Observation of the effect of hypothermia therapy combined with optimized nursing on brain protection after cardiopulmonary resuscitation: A retrospective case-control study.

This study aimed to investigate the impact of optimized emergency nursing in conjunction with mild hypothermia nursing on neurological prognosis, hemodynamics, and complications in patients with cardiac arrest. A retrospective analysis was conducted on the medical records of 124 patients who received successful cardiopulmonary resuscitation (CPR) at Fujian Provincial Hospital South Branch. The patients were divided into control and observation groups, each consisting of 62 cases. The brain function of both groups was assessed using the Glasgow Coma Scale and the National Institutes of Health Stroke Scale. Additionally, serum neuron-specific enolase level was measured in both groups. The vital signs and hemodynamics of both groups were analyzed, and the complications and satisfaction experienced by the 2 groups were compared. The experimental group exhibited significantly improved neurological function than the control group (P < .05). Furthermore, the heart rate in the experimental group was significantly lower than the control group (P < .05). However, no significant differences were observed in blood oxygen saturation, mean arterial pressure, central venous pressure, and systolic blood pressure between the 2 groups (P > 0.05). Moreover, the implementation of optimized nursing practices significantly reduced complications and improved the quality of life and satisfaction of post-CPR patients (P < .05). The integration of optimized emergency nursing practices in conjunction with CPR improves neurological outcomes in patients with cardiac arrest.

Effect of Copper Surface Roughness on the High-Temperature Structural Stability of Single-Layer-Graphene.

Graphene (Gr) has shown great potential in the field of oxidation protection for metals. However, numerous studies have shown that Gr will suffer structural degradation on metal surface during high-temperature oxidation, which significantly limited the effectiveness of their oxidation protection. Therefore, understanding the degradation mechanism of Gr is of great interest to enhance their structural stability. Here, the effect of copper (Cu) surface roughness on the high-temperature structural stability of single-layer graphene (SLG) was examined using Cu covered with SLG as a model material. SLG/Cu with different roughness values was obtained via high-temperature annealing of the model material. After high-temperature oxidation at 500 °C, Raman spectra analysis showed that the defect density of the oxidized SLG increased from 41% to 81% when the surface roughness varied from 37 nm to 81 nm. Combined with density functional theory calculations, it was found that the lower formation energy of the C-O bond on rough Cu surfaces (0.19 eV) promoted the formation of defects in SLG. This study may provide guidance for improving the effectiveness of SLG for the oxidation protection of metallic materials.

Flexible calorimetric flow sensor with unprecedented sensitivity and directional resolution for multiple flight parameter detection.

The accurate perception of multiple flight parameters, such as the angle of attack, angle of sideslip, and airflow velocity, is essential for the flight control of micro air vehicles, which conventionally rely on arrays of pressure or airflow velocity sensors. Here, we present the estimation of multiple flight parameters using a single flexible calorimetric flow sensor featuring a sophisticated structural design with a suspended array of highly sensitive vanadium oxide thermistors. The proposed sensor achieves an unprecedented velocity resolution of 0.11 mm·s-1 and angular resolution of 0.1°. By attaching the sensor to a wing model, the angles of attack and slip were estimated simultaneously. The triaxial flight velocities and wing vibrations can also be estimated by sensing the relative airflow velocity due to its high sensitivity and fast response. Overall, the proposed sensor has many promising applications in weak airflow sensing and flight control of micro air vehicles.

Leptin receptor Gln223Arg and Lys109Arg polymorphisms may be associated with HBV-related hepatocellular carcinoma risk: A system review and meta-analysis.

