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Background We compared the diagnostic performance of the short five-item and full seven-item Mini Sarcopenia Risk Assessment Questionnaire (MSRA-5 and MSRA-7) against the Strength, Assistance walking, Rise from a chair, Climb stairs, and Falls (SARC-F) and SARC-F with calf circumference (SARC-CalF) scales for sarcopenia in healthy community-dwelling older adults. Methods We conducted a post-hoc cross-sectional secondary data analysis of a prospective cohort study, using data from 230 older adults (mean age 67.2±7.4 years, 92% Chinese, and 73% female) from the “Longitudinal Assessment of Biomarkers for characterization of early Sarcopenia and Osteosarcopenic Obesity in predicting frailty and functional decline in community-dwelling Asian older adults Study” (GeriLABS-2) conducted between December 2017 and March 2019 in Singapore. We performed receiver operating characteristic curve analysis to ascertain the area under the curve (AUC) for sarcopenia diagnosis using the Asian Working Group for Sarcopenia 2019 consensus criteria. We applied the DeLong method to compare the AUCs of the four instruments. Results The MSRA-5 and MSRA-7 demonstrated poor diagnostic performance (AUC of 0.511, 95% confidence interval [CI] 0.433–0.589 and AUC of 0.526, 95% CI 0.445–0.606, respectively), compared to that in SARC-CalF (AUC of 0.739, 95% CI 0.671–0.808) and SARC-F (AUC of 0.564, 95% CI 0.591–0.636). The SARC-CalF demonstrated significantly superior discriminatory ability compared to that in the SARC-F, MSRA-5, and MSRA-7 (all p

Summary: Circadian rhythms are internal biological rhythms driving temporal tissue-specific, metabolic programs. Loss of the circadian transcription factor BMAL1 in the paraventricular nucleus (PVN) of the hypothalamus reveals its importance in metabolic rhythms, but its functions in individual PVN cells are poorly understood. Here, loss of BMAL1 in the PVN results in arrhythmicity of processes controlling energy balance and alters peripheral diurnal gene expression. BMAL1 chromatin immunoprecipitation sequencing (ChIP-seq) and single-nucleus RNA sequencing (snRNA-seq) reveal its temporal regulation of target genes, including oxytocin (OXT), and restoring circulating OXT peaks in BMAL1-PVN knockout (KO) mice rescues absent activity rhythms. While glutamatergic neurons undergo day/night changes in expression of genes involved in cell morphogenesis, astrocytes and oligodendrocytes show gene expression changes in cytoskeletal organization and oxidative phosphorylation. Collectively, our findings show diurnal gene regulation in neuronal and non-neuronal PVN cells and that BMAL1 contributes to diurnal OXT secretion, which is important for systemic diurnal rhythms.

Objective The maximum operating pressure for underground gas storage facilities designed for oil and gas reservoirs, both constructed and under construction in China, is currently set at the original formation pressure. There have yet to be successful cases of overpressure operation, which significantly impacts the economic benefits of converting depleted oil and gas reservoirs into underground gas storage facilities. This article aims to evaluate the maximum operating pressure and storage capacity of the Nanpu 1-29 gas storage facility from the perspective of the ultimate bearing capacity of cap layers and faults, with the goal of effectively enhancing the construction benefits of the facility. Methods The evaluation of the maximum operating pressure for the Nanpu 1-29 gas storage facility in eastern Hebei is based on the minimum principal stress measured in situ in the mining wells. Different effective porosity calculation methods are employed to quantitatively evaluate the effective storage capacity of gas and oil reservoirs, as well as the incremental capacity after pressure boosting operation, based on their development differences. Results The evaluation of the maximum operating pressure for the Nanpu 1-29 gas storage facility indicates that the minimum principal stress of the cap layers determined by the in-situ measurements in the mining wells is 34.00 MPa. Based on the tensile failure criteria determined by the minimum principal stress, the maximum operating pressure for the tensile failure of the cap layer is 27.20 MPa. Combined with the maximum safe injection pressure corresponding to shear failure of the cap layer (30.60 MPa) and the maximum safe injection pressure corresponding to unstable slip of the fault (27.60 MPa), the final maximum operating pressure for the Nanpu 1-29 gas storage facility is determined to be 27.20 MPa. Based on the effective storage capacity calculation model, considering factors such as the water content of the gas reservoir, residual water and edge porosity as well as the coefficient of influence, the efficiency of gas-driven fluid, and the utilization rate of oil-containing space, the maximum operating pressure increased from the original formation pressure of 22.50 MPa to 27.20 MPa. The practical storage capacity of the gas storage facility increased from 15.46×108 m3 to 18.14×108 m3, an increase of approximately 17.3%. Conclusion (1) The construction of gas storage facilities can be re-evaluated for the maximum operating pressure based on the minimum principal stress measured in situ in the mining wells, and overpressure design can be conducted under appropriate conditions. (2) Overpressure design can effectively increase storage capacity and improve the economic benefits of reservoir construction. Significance The research results have a certain reference value for the quantitative evaluation of the maximum operating pressure and storage capacity of other underground gas storage facilities, and are expected to significantly improve the economic benefits of overpressure-designed reservoir-type gas storage facilities in China.

