNN model complexity with negligible loss in performance compared to existing pruning techniques. An existing CNN model for ECG classification is used as a baseline reference. At 60% sparsity, the proposed technique achieves 97.7% accuracy and an F1 score of 93.59% for ECG classification tasks. This is an improvement of 3.3% and 9% for accuracy and F1 Score respectively, compared to traditional pruning with fine-tuning approach. Compared to the baseline model, we also achieve a 60.4% decrease in run-time complexity., 4 pages

OBJECTIVE: To investigate the effect of aqueous extract of Astragalus membranaceus on cognitive ability of rats living at high altitude. METHODS: Rats were exposed to a simulated high-altitude hypobaric hypoxia chamber. The behavior of rats was tested by eight-arm maze. The contents of malondialdehyde (MDA), glutathione (GSH), reactive oxygen species (ROS) and activity of total superoxide dismutase (T-SOD) in hippocampus were measured. The expressions of mammalian target of rapamycin (mTOR) and cleaved capase-3 in hippocampus were determined by reverse transcription-polymerase chain reaction and Western blot. RESULTS: The behavioral cognitive ability of the hypoxic control group was significantly lower than that of the normoxic control group. Under hypoxic environment, after the administration of aqueous extract of Astragalus membranaceus, the behavioral cognitive ability of rats was significantly improved. In hippocampal tissue, the content of MDA and ROS were significantly decreased, while the content of GSH and activity of T-SOD in hippocampus were significantly increased. The mRNA expression of mTOR and P70S6K and the protein expression of p-mTOR were significantly increased; the mRNA expression of 4E-binding protein 1 (4E-BP1) and the protein expression of phosphorylated-4E-BP1 (p-4E-BP1) and cleaved capase-3 were significantly decreased. CONCLUSION: When the rats are exposed to high altitude hypoxia, the behavioral cognitive ability could be significantly reduced. Aqueous extract of Astragalus membranaceus can significantly improve cognitive function in rats under hypoxia. The potential mechanism is related to improving oxidative stress, reducing the accumulation of free radicals and metabolites, and activating mTOR signaling pathway.

Purpose Metabolic syndrome (MetS), which is a global public health problem, is a state of chronic low-grade inflammation. This study looked at the changes in hematological parameters and the predictive value of the lymphocyte to high-density lipoprotein cholesterol (HDL-C) ratio (LHR) as a new index in subjects with and without MetS in coastal cities in southern China. Patients and methods In this cross-sectional study, there were 852 participants (n = 598 with MetS and n = 254 without MetS). MetS was defined in accordance with the National Cholesterol Education Program, Adult Treatment Panel III (NCEP-ATP III) criteria. Results MetS was positively correlated with white blood cell count, total lymphocyte count, neutrophil count, red blood cell count, hematocrit, hemoglobin, and high-sensitivity C-reactive protein levels (p

Triploid loquat (2n = 3x = 51) has stronger growth vigor and larger leaves, flowers, and fruit compared with its diploid parental plant (2n = 2x = 34), but the effects of triploidization on the contents of flavonoids and phenolics in leaves and flowers, which are the most important antioxidant compounds for pharmacological applications, have not been reported. In this report, 58 triploid loquat genotypes and seven corresponding diploid parental cultivars were used to evaluate the effects of triploidization on the contents of total flavonoids and phenolics and the antioxidant activities of leaves and flower buds. The results showed that the contents of total flavonoids and phenolics and their corresponding antioxidant activities were higher in most of the triploid loquat genotypes than their diploid parents. The antioxidant activities of leaves and flower buds were significantly correlated with the total flavonoids and phenolics contents in both diploid loquat and triploid loquat. It could be inferred that triploidization could increase the contents of flavonoids and phenolics in leaves and flower buds of loquat. Notably, the contents of total flavonoids and phenolics of leaves in triploid genotype ‘H3/24’ were the highest, reaching 212.00 mg rutin equivalent (RE)/g DW and 93.06 mg gallic acid equivalents (GAE)/g DW, respectively, which were significantly higher than those previously reported. Such a valuable trait may be stacked with other triploid traits that are already established, such as larger vegetative organs and better tolerance to various stresses, as a feasible strategy for breeding loquat cultivars with high pharmaceutical potency.

