Digital quantum simulation of Floquet symmetry-protected topological phases.

Quantum many-body systems away from equilibrium host a rich variety of exotic phenomena that are forbidden by equilibrium thermodynamics. A prominent example is that of discrete time crystals1-8, in which time-translational symmetry is spontaneously broken in periodically driven systems. Pioneering experiments have observed signatures of time crystalline phases with trapped ions9,10, solid-state spin systems11-15, ultracold atoms16,17 and superconducting qubits18-20. Here we report the observation of a distinct type of non-equilibrium state of matter, Floquet symmetry-protected topological phases, which are implemented through digital quantum simulation with an array of programmable superconducting qubits. We observe robust long-lived temporal correlations and subharmonic temporal response for the edge spins over up to 40 driving cycles using a circuit of depth exceeding 240 and acting on 26 qubits. We demonstrate that the subharmonic response is independent of the initial state, and experimentally map out a phase boundary between the Floquet symmetry-protected topological and thermal phases. Our results establish a versatile digital simulation approach to exploring exotic non-equilibrium phases of matter with current noisy intermediate-scale quantum processors21.

KnockTF 2.0: a comprehensive gene expression profile database with knockdown/knockout of transcription (co-)factors in multiple species.

Transcription factors (TFs), transcription co-factors (TcoFs) and their target genes perform essential functions in diseases and biological processes. KnockTF 2.0 (http://www.licpathway.net/KnockTF/index.html) aims to provide comprehensive gene expression profile datasets before/after T(co)F knockdown/knockout across multiple tissue/cell types of different species. Compared with KnockTF 1.0, KnockTF 2.0 has the following improvements: (i) Newly added T(co)F knockdown/knockout datasets in mice, Arabidopsis thaliana and Zea mays and also an expanded scale of datasets in humans. Currently, KnockTF 2.0 stores 1468 manually curated RNA-seq and microarray datasets associated with 612 TFs and 172 TcoFs disrupted by different knockdown/knockout techniques, which are 2.5 times larger than those of KnockTF 1.0. (ii) Newly added (epi)genetic annotations for T(co)F target genes in humans and mice, such as super-enhancers, common SNPs, methylation sites and chromatin interactions. (iii) Newly embedded and updated search and analysis tools, including T(co)F Enrichment (GSEA), Pathway Downstream Analysis and Search by Target Gene (BLAST). KnockTF 2.0 is a comprehensive update of KnockTF 1.0, which provides more T(co)F knockdown/knockout datasets and (epi)genetic annotations across multiple species than KnockTF 1.0. KnockTF 2.0 facilitates not only the identification of functional T(co)Fs and target genes but also the investigation of their roles in the physiological and pathological processes.

scGRN: a comprehensive single-cell gene regulatory network platform of human and mouse.

Gene regulatory networks (GRNs) are interpretable graph models encompassing the regulatory interactions between transcription factors (TFs) and their downstream target genes. Making sense of the topology and dynamics of GRNs is fundamental to interpreting the mechanisms of disease etiology and translating corresponding findings into novel therapies. Recent advances in single-cell multi-omics techniques have prompted the computational inference of GRNs from single-cell transcriptomic and epigenomic data at an unprecedented resolution. Here, we present scGRN (https://bio.liclab.net/scGRN/), a comprehensive single-cell multi-omics gene regulatory network platform of human and mouse. The current version of scGRN catalogs 237 051 cell type-specific GRNs (62 999 692 TF-target gene pairs), covering 160 tissues/cell lines and 1324 single-cell samples. scGRN is the first resource documenting large-scale cell type-specific GRN information of diverse human and mouse conditions inferred from single-cell multi-omics data. We have implemented multiple online tools for effective GRN analysis, including differential TF-target network analysis, TF enrichment analysis, and pathway downstream analysis. We also provided details about TF binding to promoters, super-enhancers and typical enhancers of target genes in GRNs. Taken together, scGRN is an integrative and useful platform for searching, browsing, analyzing, visualizing and downloading GRNs of interest, enabling insight into the differences in regulatory mechanisms across diverse conditions.

eRNAbase: a comprehensive database for decoding the regulatory eRNAs in human and mouse.

