Interchain-expanded extra-large-pore zeolites.

Stable aluminosilicate zeolites with extra-large pores that are open through rings of more than 12 tetrahedra could be used to process molecules larger than those currently manageable in zeolite materials. However, until very recently1-3, they proved elusive. In analogy to the interlayer expansion of layered zeolite precursors4,5, we report a strategy that yields thermally and hydrothermally stable silicates by expansion of a one-dimensional silicate chain with an intercalated silylating agent that separates and connects the chains. As a result, zeolites with extra-large pores delimited by 20, 16 and 16 Si tetrahedra along the three crystallographic directions are obtained. The as-made interchain-expanded zeolite contains dangling Si-CH3 groups that, by calcination, connect to each other, resulting in a true, fully connected (except possible defects) three-dimensional zeolite framework with a very low density. Additionally, it features triple four-ring units not seen before in any type of zeolite. The silicate expansion-condensation approach we report may be amenable to further extra-large-pore zeolite formation. Ti can be introduced in this zeolite, leading to a catalyst that is active in liquid-phase alkene oxidations involving bulky molecules, which shows promise in the industrially relevant clean production of propylene oxide using cumene hydroperoxide as an oxidant.

HiFun: homology independent protein function prediction by a novel protein-language self-attention model.

Protein function prediction based on amino acid sequence alone is an extremely challenging but important task, especially in metagenomics/metatranscriptomics field, in which novel proteins have been uncovered exponentially from new microorganisms. Many of them are extremely low homology to known proteins and cannot be annotated with homology-based or information integrative methods. To overcome this problem, we proposed a Homology Independent protein Function annotation method (HiFun) based on a unified deep-learning model by reassembling the sequence as protein language. The robustness of HiFun was evaluated using the benchmark datasets and metrics in the CAFA3 challenge. To navigate the utility of HiFun, we annotated 2 212 663 unknown proteins and discovered novel motifs in the UHGP-50 catalog. We proved that HiFun can extract latent function related structure features which empowers it ability to achieve function annotation for non-homology proteins. HiFun can substantially improve newly proteins annotation and expand our understanding of microorganisms' adaptation in various ecological niches. Moreover, we provided a free and accessible webservice at http://www.unimd.org/HiFun, requiring only protein sequences as input, offering researchers an efficient and practical platform for predicting protein functions.

Similarity measures-based graph co-contrastive learning for drug-disease association prediction.

MOTIVATION: An imperative step in drug discovery is the prediction of drug-disease associations (DDAs), which tries to uncover potential therapeutic possibilities for already validated drugs. It is costly and time-consuming to predict DDAs using wet experiments. Graph Neural Networks as an emerging technique have shown superior capacity of dealing with DDA prediction. However, existing Graph Neural Networks-based DDA prediction methods suffer from sparse supervised signals. As graph contrastive learning has shined in mitigating sparse supervised signals, we seek to leverage graph contrastive learning to enhance the prediction of DDAs. Unfortunately, most conventional graph contrastive learning-based models corrupt the raw data graph to augment data, which are unsuitable for DDA prediction. Meanwhile, these methods could not model the interactions between nodes effectively, thereby reducing the accuracy of association predictions. RESULTS: A model is proposed to tap potential drug candidates for diseases, which is called Similarity Measures-based Graph Co-contrastive Learning (SMGCL). For learning embeddings from complicated network topologies, SMGCL includes three essential processes: (i) constructs three views based on similarities between drugs and diseases and DDA information; (ii) two graph encoders are performed over the three views, so as to model both local and global topologies simultaneously; and (iii) a graph co-contrastive learning method is introduced, which co-trains the representations of nodes to maximize the agreement between them, thus generating high-quality prediction results. Contrastive learning serves as an auxiliary task for improving DDA predictions. Evaluated by cross-validations, SMGCL achieves pleasing comprehensive performances. Further proof of the SMGCL's practicality is provided by case study of Alzheimer's disease. AVAILABILITY AND IMPLEMENTATION: https://github.com/Jcmorz/SMGCL.

Mechanism of the Low-Temperature Organic Removal from Imidazolium-Containing Zeolites by Ozone Treatment: Fluoride Retention in Double-4-Rings.

