Search

Although several synthetic hydrogels with defined stiffness have been developed to facilitate the proliferation and maintenance of human pluripotent stem cells (hPSCs), the influence of biochemical cues in lineage-specific differentiation and functional cluster formation has been rarely reported. Here, we present the application of Supragel, a supramolecular hydrogel formed by synthesized biotinylated peptides, for islet-like cluster differentiation. We observed that Supragel, with a peptide concentration of 5 mg/mL promoted spontaneous hPSCs formation into uniform clusters, which is mainly attributable to a supporting stiffness of ∼1.5 kPa as provided by the Supragel matrix. Supragel was also found to interact with the hPSCs and facilitate endodermal and subsequent insulin-secreting cell differentiation, partially through its components: the sequences of RGD and YIGSR that interacts with cell membrane molecules of integrin receptor. Compared to Matrigel and suspension culturing conditions, more efficient differentiation of the hPSCs was also observed at the stages 3 and 4, as well as the final stage toward generation of insulin-secreting cells. This could be explained by 1) suitable average size of the hPSCs clusters cultured on Supragel; 2) appropriate level of cell adhesive sites provided by Supragel during differentiation. It is worth noting that the Supragel culture system was more tolerance in terms of the initial seeding densities and less demanding, since a standard static cell culture condition was sufficient for the entire differentiation process. Our observations demonstrate a positive role of Supragel for hPSCs differentiation into islet-like cells, with additional potential in facilitating germ layer differentiation.

AIM: To establish an animal model of form deprivation amblyopia based on a simulated cataract intraocular lens (IOLs). METHODS: Poly(dimethyl siloxane)-SiO2 thin films (PSF) with different degrees of opacity as IOL materials were prepared. The light transmission of the PSF-IOL was measured, and its in vitro biosafety was determined by cell counting kit (CCK)-8 assay using the HLEC-B3 cell line and ARPE-19 cell line. Subsequently, the in vivo safety was determined by implanting the PSF-IOL with 10% wt SiO2 into the right eyes of New Zealand white rabbits (PSF-IOL group), and compared with two control groups: contralateral comparison group and normal control (NC) group (Contralateral comparison group: the fellow eye; NC group: a group of binocular normal rabbits without intervention). The flash visual-evoked potentials (F-VEPs) were measured to verify amblyopia. RESULTS: PSFs containing 0, 2%, and 10% wt SiO2 were successfully constructed. The 0 SiO2 PSF was transparent, while the 10% wt SiO2 PSF was completely opaque. It was found that PSF did not induce unwanted cytotoxicity in HLECs and ARPE19 cells in vitro. In vitro, PSF-IOL with 10% wt SiO2 was also non-toxic, and no significant inflammation or structural changes occurred after four weeks of PSF-IOL implantation. Finally, our IOL-simulated congenital cataract rabbit detected by F-VEPs suggested tentative amblyopia. CONCLUSION: A PSF-IOL that mimics cataracts is created. A novel form deprivation model is created by the IOL-simulated congenital cataract rabbit. It can be developed fast and stable and holds great potential for future study.

As data-driven prediction models advance, an increasing number of people are enjoying news personalized to their interests. The primary problem such recommendation models solve is to precisely match information with users and, in so doing, ensure that news spreads with greater efficiency. However, these techniques only help the media platform; they do not help those who produce the news. Hence, we devised a propagation framework based on a human-in-the-loop simulation that helps content authors maximize the spread of their messages through social networks. The framework works by acting on feedback provided by the simulation model. Additionally, the spread of information is formulated as a multi-objective optimization problem in which propagation is data-driven and simulated with machine learning techniques that leverage data on the historical behaviors of users. We additionally describe an implementation for this framework as an example of how the framework might be used in real life. On the practical side, the implementation uses text data from a blog to simulate the message's propagation, while, from a technical point of view, the multi-objective optimization problem is divided into an information retrieval problem and an integer programming problem, the results of which are fed back into the content editor as content operation strategies. A case study with the Sina Weibo microblog site not only validates the framework but also provides practitioners with insights into how to maximize the spread of information through social networking platforms. The results show that the proposed propagation framework is capable of increasing retweets by 7.9575 %. As an interesting aside, our experiments also show that the Weibo retweet lottery is both popular and a highly effective mechanism for increasing reposts.

Objective: Neuropathic pain has been considered as one of the most serious chronic pain subtypes and causes intolerable suffering to patients physically and mentally. This study aimed to verify the analgesic effect of intravenous administration of human umbilical cord mesenchymal stem cells (HUC-MSCs) upon rats with chronic constriction injury (CCI)-induced neuropathic pain and the concomitant mechanism via modulating microglia. Methods: 30 male SD rats were randomized divided into three groups (n = 10 per group): Sham + Saline group (S&S group), CCI + Saline group (C&S group) and CCI + HUC-MSCs group (C&U group). Rats were injected with either saline or HUC-MSCs via the caudal vein on the 7th day after modelling. The paw mechanical withdrawal threshold (PMWT) and thermal withdrawal latency (TWL) of the ligation side were measured before (day 0) and after (day 1, 3, 5, 7, 9, 11, 13, and 15) modelling. On day 15 after modelling, western-blotting and immunofluorescent staining were used to assess the expressive abundance of Iba-1 (a typical biomarker of activated microglia) in the ligation side of the spinal cord dorsal horn, and ultrastructural changes of the ligation of sciatic nerve were evaluated by transmission electron microscope (TEM). Results: Compared with the S&S group, PMWT and TWL in the C&S group were significantly decreased on day 5 and then persisted to day 15 after modelling (C&S vs S&S, P

The diel vertical variations of chlorophyll a (Chl-a) concentration are thought of primarily as an external manifestation of regulating phytoplankton’s biomass, which is essential for dynamically estimating the biogeochemical cycle in inland waters. However, information on these variations is limited due to insufficient measurements. Undersampled observations lead to delayed responses in phytoplankton assessment, impacting accurate evaluations of carbon export and water quality in dynamic inland waters. Here, we report the first lidar-observed diel vertical variations of inland Chl-a concentration. Strong agreement with r2 of 0.83 and a root mean square relative difference (RMSRD) of 9.0% between the lidar-retrieved and in situ measured Chl-a concentration verified the feasibility of the Mie–fluorescence–Raman lidar (MFRL). An experiment conducted at a fixed observatory demonstrated the lidar-observed diel Chl-a concentration variations. The results showed that diel variations of Chl-a and the formation of subsurface phytoplankton layers were driven by light availability and variations in water temperature. Furthermore, the facilitation from solar radiation-regulated water temperature on the phytoplankton growth rate was revealed by the high correlation between water temperature and Chl-a concentration anomalies. Lidar technology is expected to provide new insights into continuous three-dimension observations and be of great importance in dynamic inland water ecosystems.

