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.

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.

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.

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.

4-Cyanotryptophan as a Sensitive Fluorescence Probe of Local Electric Field of Proteins.

Electrostatic interactions are key determinants of protein structure, dynamics, and function. Since protein electrostatics are nonuniform, assessment of the internal electric fields (EFs) of proteins requires spatial resolution at the amino acid residue level. In this regard, vibrational Stark spectroscopy, in conjunction with various unnatural amino acid-based vibrational probes, has become a common method for site-specific interrogation of protein EFs. However, application of this method is often limited to proteins with relatively high solubility, due to the intrinsically low oscillator strength of vibrational transitions. Therefore, it would be useful to develop an alternative method that can overcome this limitation. To this end, we show that, using solvatochromic study and molecular dynamics simulations, the frequency of maximum emission intensity of the fluorophore of 4-cyanotryptophan (4CN-Trp), 3-methyl-1H-indole-4-carbonitrile, exhibits a linear dependence on the local EF. Since the absorption and emission spectra of 4CN-Trp are easily distinguishable from those of naturally occurring aromatic amino acids, we believe that this linear relationship provides an easier and more sensitive means to determine the local EF of proteins.

Scalable Fabrication of Dual-Function Fabric for Zero-Energy Thermal Environmental Management through Multiband, Synergistic, and Asymmetric Optical Modulations.

Solar heating and radiative cooling techniques have been proposed for passive space thermal management to reduce the global energy burden. However, the currently used single-function envelope/coating materials can only achieve static temperature regulation, presenting limited energy savings and poor adaption to dynamic environments. In this study, a sandwich-structured fabric, composed of vertical graphene, graphene glass fiber fabric, and polyacrylonitrile nanofibers is developed, with heating and cooling functions integrated through multiband, synergistic, (solar spectrum and mid-infrared ranges) and asymmetric optical modulations on two sides of the fabric. The dual-function fabric demonstrates high adaption to the dynamic environment and superior performance in a zero-energy-input temperature regulation. Furthermore, it demonstrates ≈15.5 and ≈31.1 MJ m-2 y-1 higher annual energy savings compared to those of their cooling-only and heating-only counterparts, corresponding to ≈173.7 MT reduction in the global CO2 emission. The fabric exhibits high scalability for batch manufacturing with commercially abundant raw materials and facile technologies, providing a favorable guarantee of its mass production and use.

Construction of an SNP fingerprinting database and population genetic analysis of 329 cauliflower cultivars.

Cauliflower is one of the most important vegetable crops grown worldwide. However, the lack of genetic diversity information and efficient molecular markers hinders efforts to improve cauliflower. This study aims to construct DNA fingerprints for 329 cauliflower cultivars based on SNP markers and the KASP system. After rigorous filtering, a total of 1662 candidate SNPs were obtained from nearly 17.9 million SNP loci. The mean values of PIC, MAF, heterozygosity and gene diversity of these SNPs were 0.389, 0.419, 0.075, and 0.506, respectively. We developed a program for in silico simulations on 153 core germplasm samples to generate ideal SNP marker sets from the candidates. Finally, 41 highly polymorphic KASP markers were selected and applied to identify 329 cauliflower cultivars, mainly collected from the public market. Furthermore, based on the KASP genotyping data, we performed phylogenetic analysis and population structure analysis of the 329 cultivars. As a result, these cultivars could be classified into three major clusters, and the classification patterns were significantly related to their curd solidity and geographical origin. Finally, fingerprints of the 329 cultivars and 2D barcodes with the genetic information of each sample were generated. The fingerprinting database developed in this study provides a practical tool for identifying the authenticity and purity of cauliflower seeds and valuable genetic information about the current cauliflower cultivars.

Graphene Infrared Radiation Management Targeting Photothermal Conversion for Electric-Energy-Free Crude Oil Collection.

Graphene has been widely used as a solar absorber for its broad-band absorption. However, targeting a higher photothermal efficiency, the intrinsic infrared radiation loss of graphene requires to be further reduced. Herein, band structure engineering is performed to modulate graphene infrared radiation. Nitrogen-doped vertical graphene is grown on quartz foam (NVGQF) by the plasma-enhanced chemical vapor deposition method. Under the premise of keeping high solar absorption (250-2500 nm), graphitic nitrogen doping effectively modulates the infrared emissivity (2.5-25 µm) of NVGQF from 0.96 to 0.68, reducing the radiation loss by ∼31%. Based on the excellent photothermal properties of NVGQF, a temperature-gradient-driven crude oil collecting raft is designed, where the crude oil flows along the collecting path driven by the viscosity gradient without any external electric energy input. Compared with a nondoped vertical graphene quartz foam raft, the NVGQF raft with a superior photothermal efficiency shows a significantly enhanced crude oil collecting efficiency by three times. The advances in this work suggest broad radiation-managed application platforms for graphene materials, such as seawater desalination and personal or building thermal management.