Increasing evidence has suggested a strong association of hepatocellular carcinoma (HCC) susceptibility and Gln223Arg (rs1137101) and Lys109Arg (rs1137100) polymorphisms in leptin receptor (LEPR) genes. To provide a quantitative assessment for such correlation, we reviewed all related systems and conducted meta-analysis for case and control researches. A literature search of Web of Science, EMBASE, PubMed, Scopus as well as China National Knowledge Infrastructure databases was collected. 95% confidence intervals (95% CIs) together with odds ratios (ORs) were calculated. Five case-control researches consisting of 1323 cases and 1919 control cases were incorporated into meta-analysis. Researches indicated A-allelic and AA genotype of rs1137101 were substantially related to boosted susceptibility of hepatitis B virus (HBV)-related HCC (mutant model, OR = 1.81, 95% CI = 1.36-2.41, p < .001; allelic model, OR = 1.55, 95% CI = 1.32-1.83, p < .001). On the contrary, we observed GG genotype of rs1137101 substantially related to reduced risk of HBV-related HCC (wild model, OR 0.59, 95%CI = 0.46-0.75, p < .001). We observed AA genotype of rs1137100 relevant to boosted HCC risk (mutant model, OR = 1.51, 95%CI = 1.14-2.01, p = .005) as well as in those with HBV-related HCCs (homozygous model, OR = 2.12, 95%CI = 1.49-3.02, p < .001; mutant model, OR = 1.67, 95%CI = 1.23-2.26, p = .001). G-allele and AA genotype of rs1137101 might be in connection with boosted HBV-related HCC susceptibility, and wild-type GG genotype might prevent diseases. AA genotype of rs1137100 might also improve HBV-related HCC susceptibility. Such conclusions ought to be validated by larger and better-designed researches.

A Highly Sensitive Deep-Sea Hydrodynamic Pressure Sensor Inspired by Fish Lateral Line.

Hydrodynamic pressure sensors offer an auxiliary approach for ocean exploration by unmanned underwater vehicles (UUVs). However, existing hydrodynamic pressure sensors often lack the ability to monitor subtle hydrodynamic stimuli in deep-sea environments. In this study, we present the development of a deep-sea hydrodynamic pressure sensor (DSHPS) capable of operating over a wide range of water depths while maintaining exceptional hydrodynamic sensing performance. The DSHPS device was systematically optimized by considering factors such as piezoelectric polyvinylidene fluoride-trifluoroethylene/barium titanate [P(VDF-TrFE)/BTO] nanofibers, electrode configurations, sensing element dimensions, integrated circuits, and packaging strategies. The optimized DSHPS exhibited a remarkable pressure gradient response, achieving a minimum pressure difference detection capability of approximately 0.11 Pa. Additionally, the DSHPS demonstrated outstanding performance in the spatial positioning of dipole sources, which was elucidated through theoretical charge modeling and fluid-structure interaction (FSI) simulations. Furthermore, the integration of a high Young's modulus packaging strategy inspired by fish skull morphology ensured reliable sensing capabilities of the DSHPS even at depths of 1000 m in the deep sea. The DSHPS also exhibited consistent and reproducible positioning performance for subtle hydrodynamic stimulus sources across this wide range of water depths. We envision that the development of the DSHPS not only enhances our understanding of the evolutionary aspects of deep-sea canal lateral lines but also paves the way for the advancement of artificial hydrodynamic pressure sensors.

Upregulation of outer membrane porin gene ompC contributed to enhancement of azithromycin susceptibility in multidrug-resistant Escherichia coli.

