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Abstract Based on observations from the Magnetospheric Multiscale mission, this study presents an analysis of a short large‐amplitude magnetic structures (SLAMS) event with simultaneous occurrence of low‐ and high‐frequency magnetosonic whistler waves. It was found that low‐frequency magnetosonic whistler waves around the lower‐hybrid frequency emerge in the presence of solar wind ions and local low‐energy ions in the trailing region of SLAMS. Additionally, counter‐propagating whistler waves (the high‐frequency branch of the magnetosonic whistler wave) are observed within SLAMS, coinciding with a perpendicular temperature anisotropy in the electron population. Instability analyses demonstrate that these low‐frequency waves are induced by the two‐stream instability associated with the cross‐field relative velocity between low‐energy ions and electrons, while whistler waves are locally generated by the whistler anisotropy instability. Our results shed light on the impact of SLAMS on particle and wave dynamics in the terrestrial foreshock.

Deep sea water (DSW) is a globally utilized source of renewable energy and other resources. To understand the characteristics of DSW resources in the South China Sea, in July 2022, the Guangzhou Marine Geological Survey (GMGS) investigated temperature, salinity, pH, dissolved oxygen (DO), inorganic salts (DIN, PO43−-P, and SiO3-Si), heavy metals (Hg, Pb, As, and Cd), trace elements (Cu, Zn, Fe, Mn, Ni, Se, and Mo), and other related indicators. The results of this investigation elucidate the horizontal and vertical changes in the physical and chemical properties of deep sea water in the Xisha Sea. The surface seawater quality in Xisha was found to be excellent and to meet first-class seawater survey standards. However, the concentrations of various nutrient salts in the surface layer were relatively low. As the seawater depth increased, different trace elements and heavy metals exhibited variations, and the concentrations of various nutrients also gradually increased.

In order to achieve the goals of carbon neutrality and reduced carbon emissions, China is increasingly focusing on the development and utilization of renewable energy sources. Among these, ocean thermal energy conversion (OTEC) has the advantages of small periodic fluctuations and large potential reserves, making it an important research field. With the development of the “Maritime Silk Road”, the Xisha Islands in the South China Sea will see a growing demand for electricity, providing the potential for OTEC development in this region. Optimal site selection of OTEC power plants is a prerequisite for developing thermal energy provision, affecting both the construction costs and future benefits of the power plants. This study establishes a scientific evaluation model based on the decision-making frameworks of geographic information systems (GISs) and multi-criteria decision-making (MCDM) methods, specifically the analytic hierarchy process (AHP) for assigning weights, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to reclassify the factors, and weighted linear combination (WLC) to compute the suitability index. In addition to commonly considered factors such as temperature difference and marine usage status, this study innovatively incorporates geological conditions and maximum offshore distances of cold seawater based on cost control. The final evaluation identifies three suitable areas for OTEC development near the Xuande Atoll and the Yongle Atoll in the Xisha Sea Area, providing valuable insights for energy developers and policymakers.

Submarine pockmarks are typical indicators of submarine gas escape activity. The deep strata of the Xisha Uplift are rich in biogenic and thermogenic gas, accompanied by strong bottom current activity. Investigating the effects of controlling submarine gas escape and bottom current activity on the formation and development of pockmarks in the Xisha Uplift is significant for understanding the evolution of submarine topography and geomorphology. This study utilized high-resolution multibeam data to identify 261 submarine pockmarks in the northwest of the Xisha Uplift. These pockmarks were categorized based on their morphology into circular, elliptical, elongated, crescent-shaped, and irregular types. The diameters of pockmarks in the study area range from 0.21 to 4.96 km, with maximum depths reaching 30.88 m. Using high-resolution multi-channel seismic data, we conducted a detailed analysis of the subsurface strata characteristics of the pockmarks, identifying chaotic weak reflections, bright spots, and high-angle reflectors. We believe that deep gas in the northwest of the Xisha Uplift escapes to the seafloor through migration pathways, such as faults, fractures, and gas chimneys, resulting in the formation of submarine pockmarks. Bottom current activity has a significant impact on already-formed pockmarks. Crescent-shaped and elongated pockmarks in the Xisha Uplift are largely the result of bottom current modifications of pre-existing pockmarks.

In this study, the optimization of processing parameters of Inconel 718 using electrical discharge machining (EDM) with three kinds of renewable dielectrics (soybean oil, sunflower seed oil, and rapeseed oil) was studied. As input process parameters, pulse current, pulse duration, duty ratio, and dielectric type were all utilized. The machining performance indices of EDM were material removal rate (MRR), surface roughness (Ra), energy pulse ratio per volume (EEV), and exhaust emission characteristics (EEC). The response surface method (RSM) was used to carry out the central composite design of the EDM experiment, and it looked into how process parameters affected machining performance. In addition, the extreme learning machine (ELM)-improved integrated beta-distribution cuckoo search (IBCS) algorithm was used to optimize the EDM process, and the optimization results were verified by experiments. The research results demonstrate that the predicted results are generally better than the experimental results, and the maximum and average deviations of the experimental results are within the acceptable range (maximum deviation

Abstract The zinc finger proteins (ZNFs) mediated transcriptional regulation is critical for cell fate transition. However, it is still unclear how the ZNFs realize their specific regulatory roles in the stage-specific determination of cardiomyocyte differentiation. Here, we reported that the zinc fingers and homeoboxes 1 (Zhx1) protein, transiently expressed during the cell fate transition from mesoderm to cardiac progenitors, was indispensable for the proper cardiomyocyte differentiation of mouse and human embryonic stem cells. Moreover, Zhx1 majorly promoted the specification of cardiac progenitors via interacting with hnRNPA1 and co-activated the transcription of a wide range of genes. In-depth mechanistic studies showed that Zhx1 was bound with hnRNPA1 by the amino acid residues (Thr111–His120) of the second Znf domain, thus participating in the formation of cardiac progenitors. Together, our study highlights the unrevealed interaction of Zhx1/hnRNPA1 for activating gene transcription during cardiac progenitor specification and also provides new evidence for the specificity of cell fate determination in cardiomyocyte differentiation.

The mechanical and mechanochemical synergistic micro-grinding technology was proposed for grinding hard and brittle materials, especially for fused silica micro parts in this work. Compounded abrasive micro-grinding tools with diamond abrasives on the outer layer and cerium oxide abrasives on the inner layer were designed and fabricated. Efficient grinding was initially achieved by mechanical processing of super hard abrasives, and then ultra-precision processing was obtained by mechanochemical process to remove surface or subsurface damage. This study firstly analyzed the contact model of single diamond abrasive particle and theoretically evaluated ground surface roughness. The mechanism of abrasive layer wear was investigated for accurate error compensation. The formulation of cerium oxide abrasive layer and its processing efficiency were further analyzed. The material removal mechanisms of fused silica during mechanochemical grinding were also studied. Results showed that the material removal rate was 1.924 μm/min and the surface roughness Ra was 0.248 μm after mechanical processing. Subsequently, the surface roughness Ra was improved to 38 nm after mechanochemical processing. The study indicates that this technique is a promising approach for high-efficiency and high-quality grinding of fused silica.

