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A decision-making method with double reference points was built to address the multiattribute group decision-making (MAGDM) problem to better reflect the influences of bottom-line and target on group decision-making behaviors. First, the relationship between double reference points and attitude characteristics of decision-makers was analyzed, and the rules of use of linguistic variables were disclosed. Second, the loss and utility functions were given according to relations between the reference points and gain/loss values. Third, the weights of attributes were determined with references to the variation coefficient method. Later, alternatives were classified according to risk probability, and ranking and selection of alternatives were carried out through utility information aggregation. Finally, the new method was applied to solve the technological innovation environmental assessment problem. Research results demonstrate that the new method can classify alternatives according to feasibility. The rank of feasible alternatives of the new method is consistent with that of the traditional method. Research conclusions further enrich the research scope of multiattribute decision-making problems and provide some references to study MAGDM problems.

Liver metastasis commonly occurs; however, the luminal-type liver metastasis rarely develops at the early stage of breast cancer, posing key challenges in screening patients, giving early targeted treatment, and providing an opportunity to prolong survival. A 44-year-old female was diagnosed with breast cancer (pT2N0M0, IIa) and luminal B type postoperatively. The latest guidelines indicated four cycles of albumin-paclitaxel and cyclophosphamide chemotherapy. After 4 months of treatment, the patient was found to have hypoechoic nodules in the liver due to other diseases and was thereby diagnosed with breast cancer with liver metastasis. The latest guidelines did not recommend routine imaging and hematological examination of asymptomatic early breast cancer during follow-up. We suggest that follow-up should be strengthened for high-risk patients to maximize their benefits from early diagnosis and treatment.

With the sustained popularity of renewable energy generation, high penetration of variable energies, e.g., wind and solar, is reshaping the form of power systems and weakening the strength of the grid. The stability mechanism of the grid-connected converter in a weak power network, however, has yet to be evaluated. This paper establishes impedance and transient models for Grid-Following (GFL) as well as Grid-Forming (GFM) converters through the impedance analysis method and equal area criterion analysis method. The stability of these two control methods is then comprehensively studied under small and large interference with different grid conditions. The analytical results show that the GFM control is more stable against small disturbances in a weak network. In contrast, it is prone to a significant disturbance stability problem in the strong grid due to the large grid impedance. The GFL control is more suitable for a vigorous power grid, whereas introducing oscillation in a weak power grid due to its negative damping. Simulation experiments have verified the accuracy of the analytical results.

In this study, we propose a hypothesis that an automatic calibration framework can address modeling uncertainties in the Storm Water Management Model (SWMM) due to structural defects that result in the inability of the model to account for runoff generated on building walls from wind-driven rain. To test this hypothesis, we introduce a rainfall error model into the calibration framework to indirectly consider the effects of inclined wind-driven rain on building walls. We couple the optimization algorithm Differential Evolution Adaptive Metropolis (DREAM) with SWMM using newly developed API functions. To demonstrate the effectiveness of the framework, we conduct a case study in Guangzhou, China and assess the impacts of rainfall uncertainty on model parameter estimations and simulated runoff boundaries. The results show that the framework can improve the average Nash–Sutcliffe index of selected events by more than 5%. It also captures peak flow more accurately. This framework contributes to the theory of SWMM calibration by accounting for structural defects and considering rainfall uncertainty.

Abstract Radiation is a curative treatment for localized prostate cancer (PCa). Unfortunately, radiotherapeutic efficacy is often diminished when patients develop more aggressive or metastatic phenotypes. Recent studies have demonstrated that extracellular vesicles participate in cancer therapeutic resistance by delivering small bioactive molecules, such as small non‐coding RNAs. Here, we show that stromal cell‐derived small extracellular vesicles (sEVs) facilitate the radioresistance of PCa cells by transporting interleukin‐8 (IL‐8). Indeed, prostatic stromal cells secrete more IL‐8 than AR‐positive PCa cells, which can be accumulated in sEVs. Intriguingly, the uptake of stromal cells‐derived sEVs by radiosensitive PCa cells enhanced their radioresistance, which could be attenuated by silencing CXCL8 in stromal cells or inhibiting its receptor CXCR2 in PCa cells. sEV‐mediated radioresistance has been validated in zebrafish and mouse xenograft tumours. Mechanistically, the uptake of stromal sEVs triggers the AMPK‐activated autophagy pathway in PCa cells under the irradiation condition. Consequently, inactivating AMPK efficiently resensitized radiotherapy either by utilizing an AMPK inhibitor or silencing AMPKα in PCa cells. Furthermore, chloroquine (CQ), a lysosomal inhibitor, sufficiently resensitized radiotherapy via blockade of autophagolysosome fusion, leading to autophagosome accumulation in PC cells. Collectively, these results suggest that stromal cells enhance the radioresistance of PCa cells mainly through sEVs that deliver IL‐8.

Introduction: Polysaccharides from Grifola frondosa (Dicks.) Gray (HSH) and Inonotus obliquus (Fr.) Pilat (BHR) showed noticeable effects on dextran sulfate sodium (DSS)-induced colitis, but their systemic modulation effects have not been fully revealed. This study aimed to investigate the regulation of the gut microbiota and systemic metabolism by HSH and BHR in DSS-induced colitis.Methods: C57BL/6J mice were given DSS (2.5%) in water and were treated with HSH and BHR (200 mg/kg/day) by gavage. Body weight and colon length were recorded, and H&E and AB-PAS staining of the colon were conducted to evaluate the model and the protective effect of the polysaccharides. Additionally, an LC-QTOF/MS-based untargeted metabolomic platform was used to identify the metabolites in the serum, colon tissue, gut contents, and faeces and investigate differential metabolites and metabolic pathways. 16S rDNA gene sequencing was used to measure the composition of bacterial communities.Results: The results showed that the mouse colitis model was established successfully, as evidenced by an increased disease activity index score [2.83 ± 0.62 vs. 0.06 ± 0.14 (p < 0.001)] and shortened colon length [5.43 ± 0.64 cm vs. 7.04 ± 0.29 cm (p < 0.001)], and HSH and BHR ameliorated DSS-induced colitis by improving the disease activity index (2.17 ± 0.28 and 1.83 ± 0.29, respectively) and restoring the colon length (6.12 ± 0.30 cm and 6.62 ± 0.35 cm, respectively). HSH and BHR significantly modulated metabolites involved in aromatic amino acid metabolism, the citrate cycle, purine metabolism, pyrimidine metabolism, etc. HSH and BHR increased the Chao1 index by 64.25% and 60.25%, respectively, and they increased the Shannon index by 13.02% and 10.23%, respectively. They both reversed the increase in the abundances of g_Odoribacter, g_Clostridium, g_AF12, g_Parabacteroides and g_Turicibacter and reversed the decrease in the abundance of g_unclassified_Bacteria induced by DSS. Specifically, HSH reversed the reductions in g_unclassified_Lactobacillales and g_Ruminococcus, and BHR reversed the decreases in g_unidentified_Coriobacteriaceae and g_unclassified_Firmicutes.Discussion: These results suggested that HSH and BHR may ameliorate DSS-induced colitis by global modulation of systemic metabolism and the gut microbiota. Targeting the gut microbiota may be a potentially effective strategy to modulate systemic metabolism and treat colitis.

Background: Ventricular septal defects (VSDs) are one of the mechanical complications of acute myocardial infarction (AMI). Because of the high risks of mortality and postoperative complications, a new alternative method is needed. With the development of interventional medicine, transcatheter closure has been increasingly performed for postmyocardial infarction ventricular septal defects (PMIVSDs). The aim of this study is to explore the feasibility and safety of transcatheter closure of PMIVSDs by meta-analysis. Methods: The included studies were mainly single-arm studies of transcatheter closure of PMIVSDs. We compared VSD size, device size, preoperative risk factors and interventions among PMIVSD patients. We analysed the transcatheter closure success rate, the 30-day mortality rate, and the incidence of residual shunts. Results: A total of 12 single‐arm articles (284 patients) were included. The combined incidences of preoperative hypertension, hyperlipidaemia, and diabetes were 66% [95% CI 0.56–0.75], 54% [95% CI 0.40–0.68], and 33% [95% CI] 0.21–0.46], respectively. Multiple studies reported the combined incidences of preoperative PCI, IABP, and CABG, which were 46% [95% CI 0.15–0.80], 60% [95% CI 0.44–0.75], and 8% [95% CI 0.02–0.18]. Eleven studies reported the number of successful closures and the 30-day mortality rate; the success rate was 90% [95% CI 0.86–0.94], and the 30-day mortality rate reached 27% [95% CI 0.86–0.94]. Conclusion: For patients with PMIVSD, transcatheter closure in the acute phase can be used as a rescue measure, while in the chronic phase, it is more effective and has a lower mortality rate, but the effect of selection bias should be considered. Residual shunts are a long-term complication that have a high incidence and long-lasting effects on patients. More large, multicentre, randomized controlled trials are needed in the future to confirm the safety and reliability of transcatheter closure of PMIVSDs.

