Enhancer RNA m6A methylation facilitates transcriptional condensate formation and gene activation.

The mechanistic understanding of nascent RNAs in transcriptional control remains limited. Here, by a high sensitivity method methylation-inscribed nascent transcripts sequencing (MINT-seq), we characterized the landscapes of N6-methyladenosine (m6A) on nascent RNAs. We uncover heavy but selective m6A deposition on nascent RNAs produced by transcription regulatory elements, including promoter upstream antisense RNAs and enhancer RNAs (eRNAs), which positively correlates with their length, inclusion of m6A motif, and RNA abundances. m6A-eRNAs mark highly active enhancers, where they recruit nuclear m6A reader YTHDC1 to phase separate into liquid-like condensates, in a manner dependent on its C terminus intrinsically disordered region and arginine residues. The m6A-eRNA/YTHDC1 condensate co-mixes with and facilitates the formation of BRD4 coactivator condensate. Consequently, YTHDC1 depletion diminished BRD4 condensate and its recruitment to enhancers, resulting in inhibited enhancer and gene activation. We propose that chemical modifications of eRNAs together with reader proteins play broad roles in enhancer activation and gene transcriptional control.

Enhancer release and retargeting activates disease-susceptibility genes.

The functional engagement between an enhancer and its target promoter ensures precise gene transcription1. Understanding the basis of promoter choice by enhancers has important implications for health and disease. Here we report that functional loss of a preferred promoter can release its partner enhancer to loop to and activate an alternative promoter (or alternative promoters) in the neighbourhood. We refer to this target-switching process as 'enhancer release and retargeting'. Genetic deletion, motif perturbation or mutation, and dCas9-mediated CTCF tethering reveal that promoter choice by an enhancer can be determined by the binding of CTCF at promoters, in a cohesin-dependent manner-consistent with a model of 'enhancer scanning' inside the contact domain. Promoter-associated CTCF shows a lower affinity than that at chromatin domain boundaries and often lacks a preferred motif orientation or a partnering CTCF at the cognate enhancer, suggesting properties distinct from boundary CTCF. Analyses of cancer mutations, data from the GTEx project and risk loci from genome-wide association studies, together with a focused CRISPR interference screen, reveal that enhancer release and retargeting represents an overlooked mechanism that underlies the activation of disease-susceptibility genes, as exemplified by a risk locus for Parkinson's disease (NUCKS1-RAB7L1) and three loci associated with cancer (CLPTM1L-TERT, ZCCHC7-PAX5 and PVT1-MYC).

Emerging Atomistic Modeling Methods for Heterogeneous Electrocatalysis.

Heterogeneous electrocatalysis lies at the center of various technologies that could help enable a sustainable future. However, its complexity makes it challenging to accurately and efficiently model at an atomic level. Here, we review emerging atomistic methods to simulate the electrocatalytic interface with special attention devoted to the components/effects that have been challenging to model, such as solvation, electrolyte ions, electrode potential, reaction kinetics, and pH. Additionally, we review relevant computational spectroscopy methods. Then, we showcase several examples of applying these methods to understand and design catalysts relevant to green hydrogen. We also offer experimental views on how to bridge the gap between theory and experiments. Finally, we provide some perspectives on opportunities to advance the field.

REME: an integrated platform for reaction enzyme mining and evaluation.

A key challenge in pathway design is finding proper enzymes that can be engineered to catalyze a non-natural reaction. Although existing tools can identify potential enzymes based on similar reactions, these tools encounter several issues. Firstly, the calculated similar reactions may not even have the same reaction type. Secondly, the associated enzymes are often numerous and identifying the most promising candidate enzymes is difficult due to the lack of data for evaluation. Thirdly, existing web tools do not provide interactive functions that enable users to fine-tune results based on their expertise. Here, we present REME (https://reme.biodesign.ac.cn/), the first integrated web platform for reaction enzyme mining and evaluation. Combining atom-to-atom mapping, atom type change identification, and reaction similarity calculation enables quick ranking and visualization of reactions similar to an objective non-natural reaction. Additional functionality enables users to filter similar reactions by their specified functional groups and candidate enzymes can be further filtered (e.g. by organisms) or expanded by Enzyme Commission number (EC) or sequence homology. Afterward, enzyme attributes (such as kcat, Km, optimal temperature and pH) can be assessed with deep learning-based methods, facilitating the swift identification of potential enzymes that can catalyze the non-natural reaction.