Objective: Neuroblastoma (NB) is a prevalent pediatric tumor originating from primordial neural crest cells. As one of the latest epigenetics investigations focuses, RNA 5-methylcytosine (m5C) is closely related to cancer risk. TET methylcytosine dioxygenase 3 (TET3) is a demethylase for m5C modification. Whether there is an association between TET3 gene polymorphisms and neuroblastoma risk remains unclear. Methods: We conducted an epidemiological study in 402 patients and 473 controls to evaluate the relationship between TET3 gene SNPs (rs7560668 T > C, rs828867 G > A, and rs6546891 A > G) and NB susceptibility. Results: Our results showed that rs828867 G > A significantly reduced NB risk in Chinese children [GA vs. GG, adjusted odds ratio (OR) = 0.72, 95% confidence interval (CI) = 0.52–0.98, P=0.040; GA/AA vs. GG, adjusted OR = 0.74, 95% CI = 0.55–0.998, P=0.048]. Individuals with 2–3 risk genotypes had a significantly higher NB risk than those with 0–1 risk genotypes (adjusted OR = 1.40, 95% CI = 1.04–1.88, P=0.027). The stratified analysis showed that the rs828867 G > A associated with decreased NB risk is remarkable among children aged >18 months (adjusted OR = 0.67, 95% CI = 0.46–0.96, P=0.029) and patients at clinical III + IV stages (adjusted OR = 0.67, 95% CI = 0.45–0.98, P=0.040). Compared with the 0–1 risk genotype, the concurrence of 2–3 risk genotypes significantly increased NB risk in the following subgroups: children aged >18 months and patients at clinical III + IV stages. GTEx analysis suggested that rs828867 G > A was significantly associated with RP11-287D1.4 and POLE4 mRNA expression. Conclusions: Overall, our results revealed that rs828867 G > A in the TET3 gene is significantly associated with predisposition to NB.

DNA methylation is a key epigenetic mechanism orchestrating gene expression networks in many biological processes. Nonetheless, studying the role of specific gene methylation events in fish faces challenges. In this study, we validate the regulation of DNA methylation on empty spiracles homeobox 2 (emx2) expression with decitabine treatment in Chinese tongue sole testis cells. We used the emx2 gene as the target gene and developed a new DNA methylation editing system by fusing dnmt3a with catalytic dead Cas9 (dCas9) and demonstrated its ability for sequence-specific DNA methylation editing. Results revealed that utilizing dCas9-dnmt3a to target emx2 promoter region led to increased DNA methylation levels and decreased emx2 expression in Chinese tongue sole testis cells. More importantly, the DNA methylation editing significantly suppressed the expression of MYC proto-oncogene, bHLH transcription factor (myc), one target gene of emx2. Furthermore, we assessed the off-target effects of dCas9-dnmt3a and confirmed no significant impact on the predicted off-target gene expression. Taken together, we developed the first DNA methylation editing system in marine species and demonstrated its effective editing ability in Chinese tongue sole cells. This provides a new strategy for both epigenetic research and molecular breeding of marine species.

Plant flowering time is affected by endogenous and exogenous factors, but its variation patterns among different populations of a species has not been fully established. In this study, 27 Arabidopsis thaliana accessions were used to investigate the relationship between autonomous pathway gene methylation, gene expression and flowering time variation. DNA methylation analysis, RT-qPCR and transgenic verification showed that variation in the flowering time among the Arabidopsis populations ranged from 19 to 55 days and was significantly correlated with methylation of the coding regions of six upstream genes in the autonomous pathway, FLOWERING LOCUS VE (FVE), FLOWERING LOCUS Y (FY), FLOWERING LOCUS D (FLD), PEPPER (PEP), HISTONE DEACETYLASE 5 (HAD5) and Pre-mRNA Processing Protein 39-1 (PRP39-1), as well as their relative expression levels. The expression of FVE and FVE(CS) was modified separately through degenerate codon substitution of cytosine and led to earlier flowering of transgenic plants by 8 days and 25 days, respectively. An accurate determination of methylated sites in FVE and FVE(CS) among those transgenic plants and the recipient Col-0 verified the close relationship between the number of methylation sites, expression and flowering time. Our findings suggest that the methylation variation of these six key upstream transcription factors was associated with the gene expression level of the autonomous pathway and flowering time in Arabidopsis. The FVE(CS) and FVE genes in transgenic plants tended to be hypermethylated, which could be a protective mechanism for plants. However, modification of gene sequences through degenerate codon substitution to reduce cytosine can avoid hypermethylated transferred genes in transgenic plants. It may be possible to partially regulate the flowering of plants by modified trans-epigenetic technology.

Diameter at breast height (DBH) is a crucial parameter for forest inventory. However, accurately estimating DBH remains challenging due to the noisy and incomplete cross-sectional points. To address this, this paper proposed a reliable DBH estimation method using terrestrial LiDAR points through polar coordinate transformation and progressive outlier removal. In this paper, the initial center was initially detected by rasterizing the convex hull, and then the Cartesian coordinates were transformed into polar coordinates. In the polar coordinate system, the outliers were classified as low and high outliers according to the distribution of polar radius difference. Both types of outliers were then removed using adaptive thresholds and the moving least squares algorithm. Finally, DBH was estimated by calculating the definite integral of arc length in the polar coordinate system. Twenty publicly available individual trees were adopted for the test. Experimental results indicated that the proposed method performs better than the other four classical DBH estimation methods. Furthermore, several extreme cases scanned using terrestrial LiDAR in practice, such as cross-sectional points with lots of outliers or larger data gaps, were also tested. Experimental results demonstrate that the proposed method accurately calculates DBH even in these challenging cases.

Abstract Giant cell myocarditis (GCM) is a rare and fatal inflammatory disorder induced by T-lymphocytes, typically affecting young adults. Generally, this disease presents with a rapidly progressive course and a very poor prognosis. In recent years, atrial GCM (aGCM) has been recognized as a clinicopathological entity distinct from classical GCM. As described by retrievable case reports, although its histopathological manifestations are highly similar to those of classical GCM, this entity is characterized by preserved left ventricular function and atrial arrhythmias, without ventricular arrhythmias. aGCM tends to show benign disease progression with a better clinical prognosis compared with the rapid course and poor prognosis of vGCM. We report a patient with aGCM with a history of renal abscess whose persistent myocardial injury considered to be associated with a history of renal abscess. Infection could be a potential trigger for the development of aGCM in this patient. An extensive literature review was also performed and the following three aspects were summarized: (1) Epidemiology and histopathological characteristics of aGCM; (2) The role of imaging in the evaluation of aGCM; (3) Diagnostic points and therapeutic decisions in aGCM.

With the rapid rise of new media platforms such as Weibo and Tiktok, communities with science communication characteristics have progressively grown on social networks. These communities pursue essential objectives such as increased visibility and influence. For the success of the public understanding of science in China, case studies of science communication communities on social media are becoming increasingly valuable as a point of reference. The authenticity of user influence plays an important role in the analysis of the final outcome during the process of community detection. By integrating counterfactual reasoning theory into a community detection algorithm, we present a novel paradigm for eliminating influence bias in online communities. We consider the community of Public Science Day of the Chinese Academy of Sciences as a case study to demonstrate the validity of the proposed paradigm. In addition, we examine data on science communication activities, analyze the key elements of activity communication, and provide references for not only augmenting the communication impact of similar types of popular science activities but also advancing science communication in China. Our main finding is that the propagation channel for the science communication experiment exhibits multi-point scattered propagation and lacks a continuous chain in the process of propagation.

