Systematic identification and characterization of exon-intron circRNAs.

Exon-intron circRNAs (EIciRNAs) are a circRNA subclass with retained introns. Global features of EIciRNAs remain largely unexplored, mainly owing to the lack of bioinformatic tools. The regulation of intron retention (IR) in EIciRNAs and the associated functionality also require further investigation. We developed a framework, FEICP, which efficiently detected EIciRNAs from high-throughput sequencing (HTS) data. EIciRNAs are distinct from exonic circRNAs (EcircRNAs) in aspects such as with larger length, localization in the nucleus, high tissue specificity, and enrichment mostly in the brain. Deep learning analyses revealed that compared with regular introns, the retained introns of circRNAs (CIRs) are shorter in length, have weaker splice site strength, and have higher GC content. Compared with retained introns in linear RNAs (LIRs), CIRs are more likely to form secondary structures and show greater sequence conservation. CIRs are closer to the 5'-end, whereas LIRs are closer to the 3'-end of transcripts. EIciRNA-generating genes are more actively transcribed and associated with epigenetic marks of gene activation. Computational analyses and genome-wide CRISPR screening revealed that SRSF1 binds to CIRs and inhibits the biogenesis of most EIciRNAs. SRSF1 regulates the biogenesis of EIciLIMK1, which enhances the expression of LIMK1 in cis to boost neuronal differentiation, exemplifying EIciRNA physiological function. Overall, our study has developed the FEICP pipeline to identify EIciRNAs from HTS data, and reveals multiple features of CIRs and EIciRNAs. SRSF1 has been identified to regulate EIciRNA biogenesis. EIciRNAs and the regulation of EIciRNA biogenesis play critical roles in neuronal differentiation.

Structure of mavacamten-free human cardiac thick filaments within the sarcomere by cryoelectron tomography.

Heart muscle has the unique property that it can never rest; all cardiomyocytes contract with each heartbeat which requires a complex control mechanism to regulate cardiac output to physiological requirements. Changes in calcium concentration regulate the thin filament activation. A separate but linked mechanism regulates the thick filament activation, which frees sufficient myosin heads to bind the thin filament, thereby producing the required force. Thick filaments contain additional nonmyosin proteins, myosin-binding protein C and titin, the latter being the protein that transmits applied tension to the thick filament. How these three proteins interact to control thick filament activation is poorly understood. Here, we show using 3-D image reconstruction of frozen-hydrated human cardiac muscle myofibrils lacking exogenous drugs that the thick filament is structured to provide three levels of myosin activation corresponding to the three crowns of myosin heads in each 429Å repeat. In one crown, the myosin heads are almost completely activated and disordered. In another crown, many myosin heads are inactive, ordered into a structure called the interacting heads motif. At the third crown, the myosin heads are ordered into the interacting heads motif, but the stability of that motif is affected by myosin-binding protein C. We think that this hierarchy of control explains many of the effects of length-dependent activation as well as stretch activation in cardiac muscle control.

From G1 to M: a comparative study of methods for identifying cell cycle phases.

Accurate identification of cell cycle phases in single-cell RNA-sequencing (scRNA-seq) data is crucial for biomedical research. Many methods have been developed to tackle this challenge, employing diverse approaches to predict cell cycle phases. In this review article, we delve into the standard processes in identifying cell cycle phases within scRNA-seq data and present several representative methods for comparison. To rigorously assess the accuracy of these methods, we propose an error function and employ multiple benchmarking datasets encompassing human and mouse data. Our evaluation results reveal a key finding: the fit between the reference data and the dataset being analyzed profoundly impacts the effectiveness of cell cycle phase identification methods. Therefore, researchers must carefully consider the compatibility between the reference data and their dataset to achieve optimal results. Furthermore, we explore the potential benefits of incorporating benchmarking data with multiple known cell cycle phases into the analysis. Merging such data with the target dataset shows promise in enhancing prediction accuracy. By shedding light on the accuracy and performance of cell cycle phase prediction methods across diverse datasets, this review aims to motivate and guide future methodological advancements. Our findings offer valuable insights for researchers seeking to improve their understanding of cellular dynamics through scRNA-seq analysis, ultimately fostering the development of more robust and widely applicable cell cycle identification methods.

scEVOLVE: cell-type incremental annotation without forgetting for single-cell RNA-seq data.

