Oral Iptacopan Monotherapy in Paroxysmal Nocturnal Hemoglobinuria.

BACKGROUND: Persistent hemolytic anemia and a lack of oral treatments are challenges for patients with paroxysmal nocturnal hemoglobinuria who have received anti-C5 therapy or have not received complement inhibitors. Iptacopan, a first-in-class oral factor B inhibitor, has been shown to improve hemoglobin levels in these patients. METHODS: In two phase 3 trials, we assessed iptacopan monotherapy over a 24-week period in patients with hemoglobin levels of less than 10 g per deciliter. In the first, anti-C5-treated patients were randomly assigned to switch to iptacopan or to continue anti-C5 therapy. In the second, single-group trial, patients who had not received complement inhibitors and who had lactate dehydrogenase (LDH) levels more than 1.5 times the upper limit of the normal range received iptacopan. The two primary end points in the first trial were an increase in the hemoglobin level of at least 2 g per deciliter from baseline and a hemoglobin level of at least 12 g per deciliter, each without red-cell transfusion; the primary end point for the second trial was an increase in hemoglobin level of at least 2 g per deciliter from baseline without red-cell transfusion. RESULTS: In the first trial, 51 of the 60 patients who received iptacopan had an increase in the hemoglobin level of at least 2 g per deciliter from baseline, and 42 had a hemoglobin level of at least 12 g per deciliter, each without transfusion; none of the 35 anti-C5-treated patients attained the end-point levels. In the second trial, 31 of 33 patients had an increase in the hemoglobin level of at least 2 g per deciliter from baseline without red-cell transfusion. In the first trial, 59 of the 62 patients who received iptacopan and 14 of the 35 anti-C5-treated patients did not require or receive transfusion; in the second trial, no patients required or received transfusion. Treatment with iptacopan increased hemoglobin levels, reduced fatigue, reduced reticulocyte and bilirubin levels, and resulted in mean LDH levels that were less than 1.5 times the upper limit of the normal range. Headache was the most frequent adverse event with iptacopan. CONCLUSIONS: Iptacopan treatment improved hematologic and clinical outcomes in anti-C5-treated patients with persistent anemia - in whom iptacopan showed superiority to anti-C5 therapy - and in patients who had not received complement inhibitors. (Funded by Novartis; APPLY-PNH ClinicalTrials.gov number, NCT04558918; APPOINT-PNH ClinicalTrials.gov number, NCT04820530.).

The Y locus encodes a REPRESSOR OF PHOTOSYNTHETIC GENES protein that represses carotenoid biosynthesis via interaction with APRR2 in carrot.

Little is known about the factors regulating carotenoid biosynthesis in roots. In this study, we characterized DCAR_032551, the candidate gene of the Y locus responsible for the transition of root color from ancestral white to yellow during carrot (Daucus carota) domestication. We show that DCAR_032551 encodes a REPRESSOR OF PHOTOSYNTHETIC GENES (RPGE) protein, named DcRPGE1. DcRPGE1 from wild carrot (DcRPGE1W) is a repressor of carotenoid biosynthesis. Specifically, DcRPGE1W physically interacts with DcAPRR2, an ARABIDOPSIS PSEUDO-RESPONSE REGULATOR2 (APRR2)-like transcription factor. Through this interaction, DcRPGE1W suppresses DcAPRR2-mediated transcriptional activation of the key carotenogenic genes phytoene synthase 1 (DcPSY1), DcPSY2, and lycopene ε-cyclase (DcLCYE), which strongly decreases carotenoid biosynthesis. We also demonstrate that the DcRPGE1W-DcAPRR2 interaction prevents DcAPRR2 from binding to the RGATTY elements in the promoter regions of DcPSY1, DcPSY2, and DcLCYE. Additionally, we identified a mutation in the DcRPGE1 coding region of yellow and orange carrots that leads to the generation of alternatively spliced transcripts encoding truncated DcRPGE1 proteins unable to interact with DcAPRR2, thereby failing to suppress carotenoid biosynthesis. These findings provide insights into the transcriptional regulation of carotenoid biosynthesis and offer potential target genes for enhancing carotenoid accumulation in crop plants.

Spatial spillovers of violent conflict amplify the impacts of climate variability on malaria risk in sub-Saharan Africa.

Africa carries a disproportionately high share of the global malaria burden, accounting for 94% of malaria cases and deaths worldwide in 2019. It is also a politically unstable region and the most vulnerable continent to climate change in recent decades. Knowledge about the modifying impacts of violent conflict on climate-malaria relationships remains limited. Here, we quantify the associations between violent conflict, climate variability, and malaria risk in sub-Saharan Africa using health surveys from 128,326 individuals, historical climate data, and 17,429 recorded violent conflicts from 2006 to 2017. We observe that spatial spillovers of violent conflict (SSVCs) have spatially distant effects on malaria risk. Malaria risk induced by SSVCs within 50 to 100 km from the households gradually increases from 0.1% (not significant, P>0.05) to 6.5% (95% CI: 0 to 13.0%). SSVCs significantly promote malaria risk within the average 20.1 to 26.9 °C range. At the 12-mo mean temperature of 22.5 °C, conflict deaths have the largest impact on malaria risk, with an approximately 5.8% increase (95% CI: 1.0 to 11.0%). Additionally, a pronounced association between SSVCs and malaria risk exists in the regions with 9.2 wet days per month. The results reveal that SSVCs increase population exposure to harsh environments, amplifying the effect of warm temperature and persistent precipitation on malaria transmission. Violent conflict therefore poses a substantial barrier to mosquito control and malaria elimination efforts in sub-Saharan Africa. Our findings support effective targeting of treatment programs and vector control activities in conflict-affected regions with a high malaria risk.

