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Chlorpromazine (CPMZ) is a representative drug for the treatment of psychiatric disorders. Excessive use of CPMZ could result in some serious health problems, and therefore, construction of a sensitive electrochemical sensor for CPMZ detection is greatly significant for human health. Herein, a feasible electrochemical method for the detection of CPMZ was provided. To design a suitable electrode surface modifier, a new two-dimensional (2D) thiacalix[4]arene-based metal-organic framework was designed and synthesized under solvothermal conditions, namely, [Co(TMPA)Cl2]MeOH·2EtOH·2H2O (Co-TMPA). Afterward, a series of composite materials was prepared by combining Co-TMPA with highly conductive carbon materials. Markedly, Co-TMPA/MWCNT-2@GCE (GCE = glassy carbon electrode, MWCNT = multiwalled carbon nanotube) exhibited the best electrocatalytic performance for CPMZ detection due to the synergistic effect between MWCNT and Co-TMPA. Particularly, it featured a low limit of detection (8 nM) and a wide linear range (0.05 to 1350 µM) in quantitative determination of CPMZ. Meanwhile, the sensor possessed excellent stability, selectivity, and reproducibility. Importantly, Co-TMPA/MWCNT-2@GCE was employed to analyze CPMZ in urine and serum with satisfactory recoveries (98.87-102.17%) and relative standard deviations (1.44-3.80%). Furthermore, the electrochemical detection accuracy of the Co-TMPA/MWCNT-2@GCE sensor was verified with the ultraviolet-visible spectroscopy technique. This work offers a promising sensor for the efficient analysis of drug molecules.
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Graphyne nanoscrolls (GNSs) have attracted significant research interest because of their wide-ranging applications. However, the production of GNSs via a self-scrolling approach is environment dependent. Here, molecular dynamics simulations are conducted to evaluate the self-scrolling behavior of an α-graphyne (α-GY) ribbon on a carbon nanotube (CNT) within various multiphysical environments, accounting for the interactions among temperature, electric field, and argon gas. The results demonstrate that the fabrication of an α-GNS lies in the interplay of van der Waals (vdW) forces among the components in a vacuum. Notably, the α-GY ribbon is easier to scroll onto a thicker CNT. The electric field attenuates the vdW interaction, necessitating thicker CNTs for successful self-scrolling under a stronger electric field. In argon, both the vdW interaction and nanoscale pore contribute to the overlap formation. At 300 K, increasing argon density prolongs the time required for α-GNS formation, with self-scrolling failing beyond a critical gas density threshold. Moreover, the self-scrolling becomes easier at higher temperatures. In multiphysical environments, the interplay between the electric field and the gas density dictates the self-scrolling at low temperatures. Finally, reasonable suggestions are given for successful self-scrolling. The conclusions offer valuable insights for the practical fabrication of α-GNS.
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The contents of eight heavy metals ï¼Cr, Ni, Cu, Zn, Cd, Pb, As, and Hgï¼ were determined based on the surface soil samples of sewage irrigation and industrial complex in Kaifeng City. The absolute factor analysis-multiple linear regression ï¼APCS-MLRï¼ model and positive matrix factorization ï¼PMFï¼ model were used to analyze the sources and contribution rates of heavy metals in soil combined with correlation analysis and systematic cluster analysis. The results showed thatï¼ â The average values of ωï¼Crï¼, ωï¼Niï¼, ωï¼Cuï¼, ωï¼Znï¼, ωï¼Cdï¼, ωï¼Pbï¼, ωï¼Asï¼, and ωï¼Hgï¼ in the study area were 52.19, 25.00, 42.03, 323.53, 1.79, 53.45, 9.43, and 0.20 mg·kg-1, respectively, and Cr, Ni, and As are lower than the background values of tidal soil. Cu, Zn, Cd, Pb, and Hg are higher than the background values of the tidal soil. â¡ There were four sources of the eight heavy metalsï¼ natural sources, agricultural sewage irrigation sources, industrial atmospheric sedimentation sources, and transportation sources. Cr and Ni were mainly from natural sourcesï¼ Cu, Zn, Cd, and Pb were mainly from agricultural sewage irrigation and transportation sourcesï¼ As was mainly from natural sources and agricultural sewage irrigationï¼ and Hg was mainly from industrial atmospheric sedimentation. ⢠The APCS-MLR and PMF source analysis results indicated that industrial and agricultural activities were the main sources of heavy metals in the soil of the study area. The average contribution rates of APCS-MLR in the nine sampling areas of the research area were 76.01% ï¼natural sources and agricultural sewage irrigation sourcesï¼, 22.71% ï¼industrial atmospheric sedimentation sources and transportation sourcesï¼, and 1.28% ï¼unknown sourcesï¼. The average contribution rates of PMF were 59.66% ï¼natural sources and agricultural sewage irrigation sourcesï¼ and 40.34% ï¼industrial atmospheric sedimentation sources and transportation sourcesï¼. The source analysis results of the LZ, XZ, NLT, PT, YLZ, and BC models were basically consistent, and WL was better in the APCS-MLR model, whereas SG and QT were better in the PMF model. The research results can provide a scientific basis for the prevention and control of soil heavy metal pollution and environmental remediation.
