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Abstract We reported here on the development of a pharmacometric framework to assess patient adherence, by using two population‐based approaches – the percentile and the Bayesian method. Three different dosing strategies were investigated in patients prescribed a total of three doses; (1) non‐observed therapy, (2) directly observed administration of the first dose, and (3) directly observed administration of the first two doses. The percentile approach used population‐based simulations to derive optimal concentration percentile cutoff values from the distribution of simulated drug concentrations at a specific time. This was done for each adherence scenario and compared to full adherence. The Bayesian approach calculated the posterior probability of each adherence scenario at a given drug concentration. The predictive performance (i.e., Youden index, receiver operating characteristic [ROC] curve) of both approaches were highly influenced by sample collection time (early was better) and interindividual variability (smaller was better). The complexity of the structural model and the half‐life had a minimal impact on the predictive performance of these methods. The impact of the assay limitation (LOQ) on the predictive performance was relatively small if the fraction of LOQ data was less than 20%. Overall, the percentile method performed similar or better for adherence predictions compared to the Bayesian approach, with the latter showing slightly better results when investigating the adherence to the last dose only. The percentile approach showed acceptable adherence predictions (area under ROC curve > 0.74) when sampling the antimalarial drugs piperaquine at day 7 postdose and lumefantrine at day 3 postdose (i.e., 12 h after the last dose). This could be a highly useful approach when evaluating programmatic implementations of preventive and curative antimalarial treatment programs in endemic areas.

Silicon is considered one of the most promising anode materials owing to its high theoretical energy density, however, the volume expansion/contraction during electrochemical lithiation/delithiation cycles leads to instability of the solid electrolyte interphase (SEI), which ultimately results in capacity degradation. Herein, the local stress and deformation evolution status of an SEI layer on an anode particle are investigated through a quantitative electrochemical-mechanical model. The impacts of structural uniformity, mechanical strength, and operating conditions on the stability of the SEI layer are investigated in detail. The simulation results demonstrate that when the silicon particle radius decreases from 800 ​nm to 600 and 400 ​nm, the failure time increases by 29% and 65%, respectively, of the original failure time; When the structural defect depth ratio is reduced from 0.6 to 0.4 and 0.2, the failure time increases by 72% and 132%, respectively; For the discharge rate, the condition at 0.1 C has 34% and 139% longer time to failure than that at 0.2 C and 0.3 C, respectively. This work provides insight into the rational design of stable SEI layers and sheds light on possible methods for constructing silicon-based lithium-ion batteries with longer cycling lives.

Abstract Previous studies have shown that the three-dimensional (3D) geometric and electronic structure of molecules play a crucial role in determining their key properties and intermolecular interactions. Therefore, it is necessary to establish a quantum chemical (QC) property database containing the most stable 3D geometric conformations and electronic structures of molecules. In this study, a high-quality QC property database, called QuanDB, was developed, which included structurally diverse molecular entities and featured a user-friendly interface. Currently, QuanDB contains 154,610 compounds sourced from public databases and scientific literature, with 10,125 scaffolds. The elemental composition comprises nine elements: H, C, O, N, P, S, F, Cl, and Br. For each molecule, QuanDB provides 53 global and 5 local QC properties and the most stable 3D conformation. These properties are divided into three categories: geometric structure, electronic structure, and thermodynamics. Geometric structure optimization and single point energy calculation at the theoretical level of B3LYP-D3(BJ)/6-311G(d)/SMD/water and B3LYP-D3(BJ)/def2-TZVP/SMD/water, respectively, were applied to ensure highly accurate calculations of QC properties, with the computational cost exceeding 107 core-hours. QuanDB provides high-value geometric and electronic structure information for use in molecular representation models, which are critical for machine-learning-based molecular design, thereby contributing to a comprehensive description of the chemical compound space. As a new high-quality dataset for QC properties, QuanDB is expected to become a benchmark tool for the training and optimization of machine learning models, thus further advancing the development of novel drugs and materials. QuanDB is freely available, without registration, at https://quandb.cmdrg.com/ .

Molecular conformations generation (MCG) aims to efficiently obtain reasonable and stable three-dimensional (3D) atomic coordinates of the atoms in the molecule from scratch, providing a structural foundation for molecular representation learning models and advanced downstream molecular design tasks such as molecular property prediction, molecular generation, and molecular docking. Existing MCG methods mostly rely on indirect distance-based strategies, which which can result in geometrically unrealistic conformations, or direct coordinate-based methods, which have larger search spaces and are prone to overfitting. Therefore, this study introduces Conf-GEM, a novel geometric information-assisted direct conformation generation model based on E-GeoGNN, a geometrically augmented 3D graph neural network with multiple scales. Pre-training and divide-and-conquer strategies, are integrated into the proposed model. Conf-GEM outperforms RDKit and nine deep-learning-based MCG models on the GEOM-QM9 and GEOM-Drugs datasets, achieving conformational coverage of 96.69% and 96.07%, respectively, without force field optimization. It also excels on the X-ray diffraction crystal structure dataset with up to 97.04% conformational coverage. In conclusion, Conf-GEM provides a novel solution for stabilizing 3D conformations generation. We provide an online prediction service (https://confgem.cmdrg.com) with a user-friendly interface for researchers.

