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BackgroundThis study aims to prioritize genes potentially involved in multifactorial or causal relationships with gout.MethodsUsing the Summary Data-based Mendelian Randomization (SMR) approach, this research analyzed expression quantitative trait loci (eQTL) data from blood and renal tissues and genome-wide association study (GWAS) data related to gout. It sought to identify genetic loci potentially involved in gout. Heterogeneity testing was conducted with the HEIDI test, and results were adjusted for the False Discovery Rate (FDR). Blood cis-eQTL data were sourced from the eQTLGen Consortium’s summary-level data, and renal tissue data came from the V8 release of the GTEx eQTL summary data. Gout GWAS data was sourced from the FinnGen Documentation of the R10 release.ResultSMR analysis identified 14 gene probes in the eQTLGen blood summary-level data significantly associated with gout. The top five ranked genes are: ENSG00000169231 (labeled THBS3, PSMR = 4.16 × 10−13), ENSG00000231064 (labeled THBS3-AS1, PSMR = 1.88 × 10−8), ENSG00000163463 (labeled KRTCAP2, PSMR = 3.88 × 10−6), ENSG00000172977 (labeled KAT5, PSMR = 1.70 × 10−5), and ENSG00000161395 (labeled PGAP3, PSMR = 3.24 × 10−5). Notably, increased expression of KRTCAP2 and PGAP3 is associated with an increased risk of gout, whereas increased expression of THBS3, THBS3-AS1, and KAT5 is associated with a reduced gout risk. No significant gene associations with gout were observed in renal tissue, likely due to the limited sample size of kidney tissue.ConclusionOur findings have highlighted several genes potentially involved in the pathogenesis of gout. These results offer valuable insights into the mechanisms of gout and identify potential therapeutic targets for its treatment.

IntroductionHemorrhagic transformation (HT) is a serious complication that can occur spontaneously after an acute ischemic stroke (AIS) or after a thrombolytic/mechanical thrombectomy. Our study aims to explore the potential correlations between fibrinogen levels and the occurrence of spontaneous HT (sHT) and HT after mechanical thrombectomy (tHT).MethodsA total of 423 consecutive AIS patients diagnosed HT who did not undergone thrombolysis and 423 age- and sex-matched patients without HT (non-HT) were enrolled. Fibrinogen levels were measured within 24 h of admission after stroke. The cohorts were trisected according to fibrinogen levels. The HT were further categorized into hemorrhagic infarction (HI) or parenchymal hematoma (PH) based on their imaging characteristics.ResultsIn sHT cohort, fibrinogen levels were higher in HT patients than non-HT patients (p

BackgroundWhile some studies have suggested a link between gut microbiota (GM) and abortion, the causal relationship remains unclear.MethodsTo explore the causal relationship between GM and abortion, including spontaneous abortion (SA) and habitual abortion (HA), we performed a two-sample Mendelian randomization (MR) analysis. We used summary statistics data from MiBioGen and FinnGen for genome-wide association studies (GWAS), with GM data as the exposure variable and abortion data as the outcome variable.ResultsIn the absence of heterogeneity and horizontal pleiotropy, the inverse-variance weighted (IVW) method identified five genetically predicted GM genera linked to the risk of abortions. Lactococcus was negatively correlated with the risk of SA, whereas the Eubacterium fissicatena group was positively correlated with the risk of SA. Genetic predictions of Coprococcus3 and Odoribacter were linked to a reduced risk of HA, while the Eubacterium ruminantium group was associated with an increased risk of HA.ConclusionOur study suggests a genetic causal relationship between specific GM and two types of abortions, improving our understanding of the pathological relationship between GM and abortion.