Enhancer RNAs (eRNAs) transcribed from distal active enhancers serve as key regulators in gene transcriptional regulation. The accumulation of eRNAs from multiple sequencing assays has led to an urgent need to comprehensively collect and process these data to illustrate the regulatory landscape of eRNAs. To address this need, we developed the eRNAbase (http://bio.liclab.net/eRNAbase/index.php) to store the massive available resources of human and mouse eRNAs and provide comprehensive annotation and analyses for eRNAs. The current version of eRNAbase cataloged 10 399 928 eRNAs from 1012 samples, including 858 human samples and 154 mouse samples. These eRNAs were first identified and uniformly processed from 14 eRNA-related experiment types manually collected from GEO/SRA and ENCODE. Importantly, the eRNAbase provides detailed and abundant (epi)genetic annotations in eRNA regions, such as super enhancers, enhancers, common single nucleotide polymorphisms, expression quantitative trait loci, transcription factor binding sites, CRISPR/Cas9 target sites, DNase I hypersensitivity sites, chromatin accessibility regions, methylation sites, chromatin interactions regions, topologically associating domains and RNA spatial interactions. Furthermore, the eRNAbase provides users with three novel analyses including eRNA-mediated pathway regulatory analysis, eRNA-based variation interpretation analysis and eRNA-mediated TF-target gene analysis. Hence, eRNAbase is a powerful platform to query, browse and visualize regulatory cues associated with eRNAs.

LncSEA 2.0: an updated platform for long non-coding RNA related sets and enrichment analysis.

Long non-coding RNAs (lncRNAs) possess a wide range of biological functions, and research has demonstrated their significance in regulating major biological processes such as development, differentiation, and immune response. The accelerating accumulation of lncRNA research has greatly expanded our understanding of lncRNA functions. Here, we introduce LncSEA 2.0 (http://bio.liclab.net/LncSEA/index.php), aiming to provide a more comprehensive set of functional lncRNAs and enhanced enrichment analysis capabilities. Compared with LncSEA 1.0, we have made the following improvements: (i) We updated the lncRNA sets for 11 categories and extremely expanded the lncRNA scopes for each set. (ii) We newly introduced 15 functional lncRNA categories from multiple resources. This update not only included a significant amount of downstream regulatory data for lncRNAs, but also covered numerous epigenetic regulatory data sets, including lncRNA-related transcription co-factor binding, chromatin regulator binding, and chromatin interaction data. (iii) We incorporated two new lncRNA set enrichment analysis functions based on GSEA and GSVA. (iv) We adopted the snakemake analysis pipeline to track data processing and analysis. In summary, LncSEA 2.0 offers a more comprehensive collection of lncRNA sets and a greater variety of enrichment analysis modules, assisting researchers in a more comprehensive study of the functional mechanisms of lncRNAs.

Stripe rust effector Pst03724 modulates host immunity by inhibiting NAD kinase activation by a calmodulin.

Puccinia striiformis f. sp. tritici (Pst) secretes effector proteins that enter plant cells to manipulate host immune processes. In this report, we present an important Pst effector, Pst03724, whose mRNA expression level increases during Pst infection of wheat (Triticum aestivum). Silencing of Pst03724 reduced the growth and development of Pst. Pst03724 targeted the wheat calmodulin TaCaM3-2B, a positive regulator of wheat immunity. Subsequent investigations revealed that Pst03724 interferes with the TaCaM3-2B-NAD kinase (NADK) TaNADK2 association and thus inhibits the enzyme activity of TaNADK2 activated by TaCaM3-2B. Knocking down TaNADK2 expression by virus-mediated gene silencing significantly increased fungal growth and development, suggesting a decrease in resistance against Pst infection. In conclusion, our findings indicate that Pst effector Pst03724 inhibits the activity of NADK by interfering with the TaCaM3-2B-TaNADK2 association, thereby facilitating Pst infection.