The development of proton exchange membrane water electrolyzers (PEMWEs) is primarily challenged by the slow and unstable oxygen evolution reaction (OER) at the anode. Thus, the pursuit of low‐cost, highly efficient, and durable electrocatalysts is the foundation for the widespread adoption of PEMWEs. In the past few decades, various types of electrocatalysts are proposed to serve as anode materials for acidic OER, but only a few demonstrate catalytic activity and stability comparable to iridium‐ and ruthenium‐based electrocatalysts. In recent years, some transition‐metal oxides are studied as potential candidates for acidic OER. For instance, spinel‐type oxides, e.g., Co3O4, and corresponding compounds demonstrate promise due to the rich coordination structure of metallic ions and moderate adoption energy for intermedia. In this review, recent advances in spinel‐type oxides for acidic OER are summarized. First, a fundamental understanding of reaction mechanisms for OER in acidic media is introduced. Thereafter, recent progress in rational design principles and optimization strategies for spinel oxides is systematically summarized. Finally, challenges and perspectives for the development of spinel‐based acidic OER electrocatalysts are discussed.

Abstract Background Neuroblastoma is a common malignant tumor stemming from the sympathetic nervous system in children, which is often life‐threatening. The genetics of neuroblastoma remains unclear. Studies have shown that miRNAs participate in the regulation of a broad spectrum of biological pathways. The abnormity in the miRNA is associated with the risk of various cancers, including neuroblastoma. However, research on the relationship of miRNA polymorphisms with neuroblastoma susceptibility is still in the initial stage. Methods In this research, a retrospective case–control study was conducted to explore whether miR‐100 rs1834306 A > G polymorphism is associated with neuroblastoma susceptibility. We enrolled 402 cases and 473 controls for the study. The logistic regression analysis was adopted to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between miR‐100 rs1834306 A > G and neuroblastoma risk. Results Our results elucidated that the miR‐100 rs1834306 A > G polymorphism was associated with the decreased risk of neuroblastoma (AG versus AA: adjusted OR = 0.72, 95% CI = 0.53–0.98, and P = 0.038). The subsequent stratified analysis further found that rs1834306 AG/GG genotype reduced the risk of neuroblastoma in the subgroup with tumors of the mediastinum origin (adjusted OR = 0.63, 95% CI = 0.41–0.95, and P = 0.029). Conclusions In summary, miR‐100 rs1834306 A > G polymorphism was shown to associate with decreased neuroblastoma risk in Chinese children, especially for neuroblastoma of mediastinum origin. This conclusion needs to be verified in additional large‐size case–control studies.

Objectives: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infectious disease with a high case fatality rate. Key gaps remained as to the assessment of the clinical picture in fatal cases. Methods: A retrospective study was performed on 496 patients with fatal SFTS. The dynamic pattern of clinical manifestations and laboratory indicators were delineated. Results: The mean age of the fatal cases was 69.0 years (standard deviation: 9.3), and 52.8% were male. The median clinical course from disease onset to death was 11 (interquartile range: 10-13) days. A total of 11 laboratory indicators (neutrophil %, platelet, aspartate aminotransferase, aspartate aminotransferase/alanine transaminase, lactate dehydrogenase, creatine kinase, cystatin C, D-dimer, activated partial thromboplastin time, thrombin time, glucose) persistently deviated from normality across hospitalization. The critical time points when the rapid worsening of the indicators was at 6-9 days after disease onset. Alanine transaminase, AST, lactate dehydrogenase, total bile acid, gamma-glutamyl transpeptidase, and glucose were all elevated to a more pronounced level in fatal cases of those aged ≤70 years. Conclusion: The fatal outcome was developed in rather a short course after the disease onset of SFTS. High vigilance should be put on the key time points when the severe worsening and severe complications occur.

This research describes the dynamic behavior of an isolated slug driven by pressurized air in a voided line with an end orifice. A three-dimensional (3D) computational-fluid-dynamics (CFD) model is used to simulate the rapid propulsion and impact at the orifice for given slug length and driving air pressure, and is validated against experimental data. New mechanisms are observed: (i) the driving air pressure at the slug tail decreases with the slug motion; (ii) when the slug arrives at the orifice, the air fraction is almost one hundred percent in the most upstream part of the pipe, then it attenuates rapidly until an invariant eighty percent is achieved with a constant mass shedding rate; (iii) the velocity distribution in the radial direction of the cross-section at the midpoint of the slug length evolves from uniform to trapezoidal and then to logarithmic during slug movement; (iv) the initial vertical slug front changes its shape due to air intrusion at the top of the slug front; (v) the slug’s acceleration decreases first and then increases under the combined effects of its decreasing mass, nonlinear attenuation of the driving pressure, and increasing skin friction; (vi) the slug length has a constant rate of decrease.

Even with intensive treatment of high-risk neuroblastoma (NB) patients, half of high-risk NB patients still relapse. New therapies targeting the biological characteristics of NB have important clinical value for the personalized treatment of NB. However, the current biological markers for NB are mainly analyzed by tissue biopsy. In recent years, circulating biomarkers of NB based on liquid biopsy have attracted more and more attention. This review summarizes the analytes and methods for liquid biopsy of NB. We focus on the application of liquid biopsy in the diagnosis, prognosis assessment, and monitoring of NB. Finally, we discuss the prospects and challenges of liquid biopsy in NB.

Sucrose synthase (SuSy, EC 2.4.1.13) is a unique glycosyltransferase (GT) for developing cost-effective glycosylation processes. Up to now, some SuSys derived from plants and bacteria have been used to recycle uridine 5′-diphosphate glucose in the reactions catalyzed by Leloir GTs. In this study, after sequence mining and experimental verification, a SuSy from Micractinium conductrix (McSuSy), a single-cell green alga, was overexpressed in Escherichia coli, and its enzymatic properties were characterized. In the direction of sucrose cleavage, the specific activity of the recombinant McSuSy is 9.39 U/mg at 37°C and pH 7.0, and the optimum temperature and pH were 60°C and pH 7.0, respectively. Its nucleotide preference for uridine 5′-diphosphate (UDP) was similar to plant SuSys, and the enzyme activity remained relatively high when the DMSO concentration below 25%. The mutation of the predicted N-terminal phosphorylation site (S31D) significantly stimulated the activity of McSuSy. When the mutant S31D of McSuSy was applied by coupling the engineered Stevia glycosyltransferase UGT76G1 in a one-pot two-enzyme reaction at 10% DMSO, 50 g/L rebaudioside E was transformed into 51.06 g/L rebaudioside M in 57 h by means of batch feeding, with a yield of 76.48%. This work may reveal the lower eukaryotes as a promising resource for SuSys of industrial interest.

Background and objectiveUltrasound has been widely used in the diagnosis and minimally invasive treatment of peripheral nerve diseases in the clinic, but there is still a lack of feasibility analysis in rodent models of neurological disease. The purpose of this study was to investigate the changes in the cross-sectional area of the sciatic nerve of different genders and body weights and to explore the effectiveness and reliability of an ultrasound-guided block around the sciatic nerve in living rats.MethodsUsing ultrasound imaging anatomy of the sciatic nerve of rats, the cross-sectional area of the sciatic nerve in rats of different genders from 6 to 10 weeks old was calculated, and then analyzed its correlation with body weight. Further analyses were conducted through behavioral and cadaveric studies to evaluate the feasibility of ultrasound-guided perineural injection of the sciatic nerve in rats.ResultsWe first reported that the sciatic nerve cross-sectional area of rats was increased with age (F = 89.169, P < 0.001), males had a higher sciatic nerve cross-sectional area than females (F = 60.770, P < 0.001), and there was a positive correlation with body weight (rMale = 0.8976, P < 0.001; rFemale = 0.7733, P < 0.001). Behavioral observation of rats showed that the lower extremity complete block rate was 80% following the administration of drugs around the sciatic nerve under ultrasound guidance and staining with methylene blue occurred in all sciatic nerves and surrounding muscles and fascia using 20 ultrasound-guided injections.ConclusionsUltrasound visualization technology can be used as a new auxiliary evaluation and intervention therapy for animal models of peripheral nerve injury, and will provide overwhelming new references for the basic research of neurological diseases.