Objective1. To assess the Inter-rater reliability and test-retest reliability of FPI-6 total score and individual scores in static foot posture evaluation among elderly female patients with knee osteoarthritis (KOA), aiming to establish the reliability of the FPI-6 scale. 2. To investigate the disparity between dominant and non-dominant quadriceps characteristics in elderly female KOA patients, as well as explore the correlation between quadriceps characteristics and abnormal foot posture, thereby offering novel insights for the prevention and treatment of KOA.MethodsThe study enrolled a total of 80 lower legs of 40 participants (all female) with unilateral or bilateral KOA, who were assessed by two raters at three different time points. The inter-rater and test-retest reliability of the FPI-6 was evaluated using the intra-class correlation coefficient (ICC), while the absolute reliability of FPI-6 was examined using the standard error of measurement (SEM), minimum detectable change (MDC), and Bland-Altman analysis. The internal consistency of FPI-6 was assessed using Spearman’s correlation coefficient. Additionally, MyotonPRO was employed to assess quadriceps muscle tone and stiffness in all participants, and the association between quadriceps muscle tone/stiffness and the total score of FPI-6 was analyzed.ResultOur study found excellent inter-rater and test-retest reliability (ICC values of 0.923 and 0.931, respectively) for the FPI-6 total score, as well as good to excellent reliability (ICC values ranging from 0.680 to 0.863 and 0.739–0.883) for individual items. The SEM and MDC values for the total score of FPI-6 among our study inter-rater were 0.78 and 2.15, respectively. and the SEM and MDC values for the test-retest total score of FPI-6 were found to be 0.76 and 2.11, respectively. Furthermore, the SEM and MDC values between inter-rater and test-retest across six individual items ranged from 0.30 to 0.56 and from 0.84 to 1.56. The Bland-Altman plots and respective 95% LOA showed no evidence of systematic bias. In terms of the mechanical properties of the quadriceps on both sides, the muscle tone and stiffness of rectus femoris (RF), vastus medialis (VM), and vastus lateralis (VL) were significantly higher in the non-dominant leg compared to the dominant leg. Additionally, in the non-dominant leg, there was a significant positive correlation between the muscle tone and stiffness of VM, VL, RF and the total score of FPI-6. However, in the dominant leg, only VM’s muscle tone and stiffness showed a significant positive correlation with the total score of FPI-6.ConclusionThe reliability of the FPI-6 total score and its six individual items was good to excellent. Our findings offer a straightforward and dependable approach for researchers to assess foot posture in elderly female patients with KOA. Furthermore, we observed significantly greater quadriceps tension and stiffness in the non-dominant leg compared to the dominant leg. The FPI-6 total score exhibited a significant correlation with changes in quadriceps muscle performance among KOA patients. These observations regarding the relationship between changes in quadriceps muscle performance and foot posture in elderly female KOA patients may provide novel insights for disease prevention, treatment, and rehabilitation.

BackgroundGut microbiome (GM) and type 2 diabetes mellitus (T2DM) have two-way effects. Improving T2DM by modulating GM in various ways, such as diet, exercise, and medication, is gradually becoming popular, and related studies have yielded positive results. However, there is still a lack of high-quality bibliometric analyses of research in this area. This study aims to systematize and comprehensively summarize the knowledge structure, research tropics, and research trends of GM and T2DM through bibliometric analysis.MethodsPublications related to GM and T2DM before January 9, 2024, in the Web of Science Core Collection (WOSCC) were searched in this study. Microsoft Excel 2019 was used to analyze publishing trends and CiteSpace (v.6.1.R6 Advanced) was used to analyze institutions, cited journals, references, and keywords.SCImago Graphica (v.1.0.39) was used to analyze countries/regions, institutions’ collaborations, cited authors, and published journals.ResultsWe finally included 1004 articles published from 2008 to 2023. The number of published articles showed an upward trend and reached its peak in 2022. China is the country with the largest number of articles, Univ Copenhagen is the institution with the largest number of articles, Fukui, Michiaki, Hamaguchi, Masahide are the scholars with the largest number of articles, and Cani and Patrice D. are the scholars with the largest number of citations. NUTRIENTS(Q1/5.9) published the most publications, while Nature (Q1/64.8; Cited 804 times) is the most frequently cited journal. Gut microbiota, Obesity, and insulin resistance are the most frequently used keywords. This study found that current researches focus on the effects of diet, exercise, and pharmacological modification of GM to improve T2DM and explores specific mechanisms. Future researches will focus on three areas: complications of T2DM and specific physiological processes, methods and measures to regulate GM, and new experimental techniques and assays.ConclusionThe current researches confirmed the effects and specific mechanisms of modulating GM to improve T2DM. Further exploration of the effects of modulating GM on T2DM complications and specific physiologic processes is a future trend of research. Exploring specific methods for regulating GM and developing new experimental techniques and assays are important for future research.

