The epigenetic-modified downregulation of LOXL1 protein mediates EMT in bladder epithelial cells exposed to benzo[a]pyrene and its metabolite BPDE.

Benzo[a]pyrene (B[a]P) is a well-known polycyclic aromatic hydrocarbon (PAH) pollutant with high carcinogenicity, widespread environmental presence, and significant threat to public health. Epidemiological studies have linked exposure to B[a]P and its metabolite 7,8-dihydroxy-9,10-epoxybenzo[a]pyrene (BPDE) to the development and progression of various cancers, including bladder cancer. However, its underlying mechanism remains unclear. Our study revealed that B[a]P and BPDE induced epithelial-mesenchymal transition (EMT), a critical early event in cell malignant transformation, involving a decrease in E-Cadherin and upregulation of N-Cadherin protein levels, leading to increased cell motility and migration in bladder epithelial cells. Further studies have indicated that LOXL1 DNA undergoes methylation and modification influenced by methyltransferase 3a (DNMT3a) and DNMT3b, resulting in decreased LOXL1 protein levels. The decreased LOXL1 promotes the zinc finger transcription factor SLUG, which then inhibits E-Cadherin protein levels and initiates the EMT process. Moreover, DNMT3a/3b expression appears to be influenced by intracellular oxidative stress levels. These findings suggest that exposure to B[a]P/BPDE promotes the EMT process through the pivotal factor LOXL1, thereby contributing to bladder carcinogenesis. Our study provides a theoretical basis for considering LOXL1 as a potential biomarker for early diagnosis and a novel target for the precise diagnosis and treatment of bladder cancer.

Blueshift or redshift? Effect of hydrogen bonding interactions on the C≡N stretching frequency of 5-cyanoindole.

The nitrile (C≡N) stretching vibration is widely used as a site-specific environmental probe of proteins and, as such, many computational studies have been used to investigate the factors that affect its frequency (νCN). These studies, most of which were carried out in the ground electronic state of the molecule of interest, revealed that the formation of a normal or linear hydrogen bond (H-bond) with the nitrile group results in a blueshift in its νCN. Recently, however, several experimental studies showed that for certain aromatic nitriles, solvent relaxations in their excited electronic state(s) induce a redshift (blueshift) in νCN in protic (aprotic) solvents, suggesting that the effect of hydrogen-bonding (H-bonding) interactions on νCN may depend on the electronic state of the molecule. To test this possibility, herein we combine molecular dynamics simulations and quantum mechanical calculations to assess the effect of H-bonding interactions on the νCN of 5-cyanoindole (5-CNI) in its different electronic states. We find that its C≡N group can form either one H-bond (single-H-bond) or two H-bonds (d-H-bonds) with the solvent molecules and that in the ground electronic state, a single-H-bond can lead νCN to shift either to a higher or lower frequency, depending on its angle, which is consistent with previous studies, whereas the d-H-bonds cause νCN to redshift. However, in its lowest-lying excited electronic state (i.e., S1), which has the characteristics of a charge-transfer state, all H-bonds induce a redshift in νCN, with the d-H-bonds being most effective in this regard.

Fluid-Dynamics-Rectified Chemical Vapor Deposition (CVD) Preparing Graphene-Skinned Glass Fiber Fabric and Its Application in Natural Energy Harvest.

Graphene chemical vapor deposition (CVD) growth directly on target using substrates presents a significant route toward graphene applications. However, the substrates are usually catalytic-inert and special-shaped; thus, large-scale, high-uniformity, and high-quality graphene growth is challenging. Herein, graphene-skinned glass fiber fabric (GGFF) was developed through graphene CVD growth on glass fiber fabric, a Widely used engineering material. A fluid dynamics rectification strategy was first proposed to synergistically regulate the distribution of carbon species in 3D space and their collisions with hierarchical-structured substrates, through which highly uniform deposition of high-quality graphene on fibers in large-scale 3D-woven fabric was realized. This strategy is universal and applicable to CVD systems using various carbon precursors. GGFF exhibits high electrical conductivity and photothermal conversion capability, based on which a natural energy harvester was first developed. It can harvest both solar and raindrop energy through solar heating and droplet-based electricity generating, presenting promising potentials to alleviate energy burdens.