CRdb: a comprehensive resource for deciphering chromatin regulators in human.

Chromatin regulators (CRs) regulate epigenetic patterns on a partial or global scale, playing a critical role in affecting multi-target gene expression. As chromatin immunoprecipitation sequencing (ChIP-seq) data associated with CRs are rapidly accumulating, a comprehensive resource of CRs needs to be built urgently for collecting, integrating, and processing these data, which can provide abundant annotated information on CR upstream and downstream regulatory analyses as well as CR-related analysis functions. This study established an integrative CR resource, named CRdb (http://cr.liclab.net/crdb/), with the aim of curating a large number of available resources for CRs and providing extensive annotations and analyses of CRs to help biological researchers clarify the regulation mechanism and function of CRs. The CRdb database comprised a total of 647 CRs and 2,591 ChIP-seq samples from more than 300 human tissues and cell types. These samples have been manually curated from NCBI GEO/SRA and ENCODE. Importantly, CRdb provided the abundant and detailed genetic annotations in CR-binding regions based on ChIP-seq. Furthermore, CRdb supported various functional annotations and upstream regulatory information on CRs. In particular, it embedded four types of CR regulatory analyses: CR gene set enrichment, CR-binding genomic region annotation, CR-TF co-occupancy analysis, and CR regulatory axis analysis. CRdb is a useful and powerful resource that can help in exploring the potential functions of CRs and their regulatory mechanism in diseases and biological processes.

SEdb 2.0: a comprehensive super-enhancer database of human and mouse.

Super-enhancers (SEs) are cell-specific DNA cis-regulatory elements that can supervise the transcriptional regulation processes of downstream genes. SEdb 2.0 (http://www.licpathway.net/sedb) aims to provide a comprehensive SE resource and annotate their potential roles in gene transcriptions. Compared with SEdb 1.0, we have made the following improvements: (i) Newly added the mouse SEs and expanded the scale of human SEs. SEdb 2.0 contained 1 167 518 SEs from 1739 human H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq) samples and 550 226 SEs from 931 mouse H3K27ac ChIP-seq samples, which was five times that of SEdb 1.0. (ii) Newly added transcription factor binding sites (TFBSs) in SEs identified by TF motifs and TF ChIP-seq data. (iii) Added comprehensive (epi)genetic annotations of SEs, including chromatin accessibility regions, methylation sites, chromatin interaction regions and topologically associating domains (TADs). (iv) Newly embedded and updated search and analysis tools, including 'Search SE by TF-based', 'Differential-Overlapping-SE analysis' and 'SE-based TF-Gene analysis'. (v) Newly provided quality control (QC) metrics for ChIP-seq processing. In summary, SEdb 2.0 is a comprehensive update of SEdb 1.0, which curates more SEs and annotation information than SEdb 1.0. SEdb 2.0 provides a friendly platform for researchers to more comprehensively clarify the important role of SEs in the biological process.

Immunotherapeutic prospects and progress in bladder cancer.

Bladder cancer is one of the most common malignant tumours of the urogenital system, with high morbidity and mortality. In most cases, surgery is considered the first choice of treatment, followed by adjuvant chemotherapy. However, the 5-year recurrence rate is still as high as 65% in patients with non-invasive or in situ tumours and up to 73% in patients with slightly more advanced disease at initial diagnosis. Various treatment methods for bladder cancer have been developed, and hundreds of new immunotherapies are being tested. To date, only a small percentage of people have had success with new treatments, though studies have suggested that the combination of immunotherapy with other therapies improves treatment efficiency and positive outcomes for individuals, with great hopes for the future. In this article, we summarize the origins, therapeutic mechanisms and current status of research on immunotherapeutic agents for bladder cancer.

PBAC: A pathway-based attention convolution neural network for predicting clinical drug treatment responses.