ABSTRACTDiscrete Global Grid Systems (DGGSs) are an emerging Earth reference model that support the integration and analysis of remote sensing (RS) data. Grid modeling, sampling, quantization, and storage are the key points and difficulties of DGGS. The Icosahedral Snyder Equal-area Aperture-4 Hexagonal DGGS was introduced as the basic framework to improve the geospace sampling efficiency. We presented an approach for precise hexagonal pixel modeling and an easy-sharing storage scheme compatible with open-standard formats for RS images based on the DGGS. Firstly, the proposed interpolation is computed by overlaps between quadrilateral and hexagonal pixels. The hexagonal grids were then mapped onto the icosahedral surface, and a strict correspondence between hexagonal and rectangular pixels is established. The open-standard formats were used to accurately store the hexagonal attribute values and metadata. Finally, a multiscale hexagonal aggregation algorithm based on the dataset was designed. Experiments showed that the proposed modeling methodology had a higher accuracy and smaller errors. The hexagonal data can be stored as regular rectangles with a fixed pattern in any standard format. This storage scheme was more conducive to data processing and sharing compared to SMOS, which was expected to promote hexagonal DGGS in RS data organization, processing and sharing.

ABSTRACTThe icosahedron is currently the mainstream polygon in research and application of discrete global grid systems (DGGS). However, compared to the rhombic triacontahedron (RT), the icosahedron has disadvantages, such as lower sphere-fitting accuracy, greater projection distortion, and difficulty in incorporating the matrix structure for geospatial data storage. More importantly, the special positional relationship between the rhombic triacontahedron and the Earth enables it to effectively support event simulations related to geographical locations. To this end, bidirectional mapping of the hexagonal grid between the RT and icosahedron was proposed, which can efficiently integrate the existing datasets and algorithms of icosahedral DGGS into RT DGGS, thereby achieving seamless conversion between heterogeneous grid systems. We established geometric and topological correlations between the RT and icosahedron, abstracted the spatial algebraic structures of hexagonal grids on the two different polygons, and constructed mapping relationships between them. Finally, conversion between heterogeneous grid indices was achieved using dual quaternions. Experiments revealed that the proposed method was 3.9150 and 2.8151 times more efficient at grid conversion from RT to icosahedron and from icosahedron to RT, respectively, than was a method using latitude/longitude coordinates as a medium.

ABSTRACTDiscrete Global Grid System (DGGS) is a hierarchical structure with seamless global coverage, supporting processing and analysis of heterogeneous geospatial data. Compared with the most commonly used icosahedron, the rhombic triacontahedron (RT) approximates Earth better and can improve the accuracy of data modeling and expression. However, current RT DGGS studies have adopted a single-resolution integer coordinate scheme within a single surface that cannot achieve multilevel grid analysis. To this end, three adjacent surfaces are combined and a three-axis integer coordinate system is established to reduce the number of times crossing the surface. Then, the principle for partitioning aperture 4 hexagonal grids and a quadtree hierarchical encoding scheme are proposed. Further, this study establishes a fast transformation between the code and three-axis coordinates, implements hierarchical and neighbor code operations, and designs a transformation between the code and geographic coordinates. Experimental results indicate that, compared with the icosahedral hexagonal DGGS, the proposed scheme has a significant efficiency advantage in the transformation between the code and geographic coordinates, while the neighbor code operation efficiency can reach 40.97 times that of HLQT and 4.35 times that of HHUT. The proposed scheme provides a more suitable framework for organizing and analyzing global geospatial data.

The photonics-assisted millimeter-wave (MMW) communication technology is attractive to facilitate the MMW application in the upcoming B5G and 6G networks. However, its generated MMW signal by optical heterodyne detection usually suffers from serious laser phase noise, which will severely deteriorate the system performance. In this paper, based on a single dual-drive Mach-Zehnder modulator and a single-end photodetector, we first present a simple and spectrally efficient hybrid fiber-wireless double-sideband transmission by employing an overlapping frequency multiplexing scheme. That is, two independent wireless signals with an identical carrier frequency can be simultaneously transmitted in the hybrid fiber-wireless links. To recover the above two overlapped signals, and cancel the concomitant laser phase noise at the same time, a novel digital signal processing method for carrier extraction and signal recovery is further proposed. A proof-of-concept experiment using two independent 3-GBd quadrature phase shift keying (QPSK) signals at W band (92.5 GHz) is performed. After up to 80-km fiber and 3-m wireless transmission, the two QPSK signals can be successfully demodulated, without using the traditional carrier phase estimation algorithm. The proposed scheme not only can double the spectral efficiency of conventional double sideband transmission scheme, but also is immune to its power fading phenomenon induced by chromatic dispersion and robust to the laser phase noise resulting from two free-running lasers in the photonics-assisted MMW communication link.

Highlights The strongly coupled Ag/Sn–SnO2 nanosheets (NSs) were prepared via a versatile electrochemical template strategy, and the generated electron-enriched Sn sites promote the formation of *OCHO and alleviate the energy barriers of *OCHO to *HCOOH. Ag/Sn–SnO2 NSs afford a superior activity toward CO2 electroreduction with current densities up to 2000 mA cm‒2 and near-unity selectivity for formate production. Ag/Sn–SnO2 NSs as the cathode in a membrane electrode assembly with porous solid electrolyte reactor enable the direct production of ~ 0.12 M pure HCOOH solution for 200 h.

The Yangtze River estuary (YRE) are strongly influenced by the Kuroshio and terrigenous input from rivers, leading to the formation of distinct water masses, however, there remains a limited understanding of the full extent of this influence. Here the variation of water masses and bacterial communities of 58 seawater samples from the YRE and its adjacent waters were investigated. Our findings suggested that there were 5 water masses in the studied area: Black stream (BS), coastal water in the East China Sea (CW), nearshore mixed water (NM), mixed water in the middle and deep layers of the East China Sea (MM), and deep water blocks in the middle of the East China Sea (DM). The CW mass harbors the highest alpha diversity across all layers, whereas the NM mass exhibits higher diversity in the surface layer but lower in the middle layers. Proteobacteria was the most abundant taxa in all water masses, apart from that, in the surface layer masses, Cyanobacterium, Bacteroidota, and Actinobacteriota were the highest proportion in CW, while Bacteroidota and Actinobacteriota were the highest proportion in NM and BS; in the middle layer, Bacteroidota and Actinobacteriota were dominant phylum in CW and BS masses, but Cyanobacterium was main phylum in NM mass; in the bottom layer, Bacteroidota and Actinobacteriota were the dominant phylum in CW, while Marininimicrobia was the dominated phylum in DM and MM masses. Network analysis suggests water masses have obvious influence on community topological characteristics, moreover, community assembly across masses also differ greatly. Taken together, these results emphasized the significant impact of water masses on the bacterial composition, topological characteristics and assembly process, which may provide a theoretical foundation for predicting alterations in microbial communities within estuarine ecosystems under the influence of water masses.