The outer membrane (OM) in gram-negative bacteria contains proteins that regulate the passive or active uptake of small molecules for growth and cell function, as well as mediate the emergence of antibiotic resistance. This study aims to explore the potential mechanisms for restoring bacteria to azithromycin susceptibility based on transcriptome analysis of bacterial membrane-related genes. Transcriptome sequencing was performed by treating multidrug-resistant Escherichia coli T28R with azithromycin or in combination with colistin and confirmed by reverse transcription-quantitative PCR (RT-qPCR). Azithromycin enzyme-linked immunosorbent assay (ELISA) test, ompC gene overexpression, and molecular docking were utilized to conduct the confirmatory research of the potential mechanisms. We found that colistin combined with azithromycin led to 48 differentially expressed genes, compared to azithromycin alone, such as downregulation of tolA, eptB, lpxP, and opgE and upregulation of ompC gene. Interestingly, the addition of colistin to azithromycin differentially downregulated the mph(A) gene mediating azithromycin resistance, facilitating the intracellular accumulation of azithromycin. Also, overexpression of the ompC elevated azithromycin susceptibility, and colistin contributed to further suppression of the Mph(A) activity in the presence of azithromycin. These findings suggested that colistin firstly enhanced the permeability of bacterial OM, causing intracellular drug accumulation, and then had a repressive effect on the Mph(A) activity along with azithromycin. Our study provides a novel perspective that the improvement of azithromycin susceptibility is related not only to the downregulation of the mph(A) gene and conformational remodeling of the Mph(A) protein but also the upregulation of the membrane porin gene ompC.IMPORTANCEUsually, active efflux via efflux pumps is an important mechanism of antimicrobial resistance, such as the AcrAB-TolC complex and MdtEF. Also, bacterial porins exhibited a substantial fraction of the total number of outer membrane proteins in Enterobacteriaceae, which are involved in mediating the development of the resistance. We found that the upregulation or overexpression of the ompC gene contributed to the enhancement of resistant bacteria to azithromycin susceptibility, probably due to the augment of drug uptakes caused and the opportunity of Mph(A) function suppressed by azithromycin with colistin. Under the combination of colistin and azithromycin treatment, OmpC exhibited an increased selectivity for cationic molecules and played a key role in the restoral of the antibiotic susceptibility. Investigations on the regulation of porin expression that mediated drug resistance would be important in clinical isolates treated with antibiotics.

Combining bulk and scRNA-seq to explore the molecular mechanisms governing the distinct efferocytosis activities of a macrophage subpopulation in PDAC.

Pancreatic ductal adenocarcinoma (PDAC), a very aggressive tumour, is currently the third leading cause of cancer-related deaths. Unfortunately, many patients face the issue of inoperability at the diagnostic phase leading to a quite dismal prognosis. The onset of metastatic processes has a crucial role in the elevated mortality rates linked to PDAC. Individuals with metastatic advances receive only palliative therapy and have a grim prognosis. It is essential to carefully analyse the intricacies of the metastatic process to enhance the prognosis for individuals with PDAC. Malignancy development is greatly impacted by the process of macrophage efferocytosis. Our current knowledge about the complete range of macrophage efferocytosis activities in PDAC and their intricate interactions with tumour cells is still restricted. This work aims to resolve communication gaps and pinpoint the essential transcription factor that is vital in the immunological response of macrophage populations. We analysed eight PDAC tissue samples sourced from the gene expression omnibus. We utilized several software packages such as Seurat, DoubletFinder, Harmony, Pi, GSVA, CellChat and Monocle from R software together with pySCENIC from Python, to analyse the single-cell RNA sequencing (scRNA-seq) data collected from the PDAC samples. This study involved the analysis of a comprehensive sample of 22,124 cells, which were classified into distinct cell types. These cell types encompassed endothelial and epithelial cells, PDAC cells, as well as various immune cells, including CD4+ T cells, CD8+ T cells, NK cells, B cells, plasma cells, mast cells, monocytes, DC cells and different subtypes of macrophages, namely C0 macrophage TGM2+, C1 macrophage PFN1+, C2 macrophage GAS6+ and C3 macrophage APOC3+. The differentiation between tumour cells and epithelial cells was achieved by the implementation of CopyKat analysis, resulting in the detection and categorization of 1941 PDAC cells. The amplification/deletion patterns observed in PDAC cells on many chromosomes differ significantly from those observed in epithelial cells. The study of Pseudotime Trajectories demonstrated that the C0 macrophage subtype expressing TGM2+ had the lowest level of differentiation. Additionally, the examination of gene set scores related to efferocytosis suggested that this subtype displayed higher activity during the efferocytosis process compared to other subtypes. The most active transcription factors for each macrophage subtype were identified as BACH1, NFE2, TEAD4 and ARID3A. In conclusion, the examination of human PDAC tissue samples using immunofluorescence analysis demonstrated the co-localization of CD68 and CD11b within regions exhibiting the presence of keratin (KRT) and alpha-smooth muscle actin (α-SMA). This observation implies a spatial association between macrophages, fibroblasts, and epithelial cells. There is variation in the expression of efferocytosis-associated genes between C0 macrophage TGM2+ and other macrophage cell types. This observation implies that the diversity of macrophage cells might potentially influence the metastatic advancement of PDAC. Moreover, the central transcription factor of different macrophage subtypes offers a promising opportunity for targeted immunotherapy in the treatment of PDAC.