Drug-resistant Staphylococcus aureus stands as a prominent pathogen in nosocomial and community-acquired infections, capable of inciting various infections at different sites in patients. This includes Staphylococcus aureus bacteremia (SaB), which exhibits a severe infection frequently associated with significant mortality rate of approximately 25%. In the absence of better alternative therapies, antibiotics is still the main approach for treating infections. However, excessive use of antibiotics has, in turn, led to an increase in antimicrobial resistance. Hence, it is imperative that new strategies are developed to control drug-resistant S. aureus infections. Bacteriophages are viruses with the ability to infect bacteria. Bacteriophages, were used to treat bacterial infections before the advent of antibiotics, but were subsequently replaced by antibiotics due to limited theoretical understanding and inefficient preparation processes at the time. Recently, phages have attracted the attention of many researchers again because of the serious problem of antibiotic resistance. This article provides a comprehensive overview of phage biology, animal models, diverse clinical case treatments, and clinical trials in the context of drug-resistant S. aureus phage therapy. It also assesses the strengths and limitations of phage therapy and outlines the future prospects and research directions. This review is expected to offer valuable insights for researchers engaged in phage-based treatments for drug-resistant S. aureus infections.

ABSTRACT The global COVID-19 pandemic and frequent outbreaks of other infectious diseases, such as influenza and monkeypox, often initially manifest with non-specific influenza-like symptoms. Portability to the outbreak site and accurate identification of the various pathogens causing influenza-like illness are crucial for the rapid implementation of effective control measures. Utilizing real-time PCR and microfluidic technology, a multiplexed on-site sample-in-result-out test through microfluidic real-time PCR (MONITOR) has been developed for detecting the pathogens responsible for influenza-like illness. The operator simply needs to introduce the sample to a highly integrated microfluidic chip (requiring ≤1 minute), and the system can autonomously execute sample pre-processing, nucleic acid extraction, and PCR amplification and deliver results for eight pathogens within 85 minutes. The detection limit of MONITOR for the eight pathogens ranges from 0.78 to 6.25 copies/µL. Standard curves demonstrate notable linearity and amplification efficiency. A simulated clinical sample test reveals MONITOR’s sensitivity, specificity, and accuracy at 97.5%, 100%, and 98%, respectively. Bland-Altman analysis demonstrates strong agreement between the cycle threshold of positive MONITOR samples and quantitative polymerase chain reaction (qPCR) (R 2 = 0.952), suggesting MONITOR’s ability to indirectly quantify pathogen load. The fully enclosed structure of the system chip minimizes sample and environmental cross-contamination, rendering the assay independent of a specialized laboratory. The portable, fully automated MONITOR facilitates on-site, comprehensive detection of multiple pathogens, even non-specialized operators with minimal training. This presents a promising approach for the rapid and precise diagnosis of influenza-like illness in grassroots communities and underserved rural areas lacking centralized laboratories. IMPORTANCE This study combines quantitative polymerase chain reaction (qPCR) and microfluidics to introduce MONITOR, a portable field detection system for multiple pathogens causing influenza-like illness. MONITOR can be rapidly deployed to enable simultaneous sample-in-result-out detection of eight common influenza-like illness (ILI) pathogens with heightened sensitivity and specificity. It is particularly well suited for communities and regions without centralized laboratories, offering robust technical support for the prompt and accurate monitoring and detection of ILI. It holds the potential to be a potent tool in the early detection and prevention of infectious diseases.

Abstract Gonad somatic cells acquire sex-specific fates during sex determination. In XX gonad, a subset of somatic cells expresses Foxl2 after sex determination which is considered the progenitor of granulosa cells. However, whether these cells also contribute to other cell types at later developmental stages is unknown. In the present study, the cell fate of Foxl2-expressing cells in fetal ovaries was analyzed by lineage tracing and single-cell transcriptomics. We found that Foxl2-expressing cells gave rise to three cell types at later developmental stages, including granulosa cells, theca-interstitial cells, and stromal cells. Series single-cell RNA sequencing revealed FOXL2-positive cells were divided into two clusters at P0. One group further differentiated into granulosa cells and Theca-G (Theca-interstitial cells derived from granulosa) at P14. Another group was classified as stromal cell lineage, then a small portion of them further differentiated into 3β-HSD-positive Theca-S (Theca-interstitial cells derived from stroma). Cyp17a1 was expressed in Theca-S, but not in Theca-G. This study demonstrated that Folx2-expressing cells in XX gonad after sex determination are multipotent and theca-interstitial cells are derived from different progenitors. Our data provided an important resource, at single-cell resolution, for a better understanding of somatic cell differentiation in ovary development.

Abstract The frequency of outbreaks of newly emerging infectious diseases has increased in recent years. The coronavirus disease 2019 (COVID-19) outbreak in late 2019 has caused a global pandemic, seriously endangering human health and social stability. Rapid detection of infectious disease pathogens is a key prerequisite for the early screening of cases and the reduction in transmission risk. Fluorescence quantitative polymerase chain reaction (qPCR) is currently the most commonly used pathogen detection method, but this method has high requirements in terms of operating staff, instrumentation, venues, and so forth. As a result, its application in the settings such as poorly conditioned communities and grassroots has been limited, and the detection needs of the first-line field cannot be met. The development of point-of-care testing (POCT) technology is of great practical significance for preventing and controlling infectious diseases. Isothermal amplification technology has advantages such as mild reaction conditions and low instrument dependence. It has a promising prospect in the development of POCT, combined with the advantages of high integration and portability of microfluidic chip technology. This study summarized the principles of several representative isothermal amplification techniques, as well as their advantages and disadvantages. Particularly, it reviewed the research progress on microfluidic chip–based recombinase polymerase isothermal amplification technology and highlighted future prospects.

The immature phenotype of embryonic stem cell-derived cardiomyocytes (ESC-CMs) limits their application. However, the molecular mechanisms of cardiomyocyte maturation remain largely unexplored. This study found that overexpression of long noncoding RNA (lncRNA)-Cmarr, which was highly expressed in cardiomyocytes, promoted the maturation change and physiological maturation of mouse ESC-CMs (mESC-CMs). Moreover, transplantation of cardiac patch overexpressing Cmarr exhibited better retention of mESC-CMs, reduced infarct area by enhancing vascular density in the host heart, and improved cardiac function in mice after myocardial infarction. Mechanism studies identified that Cmarr acted as a competitive endogenous RNA to impede the repression of miR-540-3p on Dtna expression and promoted the binding of the dystrophin-glycoprotein complex (DGC) and yes-associated protein (YAP), which in turn reduced the proportion of nuclear YAP and the expression of YAP target genes. Therefore, this study revealed the function and mechanism of Cmarr in promoting cardiomyocyte maturation and provided a lncRNA that can be used as a functional factor in the construction of cardiac patches for the treatment of myocardial infarction.

Abstract As the crucial dimension (CD) of logic circuits continues to shrink, the photoresist metrics, including resolution, line edge roughness, and sensitivity, are faced with significant challenges. Photoresists are indispensable in the integrated circuit manufacturing industry, and specifically in achieving smaller critical dimensions. In this study, the effects of two categories of photosensitive compounds on lithography performance are explored, through a series of sulfonium salt‐based photoacid generators (PAGs) with diverse reactivity and photodegradable nucleophiles (PDNs) with varying nucleophilicity. The detailed characterization and exposure experiments suggest that the reactive alterations of different PAGs are mostly associated with the amount of phenyl composed of cations in PAGs. The “PDN first, PAG second” strategy, which employs a combination of low reactivity PAG and high reactivity PDN and involves PDN decomposition first and PAG decomposition second in the electron beam lithography process, achieves high sensitivity (100–270 µC cm−2), high resolution (25 nm 1:1 line/space, L/S), and low line edge roughness (LER ≤ 3.3 nm) stripes. This approach outperforms conventional formulations and may provide a potentially effective and useful strategy to improve electron beam photoresists.