For zeolites synthesized using imidazolium cations, the organic matter can be extracted at very low temperatures (100 °C) using ozone. This is possible for zeolites with 12-ring or larger pores but requires higher temperatures in medium-pore zeolites. The first chemical events in this process occur fast, even at room temperature, and imply the loss of aromaticity likely by the formation of an adduct between ozone and the imidazole ring through carbons C4 and C5. Subsequent rupture of the imidazole ring provides smaller and more flexible fragments that can desorb more readily. This process has been studied experimentally, mainly through infrared spectroscopy, and theoretically by density functional theory. Amazingly, fluoride anions occluded in the small double-four-ring units (d4r) during the synthesis remain inside the cage throughout the whole process when the temperature is not too high (≤150 °C). However, fluoride in larger cages in MFI ends up bonded to silicon in penta or hexacoordinated units, likely out of the cages, after ozone treatment at 150 °C. For several germanosilicate zeolites, the process allows their subsequent degermanation to yield stable high-silica zeolites. Quaternary ammonium cations require harsher conditions that eventually also extract fluoride from zeolite cages, including the d4r unit.

Perfusate Neutrophil Gelatinase-Associated Lipocalin, Kidney Injury Molecular-1, Liver-Type Fatty Acid Binding Protein, and Interleukin-18 as Potential Biomarkers to Predict Delayed Graft Function and Long-Term Prognosis in Kidney Transplant Recipients: A Single-Center Retrospective Study.

BACKGROUND Delayed graft function (DGF) caused by ischemia-reperfusion injury is a common pathophysiological process that should be monitored by specific biomarkers in addition to serum creatinine. Thus, this single-center retrospective study aimed to investigate the association between levels of neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecular-1 (KIM-1), liver-type fatty acid binding protein (L-FABP), and interleukin-18 (IL-18) in DGF associated with acute kidney injury in kidney transplant recipients (KTRs) and estimated glomerular filtration rate (eGFR) at 3 years post-transplant. MATERIAL AND METHODS A total of 102 KTRs [14(13.7%) of DGF and 88(86.3%) of NON-DGF] were enrolled. DGF was defined as "dialysis is needed within 1 week after kidney transplantation". NGAL, KIM-1, L-FABP, and IL-18 were obtained from perfusate samples of donation-after-cardiac-death (DCD) kidneys, and measured by ELISA. RESULTS Compared to the NON-DGF group, KTRs in the DGF group had a statistically significant increase in levels of NGAL (P<0.001) and KIM-1 (P<0.001). Multiple logistic regression analyses showed that NGAL (OR=1.204, 95% CI 1.057-1.372, P=0.005) and KIM-1 (OR=1.248, CI=1.065-1.463, P=0.006) could be regarded as independent risk factors. The accuracy of NGAL and KIM-1 was 83.3% and 82.1%, respectively, calculated using the area under the receiver operating characteristic curve. Furthermore, the eGFR at 3 years post-transplant had a moderate negative correlation with NGAL (r=-0.208, P=0.036) and KIM-1 (r=-0.260, P=0.008). CONCLUSIONS Our results support those from previous studies showing that perfusate levels of NGAL and KIM-1 are associated with DGF in KTRs and also with reduced eGFR at 3 years post-transplant.

A promising Prognostic risk model for advanced renal cell carcinoma (RCC) with immune-related genes.