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Soil salinity significantly limits rice productivity, but it is poorly understood how excess sodium (Na+) is delivered to the grains at the reproductive stage. Here, we functionally characterized OsHAK4, a member of the clade IV HAK/KUP/KT transporter subfamily in rice. OsHAK4 was localized to the plasma membrane and exhibited influx transport activity for Na+, but not for K+. Analysis of organ- and growth stage-dependent expression patterns showed that very low expression levels of OsHAK4 were detected at the vegetative growth stage, but its high expression in uppermost node I, peduncle, and rachis was found at the reproductive stage. Immunostaining indicated OsHAK4 localization in the phloem region of node I, peduncle, and rachis. Knockout of OsHAK4 did not affect the growth and Na+ accumulation at the vegetative stage. However, at the reproductive stage, the hak4 mutants accumulated higher Na+ in the peduncle, rachis, husk, and brown rice compared to the wild-type rice. Element imaging revealed higher Na+ accumulation at the phloem region of the peduncle in the mutants. These results indicate that OsHAK4 plays a crucial role in retrieving Na+ from the phloem in the upper nodes, peduncle, and rachis, thereby preventing Na+ distribution to the grains at the reproductive stage of rice.
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BACKGROUND: Insulin antibodies (IAs) affect blood glucose control in patients receiving insulin therapy. AIM: To investigate the relationship between different hypoglycemic treatments and IAs in patients with type 2 diabetes mellitus (T2DM). METHODS: This cross-sectional, retrospective study included 1863 patients with T2DM who were receiving exogenous insulin therapy. All patients received stable antidiabetic therapy in the last 3 months and IA levels were measured using an iodine-125 array. RESULTS: A total of 1863 patients were enrolled. There were 902 (48.4%) patients who had positive IAs (IA level > 5%), with a mean IA level of 11.06% (10.39%-11.72%). IA levels were positively correlated with high fasting blood glucose (odds ratio = 1.069, P < 0.001). The proportion of positive IAs was lowest in patients using glargine only (31.9%) and highest in patients using human insulin only (70.3%), P < 0.001. The IA levels in patients using sulfonylureas/glinides (8.3%), metformin (9.6%), and dipeptidyl peptidase-4 inhibitors (8.2%) were all lower than in patients without these drugs (all P < 0.05). CONCLUSION: Nearly half of patients on insulin therapy have positive IA antibodies, and IA antibody levels are associated with blood glucose control. Insulin glargine and a combination of oral glucose-lowering drugs were correlated with lower IA levels.