CD73/adenosine axis exerts cardioprotection against hypobaric hypoxia-induced metabolic shift and myocarditis in a sex-dependent manner.

BACKGROUND: Clinical and experimental studies have shown that the myocardial inflammatory response during pathological events varies between males and females. However, the cellular and molecular mechanisms of these sex differences remain elusive. CD73/adenosine axis has been linked to anti-inflammatory responses, but its sex-specific cardioprotective role is unclear. The present study aimed to investigate whether the CD73/adenosine axis elicits sex-dependent cardioprotection during metabolic changes and myocarditis induced by hypobaric hypoxia. METHODS: For 7 days, male and female mice received daily injections of the CD73 inhibitor adenosine 5'- (α, ß-methylene) diphosphate (APCP) 10 mg/kg/day while they were kept under normobaric normoxic and hypobaric hypoxic conditions. We evaluated the effects of hypobaric hypoxia on the CD73/adenosine axis, myocardial hypertrophy, and cardiac electrical activity and function. In addition, metabolic homeostasis and immunoregulation were investigated to clarify the sex-dependent cardioprotection of the CD73/adenosine axis. RESULTS: Hypobaric hypoxia-induced cardiac dysfunction and adverse remodeling were more pronounced in male mice. Also, male mice had hyperactivity of the CD73/adenosine axis, which aggravated myocarditis and metabolic shift compared to female mice. In addition, CD73 inhibition triggered prostatic acid phosphatase ectonucleotidase enzymatic activity to sustain adenosine overproduction in male mice but not in female mice. Moreover, dual inhibition prostatic acid phosphatase and CD73 enzymatic activities in male mice moderated adenosine content, alleviating glycolytic shift and proinflammatory response. CONCLUSION: The CD73/adenosine axis confers a sex-dependent cardioprotection. In addition, extracellular adenosine production in the hearts of male mice is influenced by prostatic acid phosphatase and tissue nonspecific alkaline phosphatase.

Internal validation of the GA118-24B Genetic Analyzer, a stable capillary electrophoresis system for forensic DNA identification.

The GA118-24B Genetic Analyzer (hereafter, "GA118-24B") is an independently developed capillary electrophoresis instrument. In the present research, we designed a series of validation experiments to test its performance at detecting DNA fragments compared to the Applied Biosystems 3500 Genetic Analyzer (hereafter, "3500"). Three commercially available autosomal short tandem repeat multiplex kits were used in this validation. The results showed that GA118-24B had acceptable spectral calibration for three kits. The results of accuracy and concordance studies were also satisfactory. GA118-24B showed excellent precision, with a standard deviation of less than 0.1 bp. Sensitivity and mixture studies indicated that GA118-24B could detect low-template DNA and complex mixtures as well as the results generated by 3500 in parallel experiments. Based on the experimental results, we set specific analytical and stochastic thresholds. Besides, GA118-24B showed superiority than 3500 within certain size ranges in the resolution study. Instead of conventional commercial multiplex kits, GA118-24B performed stably on a self-developed eight-dye multiplex system, which were not performed on 3500 Genetic Analyzer. We compared our validation results with those of previous research and found our results to be convincing. Overall, we conclude that GA118-24B is a stable and reliable genetic analyzer for forensic DNA identification.