Land cover classification is of great value and can be widely used in many fields. Earlier land cover classification methods used traditional image segmentation techniques, which cannot fully and comprehensively extract the ground information in remote sensing images. Therefore, it is necessary to integrate the advanced techniques of deep learning into the study of semantic segmentation of remote sensing images. However, most of current high-resolution image segmentation networks have disadvantages such as large parameters and high network training cost. In view of the problems above, a lightweight land cover classification model via semantic segmentation, DeepGDLE, is proposed in this paper. The model DeepGDLE is designed on the basis of DeeplabV3+ network and utilizes the GhostNet network instead of the backbone feature extraction network in the encoder. Using Depthwise Separable Convolution (DSC) instead of dilation convolution. This reduces the number of parameters and increases the computational speed of the model. By optimizing the dilation rate of parallel convolution in the ASPP module, the “grid effect” is avoided. ECANet lightweight channel attention mechanism is added after the feature extraction module and the pyramid pooling module to focus on the important weights of the model. Finally, the loss function Focal Loss is utilized to solve the problem of category imbalance in the dataset. As a result, the model DeepGDLE effectively reduces the parameters of the network model and the network training cost. And extensive experiments compared with several existing semantic segmentation algorithms such as DeeplabV3+, UNet, SegNet, etc. show that DeepGDLE improves the quality and efficiency of image segmentation. Therefore, compared to other networks, the DeepGDLE network model can be more effectively applied to land cover classification. In addition, in order to investigate the effects of different factors on the semantic segmentation performance of remote sensing images and to verify the robustness of the DeepGDLE model, a new remote sensing image dataset, FRSID, is constructed in this paper. This dataset takes into account more influences than the public dataset. The experimental results show that on the WHDLD dataset, the experimental metrics mIoU, mPA, and mRecall of the proposed model, DeepGDLE, are 62.29%, 72.85%, and 72.46%, respectively. On the FRSID dataset, the metrics mIoU, mPA, and mRecall are 65.89%, 74.43%, and 74.08%, respectively. For the future scope of research in this field, it may focus on the fusion of multi-source remote sensing data and the intelligent interpretation of remote sensing images.

Taking the Mongolian Plateau as the research area, this paper studied the vegetation growth from 2001 to 2018. We quantified the vegetation growth changes based on changes in gross primary productivity (GPP) and leaf area index (LAI) and their relationships to climate variables using correlation analysis, partial correlation analysis and multiple correlation analysis. The results showed that from 2001 to 2018 both GPP and LAI showed an increasing trend, with great heterogeneities among different areas and land cover types. The largest increase of GPP and LAI occurred in the northeast plateau with the land cover types of forest and cropland. The main driving factor of vegetation growth was precipitation, while temperature was significantly negatively correlated with vegetation growth. The CO2 concentration had a significant impact on the GPP in farmland, and the increase of solar radiation had a significant impact on tundra. Our study highlights the importance of precipitation in regulating vegetation growth in the Mongolian Plateau, challenging the prevailing views that the temperature dominates the vegetation growth in the northern ecosystems.

Robotics have advanced significantly over the years, and human–robot interaction (HRI) is now playing an important role in delivering the best user experience, cutting down on laborious tasks, and raising public acceptance of robots. New HRI approaches are necessary to promote the evolution of robots, with a more natural and flexible interaction manner clearly the most crucial. As a newly emerging approach to HRI, multimodal HRI is a method for individuals to communicate with a robot using various modalities, including voice, image, text, eye movement, and touch, as well as bio-signals like EEG and ECG. It is a broad field closely related to cognitive science, ergonomics, multimedia technology, and virtual reality, with numerous applications springing up each year. However, little research has been done to summarize the current development and future trend of HRI. To this end, this paper systematically reviews the state of the art of multimodal HRI on its applications by summing up the latest research articles relevant to this field. Moreover, the research development in terms of the input signal and the output signal is also covered in this manuscript.

BackgroundAggressive thyroid carcinoma (ATC) usually loses radioiodine avidity to iodine-131 (131I) due to the downregulation of sodium/iodide symporter (NIS). The expression of thyroid stimulating hormone receptor (TSHR) is more persistent than NIS and the administration of recombinant human thyroid stimulating hormone (rhTSH) promotes de novo NIS synthesis. Hence, exploring methods integrating 131I with rhTSH might be a feasible therapeutic strategy for selective delivery of 131I into thyroid cancer to fortify the effect of radioiodine ablation.MethodsThe 131I, poly (lactic-co-glycolic acid) (PLGA) and rhTSH were used to synthesize of the 131I-PLGA-rhTSH nanoparticles. The characteristics of the 131I-PLGA-rhTSH nanoparticles was determined using a light microscopy, scanning electron microscopy (SEM), autoradiography and immunofluorescence (IF) staining. The diameter of the 131I-PLGA-rhTSH nanoparticles was measured with a Mastersizer 3000, and the encapsulation efficiency (EF) of 131I in 131I-PLGA-rhTSH nanoparticles and the radioactivity of a single nanoparticle were determined. Then, the mouse tumor xenograft model was established, and the biodistribution and effect of 131I-PLGA-rhTSH nanoparticles on apoptosis of thyroid cance cells were investigated in vivo. Thereafter, the role of 131I-PLGA-rhTSH nanoparticles in cell viability using cell counting kit-8 and lactate dehydrogenase (LDH) release assays. Subsequently, the underlying mechanism of 131I-PLGA-rhTSH nanoparticles in reducing cell viability was assessed using immunostaining, boyden invasion assays and phalloidin staining.ResultsOur results showed that the method of developing nanoparticles-encapsulated 131I using poly (lactic-co-glycolic acid) (PLGA) and modified with rhTSH (131I-PLGA-rhTSH), was a feasible avenue for the integration of 131I and rhTSH. Meanwhile, the encapsulation efficiency (EF) of 131I-PLGA-rhTSH nanoparticles was approximately 60%, and the radioactivity of a single nanoparticle was about 1.1×10-2 Bq. Meanwhile, the 131I-PLGA-rhTSH nanoparticles were selectively delivered into, gradually enriched and slowly downregulated in xenograft tumor after the administration of 131I-PLGA-rhTSH nanoparticles through tail vein in mouse tumor xenograft model. Thereafter, the tumor weight was significantly reduced after the administration of 131I-PLGA-rhTSH nanoparticles. Subsequently, the application of 131I-PLGA-rhTSH nanoparticles facilitated apoptosis and attenuated immobilization via inhibiting F-actin assembling of FTC-133 cells.ConclusionThe present study develops a suitable approach integrating 131I and rhTSH, and this strategy is a feasible regimen enhancing the effect of radioiodine ablation for the treatment of thyroid cancer.