The evolution in single-cell RNA sequencing (scRNA-seq) technology has opened a new avenue for researchers to inspect cellular heterogeneity with single-cell precision. One crucial aspect of this technology is cell-type annotation, which is fundamental for any subsequent analysis in single-cell data mining. Recently, the scientific community has seen a surge in the development of automatic annotation methods aimed at this task. However, these methods generally operate at a steady-state total cell-type capacity, significantly restricting the cell annotation systems'capacity for continuous knowledge acquisition. Furthermore, creating a unified scRNA-seq annotation system remains challenged by the need to progressively expand its understanding of ever-increasing cell-type concepts derived from a continuous data stream. In response to these challenges, this paper presents a novel and challenging setting for annotation, namely cell-type incremental annotation. This concept is designed to perpetually enhance cell-type knowledge, gleaned from continuously incoming data. This task encounters difficulty with data stream samples that can only be observed once, leading to catastrophic forgetting. To address this problem, we introduce our breakthrough methodology termed scEVOLVE, an incremental annotation method. This innovative approach is built upon the methodology of contrastive sample replay combined with the fundamental principle of partition confidence maximization. Specifically, we initially retain and replay sections of the old data in each subsequent training phase, then establish a unique prototypical learning objective to mitigate the cell-type imbalance problem, as an alternative to using cross-entropy. To effectively emulate a model that trains concurrently with complete data, we introduce a cell-type decorrelation strategy that efficiently scatters feature representations of each cell type uniformly. We constructed the scEVOLVE framework with simplicity and ease of integration into most deep softmax-based single-cell annotation methods. Thorough experiments conducted on a range of meticulously constructed benchmarks consistently prove that our methodology can incrementally learn numerous cell types over an extended period, outperforming other strategies that fail quickly. As far as our knowledge extends, this is the first attempt to propose and formulate an end-to-end algorithm framework to address this new, practical task. Additionally, scEVOLVE, coded in Python using the Pytorch machine-learning library, is freely accessible at https://github.com/aimeeyaoyao/scEVOLVE.

scBOL: a universal cell type identification framework for single-cell and spatial transcriptomics data.

MOTIVATION: Over the past decade, single-cell transcriptomic technologies have experienced remarkable advancements, enabling the simultaneous profiling of gene expressions across thousands of individual cells. Cell type identification plays an essential role in exploring tissue heterogeneity and characterizing cell state differences. With more and more well-annotated reference data becoming available, massive automatic identification methods have sprung up to simplify the annotation process on unlabeled target data by transferring the cell type knowledge. However, in practice, the target data often include some novel cell types that are not in the reference data. Most existing works usually classify these private cells as one generic 'unassigned' group and learn the features of known and novel cell types in a coupled way. They are susceptible to the potential batch effects and fail to explore the fine-grained semantic knowledge of novel cell types, thus hurting the model's discrimination ability. Additionally, emerging spatial transcriptomic technologies, such as in situ hybridization, sequencing and multiplexed imaging, present a novel challenge to current cell type identification strategies that predominantly neglect spatial organization. Consequently, it is imperative to develop a versatile method that can proficiently annotate single-cell transcriptomics data, encompassing both spatial and non-spatial dimensions. RESULTS: To address these issues, we propose a new, challenging yet realistic task called universal cell type identification for single-cell and spatial transcriptomics data. In this task, we aim to give semantic labels to target cells from known cell types and cluster labels to those from novel ones. To tackle this problem, instead of designing a suboptimal two-stage approach, we propose an end-to-end algorithm called scBOL from the perspective of Bipartite prototype alignment. Firstly, we identify the mutual nearest clusters in reference and target data as their potential common cell types. On this basis, we mine the cycle-consistent semantic anchor cells to build the intrinsic structure association between two data. Secondly, we design a neighbor-aware prototypical learning paradigm to strengthen the inter-cluster separability and intra-cluster compactness within each data, thereby inspiring the discriminative feature representations. Thirdly, driven by the semantic-aware prototypical learning framework, we can align the known cell types and separate the private cell types from them among reference and target data. Such an algorithm can be seamlessly applied to various data types modeled by different foundation models that can generate the embedding features for cells. Specifically, for non-spatial single-cell transcriptomics data, we use the autoencoder neural network to learn latent low-dimensional cell representations, and for spatial single-cell transcriptomics data, we apply the graph convolution network to capture molecular and spatial similarities of cells jointly. Extensive results on our carefully designed evaluation benchmarks demonstrate the superiority of scBOL over various state-of-the-art cell type identification methods. To our knowledge, we are the pioneers in presenting this pragmatic annotation task, as well as in devising a comprehensive algorithmic framework aimed at resolving this challenge across varied types of single-cell data. Finally, scBOL is implemented in Python using the Pytorch machine-learning library, and it is freely available at https://github.com/aimeeyaoyao/scBOL.