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Improving low nitrogen (LN) tolerance in barley (Hordeum vulgare L.) increases global barley yield and quality. In this study, a recombinant inbred line (RIL) population crossed between "Baudin × CN4079" was used to conduct field experiments on twenty traits of barley yield, agronomy, and nitrogen(N)-related traits under LN and normal nitrogen (NN) treatments for two years. This study identified seventeen QTL, comprising eight QTL expressed under both LN and NN treatments, eight LN-specific QTL, and one NN-specific QTL. The localized C2 cluster contained QTL controlling yield, agronomic, and N-related traits. Of the four novel QTL, the expression of the N-related QTL Qstna.sau-5H and Qnhi.sau-5H was unaffected by N treatment. Qtgw.sau-2H for thousand-grain weight, Qph.sau-3H for plant height, Qsl.sau-7H for spike length, and Qal.sau-7H for awn length were identified to be the four stable expression QTL. Correlation studies revealed a significant negative correlation between grain N content and harvest index (p < 0.01). These results are essential for barley marker-assisted selection (MAS) breeding.
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The electrochemical carbon dioxide reduction reaction (eCO2RR) represents an effective means of achieving renewable energy storage and a supply of carbon-based raw materials. However, there are still great challenges in selectively producing specific hydrocarbon compounds. The unique ability of the copper (Cu) catalyst to promote proton-coupled electron transfer processes offers clear advantages in generating value-added products. This review presents molecular enhancement strategies for Cu-based catalysts for CO2 electroreduction. We also elucidate the principles of each strategy for enhancing eCO2RR performance, discuss the structure-activity relationships, and propose some promising molecular enhancement strategies. This review will provide guidance for the development of organic-inorganic hybrid Cu-based catalysts as high-performance CO2 electroreduction catalysts.
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Chloroplasts are key players in photosynthesis and immunity against microbial pathogens. However, the precise and timely regulatory mechanisms governing the control of photosynthesis-associated nuclear genes (PhANGs) expression in plant immunity remain largely unknown. Here we report that TaPIR1, a Pst-induced RING-finger E3 ubiquitin ligase, negatively regulates Pst resistance by specifically interacting with TaHRP1, an atypical transcription factor histidine-rich protein. TaPIR1 ubiquitinates the lysine residues K131 and K136 in TaHRP1 to regulate its stability. TaHRP1 directly binds to the TaHRP1-binding site elements within the PhANGs promoter to activate their transcription via the histidine-rich domain of TaHRP1. PhANGs expression induces the production of chloroplast-derived ROS. Although knocking out TaHRP1 reduces Pst resistance, TaHRP1 overexpression contributes to photosynthesis, and chloroplast-derived ROS production, and improves disease resistance. TaPIR1 expression inhibits the downstream activation of TaHRP1 and TaHRP1-induced ROS accumulation in chloroplasts. Overall, we show that the TaPIR1-mediated ubiquitination and degradation of TaHRP1 alters PhANGs expression to disrupt chloroplast function, thereby increasing plant susceptibility to Pst.
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Cloroplastos , Regulação da Expressão Gênica de Plantas , Triticum , Ubiquitina-Proteína Ligases , Arabidopsis/metabolismo , Arabidopsis/genética , Arabidopsis/imunologia , Cloroplastos/metabolismo , Resistência à Doença/genética , Nicotiana/metabolismo , Nicotiana/genética , Fotossíntese , Doenças das Plantas/microbiologia , Doenças das Plantas/imunologia , Doenças das Plantas/genética , Imunidade Vegetal , Plantas Geneticamente Modificadas , Regiões Promotoras Genéticas , Proteólise , Espécies Reativas de Oxigênio/metabolismo , Fatores de Transcrição/metabolismo , Fatores de Transcrição/genética , Ubiquitina-Proteína Ligases/metabolismo , Ubiquitina-Proteína Ligases/genética , Ubiquitinação , Triticum/citologia , Triticum/metabolismoRESUMO
Several studies have documented a relationship between short-term exposure to atmospheric sulfur dioxide (SO2) and chronic obstructive pulmonary disease (COPD). However, findings vary across different regions. This meta-analysis employed a random-effects model to calculate the combined risk estimate for each 10-µg/m3 increase in ambient SO2 concentration. Subgroup analysis aimed to identify sources of heterogeneity. To assess potential bias, studies were evaluated using a domain-based assessment tool developed by the World Health Organization. Sensitivity analyses, based on bias risk, explored how model assumptions influenced associations. An evidence certainty framework was used to evaluate overall evidence quality. The study protocol was registered with PROSPERO (CRD42023446823). We thoroughly reviewed 191 full-text articles, ultimately including 15 in the meta-analysis. The pooled relative risk for COPD was 1.26 (95â¯% CI 0.94-1.70) per 10-µg/m3 increase in ambient SO2. Eleven studies were deemed high risk due to inadequate handling of missing data. Overall evidence certainty was rated as medium. Given SO2's significant public health implications, continuous monitoring is crucial. Future research should include countries in Africa and Oceania to enhance global understanding of atmospheric SO2-related health issues.