Precise and personalized drug application is crucial in the clinical treatment of complex diseases. Although neural networks offer a new approach to improving drug strategies, their internal structure is difficult to interpret. Here, we propose PBAC (Pathway-Based Attention Convolution neural network), which integrates a deep learning framework and attention mechanism to address the complex biological pathway information, thereby provide a biology function-based robust drug responsiveness prediction model. PBAC has four layers: gene-pathway layer, attention layer, convolution layer and fully connected layer. PBAC improves the performance of predicting drug responsiveness by focusing on important pathways, helping us understand the mechanism of drug action in diseases. We validated the PBAC model using data from four chemotherapy drugs (Bortezomib, Cisplatin, Docetaxel and Paclitaxel) and 11 immunotherapy datasets. In the majority of datasets, PBAC exhibits superior performance compared to traditional machine learning methods and other research approaches (area under curve = 0.81, the area under the precision-recall curve = 0.73). Using PBAC attention layer output, we identified some pathways as potential core cancer regulators, providing good interpretability for drug treatment prediction. In summary, we presented PBAC, a powerful tool to predict drug responsiveness based on the biology pathway information and explore the potential cancer-driving pathways.

Understanding formation processes of calcareous nephrolithiasis in renal interstitium and tubule lumen.

Kidney stone, one of the oldest known diseases, has plagued humans for centuries, consistently imposing a heavy burden on patients and healthcare systems worldwide due to their high incidence and recurrence rates. Advancements in endoscopy, imaging, genetics, molecular biology and bioinformatics have led to a deeper and more comprehensive understanding of the mechanism behind nephrolithiasis. Kidney stone formation is a complex, multi-step and long-term process involving the transformation of stone-forming salts from free ions into asymptomatic or symptomatic stones influenced by physical, chemical and biological factors. Among the various types of kidney stones observed in clinical practice, calcareous nephrolithiasis is currently the most common and exhibits the most intricate formation mechanism. Extensive research suggests that calcareous nephrolithiasis primarily originates from interstitial subepithelial calcified plaques and/or calcified blockages in the openings of collecting ducts. These calcified plaques and blockages eventually come into contact with urine in the renal pelvis, serving as a nidus for crystal formation and subsequent stone growth. Both pathways of stone formation share similar mechanisms, such as the drive of abnormal urine composition, involvement of oxidative stress and inflammation, and an imbalance of stone inhibitors and promoters. However, they also possess unique characteristics. Hence, this review aims to provide detailed description and present recent discoveries regarding the formation processes of calcareous nephrolithiasis from two distinct birthplaces: renal interstitium and tubule lumen.

Environment-Sensitive Fluorescent Probe Enables Assessment of Anaplastic Lymphoma Kinase Activity in Nonsmall Cell Lung Cancer.

Anaplastic lymphoma kinase (ALK) rearrangements have been identified as key oncogenic drivers of a subset of nonsmall cell lung cancer (NSCLC). The final chimeric protein of the fusion gene can be constitutively activated, which accounts for the growth and proliferation of ALK-rearranged tumors and thus strongly associates with cancer invasion and metastasis. Diagnostic tools enabling the visualization of ALK activity in a structure-function-based approach are highly desirable to determine ALK status and guide ALK tyrosine kinase inhibitor (ALK-TKI) treatment making. Here, we describe the design, synthesis, and application of a new environment-sensitive fluorescent probe HX16 by introducing an environment-sensitive fluorophore 4-sulfonamidebenzoxadiazole to visualize ALK activity in living cancer cells and tumor tissue slices (mouse model and human biopsy sample). HX16 is a multifunctional chemical tool based on the pharmacophore of ALK-TKI (ceritinib) and can specifically target the kinase domain of ALK with a high sensitivity. Using flow cytometry and confocal microscopy, HX16 enables visualization of ALK activity in various cancer cells with distinct ALK fusion genes, as well as xenograft mouse models. Importantly, HX16 was also applied to visualize ALK activity in a tumor biopsy from a NSCLC patient with ALK-echinoderm microtubule-associated protein-like-4 fusion gene for prediction of ALK-TKI sensitivity. These results demonstrate that strategically designed ALK-TKI-based probe allows the assessment of ALK activity in tumor tissues and hold promise as a useful diagnostic tool in predicting ALK-TKI therapy response.