Background Frailty is prevalent in acute care and is associated with negative outcomes. While a comprehensive geriatric assessment to identify geriatric syndromes is recommended after identifying frailty, more evidence is needed to support this approach in the inpatient setting. This study examined the association between frailty and geriatric syndromes and their impact on outcomes in acutely admitted older adults. Methods A total of 733 individuals aged ≥65 years admitted to the General Surgery Service of a tertiary hospital were assessed for frailty using the Clinical Frailty Scale (CFS) and for geriatric syndromes using routine nursing admission assessments, including cognitive impairment, falls, incontinence, malnutrition, and poor oral health. Multinomial logistic regression and Cox regression were used to evaluate the associations between frailty and geriatric syndromes and their concomitant impact on hospital length of stay (LOS) and 30-day readmissions. Results Greater frailty severity was associated with an increased likelihood of geriatric syndromes. Individuals categorized as CFS 4–6 and CFS 7–8 with concomitant geriatric syndromes had 29% and 35% increased risks of a longer LOS, respectively. CFS 4–6 was significantly associated with functional decline (relative risk ratio =1.46; 95% confidence interval [CI], 1.03–2.07) and 30-day readmission (hazare ratio=1.78; 95% CI, 1.04–3.04), whereas these associations were not significant for CFS 7–8. Conclusions Geriatric syndromes in frail individuals can be identified from routine nursing assessments and represent a potential approach for targeted interventions following frailty identification. Tailored interventions may be necessary to achieve optimal outcomes at different stages of frailty. Further research is required to evaluate interventions for older adults with frailty in a wider hospital context.

At present, in order to improve the performance of spiral groove mechanical seals, the structural parameters of seals are mostly adjusted based on the experience of designers. The integration degree of existing mechanical seal performance research examples is low, and the whole performance optimization process lacks of scientific theoretical framework to guide. In order to solve this problem, combining the axiomatic design theory with the existing mechanical seal performance research, a structural optimization method of spiral groove mechanical seal based on axiomatic design theory was put forward. This method defines the mapping relationship between the three-level functional requirement domain and the design parameter domain of the spiral groove mechanical seal, and thus develops 14×14 diagonal optimization matrix. The research results show that the introduction of axiomatic design provides a basic theoretical framework for the performance optimization of spiral groove mechanical seals and decomposes the optimization process into several design modules, which improves the efficiency and accuracy of the optimization design of spiral groove mechanical seals and has good application value.

Klebsiella pneumoniae is a pathogen that commonly causes hospital-acquired infections. Bacterial biofilms are structured bacterial communities that adhere to the surface of objects or biological tissues. In this study, we investigated the genome homology and biofilm formation capacity of ESBL-producing K. pneumoniae. Thirty ESBL-producing K. pneumoniae isolates from 25 inpatients at Ruijin Hospital, Shanghai, were subjected to pulsed-field gel electrophoresis (PFGE) to estimate genomic relatedness. Based on the chromosomal DNA patterns we obtained, we identified 21 PFGE profiles from the 30 isolates, eight of which had high homology indicating that they may have genetic relationships and/or potential clonal advantages within the hospital. Approximately 84% (21/25) of the clinical patients had a history of surgery, urinary tract catheterization, and/or arteriovenous intubation, all of which may have increased the risk for nosocomial infections. Biofilms were observed in 73% (22/30) of the isolates and that strains did not express type 3 fimbriae did not have biofilm formation capacity. Above findings indicated that a high percentage of ESBL-producing K. pneumoniae isolates formed biofilms in vitro and even though two strains with cut-off of PFGE reached 100% similarity, they generated biofilms differently. Besides, the variability in biofilm formation ability may be correlated with the expression of type 3 fimbriae. Thus, we next screened four ESBL-producing K. pneumoniae isolates (Kpn5, Kpn7, Kpn11, and Kpn16) with high homology and significant differences in biofilm formation using PFGE molecular typing, colony morphology, and crystal violet tests. Kpn7 and Kpn16 had stronger biofilm formation abilities compared with Kpn5 and Kpn11. The ability of above four ESBL-producing K. pneumoniae isolates to agglutinate in a mannose-resistant manner or in a mannose-sensitive manner, as well as RNA sequencing-based transcriptome results, showed that type 3 fimbriae play a significant role in biofilm formation. In contrast, type 1 fimbriae were downregulated during biofilm formation. Further research is needed to fully understand the regulatory mechanisms which underlie these processes.