Graphene-skinned alumina fiber fabricated through metalloid-catalytic graphene CVD growth on nonmetallic substrate and its mass production.

Graphene growth on widely used dielectrics/insulators via chemical vapor deposition (CVD) is a strategy toward transfer-free applications of CVD graphene for the realization of advanced composite materials. Here, we develop graphene-skinned alumina fibers/fabrics (GAFs/GAFFs) through graphene CVD growth on commercial alumina fibers/fabrics (AFs/AFFs). We reveal a vapor-surface-solid growth model on a non-metallic substrate, which is distinct from the well-established vapor-solid model on conventional non-catalytic non-metallic substrates, but bears a closer resemblance to that observed on catalytic metallic substrates. The metalloid-catalytic growth of graphene on AFs/AFFs resulted in reduced growth temperature (~200 °C lower) and accelerated growth rate (~3.4 times faster) compared to that obtained on a representative non-metallic counterpart, quartz fiber. The fabricated GAFF features a wide-range tunable electrical conductivity (1-15000 Ω sq-1), high tensile strength (>1.5 GPa), lightweight, flexibility, and a hierarchical macrostructure. These attributes are inherited from both graphene and AFF, making GAFF promising for various applications including electrical heating and electromagnetic interference shielding. Beyond laboratory level preparation, the stable mass production of large-scale GAFF has been achieved through a home-made roll-to-roll system with capacity of 468-93600 m2/year depending on product specifications, providing foundations for the subsequent industrialization of this material, enabling its widespread adoption in various industries.

Controllable preparation of graphene glass fiber fabric towards mass production and its application in self-adaptive thermal management.

Direct synthesis of graphene on nonmetallic substrates via chemical vapor deposition (CVD) has become a frontier research realm targeting transfer-free applications of CVD graphene. However, the stable mass production of graphene with a favorable growth rate and quality remains a grand challenge. Herein, graphene glass fiber fabric (GGFF) was successfully developed through the controllable growth of graphene on non-catalytic glass fiber fabric, employing a synergistic binary-precursor CVD strategy to alleviate the dilemma between growth rate and quality. The binary precursors consisted of acetylene and acetone, where acetylene with high decomposition efficiency fed rapid graphene growth while oxygen-containing acetone was adopted for improving the layer uniformity and quality. Notably, the bifurcating introducing-confluent premixing (BI-CP) system was self-built for the controllable introduction of gas and liquid precursors, enabling the stable production of GGFF. GGFF features solar absorption and infrared emission properties, based on which the self-adaptive dual-mode thermal management film was developed. This film can automatically switch between heating and cooling modes by spontaneously perceiving the temperature, achieving excellent thermal management performances with heating and cooling power of ∼501.2 and ∼108.6 W m-2, respectively. These findings unlock a new strategy for the large-scale batch production of graphene materials and inspire advanced possibilities for further applications.

Multispecies-coadsorption-induced rapid preparation of graphene glass fiber fabric and applications in flexible pressure sensor.

Direct chemical vapor deposition (CVD) growth of graphene on dielectric/insulating materials is a promising strategy for subsequent transfer-free applications of graphene. However, graphene growth on noncatalytic substrates is faced with thorny issues, especially the limited growth rate, which severely hinders mass production and practical applications. Herein, graphene glass fiber fabric (GGFF) is developed by graphene CVD growth on glass fiber fabric. Dichloromethane is applied as a carbon precursor to accelerate graphene growth, which has a low decomposition energy barrier, and more importantly, the produced high-electronegativity Cl radical can enhance adsorption of active carbon species by Cl-CH2 coadsorption and facilitate H detachment from graphene edges. Consequently, the growth rate is increased by ~3 orders of magnitude and carbon utilization by ~960-fold, compared with conventional methane precursor. The advantageous hierarchical conductive configuration of lightweight, flexible GGFF makes it an ultrasensitive pressure sensor for human motion and physiological monitoring, such as pulse and vocal signals.