Abstract Designing an efficient and durable electrocatalyst for the sluggish anodic oxygen evolution reaction (OER) has been the primary goal of using proton exchange membrane electrolyzer owing to the highly acidic and oxidative environment at the anode. In this work, it is reported that high‐valence manganese drives the strong anchoring of the Ir species on the manganese dioxide (MnO2) matrix via the formation of an Mn–O–Ir coordination structure through a hydrothermal‐redox reaction. The iridium (Ir)‐atom‐array array is firmly anchored on the Mn–O–Ir coordination structure, endowing the catalyst with excellent OER activity and stability in an acidic environment. Ir‐MnO2(160)‐CC shows an ultralow overpotential of 181 mV at j = 10 mA cm−2 and maintains long‐term stability of 180 h in acidic media with negligible decay, superior to most reported electrocatalysts. In contrast, when reacting with low‐valence MnO2, Ir species tend to aggregate into IrOx nanoparticles, leading to poor OER stability. Density functional theory (DFT) calculations further reveal that the formation of the Mn–O–Ir coordination structure can optimize the adsorption strength of *OOH intermediates, thus boosting the acidic OER activity and stability.

Abstract Background Most antidepressants have been developed on the basis of the monoamine deficiency hypothesis of depression, in which neuronal serotonin (5-HT) plays a key role. 5-HT biosynthesis is regulated by the rate-limiting enzyme tryptophan hydroxylase-2 (TPH2). TPH2 methylation is correlated with antidepressant effects. Resting-state functional MRI (rs-fMRI) is applied for detecting abnormal brain functional activity in patients with different antidepressant effects. We will investigate the effect of the interaction between rs-fMRI and TPH2 DNA methylation on the early antidepressant effects. Methods A total of 300 patients with major depressive disorder (MDD) and 100 healthy controls (HCs) were enrolled, of which 60 patients with MDD were subjected to rs-fMRI. Antidepressant responses was assessed by a 50% reduction in 17-item Hamilton Rating Scale for Depression (HAMD-17) scores at baseline and after two weeks of medication. The RESTPlus software in MATLAB was used to analyze the rs-fMRI data. The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), fractional ALFF (fALFF), and functional connectivity (FC) were used, and the above results were used as regions of interest (ROIs) to extract the average value of brain ROIs regions in the RESTPlus software. Generalized linear model analysis was performed to analyze the association between abnormal activity found in rs-fMRI and the effect of TPH2 DNA methylation on antidepressant responses. Results Two hundred ninety-one patients with MDD and 100 HCs were included in the methylation statistical analysis, of which 57 patients were included in the further rs-fMRI analysis (3 patients were excluded due to excessive head movement). 57 patients were divided into the responder group (n = 36) and the non-responder group (n = 21). Rs-fMRI results showed that the ALFF of the left inferior frontal gyrus (IFG) was significantly different between the two groups. The results showed that TPH2–1–43 methylation interacted with ALFF of left IFG to affect the antidepressant responses (p = 0.041, false discovery rate (FDR) corrected p = 0.149). Conclusions Our study demonstrated that the differences in the ALFF of left IFG between the two groups and its association with TPH2 methylation affect short-term antidepressant drug responses.

Abstract Background The interaction between programmed death receptor (PD-1) and its ligand (PD-L1) is essential for suppressing activated T-lymphocytes. However, the precise mechanisms underlying PD-L1 overexpression in tumours have yet to be fully elucidated. Here, we describe that RelB participates in the immune evasion of prostate cancer (PCa) via cis/trans transcriptional upregulation of PD-L1. Methods Based on transcriptome results, RelB was manipulated in multiple human and murine PCa cell lines. Activated CD4+ and CD8+ T cells were cocultured with PCa cells with different levels of RelB to examine the effect of tumourous RelB on T cell immunity. Male mice were injected with murine PCa cells to validate the effect of RelB on the PD-1/PD-L1-mediated immune checkpoint using both tumour growth and metastatic experimental models. Results PD-L1 is uniquely expressed at a high level in PCa with high constitutive RelB and correlates with the patients’ Gleason scores. Indeed, a high level of PD-L1 is associated with RelB nuclear translocation in AR-negative aggressive PCa cells. Conversely, the silencing of RelB in advanced PCa cells resulted in reduced PD-L1 expression and enhanced susceptibility of PCa cells to the T cell immune response in vitro and in vivo. Mechanistically, a proximal NF-κB enhancer element was identified in the core promoter region of the human CD274 gene, which is responsible for RelB-mediated PD-L1 transcriptional activation. This finding provides an informative insight into immune checkpoint blockade by administering RelB within the tumour microenvironment. Conclusion This study deciphers the molecular mechanism by which tumourous RelB contributes to immune evasion by inhibiting T cell immunity via the amplification of the PD-L1/PD-1-mediated immune checkpoint.

IntroductionThe diagnostic value of 7 tumor-associated autoantibodies (AABs) including p53, PGP9.5, SOX2, GAGE7, GBU4-5, MEGEA1, and CAGE for the detection of lung cancer has shown inconsistency in several studies. This study aimed to confirm the diagnostic value of 7AABs and to explore whether the diagnostic value would be improved by combining them with 7 traditional tumor-associated antigens (CEA, NSE, CA125, SCC, CA15-3, pro-GRP, and CYFRA21-1) in clinical settings.MethodsThe plasma levels of 7-AABs were detected by enzyme-linked immunosorbent assay (ELISA) in 533 lung cancer cases and 454 controls. The 7 tumor antigens (7-TAs) were measured by Electrochemiluminescence immunoassay with Cobas 6000 (Roche, Basel, Switzerland).ResultsThe positive rate of 7-AABs in the lung cancer group (64.00%) was significantly higher than that of healthy controls (47.90%). The 7-AABs panel was able to discriminate lung cancer from controls with a specificity of 51.50%. After combining the 7-AABs with 7-TAs, the sensitivity showed a significantly enhancement compared with 7AABs panel alone (92.09% vs 63.21%). In patients with resectable lung cancer, the combination of 7-AABs and 7-TAs improved the sensitivity from 63.52% to 97.42%DiscussionIn conclusion, our study found that the diagnostic value of 7-AABs was enhanced when combined with 7-TAs. This combined panel could be used as promising biomarker to detect resectable lung cancer in clinical settings.

Planar double-jointed robot is a kind of widely used robot. In the past decades, with the development of science and technology, planar double-jointed robot has a great breakthrough in many aspects, especially in the actual camera and attitude analysis. In recent years, pun-section manipulator has made great progress in technology, but its kinematic characteristics and the human body’s ability to move have a great gap. So, in the moving plane, we need to study how to improve its camera ability to find a more stable and effective camera mode, and to a certain extent, to meet its requirements in complex working conditions. Simulating the pose of two joints, we seek a more stable and effective camera mode to improve its moving speed, expand its moving space, and lay a solid foundation for its application. Planar double-jointed robot is the most representative one at present. It includes machinery, material, electronics, computer, sensor, drive, intelligent control, artificial intelligence, and so on. Because it is closer to the human body, more suitable for people’s work and work, so it does not need to change its environment, so it is regarded as having a high affinity for people’s machinery. Its characteristic is that it has the good adaptability and the flexibility, but the double joint camera’s support discontinuity enables it to be able to adapt each kind of complex situation well. It can not only climb the stairs but also in the messy ground smooth through and also in the inconvenient passage through. The aim of this paper is to analyze the unique advantages and irreplaceable characteristics of the planar double-jointed robot based on the bionic and mechanical research results. This paper analyzes the mechanical technology by means of literature review and actual data analysis. The experimental results show that the biggest difference between the two articulated robots and other robots is that they have two human-like joint motions.