IntroductionThe changes in grassland management and grassland types are strongly linked with dynamics in soil physico-chemical properties and vegetation attributes, with important implications for carbon/nitrogen cycling and greenhouse gas (GHG) fluxes. However, the seasonal variations of GHG emissions from sheepfolds, and the underlying biotic and abiotic drivers affecting GHG exchanges across different steppe and management types remain largely unclear.MethodsTaking the Inner Mongolian grassland as a model system, we measured the fluxes of CO2, CH4 and N2O, as well as soil and vegetation variables, in three contrasting grassland management areas (grazing, sheepfold, enclosure) and in three representative (wet typical, dry typical, desert) grassland ecosystems in July, September and November 2016.ResultsOur results showed that: (1) GHG fluxes were mostly higher in the plant growing season (July and September) than in the nongrowing season (November); sheepfold area had significantly higher GHG emissions (in July and mean over the season) than enclosed and grazing areas, with the effects being most pronounced in dry typical steppe. (2) The high GHG emissions in dry typical steppe were closely associated with the interactions among favorable soil temperature and moisture, high total organic carbon (TOC) content, and high aboveground biomass. The important predictors for CO2 emission were soil TOC and pH, whereas that for CH4 and N2O emissions were soil temperature and moisture content, in sheepfold areas. (3) Three GHG emissions were negatively affected by species richness across all steppe and management types, which might be a consequence of indirect effects through the changes in soil TOC and total nitrogen (TN).DiscussionThese results indicate that sheepfold areas are intensive hotspot sources of GHGs in the steppes, and it is of great importance to help to account GHG emissions and develop mitigation strategies for sheepfold areas for sustainable grassland management in the natural steppe based pastoral production ecosystems.

Aim: This review summarized the recent intervertebral disc degeneration (IDD) models and described their advantages and potential disadvantages, aiming to provide an overview for the current condition of IDD model establishment and new ideas for new strategies development of the treatment and prevention of IDD. Methods: The database of PubMed was searched up to May 2021 with the following search terms: nucleus pulposus, annulus fibrosus, cartilage endplate, intervertebral disc(IVD), intervertebral disc degeneration, animal model, organ culture, bioreactor, inflammatory reaction, mechanical stress, pathophysiology, epidemiology. Any IDD model-related articles were collected and summarized. Results: The best IDD model should have the features of repeatability, measurability and controllability. There are a lot of aspects to be considered in the selection of animals. Mice, rats and rabbits are low-cost and easy to access. However, their IVD size and shape are more different from human anatomy than pigs, cattle, sheep and goats. Organ culture models and animal models are two options in model establishment for IDD. The IVD organ culture model can put the studying variables into the controllable system for transitional research. Unlike the animal model, the organ culture model can only be used to evaluate the short-term effects and it is not applicable in simulating the complex process of IDD. Similarly, the animal models induced by different methods also have their advantages and disadvantages. For studying the mechanism of IDD and the corresponding treatment and prevention strategies, the selection of model should be individualized based on the purpose of each study. Conclusions: Various models have different characteristics and scope of application due to their different rationales and methods of construction. Currently, there is no experimental model that can perfectly mimic the degenerative process of human IVD. Personalized selection of appropriate model based on study purpose and experimental designing can enhance the possibility to obtain reliable and real results.

Individuals with diffuse large B cell lymphoma (DLBCL) infected with hepatitis B virus (HBV) have worse chemotherapy efficacy and poorer outcomes. It is still unclear whether long noncoding RNAs (lncRNAs) serve as prognostic and therapeutic targets in the chemotherapy resistance of individuals with DLBCL and HBV infection. Here we found that the core component of HBV (HBX) directly upregulated the expression of lncNBAT1, which was closely associated with the chemotherapy outcomes of HBV-infected individuals with DLBCL. Upregulation of lncNBAT1 reduced the sensitivity of DLBCL cells to chemotherapeutic agents (methotrexate [MTX] or cytarabine [Ara-C]) that induced S phase arrest, whereas knockdown of lncNBAT1 significantly relieved the chemoresistance of HBX-expressing DLBCLs. Mechanistically, lncNBAT1 could interact with the signal transducer and activator of transcription 1 (STAT1) to prevent its enrichment at the promoter region of the functional target gene apolipoprotein B mRNA editing enzyme catalytic subunit 3A (APOBEC3A), inhibiting expression of APOBEC3A and inducing resistance to MTX in DLBCL cells. Furthermore, clinical data analysis showed that lncNBAT1 and APOBEC3A expression was closely related to the poor prognosis and short survival of individuals with DLBCL. Our findings suggest a potential prognostic marker and a candidate lncRNA target for treating HBV-infected individuals with DLBCL.

In order to separate the colloidal in high-turbidity water, a kind of magnetic composite (Fe3O4/HBPN) was prepared via the functional assembly of Fe3O4 and an amino-terminal hyperbranched polymer (HBPN). The physical and chemical characteristics of Fe3O4@HBPN were investigated by different means. The Fourier Transform infrared spectroscopy (FTIR) spectra showed that the characteristic absorption peaks positioned at 1110 cm−1, 1468 cm−1, 1570 cm−1 and 1641 cm−1 were ascribed to C–N, H–N–C, N–H and C=O bonds, respectively. The shape and size of Fe3O4/HBPN showed a different and uneven distribution; the particles clumped together and were coated with an oil-like film. Energy-dispersive spectroscopy (EDS) displayed that the main elements of Fe3O4/HBPN were C, N, O, and Fe. The superparamagnetic properties and good magnetic response were revealed by vibrating sample magnetometer (VSM) analysis. The characteristic diffraction peaks of Fe3O4/HBPN were observed at 2θ = 30.01 (220), 35.70 (311), 43.01 (400), 56.82 (511), and 62.32 (440), which indicated that the intrinsic phase of magnetite remained. The zeta potential measurement indicated that the surface charge of Fe3O4/HBPN was positive in the pH range 4–10. The mass loss of Fe3O4/HBPN in thermogravimetric analysis (TGA) proved thermal decomposition. The –C–NH2 or –C–NH perssad of HBPN were linked and loaded with Fe3O4 particles by the N–O bonds. When the Fe3O4/HBPN dosage was 2.5 mg/L, pH = 4–5, the kaolin concentration of 1.0 g/L and the magnetic field of 3800 G were the preferred reaction conditions. In addition, a removal efficiency of at least 86% was reached for the actual water treatment. Fe3O4/HBPN was recycled after the first application and reused five times. The recycling efficiency and removal efficiency both showed no significant difference five times (p > 0.05), and the values were between 84.8% and 86.9%.

Mycobacterium tuberculosis genome comprises approximately 10% of two families of poorly characterised genes due to their high GC content and highly repetitive nature. The largest sub-group, the proline-glutamic acid polymorphic guanine-cytosine-rich sequence (PE_PGRS) family, is thought to be involved in host response and disease pathogenicity. Due to their high genetic variability and complexity of analysis, they are typically disregarded for further research in genomic studies. There are currently limited online resources and homology computational tools that can identify and analyse PE_PGRS proteins. In addition, they are computational-intensive and time-consuming, and lack sensitivity. Therefore, computational methods that can rapidly and accurately identify PE_PGRS proteins are valuable to facilitate the functional elucidation of the PE_PGRS family proteins. In this study, we developed the first machine learning-based bioinformatics approach, termed PEPPER, to allow users to identify PE_PGRS proteins rapidly and accurately. PEPPER was built upon a comprehensive evaluation of 13 popular machine learning algorithms with various sequence and physicochemical features. Empirical studies demonstrated that PEPPER achieved significantly better performance than alignment-based approaches, BLASTP and PHMMER, in both prediction accuracy and speed. PEPPER is anticipated to facilitate community-wide efforts to conduct high-throughput identification and analysis of PE_PGRS proteins.