Role of transcriptional cofactors in cardiovascular diseases.

Cardiovascular disease is a main cause of mortality in the world and the highest incidence of all diseases. However, the mechanism of the pathogenesis of cardiovascular disease is still unclear, and we need to continue to explore its mechanism of action. The occurrence and development of cardiovascular disease is significantly associated with genetic abnormalities, and gene expression is affected by transcriptional regulation. In this complex process, the protein-protein interaction promotes the RNA polymerase II to the initiation site. And in this process of transcriptional regulation, transcriptional cofactors are responsible for passing cues from enhancers to promoters and promoting the binding of RNA polymerases to promoters, so transcription cofactors playing a key role in gene expression regulation. There is growing evidence that transcriptional cofactors play a critical role in cardiovascular disease. Transcriptional cofactors can promote or inhibit transcription by affecting the function of transcription factors. It can affect the initiation and elongation process of transcription by forming complexes with transcription factors, which are important for the stabilization of DNA rings. It can also act as a protein that interacts with other proteins to affect the expression of other genes. Therefore, the aim of this overview is to summarize the effect of some transcriptional cofactors such as BRD4, EP300, MED1, EZH2, YAP, SIRT6 in cardiovascular disease and to provide a promising therapeutic strategy for the treatment of cardiovascular disease.

Dysregulated expression of miR-140 and miR-122 compromised microglial chemotaxis and led to reduced restriction of AD pathology.

BACKGROUND: Deposition of amyloid ß, which is produced by amyloidogenic cleavage of APP by ß- and γ-secretase, is one of the primary hallmarks of AD pathology. APP can also be processed by α- and γ-secretase sequentially, to generate sAPPα, which has been shown to be neuroprotective by promoting neurite outgrowth and neuronal survival, etc. METHODS: The global expression profiles of miRNA in blood plasma samples taken from 11 AD patients as well as from 14 age and sex matched cognitively normal volunteers were analyzed using miRNA-seq. Then, overexpressed miR-140 and miR-122 both in vivo and in vitro, and knock-down of the endogenous expression of miR-140 and miR-122 in vitro. Used a combination of techniques, including molecular biology, immunohistochemistry, to detect the impact of miRNAs on AD pathology. RESULTS: In this study, we identified that two miRNAs, miR-140-3p and miR-122-5p, both targeting ADAM10, the main α-secretase in CNS, were upregulated in the blood plasma of AD patients. Overexpression of these two miRNAs in mouse brains induced cognitive decline in wild type C57BL/6J mice as well as exacerbated dyscognition in APP/PS1 mice. Although significant changes in APP and total Aß were not detected, significantly downregulated ADAM10 and its non-amyloidogenic product, sAPPα, were observed in the mouse brains overexpressing miR-140/miR-122. Immunohistology analysis revealed increased neurite dystrophy that correlated with the reduced microglial chemotaxis in the hippocampi of these mice, independent of the other two ADAM10 substrates (neuronal CX3CL1 and microglial TREM2) that were involved in regulating the microglial immunoactivity. Further in vitro analysis demonstrated that both the reduced neuritic outgrowth of mouse embryonic neuronal cells overexpressing miR-140/miR-122 and the reduced Aß phagocytosis in microglia cells co-cultured with HT22 cells overexpressing miR-140/miR-122 could be rescued by overexpressing the specific inhibitory sequence of miR-140/miR-122 TuD as well as by addition of sAPPα, rendering these miRNAs as potential therapeutic targets. CONCLUSIONS: Our results suggested that neuroprotective sAPPα was a key player in the neuropathological progression induced by dysregulated expression of miR-140 and miR-122. Targeting these miRNAs might serve as a promising therapeutic strategy in AD treatment.