Wutou decoction alleviates arthritis inflammation in CIA mice by regulating Treg cell stability and Treg/Th17 balance via the JAK2/STAT3 pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Wutou Decoction (WTD) is a classic traditional Chinese medicine formula, which has shown clinical efficacy in treating rheumatoid arthritis (RA). The Treg stability and Th17/Treg imbalance is an important immunological mechanism in RA progression. Whether WTD regulates CD4+ T cell subsets has not been thoroughly investigated yet. AIM OF THE STUDY: This study aimed to explore the potential role and mechanisms of WTD in regulating the diminished stability of Treg cells and the imbalance of CD4+ T cell subsets via in vivo and in vitro experiments. MATERIALS AND METHODS: Firstly, the therapeutic effects of WTD on the collagen-induced arthritis (CIA) mouse and its potential regulatory function on CD4+ T cell subsets were evaluated in vivo. Animal specimens were collected after 31 days of treatment with WTD. The anti-arthritic and anti-inflammatory effects of WTD were assessed through arthritis scoring, body weight, spleen index, serum IL-6 levels, and micro-PET/CT imaging. Gene enrichment analysis was performed to evaluate the activation T cell-related signaling pathway. Flow cytometry was used to determine the proportions of CD4+ T cell subsets in vitro and in vitro. Additionally, ELISA was used to assess the secretion of IL-10 and TGF-ß by Treg cells under inflammatory conditions. The suppressive function of Treg cells on cell proliferation under inflammatory conditions was examined using CFSE labeling. Immunofluorescence staining was performed to detect the phosphorylation levels of STAT3 in CD4+ T cells from mouse spleen tissues. Western blotting was used to evaluate the phosphorylation levels of JAK2/STAT3 in Treg cells. RESULTS: WTD significantly alleviated joint inflammation in CIA mice. WTD reduced serum IL-6 levels in CIA mice, improved their body weight and spleen index. WTD treatment inhibited the activation of CD4+ T cell subgroup-related signaling in the joint tissues of CIA mice. In vitro and in vitro experiments showed that WTD increased the proportion of Treg cells and decreased the proportion of Th17 cells in CIA mice spleen. Furthermore, WTD promoted the secretion of IL-10 and TGF-ß by Treg cells and enhanced the inhibitory capacity of Treg cells on cell proliferation under inflammatory conditions. Immunofluorescence detected decreased STAT3 phosphorylation levels in CD4+ T cells from CIA mice spleen, while western blotting revealed a decrease in JAK2/STAT3 phosphorylation levels in Treg cells in vitro. CONCLUSIONS: Inhibiting JAK2/STAT3 phosphorylation is a potential mechanism through which WTD improves Treg cell stability, balances CD4+ T cell subsets, and attenuates RA joint inflammation.

Diversity in Pyracantha fortuneana fruits maturity stages enables discrepancy in the phenolic compounds, antioxidant activity, and tyrosinase inhibitory activity.