Modulation of monocyte activity by hepatocellular MicroRNA delivery through HBsAg particles: Implications for pathobiology of chronic hepatitis B.

BACKGROUND AND AIMS: HBsAg serves as an important immune-modulatory factor in chronic hepatitis B. One aspect of such modulation may act through monocytes, which are the major Ag-presenting cells taking up HBsAg. There is evidence for the encapsulation of hepatocellular microRNAs (miRNAs) by HBsAg particles, while its pathobiological significance is unclear. Here, we characterized the miRNA profile in patients with chronic hepatitis B and probed their association with liver inflammation. APPROACHES AND RESULTS: We collected plasma from patients that are treatment-naive with chronic hepatitis B (n = 110) and quantified total/HBsAg-enveloped miRNAs by qRT-PCR and plasma cytokines by ELISA. The biological effects of HBsAg-delivered miRNAs in monocytes were evaluated using multiple approaches. The clinical significance of candidate miRNAs and cytokines was corroborated in patients with HBV-associated advanced liver diseases. The plasma miRNA profile showed 2 major clusters, one significantly associated with HBsAg titer and the other correlated with liver inflammation. Among HBsAg-carried miRNAs, miR-939 displayed the most significant correlation with IL-8. Mechanistically, miR-939 in subviral particles enters monocytes and significantly augments IL-8 production through the mitogen-activated protein kinase (MAPK) p38 signaling pathway. Finally, the findings that miR-939 positively correlated with IL-8 level and inflammation/fibrosis stage in the cohort of HBV-associated advanced liver diseases support its causative role in the progression of liver diseases. CONCLUSIONS: HBsAg particles carry hepatocellular miRNAs, including miR-939, which enter monocytes and alter their functional status, such as IL-8 secretion. Our findings demonstrate that the HBsAg-miR-939-IL-8 axis may play a crucial role in HBV-induced hepatic necro-inflammation and the progression of advanced liver diseases.

Mechanistic Insights into Tanshinone IIA in the Amelioration of Post-Thyroidectomy Hypoparathyroidism.