We successfully demonstrate 32-Gbaud Probabilistically Shaped 4096-ary Quadrature Amplitude Modulation (PS-4096QAM) TeraHertz (THz) signal wired transmission at 325 ​GHz over the 1-m Hollow-Core Fiber (HCF) in a photon-assisted THz-wave communication system. By employing advanced Digital Signal Processing (DSP) and the PS technique, the 352-Gbit/s line rate (288-Gbit/s net rate) delivery with a net Spectral Efficiency (SE) of 9 bit/s/Hz is realized in the experiment, satisfying the 0.86-Normalized Generalized Mutual Information (NGMI) Low-Density Parity-Check (LDPC) threshold. © 2021 Elsevier Science. All rights reserved.

Aiming at the drawbacks of Hunger Games Search (HGS) algorithm, such as slow convergence speed and the tendency to fall into local optimum, a Multi-strategy fusion Improved Adaptive Hunger Games Search (MIA-HGS) algorithm is proposed. Firstly, a good point set is employed to generate a more diverse initial population. Secondly, the control strategy selection parameter is fixed in the original HGS algorithm; an adaptive adjustment parameter is proposed to replace the fixed parameters, whose dynamically tuned update strategy strengthens the global searching ability. Finally, to further jump out of the local optimum, a mutation operation based on Logarithmic spiral opposition-based learning is performed on a population for a certain condition. Simulation experiments are carried out for 23 benchmark functions and the UAV aerial planning problem. The results show that MIA-HGS solves more accurately and converges more rapidly than the original HGS algorithm on 23 benchmark functions, with MIA-HGS leading on 69.5% of the tested functions and tying with HGS on 21.7% of the tested functions. It also showed better performance than the other algorithms on the UAV flight planning problem.

Discrete Global Grid System (DGGS) is a new multi-resolution geospatial data modeling and processing scheme for the digital earth. The icosahedron is commonly regarded as an ideal polyhedron for constructing DGGSs with small distortions; however, the shape of its face is triangular, making it difficult to incorporate the matrix structure used for geospatial data storage and parallel computing. To overcome this limitation, this study utilizes the rhombic triacontahedron (RT) as the basic polyhedron to construct DGGSs. An equal-area projection between the surface of RT and the sphere is developed and used to design a grid-generation algorithm for the aperture 4 hexagonal DGGS based on RT. Compared with the equal-area DGGS based on the icosahedron, the proposed scheme results in smaller angular projection distortions, with the mean and standard deviation decreasing by 41.6% and 30.9%, respectively. The grid cells of the RT DGGS also achieve more optimized geometric characteristics in shape compactness, length deviation, and angle deviation than those in the icosahedron DGGS. Additionally, the cross-surface computation efficiency provides advantages in code conversion to latitude and longitude and proximity queries. Furthermore, the use of RT offers a new and better framework within the context of DGGS research and application.

Abstract Background Alternative splicing (AS) is an important channel for gene expression regulation and protein diversification, in addition to a major reason for the considerable differences in the number of genes and proteins in eukaryotes. In plants, U2 small nuclear ribonucleoprotein B″ (U2B″), a component of splicing complex U2 snRNP, plays an important role in AS. Currently, few studies have investigated plant U2B″, and its mechanism remains unclear. Result Phylogenetic analysis, including gene and protein structures, revealed that U2B″ is highly conserved in plants and typically contains two RNA recognition motifs. Subcellular localisation showed that OsU2B″ is located in the nucleus and cytoplasm, indicating that it has broad functions throughout the cell. Elemental analysis of the promoter region showed that it responded to numerous external stimuli, including hormones, stress, and light. Subsequent qPCR experiments examining response to stress (cold, salt, drought, and heavy metal cadmium) corroborated the findings. The prediction results of protein–protein interactions showed that its function is largely through a single pathway, mainly through interaction with snRNP proteins. Conclusion U2B″ is highly conserved in the plant kingdom, functions in the nucleus and cytoplasm, and participates in a wide range of processes in plant growth and development.

TRPV1 channel agonists and antagonists, which have powerful analgesic effects without the addictive qualities associated with traditional analgesics, have become a focus area for the development of novel analgesics. In this study, quantitative structure–activity relationship (QSAR) models for three bioactive endpoints (Ki, IC50, and EC50) were successfully constructed using four machine learning algorithms: SVM, Bagging, GBDT, and XGBoost. These models were based on 2922 TRPV1 modulators and incorporated four types of molecular descriptors: Daylight, E-state, ECFP4, and MACCS. After the rigorous five-fold cross-validation and external test set validation, the optimal models for the three endpoints were obtained. For the Ki endpoint, the Bagging-ECFP4 model had a Q2 value of 0.778 and an R2 value of 0.780. For the IC50 endpoint, the XGBoost-ECFP4 model had a Q2 value of 0.806 and an R2 value of 0.784. For the EC50 endpoint, the SVM-Daylight model had a Q2 value of 0.784 and an R2 value of 0.809. These results demonstrate that the constructed models exhibit good predictive performance. In addition, based on the model feature importance analysis, the influence between substructure and biological activity was also explored, which can provide important theoretical guidance for the efficient virtual screening and structural optimization of novel TRPV1 analgesics. And subsequent studies on novel TRPV1 modulators will be based on the feature substructures of the three endpoints.

