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Summary: Nitrogen doped carbon materials have been studied as catalyst support for ammonia decomposition. There are 4 different types of nitrogen environments (graphitic, pyrrolic, pyridinic and nitrogen oxide) on the amorphous support identified. In this paper, we report a 5%Ru on MgCO3 pre-treated nitrogen doped carbon catalyst with high content of edge nitrogen-containing sites which displays an ammonia conversion rate of over 90% at 500°C and WHSV = 30,000 mL gcat−1 h−1. It also gives an impressive hydrogen production rate of 31.3 mmol/(min gcat) with low apparent activation energy of 43 kJ mol−1. Fundamental studies indicate that the distinct average Ru-N4 coordination site on edge regions is responsible for such high catalytic activity. Ammonia is stepwise decomposed via a Ru-N(H)-N(H)-Ru intermediate. This associative mechanism circumvents the direct cleavage of energetic surface nitrogen from metal to form N2 hence lowering the activation barrier for the decomposition over this catalyst.

Patients with Polycystic ovary syndrome (PCOS) have chronic low-grade ovarian inflammation. Inflammation can cause telomere dysfunction, and telomere and telomerase complex are also involved in regulating inflammation. However, the specific mechanisms of inflammatory signaling feedback and telomere-telomerase mutual regulation remain to be discovered. This study elucidates the role of Nuclear factor kappa-B (NF-κB)-Telomerase reverse transcriptase (TERT) feedback in PCOS granulosa cell apoptosis. Using letrozole and a high-fat diet, a PCOS rat model was established, along with a Lipopolysaccharide (LPS) -treated KGN cell inflammation model was established. NF-κB and TERT inhibitors (BAY 11-7082 and BIBR1532) were then administered to LPS-induced KGN cells. PCOS rats displayed disrupted estrous cycles, increased weight, elevated serum testosterone, cystic follicles, granulosa cell layer thinning, and reduced corpora lutea count (P are all less than 0.05). In PCOS rat ovaries, NF-κB, Interleukin-6 (IL-6), Tumor Necrosis Factor α (TNF-α), TERT, Bax, and Caspase-3 exhibited notable upregulation, while Bcl-2 decreased, with telomere elongation (P are all less than 0.05). There were significant correlations among NF-κB-related inflammatory factors, TERT and apoptotic factors, and they were positively correlated with Bax and Caspase-3, and negatively correlated with Bcl-2 (P are all less than 0.05). LPS-treated KGN cells demonstrated increased expression of inflammatory and pro-apoptotic factors, later restored post-treatment with NF-κB and TERT inhibitors (P are all less than 0.05). In conclusion, TERT may induce granulosa cell apoptosis by participating in the regulation of the NF-κB signaling pathway, thereby mediating the chronic inflammatory response of PCOS through downstream inflammatory factors IL-6 and TNF-α.

The micro-occurrence characterization of shale oil is a key geological issue that restricts the effective development of continental shale oil in China. In order to make up for the lack of research in this area, this paper carries out a series of experiments on the shale oil of the Lucaogou Formation using a multi-step extraction method, with the aim of exploring the micro-occurrence types and mechanisms of shale oil in the Lucaogou Formation, as well as exploring its direct connection with production and development. In this paper, shale oil in the reservoir is divided into two categories: free oil and residual oil. The polar substances and OSN compounds are the key factors determining the occurrence state of shale oil. Abundant polar substances and OSN compounds can preferentially react with mineral surfaces (including coordination, complexation, ionic exchange, and so on) to form a stable adsorption layer, making it difficult to extract residual oil in actual exploitation. Free oil is mainly composed of aliphatic hydrocarbons, and its adsorption capacity is related to the length of the carbon chain, i.e. long carbon chain, strong adsorption capacity, and poor movability. Free oil is widely stored in pores and cracks, and that with high mobility can be the most easily extracted, making it the main target at present exploitation. In the current state of drilling and fracturing technology, research should prioritize understanding the adsorption and desorption mechanisms of crude oil, particularly residual oil. This will help optimize exploitation programs, such as carbon dioxide fracturing and displacement, to enhance shale oil production.