Abstract Background Identifying novel regulatory factors and uncovered mechanisms of somatic cell reprogramming will be helpful for basic research and clinical application of induced pluripotent stem cells (iPSCs). Sin3a, a multifunctional transcription regulator, has been proven to be involved in the maintenance of pluripotency in embryonic stem cells (ESCs), but the role of Sin3a in somatic cell reprogramming remains unclear. Methods RNA interference of Sin3a during somatic cell reprogramming was realized by short hairpin RNAs. Reprogramming efficiency was evaluated by the number of alkaline phosphatase (AP)-positive colonies and Oct4-GFP-positive colonies. RNA sequencing was performed to identify the influenced biological processes after Sin3a knockdown and further confirmed by quantitative RT-PCR (qRT-PCR), western blotting and flow cytometry. The interaction between Sin3a and Tet1 was detected by coimmunoprecipitation. The enrichment of Sin3a and Tet1 at the epithelial gene promoters was measured by chromatin immunoprecipitation. Furthermore, DNA methylation patterns at the gene loci were investigated by hydroxymethylated DNA immunoprecipitation. Finally, Sin3a mutants that disrupt the interaction of Sin3a and Tet1 were also introduced to assess the importance of the Sin3a–Tet1 interaction during the mesenchymal-to-epithelial transition (MET) process. Results We found that Sin3a was gradually increased during OSKM-induced reprogramming and that knockdown of Sin3a significantly impaired MET at the early stage of reprogramming and iPSC generation. Mechanistic studies showed that Sin3a recruited Tet1 to facilitate the hydroxymethylation of epithelial gene promoters. Moreover, disrupting the interaction of Sin3a and Tet1 significantly blocked MET and iPSC generation. Conclusions Our studies revealed that Sin3a was a novel mediator of MET during early reprogramming, where Sin3a functioned as an epigenetic coactivator, cooperating with Tet1 to activate the epithelial program and promote the initiation of somatic cell reprogramming. These findings highlight the importance of Sin3a in the MET process and deepen our understanding of the epigenetic regulatory network of early reprogramming.

The buried depth of the main coal beds in SLN Block is more than 1,500 m, and the gas content of the coal beds is high. However, the coal beds are generally in a high geostress environment, the permeability of the coal beds is generally low, and the development effect of conventional fractured straight wells is poor. Fractured horizontal well is an important technical means to improve the development effect of low permeability coalbed methane, but the investment cost is high. To reduce the investment risk of fractured horizontal wells, it is necessary to find out the gas production capacity and main control factors of the fractured horizontal wells, and determine the area suitable for the development of fractured horizontal wells. In the area with permeability higher than 0.28 md and gas content higher than 12.8 m3/t, the daily gas production capacity of fractured horizontal well is 16,450–21500 m3/d, and the development effect is good. The research results are of great significance to quickly evaluate the adaptability of fractured horizontal wells.

BackgroundBladder urothelial carcinoma (BLCA) is associated with high mortality and recurrence. Although mRNA-based vaccines are promising treatment strategies for combating multiple solid cancers, their efficacy against BLCA remains unclear. We aimed to identify potential effective antigens of BLCA for the development of mRNA-based vaccines and screen for immune clusters to select appropriate candidates for vaccination.MethodsGene expression microarray data and clinical information were retrieved from The Cancer Genome Atlas and GSE32894, respectively. The mRNA splicing patterns were obtained from the SpliceSeq portal. The cBioPortal for Cancer Genomics was used to visualize genetic alteration profiles. Furthermore, nonsense-mediated mRNA decay (NMD) analysis, correlation analysis, consensus clustering analysis, immune cell infiltration analysis, and weighted co-expression network analysis were conducted.ResultsSix upregulated and mutated tumor antigens related to NMD, and infiltration of APCs were identified in patients with BLCA, including HP1BP3, OSBPL9, SSH3, ZCCHC8, FANCI, and EIF4A2. The patients were subdivided into two immune clusters (IC1 and IC2) with distinct clinical, cellular and molecular features. Patients in IC1 represented immunologically ‘hot’ phenotypes, whereas those in IC2 represented immunologically ‘cold’ phenotypes. Moreover, the survival rate was better in IC2 than in IC1, and the immune landscape of BLCA indicated significant inter-patient heterogeneity. Finally, CALD1, TGFB3, and ANXA6 were identified as key genes of BLCA through WGCNA analysis, and their mRNA expression levels were measured using qRT-PCR.ConclusionHP1BP3, OSBPL9, SSH3, ZCCHC8, FANCI, and EIF4A2 were identified as potential antigens for developing mRNA-based vaccines against BLCA, and patients in IC2 might benefit more from vaccination.

COVID-19 is the most severe pandemic globally since the 1918 influenza pandemic. Effectively responding to this once-in-a-century global pandemic is a worldwide challenge that the international community needs to jointly face and solve. This study reviews and discusses the key measures taken by major countries in 2020 to fight against COVID-19, such as lockdowns, social distancing, wearing masks, hand hygiene, using Fangcang shelter hospitals, large-scale nucleic acid testing, close-contacts tracking, and pandemic information monitoring, as well as their prevention and control effects. We hope it can help improve the efficiency and effectiveness of pandemic prevention and control in future.

Cashmere, a keratinised product of secondary hair follicles (SHFs) in cashmere goats, holds an important place in international high-end textiles. However, research on the complex molecular and signal regulation during the development and growth of hair follicles (HFs), which is essential for the development of the cashmere industry, is limited. Moreover, increasing evidence indicates that non-coding RNAs (ncRNAs) participate in HF development. Herein, we systematically investigated a competing endogenous RNA (ceRNA) regulatory network mediated by circular RNAs (circRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) in skin samples of cashmere goat embryos, using whole-transcriptome sequencing technology. We obtained 6468, 394, and 239 significantly differentially expressed mRNAs, circRNAs, and miRNAs, respectively. These identified RNAs were further used to construct a ceRNA regulatory network, mediated by circRNAs, for cashmere goats at a late stage of HF development. Among the molecular species identified, miR-184 and fibroblast growth factor (FGF) 10 exhibited competitive targeted interactions. In secondary HF dermal papilla cells (SHF-DPCs), miR-184 promotes proliferation, inhibits apoptosis, and alters the cell cycle via the competitive release of FGF10. This study reports that FGF10 and its interaction with ncRNAs significantly affect SHF-DPCs, providing a reference for research on the biology of HFs in cashmere goats and other mammals.

Awareness of epidemics can influence people’s behavior and further trigger changes in epidemic spreading. Previous studies concentrating on the coupled awareness-epidemic dynamics usually ignore the multi-type information and the heterogeneity of individuals. However, the real-world cases can be more complicated, and the interaction between information diffusion and epidemic spreading needs further study. In this article, we propose an individual-based epidemics and multi-type information spreading (IEMIS) model on two-layered multiplex networks considering positive and negative preventive information and two types of heterogeneity: 1) heterogeneity of aware individual’s state which leads to differences in aware transmission capacity and 2) heterogeneity of individual’s node degree which affects the epidemic infection rate. Based on Micro-Markov Chain approach (MMCA), we derive the theoretical epidemic threshold for the proposed model and validate the results by those obtained with Monto Carlo (MC) simulations. Through extensive simulations, we demonstrate that for epidemics with low infectivity, promoting the diffusion of positive preventive information, enhancing the importance ratio of neighbors who are aware of positive information, and increasing social distance among individuals can effectively suppress epidemic spreading. However, for highly infectious diseases, the influence of these factors becomes limited.