GREAP: a comprehensive enrichment analysis software for human genomic regions.

The rapid development of genomic high-throughput sequencing has identified a large number of DNA regulatory elements with abundant epigenetics markers, which promotes the rapid accumulation of functional genomic region data. The comprehensively understanding and research of human functional genomic regions is still a relatively urgent work at present. However, the existing analysis tools lack extensive annotation and enrichment analytical abilities for these regions. Here, we designed a novel software, Genomic Region sets Enrichment Analysis Platform (GREAP), which provides comprehensive region annotation and enrichment analysis capabilities. Currently, GREAP supports 85 370 genomic region reference sets, which cover 634 681 107 regions across 11 different data types, including super enhancers, transcription factors, accessible chromatins, etc. GREAP provides widespread annotation and enrichment analysis of genomic regions. To reflect the significance of enrichment analysis, we used the hypergeometric test and also provided a Locus Overlap Analysis. In summary, GREAP is a powerful platform that provides many types of genomic region sets for users and supports genomic region annotations and enrichment analyses. In addition, we developed a customizable genome browser containing >400 000 000 customizable tracks for visualization. The platform is freely available at http://www.liclab.net/Greap/view/index.

CanMethdb: a database for genome-wide DNA methylation annotation in cancers.

MOTIVATION: DNA methylation within gene body and promoters in cancer cells is well documented. An increasing number of studies showed that cytosine-phosphate-guanine (CpG) sites falling within other regulatory elements could also regulate target gene activation, mainly by affecting transcription factors (TFs) binding in human cancers. This led to the urgent need for comprehensively and effectively collecting distinct cis-regulatory elements and TF-binding sites (TFBS) to annotate DNA methylation regulation. RESULTS: We developed a database (CanMethdb, http://meth.liclab.net/CanMethdb/) that focused on the upstream and downstream annotations for CpG-genes in cancers. This included upstream cis-regulatory elements, especially those involving distal regions to genes, and TFBS annotations for the CpGs and downstream functional annotations for the target genes, computed through integrating abundant DNA methylation and gene expression profiles in diverse cancers. Users could inquire CpG-target gene pairs for a cancer type through inputting a genomic region, a CpG, a gene name, or select hypo/hypermethylated CpG sets. The current version of CanMethdb documented a total of 38 986 060 CpG-target gene pairs (with 6 769 130 unique pairs), involving 385 217 CpGs and 18 044 target genes, abundant cis-regulatory elements and TFs for 33 TCGA cancer types. CanMethdb might help biologists perform in-depth studies of target gene regulations based on DNA methylations in cancer. AVAILABILITY AND IMPLEMENTATION: The main program is available at https://github.com/chunquanlipathway/CanMethdb. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Deciphering the SOX4/MAPK1 regulatory axis: a phosphoproteomic insight into IQGAP1 phosphorylation and pancreatic Cancer progression.