Fuzzy-Inspired Sensing for Time-Domain Brain Stroke Diagnosis: Disease Retrospective Monitoring Strategy.

This paper propose a novel disease retrospective monitoring strategy (DRMS) for optimal brain stroke diagnosis. We describe the disease monitoring process using a fuzzy-based model and demonstrate the use of information at different time points to improve disease diagnosis accuracy under the framework of fuzzy-inspired sensing (FIS). Numerical examples are used to demonstrate how the proposed DRMS can be used to determine the optimal treatment strategy with the least amount of fuzziness.

Electron Slingshot Acceleration in Relativistic Preturbulent Shocks Explored via Emitted Photon Polarization.

Transient electron dynamics near the interface of counterstreaming plasmas at the onset of a relativistic collisionless shock (RCS) is investigated using particle-in-cell simulations. We identify a slingshotlike injection process induced by the drifting electric field sustained by the flowing focus of backward-moving electrons, which is distinct from the well-known stochastic acceleration. The flowing focus signifies the plasma kinetic transition from a preturbulent laminar motion to a chaotic turbulence. We find a characteristic correlation between the electron dynamics in the slingshot acceleration and the photon emission features. In particular, the integrated radiation from the RCS exhibits a counterintuitive nonmonotonic dependence of the photon polarization degree on the photon energy, which originates from a polarization degradation of relatively high-energy photons emitted by the slingshot-injected electrons. Our results demonstrate the potential of photon polarization as an essential information source in exploring intricate transient dynamics in RCSs with relevance for Earth-based plasma and astrophysical scenarios.

Macrophages in head and neck squamous cell carcinoma: A bibliometric analysis.

INTRODUCTION: The tumor microenvironment in head and neck squamous cell carcinoma (HNSCC) is densely infiltrated by macrophages. Utilizing bibliometric analysis, the characteristics, hotspots for research, and research frontiers related to macrophages in HNSCC were reviewed. METHODS: The Web of Science Core Collection database was queried for relevant articles published from 2000 to 2022. VOSviewer and CiteSpace software were utilized to evaluate and visualize macrophage-related HNSCC research trends and hotspots. RESULTS: Assessment of original articles revealed that the annual number of publications regarding the role of macrophages in HNSCC has increased steadily over the past 23 years. China produced the most articles, whereas the United States had the highest number of citations and highest H-index. Wuhan University and Oral Oncology were the most productive affiliation and journal, respectively. The paper published by Bray et al in the CA-A Cancer Journal for Clinicians in 2018 had the greatest number of citations. The keywords "expression," "cancer," and "tumor-associated macrophages (TAMs)" occurred most frequently. CONCLUSIONS: This bibliometric investigation discovered that publications about macrophages in HNSCC are steadily increasing. The majority of studies focused on macrophage polarization, macrophage markers, and inflammation in the tumor microenvironment. Furthermore, our bibliometric analysis revealed that the immunosuppressive role of tumor-associated macrophages in the tumor microenvironment and resistance to therapy in HNSCC have recently received attention.

Effect of Surface Chemistry on the Electrical Double Layer in a Long-Chain Ionic Liquid.

Room temperature ionic liquids (ILs) can create a strong accumulation of charges at solid interfaces by forming a very thin and dense electrical double layer (EDL). The structure of this EDL has important consequences in numerous applications involving ILs, for example, in supercapacitors, sensors, and lubricants, by impacting the interfacial capacitance, the charge carrier density of semiconductors, as well as the frictional properties of the interfaces. We have studied the interfacial structure of a long chain imidazolium-based IL (1-octyl-3-methylimidazolium dicyanamide) on several substrates: mica, silica, silicon, and molybdenum disulfide (MoS2), using atomic force microscopy (AFM) experiments and molecular dynamics (MD) simulations. We have observed 3 types of interfacial structures for the same IL, depending on the chemistry of the substrate and the water content, showing that the EDL structure is not an intrinsic property of the IL. We evidenced that at a low water content, neutral and apolar (thus hydrophobic) substrates promote a thin layer structure, where the ions are oriented parallel to the substrate and cations and anions are mixed in each layer. In contrast, a strongly charged (thus hydrophilic) substrate yields an extended structuration into several bilayers, while a heterogeneous layering with loose bilayer regions was observed on an intermediate polar and weakly charged substrate and on an apolar one at a high bulk water content. In the latter case, water contamination favors the formation of bilayer patches by promoting the segregation of the long chain IL into polar and apolar domains.