Non-pharmaceutical interventions (NPIs) are essential for the effective prevention and control of the COVID-19 pandemic. However, the scenarios for disease transmission are complicated and varied, and it remains unclear how real-world networks respond to the changes in NPIs. Here, we propose a multi-layer network combining structurally fixed social contact networks with a time-varying mobility network, select the COVID-19 outbreak in two metropolitans in China as case studies, and assess the effectiveness of NPIs. Human mobility, both in relatively fixed places and in urban commuting, is considered. Enclosed places are simulated by three different types of social contact networks, while urban commuting is represented by a time-varying commute network. We provide a composite framework that captures the heterogeneity and time variation of the real world and enables us to simulate large populations with low computational costs. We give out a thorough evaluation of the effectiveness of NPIs (i.e., work from home, school closure, close-off management, public transit limitation, quarantine, and mask use) under certain vaccine coverage varying with implementation timing and intensity. Our results highlight the strong correlation between the NPI pattern and the epidemic mitigation effect and suggest important operational strategies for epidemic control.

The rapid and ongoing spread of the coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emphasizes the urgent need for an easy and sensitive virus detection method. Here, we describe an immunocapture magnetic bead-enhanced electrochemical biosensor for ultrasensitive SARS-CoV-2 detection based on clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) proteins, collectively known as CRISPR-Cas13a technology. At the core of the detection process, low-cast and immobilization-free commercial screen-printed carbon electrodes are used to measure the electrochemical signal, while streptavidin-coated immunocapture magnetic beads are used to reduce the background noise signal and enhance detection ability by separating the excessive report RNA, and a combination of isothermal amplification methods in the CRISPR-Cas13a system is used for nucleic acid detection. The results showed that the sensitivity of the biosensor increased by two orders of magnitude when the magnetic beads were used. The proposed biosensor required approximately 1 h of overall processing time and demonstrated an ultrasensitive ability to detect SARS-CoV-2, which could be as low as 1.66 aM. Furthermore, owing to the programmability of the CRISPR-Cas13a system, the biosensor can be flexibly applied to other viruses, providing a new approach for powerful clinical diagnostics.

Abstract Phytolith‐occluded carbon (PhytOC) is an important long‐term stable carbon fraction in grassland ecosystems and plays a promising role in global carbon sequestration. Determination of the PhytOC traits of different plants in major grassland types is crucial for precisely assessing their phytolith carbon sequestration potential. Precipitation is the predominant factor in controlling net primary productivity (NPP) and species composition of the semiarid steppe grasslands. We selected three representative steppe communities of the desert steppe, the dry typical steppe, and the wet typical steppe in Northern Grasslands of China along a precipitation gradient, to investigate their species composition, biomass production, and PhytOC content for quantifying its long‐term carbon sequestration potential. Our results showed that (a) the phytolith and PhytOC contents in plants differed significantly among species, with dominant grass and sedge species having relatively high contents, and the contents are significantly higher in the below‐ than the aboveground parts. (b) The phytolith contents of plant communities were 16.68, 17.94, and 15.85 g/kg in the above‐ and 86.44, 58.73, and 76.94 g/kg in the belowground biomass of the desert steppe, the dry typical steppe, and the wet typical steppe, respectively; and the PhytOC contents were 0.68, 0.48, and 0.59 g/kg in the above‐ and 1.11, 0.72, and 1.02 g/kg in the belowground biomass of the three steppe types. (c) Climatic factors affected phytolith and PhytOC production fluxes of steppe communities mainly through altering plant production, whereas their effects on phytolith and PhytOC contents were relatively small. Our study provides more evidence on the importance of incorporating belowground PhytOC production for estimating phytolith carbon sequestration potential and suggests it crucial to quantify belowground PhytOC production taking into account of plant perenniality and PhytOC deposition over multiple years.

The representation and aggregation of attribute information is the key to address the multi-attribute decision-making (MADM) problems. Based on the error problem of attribute information given by experts and the heterogeneous relationship between attributes, a new MADM method based on q-rung orthopair cloud interaction weighted Maclaurin symmetric mean (q-ROCIWMSM) operator is proposed. In it, this method firstly considers the randomness of evaluation information given by experts, integrates the q-rung orthopair fuzzy (q-ROF) set and cloud model and define the new concept of q-rung orthopair cloud (q-ROC), so as to betray the error distribution characteristics of membership and non-membership information caused by randomness. Then, to investigate the multi-layer heterogeneous relationship among membership functions and different quantitative attributes, the interaction operator and Maclaurin symmetric mean (MSM) operator are introduced into q-ROC information, and the q-ROCIWMSM operator is proposed to aggregate q-ROC information with multi-dimensional parameter characteristics. Thirdly, a framework of MADM based on q-ROCIWMSM operator is established. Finally, a cross-border e-commerce consumption decision-making case is used to test the effectiveness of the proposed method. At the same time, robustness analysis and method comparison analysis further show the advantages of our approach. The study results show that the proposed method can accurately describe the error distribution characteristics of attribute information and eliminate the adverse effects of extreme values in the evaluation information on the decision-making results. In addition, the method proposed in this paper can flexibly reflect the multi-layer heterogeneous relationship between attributes, and has strong flexibility and applicability.

Abstract Background Fetal growth restriction (FGR) contributes the primary cause of perinatal mortality and morbidity with impacts on the long-term health. To determine the core gene expression network and gene signatures, which in combination with ultrasound confirmation will more effectively differentiate constitutionally normal small for gestational age and pathological FGR groups, we performed RNA sequencing for protein-coding genes, lncRNAs, and small RNAs in a case–control study of umbilical cord blood. Results Five pairs of FGR case and control umbilical cord blood samples were used for RNA sequencing and weighted gene co-expression network analysis (WGCNA). Results showed that 339 mRNAs, 295 lncRNAs, and 13 miRNAs were significantly differentially expressed between FGR cases and controls. Bioinformatics analysis indicated that these differentially expressed molecules were mainly involved in metabolism, neural, cardiac, and immune systems, and identified 18 WGCNA modules for FGR. Further quantitative verification was performed using umbilical cord blood and maternal peripheral blood from 12 pairs of FGR cases and controls. The logistic regression and receiver operating characteristic curve indicated that RP11_552M6.1, LINC01291, and Asgr1 in umbilical cord blood, while Sfrp2, miR-432-5p, and miR-1306-3p in maternal peripheral blood had potential significance for FGR. Conclusions We comprehensively profiled the whole-transcriptome landscape of human umbilical cord blood with FGR, constructed the core WGCNA modules, and delineated the critical gene signatures of FGR. These findings provide key insight into intrauterine perturbations and candidate signatures for FGR.