Rapid, sensitive and visual detection of plant viruses is conducive to effective prevention and control of plant viral diseases. Therefore, combined with reverse transcription and recombinase-aided amplification, we developed a CRISPR/Cas12a-based visual nucleic acid detection system targeting sorghum mosaic virus and rice stripe mosaic virus, which cause harm to crop production in field. When the RT-RAA products were recognized by crRNA and formed a complex with LbCas12a, the ssDNA labeled with a quenched green fluorescent molecule will be cleaved by LbCas12a, and then a significant green fluorescence signal will appear. The entire detection process can be completed within 30 min without using any sophisticated equipment and instruments. The detection system could detect samples at a dilution of 107, about 104-fold improvement over RT-PCR, so the system was successfully to detect rice stripe mosaic virus in a single leafhopper, which is the transmission vector of the virus. Finally, the CRISPR/Cas12a-based detection system was utilized to on-site detect the two viruses in the field, and the results were fully consistent with that we obtained by RT-PCR in laboratory, demonstrating that it has the application prospect of detecting important crop viruses in the field.

A single sand body is defined as a geological unit that is continuous vertically and horizontally but separated from the upper and lower sand bodies by mudstone or impermeable intercalation. The architecture of a single sand body is significant in the determination of hydrocarbon accumulation mechanisms in gas reservoirs, especially for exploitation of multiple tight sandstone gas (TSG) reservoirs. One such example is the gas reservoirs in the Tianhuan Depression, China, where the architecture and genesis of sand bodies are poorly understood. Based on the geologic background and sedimentary characteristics, the evolution of the distributary channel in the Tianhuan Depression has been examined using data from geological outcrops, cores, and well logs. The results showed that sand body architecture depends on the evolution of channel systems, and the scale and size of the channel are controlled by the sedimentary environment. Three kinds of sedimentary microfacies (distributary channel, channel mouth bar, and interdistributary bay) are mainly developed in the study area, and four types of single sand body stacking patterns (isolated, vertically superimposed, laterally tangentially superimposed, and horizontally bridged sand bodies) have formed in such a depositional environment. The target strata (Shan-1 and He-8 members) provide an ideal object for studying the evolution of the river and the architecture of the sand bodies. During the early stage of deposition, the sediment supply was insufficient, with restricted meandering river deltas dominating and sand bodies mostly existing as isolated types. Until the middle period of deposition, the sediment supply suddenly increased, the sedimentation rate accelerated with the decrease in the lake water base level, and the channel evolved into a large-scale braided river delta, generally forming superimposed sand bodies. By the late period of deposition, the provenance supply was reduced again; although braided river delta deposits were still dominant, the channel scale was restricted, and the sand bodies were predominantly isolated and horizontally bridged types. This work establishes a sedimentary evolution model for tight sandstone gas reservoirs, that is, a complete cycle of river evolution from small scale to large scale to terminal weakening, and discusses the genetic mechanism of single sand body architecture in such a depositional model.