Current antimicrobial susceptibility testing (AST) requires 16-24 hours, delaying initiation of appropriate antibiotics. Hence, there is a need for rapid AST. This study aims to develop and evaluate the feasibility of a rapid flow cytometric AST assay to determine minimum inhibitory concentration (MIC) for carbapenem-resistant Acinetobacter baumannii (CRAB). Antibiotic exposure causes increased intracellular reactive oxygen species (ROS) in bacteria. We hypothesized that ROS can be used as a marker to determine MIC. We assessed three CRAB clinical isolates across fifteen antibiotics at various concentrations in a customized 96-well microtiter plate. The antibiotics assessed include amikacin, beta-lactams (ampicillin/sulbactam, aztreonam, cefepime, ceftolozane/tazobactam, doripenem, imipenem, meropenem, and piperacillin/tazobactam), levofloxacin, polymyxin B, rifampicin, trimethoprim/sulfamethoxazole, and tetracyclines (tigecycline and minocycline). These clinical CRAB isolates were assessed for ROS after antibiotic treatment. Increased ROS levels indicated by increased RedoxSensorTM Green (RSG) fluorescence intensity was assessed using flow cytometry (FCM). MIC was set as the lowest antibiotic concentration that gives a ≥1.5-fold increase in mode RSG fluorescence intensity (MICRSG). Accuracy of MICRSG was determined by comparing against microtiter broth dilution method performed under CLSI guidelines. ROS was deemed accurate in determining the MICs for β-lactams (83.3% accuracy) and trimethoprim/sulfamethoxazole (100% accuracy). In contrast, ROS is less accurate in determining MICs for levofloxacin (33.3% accuracy), rifampicin (0% accuracy), amikacin (33.3% accuracy), and tetracyclines (33.3% accuracy). Collectively, this study described an FCM-AST assay to determine antibiotic susceptibility of CRAB isolates within 5 hours, reducing turnaround time up to 19 hours.

Abstract Aim The aim of this review was to determine the effectiveness of the e‐learning programs for improving the knowledge and professional practices of nursing personnel in managing pressure injuries patients. Design Systematic review and meta‐analysis. Methods Systematic search was done in EMBASE, SCOPUS, Cochrane library, MEDLINE, Google Scholar, ScienceDirect and Clinicaltrials.gov databases until August 2022. Meta‐analysis was carried out using random‐effects model, and the results were reported as pooled standardized mean differences (SMD), or odds ratios (OR) with 95% confidence intervals (CIs). Results Eight studies were included in the analysis. Most of the studies had higher risk of bias. The pooled SMD for knowledge score and for the classification skill were 1.40 (95%CI: 0.45–2.35; I2 = 93.1%) and 1.75 (95%CI: 0.94–3.24; I2 = 78.3%) respectively. The pooled OR for the classification skills was 1.75 (95%CI: 0.94–3.24; I2 = 78.3%). Patient or Public Contribution No patient or public contribution.

Abstract Background Maize (Zea mays L.) is one of the most important crops worldwide. Although sophisticated maize gene regulatory networks (GRNs) have been constructed for functional genomics and phenotypic dissection, a multi-omics GRN connecting the translatome and transcriptome is lacking, hampering our understanding and exploration of the maize regulatome. Results We collect spatio-temporal translatome and transcriptome data and systematically explore the landscape of gene transcription and translation across 33 tissues or developmental stages of maize. Using this comprehensive transcriptome and translatome atlas, we construct a multi-omics GRN integrating mRNAs and translated mRNAs, demonstrating that translatome-related GRNs outperform GRNs solely using transcriptomic data and inter-omics GRNs outperform intra-omics GRNs in most cases. With the aid of the multi-omics GRN, we reconcile some known regulatory networks. We identify a novel transcription factor, ZmGRF6, which is associated with growth. Furthermore, we characterize a function related to drought response for the classic transcription factor ZmMYB31. Conclusions Our findings provide insights into spatio-temporal changes across maize development at both the transcriptome and translatome levels. Multi-omics GRNs represent a useful resource for dissection of the regulatory mechanisms underlying phenotypic variation.

The natural color of biological specimens plays a crucial role in body protection, signaling, physiological adaptations, etc. Full-color optical sectioning structured illumination microscopy (OS-SIM) color is a promising approach that can reconstruct biological specimens in three-dimension meanwhile maintaining their natural color. Full-color OS-SIM takes the advantages of rapid imaging speed, compatibility with fluorescence and non-fluorescence samples, compact configuration, and low cost. However, the commonly used HSV-RMS reconstruction algorithm for full-color OS-SIM faces two issues to be improved. One is the RMS (root-mean-square) OS reconstruction algorithm is prone to background noise, and the other is the reconstruction is bound in RGB and HSV color spaces, consuming more reconstructing time. In this paper, we propose a full-color Fourier-OS-SIM method that allows for the OS reconstruction using the high-frequency spectrum of the sample and thus is immune to the low-frequency background noise. The full-color Fourier-OS-SIM directly runs in the RGB color space, providing an easy way to restore the color information. Simulation and experiments with various samples (pollen grains and tiny animals) demonstrate that the full-color Fourier-OS-SIM method is superior to the HSV-RMS method regarding background noise suppression. Moreover, benefiting from the background noise suppression merit, the quantitative morphological height map analysis with the full-color Fourier-OS-SIM method is more accurate. The proposed full-color Fourier-OS-SIM method is expected to find broad applications in biological and industrial fields where the 3D morphology and the color information of objects both need to be recovered.