Abstract In a modular multilevel converter‐based high‐voltage direct current (MMC‐HVDC) system, the dc fault ride through (FRT) control is an effective way to deal with a dc‐side pole‐to‐ground (PTG) fault. However, the setting of FRT duration brings potential hazards: 1) MMC will face the risk of “secondary short circuit” if FRT duration is short; 2) ac grid may have power angle stability issue if FRT duration is long. To avoid these hazards and provide theoretical guidance for the FRT duration setting, transient behaviour of dc fault current during the PTG FRT stage is explored in this work. Firstly, challenges of the transient analysis are summarised as non‐linearity and high‐order issues. In light of this, numerical and Hilbert‐Huang Transformation methods are introduced to evaluate the non‐linearity issue. It is found that the path of MMC from dc current to dc internal voltage is weakly non‐linear. Hence, a linear transient model is built to analyse the dc fault current. By participation factor analysis, the order of the proposed model is further reduced, so that an analytical expression of the dc fault current is approximately derived. Based on the analytical expression, regularities and mechanism of dc fault current are fully revealed. Application of the transient analysis to the setting of FRT duration is elaborated in detail. Finally, the PSCAD/EMTDC simulation verifies the validity of the proposed model and analytical expression.

Antibiotics are a category of chemical compounds used to treat bacterial infections and are widely applied in cultivation, animal husbandry, aquaculture, and pharmacy. Currently, residual antibiotics and their metabolites pose a potential risk of allergic reactions, bacterial resistance, and increased cancer incidence. Residual antibiotics and the resulting bacterial antibiotic resistance have been recognized as a global challenge that has attracted increasing attention. Therefore, monitoring antibiotics is a critical way to limit the ecological risks from antibiotic pollution. Accordingly, it is desirable to devise new analytical platforms to achieve efficient antibiotic detection with excellent sensitivity and specificity. Quantum dots (QDs) are regarded as an ideal material for use in the development of antibiotic detection biosensors. In this review, we characterize different types of QDs, such as silicon, chalcogenide, carbon, and other doped QDs, and summarize the trends in QD-based antibiotic detection. QD-based sensing applications are classified according to their recognition strategies, including molecularly imprinted polymers (MIPs), aptamers, and immunosensors. We discuss the advantages of QD-derived antibiotic sensors, including low cost, good sensitivity, excellent stability, and fast response, and illustrate the current challenges in this field.

Research on collective decision-making is based on new decision-making theories and their methods are driven by group participation, human-computer interaction, and big data, to realize complex problem solving and intelligent decision-making in an open environment.However, the open environment is of high openness, complex interaction, and emerging behaviors, making collective decision-making face the challenges of difficult incentive mechanism design, uncontrollable decision-making individuals, diverse decision-making environments, and highly complex decosion-making information.Based on the era background of collective decision-making in an open environment, a new decision-making paradigm was proposed, its conceptual connotation, main challenges, and leading technologies for effective implementation of collective decision-making were sorted out.The successful cases of collective decision-making were analyzed, in order to support the application of new decision-making paradigms in the fields of economy, medical care, and people’s livelihood, and to promote progress and changes in the corresponding fields.

For small and medium-sized enterprises and large enterprises alike, crowdsourcing innovation has become an important element of a product’s whole life cycle. It is the open call process of soliciting consumers to harvest and evaluate ideas or other intellectual assets. The previous proposed taxonomic framework for charactering this process is mainly for general crowdsourcing process and summarized by empirical study. The purpose of this paper is to propose a conceptual model for crowdsourcing innovation from a cybernetic and knowledge management perspective by normative research. The authors performed a normative study and deduced five systemic characteristics from the general laws of control system that guarantee ongoing efficiency for the innovation process. The normative research results provide two key contributions. Firstly, general control laws deduce five indispensable characteristics, and they reveal the intrinsic mechanism of crowdsourcing innovation: the knowledge flow controls, which are also the connotation of open innovation. Secondly, the authors have analyzed a five-characteristics system model and tested the model in several classical cases to show the design tricks of cases. This study provides a new conceptual framework that integrates the theory of open innovation and cybernetics to provide a new view of crowdsourcing innovation process design. In practice, this framework guides managers through the design criteria needed to implement a success crowdsourcing process.

Winds potentially affect primary production in shelf seas during the stratified season by enhancing upwelling and mixing. However, the exact extent and modalities of this effect in the Yellow Sea remain unclear. Here, based on the satellite and in situ observation data, statistical method, and wind-driven upwelling theory, we examined the wind effect on the chlorophyll-a (Chl-a) variability in the summer of 2002-2020 and the effect mechanism. The satellite data revealed a significantly positive correlation between anomalies of the monthly mean of the summer sea surface Chl-a and wind speed at the continental slope region (water depth of 20-60 m) in the southwestern Yellow Sea where strong wind-driven upwelling has been indicated by previous studies. The wind-driven upwelling along the continental slope was further verified using two summer in-situ observations. After a fortnight of southeasterly wind, the upwelling patterns of high salinity and rich nutrients from the Yellow Sea cold water mass were observed, and consequently, high Chl-a concentrations occurred in the upper layer of the slope region. The wind-driven upwelling occurred in the region at water depth of ~20-60 m, which is consistent with the result of the wind-driven coastal upwelling theory (0.5D < water depth < 1.25D, where D is the thickness of the Ekman layer). The dissolved inorganic nitrogen, phosphorus, and silicate fluxes contributed by wind-driven upwelling were estimated as 1345 ± 674 μmol/m2/d, 81 ± 45 μmol/m2/d and 1460 ± 899 μmol/m2/d, respectively, accounting for 30%-40% of total nutrient supply, and were several times larger than that contributed by the turbulent mixing, which can explain why the strong wind-Chl-a correlation only occurred at the upwelling region rather than the entire sea. In addition, in this region, the interannual variability of the summer mean Chl-a was negatively correlated to both the Pacific Decadal Oscillation (PDO) and El Niño-Southern Oscillation (ENSO) indexes, due to the opposite phase of the summer wind anomaly and the PDO/ENSO. This study revealed the wind effect on the shelf phytoplankton is regional and highlighted that wind could be a pivotal factor driving the climate variability of shelf primary production in the stratified season.

Abstract This letter is concerned with the physical layer security of the cooperative vehicular relay network where a source vehicle communicates with a destination vehicle via both a direct link in the presence of a location‐uncertain eavesdropping vehicle and an indirect link with the help of an amplify‐and‐forward relay vehicle. Based on the double‐Rayleigh fading model for all links, an approximate analytical expression of the average secrecy capacity of the considered system is derived. This analysis on the average secrecy capacity is shown to be validated by Monte‐Carlo simulations and numerical computations. The simulation and numerical results also demonstrate the effects of the uncertainty of the eavesdropper's location and the relay's location on the average secrecy capacity.