CAVE: a cloud-based platform for analysis and visualization of metabolic pathways.

Flux balance analysis (FBA) is an important method for calculating optimal pathways to produce industrially important chemicals in genome-scale metabolic models (GEMs). However, for biologists, the requirement of coding skills poses a significant obstacle to using FBA for pathway analysis and engineering target identification. Additionally, a time-consuming manual drawing process is often needed to illustrate the mass flow in an FBA-calculated pathway, making it challenging to detect errors or discover interesting metabolic features. To solve this problem, we developed CAVE, a cloud-based platform for the integrated calculation, visualization, examination and correction of metabolic pathways. CAVE can analyze and visualize pathways for over 100 published GEMs or user-uploaded GEMs, allowing for quicker examination and identification of special metabolic features in a particular GEM. Additionally, CAVE offers model modification functions, such as gene/reaction removal or addition, making it easy for users to correct errors found in pathway analysis and obtain more reliable pathways. With a focus on the design and analysis of optimal pathways for biochemicals, CAVE complements existing visualization tools based on manually drawn global maps and can be applied to a broader range of organisms for rational metabolic engineering. CAVE is available at https://cave.biodesign.ac.cn/.

Hereditary retinoblastoma iPSC model reveals aberrant spliceosome function driving bone malignancies.

The RB1 gene is frequently mutated in human cancers but its role in tumorigenesis remains incompletely defined. Using an induced pluripotent stem cell (iPSC) model of hereditary retinoblastoma (RB), we report that the spliceosome is an up-regulated target responding to oncogenic stress in RB1-mutant cells. By investigating transcriptomes and genome occupancies in RB iPSC­derived osteoblasts (OBs), we discover that both E2F3a, which mediates spliceosomal gene expression, and pRB, which antagonizes E2F3a, coregulate more than one-third of spliceosomal genes by cobinding to their promoters or enhancers. Pharmacological inhibition of the spliceosome in RB1-mutant cells leads to global intron retention, decreased cell proliferation, and impaired tumorigenesis. Tumor specimen studies and genome-wide TCGA (The Cancer Genome Atlas) expression profile analyses support the clinical relevance of pRB and E2F3a in modulating spliceosomal gene expression in multiple cancer types including osteosarcoma (OS). High levels of pRB/E2F3a­regulated spliceosomal genes are associated with poor OS patient survival. Collectively, these findings reveal an undiscovered connection between pRB, E2F3a, the spliceosome, and tumorigenesis, pointing to the spliceosomal machinery as a potentially widespread therapeutic vulnerability of pRB-deficient cancers.

Advances in morphology-controlled alumina and its supported Pd catalysts: synthesis and applications.

Alumina materials, as one of the cornerstones of the modern chemical industry, possess physical and chemical properties that include excellent mechanical strength and structure stability, which also make them highly suitable as catalyst supports. Alumina-supported Pd-based catalysts with the advantages of exceptional catalytic performance, flexible regulated surface metal/acid sites, and good regeneration ability have been widely used in many traditional chemical industry fields and have also shown great application prospects in emerging fields. This review aims to provide an overview of the recent advances in alumina and its supported Pd-based catalysts. Specifically, the synthesis strategies, morphology transformation mechanisms, and structural properties of alumina with various morphologies are comprehensively summarized and discussed in-depth. Then, the preparation approaches of Pd/Al2O3 catalysts (impregnation, precipitation, and other emerging methods), as well as the metal-support interactions (MSIs), are revisited. Moreover, Some promising applications have been chosen as representative reactions in fine chemicals, environmental purification, and sustainable development fields to highlight the universal functionality of the alumina-supported Pd-based catalysts. The role of the Pd species, alumina support, promoters, and metal-support interactions in the enhancement of catalytic performance are also discussed. Finally, some challenges and upcoming opportunities in the academic and industrial application of the alumina and its supported Pd-based are presented and put forward.