High-purity metal sputtering target is one of the key basic materials for integrated circuits. Self-dependence of the sputtering targets is vital for the high-quality development of the integrated circuit industry in China. This study analyzes the application demand for and development status of high-purity metal sputtering targets for integrated circuits, involving high-purity aluminum and aluminum alloys, high-purity copper and copper alloys, high-purity titanium, high-purity tantalum, high-purity cobalt, high-purity nickel platinum, and high-purity tungsten and tungsten alloys. Moreover, it summarizes the challenges regarding the key manufacturing technologies and engineering application of high-performance sputtering targets in China and proposes several major development directions based on the development goals of the field by 2030. Specifically, China needs to improve its material processing technologies, focus on the key technologies for high-performance target processing, develop high-end new materials according to frontier demands, and improve the capabilities of material analysis, testing, and application evaluation. Furthermore, the following suggestions are proposed: establishing an industry-education-research-application system, realizing the domestic manufacturing of key equipment, strengthening talent team construction, establishing an independent intellectual property system, and expanding international exchange and cooperation,thereby promoting the development quality and level of high-purity metal sputtering targets.

Objective: The purpose of this study was to explore the antioxidative activity in vitro experiments and the anti-fatigue activity of chickpea oligopeptides in mice. Methods: In this study, the antioxidant capacity of chickpea oligopeptide was detected by in vitro method, and the anti-fatigue capacity of chickpea oligopeptide was comprehensively evaluated by detecting physiological and biochemical indexes of mice. Results: The superoxide anion radical scavenging ability IC50 of chickpea oligopeptide was 4.26 mg/mL, which was significantly higher than that of GSH positive control group （P＜0.05）; The reducing power of chickpea oligopeptide was significantly higher than that of GSH positive control （P＜0.05）. In addition, at low, medium and high doses, the fatigue tolerance, muscle glycogen and liver glycogen reserve capacity of mice were improved, and the concentration of serum urea nitrogen, malondialdehyde and lactic acid was decreased （P＜0.05）. It can significantly increase the activities of catalase, superoxide dismutase and glutathione peroxidase （P＜0.05）. Conclusion: Chickpea oligopeptides have significant anti-fatigue effects.

Summary: Recent studies have revealed the heterogeneous nature of astrocytes; however, how diverse constituents of astrocyte-lineage cells are regulated in adult spinal cord after injury and contribute to regeneration remains elusive. We perform single-cell RNA sequencing of GFAP-expressing cells from sub-chronic spinal cord injury models and identify and compare with the subpopulations in acute-stage data. We find subpopulations with distinct functional enrichment and their identities defined by subpopulation-specific transcription factors and regulons. Immunohistochemistry, RNAscope experiments, and quantification by stereology verify the molecular signature, location, and morphology of potential resident neural progenitors or neural stem cells in the adult spinal cord before and after injury and uncover the populations of the intermediate cells enriched in neuronal genes that could potentially transition into other subpopulations. This study has expanded the knowledge of the heterogeneity and cell state transition of glial progenitors in adult spinal cord before and after injury.

Summary: It is widely believed that hematopoiesis after birth is established by hematopoietic stem cells (HSCs) in the bone marrow and that HSC-independent hematopoiesis is limited only to primitive erythro-myeloid cells and tissue-resident innate immune cells arising in the embryo. Here, surprisingly, we find that significant percentages of lymphocytes are not derived from HSCs, even in 1-year-old mice. Instead, multiple waves of hematopoiesis occur from embryonic day 7.5 (E7.5) to E11.5 endothelial cells, which simultaneously produce HSCs and lymphoid progenitors that constitute many layers of adaptive T and B lymphocytes in adult mice. Additionally, HSC lineage tracing reveals that the contribution of fetal liver HSCs to peritoneal B-1a cells is minimal and that the majority of B-1a cells are HSC independent. Our discovery of extensive HSC-independent lymphocytes in adult mice attests to the complex blood developmental dynamics spanning the embryo-to-adult transition and challenges the paradigm of HSCs exclusively underpinning the postnatal immune system.

Heterosis, the phenomenon in which hybrids outperform their parents, has been utilized in maize (Zea mays L.) for over 100 years. To provide a more complete understanding of heterosis, we collected a comprehensive transcriptome and translatome dataset on seedling leaves for B73, Mo17, and their F1 hybrid, which provided a dynamic landscape of transcriptomic and translatomic variation in maize. Although additivity accounted for a large proportion of variation at two omics-levels, an elevated nonadditive effect was observed in the translatome, especially in the translated subgenome maize1 genes, and the genes that switched from additivity in the transcriptome to nonadditivity in the translatome were significantly enriched in the subgenome maize1. Many genes with allele-specific expression and translation show dramatic regulatory switches between the transcriptome and translatome, and partial genes with allele-specific translation underlying regulatory mechanism also exhibited subgenome bias. Interestingly, we found the translated isoforms show different expression patterns compared with transcriptome and more genes changed their dominant isoforms during the genetic flow from parents to the hybrid at the translatome level. The translated genes with switched dominant isoforms significantly biased to the subgenome maize2 while genes with conserved dominant isoforms significantly enriched in subgenome maize1. Together, the dynamic changed patterns in translatome across hybrid and parental lines show translational fractionation of the maize subgenomes, which may be associated with heterosis in maize and provides a potential theoretical basis for breeding.