The outbreak of the novel coronavirus disease 2019 (COVID-19) has had an unprecedented impact worldwide, and it is of great significance to predict the prognosis of patients for guiding clinical management. This study aimed to construct a nomogram to predict the prognosis of COVID-19 patients. Clinical records and laboratory results were retrospectively reviewed for 331 patients with laboratory-confirmed COVID-19 from Huangshi Hospital of Traditional Chinese Medicine (TCM) (Infectious Disease Hospital) and Third Affiliated Hospital of Sun Yat-sen University. All COVID-19 patients were followed up for 80 days, and the primary outcome was defined as patient death. Cases were randomly divided into training (n=199) and validation (n=132) groups. Based on baseline data, we used statistically significant prognostic factors to construct a nomogram and assessed its performance. The patients were divided into Death (n=23) and Survival (n=308) groups. Analysis of clinical characteristics showed that these patients presented with fever (n=271, 81.9%), diarrhea (n=20, 6.0%) and had comorbidities (n=89, 26.9.0%). Multivariate Cox regression analysis showed that age, UREA and LDH were independent risk factors for predicting 80-day survival of COVID-19 patients. We constructed a qualitative nomogram with high C-indexes (0.933 and 0.894 in the training and validation groups, respectively). The calibration curve for 80-day survival showed optimal agreement between the predicted and actual outcomes. Decision curve analysis revealed the high clinical net benefit of the nomogram. Overall, our nomogram could effectively predict the 80-day survival of COVID-19 patients and hence assist in providing optimal treatment and decreasing mortality rates.

Diabetic nephropathy (DN) is a chronic, inflammatory disease affecting millions of diabetic patients worldwide. DN is associated with proteinuria and progressive slowing of glomerular filtration, which often leads to end-stage kidney diseases. Due to the complexity of this metabolic disorder and lack of clarity about its pathogenesis, it is often more difficult to diagnose and treat than other kidney diseases. Recent studies have highlighted that the immune system can inadvertently contribute to DN pathogenesis. Cells involved in innate and adaptive immune responses can target the kidney due to increased expression of immune-related localization factors. Immune cells then activate a pro-inflammatory response involving the release of autocrine and paracrine factors, which further amplify inflammation and damage the kidney. Consequently, strategies to treat DN by targeting the immune responses are currently under study. In light of the steady rise in DN incidence, this timely review summarizes the latest findings about the role of the immune system in the pathogenesis of DN and discusses promising preclinical and clinical therapies.

BackgroundPoor sleep quality and vitamin D deficiency are common in stroke patients. Our aim was to evaluate the possible association between vitamin D and sleep quality in acute ischemic stroke (AIS) patients.MethodsA total of 301 AIS patients were screened and completed 1-month follow-up. Serum 25-hydroxyvitamin D [25(OH)D] was used to assess the vitamin D status by a competitive protein-binding assay at baseline. All patients were divided into equal quartile according to the distribution of 25(OH)D. One month after stroke, sleep quality was evaluated by using Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) questionnaire; depression status was confirmed by 17-item Hamilton Depression Scale (HAMD).ResultsThere were 89 (29.6%) AIS patients with poor sleep quality 1-month post-event. Within 24 h after admission, serum 25(OH)D levels were significantly lower in patients with poor sleep quality after stroke (P < 0.001). In the results of multivariate-adjusted logistic regression analysis, the odds ratio (OR) of poor sleep quality was 6.199 (95% CI, 2.066–18.600) for the lowest quartile of 25(OH)D compared with the highest quartile. In patients without depression, reduced 25(OH)D were still significantly associated with poor sleep quality (OR = 8.174, 95% CI = 2.432–27.473). Furthermore, 25(OH)D and HAMD score were combined to enhance the diagnostic accuracy of poor sleep quality, with the area under the receiver operating characteristic curve of 0.775.ConclusionReduced serum levels of vitamin D at admission were independently and significantly associated with poor sleep quality at 1 month after stroke. Our findings suggested the combination of vitamin D and depression status could provide important predictive information for post-stroke sleep quality.

Numerous studies have shown that plant shading can promote the quality of green tea. However, the association of shading with metabolic regulation in tea leaves and roots remains unelucidated. Here, the metabolic profiling of two tea cultivars (“Xiangfeicui” and “Jinxuan”) in response to shading and relighting periods during the summer season was performed using non-targeted metabolomics methods. The metabolic pathway analyses revealed that long-term shading remarkably inhibit the sugar metabolism such as glycolysis, galactose metabolism, and pentose phosphate pathway in the leaves and roots of “Xiangfeicui,” and “Jinxuan” were more sensitive to light recovery changes. The lipid metabolism in the leaves and roots of “Xiangfeicui” was promoted by short-term shading, while it was inhibited by long-term shading. In addition, the intensity of the flavonoid metabolites in the leaves and roots of “Jinxuan” were upregulated with a trend of rising first and then decreasing under shading, and five flavonoid synthesis genes showed the same trend (F3H, F3′5′H, DFR, ANS, and ANR). Simultaneously, the amino acids of the nitrogen metabolism in the leaves and roots of the two cultivars were significantly promoted by long-term shading, while the purine and caffeine metabolism was inhibited in the leaves of “Xiangfeicui.” Interestingly, CsGS1.1 and CsTSI, amino acid synthase genes was upregulated in the leaves and roots of two cultivars. These results indicated that shading could participate in carbon and nitrogen metabolic regulation of both leaf and root, and root metabolism could have a positive association with leaf metabolism to promote the shaded tea quality.