Efficacy and predictors of immune checkpoint inhibitors in patients with gallbladder cancer.

Immune checkpoint inhibitors (ICIs) have shown promising efficacy in multiple cancers including biliary tract cancers (BTCs). However, the data focusing on the efficacy of ICIs in patients with gallbladder cancer (GBC) is still limited. In this study, we aim to assess the efficacy of ICIs in GBC and explore the clinicopathologic and molecular markers associated with ICI benefit. We retrospective analyzed 69 GBC patients who had received ICI therapy between January 2016 and December 2020. Tumor samples were obtained for genomic sequencing and immunohistochemical analysis. The median progression-free survival (PFS) and overall survival (OS) was 4.4 months and 8.5 months, respectively. Multivariate analysis indicated that alcohol intake history, carcinoma embryonic antigen (CEA) level ≥100 U/mL, and cutaneous immune-related adverse events (irAEs) were independent prognostic factors for PFS. CEA level ≥100 U/mL and cutaneous irAEs were independent prognostic factors for OS. The objective response rate and disease control rate (DCR) were 15.9% and 37.7%, respectively. Patients with cutaneous irAEs, high CD8+ T cell infiltrated or immune inflamed GBCs had higher DCR. Patients with high CD8+ T cell infiltrated or immune inflamed GBCs also had a notably improved prognosis. These results suggest that ICIs were effective in patients with GBC. High CEA level, cutaneous irAEs, high CD8+ T cell infiltration, and immune inflamed phenotype could be useful for predicting the efficacy of ICIs in GBC.

Impacts of continuous cropping on the rhizospheric and endospheric microbial communities and root exudates of Astragalus mongholicus.

Astragalus mongholicus is a medicinal plant that is known to decrease in quality in response to continuous cropping. However, the differences in the root-associated microbiome and root exudates in the rhizosphere soil that may lead to these decreases are barely under studies. We investigated the plant biomass production, root-associated microbiota, and root exudates of A. mongholicus grown in two different fields: virgin soil (Field I) and in a long-term continuous cropping field (Field II). Virgin soil is soil that has never been cultivated for A. mongholicus. Plant physiological measurements showed reduced fresh and dry weight of A. mongholicus under continuous cropping conditions (i.e. Field II). High-throughput sequencing of the fungal and bacterial communities revealed differences in fungal diversity between samples from the two fields, including enrichment of potentially pathogenic fungi in the roots of A. mongholicus grown in Field II. Metabolomic analysis yielded 20 compounds in A. mongholicus root exudates that differed in relative abundance between rhizosphere samples from the two fields. Four of these metabolites (2-aminophenol, quinic acid, tartaric acid, and maleamate) inhibited the growth of A. mongholicus, the soil-borne pathogen Fusarium oxysporum, or both. This comprehensive analysis enhances our understanding of the A. mongholicus microbiome, root exudates, and interactions between the two in response to continuous cropping. These results offer new information for future design of effective, economical approaches to achieving food security.

Engineering Reversible Lattice Structure for High-Capacity Co-Free Li-Rich Cathodes with Negligible Capacity Degradation.

Co-free Li-rich Mn-based cathode materials are garnering great interest because of high capacity and low cost. However, their practical application is seriously hampered by the irreversible oxygen escape and the poor cycling stability. Herein, a reversible lattice adjustment strategy is proposed by integrating O vacancies and B doping. B incorporation increases TM─O (TM: transition metal) bonding orbitals whereas decreases the antibonding orbitals. Moreover, B doping and O vacancies synergistically increase the crystal orbital bond index values enhancing the overall covalent bonding strength, which makes TM─O octahedron more resistant to damage and enables the lattice to better accommodate the deformation and reaction without irreversible fracture. Furthermore, Mott-Hubbard splitting energy is decreased due to O vacancies, facilitating electron leaps, and enhancing the lattice reactivity and capacity. Such a reversible lattice, more amenable to deformation and forestalling fracturing, markedly improves the reversibility of lattice reactions and mitigates TM migration and the irreversible oxygen redox which enables the high cycling stability and high rate capability. The modified cathode demonstrates a specific capacity of 200 mAh g-1 at 1C, amazingly sustaining the capacity for 200 cycles without capacity degradation. This finding presents a promising avenue for solving the long-term cycling issue of Li-rich cathode.