Distribution characteristics and influencing factors of soil organic carbon in tidal flat wetland of central Jiangsu, China.

We measured winter and summer soil organic carbon (SOC) contents in two typical coastal wetlands, the Spartina alterniflora salt marsh and the non-vegetation mudflat, on the south side of the Chuandong River Estuary in Yancheng, Jiangsu Province. We investigated the spatiotemporal variations of soil organic carbon contents and its driving factors. The results showed that SOC content ranged from 0.75 to 2.38 g·kg-1 in the mudflat area and from 2.07 to 18.59 g·kg-1 in the S. alterniflora salt marsh area, showing a decreasing trend towards the sea. The SOC content in the S. alterniflora salt marsh area was approximately 2.5 to 3.5 times of that in the mudflat area. Within a depth range of 1 m, there was no vertical variation in SOC content in the mudflat area, but an increasing and then decreasing pattern in the S. alterniflora marsh area with the peak occurring in the depth range of 20 to 30 cm. Soil organic carbon content exhibited significant seasonal difference, with higher value in summer than in winter. The summer SOC content was 5% to 10% higher than that in winter in the S. alterniflora marsh area, while it was 43% higher in summer than in winter in the mudflat area. In the S. alterniflora marsh area, soil organic carbon content was positively correlated with soil moisture and salinity, but negatively correlated with sediment particle size. In contrast, there was no significant correlation between soil organic carbon content and soil physicochemi-cal factors in the mudflat area. Those results indicated that the correlation between various soil physicochemical factors and SOC is established on the basis of vegetation cover in coastal wetlands. Our findings could provide valuable insights for the conservation of blue carbon ecosystems in coastal wetlands in China.

Is two-point method a valid and reliable method to predict 1RM? A systematic review.

This systematic review aimed to evaluate the reliability and validity of the two-point method in predicting 1RM compared to the direct method, as well as analyze the factors influencing its accuracy. A comprehensive search of PubMed, Web of Science, Scopus, and SPORTDiscus databases was conducted. Out of the 88 initially identified studies, 16 were selected for full review, and their outcome measures were analyzed. The findings of this review indicated that the two-point method slightly overestimated 1RM (effect size = 0.203 [95%CI: 0.132, 0.275]; P < 0.001); It showed that test-retest reliability was excellent as long as the test loads were chosen reasonably (Large difference between two test loads). However, the reliability of the two-point method needs to be further verified because only three studies have tested its reliability. Factors such as exercise selection, velocity measurement device, and selection of test loads were found to influence the accuracy of predicting 1RM using the two-point method. Additionally, the choice of velocity variable, 1RM determination method, velocity feedback, and state of fatigue were identified as potential influence factors. These results provide valuable insights for practitioners in resistance training and offer directions for future research on the two-point method.

Wafer-scale patterning of high-resolution quantum dot films with a thickness over 10 µm for improved color conversion.