OBJECTIVE: This study aims to elucidate the functional role of IQGAP1 phosphorylation modification mediated by the SOX4/MAPK1 regulatory axis in developing pancreatic cancer through phosphoproteomics analysis. METHODS: Proteomics and phosphoproteomics data of pancreatic cancer were obtained from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Differential analysis, kinase-substrate enrichment analysis (KSEA), and independent prognosis analysis were performed on these datasets. Subtype analysis of pancreatic cancer patients was conducted based on the expression of prognostic-related proteins, and the prognosis of different subtypes was evaluated through prognosis analysis. Differential analysis of proteins in different subtypes was performed to identify differential proteins in the high-risk subtype. Clinical correlation analysis was conducted based on the expression of prognostic-related proteins, pancreatic cancer typing results, and clinical characteristics in the pancreatic cancer proteomics dataset. Functional pathway enrichment analysis was performed using GSEA/GO/KEGG, and most module proteins correlated with pancreatic cancer were selected using WGCNA analysis. In cell experiments, pancreatic cancer cells were grouped, and the expression levels of SOX4, MAPK1, and the phosphorylation level of IQGAP1 were detected by RT-qPCR and Western blot experiments. The effect of SOX4 on MAPK1 promoter transcriptional activity was assessed using a dual-luciferase assay, and the enrichment of SOX4 on the MAPK1 promoter was examined using a ChIP assay. The proliferation, migration, and invasion functions of grouped pancreatic cancer cells were assessed using CCK-8, colony formation, and Transwell assays. In animal experiments, the impact of SOX4 on tumor growth and metastasis through the regulation of MAPK1-IQGAP1 phosphorylation modification was studied by constructing subcutaneous and orthotopic pancreatic cancer xenograft models, as well as a liver metastasis model in nude mice. RESULTS: Phosphoproteomics and proteomics data analysis revealed that the kinase MAPK1 may play an important role in pancreatic cancer progression by promoting IQGAP1 phosphorylation modification. Proteomics analysis classified pancreatic cancer patients into two subtypes, C1 and C2, where the high-risk C2 subtype was associated with poor prognosis, malignant tumor typing, and enriched tumor-related pathways. SOX4 may promote the occurrence of the high-risk C2 subtype of pancreatic cancer by regulating MAPK1-IQGAP1 phosphorylation modification. In vitro cell experiments confirmed that SOX4 promoted IQGAP1 phosphorylation modification by activating MAPK1 transcription while silencing SOX4 inhibited the proliferation, migration, and invasion of pancreatic cancer cells by reducing the phosphorylation level of MAPK1-IQGAP1. In vivo, animal experiments further confirmed that silencing SOX4 suppressed the growth and metastasis of pancreatic cancer by reducing the phosphorylation level of MAPK1-IQGAP1. CONCLUSION: The findings of this study suggest that SOX4 promotes the phosphorylation modification of IQGAP1 by activating MAPK1 transcription, thereby facilitating the growth and metastasis of pancreatic cancer.

Glycine-serine-rich effector PstGSRE4 in Puccinia striiformis f. sp. tritici inhibits the activity of copper zinc superoxide dismutase to modulate immunity in wheat.

Puccinia striiformis f. sp. tritici (Pst) secretes an array of specific effector proteins to manipulate host immunity and promote pathogen colonization. In a previous study, we functionally characterized a glycine-serine-rich effector PstGSRE1 with a glycine-serine-rich motif (m9). However, the mechanisms of glycine-serine-rich effectors (GSREs) remain obscure. Here we report a new glycine-serine-rich effector, PstGSRE4, which has no m9-like motif but inhibits the enzyme activity of wheat copper zinc superoxide dismutase TaCZSOD2, which acts as a positive regulator of wheat resistance to Pst. By inhibiting the enzyme activity of TaCZSOD2, PstGSRE4 reduces H2O2 accumulation and HR areas to facilitate Pst infection. These findings provide new insights into the molecular mechanisms of GSREs of rust fungi in regulating plant immunity.

Exploration of the mode of death and potential death mechanisms of nucleus pulposus cells.

Intervertebral disc degeneration (IVDD) is a common chronic orthopaedic disease in orthopaedics that imposes a heavy economic burden on people and society. Although it is well established that IVDD is associated with genetic susceptibility, ageing and obesity, its pathogenesis remains incompletely understood. Previously, IVDD was thought to occur because of excessive mechanical loading leading to destruction of nucleus pulposus cells (NPCs), but studies have shown that IVDD is a much more complex process associated with inflammation, metabolic factors and NPCs death and can involve all parts of the disc, characterized by causing NPCs death and extracellular matrix (ECM) degradation. The damage pattern of NPCs in IVDD is like that of some programmed cell death, suggesting that IVDD is associated with programmed cell death. Although apoptosis and pyroptosis of NPCs have been studied in IVDD, the pathogenesis of intervertebral disc degeneration can still not be fully elucidated by using only traditional cell death modalities. With increasing research, some new modes of cell death, PANoptosis, ferroptosis and senescence have been found to be closely related to intervertebral disc degeneration. Among these, PANoptosis combines essential elements of pyroptosis, apoptosis and necroptosis to form a highly coordinated and dynamically balanced programmed inflammatory cell death process. Furthermore, we believe that PANoptosis may also crosstalk with pyroptosis and senescence. Therefore, we review the progress of research on multiple deaths of NPCs in IVDD to provide guidance for clinical treatment.