Membrane Design Principles for Ion-Selective Electrodialysis: An Analysis for Li/Mg Separation.

Selective electrodialysis (ED) is a promising membrane-based process to separate Li+ from Mg2+, which is the most critical step for Li extraction from brine lakes. This study theoretically compares the ED-based Li/Mg separation performance of different monovalent selective cation exchange membranes (CEMs) and nanofiltration (NF) membranes at the coupon scale using a unified mass transport model, i.e., a solution-friction model. We demonstrated that monovalent selective CEMs with a dense surface thin film like a polyamide film are more effective in enhancing the Li/Mg separation performance than those with a loose but highly charged thin film. Polyamide film-coated CEMs when used in ED have a performance similar to that of polyamide-based NF membranes when used in NF. NF membranes, when expected to replace monovalent selective CEMs in ED for Li/Mg separation, will require a thin support layer with low tortuosity and high porosity to reduce the internal concentration polarization. The coupon-scale performance analysis and comparison provide new insights into the design of composite membranes used for ED-based selective ion-ion separation.

Strong electron-phonon coupling and high lattice thermal conductivity in half-Heusler thermoelectric materials.

Traditional half-Heusler thermoelectric materials, identified as 18-electron compounds, are characterized by the high power factor and the high lattice thermal conductivity. Interestingly, the emerging 19-electron half-Heusler compounds were also found to be promising thermoelectric materials, but with a 5-10 times lower lattice thermal conductivity. Since the two kinds of compounds have similar chemical and physical structures, such as TiCoSb and VCoSb, the large difference in lattice thermal conductivity is a puzzling question. Here, we present a theoretical study to clarify the lattice thermal transport in half-Heusler thermoelectric materials. Based on electronic band structure analysis, we show that the two transition-metal elements in half-Heusler compounds form the strong and direct d-d interaction that is responsible for the high lattice thermal conductivity of 18-electron compounds. In 19-electron half-Heusler compounds, however, the extra valence electron enters the d-d antibonding states, which significantly weakens the atomic bond strength, leading to a large decrease in the cohesive energy. The resulting softened acoustic phonons enhance the phonon-phonon scattering, and thus reduce the lattice thermal conductivity significantly. By constructing an artificial 18-e compound V0.5Sc0.5CoSb, it is proved that the one less electron relative to VCoSb increases the lattice thermal conductivity significantly.

Inhibition of TGF-ß1/Smad3 signaling by compound 5aa: A potential treatment for idiopathic pulmonary fibrosis.

The incidence of idiopathic pulmonary fibrosis (IPF) has been steadily increasing each year, posing significant challenges in its treatment. In this study, we conducted the design and synthesis of 23 new inhibitors that specifically target the TGF-ß1/Smad3 pathway. Initially, we employed a cell model of TGF-ß-induced pulmonary fibrosis, using cell survival rate and HYP expression as indicators to identify the potent ingredient 5aa, which demonstrated significant anti-pulmonary fibrosis activity. Subsequently, we induced mice with bleomycin (BLM) to establish an experimental animal model of pulmonary fibrosis, and evaluated the pharmacodynamics of 5aa in vivo against pulmonary fibrosis. The alterations in HYP and collagen levels in BLM-induced pulmonary fibrosis mice were analyzed using ELISA and immunohistochemistry techniques. The results indicated that compound 5aa effectively suppressed the fibrotic response induced by TGF-ß1, inhibited the expression of the fibrotic marker α-SMA, and hindered the EMT process in NIH3T3 cells. Additionally, oral administration of 5aa demonstrated significant therapeutic effects in a mouse model of IPF, comparable to the established drug Nintedanib. Moreover, compound 5aa exhibited higher bioavailability in vivo compared to Nintedanib. These collective outcomes suggest that 5aa holds promise as a potential inhibitor of TGF-ß1/Smad3 signaling for the treatment of IPF.