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic is having a dramatic impact on acute stroke care. Its effects may accompany stroke care for a long time. We compared the treatment, short-term and long-term functional outcomes of patients with AIS from 2019 to 2020. Our objective was to evaluate the effect of COVID-19 epidemic on mechanical thrombectomy (MT) in patients in our hospital.MethodsWe collected information on subjects treated with MT in 2019–2020, including age, sex, time from the onset to arterial sheath insertion, time from the onset to recanalization, the rate of lung infection and hemorrhagic transformation, modified Rankin scale (mRS), NHISS, and ASPECTS.ResultsThe number of patients with MT decreased significantly by 26.6% in 2020 (p = 0.025). The pretreatment ASPECTS score for 2020 was significantly higher than 2019 (p = 0.004). Besides, the patients were more likely to develop lung infection (65 vs. 54.1%, p = 0.042) and had a higher risk of hemorrhagic transformation (47.4% vs. 30.4%, p = 0.005) in 2019. The discharged mRS reflected the worse short-term functional prognosis of patients with MT in 2019 (66 vs. 44.9%, p = 0.046). In the subgroup analysis of bridging thrombolysis (BT), more patients with BT are expected to have a poor short-term functional prognosis in 2020, according to the discharged mRS (62.5 vs. 37.5%, p = 0.024). However, there was no difference in mRS at 180 days between the two groups (p = 0.094).ConclusionFor patients with MT, both short- and long-term functional outcomes were not significantly affected due to the mild condition of patients admitted to hospital in 2020. For patients with BT, the COVID-19 pandemic has prolonged the green channel time of stroke, leading to a poor short-term functional prognosis of patients with stroke in the pandemic period. There was no difference in the effectiveness of direct MT and BT during the COVID-19 pandemic.

A biomaterial-mediated immune response is a critical factor to determine the cell fate as well as the tissue-regenerative outcome. Although piezoelectric-membranes have attracted considerable interest in the field of guided bone regeneration thanks to their biomimetic electroactivity, the influence of their different surface-charge polarities on the immune-osteogenic microenvironment remains obscure. The present study aimed at investigating the interaction between piezoelectric poly (vinylidene fluoridetrifluoroethylene) [P (VDF-TrFE)] membranes with different surface polarities (negative or positive) and macrophage response, as well as their subsequent influence on osteogenesis from an immunomodulating perspective. Specifically, the morphology, wettability, crystal phase, piezoelectric performance, and surface potential of the synthetic P (VDF-TrFE) samples were systematically characterized. In addition, RAW 264.7 macrophages were seeded onto differently charged P (VDF-TrFE) surfaces, and the culture supernatants were used to supplement cultures of rat bone marrow mesenchymal stem cells (rBMSCs) on the corresponding P (VDF-TrFE) surfaces. Our results revealed that oppositely charged surfaces had different abilities in modulating the macrophage-immune-osteogenic microenvironment. Negatively charged P (VDF-TrFE), characterized by the highest macrophage elongation effect, induced a switch in the phenotype of macrophages from M0 (inactivated) to M2 (anti-inflammatory), thus promoting the osteogenic differentiation of rBMSCs by releasing anti-inflammatory cytokine IL-10. Interestingly, positively charged P (VDF-TrFE) possessed pro-inflammatory properties to induce an M1 (pro-inflammatory) macrophage-dominated reaction, without compromising the subsequent osteogenesis as expected. In conclusion, these findings highlighted the distinct modulatory effect of piezoelectric-P (VDF-TrFE) membranes on the macrophage phenotype, inflammatory reaction, and consequent immune-osteogenic microenvironment depending on their surface-charge polarity. This study provides significant insight into the design of effective immunoregulatory materials for the guided bone regeneration application.