Aiming at the problem that the characteristic distribution of rolling bearing vibration data collected under different speed environment is inconsistent and it is difficult to obtain the label of samples to be diagnosed, a fault diagnosis method based on deep migration network is proposed. In this model, a domain-shared feature extraction network is constructed. The convolutional neural network（CNN） is used to extract vibration signal sensitive fault features, and bi-directional Long short-term Memory is used to extract vibration signal sensitive fault features. BiLSTM) network to extract the time information of sensitive fault features; Then, CORAL loss and JMMD loss were embedded in the deep migration network, respectively. By minimizing the second-order statistical difference and the maximum mean difference of the joint distribution, the differences in the feature distributions of the source domain and target domain were reduced, and the common features of the two domains were extracted. Finally, add Softmax classification layer to realize fault status recognition of target data. The results show that the average recognition accuracy of this method is 97.87% when the target domain data is unlabeled, which is significantly higher than the other five popular adaptive fault diagnosis methods.

Abstract Electric drives, which are a main component in industrial applications, control electric motors and record vital information about their respective industrial processes. The development of electric drives as Fog nodes within a fog computing platform (FCP) leads to new abilities such as programmability, analytics, and connectivity, increasing their value. In this study, the FORA FCP reference architecture is used to implement electric drives as Fog nodes, which is called “fogification”. The fogified drive architecture and its components are designed using Architecture Analysis and Design Language (AADL). The design process was driven by the high‐level requirements that the authors elicited. Both the fogified drive architecture and the current drive architecture are used to implement a self baggage drop system in which electric drives are the key components. The fog‐based design was then evaluated using several key performance indicators (KPIs), which reveal its advantages over the current drive architecture. The evaluation results show that safety‐related isolation is enabled with only 9% overhead on the total Fog node utilization, control applications are virtualized with zero input–output jitter, the hardware cost is reduced by 44%, and machine learning at the edge is performed without interrupting the main drive functionalities and with an average 85% accuracy. The conclusion is that the fog‐based design can successfully implement the required electric drive functionalities and can also enable innovative uses needed for realizing the vision of Industry 4.0.

Hyperuricemic nephropathy (HN) is a common clinical complication of hyperuricemia. The pathogenesis of HN is directly related to urea metabolism in the gut microbiota. Febuxostat, a potent xanthine oxidase inhibitor, is the first-line drug used for the treatment of hyperuricemia. However, there have been few studies on the pharmacokinetics of febuxostat in HN animal models or in patients. In this study, a high-purine diet-induced HN rat model was established. The pharmacokinetics of febuxostat in HN rats was evaluated using LC-MS/MS. Astragaloside IV (AST) was used to correct the abnormal pharmacokinetics of febuxostat. Gut microbiota diversity analysis was used to evaluate the effect of AST on gut microbiota. The results showed that the delayed elimination of febuxostat caused drug accumulation after multiple administrations. Oral but not i. p. AST improved the pharmacokinetics of febuxostat in HN rats. The mechanistic study showed that AST could regulate urea metabolism in faeces and attenuate urea-ammonia liver-intestine circulation. Urease-related genera, including Eubacterium, Parabacteroides, Ruminococcus, and Clostridia, decreased after AST prevention. In addition, the decrease in pathogenic genera and increase in short-chain fatty acids (SCFA) producing genera also contribute to renal function recovery. In summary, AST improved the pharmacokinetics of febuxostat in HN rats by comprehensive regulation of the gut microbiota, including urea metabolism, anti-calcification, and short-chain fatty acid generation. These results imply that febuxostat might accumulate in HN patients, and AST could reverse the accumulation through gut microbiota regulation.

Neurodegenerative diseases affect millions of people worldwide and there are currently no cures. Two types of common neurodegenerative diseases are Alzheimer’s (AD) and Parkinson’s disease (PD). Single-cell and single-nuclei RNA sequencing (scRNA-seq and snRNA-seq) have become powerful tools to elucidate the inherent complexity and dynamics of the central nervous system at cellular resolution. This technology has allowed the identification of cell types and states, providing new insights into cellular susceptibilities and molecular mechanisms underlying neurodegenerative conditions. Exciting research using high throughput scRNA-seq and snRNA-seq technologies to study AD and PD is emerging. Herein we review the recent progress in understanding these neurodegenerative diseases using these state-of-the-art technologies. We discuss the fundamental principles and implications of single-cell sequencing of the human brain. Moreover, we review some examples of the computational and analytical tools required to interpret the extensive amount of data generated from these assays. We conclude by highlighting challenges and limitations in the application of these technologies in the study of AD and PD.