A single-center, retrospective study of hospitalized patients with lower respiratory tract infections: clinical assessment of metagenomic next-generation sequencing and identification of risk factors in patients.

INTRODUCTION: Lower respiratory tract infections(LRTIs) in adults are complicated by diverse pathogens that challenge traditional detection methods, which are often slow and insensitive. Metagenomic next-generation sequencing (mNGS) offers a comprehensive, high-throughput, and unbiased approach to pathogen identification. This retrospective study evaluates the diagnostic efficacy of mNGS compared to conventional microbiological testing (CMT) in LRTIs, aiming to enhance detection accuracy and enable early clinical prediction. METHODS: In our retrospective single-center analysis, 451 patients with suspected LRTIs underwent mNGS testing from July 2020 to July 2023. We assessed the pathogen spectrum and compared the diagnostic efficacy of mNGS to CMT, with clinical comprehensive diagnosis serving as the reference standard. The study analyzed mNGS performance in lung tissue biopsies and bronchoalveolar lavage fluid (BALF) from cases suspected of lung infection. Patients were stratified into two groups based on clinical outcomes (improvement or mortality), and we compared clinical data and conventional laboratory indices between groups. A predictive model and nomogram for the prognosis of LRTIs were constructed using univariate followed by multivariate logistic regression, with model predictive accuracy evaluated by the area under the ROC curve (AUC). RESULTS: (1) Comparative Analysis of mNGS versus CMT: In a comprehensive analysis of 510 specimens, where 59 cases were concurrently collected from lung tissue biopsies and BALF, the study highlights the diagnostic superiority of mNGS over CMT. Specifically, mNGS demonstrated significantly higher sensitivity and specificity in BALF samples (82.86% vs. 44.42% and 52.00% vs. 21.05%, respectively, p < 0.001) alongside greater positive and negative predictive values (96.71% vs. 79.55% and 15.12% vs. 5.19%, respectively, p < 0.01). Additionally, when comparing simultaneous testing of lung tissue biopsies and BALF, mNGS showed enhanced sensitivity in BALF (84.21% vs. 57.41%), whereas lung tissues offered higher specificity (80.00% vs. 50.00%). (2) Analysis of Infectious Species in Patients from This Study: The study also notes a concerning incidence of lung abscesses and identifies Epstein-Barr virus (EBV), Fusobacterium nucleatum, Mycoplasma pneumoniae, Chlamydia psittaci, and Haemophilus influenzae as the most common pathogens, with Klebsiella pneumoniae emerging as the predominant bacterial culprit. Among herpes viruses, EBV and herpes virus 7 (HHV-7) were most frequently detected, with HHV-7 more prevalent in immunocompromised individuals. (3) Risk Factors for Adverse Prognosis and a Mortality Risk Prediction Model in Patients with LRTIs: We identified key risk factors for poor prognosis in lower respiratory tract infection patients, with significant findings including delayed time to mNGS testing, low lymphocyte percentage, presence of chronic lung disease, multiple comorbidities, false-negative CMT results, and positive herpesvirus affecting patient outcomes. We also developed a nomogram model with good consistency and high accuracy (AUC of 0.825) for predicting mortality risk in these patients, offering a valuable clinical tool for assessing prognosis. CONCLUSION: The study underscores mNGS as a superior tool for lower respiratory tract infection diagnosis, exhibiting higher sensitivity and specificity than traditional methods.