Ferric ion detection mechanism of a dicarboxylic cellulose nanocrystal and a 7-amino-4-methylcoumarin based fluorescent chemosensor.

As one of Earth's most widely distributed and abundant elements, iron impacts the natural environment and biological systems. Therefore, developing a simple, rapid, and accurate Fe3+ detection method is vital. Fluorescent dicarboxylic cellulose nanocrystals (FDCN) with selective quenching of Fe3+ were synthesized using 7-amino-4-methylcoumarin (AMC), and dicarboxylic cellulose nanocrystals (DCN) prepared by sequential periodate-chlorite oxidation. The sensing characteristics and detection mechanism of FDCN for Fe3+ were studied by fluorescence spectrophotometry, Fourier-transform infrared spectroscopy (FTIR), the Stern-Volmer equation, Job's plot method, and the Benesi-Hildebrand equation. The results showed that FDCN was highly selective for Fe3+, and other metal ions did not reduce the selectivity. High sensitivity with a detection limit of 0.26 µM and a Stern-Volmer quenching constant of 0.1229 were also achieved. The coordination between Fe3+ and the carboxylic, hydroxyl, and amide groups on the surface of FDCN and the carbonyl of coumarin lactones to form FDCN/Fe3+ complexes prevented the intramolecular charge transfer (ICT) process and led to the fluorescence quenching of FDCN. EDTA restored the fluorescence emission of quenched FDCN. The complexation stoichiometry of Fe3+ to FDCN was 1 : 1, and the association constant was 3.23 × 104 M-1. The high hydrophilicity, sensitivity, and selectivity of FDCN for Fe3+ make the chemosensor suitable for Fe3+ trace detection in drinking water and biology.

Fetal Electrocardiogram Signal Extraction Based on Fast Independent Component Analysis and Singular Value Decomposition.

Fetal electrocardiograms (FECGs) provide important clinical information for early diagnosis and intervention. However, FECG signals are extremely weak and are greatly influenced by noises. FECG signal extraction and detection are still challenging. In this work, we combined the fast independent component analysis (FastICA) algorithm with singular value decomposition (SVD) to extract FECG signals. The improved wavelet mode maximum method was applied to detect QRS waves and ST segments of FECG signals. We used the abdominal and direct fetal ECG database (ADFECGDB) and the Cardiology Challenge Database (PhysioNet2013) to verify the proposed algorithm. The signal-to-noise ratio of the best channel signal reached 45.028 dB and the issue of missing waveforms was addressed. The sensitivity, positive predictive value and F1 score of fetal QRS wave detection were 96.90%, 98.23%, and 95.24%, respectively. The proposed algorithm may be used as a new method for FECG signal extraction and detection.

Phenotype Shifting in Astrocytes Account for Benefits of Intra-Arterial Selective Cooling Infusion in Hypertensive Rats of Ischemic Stroke.

The translational failure of neuroprotective therapies in stroke may be influenced by the mismatch of existing comorbidities between animal models and patients. Previous studies found that single-target neuroprotective agents reduced infarction in Sprague-Dawley but not in spontaneously hypertensive rats. It is of great interest to explore whether multi-target neuroprotectants and stroke models with comorbidities should be used in further translational researches. Ischemic stroke was induced in normotensive or hypertensive rats by 90- or 120-min middle cerebral artery occlusion (MCAO) and reperfusion. Intra-Arterial Selective Cooling Infusion (IA-SCI) was started at the onset of reperfusion for 30 minutes. Acute neurological deficits, infarct volumes, gene expression and markers of A1-like and A2-like astrocytes were evaluated. In further analysis, TNFα and IL-1α were administrated intracerebroventricularly, phenotype shifting of astrocytes and infarct volumes were assessed. Normobaric oxygen treatment, as a negative control, was also assessed in hypertensive rats. IA-SCI led to similar benefits in normotensive rats with 120-min MCAO and hypertensive rats with both 90-min and 120-min MCAO, including mitigated functional deficit and reduced infarct volumes. IA-SCI shifted astrocyte phenotypes partly by downregulating A1-like astrocytes and upregulating A2-like astrocytes in both RNA and protein levels. Upregulated A1-type astrocyte markers levels, induced by intracerebroventricular injection of TNFα and IL-1α, were closely related to increased infarct volumes in hypertensive rats, despite receiving IA-SCI treatment. In addition, infarct volumes and A1/A2-like genes were not affected by normobaric oxygen treatment. IA-SCI reduced infarction in both normotensive and hypertensive rats. Our results demonstrated the neuroprotective effects of IA-SCI in hypertensive rats may be related with phenotype shifting of astrocytes.