Kidney renal clear cell carcinoma (KIRC) is one of the most prevalent primary malignancies with high heterogeneity in the urological system. Growing evidence implies that lactate is a significant carbon source for cell metabolism and plays a vital role in tumor development, maintenance, and therapeutic response. However, the global influence of lactate-related genes (LRGs) on prognostic significance, tumor microenvironment characteristics, and therapeutic response has not been comprehensively elucidated in patients with KIRC. In the present study, we collected RNA sequencing and clinical data of KIRC from The Cancer Genome Atlas (TCGA), E-MTAB-1980, and GSE22541 cohorts. Unsupervised clustering of 17 differentially expressed LRG profiles divided the samples into three clusters with distinct immune characteristics. Three genes (FBP1, HADH, and TYMP) were then identified to construct a lactate-related prognostic signature (LRPS) using the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses. The novel signature exhibited excellent robustness and predictive ability for the overall survival of patients. In addition, the constructed nomogram based on the LRPS-based risk scores and clinical factors (age, gender, tumor grade, and stage) showed a robust predictive performance. Furthermore, patients classified by risk scores had distinguishable immune status, tumor mutation burden, response to immunotherapy, and sensitivity to drugs. In conclusion, we developed an LRPS for KIRC that was closely related to the immune landscape and therapeutic response. This LRPS may guide clinicians to make more precise and personalized treatment decisions for KIRC patients.

Carbon dioxide (CO2) storage in underwater reservoirs is a valuable method of reducing carbon emissions. Saline aquifers such as those in the South Yellow Sea Basin (SYSB), China, have great potential for geological CO2 storage. Thus, we use the recommended calculation method of USDOE and a formation volume model to determine the geological conditions for CO2 storage and estimate the CO2 storage capacity of the Cenozoic saline aquifers in the SYSB (depth: 800–3200 m). Overall, the SYSB exhibits weak fault activity and seismicity, medium and low geothermal fields, four types of source sandstone reservoir, and four sets of carbon reservoir–caprock assemblages developed from the Cenozoic strata, providing relatively good geological conditions for CO2 storage. The estimated capacity of the Cenozoic strata ranges from 39.59 Gt to 426.94 Gt (average: 155.25 Gt), indicating an extensive storage capacity that can meet the carbon sequestration needs of Shandong and Jiangsu Provinces for approximately 89 years. The Yantai Depression has a lower geothermal gradient and terrestrial heat, weaker seismic activity, and double the storage capacity of the Qingdao Depression, indicating that it is the most suitable area for Cenozoic CO2 storage in the SYSB, whereas the Laoshan Uplift is not suitable for storage. This study provides a scientific basis for the selection of offshore CO2 storage sites.

Acute myocardial infarction (AMI) accompanied by cardiac remodeling still lacks effective treatment to date. Accumulated evidences suggest that exosomes from various sources play a cardioprotective and regenerative role in heart repair, but their effects and mechanisms remain intricate. Here, we found that intramyocardial delivery of plasma exosomes from neonatal mice (npEXO) could help to repair the adult heart in structure and function after AMI. In-depth proteome and single-cell transcriptome analyses suggested that npEXO ligands were majorly received by cardiac endothelial cells (ECs), and npEXO-mediated angiogenesis might serve as a pivotal reason to ameliorate the infarcted adult heart. We then innovatively constructed systematical communication networks among exosomal ligands and cardiac ECs and the final 48 ligand–receptor pairs contained 28 npEXO ligands (including the angiogenic factors, Clu and Hspg2), which mainly mediated the pro-angiogenic effect of npEXO by recognizing five cardiac EC receptors (Kdr, Scarb1, Cd36, etc.). Together, the proposed ligand–receptor network in our study might provide inspiration for rebuilding the vascular network and cardiac regeneration post-MI.

To investigate the feasibility of using absorbable Mg alloy pedicle screws for atlantoaxial dislocation fixation, four types of Mg alloy pedicle screws of different thread forms were designed, and simulation analysis of the pull-out force was performed using the finite element method. Stress and displacement distributions of the atlantoaxial fixation model were obtained. Subsequently, screw samples were prepared using the WE43 Mg alloy for extraction, torsion, and immersion corrosion tests. Finite element analysis results showed that the pull-out forces of triangular, rectangular, trapezoidal, and zigzag thread screws were 552.61, 540.91, 546.4, and 542.74 N, respectively, and the stresses on the screws were 146, 185, 195, and 265 MPa, respectively, when they were pulled out. In other words, the triangular thread screw had the largest pull-out resistance and smallest stress peak. The average corrosion rate of Mg alloy screws in vitro was 0.46 mg·cm−2·day−1. Compared with that before corrosion, the extraction resistance of the corroded screws did not change significantly; however, the torsional strength decreased, but it was still greater than the torque required for screw implantation. It can be concluded that triangular thread Mg alloy pedicle screws have good extraction resistance and mechanical stability and can meet the load-bearing requirements for atlantoaxial dislocation fixation. The degradation of the Mg alloy reduced the mechanical strength of the screws, but the triangularly threaded screws can still maintain their effectiveness.

Summary: Fetal growth restriction (FGR) increases the risk for impaired cognitive function later in life. However, the precise mechanisms remain elusive. Using dexamethasone-induced FGR and protein restriction-influenced FGR mouse models, we observe learning and memory deficits in adult FGR offspring. FGR induces decreased hippocampal neurogenesis from the early post-natal period to adulthood by reducing the proliferation of neural stem cells (NSCs). We further find a persistent decrease of Tet1 expression in hippocampal NSCs of FGR mice. Mechanistically, Tet1 downregulation results in hypermethylation of the Dll3 and Notch1 promoters and inhibition of Notch signaling, leading to reduced NSC proliferation. Overexpression of Tet1 activates Notch signaling, offsets the decline in neurogenesis, and enhances learning and memory abilities in FGR offspring. Our data indicate that a long-term decrease in Tet1/Notch signaling in hippocampal NSCs contributes to impaired neurogenesis following FGR and could serve as potential targets for the intervention of FGR-related cognitive disorders.

Kidney renal clear cell carcinoma (KIRC) has long been identified as a highly immune-infiltrated tumor. However, the underlying role of pyroptosis in the tumor microenvironment (TME) of KIRC remains poorly described. Herein, we systematically analyzed the prognostic value, role in the TME, response to ICIs, and drug sensitivity of pyroptosis-related genes (PRGs) in KIRC patients based on The Cancer Genome Atlas (TCGA) database. Cluster 2, by consensus clustering for 24 PRGs, presented a poor prognosis, likely because malignancy-related hallmarks were remarkably enriched. Additionally, we constructed a prognostic prediction model that discriminated well between high- and low-risk patients and was further confirmed in external E-MTAB-1980 cohort and HSP cohort. By further analyzing the TME based on the risk model, higher immune cell infiltration and lower tumor purity were found in the high-risk group, which presented a poor prognosis. Patients with high risk scores also exhibited higher ICI expression, indicating that these patients may be more prone to profit from ICIs. The sensitivity to anticancer drugs that correlated with model-related genes was also identified. Collectively, the pyroptosis-related prognosis risk model may improve prognostic information and provide directions for current research investigations on immunotherapeutic strategies for KIRC patients.

The intensity of influenza epidemics varies significantly from year to year among regions with similar climatic conditions and populations. However, the underlying mechanisms of the temporal and spatial variations remain unclear. We investigated the impact of urbanization and public transportation size on influenza activity. We used 6-year weekly provincial-level surveillance data of influenza-like disease incidence (ILI) and viral activity in northern China. We derived the transmission potential of influenza for each epidemic season using the susceptible–exposed–infectious–removed–susceptible (SEIRS) model and estimated the transmissibility in the peak period via the instantaneous reproduction number (Rt). Public transport was found to explain approximately 28% of the variance in the seasonal transmission potential. Urbanization and public transportation size explained approximately 10% and 21% of the variance in maximum Rt in the peak period, respectively. For the mean Rt during the peak period, urbanization and public transportation accounted for 9% and 16% of the variance in Rt, respectively. Our results indicated that the differences in the intensity of influenza epidemics among the northern provinces of China were partially driven by urbanization and public transport size. These findings are beneficial for predicting influenza intensity and developing preparedness strategies for the early stages of epidemics.