Pyracantha fortuneana (P. fortuneana) fruit is a wild fruit that is popular because of its delicious taste and numerous nutrients, and phenolic compounds are considered to be the main bioactive components in P. fortuneana fruits. However, the relationship between phenolic compounds and their antioxidant and tyrosinase (TYR) inhibitory activities during the ripening process is still unclear. The study compared the influence of the five developmental stages on the accumulation of phenolic compounds, antioxidant activity, and TYR inhibitory activity in the fruits of P. fortuneana. The compounds were identified by offline two-dimensional liquid chromatography-electrochemical detection (2D-LC-ECD) combined with liquid chromatography-tandem mass spectrometry, and the main active ingredients were quantified. The results showed that stage II had higher total phenolic and flavonoid content, as well as higher antioxidant and TYR inhibitory activity, but the total anthocyanin content was lowest at this stage. A total of 30 compounds were identified by 2D-LC-ECD. Orthogonal partial least squares discriminant analysis screened out six major potential markers, including phenolic acids, procyanidins, and flavonoids. In addition, it was found that caffeoylquinic acids, procyanidins, and flavonoids were higher in stage II than in stages I, III, IV, and V, whereas anthocyanins accumulated gradually from stages III to V. Therefore, this study suggests that the changes in antioxidant and TYR inhibitory activities of P. fortuneana during the five developmental stages may be due to the transformation of procyanidins, caffeoylquinic acids, and phenolic glycosides into other forms during the fruit maturation process. Practical Application: Differences in chemical constituents, antioxidant, and tyrosinase inhibitory activities in fruit maturity stages of P. fortuneana were elucidated to provide reference for rational harvesting and utilization of the fruits and their bioactive components. These findings are expected to provide a comprehensive assessment of the bioactive profile and guide the food industrial production.

Enhancing Fetal Electrocardiogram Signal Extraction Accuracy through a CycleGAN Utilizing Combined CNN-BiLSTM Architecture.

The fetal electrocardiogram (FECG) records changes in the graph of fetal cardiac action potential during conduction, reflecting the developmental status of the fetus in utero and its physiological cardiac activity. Morphological alterations in the FECG can indicate intrauterine hypoxia, fetal distress, and neonatal asphyxia early on, enhancing maternal and fetal safety through prompt clinical intervention, thereby reducing neonatal morbidity and mortality. To reconstruct FECG signals with clear morphological information, this paper proposes a novel deep learning model, CBLS-CycleGAN. The model's generator combines spatial features extracted by the CNN with temporal features extracted by the BiLSTM network, thus ensuring that the reconstructed signals possess combined features with spatial and temporal dependencies. The model's discriminator utilizes PatchGAN, employing small segments of the signal as discriminative inputs to concentrate the training process on capturing signal details. Evaluating the model using two real FECG signal databases, namely "Abdominal and Direct Fetal ECG Database" and "Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeat Annotations", resulted in a mean MSE and MAE of 0.019 and 0.006, respectively. It detects the FQRS compound wave with a sensitivity, positive predictive value, and F1 of 99.51%, 99.57%, and 99.54%, respectively. This paper's model effectively preserves the morphological information of FECG signals, capturing not only the FQRS compound wave but also the fetal P-wave, T-wave, P-R interval, and ST segment information, providing clinicians with crucial diagnostic insights and a scientific foundation for developing rational treatment protocols.

Genomic analyses reveal the stepwise domestication and genetic mechanism of curd biogenesis in cauliflower.

Cauliflower (Brassica oleracea L. var. botrytis) is a distinctive vegetable that supplies a nutrient-rich edible inflorescence meristem for the human diet. However, the genomic bases of its selective breeding have not been studied extensively. Herein, we present a high-quality reference genome assembly C-8 (V2) and a comprehensive genomic variation map consisting of 971 diverse accessions of cauliflower and its relatives. Genomic selection analysis and deep-mined divergences were used to explore a stepwise domestication process for cauliflower that initially evolved from broccoli (Curd-emergence and Curd-improvement), revealing that three MADS-box genes, CAULIFLOWER1 (CAL1), CAL2 and FRUITFULL (FUL2), could have essential roles during curd formation. Genome-wide association studies identified nine loci significantly associated with morphological and biological characters and demonstrated that a zinc-finger protein (BOB06G135460) positively regulates stem height in cauliflower. This study offers valuable genomic resources for better understanding the genetic bases of curd biogenesis and florescent development in crops.

Overcoming the Incompatibility Between Electrical Conductivity and Electromagnetic Transmissivity: A Graphene Glass Fiber Fabric Design Strategy.