Cherry tomatoes, a very popular fruit, are highly susceptible to microbial infestation, which cause significant economic losses. In order to preserve cherry tomatoes better, we treat them with a Chitosan (CTS) and Curdlan (CUR) composite coating. The lowest inhibitory concentration of CTS/CUR composite coating on Serratia marcescens and Pseudomonas syringae, the growth curves, and the changes of the cell lysis rate were determined to explore the inhibitory mechanism of CTS/CUR composite coating on Serratia marcescens and Pseudomonas syringae and the microscopic morphology of Serratia marcescens and Pseudomonas syringae was observed using scanning electron microscopy at the same time. The results showed that the CTS/CUR composite coating could effectively inhibit the growth of Serratia marcescens and Pseudomonas, and the inhibitory effect reflected the concentration-dependent characteristics. The electron microscopy results indicated that the inhibition of Serratia marcescens and Pseudomonas syringae by the CTS/CUR composite coating might originate from its disruptive effect on the cell wall and cell membrane of the bacterium.

BackgroundMajor depression disorder (MDD) is a devastating neuropsychiatric disease, and one of the leading causes of suicide. Ferroptosis, an iron-dependent form of regulated cell death, plays a pivotal role in numerous diseases. The study aimed to construct and validate a gene signature for diagnosing MDD based on ferroptosis-related genes (FRGs) and further explore the biological functions of these genes in MDD.MethodsThe datasets were downloaded from the Gene Expression Omnibus (GEO) database and FRGs were obtained from the FerrDb database and other literatures. Least absolute shrinkage and selection operator (LASSO) regression and stepwise logistic regression were performed to develop a gene signature. Receiver operating characteristic (ROC) curves were utilized to assess the diagnostic power of the signature. Gene ontology (GO) enrichment analysis was used to explore the biological roles of these diagnostic genes, and single sample gene set enrichment analysis (ssGSEA) algorithm was used to evaluate immune infiltration in MDD. Animal model of depression was constructed to validate the expression of the key genes.ResultsEleven differentially expressed FRGs were identified in MDD patients compared with healthy controls. A signature of three FRGs (ALOX15B, RPLP0, and HP) was constructed for diagnosis of MDD. Afterwards, ROC analysis confirmed the signature’s discriminative capacity (AUC = 0.783, 95% CI = 0.719–0.848). GO enrichment analysis revealed that the differentially expressed genes (DEGs) related to these three FRGs were mainly involved in immune response. Furthermore, spearman correlation analysis demonstrated that these three FRGs were associated with infiltrating immune cells. ALOX15B and HP were significantly upregulated and RPLP0 was significantly downregulated in peripheral blood of the lipopolysaccharide (LPS)-induced depressive model.ConclusionOur results suggest that the novel FRG signature had a good diagnostic performance for MDD, and these three FRGs correlated with immune infiltration in MDD.

Long noncoding RNAs (lncRNAs) are a class of RNAs longer than 200 nt and cannot encode the protein. Studies have shown that lncRNAs can regulate gene expression at the epigenetic, transcriptional, and posttranscriptional levels, which are not only closely related to the occurrence, development, and prevention of human diseases, but also can regulate plant flowering and participate in plant abiotic stress responses such as drought and salt. Therefore, how to accurately and efficiently identify lncRNAs is still an essential job of relevant researches. There have been a large number of identification tools based on machine-learning and deep learning algorithms, mostly using human and mouse gene sequences as training sets, seldom plants, and only using one or one class of feature selection methods after feature extraction. We developed an identification model containing dicot, monocot, algae, moss, and fern. After comparing 20 feature selection methods (seven filter and thirteen wrapper methods) combined with seven classifiers, respectively, considering the correlation between features and model redundancy at the same time, we found that the WOA-XGBoost-based model had better performance with 91.55%, 96.78%, and 91.68% of accuracy, AUC, and F1_score. Meanwhile, the number of elements in the feature subset was reduced to 23, which effectively improved the prediction accuracy and modeling efficiency.