As a branch of 3D microscopy, optical sectioning structured illumination microscopy (OS-SIM) has the advantages of fast imaging speed, weak photobleaching and phototoxicity, and flexible and compatible configuration. Although the method of using the one-dimensional periodic fringe pattern projected on the sample can remove the out-of-focus background from the in-focus signal, the axial resolution of the final reconstructed 3D image is not improved. Here, we propose a three-beam interference OS-SIM, namely TBOS, instead of the common-used dual-beam interference OS-SIM (DBOS). The three-beam interference scheme has been adopted in 3D super-resolution SIM (3D-SR-SIM), where the fringe phase shifting needs to be along each of the three orientations. In contrast, TBOS applies phase shifting only in one arbitrary direction. We built a TBOS SIM microscope and performed the 3D imaging experiments with 46 nm diameter fluorescent microspheres and a mouse kidney section. The axial resolution of the 3D image obtained with TBOS was enhanced by a factor of 1.36 compared to the DBOS method, consistent with the theoretical analysis and simulation. The OS-SIM with enhanced axial resolution for 3D imaging may find a wide range of applications in the biomedical field.

The seed industry is a basic and core industry that is strategically important for a nation. Considering the national guidance opinions on fields such as seeds and cultivated land, industrialization of biological breeding, and development of core technologies for germplasm resources, the seed industry has become a driving force for the rapid development of China’s agriculture. In this study, we summarize the current status of the global crop seed industry from the aspects of germplasm resources protection and utilization, biological breeding technology development, seed industry development, etc. Moreover, we analyze the problems of China’s seed industry from an international perspective. To promote the development of the seed industry, China should implement a national germplasm resources strategy to consolidate the foundation of its seed industry; implement a scientific and technological innovation strategy in the seed industry to achieve breakthroughs in original innovation; construct a seed industry system with Chinese characteristics to enhance industrial competitiveness; promote the role of enterprises in technological innovation; and modernize the supervision system to improve industrial advantages.

Measurement(s) RNA Technology Type(s) RNA sequencing Factor Type(s) motor cortex electrical stimulation Sample Characteristic - Organism Rattus norvegicus Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14129012

Abstract Background Oligodendrocytes, responsible for axon ensheathment, are critical for central nervous system (CNS) development, function, and diseases. OLIG2 is an important transcription factor (TF) that acts during oligodendrocyte development and performs distinct functions at different stages. Previous studies have shown that lncRNAs (long non-coding RNAs; > 200 bp) have important functions during oligodendrocyte development, but their roles have not been systematically characterized and their regulation is not yet clear. Results We performed an integrated study of genome-wide OLIG2 binding and the epigenetic modification status of both coding and non-coding genes during three stages of oligodendrocyte differentiation in vivo: neural stem cells (NSCs), oligodendrocyte progenitor cells (OPCs), and newly formed oligodendrocytes (NFOs). We found that 613 lncRNAs have OLIG2 binding sites and are expressed in at least one cell type, which can potentially be activated or repressed by OLIG2. Forty-eight of them have increased expression in oligodendrocyte lineage cells. Predicting lncRNA functions by using a “guilt-by-association” approach revealed that the functions of these 48 lncRNAs were enriched in “oligodendrocyte development and differentiation.” Additionally, bivalent genes are known to play essential roles during embryonic stem cell differentiation. We identified bivalent genes in NSCs, OPCs, and NFOs and found that some bivalent genes bound by OLIG2 are dynamically regulated during oligodendrocyte development. Importantly, we unveiled a previously unknown mechanism that, in addition to transcriptional regulation via DNA binding, OLIG2 could self-regulate through the 3′ UTR of its own mRNA. Conclusions Our studies have revealed the missing links in the mechanisms regulating oligodendrocyte development at the transcriptional level and after transcription. The results of our research have improved the understanding of fundamental cell fate decisions during oligodendrocyte lineage formation, which can enable insights into demyelination diseases and regenerative medicine.

Biomacromolecule drugs of nucleic acids and proteins/peptides have occupied growing share of global pharmaceutical market, but their biomedical application faces substantial challenges in lacking of safe and effective delivery vehicles due to the high molecular weight and the sensitive structure. Because of the unique physicochemical and biological properties of hydrophobicity and lipophobicity, superior assembly performance, desirable chemical stability, and biological inertness, fluoropolymers are a modular solution to these problems as an ideal delivery vehicle of biomacromolecules. In the review, we discuss how to endow the polymer with “fluorine magic” as fluoropolymers and summarized the recent advances of fluoropolymers specifically tailored to the delivery challenges of biomacromolecule drugs, including stability, serum tolerance, membrane permeability, endosomal escape of nucleic acids and intercellular delivery of proteins/peptides. Moreover, this work concludes the application of fluoropolymers-mediated biomacromolecule drug delivery in cancer therapy. Finally, we discuss the opportunities, challenges and further perspectives of fluoropolymers for the delivery of biomacromolecule drugs, aiming to facilitate further development of fluoropolymers in biomedical application.