In addition to serving as the building blocks for protein synthesis, amino acids serve as critical signaling molecules in cells. However, the mechanism through which amino acid signals are sensed in cells is not yet fully understood. This study examined differences in the phosphorylation levels of proteins in response to amino acid signals in Cashmere goat fetal fibroblasts (GFb). Amino acid deficiency was found to induce autophagy and attenuate mammalian/mechanistic target of rapamycin complex (mTORC1)/Unc-51-like autophagy activating kinase 1 (ULK1) signaling in GFb cells. A total of 144 phosphosites on 102 proteins positively associated with amino acid signaling were screened using phosphorylation-based proteomics analysis. The mitogen-activated protein kinase (MAPK) signaling pathway was found to play a potentially important role in the interaction network involved in the response to amino acid signals, according to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and MAPK1/3 may serve as a central hub for the entire network. Motif analysis identified three master motifs, xxx_S_Pxx, xxx_S_xxE, and xxx_S_xDx, which were centered on those phosphosites at which phosphorylation was positively regulated by amino acid signaling. Additionally, the phosphorylation levels of three membrane proteins, the zinc transporter SLC39A7, the sodium-dependent neutral amino acid transporters SLC1A5 and SLC38A7, and three translation initiation factors, eukaryotic initiation factor (eIF)5B, eIF4G, and eIF3C, were positively regulated by amino acid signals. These pivotal proteins were added to currently known signaling pathways to generate a novel model of the network pathways associated with amino acid signals. Finally, the phosphorylation levels of threonine 203 and tyrosine 205 on MAPK3 in response to amino acid signals were examined by western blot analysis, and the results were consistent with the data from the phosphoproteomics analysis. The findings of this study provide new evidence and insights into the precise mechanism through which amino acid signals are sensed and conducted in Cashmere goat fetal fibroblasts.

Periostin, an extracellular matrix protein, is widely expressed in a variety of tissues and cells. It has many biological functions and is related to many diseases: for example, it promotes cell proliferation and differentiation in osteoblasts, which are closely related to osteoporosis, and mediates cell senescence and apoptosis in chondrocytes, which are involved in osteoarthritis. Furthermore, it also plays an important role in mediating inflammation and reconstruction during bronchial asthma, as well as in promoting bone development, reconstruction, repair, and strength. Therefore, periostin has been explored as a potential biomarker for various diseases. Recently, periostin has also been found to be expressed in intervertebral disc cells as a component of the intervertebral extracellular matrix, and to play a crucial role in the maintenance and degeneration of intervertebral discs. This article reviews the biological role of periostin in bone marrow-derived mesenchymal stem cells, osteoblasts, osteoclasts, chondrocytes, and annulus fibrosus and nucleus pulposus cells, which are closely related to spinal degenerative diseases. The study of its pathophysiological effects is of great significance for the diagnosis and treatment of spinal degeneration, although additional studies are needed.

TRIM66 protein has an N-terminal tripartite motif and a C-terminal PHD Bromodomain. Here the authors show the specific histone modification recognition of TRIM66-PHD-Bromodomain through crystallography and biochemistry assay, and further reveal that TRIM66 recognition of certain histone modification is important for DNA damage repair in ESCs.

With the application of Internet of Things (IoT) in tourism, the functions and management modes of tourist attractions are being greatly updated. It becomes a faced problem to assess the intelligence level of IoT-based tourist attractions. The assessment is helpful for managers to equip their tourist attractions with smart services which further improve the management efficiency and tourist satisfaction. However, there are few recognized standards for the implementation of IoT-based tourist attractions, and the common practice of using the average value to replace multiple assessment scores has a shortage. Motivated by these observations, we present a framework of IoT-based intelligent tourist attractions and recognize specific intelligent functions brought by IoT techniques to tourist attractions. Then, two fuzzy TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) approaches, that is, a centroid-based fuzzy TOPSIS and an integral-based fuzzy TOPSIS, are formulated to deal with the inconsistent assessment scores from multiple experts. An application study shows the effectiveness and advantage of our approaches in comparison with the classical TOPSIS. Both the centroid-based fuzzy TOPSIS and the classical TOPSIS cannot reflect the preferences of decision-makers, but their assessment results are not fully consistent. The assessment results by the integral-based fuzzy TOPSIS are subject to the given optimism level which may make difference on assessment orders. We observe some insightful findings helpful for improving the intelligence level of IoT-based tourist attractions.

Protein arginine methyltransferase 5 (PRMT5) catalyzes the formation of mono- or symmetric dimethylarginine residues on histones and non-histone substrates and has been demonstrated to play important roles in many biological processes. In the present study, we observed that PRMT5 is abundantly expressed in spermatogonial stem cells (SSCs) and that Prmt5 deletion results in a progressive loss of SSCs and male infertility. The proliferation of Prmt5-deficient SSCs cultured in vitro exhibited abnormal proliferation, cell cycle arrest in G0/G1 phase and a significant increase in apoptosis. Furthermore, PLZF expression was dramatically reduced in Prmt5-deficient SSCs, and the levels of H3K9me2 and H3K27me2 were increased in the proximal promoter region of the Plzf gene in Prmt5-deficient SSCs. Further study revealed that the expression of lysine demethylases (JMJD1A, JMJD1B, JMJD1C, and KDM6B) was significantly reduced in Prmt5-deficient SSCs and that the level of permissive arginine methylation H3R2me2s was significantly decreased at the upstream promoter region of these genes in Prmt5-deficient SSCs. Our results demonstrate that PRMT5 regulates spermatogonial stem cell development by modulating histone H3 lysine modifications.

A low molecular weight organic compound containing bis-phenol A backbone (BPA-6OH) is reported as a negative-tone photoresist. This material has a high glass transition temperature and excellent thermal stability. A good contrast, well-resolved line pattern around 73.4 nm and sensitivity of 52 µC cm−2 can be received for negative-tone molecular glass photoresist upon exposure in electron beam lithography system. It indicates that the negative-tone molecular glass photoresist is one of the promising candidates for use in electron beam lithography.

Photoresists are radiation-sensitive materials used for forming patterns to build up IC devices. To date, most photoresists have been based on organic polymers, which have been dominating the semiconductor industries over the past few decades. It is obvious that extreme ultraviolet (EUV) lithography has become the next-generation lithography technology. The development of comprehensive performance EUV resist is one of the most critical issues. However, organic polymeric photoresists are difficult to meet the harsh requirements of EUV lithography. Pure inorganic photoresists such as metal salts, hydrogen silsesquioxane (HSQ) are expected for EUV lithography due to their high resistance and high resolution. But the low sensitivity makes them not suitable for high volume manufacturing (HVM). Organic-inorganic hybrid photoresists, containing both organic and inorganic components, are regarded as one of the most promising EUV resists. They combine both merits of organic and inorganic materials and have significant advantages in machinability, etching resistance, EUV absorption, and chemical/thermal stability. Organic-inorganic hybrid photoresists are considered as ideal materials for realizing industrial-grade patterns below 10 nm. This review mainly focuses on the development of organic-inorganic hybrid photoresists over the past decade.