The green peach aphid, Myzus persicae (Sulzer) (Hemiptera: Aphididae), is an economically devastating crop pest worldwide. The M. persicae (SEF-R) population of a cabbage field in China was tested for susceptibilities to 13 insecticides. Compared with the susceptible population (FFJ-S), extremely high and high resistance to beta-cypermethrin (324-fold) and imidacloprid (106.9-fold) was detected in SEF-R. More importantly, this is the first report of resistance in the field M. persicae population to sulfoxaflor (32.4-fold), flupyradifurone (9.5-fold), pymetrozine (34.8-fold), spirotetramat (8.1-fold), flonicamid (5.8-fold), and broflanilide (15.8-fold) in China when compared with FFJ-S. The resistance factor decayed to a low level to sulfoxaflor and pymetrozine after 15 generations without any selection pressure. The resistance-related mutations (R81T and kdr) detected in SEF indicated target-site resistance to neonicotinoids and pyrethroids, respectively. Biochemical assays revealed the involvement of monooxygenase, carboxylesterase, superoxide dismutase, and peroxidase in a multi-insecticide resistance mechanism. The overexpression of P450s, esterases, and a UDP-glycosyltransferase might be responsible for the multi-insecticide resistance in SEF-R. The knockdown of CYP6CY3 in SEF-R increased its susceptibility to imidacloprid, thiacloprid, and thiamethoxam, which verified that P450s play vital roles in neonicotinoid metabolism. Our findings provide guidance for the rational use of insecticides to delay resistance development in GPA.

Background Type XI collagen (COL11A1) was reported to associate with malignancy in several cancer types, whereas its role in lung cancer is not fully understood. Therefore, the present study aimed to explore the expression level and biological role of COL11A1 in lung cancer cells. Methods Gene Expression Omnibus (GEO) database containing 6 lung cancer tissues and normal lung tissues was used to identify potential aberrantly expressed genes. The expression of COL11A1, apoptosis related genes, cell cycle related genes and migration associated genes at the protein level were evaluated by western blot and at the mRNA level was determined by real-time PCR in lung cancer cell lines. Furthermore, the expression of COL11A1 was silenced by siRNA, and cell viability was detected by Cell counting kit-8 (CCK-8) assay. Moreover, cell apoptosis and cell cycle were determined by flow cytometry. In addition, transwell and wound-healing assay were applied to determine cell migration ability. Results GEO analysis suggests that COL11A1 was highly expressed in patients with lung cancer, which was consistent with the results in lung cancer cell lines. COL11A1 knockdown in lung cancer cells significantly lowered the colony formation ability, augmented cell apoptosis rate and elevated the expression of cleaved caspase-3, cleaved caspase-9, Bax, P21 and the expression of Bcl-2, CyclinD1, CDK2 and CDK-4 was significantly downregulated (all p

Abstract COVID-19 has affected every sector of our society, among which human mobility is taking a dramatic change due to quarantine and social distancing. We investigate the impact of the pandemic and subsequent mobility changes on road traffic safety. Using traffic accident data from the city of Los Angeles and New York City, we find that the impact is not merely a blunt reduction in traffic and accidents; rather, (1) the proportion of accidents unexpectedly increases for “Hispanic” and “Male” groups; (2) the “hot spots” of accidents have shifted in both time and space and are likely moved from higher-income areas (e.g., Hollywood and Lower Manhattan) to lower-income areas (e.g., southern LA and southern Brooklyn); (3) the severity level of accidents decreases with the number of accidents regardless of transportation modes. Understanding those variations of traffic accidents not only sheds a light on the heterogeneous impact of COVID-19 across demographic and geographic factors, but also helps policymakers and planners design more effective safety policies and interventions during critical conditions such as the pandemic.

Abstract It is well known that noncoding RNAs (ncRNAs) cannot encode proteins, but they can play important regulatory roles in tumors by combining with proteins, RNAs, and DNAs. As more and more studies reveal the important roles and underlying mechanisms of long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) in cancer, their huge application potential in cancer therapy cannot be ignored. For example, lncRNAs can be involved in tumor‐related signal transduction pathways, cell cycle control, DNA damage, epigenetic regulation, and microRNA control. A group of studies confirmed that abnormal expression of lncRNAs can affect cancer progression. Furthermore, as covalently closed continuous circular ncRNAs, many recent studies have shown that circRNAs have regulatory effects and other important biological significances in cancer. Interestingly, circRNAs were found to have translational functions. This has greatly attracted people's attention to circRNAs research. In this review, we introduce the important roles of lncRNAs and circRNAs in some representative cancers, respectively. Furthermore, we focus on the biological functions and important clinical therapeutic implications of lnRNAs and circRNAs in neuroblastoma. Our review also focuses on providing rationale and relevant references for novel biomarkers for neuroblastoma diagnosis, prognosis, and treatment.

Monitoring marine primary productivity (PP) is crucial for understanding changes in the marine ecosystem. Based on satellite data and the vertically generalized production model (VGPM), this study investigated the spatiotemporal distribution and long-term trend of PP in the Yellow and Bohai Seas (YBSs) from 2003 to 2020. By using the calibrated satellite data and optimized parameterization scheme, the accuracy of the PP results in the YBSs was significantly improved compared to online PP products. The annual mean PP in the YBSs from 2003 to 2020 was 523.8 mgC/(m2·d), with significant seasonal and interannual differences. Seasonally, PP in the Yellow Sea and the Bohai Sea exhibited bimodal (two peaks in May and October) and unimodal (one peak in June) variation, respectively. The magnitude of mean PP in the YBSs was ranked as spring > summer > autumn > winter, with spring PP (~1000 mgC/(m2·d)) contributing more than 40% of the annual PP. The annual mean PP in the YBSs showed an overall decrease from 2003 to 2020, with a decrease rate of 5–6 mgC/(m2·d)/y. The interannual variation of the PP was mainly related to the variability of the chlorophyll-a concentration and was essentially inverse to the phases of the Pacific Decadal Oscillation and the El Niño-Southern Oscillation.

We propose a modular multilevel converter (MMC) based three-phase four-wire (3P4W) split capacitor distribution static synchronous compensator (DSTATCOM), aiming at compensating unbalanced and reactive load currents. Due to the zero-sequence current compensation, the circulating current characteristics of 3P4W MMC-DSTATCOM are different from conventional MMCs. Moreover, the distinct working principle of MMC would affect the features of split capacitor voltage. The decoupled positive-, negative- and zero-sequence second-order and DC components of the circulating current are deduced explicitly. Two proportional-integral controllers with dual dq transformation are employed to suppress the positive- and negative-sequence components of second-order circulating current, while quasi proportional-resonance controller is designed to eliminate the zero-sequence component. Besides, the phenomenon of the unbalanced split capacitor voltages is revealed, and fast-tracking balancing method by controlling zero-sequence current flowing through the split capacitors is provided. Digital simulation results verify the accuracy of the analysis and the feasibility of the suppression methods.