Conventional conductive materials such as metals are crucial functional components of conductive systems in diverse electronic instruments. However, their severe intrinsic impedance mismatch with air dielectric causes strong reflection of incident electromagnetic waves, and the resulting low electromagnetic transmissivity typically interferes with surrounding electromagnetic signal communications in modern multifunction-integrated instruments. Herein, graphene glass fiber fabric (GGFF) that merges intrinsic electrical and electromagnetic properties of graphene with dielectric attributes and highly porous macrostructure of glass fiber fabric (GFF) is innovatively developed. Using a novel decoupling chemical vapor deposition growth strategy, high-quality and layer-limited graphene is prepared on noncatalytic nonmetallic GFF in a controlled manner; this is pivotal to realizing GGFF with the desired compatibility among high conductivity, low electromagnetic reflectivity, and high electromagnetic transmissivity. At the same sheet resistance over a wide range of values (250-3000 Ω·sq-1), the GGFF exhibits significantly lower electromagnetic reflectivity (by 0.42-0.51) and higher transmissivity (by 0.27-0.62) than those of its metal-based conductive counterpart (CuGFF). The material design strategy reported herein provides a constructive solution to eliminate the incompatibility between electrical conductivity and electromagnetic transmissivity faced by conventional conductive materials, spotlighting the applicability of GGFF in electric heating scenarios in radar, antenna, and stealth systems.

Genome-wide identification of MAPK family in papaya (Carica papaya) and their involvement in fruit postharvest ripening.

BACKGROUND: Papaya (Carica papaya) is an economically important fruit cultivated in the tropical and subtropical regions of China. However, the rapid softening rate after postharvest leads to a short shelf-life and considerable economic losses. Accordingly, understanding the mechanisms underlying fruit postharvest softening will be a reasonable way to maintain fruit quality and extend its shelf-life. RESULTS: Mitogen-activated protein kinases (MAPKs) are conserved and play essential roles in response to biotic and abiotic stresses. However, the MAPK family remain poorly studied in papaya. Here, a total of nine putative CpMAPK members were identified within papaya genome, and a comprehensive genome-wide characterization of the CpMAPKs was performed, including evolutionary relationships, conserved domains, gene structures, chromosomal locations, cis-regulatory elements and expression profiles in response to phytohormone and antioxidant organic compound treatments during fruit postharvest ripening. Our findings showed that nearly all CpMAPKs harbored the conserved P-loop, C-loop and activation loop domains. Phylogenetic analysis showed that CpMAPK members could be categorized into four groups (A-D), with the members within the same groups displaying high similarity in protein domains and intron-exon organizations. Moreover, a number of cis-acting elements related to hormone signaling, circadian rhythm, or low-temperature stresses were identified in the promoters of CpMAPKs. Notably, gene expression profiles demonstrated that CpMAPKs exhibited various responses to 2-chloroethylphosphonic acid (ethephon), 1-methylcyclopropene (1-MCP) and the combined ascorbic acid (AsA) and chitosan (CTS) treatments during papaya postharvest ripening. Among them, both CpMAPK9 and CpMAPK20 displayed significant induction in papaya flesh by ethephon treatment, and were pronounced inhibition after AsA and CTS treatments at 16 d compared to those of natural ripening control, suggesting that they potentially involve in fruit postharvest ripening through ethylene signaling pathway or modulating cell wall metabolism. CONCLUSION: This study will provide some valuable insights into future functional characterization of CpMAPKs, and hold great potential for further understanding the molecular mechanisms underlying papaya fruit postharvest ripening.

Mechanisms of NLRP3 inflammasome in rheumatoid arthritis and osteoarthritis and the effects of traditional Chinese medicine.