The clinical application and biological function of interferon regulatory factor 1 (IRF1) in non-small cell lung cancer (NSCLC) patients undergoing chemoimmunotherapy remain elusive. The aim of this study was to investigate the predictive and prognostic significance of IRF1 in NSCLC patients. We employed the cBioPortal database to predict frequency changes in IRF1 and explore its target genes. Bioinformatic methods were utilized to analyze the relationship between IRF1 and immune regulatory factors. Retrospective analysis of clinical samples was conducted to assess the predictive and prognostic value of IRF1 in chemoimmunotherapy. Additionally, A549 cells with varying IRF1 expression levels were constructed to investigate its effects on NSCLC cells, while animal experiments were performed to study the role of IRF1 in vivo. Our findings revealed that the primary mutation of IRF1 is deep deletion and it exhibits a close association with immune regulatory factors. KRAS and TP53 are among the target genes of IRF1, with interferon and IL-2 being the predominantly affected pathways. Clinically, IRF1 levels significantly correlate with the efficacy of chemoimmunotherapy. Patients with high IRF1 levels exhibited a median progression-free survival (mPFS) of 9.5 months, whereas those with low IRF1 levels had a shorter mPFS of 5.8 months. IRF1 levels positively correlate with PD-L1 distribution and circulating IL-2 levels. IL-2 enhances the biological function of IRF1 and recapitulates its role in vivo in the knockdown group. Therefore, IRF1 may possess predictive and prognostic value for chemoimmunotherapy in NSCLC patients through the regulation of the IL-2 inflammatory pathway.

The xanthophyll cycle is a photoprotective mechanism in plants and algae, which protects the photosynthetic system from excess light damage under abiotic stress. Zeaxanthin is considered to play a pivotal role in this process. In this study, the relative content of xanthophylls was determined using HPLC-MS/MS in Ulva prolifera exposed to different salinities. The results showed that high-salt stress significantly increased the relative content of xanthophylls and led to the accumulation of zeaxanthin. It was speculated that the accumulated zeaxanthin may contribute to the response of U. prolifera to high-salt stress. Zeaxanthin epoxidase (ZEP) is a key enzyme in the xanthophyll cycle and is also involved in the synthesis of abscisic acid and carotenoids. In order to explore the biological function of ZEP, a ZEP gene was cloned and identified from U. prolifera. The CDS of UpZEP is 1122 bp and encodes 373 amino acids. Phylogenetic analysis showed that UpZEP clusters within a clade of green algae. The results of qRT-PCR showed that high-salt stress induced the expression of UpZEP. In addition, heterologous overexpression of the UpZEP gene in yeast and Chlamydomonas reinhardtii improved the salt tolerance of transgenic organisms. In conclusion, the UpZEP gene may be involved in the response of U. prolifera to high-salt stress and can improve the high-salt tolerance of transgenic organisms.

Ulva prolifera, a type of green algae that can be consumed, was utilized in the production of an angiotensin-I converting enzyme (ACE) inhibitory peptide. The protein from the algae was isolated and subsequently hydrolyzed using a neutral protease. The resulting hydrolysate underwent several processes including Sephadex-G100 filtration chromatography, ultrafiltration, HPLC-Q-TOF-MS analysis, ADMET screening, UV spectrum detection test, molecular docking, and molecular dynamic simulation. Then, the ACE inhibitory peptide named KAF (IC50, 0.63 ± 0.26 µM) was identified. The effectiveness of this peptide in inhibiting ACE can be primarily attributed to two conventional hydrogen bonds. Additionally, it could activate endothelial nitric oxide synthase (eNOS) activity to promote the generation of nitric oxide (NO). Additionally, KAF primarily increased the intracellular calcium (Ca2+) level by acting on L-type Ca2+ channel (LTCC) and the ryanodine receptor (RyR) in the endoplasmic reticulum, and completed the activation of eNOS under the mediation of protein kinase B (Akt) signaling pathway. Our study has confirmed that KAF has the potential to be processed into pharmaceutical candidate functions on vasoconstriction.