Heteryunine A, an amidated tryptophan-catechin-spiroketal hybrid with antifibrotic activity from Heterosmilax yunnanensis.

An unprecedented spiro-C-glycoside adduct, heteryunine A (1), along with two uncommon alkaloids featuring a 2,3-diketopiperazine skeleton, heterpyrazines A (2) and B (3), were discovered in the roots of Heterosmilax yunnanensis. The detailed spectroscopic analysis helped to clarify the planar structures of these compounds. Compound 1, containing 7 chiral centers, features a catechin fused with a spiroketal and connects with a tryptophan derivative by a CC bond. Its complex absolute configuration was elucidated by rotating frame overhauser enhancement spectroscopy (ROESY), specific rotation, and the 13C nuclear magnetic resonance (NMR) and electronic circular dichroism (ECD) calculation. The possible biosynthetic routes for 1 were deduced. Compounds 1 and 2 showed significant antifibrotic effects and further research revealed that they inhibited the activation, migration and proliferation of hepatic stellate cells (HSCs) through suppressing the activity of Ras homolog family member A (RhoA).

Analysis of schizophrenia-associated genetic markers in the HLA region as risk factors for tardive dyskinesia.

OBJECTIVES: The pathology of Tardive Dyskinesia (TD) has yet to be fully understood, but there have been proposed hypotheses for the cause of this condition. Our team previously reported a possible association of TD with the Complement Component C4 gene in the HLA region. In this study, we explored the HLA region further by examining two previously identified schizophrenia-associated HLA-region single-nucleotide polymorphisms (SNPs), namely rs13194504 and rs210133. METHODS: The SNPs rs13194504 and rs210133 were tested for association with the occurrence and severity of TD in a sample of 172 schizophrenia patients who were recruited for four studies from three different clinical sites in Canada and USA. RESULTS: The rs13194504 AA genotype was associated with decreased severity for TD as measured by Abnormal Involuntary Movement Scale (AIMS) scores (p = 0.047) but not for TD occurrence. SNP rs210133 was not significantly associated with either TD occurrence or AIMS scores. CONCLUSION: Our findings suggest that the rs13194504 AA genotype may play a role in TD severity, while SNP rs210133 may not have a major role in the risk or severity of TD.

ERMer: a serverless platform for navigating, analyzing, and visualizing Escherichia coli regulatory landscape through graph database.

Cellular regulation is inherently complex, and one particular cellular function is often controlled by a cascade of different types of regulatory interactions. For example, the activity of a transcription factor (TF), which regulates the expression level of downstream genes through transcriptional regulation, can be regulated by small molecules through compound-protein interactions. To identify such complex regulatory cascades, traditional relational databases require ineffective additional operations and are computationally expensive. In contrast, graph databases are purposefully developed to execute such deep searches efficiently. Here, we present ERMer (E. coli Regulation Miner), the first cloud platform for mining the regulatory landscape of Escherichia coli based on graph databases. Combining the AWS Neptune graph database, AWS lambda function, and G6 graph visualization engine enables quick search and visualization of complex regulatory cascades/patterns. Users can also interactively navigate the E. coli regulatory landscape through ERMer. Furthermore, a Q&A module is included to showcase the power of graph databases in answering complex biological questions through simple queries. The backend graph model can be easily extended as new data become available. In addition, the framework implemented in ERMer can be easily migrated to other applications or organisms. ERMer is available at https://ermer.biodesign.ac.cn/.

AutoESD: a web tool for automatic editing sequence design for genetic manipulation of microorganisms.