The power system is migrating to 100% penetration of the converter-interfaced generation (CIG). The grid-forming converter-based CIG has been proposed to be a solution to replace the synchronous generation (SG) in order to form the grid and achieve the 100% penetration target. However, besides the generation, whether the protection system can coordinate this transition is still an open question. Although the grid-forming converter operates as the same manner as the SG, unlike SG, it physically has constraints on its current output which in transient leads to different operation to the SG. This paper aims to investigate whether these different transients have effects on the protection system, specifically, investigate if the protection system remains reliable when the system migrates to 100% penetration. The investigation is based on the hardware in-the-loop experiment, considering different converter control, different type of the fault, different length of the line and different fault location. The result shows that the grid-forming converter has a reliable coordination with the protection system in response to the fault.

BackgroundFactors that may influence the recovery of patients with confirmed SARS-CoV-2 infection hospitalized in the Fangcang shelter were explored, and machine learning models were constructed to predict the duration of recovery during the Omicron BA. 2.2 pandemic.MethodsA retrospective study was conducted at Hongqiao National Exhibition and Convention Center Fangcang shelter (Shanghai, China) from April 9, 2022 to April 25, 2022. The demographics, clinical data, inoculation history, and recovery information of the 13,162 enrolled participants were collected. A multivariable logistic regression model was used to identify independent factors associated with 7-day recovery and 14-day recovery. Machine learning algorithms (DT, SVM, RF, DT/AdaBoost, AdaBoost, SMOTEENN/DT, SMOTEENN/SVM, SMOTEENN/RF, SMOTEENN+DT/AdaBoost, and SMOTEENN/AdaBoost) were used to build models for predicting 7-day and 14-day recovery.ResultsOf the 13,162 patients in the study, the median duration of recovery was 8 days (interquartile range IQR, 6–10 d), 41.31% recovered within 7 days, and 94.83% recovered within 14 days. Univariate analysis showed that the administrative region, age, cough medicine, comorbidities, diabetes, coronary artery disease (CAD), hypertension, number of comorbidities, CT value of the ORF gene, CT value of the N gene, ratio of ORF/IC, and ratio of N/IC were associated with a duration of recovery within 7 days. Age, gender, vaccination dose, cough medicine, comorbidities, diabetes, CAD, hypertension, number of comorbidities, CT value of the ORF gene, CT value of the N gene, ratio of ORF/IC, and ratio of N/IC were related to a duration of recovery within 14 days. In the multivariable analysis, the receipt of two doses of the vaccination vs. unvaccinated (OR = 1.118, 95% CI = 1.003–1.248; p = 0.045), receipt of three doses of the vaccination vs. unvaccinated (OR = 1.114, 95% CI = 1.004–1.236; p = 0.043), diabetes (OR = 0.383, 95% CI = 0.194–0.749; p = 0.005), CAD (OR = 0.107, 95% CI = 0.016–0.421; p = 0.005), hypertension (OR = 0.371, 95% CI = 0.202–0.674; p = 0.001), and ratio of N/IC (OR = 3.686, 95% CI = 2.939–4.629; p < 0.001) were significantly and independently associated with a duration of recovery within 7 days. Gender (OR = 0.736, 95% CI = 0.63–0.861; p < 0.001), age (30–70) (OR = 0.738, 95% CI = 0.594–0.911; p < 0.001), age (>70) (OR = 0.38, 95% CI = 0292–0.494; p < 0.001), receipt of three doses of the vaccination vs. unvaccinated (OR = 1.391, 95% CI = 1.12–1.719; p = 0.0033), cough medicine (OR = 1.509, 95% CI = 1.075–2.19; p = 0.023), and symptoms (OR = 1.619, 95% CI = 1.306–2.028; p < 0.001) were significantly and independently associated with a duration of recovery within 14 days. The SMOTEEN/RF algorithm performed best, with an accuracy of 90.32%, sensitivity of 92.22%, specificity of 88.31%, F1 score of 90.71%, and AUC of 89.75% for the 7-day recovery prediction; and an accuracy of 93.81%, sensitivity of 93.40%, specificity of 93.81%, F1 score of 93.42%, and AUC of 93.53% for the 14-day recovery prediction.ConclusionAge and vaccination dose were factors robustly associated with accelerated recovery both on day 7 and day 14 from the onset of disease during the Omicron BA. 2.2 wave. The results suggest that the SMOTEEN/RF-based model could be used to predict the probability of 7-day and 14-day recovery from the Omicron variant of SARS-CoV-2 infection for COVID-19 prevention and control policy in other regions or countries. This may also help to generate external validation for the model.

The oral and maxillofacial organs play vital roles in chewing, maintaining facial beauty, and speaking. Almost all physiological processes display circadian rhythms that are driven by the circadian clock, allowing organisms to adapt to the changing environment. In recent years, increasing evidence has shown that the circadian clock system participates in oral and maxillofacial physiological and pathological processes, such as jaw and tooth development, salivary gland function, craniofacial malformations, oral carcinoma and other diseases. However, the roles of the circadian clock in oral science have not yet been comprehensively reviewed. Therefore, This paper provides a systematic and integrated perspective on the function of the circadian clock in the fields of oral science, reviews recent advances in terms of the circadian clock in oral and maxillofacial development and disease, dialectically analyzes the importance of the circadian clock system and circadian rhythm to the activities of oral and maxillofacial tissues, and focuses on analyzing the mechanism of the circadian clock in the maintenance of oral health, affecting the common diseases of the oral and maxillofacial region and the process of oral-related systemic diseases, sums up the chronotherapy and preventive measures for oral-related diseases based on changes in tissue activity circadian rhythms, meanwhile, comes up with a new viewpoint to promote oral health and human health.

Numerical simulation on the U-shaped channel with various inlet positions using air cooling is investigated to solve heat dissipation issue of battery pack in electric vehicle. The mechanism of the influences of inlet position and inlet air velocity on the cooling performance of battery pack is revealed. The results show that the maximum temperature of battery pack decreases by 4.17 K at inlet position of 30 mm compared with that of 20 mm due to the increase of airflow velocity in the second half of the battery pack caused by flow around effect. The maximum temperature of battery pack decreases by 8.5–18.5 K with increasing inlet air velocity from 2 m/s to 5 m/s. The cooling performance improves because of flow around effect and high convective heat transfer using reasonable matching between inlet position (10–30 mm) and inlet air velocity (3–6 m/s). This paper provides valuable guidelines for cooling design of battery pack in electric vehicle.

Abstract Seawater electrolysis is an attractive technique for mass production of high‐purity hydrogen considering the abundance of seawater. Nevertheless, due to the complexity of seawater environment, efficient anode catalyst, that should be, cost effective, highly active for oxygen evolution reaction (OER) but negligible for Cl2/ClO– formation, and robust toward chlorine corrosion, is urgently demanded for large‐scale application. Although catalysis typically appears at surface, while the bulk properties and morphology structure also have a significant impact on the performance, thus requiring a systematic optimization. Herein, a multiscale engineering approach toward the development of cost‐effective and robust OER electrocatalyst for operation in seawater is reported. Specifically, the engineering of hollow‐sphere structure can facilitate the removal of gas product, while atom‐level synergy between Co and Fe can promote Co sites transforming to active phase, and in situ transformation of sulfate ions layer protects catalysts from corrosion. As a result, the as‐developed hollow‐sphere structured CoFeSx electrocatalyst can stably operate at a high current density of 100 mA cm–2 in the alkaline simulated seawater (pH = 13) for 700 h and in a neutral seawater for 20 h without attenuation. It provides a new strategy for the development of electrocatalysts with a broader application potential.