Salt stress is a lethal abiotic stress threatening global food security on a consistent basis. In this study, we identified an AP2 and B3 domain-containing transcription factor (TF) named SmRAV1, and its expression levels were significantly up-regulated by NaCl, abscisic acid (ABA), and hydrogen peroxide (H2O2) treatment. High expression of SmRAV1 was observed in the roots and sepal of mature plants. The transient expression assay in Nicotiana benthamiana leaves revealed that SmRAV1 was localized in the nucleus. Silencing of SmRAV1 via virus-induced gene silencing (VIGS) decreased the tolerance of eggplant to salt stress. Significant down-regulation of salt stress marker genes, including SmGSTU10 and SmNCED1, was observed. Additionally, increased H2O2 content and decreased catalase (CAT) enzyme activity were recorded in the SmRAV1-silenced plants compared to the TRV:00 plants. Our findings elucidate the functions of SmRAV1 and provide opportunities for generating salt-tolerant lines of eggplant.

In recent years, the widespread application of artificial intelligence algorithms in protein structure, function prediction, and de novo protein design has significantly accelerated the process of intelligent protein design and led to many noteworthy achievements. This advancement in protein intelligent design holds great potential to accelerate the development of new drugs, enhance the efficiency of biocatalysts, and even create entirely new biomaterials. Protein characterization is the key to the performance of intelligent protein design. However, there is no consensus on the most suitable characterization method for intelligent protein design tasks. This review describes the methods, characteristics, and representative applications of traditional descriptors, sequence-based and structure-based protein characterization. It discusses their advantages, disadvantages, and scope of application. It is hoped that this could help researchers to better understand the limitations and application scenarios of these methods, and provide valuable references for choosing appropriate protein characterization techniques for related research in the field, so as to better carry out protein research.

Abstract Background Rice sheath blight, caused by Rhizoctonia solani Kühn (teleomorph: Thanatephorus cucumeris), is one of the most severe diseases in rice (Oryza sativa L.) worldwide. Studies on resistance genes and resistance mechanisms of rice sheath blight have mainly focused on indica rice. Rice sheath blight is a growing threat to rice production with the increasing planting area of japonica rice in Northeast China, and it is therefore essential to explore the mechanism of sheath blight resistance in this rice subspecies. Results In this study, RNA-seq technology was used to analyse the gene expression changes of leaf sheath at 12, 24, 36, 48, and 72 h after inoculation of the resistant cultivar ‘Shennong 9819’ and susceptible cultivar ‘Koshihikari’ with R. solani. In the early stage of R. solani infection of rice leaf sheaths, the number of differentially expressed genes (DEGs) in the inoculated leaf sheaths of resistant and susceptible cultivars showed different regularity. After inoculation, the number of DEGs in the resistant cultivar fluctuated, while the number of DEGs in the susceptible cultivar increased first and then decreased. In addition, the number of DEGs in the susceptible cultivar was always higher than that in the resistant cultivar. After inoculation with R. solani, the overall transcriptome changes corresponding to multiple biological processes, molecular functions, and cell components were observed in both resistant and susceptible cultivars. These included metabolic process, stimulus response, biological regulation, catalytic activity, binding and membrane, and they were differentially regulated. The phenylalanine metabolic pathway; tropane, piperidine, and pyridine alkaloid biosynthesis pathways; and plant hormone signal transduction were significantly enriched in the early stage of inoculation of the resistant cultivar Shennong 9819, but not in the susceptible cultivar Koshihikari. This indicates that the response of the resistant cultivar Shennong 9819 to pathogen stress was faster than that of the susceptible cultivar. The expression of plant defense response marker PR1b gene, transcription factor OsWRKY30 and OsPAL1 and OsPAL6 genes that induce plant resistance were upregulated in the resistant cultivar. These data suggest that in the early stage of rice infection by R. solani, there is a pathogen-induced defence system in resistant rice cultivars, involving the expression of PR genes, key transcription factors, PAL genes, and the enrichment of defence-related pathways. Conclusion The transcriptome data revealed the molecular and biochemical differences between resistant and susceptible cultivars of rice after inoculation with R. solani, indicating that resistant cultivars have an immune response mechanism in the early stage of pathogen infection. Disease resistance is related to the overexpression of PR genes, key transcriptome factors, and PAL genes, which are potential targets for crop improvement.

Abstract Background Ischemic colitis is the most prevalent ischemic injury of the gastrointestinal tract. The majority of patients with mild ischemic colitis usually achieve complete clinical recovery shortly. However, the predictors of longer hospital stay duration are unclear. This study aimed to evaluate the predictors of hospital stay duration for patients with mild ischemic colitis. Methods We retrospectively evaluated 100 patients with mild ischemic colitis between January 2010 and December 2020 at Xiangya Hospital (a tertiary care center). The clinical characteristics and therapeutic drugs of patients who were hospitalized for ≤ 8 days and ≥ 12 days were compared. Results Of the 100 patients included, 63 (63%) were hospitalized for ≤ 8 days and 37 (37%) were hospitalized for ≥ 12 days. Patients with cerebrovascular disease (29.7% vs. 11.1%, p = 0.019) and abdominal surgical history (29.7% vs. 7.9%, p = 0.004) were more likely to be hospitalized for ≥ 12 days than for ≤ 8 days. The d-dimer levels [0.78 (0.41–1.82) vs. 0.28 (0.16–0.73), p = 0.001] and positive fecal occult blood test results (86.5% vs. 60.3%, p = 0.006) were higher in patients who were hospitalized for ≥ 12 days than in those who were hospitalized for ≤ 8 days. Probiotic use was greater in patients hospitalized for ≤ 8 days (76.2% vs. 54.1%, p = 0.022). Multivariate analysis indicated that cerebrovascular disease (odds ratio [OR] = 4.585; 95% confidence interval [CI] 1.129–18.624; p = 0.033), abdominal surgical history (OR = 4.551; 95% CI 1.060–19.546; p = 0.042), higher d-dimer levels (OR = 1.928; 95% CI 1.024–3.632; p = 0.042), and higher positive fecal occult blood test results (OR = 7.211; 95% CI 1.929–26.953; p = 0.003) were associated with longer hospital stays. Conclusion Cerebrovascular disease, abdominal surgical history, higher d-dimer levels, and higher positive fecal occult blood test results are independent and significant factors that influence longer hospital stays for patients with mild ischemic colitis. Probiotics helped reduce hospital stay in these patients.