ObjectiveTo analyze the risk factors of in-stent restenosis (ISR) after the first implantation of drug-eluting stent (DES) patients with coronary heart disease (CHD) and to establish a nomogram model to predict the risk of ISR.MethodsThis study retrospectively analyzed the clinical data of patients with CHD who underwent DES treatment for the first time at the Fourth Affiliated Hospital of Zhejiang University School of Medicine from January 2016 to June 2020. Patients were divided into an ISR group and a non-ISR (N-ISR) group according to the results of coronary angiography. The least absolute shrinkage and selection operator (LASSO) regression analysis was performed on the clinical variables to screen out the characteristic variables. Then we constructed the nomogram prediction model using conditional multivariate logistic regression analysis combined with the clinical variables selected in the LASSO regression analysis. Finally, the decision curve analysis, clinical impact curve, area under the receiver operating characteristic curve, and calibration curve were used to evaluate the nomogram prediction model's clinical applicability, validity, discrimination, and consistency. And we double-validate the prediction model using ten-fold cross-validation and bootstrap validation.ResultsIn this study, hypertension, HbA1c, mean stent diameter, total stent length, thyroxine, and fibrinogen were all predictive factors for ISR. We successfully constructed a nomogram prediction model using these variables to quantify the risk of ISR. The AUC value of the nomogram prediction model was 0.806 (95%CI: 0.739–0.873), indicating that the model had a good discriminative ability for ISR. The high quality of the calibration curve of the model demonstrated the strong consistency of the model. Moreover, the DCA and CIC curve showed the model's high clinical applicability and effectiveness.ConclusionsHypertension, HbA1c, mean stent diameter, total stent length, thyroxine, and fibrinogen are important predictors for ISR. The nomogram prediction model can better identify the high-risk population of ISR and provide practical decision-making information for the follow-up intervention in the high-risk population.

White matter is primarily composed of myelin and myelinated axons. Structural and functional completeness of myelin is critical for the reliable and efficient transmission of information. White matter injury has been associated with the development of many demyelinating diseases. Despite a variety of scientific advances aimed at promoting re-myelination, their benefit has proven at best to be marginal. Research suggests that the failure of the re-myelination process may be the result of an unfavorable microenvironment. Astrocytes, are the most ample and diverse type of glial cells in central nervous system (CNS) which display multiple functions for the cells of the oligodendrocytes lineage. As such, much attention has recently been drawn to astrocyte function in terms of white matter myelin repair. They are different in white matter from those in gray matter in specific regards to development, morphology, location, protein expression and other supportive functions. During the process of demyelination and re-myelination, the functions of astrocytes are dynamic in that they are able to change functions in accordance to different time points, triggers or reactive pathways resulting in vastly different biologic effects. They have pivotal effects on oligodendrocytes and other cell types in the oligodendrocyte lineage by serving as an energy supplier, a participant of immunological and inflammatory functions, a source of trophic factors and iron and a sustainer of homeostasis. Astrocytic impairment has been shown to be directly linked to the development of neuromyelities optica (NMO). In addition, astroctyes have also been implicated in other white matter conditions such as psychiatric disorders and neurodegenerative diseases such as Alzheimer's disease (AD), multiple sclerosis (MS) and amyotrophic lateral sclerosis (ALS). Inhibiting specifically detrimental signaling pathways in astrocytes while preserving their beneficial functions may be a promising approach for remyelination strategies. As such, the ability to manipulate astrocyte function represents a novel therapeutic approach that can repair the damaged myelin that is known to occur in a variety of white matter-related disorders. [ABSTRACT FROM AUTHOR]

In this study, the filling process of high aspect ratio through-silicon-vias (TSVs) under dense conditions using the electroplating method was efficiently achieved and optimized. Pulsed power was used as the experimental power source and the electroplating solution was prepared with various additive concentrations. Designed control variable experiments were conducted to determine the optimized method. In the control variable experiments, the relationship of multiple experimental variables, including current density (0.25–2 A/dm2), additive concentration (0.5–2 mL/L), and different shapes of TSVs (circle, oral, and square), were systematically analyzed. Considering the electroplating speed and quality, the influence of different factors on experimental results and the optimized parameters were determined. The results showed that increasing current density improved the electroplating speed but decreased the quality. Additives worked well, whereas their concentrations were controlled within a suitable range. The TSV shape also influenced the electroplating result. When the current density was 1.5 A/dm2 and the additive concentration was 1 mL/L, the TSV filling was relatively better. With the optimized parameters, 500-μm-deep TSVs with a high aspect ratio of 10:1 were fully filled in 20 h, and the via density reached 70/mm2. Finally, optimized parameters were adopted, and the electroplating of 1000-μm-deep TSVs with a diameter of 100 μm was completed in 45 h, which is the deepest and smallest through which a three-dimensional inductor has ever been successfully fabricated.