The hybrid heating system consisting of loop heat pipe solar collector (LHPSC) and ground source heat pump (GSHP) is proposed to control greenhouse temperature in Harbin (the coldest provincial capital of China) in this paper. The combined thermal resistance network and energy balance model is developed to predict transient greenhouse temperature corresponding to the energy supplied by GSHP. The influence of ambient temperature on the thermal performance of greenhouse heating system is analyzed. The results show that the greenhouse temperature fluctuates in the range of 17–24 °C corresponding to the energy of 200 kW intermittently supplied by GSHP, which is reasonable for predicting greenhouse temperature in severely cold regions. As ambient temperature varies from −24 °C to −13 °C, heat loss of maintenance structure, ground, ventilation and water storage tank change in the range of 51.9–73.2 kW, 2.45–3.45 kW, 11.1–15.5 kW and 5.87–6.91 kW, respectively. The maximum thermal efficiency of loop heat pipe solar collector is higher (76.38%) than that of evacuated tube solar collectors (45%–50%), which will be promising for greenhouse heating due to higher thermal efficiency and better environmental adaptability. The results presented in this study will provide further valuable guidelines for designing greenhouse heating system.

pH-responsive viscoelastic fluids are often achieved by adding hydrotropes into surfactant solutions. However, the use of metal salts to prepare pH-responsive viscoelastic fluids has been less documented. Herein, a pH-responsive viscoelastic fluid was developed by blending an ultra-long-chain tertiary amine, N-erucamidopropyl-N, N-dimethylamine (UC22AMPM), with metal salts (i.e., AlCl3, CrCl3, and FeCl3). The effects of the surfactant/metal salt mixing ratio and the type of metal ions on the viscoelasticity and phase behavior of fluids were systematically examined by appearance observation and rheometry. To elucidate the role of metal ions, the rheological properties between AlCl3− and HCl−UC22AMPM systems were compared. Results showed the above metal salt evoked the low-viscosity UC22AMPM dispersions to form viscoelastic solutions. Similar to HCl, AlCl3 could also protonate the UC22AMPM into a cationic surfactant, forming wormlike micelles (WLMs). Notably, much stronger viscoelastic behavior was evidenced in the UC22AMPM−AlCl3 systems because the Al3+ as metal chelators coordinated with WLMs, promoting the increment of viscosity. By tuning the pH, the macroscopic appearance of the UC22AMPM−AlCl3 system switched between transparent solutions and milky dispersion, concomitant with a viscosity variation of one order of magnitude. Importantly, the UC22AMPM−AlCl3 systems showed a constant viscosity of 40 mPa·s at 80 °C and 170 s−1 for 120 min, indicative of good heat and shear resistances. The metal-containing viscoelastic fluids are expected to be good candidates for high-temperature reservoir hydraulic fracturing.

Abstract Background Coronavirus disease 2019 (COVID-19) has spread around the world. This retrospective study aims to analyze the clinical features of COVID-19 patients with cancer and identify death outcome related risk factors. Methods From February 10th to April 15th, 2020, 103 COVID-19 patients with cancer were enrolled. Difference analyses were performed between severe and non-severe patients. A propensity score matching (PSM) analysis was performed, including 103 COVID-19 patients with cancer and 206 matched non-cancer COVID-19 patients. Next, we identified death related risk factors and developed a nomogram for predicting the probability. Results In 103 COVID-19 patients with cancer, the main cancer categories were breast cancer, lung cancer and bladder cancer. Compared to non-severe patients, severe patients had a higher median age, and a higher proportion of smokers, diabetes, heart disease and dyspnea. In addition, most of the laboratory results between two groups were significantly different. PSM analysis found that the proportion of dyspnea was much higher in COVID-19 patients with cancer. The severity incidence in two groups were similar, while a much higher mortality was found in COVID-19 patients with cancer compared to that in COVID-19 patients without cancer (11.7% vs. 4.4%, P = 0.028). Furthermore, we found that neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) were related to death outcome. And a nomogram based on the factors was developed. Conclusion In COVID-19 patients with cancer, the clinical features and laboratory results between severe group and non-severe group were significantly different. NLR and CRP were the risk factors that could predict death outcome.

Abstract Background The novel coronavirus disease 2019 (COVID-19) spreads rapidly among people and causes a pandemic. It is of great clinical significance to identify COVID-19 patients with high risk of death. Methods A total of 2169 adult COVID-19 patients were enrolled from Wuhan, China, from February 10th to April 15th, 2020. Difference analyses of medical records were performed between severe and non-severe groups, as well as between survivors and non-survivors. In addition, we developed a decision tree model to predict death outcome in severe patients. Results Of the 2169 COVID-19 patients, the median age was 61 years and male patients accounted for 48%. A total of 646 patients were diagnosed as severe illness, and 75 patients died. An older median age and a higher proportion of male patients were found in severe group or non-survivors compared to their counterparts. Significant differences in clinical characteristics and laboratory examinations were found between severe and non-severe groups, as well as between survivors and non-survivors. A decision tree, including three biomarkers, neutrophil-to-lymphocyte ratio, C-reactive protein and lactic dehydrogenase, was developed to predict death outcome in severe patients. This model performed well both in training and test datasets. The accuracy of this model were 0.98 in both datasets. Conclusion We performed a comprehensive analysis of COVID-19 patients from the outbreak in Wuhan, China, and proposed a simple and clinically operable decision tree to help clinicians rapidly identify COVID-19 patients at high risk of death, to whom priority treatment and intensive care should be given.

Neuroinflammation and anhedonia in major depressive disorder (MDD) are closely connected, though the exact mechanism is unclear. This study aimed to investigate the relationships between cytokines, C-reactive protein (CRP), cortisol, and anhedonia, revealing the potential predictive value in identifying anhedonic MDD. In total, 66 patients with MDD (29 with anhedonia and 37 without anhedonia) and 66 healthy controls (HCs) were included. The severity of depression and anhedonia was evaluated using the Hamilton Rating Scale for Depression-24 (HAMD-24) and Snaith-Hamilton Pleasure Scale (SHAPS), respectively. Serum cytokines were measured using flow cytofluorometric kits, while CRP and cortisol were measured using enzyme-linked immunosorbent assay kits. We found higher serum levels of interleukin-2 (IL-2), IL-6, and cortisol in MDD than in HC where anhedonic MDD was highest. CRP and IL-6 were positively associated with anhedonia, and cortisol levels were related to both anhedonia and depression. A combination of IL-6, CRP, and cortisol had optimal predictive value for distinguishing anhedonic MDD. Anhedonic MDD has unique neuroendocrine-immune characteristics compared with those without anhedonia. The combination of IL-6, CRP, and cortisol might be an early marker to distinguish anhedonic MDD.

Composting can convert organic materials into stable humus (HS), resulting in high-fertility organic fertilizers that were widely used in the treatment of agricultural wastes. Therefore, it would be beneficial to strengthen the degree of composting humification by exploring the formation law and the main influencing factors of composting humification for different agricultural wastes. In this study, straw, cabbage, chicken manure, and pig manure were used as research objects, and the industrial mixed-material strip-stack composting and the single-material laboratory reactor composting were carried out, respectively. The results showed that the industrial mixed-material composting mode was beneficial to the continuation of the high-temperature period for composting (the heat lasts for 20 days), and the high lignin treatment T2 (straw + chicken manure composting) helped to promote the degradation of lignin and formation of humic acid (HA). At the end of composting, the absolute degradation of lignin in T2 treatment increased by 13.18% and 120.02% (p < 0.01) compared with T1 (straw + cabbage + chicken manure) and T3 (straw + pig manure) treatments, respectively (p < 0.01), and the humic acid (HA) content increased by 11.78% and 26.59% (p < 0.05). In the single-material laboratory reactor composting system, the continuous high-temperature period (31 days) contributed to the degradation of the composting materials and the formation of HA in the straw (TS) composting treatment; at the end of composting, the absolute degradation amount of TS lignin increased by 137.98%, 170.99%, and 196.82% compared with TV (cabbage), TC (chicken manure), and TP (pig manure) treatments (p < 0.01), and the HA content increased by 281.76%, 377.57%, and 460.71% (p < 0.01), respectively. Redundancy analysis showed that temperature was the main environmental factor affecting the decomposition and humification process of composting organic materials; the increase of lignin absolute degradation was helpful to promote the formation of HA. This study found that temperature was the main environmental factor that drove lignin degradation and promoted the humification process of agricultural waste composting; the lignin content in the composting material was the basis for the formation of HA, and the absolute degradation amount of lignin was the main material factor that promoted the humification process.