BACKGROUND: Renal cell carcinoma (RCC) is a third most common tumor of the urinary system. Nowadays, Immunotherapy is a hot topic in the treatment of solid tumors, especially for those tumors with pre-activated immune state. METHODS: In this study, we downloaded genomic and clinical data of RCC samples from The Cancer Genome Atlas (TCGA) database. Four immune-related genetic signatures were used to predict the prognosis of RCC by Cox regression analysis. Then we established a prognostic risk model consisting of the genes most related to prognosis from four signatures to value prognosis of the RCC samples via Kaplan-Meier (KM) survival analysis. An independent data from International Cancer Genome Consortium (ICGC) database were used to test the predictive stability of the model. Furthermore, we performed landscape analysis to assess the difference of gene mutant in the RCC samples from TCGA. Finally, we explored the correlation between the selected genes and the level of tumor immune infiltration via Tumor Immune Estimation Resource (TIMER) platform. RESULTS: We used four genetic signatures to construct prognostic risk models respectively and found that each of the models could divide the RCC samples into high- and low-risk groups with significantly different prognosis, especially in advanced RCC. A comprehensive prognostic risk model was constructed by 8 candidate genes from four signatures (HLA-B, HLA-A, HLA-DRA, IDO1, TAGAP, CIITA, PRF1 and CD8B) dividing the advanced RCC samples from TCGA database into high-risk and low-risk groups with a significant difference in cancer-specific survival (CSS). The stability of the model was verified by independent data from ICGC database. And the classification efficiency of the model was stable for the samples from different subgroups. Landscape analysis showed that mutation ratios of some genes were different between two risk groups. In addition, the expression levels of the selected genes were significantly correlated with the infiltration degree of immune cells in the advanced RCC. CONCLUSIONS: Sum up, eight immune-related genes were screened in our study to construct prognostic risk model with great predictive value for the prognosis of advanced RCC, and the genes were associated with infiltrating immune cells in tumors which have potential to conduct personalized treatment for advanced RCC.

Synthesis of Extra-Large Pore, Large Pore and Medium Pore Zeolites Using a Small Imidazolium Cation as the Organic Structure-Directing Agent.

One common strategy in the search for new zeolites is the use of organic structure-directing agents (OSDA). Typically, one seeks to achieve a high specificity in the structure-directing effect of the OSDA. This study shows, however, that an OSDA lacking strong specificity towards any particular zeolite may provide opportunities for discovery when other synthesis parameters are systematically screened. Thus, 1-methyl-2-ethyl-3-n-propylimidazolium has allowed to crystallize the new large/medium pore zeolite HPM-16 as well as the recently reported extra-large pore -SYT and the medium/small pore and chiral STW. The sophisticated OSDA originally affording -SYT and the new simple OSDA have very little in common, both in terms of size, shape and flexibility, while both may still direct the synthesis of the same zeolite. In fact, molecular simulations show that the new OSDA is located in three different positions of the -SYT structure, including the discrete 8MR where the original organic could not fit.

HPM-16, a Stable Interrupted Zeolite with a Multidimensional Mixed Medium-Large Pore System Containing Supercages.

HPM-16 is a highly porous germanosilicate zeolite with an interrupted framework that contains a three-dimensional system of 12+10×10(12)×12+10-membered ring (MR) pores. The 10(12) MR pore in the b direction is a 10 MR pore with long 12 MR stretches forming 30 Šlong tubular supercages. Along one direction the 10 MR pores are fused, meaning that the separation between adjacent pores consists of a single tetrahedron that is, additionally, connected to only three additional tetrahedra (a Q3 ). These fused pores are thus decorated by T-OH groups along the whole diffusion path, creating a hydrophilic region embedded in an otherwise essentially hydrophobic environment. The structure is built from highly porous 12×12×12 MR uninterrupted layers that are connected to each other through Q3 producing a second system of 10×10×10 MR pores. This zeolite can be extensively degermanated yielding a material with high thermal stability, despite its interrupted nature.

HPM-14: A New Germanosilicate Zeolite with Interconnected Extra-Large Pores Plus Odd-Membered and Small Pores*.

HPM-14 is a new extra-large pore zeolite synthesized using imidazolium-based organic structure-directing agents (SDAs), fluoride anions, and germanium and silicon as tetrahedral components of the framework. Owing to the presence of stacking disorder, the structure elucidation of HPM-14 was challenging, and different techniques were necessary to clarify the details of the structure and to understand the nature of the disorder. The structure has been solved by three-dimensional electron-diffraction technique (3D ED) and consists of an intergrowth of two polymorphs possessing a three-dimensional channel system, including an extra-large pore opened through windows made up of sixteen tetrahedral atoms (16-membered ring, 16MR) as well as two additional sets of odd-membered (9MR) and small (8MR) pores. The intergrowth has been studied by scanning transmission electron microscopy (Cs -STEM) and powder X-ray diffraction simulations (DIFFaX), which show a large predominance of the monoclinic polymorph A.

IDM-1: A Zeolite with Intersecting Medium and Extra-Large Pores Built as an Expansion of Zeolite MFI.