Quantum dots (QDs) are promising color conversion materials for efficient full-color micro light-emitting diode (micro-LED) displays owing to their high color purity and wide color gamut. However, achieving high-resolution QD patterns with enough thickness for efficient color conversion is challenging. Here, we demonstrate a facile and compatible approach by combining replicate molding, plasma etching and transfer printing to produce QD patterns with a sufficient thickness over ten micrometers in a wide range of resolutions. Our technique can remarkably simplify the preparation of QD inks and minimize optical damage to QD materials. The pixel resolution and thickness of QD patterns can be controlled by well-defining the microstructures of the molding template and the etching process. The transfer printing process allows QD patterns to be assembled sequentially onto a receiving substrate, which will further improve the original pixel resolution and avoid repetitive optical damage to QDs during the patterning process. Consequently, various QD patterns can be fabricated in this work, including perovskite quantum dot (PQD) patterns with a pixel resolution of up to 669 pixels per inch (ppi) and a maximum thickness of up to 19.74 µm, a wafer-scale high-resolution PQD pattern with sufficient thickness on a flexible substrate, and a dual-color pattern comprising green PQDs and red CdSe QDs. Furthermore, these fabricated QD films with a thickness of over 10 µm show improved color conversion when integrated onto a blue micro-LED, revealing the potential of our technique for full-color micro-LED displays.

PML-mediated nuclear loosening permits immunomodulation of mesenchymal stem/stromal cells under inflammatory conditions.

Nuclear configuration plays a critical role in the compartmentalization of euchromatin and heterochromatin and the epigenetic regulation of gene expression. Under stimulation by inflammatory cytokines IFN-γ and TNF-α, human mesenchymal stromal cells (hMSCs) acquire a potent immunomodulatory function enabled by drastic induction of various effector genes, with some upregulated several magnitudes. However, whether the transcriptional upregulation of the immunomodulatory genes in hMSCs exposed to inflammatory cytokines is associated with genome-wide nuclear reconfiguration has not been explored. Here, we demonstrate that hMSCs undergo remarkable nuclear reconfiguration characterized by an enlargement of the nucleus, downregulation of LMNB1 and LMNA/C, decondensation of heterochromatin, and derepression of repetitive DNA. Interestingly, promyelocytic leukaemia-nuclear bodies (PML-NBs) were found to mediate the nuclear reconfiguration of hMSCs triggered by the inflammatory cytokines. Significantly, when PML was depleted, the immunomodulatory function of hMSCs conferred by cytokines was compromised, as reflected by the attenuated expression of effector molecules in hMSCs and their failure to block infiltration of immune cells to lipopolysaccharide (LPS)-induced acute lung injury. Our results indicate that the immunomodulatory function of hMSCs conferred by inflammatory cytokines requires PML-mediated chromatin loosening.

Efficient Exploration of Chemical Compound Space Using Active Learning for Prediction of Thermodynamic Properties of Alkane Molecules.

We introduce an exploratory active learning (AL) algorithm using Gaussian process regression and marginalized graph kernel (GPR-MGK) to sample chemical compound space (CCS) at minimal cost. Targeting 251,728 enumerated alkane molecules with 4-19 carbon atoms, we applied the AL algorithm to select a diverse and representative set of molecules and then conducted high-throughput molecular simulations on these selected molecules. To demonstrate the power of the AL algorithm, we built directed message-passing neural networks (D-MPNN) using simulation data as the training set to predict liquid densities, heat capacities, and vaporization enthalpies of the CCS. Validations show that D-MPNN models built on the smallest training set considered in this work, which consists of 313 molecules or 0.124% of the original CCS, predict the properties with R2 > 0.99 against the computational data and R2 > 0.94 against the experimental data. The advantage of the presented AL algorithm is that the predicted uncertainty of GPR depends on only the molecular structures, which renders it compatible with high-throughput data generation.

Dynamic simulation of green technology innovation in large construction companies.

The construction sector plays an important role in environmental sustainable development and the green economy. Green technology innovation in the construction sector can improve the energy, cost, and environmental performance of the industry. The lagging effects of influential factors for green technology innovation have yet to be fully understood. This study aims to explore the process of green technology innovation in large construction companies based on the innovation value chain theory and through a system dynamics (SD) approach. The results revealed the dynamic interaction between various influencing factors of green technology innovation in the construction industry. The effects of different knowledge bases and market shares show heterogeneity when the influencing factors are considered as an integrated system. The study helps researchers and practitioners gain a better understanding of the nature of green technology innovation from a systematic view. Suggestions are provided for decision-makers and practitioners to better manage green technology innovation.