BackgroundBipolar disorder (BD) is easy to be misdiagnosed as major depressive disorder (MDD), which may contribute to a delay in treatment and affect prognosis. Circadian rhythm dysfunction is significantly associated with conversion from MDD to BD. So far, there has been no study that has revealed a relationship between circadian rhythm gene polymorphism and MDD-to-BD conversion. Furthermore, the prediction of MDD-to-BD conversion has not been made by integrating multidimensional data. The study combined clinical and genetic factors to establish a predictive model through machine learning (ML) for MDD-to-BD conversion.MethodBy following up for 5 years, 70 patients with MDD and 68 patients with BD were included in this study at last. Single nucleotide polymorphisms (SNPs) of the circadian rhythm genes were selected for detection. The R software was used to operate feature screening and establish a predictive model. The predictive model was established by logistic regression, which was performed by four evaluation methods.ResultsIt was found that age of onset was a risk factor for MDD-to-BD conversion. The younger the age of onset, the higher the risk of BD. Furthermore, suicide attempts and the number of hospitalizations were associated with MDD-to-BD conversion. Eleven circadian rhythm gene polymorphisms were associated with MDD-to-BD conversion by feature screening. These factors were used to establish two models, and 4 evaluation methods proved that the model with clinical characteristics and SNPs had the better predictive ability.ConclusionThe risk factors for MDD-to-BD conversion have been found, and a predictive model has been established, with a specific guiding significance for clinical diagnosis.

Patients with metastatic cancer refractory to standard systemic therapies have a poor prognosis and few therapeutic options. Radiotherapy can shape the tumor microenvironment (TME) by inducing immunogenic cell death and promoting tumor recognition by natural killer cells and T lymphocytes. Granulocyte macrophage-colony stimulating factor (GM-CSF) was known to promote dendric cell maturation and function, and might also induce the macrophage polarization with anti-tumor capabilities. A phase II trial (ChiCTR1900026175) was conducted to assess the clinical efficacy and safety of radiotherapy, PD-1 inhibitor and GM-CSF (PRaG regimen). This trial was registered at http://www.chictr.org.cn/index.aspx. A PRaG cycle consisted of 3 fractions of 5 or 8 Gy delivered for one metastatic lesion from day 1, followed by 200 μg subcutaneous injection of GM-CSF once daily for 2 weeks, and intravenous infusion of PD-1 inhibitor once within one week after completion of radiotherapy. The PRaG regimen was repeated every 21 days for at least two cycles. Once the PRaG therapy was completed, the patient continued PD-1 inhibitor monotherapy until confirmed disease progression or unacceptable toxicity. The primary endpoint was objective response rate (ORR). A total of 54 patients were enrolled with a median follow-up time of 16.4 months. The ORR was 16.7%, and the disease control rate was 46.3% in intent-to-treat patients. Median progression-free survival was 4.0 months (95% confidence interval [CI], 3.3 to 4.8), and median overall survival was 10.5 months (95% CI, 8.7 to 12.2). Grade 3 treatment-related adverse events occurred in five patients (10.0%) and grade 4 in one patient (2.0%). Therefore, the PRaG regimen was well tolerated with acceptable toxicity and may represent a promising salvage treatment for patients with chemotherapy-refractory solid tumors. It is likely that PRaG acts via heating upthe TME with radiotherapy and GM-CSF, which was further boosted by PD-1 inhibitors.

When traditional STATCOM (Static Synchronous Compensator) performs large-capacity reactive power compensation, the control accuracy of the DC side voltage will be affected and the DC side voltage will fluctuate greatly. Therefore, this study proposes to use battery energy storage STATCOM (STATCOM/BESS) and gives the main circuit topology of STATCOM/BESS. By analyzing the working principle of STATCOM/BESS, the mathematical model and control method are derived and modeled, in which the Shepherd model is used as the energy storage battery in STATCOM/BESS. Aiming at the possible imbalance of the battery state of charge (SOC) in STATCOM/BESS, the phase-to-phase SOC balance control and phase control are proposed. At last, in PSCAD/EMTDC simulation software, STATCOM/BESS is tested for dynamic response and steady-state response performance of active power control, reactive power control, and transformation failure suppression test, which verifies the effectiveness and superiority of STATCOM/BESS commutation failure.

Chemotherapeutic resistance is a major obstacle in the control of advanced breast cancer (BCa). We have previously shown that small extracellular vesicles (sEVs) can transmit adriamycin resistance between BCa cells. Here, we describe that sEV‐mediated TGF‐β1 intercellular transfer is involved in the drug‐resistant transmission. sEVs were isolated and characterized from both sensitive and resistant cells. sEVs derived from the resistant cells were incubated with the sensitive cells and resulted in transmitting the resistant phenotype to the recipient cells. Cytokine antibody microarray revealed that most metastasis‐associated cytokines present at the high levels in sEVs from the resistant cells compared with their levels in sEVs from the sensitive cells, particularly TGF‐β1 is enriched in sEVs from the resistant cells. The sEV‐mediated TGF‐β1 intercellular transfer led to increasing Smad2 phosphorylation and improving cell survival by suppressing apoptosis and enhancing cell mobility. Furthermore, sEV‐mediated drug‐resistant transmission by delivering TGF‐β1 was validated using a zebrafish xenograft tumor model. These results elaborated that sEV‐mediated TGF‐β1 intercellular transfer contributes to adriamycin resistance in BCa.

The current energy crisis has prompted the development of new energy sources and energy storage/conversion devices. Membranes, as the key component, not only provide enormous separation potential for energy purification but also guarantee stable and high-efficiency operation for rechargeable batteries and fuel cells. Remarkably, two-dimensional (2D) material separation membranes have attracted intense attention on their excellent performance in energy field applications, owing to high mechanical/chemical stability, low mass transport resistance, strict size-exclusion, and abundant modifiable functional groups. In this review, we concentrate on the recent progress of 2D membrane and introduce 2D membranes based on graphene oxide (GO), MXenes, 2D MOFs, 2D COFs, and 2D zeolite nanosheets, which are applied in membrane separation (H2 collection and biofuel purification) and battery separators (vanadium flow battery, Li–S battery, and fuel cell). The mass transport mechanism, selectivity mechanism, and modification methods of these 2D membranes are stated in brief, mainly focusing on interlayer dominant membranes (GO and MXenes) and pore dominant membranes (MOFs, COFs, and zeolite nanosheets). In conclusion, we highlight the challenges and outlooks of applying 2D membranes in energy fields.

The soil water supply and atmospheric humidity conditions are crucial in controlling plants’ stomatal behavior and water use efficiency. When there is water stress caused by an increase in saturated water vapor pressure (VPD) and a decrease in soil water content (SWC), plants tend to close stomata to reduce water loss. This affects the gross primary productivity (GPP) and evapotranspiration (ET), subsequently leading to changes in water use efficiency (WUE) and carbon use efficiency (CUE) in plants. However, land–atmosphere interactions mean that water vapor in the atmosphere and soil moisture content causing water stress for plants are closely related. This study aims to compare and estimate the effects of VPD and SWC on the carbon cycle and water cycle for different plant functional types. Based on the fluxnet2015 dataset from around the world, the WUE and CUE of five plant functional types (PFTs) were estimated under varying levels of VPD and SWC. The results showed that high VPD and low SWC limit the stomatal conductance (Gs) and gross primary productivity (GPP) of plants. However, certain types of vegetation (crops, broad-leaved forests) could partially offset the negative effects of high VPD with higher SWC. Notably, higher SWC could even alleviate limitations and partially promote the increase in GPP and net primary production (NPP) with increasing VPD. WUE and CUE were directly affected by Gs and productivity. In general, the increase in VPD in the five PFTs was the dominant factor in changing WUE and CUE. The impact of SWC limitations on CUE was minimal, with an overall impact of only −0.05μmol/μmol on the four PFTs. However, the CUE of savanna plants changed differently from the other four PFTs. The rise in VPD dominated the changes in CUE, and there was an upward trend as SWC declined, indicating that the increase in VPD and decrease in SWC promote the increase in the CUE of savanna plants to some extent.