BACKGROUND: Thyroidectomy causes impaired blood supply to the parathyroid glands, which leads to hypoparathyroidism. Tanshinone IIA (Tan IIA) is helpful in blood activation and cardiovascular protection. Therefore, the efficacy of Tan IIA in improving hypoparathyroidism was explored in this study. METHODS: New Zealand white rabbits were utilized to establish a unilateral parathyroid gland ischemia injury model. The model was created by selectively ligating the main blood supply vessel of one parathyroid gland, and the rabbits were then divided into three groups receiving 1, 5, and 10 mg/kg of Tan IIA. Serum calcium and parathyroid hormone (PTH) levels were measured using specialized assay kits. Immunohistochemistry was used to assess the microvessel density (MVD) in parathyroid glands. Western blotting (WB) was used to analyze protein expression related to the PI3K/AKT signaling pathway and the pathway-associated HIF-1α and VEGF. Moreover, MMP-2 and MMP-9 involved in angiogenesis were detected by WB. RESULTS: Tan IIA treatment effectively restored serum calcium and PTH levels in a dose-dependent manner. Notably, MVD in the parathyroid glands increased significantly, especially at higher doses. The Tan IIA treatment also elevated the p-PI3K/PI3K and p-AKT/AKT ratios, indicating that the PI3K/AKT pathway was reactivated. Moreover, Tan IIA significantly restored the decreased expression levels of VEGF and HIF-1α caused by parathyroid surgery. Additionally, Tan IIA increased MMP-2 and MMP-9 levels. CONCLUSION: Tan IIA activates the PI3K/AKT pathway, promotes angiogenesis by modulating VEGF, HIF-1α, MMP-2, and MMP-9, thereby further enhancing MVD within the parathyroid glands. This study demonstrates that Tan IIA improved post-thyroidectomy hypoparathyroidism.

Role of HCN channels in the functions of basal ganglia and Parkinson's disease.

Parkinson's disease (PD) is a motor disorder resulting from dopaminergic neuron degeneration in the substantia nigra caused by age, genetics, and environment. The disease severely impacts a patient's quality of life and can even be life-threatening. The hyperpolarization-activated cyclic nucleotide-gated (HCN) channel is a member of the HCN1-4 gene family and is widely expressed in basal ganglia nuclei. The hyperpolarization-activated current mediated by the HCN channel has a distinct impact on neuronal excitability and rhythmic activity associated with PD pathogenesis, as it affects the firing activity, including both firing rate and firing pattern, of neurons in the basal ganglia nuclei. This review aims to comprehensively understand the characteristics of HCN channels by summarizing their regulatory role in neuronal firing activity of the basal ganglia nuclei. Furthermore, the distribution and characteristics of HCN channels in each nucleus of the basal ganglia group and their effect on PD symptoms through modulating neuronal electrical activity are discussed. Since the roles of the substantia nigra pars compacta and reticulata, as well as globus pallidus externus and internus, are distinct in the basal ganglia circuit, they are individually described. Lastly, this investigation briefly highlights that the HCN channel expressed on microglia plays a role in the pathological process of PD by affecting the neuroinflammatory response.

Cefiderocol: Clinical application and emergence of resistance.

Antibacterial drug resistance of gram-negative bacteria (GNB) results in high morbidity and mortality of GNB infection, seriously threaten human health globally. Developing new antibiotics has become the critical need for dealing with drug-resistant bacterial infections. Cefiderocol is an iron carrier cephalosporin that achieves drug accumulation through a unique "Trojan horse" strategy into the bacterial periplasm. It shows high antibacterial activity against multidrug-resistant (MDR) Enterobacteriaceae and MDR non-fermentative bacteria. The application of cefiderocol offers new hope for treating clinical drug-resistant bacterial infections. However, limited clinical data and uncertainties about its resistance mechanisms constrain the choice of its therapeutic use. This review aimed to summarize the clinical applications, drug resistance mechanisms, and co-administration of cefiderocol.

Silicon-containing nanomedicine and biomaterials: materials chemistry, multi-dimensional design, and biomedical application.

The invention of silica-based bioactive glass in the late 1960s has sparked significant interest in exploring a wide range of silicon-containing biomaterials from the macroscale to the nanoscale. Over the past few decades, these biomaterials have been extensively explored for their potential in diverse biomedical applications, considering their remarkable bioactivity, excellent biocompatibility, facile surface functionalization, controllable synthesis, etc. However, to expedite the clinical translation and the unexpected utilization of silicon-composed nanomedicine and biomaterials, it is highly desirable to achieve a thorough comprehension of their characteristics and biological effects from an overall perspective. In this review, we provide a comprehensive discussion on the state-of-the-art progress of silicon-composed biomaterials, including their classification, characteristics, fabrication methods, and versatile biomedical applications. Additionally, we highlight the multi-dimensional design of both pure and hybrid silicon-composed nanomedicine and biomaterials and their intrinsic biological effects and interactions with biological systems. Their extensive biomedical applications span from drug delivery and bioimaging to therapeutic interventions and regenerative medicine, showcasing the significance of their rational design and fabrication to meet specific requirements and optimize their theranostic performance. Additionally, we offer insights into the future prospects and potential challenges regarding silicon-composed nanomedicine and biomaterials. By shedding light on these exciting research advances, we aspire to foster further progress in the biomedical field and drive the development of innovative silicon-composed nanomedicine and biomaterials with transformative applications in biomedicine.