Abstract Background Frogeye leaf spot (FLS) is a destructive fungal disease that affects soybean production. The most economical and effective strategy to control FLS is the use of resistant cultivars. However, the use of a limited number of resistant loci in FLS management will be countered by the emergence of new high-virulence Cercospora sojina races. Therefore, we identified quantitative trait loci (QTL) that control resistance to FLS and identified novel resistant genes using a genome-wide association study (GWAS) on 234 Chinese soybean cultivars. Results A total of 30,890 single nucleotide polymorphism (SNP) markers were used to estimate linkage disequilibrium (LD) and population structure. The GWAS results showed four loci (p

The preparation of nanocages with unprecedented architectures may lead to new functions. Here the authors report the self-assembly of organic cages featuring twin cavities; the geometry and pocket size determine the molecular packing and the proton conductivity performance.

Abstract Background Multidrug-resistant (MDR) Klebsiella pneumoniae infections, from pancreatic infections to bloodstream infections, influence the mortality of patients with acute pancreatitis (AP) on the condition of limited antibiotic choices. The aim of this study was to investigate the predictor of mortality among AP patients complicated with MDR-K. pneumoniae infections. Methods Seventy-one AP patients who occurred MDR-K. pneumoniae infections from August 1st, 2016 to August 1st, 2020 were enrolled. MDR-K. pneumoniae was defined as the K. pneumoniae strain non-susceptible to at least one agent in three or more antimicrobial categories. MDR-K. pneumoniae isolates were confirmed by Vitek-2 system. Antibiotic susceptibility test was carried out using a micro broth dilution method. Clinical characteristics and drug-resistance rates were retrospectively reviewed, and the predictors of mortality were evaluated by univariate and multivariate analyses. Results The mortality rate of AP patients complicated with MDR-K. pneumoniae infections reached 46.5% (33 of 71), and pancreas (n = 53) was the most common site of MDR-K pneumoniae strains. The drug resistance rates of MDR-K. pneumoniae were high to 11 of 12 common antibiotics (more than 50.0%) except of tigecycline (23.9%). The predictor independently associated with mortality was septic shock (hazard ratio 2.959, 95% confidence intervals 1.396 – 6.272, P = 0.005). Conclusions More attention should be paid for pancreatic MDR-K. pneumoniae infections among AP patients The predictor for mortality of AP patients complicated with MDR-K. pneumoniae infection is septic shock. Therefore, further clinical investigations should focus on areas against septic shock.

As energy and environmental issues become more prominent, people must find sustainable, green development paths. Bio-based polymeric phase change energy storage materials provide solutions to cope with these problems. Therefore, in this paper, a fully degradable polyethylene glycol (PEG20000)/polylactic acid (PLA)/g-C3N4 composite phase change energy storage material (CPCM) was obtained by confinement. The CPCM was characterized by FTIR and SEM for compatibility, XRD and nanoindentation for mechanical properties and DSC, LFA, and TG for thermal properties. The results showed that the CPCM was physical co-mingling; when PLA: PEG: g-C3N4 was 6:3:1, the consistency was good. PEG destroys the crystallization of PLA and causes the hardness to decrease. When PLA: PEG: g-C3N4 was 6: 3: 1, it had a maximum hardness of 0.137 GPa. The CPCM had a high latent enthalpy, and endothermic and exothermic enthalpies of 106.1 kJ/kg and 80.05 kJ/kg for the PLA: PEG: g-C3N4 of 3: 6: 1. The CPCM showed an increased thermal conductivity compared to PLA, reaching 0.30 W/(m·K),0.32 W/(m·K) when PLA: PEG: g-C3N4 was 6: 3: 1 and when PLA: PEG: g-C3N4 was 3: 6: 1, respectively. Additionally, the CPCM was stable within 250 °C, indicating a wide appliable temperature range. The CPCM can be applied to solar thermal power generation, transportation, and building construction.

Routine clinical meropenem therapeutic drug monitoring data can be applied to model-informed precision dosing. The current study aimed to evaluate the adequacy and predictive capabilities of the published models with routine meropenem data and identify the dosing adaptations using a priori and Bayesian estimation. For this, 14 meropenem models for the external evaluation carried out on an independent cohort of 134 patients with 205 meropenem concentrations were encoded in NONMEM 7.3. The performance was determined using: 1) prediction-based and simulation-based diagnostics; and 2) predicted meropenem concentrations by a priori prediction using patient covariates only; and Bayesian forecasting using previous observations. The clinical implications were assessed according to the required dose adaptations using the meropenem concentrations. All assessments were stratified based on the patients with or without continuous renal replacement therapy. Although none of the models passed all tests, the model by Muro et al. showed the least bias. Bayesian forecasting could improve the predictability over an a priori approach, with a relative bias of −11.63–68.89% and −302.96%–130.37%, and a relative root mean squared error of 34.99–110.11% and 14.78–241.81%, respectively. A dosing change was required in 40.00–68.97% of the meropenem observation results after Bayesian forecasting. In summary, the published models couldn’t adequately describe the meropenem pharmacokinetics of our center. Although the selection of an initial meropenem dose with a priori prediction is challenging, the further model-based analysis combining therapeutic drug monitoring could be utilized in the clinical practice of meropenem therapy.