Auricularia cornea is a widely cultivated edible fungus with substantial nutritive value. This study aimed to enrich the multifunctional bionutrient element selenium in A. cornea to improve its quality and explore the accumulation of selenium in the fungus using high-throughput RNA-Seq technology. In general, the treatment group with a 100 µg/g supply of selenium outperformed the other treatment groups in terms of high yield, rich crude polysaccharides and a high total selenium concentration. Additional evidences demonstrated the budding and mature phases were two typical growth stages of A. cornea and were important for the accumulation of selenium. Therefore, the budding and mature phase tissues of A. cornea in the treatment group with a 100 µg/g supply of selenium were used for transcriptome analysis and compared to those of a control group that lacked additional selenium. A total of 2.56 × 105 unigenes from A. cornea transcriptome were assembled and annotated to five frequently used databases including NR, GO, KEGG, eggNOG and SwissProt. GO and KEGG pathway analysis revealed that genes involved in metabolic process and translation were up-expressed at the budding stage in response to selenium supplementation, including amino acid metabolism, lipid metabolism, ribosome. In addition, the differential gene expression patterns of A. cornea suggested that the up-expressed genes were more likely to be detected at the budding stage than at the mature stage. These results provide insights into the transcriptional response of A. cornea to selenium accumulation.

Near-infrared fluorescence immunoassay has been widely studied in the bio analytical field. This review mainly introduces the basic principles of near-infrared spectroscopy and near-infrared detection technology, and summarizes the properties, characteristics and recent improvement of optical properties and signal intensity of three near-infrared fluorescence probes (i.e. organic fluorophores, quantum dots and rare earth compounds). We describe the applications of near-infrared fluorescence technology in immunoassay, and prospect the application potential of lateral flow assay (LFA) based on this probe in the rapid detection of pathogens. Our team intends to establish a new platform which has highly sensitive near-infrared fluorescence probes (NIFPs) combined with portable and simple immunochromatographic test strips (ICTSs) for rapid detection of food borne viruses. This will provide technical support for a rapid detection on the port.

Here, we investigated the influence of Chinese white truffle (Tuber panzhihuanense) symbioses on the microbial communities associated with Corylus avellana during the early development stage of symbiosis. The microbial communities associated with ectomycorrhizae, and associated with roots without T. panzhihuanense colonization, were determined via high-throughput sequencing of bacterial 16S rRNA genes and fungal ITS genes. Microbial community diversity was higher in the communities associated with the ectomycorrhizae than in the control treatment. Further, bacterial and fungal community structures were different in samples containing T. panzhihuanense in association with C. avellana compared to the control samples. In particular, the bacterial genera Rhizobium, Pedomicrobium, and Herbiconiux were more abundant in the ectomycorrhizae, in addition to the fungal genus Monographella. Moreover, there were clear differences in some physicochemical properties among the rhizosphere soils of the two treatments. Statistical analyses indicated that soil properties including exchangeable magnesium and exchangeable calcium prominently influenced microbial community structure. Lastly, inference of bacterial metabolic functions indicated that sugar and protein metabolism functions were significantly more enriched in the communities associated with the ectomycorrhizae from C. avellana mycorrhized with T. panzhihuanense compared to communities from roots of cultivated C. avellana without T. panzhihuanense. Taken together, these results highlight the interactions among ectomycorrhizal fungi, soil properties, and microbial communities that are associated with host plants and further our understanding of the ecology and cultivation of the economically important T. panzhihuanense truffles.

This paper is bases on the data of fund holding stocks held by equity funds from 2013 to 2017 in China’s stock market, empirically analyzing whether the investment behaviors of mutual funds follow value investment that improve fund performance in both bull and bear markets. The research indicates that there exists a significant difference in the correlation between industry concentration and fund performance in the bear and bull markets. Specifically, industry concentration and fund performance is negatively correlated in the bull market and is positively correlated in the bear market. The empirical results indicate that stock market in China demonstrates the phenomenon that “the bear market follows value investment while the bull market ignores value investment” to a certain extent. It is illustrated that fund investment behaviors in the bear market fundamentally meet the standards of value investment and illustrate that mutual funds have a certain ability to extract valuable information. However, fund managers in China tend to concentrate their holdings in a few industries in the bull market with the aim to gain high returns. The excessively concentrated investment strategies not only fail to bring them excess returns, but also reduce their performance. Therefore, fund managers should maintain conservative and prudent investment strategies when constructing portfolios and should not over-concentrate on specific industries.

Additional file 1.

Supplemental material, sj-pdf-1-asp-10.1177_00037028211022375 for A Lanthanide Complex Fluorescent Probe for the Detection of Melamine by Xiaolin Li, Chaoqun Ma, Lei Li, Hui Gao, Jiao Gu, Chun Zhu, Yamin Wu, Senqi Guo, Yitao Wei, Guoyu Wang, Zirui Wang and Guoqing Chen in Applied Spectroscopy

Additional file 1.