ETHNOPHARMACOLOGICAL RELEVANCE: It has been widely reported that various anti-rheumatic traditional Chinese medicines (TCMs) ameliorate rheumatoid arthritis (RA) and osteoarthritis (OA) through regulating the abnormal production, assembly, and activation of the NOD-like receptor thermal protein domain-associated protein 3 (NLRP3) inflammasome. These TCMs include monomers isolated from Chinese herbs, extracts of Chinese herbs, and Chinese medical formulae with a lengthy application history. AIM OF THE STUDY: This review aimed to summarize and analyze the published articles about the NLRP3 inflammasome and its role in the pathogenesis of RA and OA. We also reviewed existing knowledge on the therapeutic mechanism of TCMs in RA and OA via the regulation of the NLRP3 inflammasome. MATERIALS AND METHODS: We searched for relevant articles with the keywords "NLRP3 inflammasome", "traditional Chinese medicine," "Chinese herbal drugs," "rheumatoid arthritis," and "osteoarthritis." The information retrieval was conducted in medical Chinese and English databases from the date of construction to April 19, 2023, including PubMed, MEDLINE, Web of Science, Scopus, Ovid, China National Knowledge Infrastructure (CNKI), Chinese Biomedicine Literature Database (CBM), Chinese Science and Technology Periodicals Database (VIP), and China Online Journals (COJ). RESULTS: According to retrieval results, 35 TCMs have been demonstrated to relieve RA by targeting the NLRP3 inflammasome, including six traditional Chinese prescriptions, seven extracts of Chinese herbs, and 22 monomers extracted from traditional Chinese herbs and formulae. Additionally, 23 TCMs have shown anti-OA effects with abilities to modulate the NLRP3 inflammasome, including five traditional Chinese prescriptions, one extract of Chinese herbs, and 17 monomers from Chinese herbs. CONCLUSIONS: We summarized mechanism research about the pivotal roles of the NLRP3 inflammasome in the pathogenesis of RA and OA. Moreover, a review of TCMs with targets of the NLRP3 inflammasome in RA and OA treatment was also conducted. Our work is conducive to a better application of TCMs in complementary and alternative therapies in RA and OA.

Association between nocturnal light exposure and melatonin in humans: a meta-analysis.

BACKGROUND: Night shift workers are more susceptible to circadian rhythm disturbances due to their prolonged exposure to nighttime light. This exposure during abnormal periods causes inappropriate suppression of melatonin synthesis and secretion in the pineal gland, thereby disrupting circadian rhythms. While it is believed that nocturnal light exposure is involved in suppressing melatonin secretion, research findings in this area have been inconsistent. METHODS: Thirteen publications retrieved from PubMed and Web of Science databases were included to compare the differences between night shift workers and controls using aggregated mean differences (MD) and 95% confidence intervals (CI). RESULTS: After a comprehensive review, 13 publications were included and data on urinary melatonin metabolite 6-sulfameoxymelatonin(aMT6s) were collected for meta-analysis. The results showed that the morning urinary aMT6s levels were significantly lower in the exposed group than in the non-exposed group (MD = -3.69, 95%CI = (-5.41, -1.98), P < 0.0001), with no significant heterogeneity among the original studies (I2 = 42%, P = 0.13). In addition, night shift workers had significantly lower mean levels of 24-h urinary aMT6s than day shift workers (MD = -3.38, 95%CI = (-4.27, -2.49), P < 0.00001, I2 = 0). Nocturnal light was correlated with nocturnal urine aMT6s secretion and inhibited nocturnal aMT6s secretion (MD = -11.68, 95%CI = (-15.70, -7.67), P < 0.00001, I2 = 0). Additionally, nocturnal light inhibited the secretion of melatonin in the blood, with no significant heterogeneity between studies (MD = -11.37, 95%CI = (-15.41, -7.33), P < 0.00001, I2 = 0). CONCLUSION: The findings of this study indicate that exposure to nocturnal light among night shift workers leads to inhibition of melatonin secretion.

Assessment of five typical environmental endocrine disruptors and thyroid cancer risk: a meta-analysis.