IDM-1 is a new silica zeolite with an ordered and well-defined framework constructed by alternating pentasil layers and interrupted layers, giving rise to an intersecting system of straight medium pores and undulating extra-large lobed pores. This unique structure was solved by rotation electron diffraction and refined against synchrotron powder X-ray diffraction data. Despite the presence of both Si(OSi)3 (OH) and Si(OSi)2 (OH)2 sites, this new zeolite presents high thermal stability, withstanding calcination even to 1000 °C. The location of defects at specific sites of the structure results in alternating hydrophobic SiO2 and hydrophilic SiO(2-x) (OH)2x intracrystalline regions. This peculiar combination of intersecting medium and extra-large pores and alternating regions of different chemical character may provide this zeolite with unique catalytic properties.

An Extra-Large-Pore Pure Silica Zeolite with 16×8×8-Membered Ring Pore Channels Synthesized using an Aromatic Organic Directing Agent.

Extra-large-pore zeolites for processing large molecules have long been sought after by both the academia and industry. However, the synthesis of these materials, particularly extra-large-pore pure silica zeolites, remains a big challenge. Herein we report the synthesis of a new extra-large-pore silica zeolite, designated NUD-6, by using an easily synthesized aromatic organic cation as structure-directing agent. NUD-6 possesses an intersecting 16×8×8-membered ring pore channel system constructed by four-connected (Q4 ) and unusual three-connected (Q3 ) silicon species. The organic cations in NUD-6 can be removed in nitric acid to yield a porous material with high surface area and pore volume. The synthesis of NUD-6 presents a feasible means to prepare extra-large pore silica zeolites by using assembled aromatic organic cations as structure-directing agents.

Nuclear delivery of plasmid DNA determines the efficiency of gene expression.

As a cationic non-viral gene delivery vector, poly(agmatine/ N, N'-cystamine-bis-acrylamide) (AGM-CBA) showed significantly higher plasmid DNA (pDNA) transfection ability than polyethylenimine (PEI) in NIH/3T3 cells. The transfection expression of AGM-CBA/pDNA polyplexes was found to have a non-linear relationship with AGM-CBA/pDNA weight ratios. To further investigate the mechanism involved in the transfection process of poly(AGM-CBA), we used pGL3-control luciferase reporter gene (pLUC) as a reporter pDNA in this study. The distribution of pLUC in NIH/3T3 cells and nuclei after AGM-CBA/pLUC and PEI/pLUC transfection were determined by quantitative polymerase chain reaction (qPCR) analysis. The intracellular trafficking of the polyplexes was evaluated by cellular uptake and nuclei delivery of pLUC, and the intracellular availability was evaluated by the ratio of transfection expression to the numbers of pLUC delivered in nuclei. It was found that pLUC intracellular trafficking did not have any correlation with the transfection expression, while an excellent correlation was found between the nuclei pLUC availability and transfection expression. These results suggested that the intracellular availability of pLUC in nuclei was the rate-limiting step for pLUC transfection expression. Further optimization of the non-viral gene delivery system can be focused on the improvement of gene intracellular availability.

Crystallization of a Novel Germanosilicate ECNU-16 Provides Insights into the Space-Filling Effect on Zeolite Crystal Symmetry.

Synthesis of new zeolites involving organic molecules relies heavily on the trial-and-error approach, because it is difficult to interpret the determining effects of organics on zeolite crystal symmetry. Here, the intrinsic relationships among the space-filling of organics, included volume of channels, and zeolite crystal symmetry, are systematically demonstrated by experimental and computational means. Under controlled conditions, the "dimer" and "monomer" organics of 1-ethyl-3-methylimidazolium selectively direct different, but related, germanosilicates, the ECNU-16 with a new topology and the existing IM-16 with the UOS topology, respectively. The comprehensive computational study reveals that the zeolite phase selectivity is determined by the unique space-filling behavior of the "dimer" and "monomer" organics, which is closely correlated to their rotation freedom, as well as the included volume of host zeolite channels. The elucidation of this crucial space-filling effect from the fundamental viewpoint will provide new guidelines for the rational design and synthesis of new zeolites in future.

A Stable Extra-Large-Pore Zeolite with Intersecting 14- and 10-Membered-Ring Channels.