Satellite image time series (SITS) classification is a major research topic in remote sensing and is relevant for a wide range of applications. Deep learning approaches have been commonly employed for the SITS classification and have provided state-of-the-art performance. However, deep learning methods suffer from overfitting when labeled data are scarce. To address this problem, we propose a novel self-supervised pretraining scheme to initialize a transformer-based network by utilizing large-scale unlabeled data. In detail, the model is asked to predict randomly contaminated observations given an entire time series of a pixel. The main idea of our proposal is to leverage the inherent temporal structure of satellite time series to learn general-purpose spectral-temporal representations related to land cover semantics. Once pretraining is completed, the pretrained network can be further adapted to various SITS classification tasks by fine-tuning all the model parameters on small-scale task-related labeled data. In this way, the general knowledge and representations about SITS can be transferred to a label-scarce task, thereby improving the generalization performance of the model as well as reducing the risk of overfitting. Comprehensive experiments have been carried out on three benchmark datasets over large study areas. Experimental results demonstrate the effectiveness of the proposed pretraining scheme, leading to substantial improvements in classification accuracy using transformer, 1-D convolutional neural network, and bidirectional long short-term memory network. The code and the pretrained model will be available at https://github.com/linlei1214/SITS-BERT upon publication.

Abstract Background and Aim Health‐related quality‐of‐life measurements are important to understand lived experiences of patients who have cirrhosis. These measures also inform economic evaluations by modelling quality‐adjusted life years (QALYs). We aimed to describe health‐related quality of life, specifically multiattribute utility (scale anchors of death = 0.00 and full health = 1.00), across various stages and etiologies of cirrhosis. Methods Face‐to‐face interviews were used to collect Short Form 36 (SF‐36) questionnaire responses from CirCare study participants with cirrhosis (June 2017 to December 2018). The severity of cirrhosis was assessed using the Child‐Pugh score classified as class A (5–6 points), B (7–9), or C (10–15) and by the absence (“compensated”) versus presence (“decompensated”) of cirrhosis‐related complications. Results Patients (n = 562, average 59.8 years [SD = 11.0], male 69.9%) had a range of primary etiologies (alcohol‐related 35.2%, chronic hepatitis C 25.4%, non‐alcoholic fatty liver disease (NAFLD) 25.1%, chronic hepatitis B 5.9%, “other” 8.4%). Significantly lower (all P

Abstract Anthropogenic aerosol (AA) forcing has been shown as a critical driver of climate change over Asia since the mid-20th century. Here we show that almost all Coupled Model Intercomparison Project Phase 6 (CMIP6) models fail to capture the observed dipole pattern of aerosol optical depth (AOD) trends over Asia during 2006–2014, last decade of CMIP6 historical simulation, due to an opposite trend over eastern China compared with observations. The incorrect AOD trend over China is attributed to problematic AA emissions adopted by CMIP6. There are obvious differences in simulated regional aerosol radiative forcing and temperature responses over Asia when using two different emissions inventories (one adopted by CMIP6; the other from Peking university, a more trustworthy inventory) to driving a global aerosol-climate model separately. We further show that some widely adopted CMIP6 pathways (after 2015) also significantly underestimate the more recent decline in AA emissions over China. These flaws may bring about errors to the CMIP6-based regional climate attribution over Asia for the last two decades and projection for the next few decades, previously anticipated to inform a wide range of impact analysis.

Rebaudioside M (RebM) is a desired natural non-caloric and high potency sweetener with very low content in the leaves of Stevia rebaudiana. In this study, based on the crystal structure of UDP-dependent glycosyltransferase UGT76G1, a key enzyme responsible for RebM production in S. rebaudiana, a computational strategy combining protein structure, molecular docking, and single-point saturation mutation was adopted to engineer UGT76G1 to promote the transformation of rebaudioside E (RebE) into RebM via a two-step continuous glycosylation. An S195Q mutant was verified to have better performance, with a catalytic efficiency 1.2-fold higher towards RebE and 2-fold higher towards rebaudioside D (RebD) than wild-type UGT76G1. RebM (12.8 ± 0.6 g/L) and RebD (10.5 ± 0.1 g/L) were generated from RebE (20 g/L) catalyzed by the S195Q mutant coupling with a sucrose synthase from Micractinium conductrix at 40 °C for 32 h. This work would expand the application of structure-based enzyme design for glycosyltransferase engineering.

ObjectiveTo evaluate the dosimetric characteristics and the clinical application of radioactive iodine-125 brachytherapy stent (RIBS) in malignant esophageal obstruction.MethodsThe dose distribution of RIBS with different seed spacing, diameter and length was studied by treatment planning system (TPS) calculation, thermoluminescence dosimeter (TLD) measurement and Monte Carlo (MC) data fitting. And the data of esophageal cancer patients who were treat with this type of RIBS was analyzed retrospectively.ResultsDoses around the RIBS calculated by the TPS lay between those measured by the TLDs and those simulated by the MC, and the differences between the three methods were significant (p

The submodule (SM) capacitor voltage ripple and the root mean square (RMS) of the arm current are related to the costs and losses of the modular multilevel converter (MMC). The optimization issues have received great attention. The second-order circulating current control and third-order harmonic voltage injection are two conventional optimization methods, but the existing research neglects their coupling effects. In this paper, these two methods are comprehensively investigated and coordinately combined. First, the various performances of MMC under multiple injections are characterized. Then, a multi-objective optimization model considering the output capability of arm voltage and the energy balance of capacitors, is proposed to reduce the SM capacitor voltage ripple and the RMS of the arm current. The amplitudes and phases of the injected second- and third-order harmonic voltages are designed coordinately by genetic algorithm. The simulation and experimental results have validated the effectiveness and feasibility of the proposed method.

Pole-to-ground (PTG) fault analysis is of vital importance for high-voltage direct current (HVDC) grid. However, many factors are not considered in the existing studies such as the asymmetrical property of PTG fault, the coupling issue between DC transmission lines and the complexity of the structure of DC grid. This paper presents a PTG fault analysis method, which is based on common- and differential-mode (CDM) transformation. Similar to the symmetrical component method in AC system, the transformation decomposes the HVDC grid into CDM networks, which is balanced and decoupled. Then, a transfer impedance is defined and calculated based on the impedance matrices of the CDM networks. With the transfer impedance, analytical expressions of fault characteristics that vary with space and time are obtained. The proposed PTG fault analysis method is applicable to arbitrary HVDC grid topologies, and provides a new perspective to understand the fault mechanism. Moreover, the analytical expressions offer theoretical guidance for PTG fault protection. The validity of the proposed PTG fault analysis method is verified in comparison with the simulation results in PSCAD/EMTDC.

Accurate prediction of future observations based on past data is the key to near real-time disturbance detection using satellite image time series (SITS). To overcome the limitations of existing methods, we present an attention-based long-short-term memory (LSTM) encoder-decoder model in which the historical time series of a pixel is encoded with a bidirectional LSTM encoder while the future time series is produced by another LSTM decoder. An attention mechanism is integrated into the encoder-decoder model to align the input time series with the output time series and to dynamically choose the most relevant contextual information while forecasting. Based on the proposed model, we develop a framework for near real-time disturbance detection and verify its effectiveness in the case of burned area mapping. The prediction accuracy of the proposed model is evaluated using moderate resolution imaging spectroradiometer (MODIS) time series and compared with state-of-the-art models. Experimental results show that our model achieves the best results in terms of lower prediction error and higher model fitness. We also evaluate the disturbance detection ability of the proposed framework. The proposed approach improves the detection rate of disturbances while suppressing false alarms, and increases the temporal accuracy. We suggest that the proposed methods provide new tools for enhancing current early warning systems in real time.