Introduction: There are conflicting reports on the association between environmental endocrine disruptors (EEDs) and thyroid cancer. This meta-analysis aimed to elucidate the relationship between EEDs and thyroid cancer. Methods: We searched for epidemiological studies on EEDs and thyroid cancer published in PubMed and Web of Science up to December 2022. We then screened the articles that could extract data on EEDs concentration levels in both thyroid cancer patients and healthy controls. We excluded articles that could not calculate effect sizes, focused on other thyroid diseases, or lacked controls. Standardized mean difference (SMD) was calculated to analyze the association between EEDs and thyroid cancer. We measured the heterogeneity among the included studies using I2, assessed publication bias by Egger's and Begg's test, and evaluated article quality using the Newcastle-Ottawa Quality Score (NOS). In the end, fifteen eligible case-control studies were included. Results: Our comprehensive analysis revealed that polychlorinated biphenyls (PCBs) were negatively associated with thyroid cancer{ SMD = -0.03, 95% confidence interval (CI) = (-0.05, -0.00), P = 0.03}, while polybrominated diphenyl ethers (PBDEs), phthalates (PAEs), and heavy metals were positively associated with thyroid cancer{PBDEs: SMD = 0.14, 95%CI = (0.04, 0.23), P = 0.007; PAEs: SMD = 0.30, 95%CI = (0.02, 0.58), P = 0.04; heavy metals: SMD = 0.21, 95%CI = (0.11, 0.32), P < 0.001}. We did not find a statistically significant relationship between bisphenol A (BPA) and thyroid cancer. Most of the included studies did not show publication bias, except for those on PCBs. Discussion: Our results indicate that exposure to certain EEDs, such as PBDEs, PAEs, and heavy metals, increases the risk of thyroid cancer. However, further large-scale epidemiological studies and mechanism studies are needed to verify these potential relationships and understand the underlying biological mechanisms.

Hierarchical power control of a large-scale wind farm by using a data-driven optimization method.

With the participation in automatic generation control (AGC), a large-scale wind farm should distribute the real-time AGC signal to numerous wind turbines (WTs). This easily leads to an expensive computation for a high-quality dispatch scheme, especially considering the wake effect among WTs. To address this problem, a hierarchical power control (HPC) is constructed based on the geographical layout and electrical connection of all the WTs. Firstly, the real-time AGC signal of the whole wind farm is distributed to multiple decoupled groups in proportion of their regulation capacities. Secondly, the AGC signal of each group is distributed to multiple WTs via the data-driven surrogate-assisted optimization, which can dramatically reduce the computation time with a small number of time-consuming objective evaluations. Besides, a high-quality dispatch scheme can be acquired by the efficient local search based on the dynamic surrogate. The effectiveness of the proposed technique is thoroughly verified with different AGC signals under different wind speeds and directions.

C≡N Stretching Frequency as a Convenient Reporter of Charge Separation in Molecular Systems.

Previously, several studies have shown that, for a set of structurally related nitrile compounds, there could be a linear relationship between the total charge on the nitrile group (qCN) and its stretching frequency (νCN). However, it is unclear whether the corresponding frequency and charge properties of structurally different nitrile compounds can be described by a single linear νCN-qCN relationship. Herein, we compute the qCN magnitudes of a large number of nitrile-containing molecules whose νCN values cover a spectral range of ca. 200 cm-1 and are measured under different experimental conditions. Our results reveal that νCN indeed exhibits a linear dependence on qCN, with a slope of 637 ± 30 cm-1/charge. Because the nitrile moiety is a commonly used building block in electronic donor-acceptor (D-A) molecular systems, we believe that this linear relationship will find utility in a wide range of applications where such D-A constructs are used, such as in organic photovoltaic assemblies. In addition, we apply this linear relationship to characterize the degree of charge transfer upon photoexcitation of two indole derivatives, 5-cyanoindole and 6-cyanoindole, and are able to show that in both cases, the fluorescence emission arises from a charge-transfer or La state.