Abstract Background The association of upper gastrointestinal endoscopic findings with sex, age, and Helicobacter pylori infection in asymptomatic healthy people is unclear. The aim of this study was to retrospectively determine the associations of upper gastrointestinal endoscopic findings in asymptomatic healthy people with sex, age, and H. pylori infection. Methods A retrospective study was conducted on 2923 patients from a health examination center in Xiangya Hospital between September 2015 and September 2019. Data on sex, age, H. pylori infection, and gastroscopy results were collected. Results Among 2923 asymptomatic patients who underwent gastroscopy, 2911 (99.59%) had abnormal results. The top three results were chronic gastritis (95.11%), peptic ulcer (17.45%), and duodenitis (9.17%). Inflammation of the gastric mucosa in chronic gastritis was more severe in the H. pylori-positive group. The incidence of peptic ulcer decreased with increasing age and was higher in men, patients aged

Abstract Background Cercospora sojina is a fungal pathogen that causes frogeye leaf spot in soybean-producing regions, leading to severe yield losses worldwide. It exhibits variations in virulence due to race differentiation between strains. However, the candidate virulence-related genes are unknown because the infection process is slow, making it difficult to collect transcriptome samples. Results In this study, virulence-related differentially expressed genes (DEGs) were obtained from the highly virulent Race 15 strain and mildly virulent Race1 strain under nitrogen starvation stress, which mimics the physiology of the pathogen during infection. Weighted gene co-expression network analysis (WGCNA) was then used to find co-expressed gene modules and assess the relationship between gene networks and phenotypes. Upon comparison of the transcriptomic differences in virulence between the strains, a total of 378 and 124 DEGs were upregulated, while 294 and 220 were downregulated in Race 1 and Race 15, respectively. Annotation of these DEGs revealed that many were associated with virulence differences, including scytalone dehydratase, 1,3,8-trihydroxynaphthalene reductase, and β-1,3-glucanase. In addition, two modules highly correlated with the highly virulent strain Race 15 and 36 virulence-related DEGs were found to contain mostly β-1,4-glucanase, β-1,4-xylanas, and cellobiose dehydrogenase. Conclusions These important nitrogen starvation-responsive DEGs are frequently involved in the synthesis of melanin, polyphosphate storage in the vacuole, lignocellulose degradation, and cellulose degradation during fungal development and differentiation. Transcriptome analysis indicated unique gene expression patterns, providing further insight into pathogenesis.

Abstract Background Recently, a new strain of Cercospora sojina (Race15) has been identified, which has caused the breakdown of resistance in most soybean cultivars in China. Despite this serious yield reduction, little is known about why this strain is more virulent than others. Therefore, we sequenced the Race15 genome and compared it to the Race1 genome sequence, as its virulence is significantly lower. We then re-sequenced 30 isolates of C. sojina from different regions to identifying differential virulence genes using genome-wide association analysis (GWAS). Results The 40.12-Mb Race15 genome encodes 12,607 predicated genes and contains large numbers of gene clusters that have annotations in 11 different common databases. Comparative genomics revealed that although these two genomes had a large number of homologous genes, their genome structures have evolved to introduce 245 specific genes. The most important 5 candidate virulence genes were located on Contig 3 and Contig 1 and were mainly related to the regulation of metabolic mechanisms and the biosynthesis of bioactive metabolites, thereby putatively affecting fungi self-toxicity and reducing host resistance. Our study provides insight into the genomic basis of C. sojina pathogenicity and its infection mechanism, enabling future studies of this disease. Conclusions Via GWAS, we identified five candidate genes using three different methods, and these candidate genes are speculated to be related to metabolic mechanisms and the biosynthesis of bioactive metabolites. Meanwhile, Race15 specific genes may be linked with high virulence. The genes highly prevalent in virulent isolates should also be proposed as candidates, even though they were not found in our SNP analysis. Future work should focus on using a larger sample size to confirm and refine candidate gene identifications and should study the functional roles of these candidates, in order to investigate their potential roles in C. sojina pathogenicity.

We experimentally demonstrate the transmission performance of the bit-loading discrete multi-tone (DMT) signal in intensity modulation and direct detection (IM-DD) system with a transmission distance of 2km and a net data rate of 108-Gb/s by two different shaping methods. A detailed comparison between the application of geometric shaping (GS) and probabilistic shaping (PS) in bit-loading DMT is presented. With continuous entropy loading for better channel fitting, probabilistically shaped bit-loading DMT achieves 1-dB receiver sensitivity gain compared to the conventional bit-loading DMT and outperforms geometrically shaped bit-loading DMT in the transmission experiment.

For the millimeter wave (mm-Wave) and terahertz (THz) indoor wireless communication system, the reflection channels need to be characterized and modeled. In this paper, the reflection measurements of the parallel polarized wave are carried out under multiple incident angles and five kinds of materials in the D-band (110–170 GHz). A modified reflection model with two parameters estimated by the minimum mean square error (MMSE) criterion is proposed. The results show that the measurements are in good agreement with the proposed model. Furthermore, a set of measured properties is demonstrated and it can be concluded that both the reflection coefficients and relative permittivity gradually decrease, whereas the surface roughness increases slightly with the increasing frequency, indicating a weak frequency dependence. Interestingly, the concrete board with high surface roughness, which means more power loss in a specular direction, has the lowest reflection loss at a certain frequency and incident angle. It implies that the reflection characteristics of indoor building materials are determined not only by surface roughness, but also by many other factors, such as relative permittivity, frequency, and incident angle. Our work suggests that the reflection measurements of indoor D-band wireless links have a prospective application for future indoor wireless communication systems.