Super-resolution structured illumination microscopy (SIM) routinely performs image reconstruction in the frequency domain using an approach termed frequency-domain reconstruction (FDR). Due to multiple Fourier transforms between the spatial and frequency domains, SIM suffers from low reconstruction speed, constraining its applications in real-time, dynamic imaging. To overcome this limitation, we developed a new method for SIM image reconstruction, termed spatial domain reconstruction (SDR). SDR is intrinsically simpler than FDR, does not require Fourier transforms and the theory predicts it to be a rapid image reconstruction method. Results show that SDR reconstructs a super-resolution image 7-fold faster than FDR, producing images that are equal to either FDR or the widely-used FairSIM. We provide a proof-of-principle using mobile fluorescent beads to demonstrate the utility of SDR in imaging moving objects. Consequently, replacement of the FDR approach with SDR significantly enhances SIM as the desired method for live-cell, instant super-resolution imaging. This means that SDR-SIM is a “What You See Is What You Get” approach to super-resolution imaging.

Optical sectioning structured illumination microscopy (OS-SIM) has been attracting considerable interest in fast 3D microscopy. The reconstruction of optical sectioning images in the conventional method employs the root-mean-square (RMS) algorithm in the spatial domain, which is prone to residual background noise. To overcome this problem, we propose a Fourier domain based optical sectioning image reconstruction algorithm (termed Fourier-OS-SIM), which has an improved background noise suppression capability compared to the RMS algorithm. The experimental results verified the feasibility and the effectiveness of the algorithm. The improved performance of the Fourier-OS-SIM may find more applications in biomedical or industrial fields.

The standardized training of cardiologists in china is an important continuing medical education program to improve the individual and national level of clinical diagnosis and treatment. On account of the varying quality of standardized training trainees and the lack of targeted clinical training and assessment system, the current training program is unable to meet the future job demand of cardiologists. From the training base perspective, the study put forward a goal of improving Core Competencies and focus on the development of self-growth capability. Through the elaboration of training system, the development of personalized training programs, the classification of assessment forms and standard, and other measures, the aim to improve trainees' self-growth capability to figure out problems, to think and solve the problems, and to explore a new way to improve the quality of cardiologists standardized training in China.

Multispectral LiDAR technology can simultaneously acquire spatial geometric data and multispectral wavelength intensity information, which can provide richer attribute features for semantic segmentation of point cloud scenes. However, due to the disordered distribution and huge number of point clouds, it is still a challenging task to accomplish fine-grained semantic segmentation of point clouds from large-scale multispectral LiDAR data. To deal with this situation, we propose a deep learning network that can leverage contextual semantic information to complete the semantic segmentation of large-scale point clouds. In our network, we work on fusing local geometry and feature content based on 3D spatial geometric associativity and embed it into a backbone network. In addition, to cope with the problem of redundant point cloud feature distribution found in the experiment, we designed a data preprocessing with principal component extraction to improve the processing capability of the proposed network on the applied multispectral LiDAR data. Finally, we conduct a series of comparative experiments using multispectral LiDAR point clouds of real land cover in order to objectively evaluate the performance of the proposed method compared with other advanced methods. With the obtained results, we confirm that the proposed method achieves satisfactory results in real point cloud semantic segmentation. Moreover, the quantitative evaluation metrics show that it reaches state-of-the-art.

Alzheimer's disease (AD) is a progressive neurodegenerative disease and is the most common cause of dementia in an aging population. The majority of research effort has focused on the role of neurons in neurodegeneration and current therapies have limited ability to slow disease progression. Recently more attention has been given to the role of astrocytes in the process of neurodegeneration. Specifically, reactive astrocytes have both advantageous and adverse effects during neurodegeneration. The ability to isolate and depict astrocyte phenotype has been challenging. However, with the recent development of single-cell sequencing technologies researchers are provided with the resource to delineate specific biomarkers associated with reactive astrocytes in AD. In this review, we will focus on the role of astrocytes in normal conditions and the pathological development of AD. We will further review recent developments in the understanding of astrocyte heterogeneity and associated biomarkers. A better understanding of astrocyte contributions and phenotypic changes in AD can ultimately lead to more effective therapeutic targets.

Small peptides (sPeptides),

Abstract Motivation Sequencing technologies allow the sequencing of microbial communities directly from the environment without prior culturing. Because assembly typically produces only genome fragments, also known as contigs, it is crucial to group them into putative species for further taxonomic profiling and down-streaming functional analysis. Taxonomic analysis of microbial communities requires contig clustering, a process referred to as binning, that is still one of the most challenging tasks when analyzing metagenomic data. The major problems are the lack of taxonomically related genomes in existing reference databases, the uneven abundance ratio of species, sequencing errors, and the limitations due to binning contig of different lengths. Results In this context we present MetaCon a novel tool for unsupervised metagenomic contig binning based on probabilistic k-mers statistics and coverage. MetaCon uses a signature based on k-mers statistics that accounts for the different probability of appearance of a k-mer in different species, also contigs of different length are clustered in two separate phases. The effectiveness of MetaCon is demonstrated in both simulated and real datasets in comparison with state-of-art binning approaches such as CONCOCT, MaxBin and MetaBAT.