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Melon (Cucumis melo L.) is an economically important horticultural crop. Spotted rind at maturity is an important appearance quality trait in melons. However, the gene controlling this trait remains unknown. In this study, the inheritance pattern of this trait was explored, and the candidate gene underlying this trait was also successfully identified. Genetic analysis showed that a single dominant gene, Cucumis melo Spotted Rind (CmSR), regulates the spotted rind trait. A preliminary genetic mapping analysis was conducted based on a BSA-seq approach. The CmAPRR2 gene was identified to be linked with the spotted rind trait and was located on the short arm of chromosome 4. It harbored two single-nucleotide mutations (chr4: 687014 G/A and chr4: 687244 C/A) in the non-spotted line 'Yellow 2', which may result in the alternative splicing of the transcript and an amino acid change in the respective protein, from proline to glutamine, respectively. Moreover, marker SNP687014-G/A was developed and co-segregated with the spotted rind trait. Therefore, it is speculated that the CmAPRR2 gene may be involved in the regulation of the spotted rind trait in melon. This study provides a theoretical foundation for further research on the gene regulatory mechanism of the rind color in melon.
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Summary: Network biology is an interdisciplinary field bridging computational and biological sciences that has proved pivotal in advancing the understanding of cellular functions and diseases across biological systems and scales. Although the field has been around for two decades, it remains nascent. It has witnessed rapid evolution, accompanied by emerging challenges. These stem from various factors, notably the growing complexity and volume of data together with the increased diversity of data types describing different tiers of biological organization. We discuss prevailing research directions in network biology, focusing on molecular/cellular networks but also on other biological network types such as biomedical knowledge graphs, patient similarity networks, brain networks, and social/contact networks relevant to disease spread. In more detail, we highlight areas of inference and comparison of biological networks, multimodal data integration and heterogeneous networks, higher-order network analysis, machine learning on networks, and network-based personalized medicine. Following the overview of recent breakthroughs across these five areas, we offer a perspective on future directions of network biology. Additionally, we discuss scientific communities, educational initiatives, and the importance of fostering diversity within the field. This article establishes a roadmap for an immediate and long-term vision for network biology. Availability and implementation: Not applicable.
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Recent advances in machine learning have enabled the development of next-generation predictive models for complex computational biology problems, thereby spurring the use of interpretable machine learning (IML) to unveil biological insights. However, guidelines for using IML in computational biology are generally underdeveloped. We provide an overview of IML methods and evaluation techniques and discuss common pitfalls encountered when applying IML methods to computational biology problems. We also highlight open questions, especially in the era of large language models, and call for collaboration between IML and computational biology researchers.
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Biologia Computacional , Aprendizado de Máquina , Biologia Computacional/métodos , Humanos , AlgoritmosRESUMO
Inflammatory retinal diseases such as diabetic retinopathy (DR) and age-related macular degeneration (AMD) are prominent causes of blindness in industrialized countries. The complexity of these diseases, involving diverse cell types and pathways that give rise to a multifactorial pathogenesis, complicates drug discovery. As such, therapies exhibiting polypharmacology are expected to improve outcomes through broader disease stage coverage and beneficial spatiotemporal effects. We report herein the first dual modulator of PPARα and STING, two targets tied to disparate pathologies in retinal diseases. Recognizing structural similarities between a reported STING inhibitor SN-013 and our previously described PPARα agonist A229, we designed BH400, which agonizes PPARα (EC50 = 1.2 µM) and inhibits STING (IC50 = 8.1 µM). BH400 demonstrates superior protection over single-target PPARα or STING modulation in microglial and photoreceptor cells. These findings provide compelling evidence for the potential benefit of polypharmacology in common retinal diseases through dual PPARα/STING modulation, motivating further studies.