Urinary eicosanoid levels in early life and risk of atopic disease in childhood.

BACKGROUND: Eicosanoids are lipid mediators including thromboxanes (TXs), prostaglandins (PGs), and leukotrienes with a pathophysiological role in established atopic disease. However, their role in the inception of disease is unclear. This study aimed to investigate the association between urinary eicosanoids in early life and development of atopic disease. METHODS: This study quantified the levels of 21 eicosanoids in urine from children from the COPSAC2010 (Copenhagen Prospective Studies on Asthma in Childhood 2010) (age 1 year, n = 450) and VDAART (Vitamin D Antenatal Asthma Reduction Trial) (age 3 years, n = 575) mother-child cohorts and analyzed the associations with development of wheeze/asthma, atopic dermatitis, and biomarkers of type-2 inflammation, applying false discovery rate of 5% (FDR5%) multiple testing correction. RESULTS: In both cohorts, analyses adjusted for environmental determinants showed that higher TXA2 eicosanoids in early life were associated with increased risk of developing atopic dermatitis (P < FDR5%) and type-2 inflammation (P < .05). In VDAART, lower PGE2 and PGI2 eicosanoids and higher isoprostanes were also associated with increased risk of atopic dermatitis (P < FDR5%). For wheeze/asthma, analyses in COPSAC2010 showed that lower isoprostanes and PGF2 eicosanoids and higher PGD2 eicosanoids at age 1 year associated with an increased risk at age 1-10 years (P < .05), whereas analyses in VDAART showed that lower PGE2 and higher TXA2 eicosanoids at age 3 years associated with an increased risk at 6 years (P < FDR5%). CONCLUSIONS: This study suggests that early life perturbations in the eicosanoid metabolism are present before the onset of atopic disease in childhood, which provides pathophysiological insight in the inception of atopic diseases.

LncRNA CARD8-AS1 suppresses lung adenocarcinoma progression by enhancing TRIM25-mediated ubiquitination of TXNRD1.

Long non-coding RNAs (lncRNAs) play crucial roles in the tumorigenesis and progression of lung adenocarcinoma (LUAD). However, little was known about the role of lncRNAs in high-risk LUAD subtypes: micropapillary-predominant adenocarcinoma (MPA) and solid-predominant adenocarcinoma (SPA). In this study, we conducted a systematic screening of differentially expressed lncRNAs using RNA sequencing in 10 paired MPA/SPA tumor tissues and adjacent normal tissues. Consequently, 110 significantly up-regulated lncRNAs and 288 aberrantly down-regulated lncRNAs were identified (|Log2 Foldchange| ≥ 1 and corrected P < 0.05). The top 10 lncRNAs were further analyzed in 89 MPA/SPA tumor tissues and 59 normal tissues from The Cancer Genome Atlas database. Among them, CARD8-AS1 showed the most significant differential expression, and decreased expression of CARD8-AS1 was significantly associated with a poorer prognosis. Functionally, CARD8-AS1 overexpression remarkably suppressed the proliferation, migration and invasion of LUAD cells both in vitro and in vivo. Conversely, inhibition of CARD8-AS1 yielded opposite effects. Mechanistically, CARD8-AS1 acted as a scaffold to facilitate the interaction between TXNRD1 and E3 ubiquitin ligase TRIM25, thereby promoting the degradation of TXNRD1 through the ubiquitin-proteasome pathway. Additionally, TXNRD1 was found to promote LUAD cell proliferation, migration and invasion in vitro. Furthermore, the suppressed progression of LUAD cells resulting from CARD8-AS1 overexpression could be significantly reversed by simultaneous overexpression of TXNRD1. In conclusion, this study revealed that the lncRNA CARD8-AS1 played a suppressive role in the progression of LUAD by enhancing TRIM25-mediated ubiquitination of TXNRD1. The CARD8-AS1-TRIM25-TXNRD1 axis may represent a promising therapeutic target for LUAD.