Many efforts have been devoted to the forecasting of the capillary force generated by capillary adsorption between solids, which is fundamental and essential in the fields of micro-object manipulation and particle wetting. In this paper, an artificial neural network (ANN) model optimized by a genetic algorithm (GA-ANN) was proposed to predict the capillary force and contact diameter of the liquid bridge between two plates. The mean square error (MSE) and correlation coefficient (R2) were employed to evaluate the prediction accuracy of the GA-ANN model, theoretical solution method of the Young–Laplace equation and simulation approach based on the minimum energy method. The results showed that the values of MSE of capillary force and contact diameter using GA-ANN were 10.3 and 0.0001, respectively. The values of R2 were 0.9989 and 0.9977 for capillary force and contact diameter in regression analysis, respectively, demonstrating the accuracy of the proposed predictive model. The sensitivity analysis was conducted to investigate the influence of input parameters, including liquid volume and separation distance, on the capillary force and contact diameter. The liquid volume and separation distance played dominant roles in affecting the capillary force and contact diameter.

Barley (Hordeum vulgare L.) is the most important cereal crop in the Qinghai-Tibet Plateau, and the yield has been seriously threatened by Blumeria graminis f. sp. hordei (Bgh) in recent years. To understand the virulence and genetic traits of different Bgh populations, 229 isolates of Bgh were collected from Tibet, Sichuan, Gansu and Yunnan provinces of China during 2020 and 2021, and their pathogenicity to 21 barley lines of different genotypes was assessed. A total of 132 virulent types were identified. The Bgh isolates from Yunnan showed the highest diversity in terms of virulence complexity (Rci) and genetic diversity (KWm), followed by those from Sichuan, Gansu, and Tibet, in that order. Single nucleotide polymorphism (SNP) in genes coding for alternative oxidase (AOX), protein kinase A (PKA), and protein phosphatase type 2A (PPA) were detected at seven polymorphic sites. Nine haplotypes (H1–H9) with an average haplotype diversity (Hd) and nucleotide diversity π of 0.564 and 0.00034, respectively, were observed. Of these, haplotypes H1 and H4 accounted for 88.8% of the isolates, and H4 was predominant in Tibet. Genetic diversity analysis using the STRUCTURE (K = 2) and AMOVE indicated that the inter-group variation accounted for 54.68%, and inter- and intra-population genotypic heterogeneity accounted for 23.90% and 21.42%, respectively. The results revealed the recent expansion of the Bgh population in Tibet, accompanied by an increase in virulence and a loss of genetic diversity.

This study aimed to systematically explore the chemical constituents of D. nobile and its hypoglycemic effect by UPLC-ESI-Q-Orbitrap, network pharmacology and in vivo experiment. The chemical constituents of D. nobile were qualitatively analyzed, and the hypoglycemic compounds were quickly identified. Network pharmacological analysis and molecular docking technique were applied to assist in the elucidation of the hypoglycemic mechanisms of D. nobile. A type 2 diabetic mellitus (T2DM) rat model was established using the HFD and STZ method for in vivo experimental verification, and these T2DM rats were treated with D. nobile extract and D. nobile polysaccharide for two months by gavage. The results showed that a total of 39 chemical constituents of D. nobile, including alkaloids, bibenzyls, phenanthrenes and other types of compounds, were identified. D. nobile extract and D. nobile polysaccharide could significantly ameliorate the body weight, hyperglycemia, insulin resistance, dyslipidemia and morphological impairment of the liver and pancreas in the T2DM rats. α-Linolenic acid, dihydroconiferyl dihydro-p-coumarate, naringenin, trans-N-feruloyltyramine, gigantol, moscatilin, 4-O-methylpinosylvic acid, venlafaxine, nordendrobin and tristin were regarded as the key hypoglycemic compounds of D. nobile, along with the hypoglycemic effect on the PI3K-AKT signaling pathway, the insulin signaling pathway, the FOXO signaling pathway, the improvement of insulin resistance and the AGE-RAGE signaling pathway. The Western blotting experiment results confirmed that D. nobile activated the PI3K/AKT pathway and insulin signaling pathway, promoted glycogen synthesis via regulating the expression of glycogen synthase kinase 3 beta (GSK-3β) and glucose transporter 4 (GLUT4), and inhibited liver gluconeogenesis by regulating the expression of phosphoenolpyruvate carboxykinase (PEPCK) and glucose 6 phosphatase (G6pase) in the liver. The results suggested that the hypoglycemic mechanism of D. nobile might be associated with liver glycogen synthesis and gluconeogenesis, contributing to improving insulin resistance and abnormal glucose metabolism in the T2DM rats.

Abstract Background Knowledge on the etiology of LRTIs is essential for improvement of the clinical diagnosis and accurate treatment. Molecular detection methods were applied to identify a broad range of bacterial and viral pathogens in a large set of bronchial alveolar lavage (BAL) fluid samples. The patterns of detected pathogens were correlated to the clinical symptoms. Methods BAL fluid samples and clinical data were collected from 573 hospitalized children between 1 month and 14 years of age with LRTIs, enrolled from January to December 2018. Pathogens were detected using standardized clinical diagnostics, with a sensitive, high-throughput GeXP-based multiplex PCR and with multiplex qPCR. Data were analyzed to describe the correlation between the severity of respiratory tract disease and the pathogens identified. Results The pathogen detection rate with GeXP-based PCR and multiplex qPCR was significantly higher than by clinical routine diagnostics (76.09% VS 36.13%,χ2 = 8.191, P = 0.004). The most frequently detected pathogens in the BAL fluid were human adenovirus (HADV)(21.82%), Mycoplasma pneumoniae (20.24%), human rhinovirus (13.96%), Streptococcus pneumoniae (8.90%) and Haemophilus influenzae (8.90%). In 16.4% of the cases co-detection with two or three different pathogens was found. Viral detection rates declined with age, while atypical pathogen detection rates increased with age. Oxygen supply in the HADV and Influenza H1N1 infected patients was more frequent (49.43%) than in patients infected with other pathogens. Conclusion Broad range detection of viral and bacterial pathogens using molecular methods is a promising and implementable approach to improve clinical diagnosis and accurate treatment of LRTI in children.

Mapping local phonon dispersion in individual nanostructures reveals their thermal, optical, and mechanical properties but requires high detection sensitivity. Here, the authors present position-dependent phonon dispersion measurements in individual boron nitride nanotubes.

Video monitoring is an important means to ensure production safety in coal mine. However, the currently intelligent video surveillance is difficult to respond in real-time due to the latency of cloud computing. In this paper, a cloud-edge cooperation framework is proposed, which integrates cloud computing and edge computing in a coordinated manner. The cloud computing is used to process non-real-time and global tasks, while the edge computing is responsible for handling local monitoring video in real-time. In order to realize cloud-edge data interaction and online optimization for edge models, the heterogeneous converged network is built. In addition, an object detection model FL-YOLO composed of depthwise separable convolution and down-sampling inverted residual block is proposed, which realizes real-time video analysis at the edge. Finally, this paper discusses the complexity of FL-YOLO by its computational cost and model size. The experiment results show that the model size of FL-YOLO is 16.1MB, which is very light, and it achieves 36.7 FPS on NVIDIA Jetson TX1 and an AP of 76.7% on Multi-scene pedestrian dataset. Comparing with mainstream object detection models, FL-YOLO completes faster detection speed and higher accuracy, and it has lower calculation complexity and smaller model scale. Furthermore, the AP on Single-scene pedestrian dataset of FL-YOLO is improved to 80.7% by cloud-edge cooperation. K-Fold method is also used to further compared the performance of FL-YOLO and other models. Moreover, system test is implemented on coal mine, which validates the actual engineering effect of the proposed cloud-edge cooperation framework.

Intelligent video surveillance is important to ensure production safety in coal mines, while cloud-edge cooperation is an effective means to improve the performance of intelligent video monitoring. However, in edge layers, incorrect resource allocation of computing and network resources will result in the waste of resources and low real-time performance. In this paper, a DDPG-Based (Deep deterministic policy gradient-based) edge resource allocation method for cloud-edge cooperation framework is proposed. Firstly, the cloud-edge cooperation framework is designed for different tasks. Secondly, the joint minimizing problem of latency and bandwidth usage caused by edge computing is modeled. To quickly solve the joint optimization problem, we convert it to MDP (Markov Decision Process). In addition, ESPN (Edge status perception network) is proposed, which enhances the ability of feature perception and action output of DDPG. Finally, DDPG-ESPN is proposed to solve the joint optimization problem. Simulation results show that compared with other methods, DDPG-ESPN improves the real-time performance and bandwidth usage by up to 18.88% and 42.81% respectively.