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Iron-based catalysts play an important role in the ammonia industry. As one of the most abundant iron minerals, Fe3O4 containing FeII and FeIII sites is widely distributed in the earth's crust and even on exoplanets, theoretically giving it both economic and catalytic potentials in ammonia synthesis. However, in the absence of specific active co-catalyst and harsh conditions, Fe3O4 is impossible to achieve ammonia synthesis alone. Here, we designed to activate the relatively inert FeII and FeIII sites in Fe3O4 with a third FeIII site inlayed in a coordination framework (MIL-101(Fe)) to achieve the unpresented multi-site collaborative catalysis. In-depth mechanism study confirmed the roles of three different Fe sites in N2 activation, H2 activation, and product transfer, respectively. Efficient N2-H2 activation to NH3 on the Fe3O4-based catalytic system has been achieved at extremely mild conditions. Our research provides a theoretical basis and a new strategy for designing efficient non-noble metal-based ammonia synthesis catalyst with minimized energy consumption.
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Deamidation is a post-translational chemical modification that occurs within proteins and can be influenced by many factors, including temperature and pH. In vaccines, deamidation is considered undesirable as it may lead to changes in structure, function, stability, and immunogenicity. Detecting deamidation in vaccines, especially adjuvanted vaccines, can be challenging due to the lack of simple quantitative techniques. In this study, the quantification of isoaspartic acid (isoAsp) was used to assess deamidation in model antigens in the presence and absence of common vaccine adjuvants. This study shows that the detection of isoAsp was possible in the presence of various types of adjuvants with little to no interference. High levels of isoAsp were detected in thermally and pH-stressed adjuvanted vaccines, suggesting significant deamidation and highlighting the stability-indicating capabilities of the assay. The quantification of isoAsp in stability programs of a vaccine drug product could possibly find applications in product shelf-life determination, using thermal kinetic modeling to predict deamidation over time. The ability to detect deamidation early in vaccine development enhances process improvements and ultimately improves the vaccine's stability. To summarize, this paper describes a rapid and simple method to determine deamidation in adjuvanted vaccines. This method could be applicable to formulation development, stability assessment, or shelf-life determination.
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Semihydrogenation is a crucial industrial process. Noble metals such as Pd have been extensively studied in semihydrogenation reactions, owing to their unique catalytic activity toward hydrogen activation. However, the overhydrogenation of alkenes to alkanes often happens due to the rather strong adsorption of alkenes on Pd active phases. Herein, we demonstrate that the incorporation of Pd active phases as single-atom sites in perovskite lattices such as SrTiO3 can greatly alternate the electronic structure and coordination environment of Pd active phases to facilitate the desorption of alkenes rather than further hydrogenation. Furthermore, the incorporated Pd sites can be well stabilized without sintering by a strong host-guest interaction with SrTiO3 during the activation of H species in hydrogenation reactions. As a result, the Pd incorporated SrTiO3 (Pd-SrTiO3) exhibits an excellent time-independent selectivity (> 99.9 %) and robust durability for the photocatalytic semihydrogenation of phenylacetylene to styrene. This strategy based on incorporation of active phases in perovskite lattices will have broad implications in the development of high-performance photocatalysts for selective hydrogenation reactions.