In this short article, we mainly prove that, for any spectral operator $A$ of type $m$ on a complex Hilbert space, if a bounded operator $B$ lies in the collection of bounded linear operators that are in the $k$-centralizer of every bounded linear operator in the $l$-centralizer of $A$, where $k\leqslant l$ is two arbitrary positive integers satisfying $l\geqslant k$ as well as $l\geqslant 2m+1$, then $B$ must belong to the von Neumann algebra generated by $A$ and identity operator. This result generalizes a matrix commutator theorem proved by M.\ F.\ Smiley. For this aim, Smiley-type operators are defined and studied., Comment: 10 pages

Federated learning allows distributed devices to collectively train a model without sharing or disclosing the local dataset with a central server. The global model is optimized by training and averaging the model parameters of all local participants. However, the improved privacy of federated learning also introduces challenges including higher computation and communication costs. In particular, federated learning converges slower than centralized training. We propose the server averaging algorithm to accelerate convergence. Sever averaging constructs the shared global model by periodically averaging a set of previous global models. Our experiments indicate that server averaging not only converges faster, to a target accuracy, than federated averaging (FedAvg), but also reduces the computation costs on the client-level through epoch decay.

Additional file 2.

In the present study, the mitogenome of Tuber calosporum was assembled and analyzed. The mitogenome of T. calosporum comprises 15 conserved protein-coding genes, two rRNA genes, and 14 tRNAs, with a total size of 287,403 bp. Fifty-eight introns with 170 intronic open reading frames were detected in the T. calosporum mitogenome. The intronic region occupied 69.41% of the T. calosporum mitogenome, which contributed to the T. calosporum mitogenome significantly expand relative to most fungal species. Comparative mitogenomic analysis revealed large-scale gene rearrangements occurred in the mitogenome of T. calosporum, involving gene relocations and position exchanges. The mitogenome of T. calosporum was found to have lost several tRNA genes encoding for cysteine, aspartate, histidine, etc. In addition, a pair of fragments with a total length of 32.91 kb in both the nuclear and mitochondrial genomes of T. calosporum was detected, indicating possible gene transfer events. A total of 12.83% intragenomic duplications were detected in the T. calosporum mitogenome. Phylogenetic analysis based on mitochondrial gene datasets obtained well-supported tree topologies, indicating that mitochondrial genes could be reliable molecular markers for phylogenetic analyses of Ascomycota. This study served as the first report on mitogenome in the family Tuberaceae, thereby laying the groundwork for our understanding of the evolution, phylogeny, and population genetics of these important ectomycorrhizal fungi.

News text is often divided into two parts: title and content. In the research of news text classification, many studies have not considered the characteristics of news text classification. It is unscientific to merge the title and content as input hastily. The title is of great value to news text, and its importance is ignored in text classification, which has a certain impact on the classification effect. Aiming at this problem, this article designs a word vector weighting method based on attention mechanism, and builds a bidirectional long short memory neural network (BiLSTM) model for text classification. The experimental results show that BiLSTM news text classification with the introduction of attention mechanism improves the classification effect.

In recent years, Generative Adversarial Network (GAN) has quickly become the most popular deep generative model framework, and it is also the most popular topic in the current deep learning research field. Although the generative adversarial network has achieved remarkable results from text description to image generation, when a complex image containing multiple objects, the position of each object will be blurred and overlapped, and the edges of the generated image will be blurred and local textures will be unclear. Usually given text description can generate the corresponding rough image, but there are still some problems in the image details. In order to solve the above problems, on the basis of Stack GAN, a scene graph-based stacked generative confrontation network model (Scene graph stack GAN, SGS-GAN) is proposed, which converts the text description into The scene graph uses the scene graph as the condition vector and inputs the random noise into the generator model to obtain the result image. The experimental results show that the Inception store of the SGS-GAN model on the Visual Genome and COCO data sets reached 6.64 and 6.52, respectively, which were increased by 0.212 and 0.219 compared to Sg2Im. This proves that the diversity and vividness of the generated samples and the sharpness of the image are obviously improved after the number of times of training and the input of the scene graph.

The advent of low-cost wearable Internet of Things (IoT) sensors has made it possible to continuously acquire physiological signals such as electrocardiogram (ECG) for long durations. Techniques for automated analysis is essential for deriving intelligence from such a large quantity of data. This paper presents a 1-dimenslonal convolutional neural network (CNN) for heartbeat classification from ECG signals obtained from an ambulatory device. The proposed technique can classify heartbeats into 5 classes as specified in AAMI standard and was tested using the Physionet MIT-BIH Arrhythmia database. To address the imbalance of classes in the dataset we used the SMOTE algorithm to augment the dataset. The network was trained using the augmented data and achieved an accuracy of 98.12%, sensitivity of 98.07%, and a specificity of 98.29%.