The development of inorganic frameworks with extra-large pores (larger than 12-membered rings) has attracted considerable attention because of their potential applications in catalysis, the separation of large molecules, and so forth. We herein report the synthesis of the new extra-large-pore zeolite NUD-2 by using the supramolecular self-assembly of simple aromatic organic cations as structure-directing agents (SDAs). NUD-2 is a high-silicon-content germanosilicate with interconnecting 14×10-membered-ring channels. The SDAs in NUD-2 can be removed by calcination in air at 550 °C to yield permanent pores with a BET surface area of 500 m(2) g(-1) . Both germanium and organic cations in NUD-2 can also be removed by treatment with acid at lower temperature, thus not only affording recycling of germanium and SDAs, but also providing a highly stable siliceous zeolite. In addition, aluminum ions can be incorporated into the framework of NUD-2. The NUD-2 structure is yet another extra-large-pore zeolite synthesized by using the supramolecular self-assembling templating approach, thus demonstrating that this approach is a general and applicable strategy for synthesis of new large- and extra-large-pore zeolites.

Intolerance of uncertainty and mental health in China "Post-pandemic" age: The mediating role of difficulties in emotion regulation.

The Chinese government adjusted its national epidemic prevention and control policy in December 2022 after the worldwide declaration of COVID-19 as a common influenza. After the policy adjustment, there has been widespread infection in China, which has brought a lot of uncertainty to the lives and studies of Chinese university students. This study focused on the impact of the intolerance of uncertainty for COVID-19 (IUC) on the emotional and mental health of college students in China "Post-pandemic" age. This study examined the mediating role of difficulties in emotion regulation (DER) between IUC and mental health (MH). 1,281 university students in China were surveyed using the intolerance of uncertainty for COVID-19 scale, the difficulties in emotion regulation scale and the mental health scale. A structural equation model was used to test the hypothesis model, and it was shown that IUC had a significant negative effect on the MH of college students and a significant positive effect on the DER. DER had a significant negative effect on the MH, and DER had a complete mediation effect between IUC and MH. The findings of this study enrich our understanding of the influencing factors of mental health of university students under the background of post-epidemic in China, and provide practical reference for universities on how to prevent mental health problems under the current uncertain environment in China.

Effects of 17ß-Estradiol Pollution on Microbial Communities and Methane Emissions in Aerobic Water Bodies.

17ß-Estradiol (E2) is a widely present trace pollutant in aquatic environments. However, its impact on microbial communities in aerobic lake waters, which are crucial for methane (CH4) production, remains unclear. This study conducted an E2 contamination experiment by constructing laboratory-simulated aerobic microecosystems. Using 16S rRNA high-throughput sequencing, the effects of E2 on bacterial and archaeal communities were systematically examined. Combined with gas chromatography, the patterns and mechanisms of E2's impact on CH4 emissions in aerobic aquatic systems were uncovered for the first time. Generally, E2 contamination increased the randomness of bacterial and archaeal community assemblies and weakened microbial interactions. Furthermore, changes occurred in the composition and ecological functions of bacterial and archaeal communities under E2 pollution. Specifically, two days after exposure to E2, the relative abundance of Proteobacteria in the low-concentration (L) and high-concentration (H) groups decreased by 6.99% and 4.01%, respectively, compared to the control group (C). Conversely, the relative abundance of Planctomycetota was 1.81% and 1.60% higher in the L and H groups, respectively. E2 contamination led to an increase in the relative abundance of the methanogenesis functional group and a decrease in that of the methanotrophy functional group. These changes led to an increase in CH4 emissions. This study comprehensively investigated the ecotoxicological effects of E2 pollution on microbial communities in aerobic water bodies and filled the knowledge gap regarding aerobic methane production under E2 contamination.

Community Structure, Drivers, and Potential Functions of Different Lifestyle Viruses in Chaohu Lake.

Viruses, as the most prolific entities on Earth, constitute significant ecological groups within freshwater lakes, exerting pivotal ecological roles. In this study, we selected Chaohu Lake, a representative eutrophic freshwater lake in China, as our research site to explore the community distribution, driving mechanisms, and potential ecological functions of diverse viral communities, the intricate virus-host interaction systems, and the overarching influence of viruses on global biogeochemical cycling.

NiOx Nanoparticles Hole-Transporting Layer Regulated by Ionic Radius-Controlled Doping and Reductive Agent for Organic Solar Cells with Efficiency of 19.18.