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Objectives: The relationship between adiposity and sepsis has received increasing attention. This study aims to explore the causal relationship between life course adiposity and the sepsis incidence. Methods: Mendelian randomization (MR) method was employed in this study. Instrumental variants were obtained from genome-wide association studies for life course adiposity, including birth weight, childhood body mass index (BMI), childhood obesity, adult BMI, waist circumference, visceral adiposity, and body fat percentage. A meta-analysis of genome-wide association studies for sepsis including 10,154 cases and 454,764 controls was used in this study. MR analyses were performed using inverse variance weighted, MR Egger regression, weighted median, weighted mode, and simple mode. Instrumental variables were identified as significant single nucleotide polymorphisms at the genome-wide significance level (P < 5×10-8). The sensitivity analysis was conducted to assess the reliability of the MR estimates. Results: Analysis using the MR analysis of inverse variance weighted method revealed that genetic predisposition to increased childhood BMI (OR = 1.29, P = 0.003), childhood obesity (OR = 1.07, P = 0.034), adult BMI (OR = 1.38, P < 0.001), adult waist circumference (OR = 1.01, P = 0.028), and adult visceral adiposity (OR = 1.53, P < 0.001) predicted a higher risk of sepsis. Sensitivity analysis did not identify any bias in the MR results. Conclusion: The results demonstrated that adiposity in childhood and adults had causal effects on sepsis incidence. However, more well-designed studies are still needed to validate their association.
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Adiposidade , Índice de Massa Corporal , Estudo de Associação Genômica Ampla , Análise da Randomização Mendeliana , Polimorfismo de Nucleotídeo Único , Sepse , Humanos , Adiposidade/genética , Sepse/genética , Sepse/epidemiologia , Predisposição Genética para Doença , Obesidade Infantil/genética , Obesidade Infantil/epidemiologia , Obesidade Infantil/complicações , Adulto , Circunferência da Cintura , Criança , Masculino , FemininoRESUMO
Discovering new treatments for melanoma will benefit human health. The mechanism by which deoxyhypusine synthase (DHPS) promotes melanoma development remains elucidated. Multi-omics studies have revealed that DHPS regulates m6A modification and maintains mRNA stability in melanoma cells. Mechanistically, DHPS activates the hypusination of eukaryotic translation initiation factor 5A (eIF5A) to assist METTL3 localizing on its mRNA for m6A modification, then promoting METTL3 expression. Structure-based design, synthesis, and activity screening yielded the hit compound GL-1 as a DHPS inhibitor. Notably, GL-1 directly inhibits DHPS binding to eIF5A, whereas GC-7 cannot. Based on the clarification of the mode of action of GL-1 on DHPS, it is found that GL-1 can promote the accumulation of intracellular Cu2+ to induce apoptosis, and antibody microarray analysis shows that GL-1 inhibits the expression of several cytokines. GL-1 shows promising antitumor activity with good bioavailability in a xenograft tumor model. These findings clarify the molecular mechanisms by which DHPS regulates melanoma proliferation and demonstrate the potential of GL-1 for clinical melanoma therapy.
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Background: The species composition of and changes in grassland communities are important indices for inferring the number, quality and community succession of grasslands, and accurate monitoring is the foundation for evaluating, protecting, and utilizing grassland resources. Remote sensing technology provides a reliable and powerful approach for measuring regional terrain information, and the identification of grassland species by remote sensing will improve the quality and effectiveness of grassland monitoring. Methods: Ground hyperspectral images of a sericite-Artemisia desert grassland in different seasons were obtained with a Soc710 VP imaging spectrometer. First-order differential processing was used to calculate the characteristic parameters. Analysis of variance was used to extract the main species, namely, Seriphidium transiliense (Poljak), Ceratocarpus arenarius L., Petrosimonia sibirica (Pall), bare land and the spectral characteristic parameters and vegetation indices in different seasons. On this basis, Fisher discriminant analysis was used to divide the samples into a training set and a test set at a ratio of 7:3. The spectral characteristic parameters and vegetation indices were used to identify the three main plants and bare land. Results: The selection of parameters with significant differences (P < 0.05) between the recognition objects effectively distinguished different land features, and the identification parameters also differed due to differences in growth period and species. The overall accuracy of the recognition model established by the vegetation index decreased in the following order: June (98.87%) > September (91.53%) > April (90.37%). The overall accuracy of the recognition model established by the feature parameters decreased in the following order: September (89.77%) > June (88.48%) > April (85.98%). Conclusions: The recognition models based on vegetation indices in different months are superior to those based on feature parameters, with overall accuracies ranging from 1.76% to 9.40% higher. Based on hyperspectral image data, the use of vegetation indices as identification parameters can enable the identification of the main plants in sericite-Artemisia desert grassland, providing a basis for further quantitative classification of the species in community images.