Historical marquisette curtains were composed of lightweight fabrics, woven in an open-mesh and leno-type weave, usually made of silk, and found in Qing imperial buildings. As panel curtains, they were exposed to light, and so underwent fading. This study investigated the manufacturing technology and fading mechanism of dyed marquisette fabric from the Studio of Cleansing Fragrance, the Palace Museum (Beijing). The technological aspects were identified. The types of weave, fiber, and adhesive used to fix the curtain to the wooden frame were identified through microscopic observation and infrared spectroscopy. A color change characterization was performed based on UV-visible diffuse reflectance spectra. The textile colorant was identified as malachite green (MG), and its degradation by light was subsequently studied by dynamic photolysis experiments in a kinetic solution for the rapid exploration of by-products. The main degradation pathways were thus identified and the factors responsible for the induced color changes were discussed. A comparison of the liquid chromatography-mass spectrometry (LC–MS) results of the products derived from the photolysis method as well as of the samples extracted from the object allowed for the identification of the presence of different degradation pathways in the faded and unfaded parts of the textile. A metabolomics analysis was applied to account for the differences in the degradation pathways.

Abstract Background Electrical impedance tomography (EIT) is an emerging imaging technology that has been used to monitor brain injury and detect acute stroke. The time and frequency properties of electrode–skin contact impedance are important for brain EIT because brain EIT measurement is performed over a long period when used to monitor brain injury, and is carried out across a wide range of frequencies when used to detect stroke. To our knowledge, no study has simultaneously investigated the time and frequency properties of both electrode and conductive gel for brain EIT. Methods In this study, the contact impedance of 16 combinations consisting of 4 kinds of clinical electrode and five types of commonly used conductive gel was measured on ten volunteers’ scalp for a period of 1 h at frequencies from 100 Hz to 1 MHz using the two-electrode method. And then the performance of each combination was systematically evaluated in terms of the magnitude of contact impedance, and changes in contact impedance with time and frequency. Results Results showed that combination of Ag+/Ag+Cl− powder electrode and low viscosity conductive gel performed best overall (Ten 20® in this study); it had a relatively low magnitude of contact impedance and superior performance regarding contact impedance with time (p

Background: Lithium is a well-established treatment for bipolar disorders and has been shown to be neuroprotective, and thus low doses might be useful for the treatment of childhood brain injury and neurological sequelae. However, pharmacokinetic (PK) data in children are limited. This study was to investigate the PKs after oral administration of low-dose lithium carbonate in young children with intellectual disability.Methods: Fifty-two children with intellectual disability aged 4–10 years old were enrolled. A series of blood samples were collected after a single-dose administration of lithium carbonate. The serum lithium concentration was measured using a validated ion chromatography assay, and the PK concentration data were modeled using a nonlinear mixed effect model in the NONMEM program.Results: The lithium concentration over time was adequately described by a two-compartment disposition, with a transient absorption and first-order elimination process. The inclusion of body weight as an allometric factor significantly improved the model fit, but age and gender were not associated with the PKs of lithium. The clearance, central volume, inter-compartmental clearance, and peripheral volume estimates from the final population PK model were 0.98 L/h, 13.1 L, 0.84 L/h, and 8.2 L for children with a body weight of 20 kg. The model evaluation suggested that there is no obvious discrepancy between the observations and predictions in the proposed model. A visual predictive check demonstrated the good predictive performance of the final model.Conclusions: The lithium PK properties in young children were similar to those in older children and adults. The proposed model can be used for further PK/PD analysis to optimize the dosage regimen of lithium in children.

In recent years, the delay in sowing has become a major obstacle to high wheat yield in Jiangsu Province, one of the major wheat producing areas in China; hence, it is necessary to screen wheat varieties are resilient for late sowing. This study aimed to provide an effective, fast, and non-destructive monitoring method of soil plant analysis development (SPAD) values, which can represent leaf chlorophyll contents, for late-sown winter wheat variety screening. This study acquired multispectral images using an unmanned aerial vehicle (UAV) at the overwintering stage of winter wheat growth, and further processed these images to extract reflectance of five single spectral bands and calculated 26 spectral vegetation indices. Based on these 31 variables, this study combined three variable selection methods (i.e., recursive feature elimination (RFE), random forest (RF), and Pearson correlation coefficient (r)) with four machine learning algorithms (i.e., random forest regression (RFR), linear kernel-based support vector regression (SVR), radial basis function (RBF) kernel-based SVR, and sigmoid kernel-based SVR), resulted in seven SVR models (i.e., RFE-SVR_linear, RF-SVR_linear, RF-SVR_RBF, RF-SVR_sigmoid, r-SVR_linear, r-SVR_RBF, and r-SVR_sigmoid) and three RFR models (i.e., RFE-RFR, RF-RFR, and r-RFR). The performances of the 10 machine learning models were evaluated and compared with each other according to the achieved coefficient of determination (R2), residual prediction deviation (RPD), root mean square error (RMSE), and relative RMSE (RRMSE) in SPAD estimation. Of the 10 models, the best one was the RF-SVR_sigmoid model, which was the combination of the RF variable selection method and the sigmoid kernel-based SVR algorithm. It achieved high accuracy in estimating SPAD values of the wheat canopy (R2 = 0.754, RPD = 2.017, RMSE = 1.716 and RRMSE = 4.504%). The newly developed UAV- and machine learning-based model provided a promising and real time method to monitor chlorophyll contents at the overwintering stage, which can benefit late-sown winter wheat variety screening.