Oral microecosystem is a very complicated ecosystem that is located in the mouth and comprises oral microbiome, diverse anatomic structures of oral cavity, saliva and interactions between oral microbiota and between oral microbiota and the host. More and more evidence from studies of epidemiology, microbiology and molecular biology is establishing a significant link between oral microecosystem and respiratory diseases. Microbiota settling down in oral microecosystem is known as the main source of lung microbiome and has been associated with the occurrence and development of respiratory diseases like pneumonia, chronic obstructive pulmonary disease, lung cancer, cystic fibrosis lung disease and asthma. In fact, it is not only indigenous oral microbes promote or directly cause respiratory infection and inflammation when inhaled into the lower respiratory tract, but also internal environment of oral microecosystem serves as a reservoir for opportunistic respiratory pathogens. Moreover, poor oral health and oral diseases caused by oral microecological dysbiosis (especially periodontal disease) are related with risk of multiple respiratory diseases. Here, we review the research status on the respiratory diseases related with oral microecosystem. Potential mechanisms on how respiratory pathogens colonize oral microecosystem and the role of indigenous oral microbes in pathogenesis of respiratory diseases are also summarized and analyzed. Given the importance of oral plaque control and oral health interventions in controlling or preventing respiratory infection and diseases, we also summarize the oral health management measures and attentions, not only for populations susceptible to respiratory infection like the elderly and hospitalized patients, but also for dentist or oral hygienists who undertake oral health care. In conclusion, the relationship between respiratory diseases and oral microecosystem has been established and supported by growing body of literature. However, etiological evidence on the role of oral microecosystem in the development of respiratory diseases is still insufficient. Further detailed studies focusing on specific mechanisms on how oral microecosystem participate in the pathogenesis of respiratory diseases could be helpful to prevent and treat respiratory diseases.

Camellia sinensis cv. ‘Yanlingyinbiancha’ is a leaf-variegated mutant with stable genetic traits. The current study aimed to reveal the differences between its albino and green tissues, and the molecular mechanism underlying the variegation. Anatomic analysis showed the chloroplasts of albino tissues to have no intact lamellar structure. Photosynthetic pigment in albino tissues was significantly lower than that in green tissues, whereas all catechin components were more abundant in the former. Transcriptome analysis revealed most differentially expressed genes involved in the biosynthesis of photosynthetic pigment, photosynthesis, and energy metabolism to be downregulated in albino tissues while most of those participating in flavonoid metabolism were upregulated. In addition, it was found cryptochrome 1 (CRY1) and phytochrome B (PHYB) genes that encode blue and red light photoreceptors to be downregulated. These photoreceptors mediate chloroplast protein gene expression, chloroplast protein import and photosynthetic pigment biosynthesis. Simultaneously, SUS gene, which was upregulated in albino tissues, encodes sucrose synthase considered a biochemical marker for sink strength. Collectively, we arrived to the following conclusions: (1) repression of the biosynthesis of photosynthetic pigment causes albinism; (2) destruction of photoreceptors in albino tissues suppresses photomorphogenesis, leading to abnormal chloroplast development; (3) albino tissues receive sucrose from the green tissues and decompose their own storage substances to obtain the energy needed for survival; and (4) UV-B signal and brassinosteroids promote flavonoid biosynthesis.

Background and Purpose: The results regarding the independent association between homocysteine (Hcy) levels and post-stroke cognitive impairment (PSCI) were inconsistent. The effect of age on this association has yet to be explored. This study aims to determine the relationship between Hcy levels, age, and cognitive impairment in a post-stroke population.Methods: A total of 592 patients with acute ischemic stroke (AIS) completed follow-up. Serum Hcy levels were measured enzymatically by spectrophotometry within 24 h of admission. Cognitive function was evaluated by the Mini-Mental State Examination (MMSE) 1 month after stroke, and the scores ≤ 24 were considered as cognitive impairment. Our study was dichotomized into two groups by a cut-off of 65 years. Multivariate logistic regression models were used to determine the association between baseline Hcy levels and cognitive impairment.Results: According to the MMSE score, 317 (53.5%) patients had cognitive impairment. Patients with higher levels of Hcy were more prone to have cognitive impairment 1 month after stroke than patients with lower levels of Hcy (p < 0.001). The optimal cut-off points of Hcy level (μmol/L) were (T1) ≤ 8, (T2) 8–12, and (T3) ≥ 12. After adjusting for confounding factors, the multivariate regression analysis showed that the third Hcy tertile was independently associated with cognitive impairment [odds ratio (OR) = 2.057, 95% confidence interval (CI) = 1.133–3.735, p = 0.018). A stronger association [T2 (OR = 2.266, 95% CI = 1.042–4.926, p = 0.039); T3 (OR =3.583, 95% CI = 1.456–8.818, p = 0.005)] was found in the younger group. However, the independent association was not confirmed in the older group.Conclusions: Elevated Hcy levels in the acute phase of ischemic stroke were independently associated with cognitive impairment in a post-stroke population. Furthermore, the association was age-dependent and more meaningful in a younger population aged below 65. So, Hcy levels in patients with stroke should be well-monitored, especially in younger patients.