Differential functions of RhoGDIß in malignant transformation and progression of urothelial cell following N-butyl-N-(4-hydmoxybutyl) nitrosamine exposure.

BACKGROUND: Functional role of Rho GDP-dissociation inhibitor beta (RhoGDIß) in tumor biology appears to be contradictory across various studies. Thus, the exploration of the molecular mechanisms underlying the differential functions of this protein in urinary bladder carcinogenesis is highly significant in the field. Here, RhoGDIß expression patterns, biological functions, and mechanisms leading to transformation and progression of human urothelial cells (UROtsa cells) were evaluated following varying lengths of exposure to the bladder carcinogen N-butyl-N-(4-hydmoxybutyl) nitrosamine (BBN). RESULTS: It was seen that compared to expression in vehicle-treated control cells, RhoGDIß protein expression was downregulated after 2-month of BBN exposure, but upregulated after 6-month of exposure. Assessments of cell function showed that RhoGDIß inhibited UROtsa cell growth in cells with BBN for 2-month exposure, whereas it promoted the invasion of cells treated with BBN for 6 months. Mechanistic studies revealed that 2-month of BBN exposure markedly attenuated DNMT3a abundance, and this led to reduced miR-219a promoter methylation, increased miR-219a binding to the RhoGDIß mRNA 3'UTR, and reduced RhoGDIß protein translation. While after 6-mo of BBN treatment, the cells showed increased PP2A/JNK/C-Jun axis phosphorylation and this in turn mediated overall RhoGDIß mRNA transcription and protein expression as well as invasion. CONCLUSIONS: These findings indicate that RhoGDIß is likely to inhibit the transformation of human urothelial cells during the early phase of BBN exposure, whereas it promotes invasion of the transformed/progressed urothelial cells in the late stage of BBN exposure. The studies also suggest that RhoGDIß may be a useful biomarker for evaluating the progression of human bladder cancers.

China's electric vehicle and climate ambitions jeopardized by surging critical material prices.

The adoption of electric vehicles (EVs) on a large scale is crucial for meeting the desired climate commitments, where affordability plays a vital role. However, the expected surge in prices of lithium, cobalt, nickel, and manganese, four critical materials in EV batteries, could hinder EV uptake. To explore these impacts in the context of China, the world's largest EV market, we expand and enrich an integrated assessment model. We find that under a high material cost surge scenario, EVs would account for 35% (2030) and 51% (2060) of the total number of vehicles in China, significantly lower than 49% (2030) and 67% (2060) share in the base-line, leading to a 28% increase in cumulative carbon emissions (2020-2060) from road transportation. While material recycling and technical battery innovation are effective long-term countermeasures, securing the supply chains of critical materials through international cooperation is highly recommended, given geopolitical and environmental fragilities.

[Fetal electrocardiogram signal extraction and analysis method combining fast independent component analysis algorithm and convolutional neural network].

Fetal electrocardiogram (ECG) signals provide important clinical information for early diagnosis and intervention of fetal abnormalities. In this paper, we propose a new method for fetal ECG signal extraction and analysis. Firstly, an improved fast independent component analysis method and singular value decomposition algorithm are combined to extract high-quality fetal ECG signals and solve the waveform missing problem. Secondly, a novel convolutional neural network model is applied to identify the QRS complex waves of fetal ECG signals and effectively solve the waveform overlap problem. Finally, high quality extraction of fetal ECG signals and intelligent recognition of fetal QRS complex waves are achieved. The method proposed in this paper was validated with the data from the PhysioNet computing in cardiology challenge 2013 database of the Complex Physiological Signals Research Resource Network. The results show that the average sensitivity and positive prediction values of the extraction algorithm are 98.21% and 99.52%, respectively, and the average sensitivity and positive prediction values of the QRS complex waves recognition algorithm are 94.14% and 95.80%, respectively, which are better than those of other research results. In conclusion, the algorithm and model proposed in this paper have some practical significance and may provide a theoretical basis for clinical medical decision making in the future.