Ommastrephes bartramii can vertically swim during its life, and previous studies have suggested the need to account for preferred habitat distribution influenced by water temperatures at different depths. To explore the impacts of deep-water temperature on O. bartramii spatial distribution, we constructed generalized additive models (GAMs) based on the Chinese squid-jigging fishery data and the Argo deep water temperature data during 2005–2018 in the Northwest Pacific Ocean to analyze the relationships between the local abundance of O. bartramii and deep-water temperatures. The results showed that the variables including surface water temperature (T0), water temperature at 30- and 100-m depths (T30 and T100), and water differences between T0 and T30 (D0–30) significantly affected the spatial distribution of O. bartramii. The suitable ranges of each variable are different, > 15.5°C for T0, 11–18°C for T30, < 6°C for T100, and 4–4.5°C for D0–30. The areas occupied by the suitable T30 seemed to reflect the outline of fishing ground, whereas the areas with suitable T100 were to indicate the high density of O. bartramii. The predicted suitable habitat area and high-density area for O. bartramii are also regulated by El Niño–Southern Oscillation (ENSO) events. We demonstrated how the estimates of O. bartramii spatial distribution would vary influenced by deep-water temperatures in the Northwest Pacific Ocean. This information may help develop an appropriate method for investigating the effects of deep-water temperature on species with vertical migration.

Abstract The response of precipitation extremes (PEs) to global warming is found to be nonlinear in Community Earth System Model version 1 (CESM1) and other global climate models (Pendergrass et al., 2019), which led to the concern that it is not accurate to approximate the response of PE to a single forcing as the difference between simulations with all forcing agents and those that exclude one specific forcing. This calls into question previous model‐based results that the sensitivity of PE with warming due to aerosol forcing is significantly larger than that due to greenhouse gases (GHGs). We reevaluate the PE sensitivity to GHGs and aerosols using available CESM1 ensemble simulations. We show that although the PE response to warming is nonlinear in CESM1, especially for the high warming projected in the twenty‐first‐century, PE sensitivity to aerosols is still significantly stronger than that due to GHGs when the comparison is made within similar warming regimes to avoid the bias induced by the nonlinear behavior. But the difference is smaller than previously estimated. We also conclude that the additivity assumption is largely valid to isolate the PE response due to aerosol forcing from the paired simulations including the “all forcing” experiment when the warming regime is small (e.g., 1°C–2°C in the next few decades when aerosol forcing is projected to decline and becomes a major source of uncertainty for model projection).

Phytochelatins are plants’ small metal-binding peptides which chelate internal heavy metals to form nontoxic complexes. Detecting the complexes in plants would simplify identification of cultivars with both high tolerance and enrichment capabilities for heavy metals which represent phytoextraction performance. Thus, a terahertz spectroscopy combined with density functional theory, chemometrics and circular dichroism was used for characterization of phytochelatin2 (PC2), Cd-PC2 mixture standards, and pak choi (Brassica chinensis) leaves as a plant model. Results showed PC2 chelates Cd2+ in a 2:1 ratio to form Cd(PC2)2 complex; Cd connected to thoils of PC2 and changed β-turn and random coil of PC2 peptide chain to β-Sheet which presented as terahertz vibrations of PC2 around 1.03 and 1.71 THz being suppressed; the best models for detecting the complex in pak choi were obtained by partial least squares regression modeling combined with successive projections algorithm selection; the models used PC2 as a natural probe for visualizing and quantifying chelated Cd in pak choi leaf and achieved a limit of detection up to 1.151 ppm. This study suggested that terahertz information of the heavy metal-PCs complexes is qualified for representing a simpler alternative to classical index for evaluating phytoextraction performance of plant; it provided a general protocol for structure analysis and detection of heavy metal-PCs complexes in plant by terahertz absorbance.

Water electrolysis offers a zero-carbon route to generate renewable energy conversion systems. Herein, a self-supported nickel phosphosulfide nanosheet (NS) electrocatalyst was fabricated at a low temperature on carbon cloth, which was then subjected to Ar etching to enhance its catalytic activity. Etching resulted in better hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) performance than other samples, with overpotentials of 103.1 mV (at 10 mA cm−2) and 278.9 mV (at 50 mA cm−2), respectively. The characterization results confirmed that Ar etching created a thin amorphous layer around the NiPS3 NSs, which increased the number of active sites and modulated their electronic structures. These 3D-structured NiPS3 NSs and their subsequent Ar etching process show promise for applications in overall water splitting in alkaline media.

Hantavirus nucleocapsid protein (NP) inhibits protein kinase R (PKR) dimerization by an unknown mechanism to counteract its antiviral responses during virus infection. Here we demonstrate that NP exploits an endogenous PKR inhibitor P58IPK to inhibit PKR. The activity of P58IPK is normally restricted in cells by the formation of an inactive complex with its negative regulator Hsp40. On the other hand, PKR remains associated with the 40S ribosomal subunit, a unique strategic location that facilitates its free access to the downstream target eIF2α. Although both NP and Hsp40 bind to P58IPK, the binding affinity of NP is much stronger compared to Hsp40. P58IPK harbors an NP binding site, spanning to N-terminal TPR subdomains I and II. The Hsp40 binding site on P58IPK was mapped to the TPR subdomain II. The high affinity binding of NP to P58IPK and the overlap between NP and Hsp40 binding sites releases the P58IPK from its negative regulator by competitive inhibition. The NP-P58IPK complex is selectively recruited to the 40S ribosomal subunit by direct interaction between NP and the ribosomal protein S19 (RPS19), a structural component of the 40S ribosomal subunit. NP has distinct binding sites for P58IPK and RPS19, enabling it to serve as bridge between P58IPK and the 40S ribosomal subunit. NP mutants deficient in binding to either P58IPK or RPS19 fail to inhibit PKR, demonstrating that selective engagement of P58IPK to the 40S ribosomal subunit is required for PKR inhibition. Cells deficient in P58IPK mount a rapid PKR antiviral response and establish an antiviral state, observed by global translational shutdown and rapid decline in viral load. These studies reveal a novel viral strategy in which NP releases P58IPK from its negative regulator and selectively engages it on the 40S ribosomal subunit to promptly combat the PKR antiviral responses.

Background and AimCoronary artery disease (CAD) poses a worldwide health threat. Compelling evidence shows that pericardial adipose tissue (PAT), a brown-like adipose adjacent to the external surface of the pericardium, is associated with CAD. However, the specific molecular mechanisms of PAT in CAD are elusive. This study aims to characterize human PAT and explore its association with CAD.MethodsWe acquired samples of PAT from 31 elective cardiac surgery patients (17 CAD patients and 14 controls). The transcriptome characteristics were assessed in 5 CAD patients and 4 controls via RNA-sequencing. Cluster profile R package, String database, Cytoscape were applied to analyze the potential pathways and PPI-network key to DEGS, whereas the hubgenes were predicted via Metascape, Cytohubba, and MCODE. We use Cibersort, ENCORI, and DGIDB to predict immunoinfiltration, mRNA-miRNA target gene network, and search potential drugs targeting key DEGs. The predictable hubgenes and infiltrating inflammatory cells were validated in 22 patients (12 CAD samples and 10 control samples) through RT-qPCR and immunohistochemistry.ResultsA total of 147 different genes (104 up-regulated genes and 43 down-regulated genes) were identified in CAD patients. These different genes were associated with immunity and inflammatory dysfunction. Cibersort analysis showed monocytes and macrophages were the most common subsets in immune cells, whereas immunohistochemical results revealed there were more macrophages and higher proportion of M1 subtype cells in PAT of CAD patients. The PPI network and module analysis uncovered several crucial genes, defined as candidate genes, including Jun, ATF3, CXCR4, FOSB, CCl4, which were validated through RT-qPCR. The miRNA-mRNA network implicated hsa-miR-185-5p as diagnostic targets and drug-gene network showed colchicine, fenofibrate as potential therapeutic drugs, respectively.ConclusionThis study demonstrates that PAT is mainly associated with the occurrence of CAD following the dysfunction of immune and inflammatory processes. The identified hubgenes, predicted drugs and miRNAs are promising biomarkers and therapeutic targets for CAD.