The synergistic effect of chitosan (CS), glycyrrhizic acid (GA) and ZnO/palygorskite (ZnO/PAL) as potential wound dressing was evaluated in the form of films by the solution casting method. The nanocomposite films were well-characterized with ATR-FTIR, XRD and SEM to explore the interactions between CS, GA and ZnO/PAL. Physical, mechanical and antibacterial properties of the nanocomposite films were systematically investigated for their reliability in end-up utilization. Importantly, it was found that the presence of PAL in the films provided enhanced mechanical properties, whereas CS, GA and ZnO supplied a broad-spectrum antibacterial activity, especially for drug-resistant bacteria such as ESBL—E. coli and MRSA. Overall, this research demonstrated that the prepared films can be a promising candidate for wound-care materials.

Urban evapotranspiration (ET) is an effective way to mitigate ecological challenges resulting from rapid urbanization. However, the characteristics of urban vegetation ET, especially how they respond to meteorological factors and soil water, remains unclear, which is crucial for urban ET regulation. Therefore, this study measured the actual ET rate of an urban lawn (ETlawn) using the Bowen ratio system and an urban tree (Ttree) by a sap flow system in the hot summer of a subtropical megacity, Shenzhen. The results showed that the daily ETlawn was more restricted by energy (Rs) and diffusion conditions (vapor pressure deficit, VPD), while the daily Ttree was more restricted by VPD and relative extractable water (REW) in the urban area. The daily Ttree decreased when the REW was lower than 0.18, while the daily ETlawn started to decrease when it was lower than 0.14. When REW was lower than 0.11, the Ttree stayed at a relatively low level. The impacts of VPD was more evident on the diurnal Ttree than on the diurnal ETlawn. Wind speed had a scarce impact as it was relatively low in urban areas. This study clarifies the different responses of ETlawn and Ttree to meteorological factors and soil water based on actual ET. The results are of great significance for the knowledge of urban forestry and urban hydrology.

Phytophthora root rot (PRR) caused by Phytophthora sojae is a major soybean disease that causes severe economic losses worldwide. Using soybean cultivars carrying a Rps resistance gene is the most effective strategy for controlling this disease. We previously detected a novel Phytophthora resistance gene, RpsZS18, on chromosome 2 of the soybean cultivar Zaoshu18. The aim of the present study was to identify and finely map RpsZS18. We used 232 F2:3 families generated from a cross between Zaoshu18 (resistant) and Williams (susceptible) as the mapping population. Simple sequence repeat (SSR) markers distributed on chromosome 2 were used to map RpsZS18. First, 12 SSR markers linked with RpsZS18 were identified by linkage analyses, including two newly developed SSR markers, ZCSSR33 and ZCSSR46, that flanked the gene at distances of 0.9 and 0.5 cM, respectively. Second, PCR-based InDel markers were developed based on sequence differences between the two parents and used to further narrow down the mapping region of RpsZS18 to 71.3 kb. Third, haplotype analyses were carried out in the RpsZS18 region using 14 soybean genotypes with whole-genome resequencing. We detected six genes with unique haplotype sequences in Zaoshu18. Finally, quantitative real-time PCR assays of the six genes revealed an EF-hand calcium-binding domain containing protein encoding gene (Glyma.02g245700), a pfkB carbohydrate kinase encoding gene (Glyma.02g245800), and a gene with no functional annotation (Glyma.02g246300), are putative candidate PRR resistance genes. This study provides useful information for breeding P. sojae-resistant soybean cultivars.

A series of environment-friendly clay minerals—α-Fe2O3 iron-red hybrid pigments—were prepared by a simple one-step hydrothermal reaction process using natural nanostructured silicate clay minerals as starting materials. The influence of structure, morphology and composition of different clay minerals on the structure, color properties, and stability of the pigments was studied comparatively by systematic structure characterizations with X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmittance electron microscope (TEM), X-ray fluorescence spectroscopy (XRF), X-ray photoelectron spectroscopy (XPS) and CIE-L*a*b* Colorimetric analyses. The results showed that the clay minerals act as green precipitants during the hydrothermal reaction to induce in-situ transformation of Fe(III) ions into Fe2O3 crystals. Meanwhile, they also act as the “micro-reactor„ for forming Fe2O3 crystals and the supporter for inhibiting the aggregation of Fe2O3 nanoparticles. The color properties of iron-red hybrid pigments are closely related to the surface charges, surface silanol groups, and solid acid sites of clay minerals. The clay minerals with higher surface activity are more suitable to prepare iron-red pigments with better performance. The iron-red hybrid pigment derived from illite (ILL) clay showed the best red color performance with the color values of L* = 31.8, a* = 35.2, b* = 27.1, C* = 44.4 and h° = 37.6, and exhibited excellent stability in different chemical environments such as acid, alkaline, and also in high-temperature conditions.

Reversible addition-fragmentation chain transfer (RAFT) is considered to be one of most famous reversible deactivation radical polymerization protocols. Benefiting from its living or controlled polymerization process, complex polymeric architectures with controlled molecular weight, low dispersity, as well as various functionality have been constructed, which could be applied in wide fields, including materials, biology, and electrology. Under the continuous research improvement, main achievements have focused on the development of new RAFT techniques, containing fancy initiation methods (e.g., photo, metal, enzyme, redox and acid), sulfur-free RAFT system and their applications in many fields. This review summarizes the current advances in major bright spot of novel RAFT techniques as well as their potential applications in the optoelectronic field, especially in the past a few years.