EIF4A3-Induced CircDHTKD1 regulates glycolysis in non-small cell lung cancer via stabilizing PFKL.

Lung cancer (LC) is one of the malignancies with the highest incidence and mortality in the world, approximately 85% of which is non-small cell lung cancer (NSCLC). Circular RNAs (circRNAs) exert multiple roles in NSCLC occurrence and development. The sequencing results in previous literature have illustrated that multiple circRNAs exhibit upregulation in NSCLC. We attempted to figure out which circRNA exerts an oncogenic role in NSLCL progression. RT-qPCR evaluated circDHTKD1 level in NSCLC tissue specimens and cells. Reverse transcription as well as RNase R digestion assay evaluated circDHTKD1 circular characterization in NSCLC cells. FISH determined circDHTKD1 subcellular distribution in NSCLC cells. Loss- and gain-of-function assays clarified circDHTKD1 role in NSCLC cell growth, tumour growth and glycolysis. Bioinformatics and RIP and RNA pull-down assessed association of circDHTKD1 with upstream molecule Eukaryotic initiation factor 4A-III (EIF4A3) or downstream molecule phosphofructokinase-1 liver type (PFKL) and insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) in NSCLC cells. Rescue assays assessed regulatory function of PFKL in circDHTKD1-meidated NSCLC cellular phenotypes. CircDHTKD1 exhibited upregulation and stable circular nature in NSCLC cells. EIF4A3 upregulated circDHTKD1 in NSCLC cells. CircDHTKD1 exerted a promoting influence on NSCLC cell malignant phenotypes and tumour growth. CircDHTKD1 exerted a promoting influence on NSCLC glucose metabolism. CircDHTKD1 exerts a promoting influence on NSCLC glucose metabolism through PFKL upregulation. RIP and RNA pull-down showed that circDHTKD1 could bind to IGF2BP, PFKL could bind to IGF2BP2, and circDHTKD1 promoted the binding of PFKL to IGF2BP2. In addition, RT-qPCR showed that IGF2BP2 knockdown promoted PFKL mRNA degradation, suggesting that IGF2BP2 stabilized PFKL in NSCLC cells. CircDHTKD1 exhibits upregulation in NSCLC. We innovatively validate that EIF4A3-triggered circDHTKD1 upregulation facilitates NSCLC glycolysis through recruiting m6A reader IGF2BP2 to stabilize PFKL, which may provide a new direction for seeking targeted therapy plans of NSCLC.

Microglia orchestrate synaptic and neuronal stripping: Implication in neuropsychiatric lupus.

Systemic lupus erythematosus (SLE), a multifactorial autoimmune disease, can affect the brain and cause neuropsychiatric dysfunction, also named neuropsychiatric lupus (NPSLE). Microglial activation is observed in NPSLE patients. However, the mechanisms regulating microglia-mediated neurotoxicity in NPSLE remain elusive. Here, we showed that M1-like proinflammatory cytokine levels were increased in the cerebrospinal fluid (CSF) of SLE patients, especially those with neuropsychiatric symptoms. We also demonstrated that MRL/lpr lupus mice developed anxiety-like behaviours and cognitive deficits in the early and active phases of lupus, respectively. An increase in microglial number was associated with upregulation of proinflammatory cytokines in the MRL/lpr mouse brain. RNA sequencing revealed that genes associated with phagocytosis and M1 polarization were upregulated in microglia from lupus mice. Functionally, activated microglia induced synaptic stripping in vivo and promoted neuronal death in vitro. Finally, tofacitinib ameliorated neuropsychiatric disorders in MRL/lpr mice, as evidenced by reductions in microglial number and synaptic/neuronal loss and alleviation of behavioural abnormalities. Thus, our results indicated that classically activated (M1) microglia play a crucial role in NPSLE pathogenesis. Minocycline and tofacitinib were found to alleviate NPSLE by inhibiting micrglial activation, providing a promising therapeutic strategy.