Aims: Management of inflammatory renal disease (IRD) can still be technically challenging for laparoscopic procedures. The aim of the present study was to compare the safety and feasibility of laparoscopic and hand-assisted laparoscopic nephrectomy in patients with IRD. Patients and methods: We retrospectively analyzed the data of 107 patients who underwent laparoscopic nephrectomy (LN) and hand-assisted laparoscopic nephrectomy (HALN) for IRD from January 2008 to March 2020, including pyonephrosis, renal tuberculosis, hydronephrosis, and xanthogranulomatous pyelonephritis. Patient demographics, operative outcomes, and postoperative recovery and complications were compared between the LN and HALN groups. Multivariable logistic regression analysis was conducted to identify the independent predictors of adverse outcomes. Results: Fifty-five subjects in the LN group and 52 subjects in the HALN group were enrolled in this study. In the LN group, laparoscopic nephrectomy was successfully performed in 50 patients (90.9%), while four (7.3%) patients were converted to HALN and one (1.8%) case was converted to open procedure. In HALN group, operations were completed in 51 (98.1%) patients and conversion to open surgery was necessary in one patient (1.9%). The LN group had a shorter median incision length (5 cm versus 7 cm, p

The entire world has suffered a lot since the outbreak of the novel coronavirus (COVID-19) in 2019, so simulation models of COVID-19 dynamics are urgently needed to understand and control the pandemic better. Meanwhile, emotional contagion, the spread of vigilance or panic, serves as a negative feedback to the epidemic, but few existing models take it into consideration. In this study, we proposed an innovative multi-layer hybrid modelling and simulation approach to simulate disease transmission and emotional contagion together. In each layer, we used a hybrid simulation method combining agent-based modelling (ABM) with system dynamics modelling (SDM), keeping spatial heterogeneity while reducing computation costs. We designed a new emotion dynamics model IWAN (indifferent, worried, afraid and numb) to simulate emotional contagion inside a community during an epidemic. Our model was well fit to the data of China, the UK and the US during the COVID-19 pandemic. If there weren't emotional contagion, our experiments showed that the confirmed cases would increase rapidly, for instance, the total confirmed cases during simulation in Guangzhou, China would grow from 334 to 2096, which increased by 528%. We compared the calibrated emotional contagion parameters of different countries and found that the suppression effect of emotional contagion in China is relatively more visible than that in the US and the UK. Due to the experiment results, the proposed multi-layer network model with hybrid simulation is valid and can be applied to the quantitative analysis of the epidemic trends and the suppression effect of emotional contagion in different countries. Our model can be modified for further research to study other social factors and intervention policies in the COVID-19 pandemic or future epidemics.

Pandemics have been recognized as a serious global threat to humanity. To effectively prevent the spread and outbreak of the epidemic disease, theoretical models intended to depict the disease dynamics have served as the main tools to understand its underlying mechanisms and thus interrupt its transmission. Two commonly-used models are mean-field compartmental models and agent-based models (ABM). The former ones are analytically tractable for describing the dynamics of subpopulations by cannot explicitly consider the details of individual movements. The latter one is mainly used to the spread of epidemics at a microscopic level but have limited simulation scale for the randomness of the results. To overcome current limitations, a hierarchical hybrid modeling and simulation method, combining mean-field compartmental model and ABM, is proposed in this paper. Based on this method, we build a hybrid model, which takes both individual heterogeneity and the dynamics of sub-populations into account. The proposed model also investigates the impact of combined interventions (i. e. vaccination and pre-deployment training) for healthcare workers (HCWs) on the spread of disease. Taking the case of 2014-2015 Ebola Virus Disease (EVD) in Sierra Leone as an example, we examine its spreading mechanism and evaluate the effect of prevention by our parameterized and validated hybrid model. According to our simulation results, an optimal combination of pre-job training and vaccination deployment strategy has been identified. To conclude, our hybrid model helps informing the synergistic disease control strategies and the corresponding hierarchical hybrid modeling and simulation method can further be used to understand the individual dynamics during epidemic spreading in large scale population and help inform disease control strategies for different infectious disease.

Flow regime is a key driver of invasive aquatic organisms, and the invasiveness of mangrove species may be simultaneously attributed to plant traits and flowing hydrological conditions at the estuary scale. We focused on hydrological and topographic conditions for a non-native mangrove species, Sonneratia apetala, in Zhangjiang Estuary of Fujian, China. A hydrological model and a micro-topographic model were used to predict its dispersal and early establishment, and field surveys and simulated experiments were integrated to estimate its future dispersal patterns. The mesohaline mudflat with a salinity of 8 ~ 10 PSU at the mangrove seaward edge was the most likely colonization area for S. apetala under current conditions. The south-western region of the estuary with native mangroves was the most likely area for its colonization according to the unstructured-grid finite-volume community ocean model (FVCOM) in September, when the largest tidal currents within a year and the maximum fruit maturity period occur. Approximately 42% of the mudflats throughout the whole estuary may be available for seedling establishment under the future sea-level rise RCP 4.5 scenarios compared with 44% for current establishment; however, the RCP 8.5 scenarios would significantly decrease seedling establishment by 2100 due to serious tidal inundation according to the micro-topographical model.

This paper proposed a hybrid intelligent process model, based on a hybrid model combining the two-temperature model (TTM) and molecular dynamics simulation (MDS) (TTM-MDS). Combined atomistic-continuum modeling of short-pulse laser melting and disintegration of metal films [Physical Review B, 68, (064114):1–22.], and Gaussian process regression (GPR), for micro-electrical discharge machining (micro-EDM) were also used. A model of single-spark micro-EDM process has been constructed based on TTM-MDS model to predict the removed depth (RD) and material removal rate (MRR). Then, a GPR model was proposed to establish the relationship between input process parameters (energy area density and pulse-on duration) and the process responses (RD and MRR) for micro-EDM machining. The GPR model was trained, tested, and tuned using the data generated from the numerical simulations. Through the GPR model, it was found that micro-EDM process responses can be accurately predicted for the chosen process conditions. Therefore, the hybrid intelligent model proposed in this paper can be used for a micro-EDM process to predict the performance.

Poker has been considered a challenging problem in both artificial intelligence and game theory because poker is characterized by imperfect information and uncertainty, which are similar to many realistic problems like auctioning, pricing, cyber security, and operations. However, it is not clear that playing an equilibrium policy in multi-player games would be wise so far, and it is infeasible to theoretically validate whether a policy is optimal. Therefore, designing an effective optimal policy learning method has more realistic significance. This paper proposes an optimal policy learning method for multi-player poker games based on Actor-Critic reinforcement learning. Firstly, this paper builds the Actor network to make decisions with imperfect information and the Critic network to evaluate policies with perfect information. Secondly, this paper proposes a novel multi-player poker policy update method: asynchronous policy update algorithm (APU) and dual-network asynchronous policy update algorithm (Dual-APU) for multi-player multi-policy scenarios and multi-player sharing-policy scenarios, respectively. Finally, this paper takes the most popular six-player Texas hold ’em poker to validate the performance of the proposed optimal policy learning method. The experiments demonstrate the policies learned by the proposed methods perform well and gain steadily compared with the existing approaches. In sum, the policy learning methods of imperfect information games based on Actor-Critic reinforcement learning perform well on poker and can be transferred to other imperfect information games. Such training with perfect information and testing with imperfect information models show an effective and explainable approach to learning an approximately optimal policy.