A triploid was obtained from loquat (Eriobotrya japonica cv. ‘Ninghaibai’) (2n = 2x = 34) × bronze loquat (Eriobotrya deflexa, 2n = 2x = 34). The leaves of the triploid had no petioles, similar to the female parent, and its stipules were obvious and dark green, similar to those of the male parent. There were signals of male parent DNA on ten chromosomes of the triploid according to genomic in situ hybridization (GISH) when DNA of bronze loquat was used as probe; the diploid hybrid also had ten chromosomes with signals of male parent DNA. All five selected simple sequence repeats (SSR) primers amplified specific loci of both parents. In particular, primer CH04c06 amplified both specific loci of the female parent but only amplified one specific locus of the male parent. The results of GISH and SSR marker analysis indicated that the 2n gamete which formed the triploid was from first-division restitution or pre-meiotic doubling of the female parent cv. ‘Ninghaibai’. The allotriploid can be used to breed seedless loquat germplasm with different flowering times from loquat directly or to breed new germplasm containing a few genomic components from bronze loquat, such as monosomic alien addition lines, monosomic alien substitution lines, and introgression lines. This is the first report of allotriploid in the genus Eriobotrya and it will provide a basis for breeding new loquat germplasms by distant hybridization and provide an ideal material for breeding new loquat varieties with different flowering time or time to maturity.

Ling Feng,* Haishan Chen,* Jianhui Chen, Chongxiang Xiong, Xiaofei Shao, Xin Wang, Jing Ning, Zhicong Xiang, Xuan Wang, Tong Chen, Hua Xiao, Hongjuan Tang, Xiaolin Li, Guobao Hong, Hequn Zou Department of Nephrology, The Third Affiliated Hospital, Southern Medical University, Guangzhou 510630, People’s Republic of China*These authors contributed equally to this work.Correspondence: Hequn Zou; Xiaofei ShaoDepartment of Nephrology, The Third Affiliated Hospital, Southern Medical University, 183, Zhongshan West Avenue, Tianhe District, Guangzhou 510630, People’s Republic of ChinaEmail Hequnzou@hotmail.com; 413151187@qq.comObjective: To explore whether the red blood cell count multiplied by hematocrit index (RBCHct) in blood routine parameters can indicate the risk of impaired fasting blood glucose (IFG), and whether it is related to insulin resistance and inflammation.Methods: In this cross-sectional study, previous history of diabetes was excluded, and people with normal and impaired IFG were included. We use Spearman analysis to evaluate the correlation between RBCHct index and fasting plasma glucose, insulin resistance homeostasis model assessment (HOMA-IR), and hypersensitive C-reactive protein (hs-CRP). Binary logistic regression analysis was used to evaluate the RBCHct index for assessing the potential risk of IFG, and the receiver operating characteristic (ROC) curve was used to evaluate the RBCHct index for diagnosing insulin resistance and chronic low-grade inflammatory efficacy among those with IFG.Results: Correlation analysis showed that the RBCHct index and fasting plasma glucose (r=0.088, P=0.003); HOMA-IR (r=0.199, P< 0.001); and hs-CRP (r=0.097, P=0.001) were positively correlated. After adjusting for confounding factors, the risk of IFG in the third and fourth quartiles of the RBCHct index increased to 1.889 and 3.048 times. The area under the ROC curve of the RBCHct index for diagnosis of insulin resistance state (HOMA-IR) was 0.695 (p< 0.001), and the area under the ROC curve of the RBCHct index for the diagnosis of chronic low-inflammatory state (hs-CRP) was 0.641 (P=0.010).Conclusion: The RBCHct index may be a potential indicator for assessing the risk of prediabetes and is closely related to whether the body is in a state of insulin resistance and inflammation under IFG.Keywords: diabetes mellitus, erythrocyte, RBCHct index, insulin resistance, inflammation

To leverage enormous unlabeled data on distributed edge devices, we formulate a new problem in federated learning called Federated Unsupervised Representation Learning (FURL) to learn a common representation model without supervision while preserving data privacy. FURL poses two new challenges: (1) data distribution shift (Non-IID distribution) among clients would make local models focus on different categories, leading to the inconsistency of representation spaces. (2) without the unified information among clients in FURL, the representations across clients would be misaligned. To address these challenges, we propose Federated Constrastive Averaging with dictionary and alignment (FedCA) algorithm. FedCA is composed of two key modules: (1) dictionary module to aggregate the representations of samples from each client and share with all clients for consistency of representation space and (2) alignment module to align the representation of each client on a base model trained on a public data. We adopt the contrastive loss for local model training. Through extensive experiments with three evaluation protocols in IID and Non-IID settings, we demonstrate that FedCA outperforms all baselines with significant margins.