Bioinformatics analysis identifies a key gene HLA_DPA1 in severe influenza-associated immune infiltration.

BACKGROUND: Severe influenza is a serious global health issue that leads to prolonged hospitalization and mortality on a significant scale. The pathogenesis of this infectious disease is poorly understood. Therefore, this study aimed to identify the key genes associated with severe influenza patients necessitating invasive mechanical ventilation. METHODS: The current study utilized two publicly accessible gene expression profiles (GSE111368 and GSE21802) from the Gene Expression Omnibus database. The research focused on identifying the genes exhibiting differential expression between severe and non-severe influenza patients. We employed three machine learning algorithms, namely the Least Absolute Shrinkage and Selection Operator regression model, Random Forest, and Support Vector Machine-Recursive Feature Elimination, to detect potential key genes. The key gene was further selected based on the diagnostic performance of the target genes substantiated in the dataset GSE101702. A single-sample gene set enrichment analysis algorithm was applied to evaluate the participation of immune cell infiltration and their associations with key genes. RESULTS: A total of 44 differentially expressed genes were recognized; among them, we focused on 10 common genes, namely PCOLCE2, HLA_DPA1, LOC653061, TDRD9, MPO, HLA_DQA1, MAOA, S100P, RAP1GAP, and CA1. To ensure the robustness of our findings, we employed overlapping LASSO regression, Random Forest, and SVM-RFE algorithms. By utilizing these algorithms, we were able to pinpoint the aforementioned 10 genes as potential biomarkers for distinguishing between both cases of influenza (severe and non-severe). However, the gene HLA_DPA1 has been recognized as a crucial factor in the pathological condition of severe influenza. Notably, the validation dataset revealed that this gene exhibited the highest area under the receiver operating characteristic curve, with a value of 0.891. The use of single-sample gene set enrichment analysis has provided valuable insights into the immune responses of patients afflicted with severe influenza that have further revealed a categorical correlation between the expression of HLA_DPA1 and lymphocytes. CONCLUSION: The findings indicated that the HLA_DPA1 gene may play a crucial role in the immune-pathological condition of severe influenza and could serve as a promising therapeutic target for patients infected with severe influenza.

Suppression of protein quality control system by TRIM30a sensitises tumour cells to NK cell-mediated immune surveillance.

Tumorigenesis entails circumventing cell-intrinsic regulatory mechanisms while avoiding extrinsic immune surveillance and other host defence systems. Nevertheless, how tumour cells' ability to eliminate misfolded proteins affects immune surveillance remains poorly understood. In this study, we find that overexpression of murine tripartite motif-containing protein 30a (TRIM30a) sensitises tumour cells to natural killer (NK) cells-mediated cytolysis. TRIM30a has no effect on tumour cell proliferation or apoptosis in vitro. However, TRIM30a-overexpressing tumour cells grow substantially slower than control tumour cells in immune-competent mice but not in NK cell-depleted mice. [Correction added on 04 October 2023, after first online publication: 'NK-depleted' has been changed to 'NK cell-depleted' in the preceding sentence.] Mechanistically, TRIM30a overexpression impedes the clearance of misfolded proteins and increases the production of reactive oxygen species induced by proteotoxic stress, implying that TRIM30a impairs protein quality control (PQC) systems in tumour cells. Furthermore, TRIM30a reduces expression of genes encoding proteasome subunits and antioxidant proteins. Our study demonstrates that TRIM30a is a potential tumour suppressor and immune modulator that promotes tumour cytolysis by NK cells, and suggests that an enhanced PQC and antioxidant capacity is an integral part of the immune escape mechanism during tumorigenesis.

Regulation of stomatal development by epidermal, subepidermal and long-distance signals.