Nickel oxide (NiOx ) has garnered considerable attention as a prospective hole-transporting layer (HTL) in organic solar cells (OSCs), offering a potential solution to the stability challenges posed by traditional HTL, PEDOT:PSS, arising from acidity and hygroscopicity. Nevertheless, the lower work function (WF) of NiOx relative to donor polymers reduces charge injection efficiency in OSCs. Herein, NiOx nanoparticles are tailored through rare earth doping to optimize WF and the impact of ionic radius on their electronic properties is explored. Lanthanum (La3+ ) and yttrium (Y3+ ) ions, with larger ionic radii, are effectively doped at 1 and 3%, respectively, while scandium (Sc3+ ), with a smaller ion radius, allows enhanced 5% doping. Higher doping ratios significantly enhance WF of NiOx . A 5% Sc3+ doping raises WF to 4.99 eV from 4.77 eV for neat NiOx while maintaining high conductivity. Consequently, using 5% Sc-doped NiOx as HTL improves the power conversion efficiency (PCE) of OSCs to 17.13%, surpassing the 15.64% with the neat NiOx . Further enhancement to 18.42% is achieved by introducing the reductant catechol, outperforming the PEDOT:PSS-based devices. Additionally, when employed in a ternary blend system (D18:N3:F-BTA3), an impressive PCE of 19.18 % is realized, top-performing among reported OSCs utilizing solution-processed inorganic nanoparticles.

Marker Density and Models to Improve the Accuracy of Genomic Selection for Growth and Slaughter Traits in Meat Rabbits.

The selection and breeding of good meat rabbit breeds are fundamental to their industrial development, and genomic selection (GS) can employ genomic information to make up for the shortcomings of traditional phenotype-based breeding methods. For the practical implementation of GS in meat rabbit breeding, it is necessary to assess different marker densities and GS models. Here, we obtained low-coverage whole-genome sequencing (lcWGS) data from 1515 meat rabbits (including parent herd and half-sibling offspring). The specific objectives were (1) to derive a baseline for heritability estimates and genomic predictions based on randomly selected marker densities and (2) to assess the accuracy of genomic predictions for single- and multiple-trait linear mixed models. We found that a marker density of 50 K can be used as a baseline for heritability estimation and genomic prediction. For GS, the multi-trait genomic best linear unbiased prediction (GBLUP) model results in more accurate predictions for virtually all traits compared to the single-trait model, with improvements greater than 15% for all of them, which may be attributed to the use of information on genetically related traits. In addition, we discovered a positive correlation between the performance of the multi-trait GBLUP and the genetic correlation between the traits. We anticipate that this approach will provide solutions for GS, as well as optimize breeding programs, in meat rabbits.

Spinal interleukin-16 mediates inflammatory pain via promoting glial activation.

Proinflammatory cytokines are crucial contributors to neuroinflammation in the development of chronic pain. Here, we identified il16, which encodes interleukin-16 (IL-16), as a differentially expressed gene in spinal dorsal horn of a complete Freund's Adjuvant (CFA) inflammatory pain model in mice by RNA sequencing. We further investigated whether and how IL-16 regulates pain transmission in the spinal cord and contributes to the development of inflammatory pain hypersensitivity. RNA sequencing and bioinformatics analysis revealed elevated IL-16 transcript levels in the spinal dorsal horn after CFA injection. This increase was further confirmed by qPCR, immunofluorescence, and western blotting. Knockdown of IL-16 by intrathecal injection of IL-16 siRNA not only attenuated CFA-induced mechanical and thermal pain hypersensitivity, but also inhibited enhanced c-fos expression and glial activation in the spinal dorsal horn in male mice injected with CFA. Moreover, exogenous IL-16 induced nociceptive responses and increased c-fos expression and glial activation in spinal dorsal horn. This effect was largely impaired when CD4, the binding receptor for IL-16, was inhibited. In addition, CD4 expression was upregulated in the spinal dorsal horn after CFA injection and CD4 was present in microglia and in contact with astrocytes and activated spinal neurons. Taken together, these results suggest that enhanced IL-16-CD4 signaling triggers pain and activates microglia and astrocytes in the spinal dorsal horn, thus contributing to inflammatory pain. IL-16 may serve as a promising target for the treatment of inflammatory pain.