Monitoring the spatiotemporal variability of nutrient concentrations in shelf seas is important for understanding marine primary productivity and ecological problems. However, long time-series and high spatial-resolution nutrient concentration data are difficult to obtain using only on ship-based measurements. In this study, we developed a machine-learning approach to reconstruct monthly sea-surface dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP), and dissolved silicate (DSi) concentrations in the Yellow and Bohai seas from 2003–2019. A large amount of in situ measured data were first used to train the machine-learning model and derive a reliable model with input of environmental data (including sea-surface temperature, salinity, chlorophyll-a, and Kd490) and output of DIN, DIP, and DSi concentrations. Then, longitudinal (2003–2019) monthly satellite remote-sensing environmental data were input into the model to reconstruct the surface nutrient concentrations. The results showed that the nutrient concentrations in nearshore (water depth < 40 m) and offshore (water depth > 40 m) waters had opposite seasonal variabilities; the highest (lowest) in summer in nearshore (offshore) waters and the lowest (highest) in winter in nearshore (offshore) waters. However, the DIN:DIP and DIN:DSi in most regions were consistently higher in spring and summer than in autumn and winter, and generally exceeded the Redfield ratio. From 2003–2019, DIN showed an increasing trend in nearshore waters (average 0.14 μmol/L/y), while DSi showed a slight increasing trend in the Changjiang River Estuary (0.06 μmol/L/y) but a decreasing trend in the Yellow River Estuary (–0.03 μmol/L/y), and DIP exhibited no significant trend. Furthermore, surface nutrient concentrations were sensitive to changes in sea-surface temperature and salinity, with distinct responses between nearshore and offshore waters. We believe that our novel machine learning method can be applied to other shelf seas based on sufficient observational data to reconstruct a long time-series and high spatial resolution sea-surface nutrient concentrations.

Fentanyl is a potent opioid analgesic with high bioavailability. It is the leading cause of drug addiction and overdose death. To better control the abuse of fentanyl and its derivatives, it is crucial to develop rapid and sensitive detection methods. However, fentanyl-related substrates undergo similar molecular structures resulting in similar properties, which are difficult to be identified by conventional spectroscopic methods. In this work, a method for the automatic identification of 8 fentanyl-related substances with similar spectral characteristics was developed using terahertz (THz) spectroscopy coupled with density functional theory (DFT) and spectral similarity mapping (SSM). To characterize the THz fingerprints of these fentanyl-related samples more accurately, the method of baseline estimation and denoising with sparsity was performed before revealing the unique molecular dynamics of each substance by DFT. The SSM method was proposed to identify these fentanyl analogs based on weighted spectral cosine–cross similarity and fingerprint discrete Fréchet distance, generating a matching list by stepwise searching the entire spectral database. The top matched list returned the identification results of the target fentanyl analogs with accuracies of 94.48~99.33%. Results from this work provide algorithms’ increased reliability, which serves as an artificial intelligence-based tool for high-precision fentanyl analysis in real-world samples.

An input vector composed of various features plays an important role in short-term traffic forecasting. However, there is limited research on the optimal feature selection of an input vector for a certain forecasting task. To fill the gap, this paper proposes a cohesion-based heuristic feature selection method by analyzing the nature of the forecasting methods. This method is able to determine which features should be contained in an input vector to make a forecasting algorithm perform better. The proposed method is demonstrated in two experiments based on the empirical traffic flow data. The results show that the method is able to improve the performances of the short-term traffic forecasting algorithms. It is then suggested to consider the proposed method as a preprocessing procedure in practical forecasting applications.

Zengye decoction (ZYD), a traditional Chinese medicinal formula, has been used in the treatment of various chronic diseases, such as constipation and skin dryness syndrome. Clinically, the specific mechanisms and targets of ZYD for treating disease remain unclear. The present study was undertaken to investigate the effects of ZYD on the gut microbiota and host metabolites in aged constipated rats and the relationship between the intestinal microbiota and the host. Rats were divided randomly into three groups, the control group (n = 10), recovery group (n = 10) and ZYD group (n = 10). First, the aged constipation model was established for the ZYD group and recovery group. Then, rats in the ZYD group were treated with ZYD. Urinary and faecal samples of each animal were collected in microcentrifuge tubes. Next, 16s rRNA gene sequencing was employed to analyse the composition of the gut microbiome in faecal samples and afterwards the metabolic function of the altered gut microbiota was predicted. Additionally, 1H NMR profiling was used to detect the alterations of host metabolites in urine and faecal samples to verify the metabolic function results obtained from sequencing. As a result, ZYD reduced the level of harmful bacteria, such as Desulfovibrio, Ruminococcus, Prevotella and Dorea, and increased the abundance of Oxalobacter, Clostridium and Roseburia. The functional prediction of changes in the gut microbiota induced by ZYD revealed that ZYD promoted energy storage, regulated amino acid metabolism, inhibited methane metabolism, strengthened the physiological function of glutathione and reduced bacterial toxin. The 1H NMR profiles revealed that ZYD regulated the carbohydrates, short chain fatty acids, amino acids and amines in the aged constipated rats. In addition, most metabolic changes observed were related to the function of intestinal microbiota. These results suggest that ZYD can regulate the intestinal microbiota of constipated rats to normal levels and change the endogenous metabolites of the host through the intestinal microbiota to achieve therapeutic effects.

The main analyzed aspect of lithium-ion battery (LIB) degradation so far has been capacity fading. On the other hand, interest in efficiency degradation has also increased in recent years. Battery aggregation, which is expected to absorb the surplus of variable renewable energies such as photovoltaic energy, is affected by efficiency degradation in terms of the decreases in the economic gain and renewable energy use. Reusable LIBs could be used as aggregation components in the future; naturally, the variety of charge–discharge efficiencies might be more complex. To improve the operation efficiency of aggregation, including that obtained using reusable LIBs, we propose the Kalman-filter-based quasi-unsupervised learning of the characteristic profiles of LIBs. This method shows good accuracy in the estimation of charge–discharge energy. It should be emphasized that there are no reports of charge–discharge energy estimation using the Kalman filter. In addition, this study shows that the incorrect open-circuit voltage function for the state of charge, which is assumed in the case of a reused battery, could be applied as the reference for the Kalman filter for LIB state estimation. In summary, it is expected that this diagnosis method could contribute to the economic and renewable energy usage improvement of battery aggregation.