Abstract Single-cell RNA-sequencing (scRNA-seq) is revolutionizing our understanding of the genomic, transcriptomic and epigenomic landscapes of cells within organs. The mammalian brain is composed of a complex network of millions to billions of diverse cells with either highly specialized functions or support functions. With scRNA-seq it is possible to comprehensively dissect the cellular heterogeneity of brain cells, and elucidate their specific functions and state. In this review, we describe the current experimental methods used for scRNA-seq. We also review bioinformatic tools and algorithms for data analyses and discuss critical challenges. Additionally, we summarized recent mouse brain scRNA-seq studies and systematically compared their main experimental approaches, computational tools implemented, and important findings. scRNA-seq has allowed researchers to identify diverse cell subpopulations within many brain regions, pinpointing gene signatures and novel cell markers, as well as addressing functional differences. Due to the complexity of the brain, a great deal of work remains to be accomplished. Defining specific brain cell types and functions is critical for understanding brain function as a whole in development, health, and diseases.

The article studies the semantics of Chinese number word one on the material of “the Classic of the Way and the Power” (by the sage Laozi, 4-3 centuries. BC.), “the Book of Changes” (by The King Wen, 700 BC.), and the dictionary “Shuowen Jiezi” (by Xu Shen, about 147 BC.). The paper deals with the semantics of Chinese number one in detail, offering detailed analyses and intersection and overlaps between Chinese number one and Russian lexemes один and единица . Although there is no distinction in term of isosemia, ontological content of Chinese number one and Russian lexemes один and единица , it doesn’t result in the coincidence of internal forms of those linguistic signs.

A sample of undergraduate Psychology students (n = 1005), prevalently females (82.4%), mean age 20.5 (sd 2.5), was examined regarding their attitudes toward people suffering from mental illness. The survey instrument included a brief form for demographic variables, the Attribution Questionnaire-9 (AQ-9), the Ten Items Personality Inventory (TIPI), and two questions exploring attitudes toward open-door and restraint-free policies in Psychiatry. Higher levels of stigmatizing attitudes were found in males (Pity, Blame, Help, and Avoidance) and in those (76.5%) who had never had any experience with psychiatric patients (Danger, Fear, Blame, Segregation, Help, Avoidance and Coercion). A similar trend was also found in those who don't share the policy of no seclusion/restraint, while subjects who are favorable to open-door policies reported higher Coercion scores. No correlations were found between dimensions of stigma and personality traits. A machine learning approach was then used to explore the role of demographic, academic and personality variables as predictors of stigmatizing attitudes. Agreeableness and Extraversion emerged as the most relevant predictors for blaming attitudes, while Emotional Stability and Openness appeared to be the most effective contributors to Anger. Our results confirmed that a training experience in Psychiatry might successfully reduce stigma in Psychology students. Further research, with increased generalizability of samples and more reliable instruments, should address the role of personality traits and gender on attitudes toward people suffering from mental illness.

Long non-coding RNAs (lncRNAs) (> 200 bp) play crucial roles in transcriptional regulation during numerous biological processes. However, it is challenging to comprehensively identify lncRNAs, because they are often expressed at low levels and with more cell-type specificity than are protein-coding genes. In the present study, we performed ab initio transcriptome reconstruction using eight purified cell populations from mouse cortex and detected more than 5000 lncRNAs. Predicting the functions of lncRNAs using cell-type specific data revealed their potential functional roles in Central Nervous System (CNS) development. We performed motif searches in ENCODE DNase I digital footprint data and Mouse ENCODE promoters to infer transcription factor (TF) occupancy. By integrating TF binding and cell-type specific transcriptomic data, we constructed a novel framework that is useful for systematically identifying lncRNAs that are potentially essential for brain cell fate determination. Based on this integrative analysis, we identified lncRNAs that are regulated during Oligodendrocyte Precursor Cell (OPC) differentiation from Neural Stem Cells (NSCs) and that are likely to be involved in oligodendrogenesis. The top candidate, lnc-OPC, shows highly specific expression in OPCs and remarkable sequence conservation among placental mammals. Interestingly, lnc-OPC is significantly up-regulated in glial progenitors from experimental autoimmune encephalomyelitis (EAE) mouse models compared to wild-type mice. OLIG2-binding sites in the upstream regulatory region of lnc-OPC were identified by ChIP (chromatin immunoprecipitation)-Sequencing and validated by luciferase assays. Loss-of-function experiments confirmed that lnc-OPC plays a functional role in OPC genesis. Overall, our results substantiated the role of lncRNA in OPC fate determination and provided an unprecedented data source for future functional investigations in CNS cell types. We present our datasets and analysis results via the interactive genome browser at our laboratory website that is freely accessible to the research community. This is the first lncRNA expression database of collective populations of glia, vascular cells, and neurons. We anticipate that these studies will advance the knowledge of this major class of non-coding genes and their potential roles in neurological development and diseases.