The two-line rice hybrid “Super 1000” (GX24S × R900) represents a major landmark achievement of breeding for super-hybrid rice in China. However, both male parent R900 and hybrid “Super 1000” have an obvious defect of high susceptibility to rice bacterial blight (BB) and blast. Thus, improving disease resistance and maintaining the original high-yield capacity are essential for the sustainable application of “Super 1000.” In this study, the application of closely linked single-nucleotide polymorphism (SNP) markers for foreground selection of dominant resistance gene loci together with genome-wide SNP markers for the background selection rapidly improved the disease resistance of R900 without disturbing its high-yield capacity. A series of improved R900 lines (iR900, in BC2Fn and BC3Fn generations) were developed to stack resistance genes (Xa23+Pi9, Xa23+Pi1+Pi2/9) by marker-assisted backcrossing and field selection for phenotypes, and further crossed with the female line GX24S to obtain improved hybrid variety Super 1000 (iS1000). The genetic backgrounds of iS1000 and “Super 1000” were profiled by using a 56 K SNP-Chip, and results showed that they shared 98.76% of similarity. Meanwhile, evaluation of the field disease resistance showed that the iR900 lines and iS1000 hybrids possess significantly enhanced resistance to both BB and rice blast. Resistance spectrum assays revealed that the iR900 lines and their derived hybrids exhibited high-level resistance to 28 Xoo strains tested, and enhanced resistance to leaf blast at the seedling stage when infected with 38 Magnaporthe oryzae isolates. Between 2019 and 2020, the multi-location field trials across the middle and lower reaches of the Yangtze River were launched and showed that the iS1000 slightly out-yielded than the original variety. In a large-scale demonstration site (6.73 ha, Yunnan, China), the iS1000 achieved 17.06 t/hm2 of yield in 2019. Moreover, the high similarity was observed in main agronomic traits and grain quality when comparing the improved lines/hybrids to original ones (iR900 vs. R900, iS1000 vs. S1000). This work presented a typical genomics-assisted breeding strategy and practice, which involves in directional introgression and rapid stack of multiple disease resistance genes, endowing the super-high-yield hybrid rice variety with holistic disease resistance but without yield penalty.

Pyrolysis of rice straw (RS), a popular method for producing biochar, effectively treats heavy metal(loid)-contaminated RS. Here, we carried out this process at different temperatures and investigated the deportment of heavy metal(loid)s and the property evolution of biochars. Also, the optimal pyrolysis temperature for Pb adsorption and immobilization was studied. We observed that increasing the temperature could volatilize the heavy metal(loid)s. Cd was the most volatile metal therein, followed by As, while Ni, Cu, and Pb were relatively refractory. More than 75% of the remaining heavy metal(loid)s were non-exchangeable fractions at 700 °C, significantly reducing the environmental risk during subsequent application. Meanwhile, higher pyrolysis temperature resulted in higher pH values, higher surface areas, and stronger Pb adsorption capacity of RS biochars. The maximum adsorption capacity (Qm) of biochars was in the order of BC300 (77.2 mg·g−1)

Due to the poor performance of traditional STATCOM in DC engineering, a compensation method using battery energy storage STATCOM (STATCOM/BESS) to suppress commutation failure of the weak receiving-end high voltage direct current transmission system is proposed, and its effect is better than traditional STATCOM. First, the mechanism and influencing factors of commutation failure are analyzed; the extinction angle of the converter valve is taken as the decision index of commutation failure; the relationship between various electrical parameters and extinction angle is studied under the condition of the single-phase grounding fault on the inverter side. Second, according to the differences between the positive and negative sequence reactive current output by STATCOM/BESS when a fault occurs in single-phase grounding, a compensation method is proposed to suppress commutation failure by STATCOM/BESS, which increases the proportion of positive sequence reactive current output by STATCOM/BESS under the condition of constant output so as to reduce the probability of commutation failure. At last, STATCOM/BESS is added into the standard model of LCC-HVDC for the simulation experiment and compared with conventional running characteristics of STATCOM in order to verify the effect of STATCOM/BESS in suppressing commutation failure.

Abstract Background Mesenchymal stem cells (MSCs) serve as an attractive vehicle for cell-directed enzyme prodrug therapy (CDEPT) due to their unique tumour-nesting ability. Such approach holds high therapeutic potential for treating solid tumours including glioblastoma multiforme (GBM), a devastating disease with limited effective treatment options. Currently, it is a common practice in research and clinical manufacturing to use viruses to deliver therapeutic genes into MSCs. However, this is limited by the inherent issues of safety, high cost and demanding manufacturing processes. The aim of this study is to identify a facile, scalable in production and highly efficient non-viral method to transiently engineer MSCs for prolonged and exceptionally high expression of a fused transgene: yeast cytosine deaminase::uracil phosphoribosyl-transferase::green fluorescent protein (CD::UPRT::GFP). Methods MSCs were transfected with linear polyethylenimine using a cpg-free plasmid encoding the transgene in the presence of a combination of fusogenic lipids and β tubulin deacetylase inhibitor (Enhancer). Process scalability was evaluated in various planar vessels and microcarrier-based bioreactor. The transfection efficiency was determined with flow cytometry, and the therapeutic efficacy of CD::UPRT::GFP expressing MSCs was evaluated in cocultures with temozolomide (TMZ)-sensitive or TMZ-resistant human glioblastoma cell lines. In the presence of 5-fluorocytosine (5FC), the 5-fluorouracil-mediated cytotoxicity was determined by performing colometric MTS assay. In vivo antitumor effects were examined by local injection into subcutaneous TMZ-resistant tumors implanted in the athymic nude mice. Results At > 90% transfection efficiency, the phenotype, differentiation potential and tumour tropism of MSCs were unaltered. High reproducibility was observed in all scales of transfection. The therapeutically modified MSCs displayed strong cytotoxicity towards both TMZ-sensitive and TMZ-resistant U251-MG and U87-MG cell lines only in the presence of 5FC. The effectiveness of this approach was further validated with other well-characterized and clinically annotated patient-derived GBM cells. Additionally, a long-term suppression (> 30 days) of the growth of a subcutaneous TMZ-resistant U-251MG tumour was demonstrated. Conclusions Collectively, this highly efficient non-viral workflow could potentially enable the scalable translation of therapeutically engineered MSC for the treatment of TMZ-resistant GBM and other applications beyond the scope of this study.

Abstract Background The activation of the NF-κB pathway plays a crucial role in the progression of breast cancer (BCa) and also involved in endocrine therapy resistance. On the contrary to the canonical NF-κB pathway, the effect of the noncanonical NF-κB pathway in BCa progression remains elusive. Methods BCa tumor tissues and the corresponding cell lines were examined to determine the correlation between RelB and the aggressiveness of BCa. RelB was manipulated in BCa cells to examine whether RelB promotes cell proliferation and motility by quantitation of apoptosis, cell cycle, migration, and invasion. RNA-Seq was performed to identify the critical RelB-regulated genes involved in BCa metastasis. Particularly, RelB-regulated MMP1 transcription was verified using luciferase reporter and ChIP assay. Subsequently, the effect of RelB on BCa progression was further validated using BCa mice xenograft models. Results RelB uniquely expresses at a high level in aggressive BCa tissues, particularly in triple-negative breast cancer (TNBC). RelB promotes BCa cell proliferation through increasing G1/S transition and/or decreasing apoptosis by upregulation of Cyclin D1 and Bcl-2. Additionally, RelB enhances cell mobility by activating EMT. Importantly, RelB upregulates bone metastatic protein MMP1 expression through binding to an NF-κB enhancer element located at the 5′-flanking region. Accordingly, in vivo functional validation confirmed that RelB deficiency impairs tumor growth in nude mice and inhibits lung metastasis in SCID mice. Video abstract