Advances in genetic manipulation and genome engineering techniques have enabled on-demand targeted deletion, insertion, and substitution of DNA sequences. One important step in these techniques is the design of editing sequences (e.g. primers, homologous arms) to precisely target and manipulate DNA sequences of interest. Experimental biologists can employ multiple tools in a stepwise manner to assist editing sequence design (ESD), but this requires various software involving non-standardized data exchange and input/output formats. Moreover, necessary quality control steps might be overlooked by non-expert users. This approach is low-throughput and can be error-prone, which illustrates the need for an automated ESD system. In this paper, we introduce AutoESD (https://autoesd.biodesign.ac.cn/), which designs editing sequences for all steps of genetic manipulation of many common homologous-recombination techniques based on screening-markers. Notably, multiple types of manipulations for different targets (CDS or intergenic region) can be processed in one submission. Moreover, AutoESD has an entirely cloud-based serverless architecture, offering high reliability, robustness and scalability which is capable of parallelly processing hundreds of design tasks each having thousands of targets in minutes. To our knowledge, AutoESD is the first cloud platform enabling precise, automated, and high-throughput ESD across species, at any genomic locus for all manipulation types.

Two-dimensional fractal nanocrystals templating for substantial performance enhancement of polyamide nanofiltration membrane.

In this study, we report the emergence of two-dimensional (2D) branching fractal structures (BFS) in the nanoconfinement between the active and the support layer of a thin-film-composite polyamide (TFC-PA) nanofiltration membrane. These BFS are crystal dendrites of NaCl formed when salts are either added to the piperazine solution during the interfacial polymerization process or introduced to the nascently formed TFC-PA membrane before drying. The NaCl dosing concentration and the curing temperature have an impact on the size of the BFS but not on the fractal dimension (∼1.76). The BFS can be removed from the TFC-PA membranes by simply dissolving the crystal dendrites in deionized water, and the resulting TFC-PA membranes have substantially higher water fluxes (three- to fourfold) without compromised solute rejection. The flux enhancement is believed to be attributable to the distributed reduction in physical binding between the PA active layer and the support layer, caused by the exertion of crystallization pressure when the BFS formed. This reduced physical binding leads to an increase in the effective area for water transport, which, in turn, results in higher water flux. The BFS-templating method, which includes the interesting characteristics of 2D crystal dendrites, represents a facile, low-cost, and highly practical method of enhancing the performance of the TFC-PA nanofiltration membrane without having to alter the existing infrastructure of membrane fabrication.

Exploring the pathways linking visual green space to depression in older adults in Shanghai, China: using street view data.

OBJECTIVES: To examine (1) how visual green space quantity and quality affect depression among older adults; (2) whether and how the links may be mediated by perceived stress, physical activity, neighbourhood social cohesion, and air pollution (PM2.5); and (3) whether there are differences in the mediation across visual green space quantity and quality. METHOD: We used older adults samples (aged over 65) from the WHO Study on Global Ageing and Adult Health in Shanghai, China. Depression was quantified by two self-reported questions related to the diagnosis of depression and medications or other treatments for depression. Visual green space quantity and quality were calculated using street view images and machine learning methods (street view green space = SVG). Mediators included perceived stress, social cohesion, physical activity, and PM2.5. Multilevel logistic and linear regression models were applied to understand the mediating roles of the above mediators in the link between visual green space quantity and quality and depression in older adults. RESULTS: SVG quantity and quality were negatively related to depression. Significant partial mediators for SVG quality were social cohesion and perceived stress. For SVG quantity, there was no evidence that any of the above mediators mediated the association. CONCLUSION: Our results indicated that visual green space quantity and quality may be related to depression in older adults through different mechanisms.

Channel utilization of media access control protocols for underwater acoustic networks with propagation delay and mobilitya).

This paper investigates the impact of mobility on underwater acoustic communication networks in which the propagation delay is comparable to or larger than the packet duration. An underwater acoustic wireless network, consisting of static and mobile nodes, is studied for its link-layer channel utilization. Synchronous and asynchronous media access control (MAC) protocols are employed with ALOHA, TDMA (time-division multiple access), and artificial intelligence (AI) agent nodes. The simulation results of a multi-node network show that the asynchronous MAC protocols achieve up to 6.66× higher channel utilization than synchronous protocols by allowing time slots to be shorter than the maximum propagation delay among nodes and permitting asynchronous transmission time. The high mobility of a few mobile nodes also favors asynchronous protocols and increases the overall channel utilization. However, node mobility causes more difficulties for the AI node to learn the environment, which may be ineffective to achieve higher gains in channel utilization.