Plant leaves consist of three layers, including epidermis, mesophyll and vascular tissues. Their development is meticulously orchestrated. Stomata are the specified structures on the epidermis for uptake of carbon dioxide (CO2) while release of water vapour and oxygen (O2), and thus play essential roles in regulation of plant photosynthesis and water use efficiency. To function efficiently, stomatal formation must coordinate with the development of other epidermal cell types, such as pavement cell and trichome, and tissues of other layers, such as mesophyll and leaf vein. This review summarizes the regulation of stomatal development in three dimensions (3D). In the epidermis, specific stomatal transcription factors determine cell fate transitions and also activate a ligand-receptor- MITOGEN-ACTIVATED PROTEIN KINASE (MAPK) signaling for ensuring proper stomatal density and patterning. This forms the core regulation network of stomatal development, which integrates various environmental cues and phytohormone signals to modulate stomatal production. Under the epidermis, mesophyll, endodermis of hypocotyl and inflorescence stem, and veins in grasses secrete mobile signals to influence stomatal formation in the epidermis. In addition, long-distance signals which may include phytohormones, RNAs, peptides and proteins originated from other plant organs modulate stomatal development, enabling plants to systematically adapt to the ever changing environment.

Unraveling the Influence of Solvent on Side Reactions between Formamidinium Lead Triiodide and Methylammonium Cations.

Formamidinium lead triiodide (FAPbI3) perovskite thin films are commonly deposited through a solution process, often incorporating a specific amount of methylammonium halide to stabilize the α-phase or enhance their crystallinity. The precursor solution for such coatings significantly influences the fabrication of perovskite solar cells (PSCs), involving time-dependent aging and byproduct formation. The chemical principle underlying this behavior is believed to be related to the deprotonation of methylamine cations (MA+) and subsequent chemical reactions with FA+ to generate N-methylformamidinium. Nevertheless, the role of the solvent in the side reactions between these organic cations remains unclear. This work systematically investigates the reaction reactivity in three protic solvents and three aprotic solvents. We uncover the hidden role of dimethylamine from the hydrolysis products of N,N-dimethylformamide, promoting the reaction between FA+ and MA+. Additionally, we elucidate the impact of environmental factors, such as water and oxygen, in stabilizing precursor solutions. This work establishes a basic concept and scientific direction for rationalizing high-efficiency, reproducible, and long-term-stable PSCs.

PARP inhibition leads to synthetic lethality with key splicing-factor mutations in myelodysplastic syndromes.

BACKGROUND: Splicing factors are frequently mutated in patients with myelodysplastic syndromes and acute myeloid leukaemia. Recent studies have revealed convergent molecular defects caused by splicing factor mutations, among which R-loop dysregulation and resultant genome instability are suggested as contributing factors to disease progression. On the other hand, understanding how mutant cells survive upon aberrant R-loop formation and genome instability is essential for developing novel therapeutics. METHODS: The immunoprecipitation was performed to identify R-loops in association with PARP1/poly-ADP-ribosylation. The western blot, immunofluorescence, and flow cytometry assays were used to test the cell viability, cell cycle arrest, apoptosis, and ATM activation in mutant cells following the treatment of the PARP inhibitor. The Srsf2(P95H) knock-in murine hematopoietic cells and MLL-AF9 transformed leukaemia model were generated to investigate the potential of the PARP inhibitor as a therapy for haematological malignancies. RESULTS: The disease-causing mutations in SRSF2 activate PARP and elevate the overall poly-ADP-ribosylation levels of proteins in response to R-loop dysregulation. In accordance, mutant cells are more vulnerable to the PARP inhibitors in comparison to the wild-type counterpart. Notably, the synthetic lethality was further validated in the Srsf2(P95H) knock-in murine hematopoietic cell and MLL-AF9 leukaemia model. CONCLUSIONS: Our findings suggest that mutant cells antagonise the genome threat caused by R-loop disruption by PARP activation, thus making PARP targeting a promising therapeutic strategy for myeloid cancers with mutations in SRSF2.