Abstract Background Variation in genes implicated in homocysteine and lipid metabolism systems may influence antidepressant response for patients with major depressive disorder (MDD). This study aimed to investigate whether association of polymorphisms on the MTHFR, ApoE and ApoA4 genes with the treatment response in MDD subjects. Methods A total of 281 Han Chinese MDD patients received a single antidepressant drug (SSRI or SNRI) for at least 6 weeks, among whom 275 were followed up for 8 weeks. Their response to 6 weeks’ treatment and remission to 8 weeks’ treatment with antidepressant drugs was determined by changes in the 17-item Hamilton Depression Rating Scale (HARS-17) score. Single SNP and haplotype associations with treatment response were analyzed by UNPHASED 3.0.13. Logistic regression analysis was used to explore the interactions between genotypes and gender or drug type on treatment outcome, only those SNPs that had interactional association with gender or drug type were subjected to further stratified analysis. Results In total group, the haplotype (C-A) in MTHFR (rsl801133 and rs1801131) and the ApoE rs405509 AA genotype were significantly associated with better efficacy of antidepressants; In gender subgroups, only haplotype (C-A) in MTHFR (rsl801133 and rs1801131) was significantly associated with better efficacy of antidepressants in male subgroup; In drug type subgroup, the haplotype (C-A) in MTHFR (rsl801133 and rs1801131) and haplotype (G-C) in ApoE (rs7412 and rs405509) were associated with better efficacy of antidepressants in SNRI treated subgroup; The ApoA4 rs5092 G allele and GG genotype were associated with worse efficacy of antidepressants in SNRI treated subgroup. Conclusions Genetic polymorphisms in homocysteine and lipid metabolism systems are associated with antidepressant response, particularly for the interactions of the certain genetic with gender or drug type.

Abstract Background With the development of wearable health-monitoring technologies, a variety of textile electrodes have been produced and applied by researchers. However, there are no universal and effective methods even testing platforms for evaluating the skin–electrode electrochemical interface for textile electrodes because different human bodies have different skin characteristics. Methods An electrochemical modeling and evaluation for textile electrodes to skin was proposed, and two electrochemical evaluation platforms (EEP) were set up based on two simulated skin models (SSM). First, skin–electrode electrochemical interface (SEEI) models for traditional wet electrodes and textile electrodes were analyzed. Based on the SEEI models and YY/T 0196-2005 (Chinese YY/T pharmaceutical industry standard for disposable ECG electrode), three skin–electrode electrochemical characteristics (SEEC), including skin–electrode static impedance (SESI), skin–electrode alternating current impedance (SEAI), and skin–electrode polarization voltage (SEPV), were proposed. Then, three electrochemical evaluation methods for textile electrodes to skin were proposed and analyzed, which were the correlation between SEEC and skin–electrode contact pressure (SECP), skin–electrode relative movement (SERM), and conduction loss of active signals (CLAS). Finally, an electrochemical evaluation platform was set up based on an active simulated skin model (ASSM) and passive simulated skin model (PSSM). Results 9 feature parameters based on the passive electrochemical evaluation platform (PEEP) and 11 feature parameters based on the active electrochemical evaluation platform (AEEP) were obtained for evaluating textile electrodes. And four kinds of textile electrode characteristics including SEEC, SECP, SERM, and CLAS were quantitatively measured based on the electrochemical evaluation platform, and the testing accuracy and range for these characteristics were measured separately. Finally, correlation between SEEC and SECP for 10 kinds of textile electrode samples was studied, and 14 electrochemical characteristics and four skin–electrode contact pressure characteristics were extracted. Experimental results showed that significant correlations were found between six SEEC characteristics and SECP characteristics, and the correlation coefficient between ACI_3 and USECP was the highest. And the polarization voltages of most dry electrode samples showed a downward trend with the increase of contact pressure. Conclusions The electrochemical evaluation platform yielded effective experimental data and could provide strong support for the evaluation and application of textile electrodes, which was also effective in evaluating other bioelectric electrodes such as 3M electrode, stainless steel electrode, dry electrode and microneedle electrode.

Controlling topological polar vortices promises to open up new applications for ferroelectric materials. Here, the authors proposed a method to mechanically manipulate polar vortices and monitored the transition between vortex and ferroelectric phase by in-situ scanning transmission electron microscopy.

Abstract Background Osteonecrosis of the femoral head (ONFH) is a common disease that greatly affects the quality of life of patients. Repair of the necrotic area is key to successful treatment. Currently, the combination of stem cell transplantation and decompression is used clinically to promote the repair of necrotic areas based on the characteristics of stem cells. However, a considerable number of patients do not achieve a satisfactory outcome in terms of repair of the femoral head necrotic area, and it is very important to determine the reasons for the poor curative effect. The aim of this study was to investigate the correlation between stem cell viability and the repair efficacy of stem cell therapy combined with core decompression for early-stage ONFH. Methods A total of 30 patients with idiopathic ONFH underwent core decompression combined with autologous stem cell transplantation. The Harris hip score (HHS) and difference in necrosis area before and after surgery were measured. The mean repair ratio was set as the threshold to divide the patients into group A (ratio above the mean) and group B (ratio below the mean). The ultrastructure, proliferative capacity, and multidirectional differentiation ability were compared between the groups. Results At 9 months after surgery, the HHS and magnetic resonance imaging (MRI) findings improved by varying degrees. Based on the mean repair ratio of (62.2 ± 27.0)%, the threshold for dividing the patients into groups A and B was set to 62.2%. Better repair (group A) was associated with more rapid proliferation and a healthier ultrastructure. The cells in group A showed stronger specific staining signifying osteogenic and chondrogenic differentiation; alkaline phosphatase (ALP) activity, an indicator of osteogenic differentiation, was higher in group A than in group B (OD, 2.39 ± 0.44 and 1.85 ± 0.52; p

It is very challenging to detect traffic signs using a high-precision real-time approach in realistic scenes with respect to driver-assistance systems for driving vehicles and autonomous driving. To address this challenge, in this paper, a new detection scheme (named MSA_YOLOv3) is proposed to accurately achieve real-time localization and classification of small traffic signs. First, data augmentation is achieved using image mixup technology. Second, a multi-scale spatial pyramid pooling block is introduced into the Darknet53 network to enable the network to learn object features more comprehensively. Finally, a bottom-up augmented path is designed to enhance the feature pyramid in YOLOv3, and the result is to achieve accurate localization of objects by utilizing fine-grained features effectively in the lower layers. According to the tests on the TT100K dataset (which is a dataset for traffic sign detection), the performance of the proposed MSA_YOLOv3 is better than that of YOLOv3 in detecting small traffic signs. The detection speed of MSA_YOLOv3 is 23.81 FPS, and the mAP (mean Average Precision) reaches up to 86%.

Multitask sparse representation method improves the detection performance by constructing multiple associated sub-sparse representation tasks and jointly learning multiple sub-sparse representation tasks, and this method can make use of the spectral information. However, the using of spatial information needs to be improved. This paper designs a hyperspectral image target detection method which can both make use of spectral and spatial information, that is a weighted joint k-nearest neighbor and multitask learning sparse representation method (WJNN-MTL-SR) is proposed. This method mainly consists of the following steps:1) using multitask sparse representation to obtain the representation residuals. 2) weighted joint k-nearest neighbor is used into the joint region of test pixels to obtain the weighted joint Euclidean distance. 3) a decision function, combining the weighted joint Euclidean distance and residuals of the multitask sparse representation, is used to get target detection result. Experimental results demonstrate that the proposed method show better detection performance than state-of-the-art methods.

In hyperspectral image (HSI) classification, the performance of supervised learning tends to be affected by priori knowledge, i.e., quantity and quality of samples. However, it is inevitable to limit the performance of supervised classification due to the presence of noisy labels in the training samples. In this article, we first propose a hierarchical constrained energy minimum (HCEM) method to detect mislabeled samples (noisy labels) of original training set trained with supervised task and boost the performance of classifiers and spectral-spatial classification methods in HSI applications. The basic idea behind this work is that the filter output energy of noisy label spectrum is hierarchically suppressed based on the cascade of CEM detectors at different layers. The proposed HCEM method consists of four key steps: First, the distance information among samples is obtained to calculate the spectral similarity between samples per class in original training set. Then, the confidence spectra per class is constructed according to the maximum similarity domain. Next, the spectra of mislabeled samples is suppressed and the spectra of true samples is preserved by multilayers CEM detector. Finally, the noisy labels are detected and removed based on the output evaluated by the proposed HCEM method. Experimental results on four real hyperspectral datasets are verified by a series of spectral classifiers and spectral-spatial classification methods, it demonstrated that the proposed HCEM method, can accurately remove noisy labels of original training set and effectively improve the performance of supervised classification task.