Floating offshore wind turbines (FOWTs) still face many challenges on how to better predict the dynamic responses. Artificial intelligence (AI) brings a new solution to overcome these challenges with intelligent strategies. A new AI technology-based method, named SADA, is proposed in this paper for the prediction of dynamic responses of FOWTs. Firstly, the methodology of SADA is introduced with the selection of Key Disciplinary Parameters (KDPs). The AI module in SADA was built in a coupled aero-hydro-servo-elastic in-house program DARwind and the policy decision is provided by the machine learning algorithms deep deterministic policy gradient (DDPG). Secondly, a set of basin experimental results of a Hywind Spar-type FOWT were employed to train the AI module. SADA weights KDPs by DDPG algorithms' actor network and changes their values according to the training feedback of 6DOF motions of Hywind platform through comparing the DARwind simulation results and that of experimental data. Many other dynamic responses that cannot be measured in basin experiment could be predicted in higher accuracy with this intelligent DARwind. Finally, the case study of SADA method was conducted and the results demonstrated that the mean values of the platform's motions can be predicted by AI-based DARwind with higher accuracy, for example the maximum error of surge motion is reduced by 21%. This proposed SADA method takes advantage of numerical-experimental method and the machine learning method, which brings a new and promising solution for overcoming the handicap impeding direct use of traditional basin experimental technology in FOWTs design.

As one of the most promising fast energy storage devices, supercapacitor has been attracting intense attention for many emerging applications. However, how to enhance the electrochemical performance of electrode materials is still the main issue among various researches. In this paper, hierarchical porous carbons derived from Eleocharis dulcis has been prepared by chemical activation process with the aid of KOH at elevated temperature. Results show that the N, P co-doped porous carbon exhibits excellent electrochemical performance, it owns a specific capacitance of 340.2 F/g at 1 A/g, and obtains outstanding cycling stability of 96.9% of capacitance retention at 10 A/g after 5,000 cycles in a three-electrode system. Moreover, in the two-electrode system, the product still maintains a high specific capacitance of 227.2 F/g at 1 A/g, and achieves good electrochemical cycle stability (94.2% of capacitance retention at 10 A/g after 10,000 cycles); besides, its power/energy density are 3694.084 and 26.289 Wh/kg, respectively. Therefore, the combination of facile synthesis strategy and excellent electrochemical performance makes Eleocharis dulcis-based porous carbon as a promising electrode material for supercapacitor.

Redundant muscles in human-like musculoskeletal robots provide additional dimensions to the solution space. Consequently, the computation of muscle excitations remains an open question. Conventional methods like dynamic optimization and reinforcement learning usually have high computational costs or unstable learning processes when applied to a complex musculoskeletal system. Inspired by human learning, we propose a phased target learning framework that provides different targets to learners at varying levels, to guide their training process and to avoid local optima. By introducing an extra layer of neurons reflecting a preference, we improve the Q-network method to generate continuous excitations. In addition, based on information transmission in the human nervous system, two kinds of biological noise sources are introduced into our framework to enhance exploration over the solution space. Tracking experiments based on a simplified musculoskeletal arm model indicate that under guidance of phased targets, the proposed framework prevents divergence of excitations, thus stabilizing training. Moreover, the enhanced exploration of solutions results in smaller motion errors. The phased target learning framework can be expanded for general-purpose reinforcement learning, and it provides a preliminary interpretation for modeling the mechanisms of human motion learning.

A solid oxide fuel cell (SOFC) is regarded as the first choice of high-efficiency and clean power generation technology in the 21st century due to its characteristics of high power generation efficiency and low pollutant emission. In this paper, hydrogen is used as a fuel for SOFCs using the EBSILON platform. A sensitivity analysis of the solid oxide fuel cell–gas turbine (SOFC–GT) system with steam reinjection is carried out to investigate the effect of the steam reinjection mass flow rate on the improvement of the electrical efficiency of the system and on the values of the other parameters. The results show that the variation in the steam reinjection mass flow rate has an effect on other parameters. Changes in several parameters affect the electrical efficiency of the system, which reaches 74.11% at a pressure ratio of 10, SOFC inlet temperature of 783.15 K, turbine back pressure of 70 kPa, and steam reinjection mass flow rate of 6.16 kg/s. Future research can optimize the overall parameter selection of the system in terms of economy and other aspects.