Insights into Strain Engineering: From Ferroelectrics to Related Functional Materials and Beyond.

Ferroelectrics have become indispensable components in various application fields, including information processing, energy harvesting, and electromechanical conversion, owing to their unique ability to exhibit electrically or mechanically switchable polarization. The distinct polar noncentrosymmetric lattices of ferroelectrics make them highly responsive to specific crystal structures. Even slight changes in the lattice can alter the polarization configuration and response to external fields. In this regard, strain engineering has emerged as a prevalent regulation approach that not only offers a versatile platform for structural and performance optimization within ferroelectrics but also unlocks boundless potential in various functional materials. In this review, we systematically summarize the breakthroughs in ferroelectric-based functional materials achieved through strain engineering and progress in method development. We cover research activities ranging from fundamental attributes to wide-ranging applications and novel functionalities ranging from electromechanical transformation in sensors and actuators to tunable dielectric materials and information technologies, such as transistors and nonvolatile memories. Building upon these achievements, we also explore the endeavors to uncover the unprecedented properties through strain engineering in related chemical functionalities, such as ferromagnetism, multiferroicity, and photoelectricity. Finally, through discussions on the prospects and challenges associated with strain engineering in the materials, this review aims to stimulate the development of new methods for strain regulation and performance boosting in functional materials, transcending the boundaries of ferroelectrics.

The high-quality genome of Cryptotaenia japonica and comparative genomics analysis reveals anthocyanin biosynthesis in Apiaceae.

Cryptotaenia japonica, a traditional medicinal and edible vegetable crops, is well-known for its attractive flavors and health care functions. As a member of the Apiaceae family, the evolutionary trajectory and biological properties of C. japonica are not clearly understood. Here, we first reported a high-quality genome of C. japonica with a total length of 427 Mb and N50 length 50.76 Mb, was anchored into 10 chromosomes, which confirmed by chromosome (cytogenetic) analysis. Comparative genomic analysis revealed C. japonica exhibited low genetic redundancy, contained a higher percentage of single-cope gene families. The homoeologous blocks, Ks, and collinearity were analyzed among Apiaceae species contributed to the evidence that C. japonica lacked recent species-specific WGD. Through comparative genomic and transcriptomic analyses of Apiaceae species, we revealed the genetic basis of the production of anthocyanins. Several structural genes encoding enzymes and transcription factor genes of the anthocyanin biosynthesis pathway in different species were also identified. The CjANSa, CjDFRb, and CjF3H gene might be the target of Cjaponica_2.2062 (bHLH) and Cjaponica_1.3743 (MYB). Our findings provided a high-quality reference genome of C. japonica and offered new insights into Apiaceae evolution and biology.

Rectifying METTL4-Mediated N6-Methyladenine Excess in Mitochondrial DNA Alleviates Heart Failure.

BACKGROUND: Myocardial mitochondrial dysfunction underpins the pathogenesis of heart failure (HF), yet therapeutic options to restore myocardial mitochondrial function are scarce. Epigenetic modifications of mitochondrial DNA (mtDNA), such as methylation, play a pivotal role in modulating mitochondrial homeostasis. However, their involvement in HF remains unclear. METHODS: Experimental HF models were established through continuous angiotensin II and phenylephrine (AngII/PE) infusion or prolonged myocardial ischemia/reperfusion injury. The landscape of N6-methyladenine (6mA) methylation within failing cardiomyocyte mtDNA was characterized using high-resolution mass spectrometry and methylated DNA immunoprecipitation sequencing. A tamoxifen-inducible cardiomyocyte-specific Mettl4 knockout mouse model and adeno-associated virus vectors designed for cardiomyocyte-targeted manipulation of METTL4 (methyltransferase-like protein 4) expression were used to ascertain the role of mtDNA 6mA and its methyltransferase METTL4 in HF. RESULTS: METTL4 was predominantly localized within adult cardiomyocyte mitochondria. 6mA modifications were significantly more abundant in mtDNA than in nuclear DNA. Postnatal cardiomyocyte maturation presented with a reduction in 6mA levels within mtDNA, coinciding with a decrease in METTL4 expression. However, an increase in both mtDNA 6mA level and METTL4 expression was observed in failing adult cardiomyocytes, suggesting a shift toward a neonatal-like state. METTL4 preferentially targeted mtDNA promoter regions, which resulted in interference with transcription initiation complex assembly, mtDNA transcriptional stalling, and ultimately mitochondrial dysfunction. Amplifying cardiomyocyte mtDNA 6mA through METTL4 overexpression led to spontaneous mitochondrial dysfunction and HF phenotypes. The transcription factor p53 was identified as a direct regulator of METTL4 transcription in response to HF-provoking stress, thereby revealing a stress-responsive mechanism that controls METTL4 expression and mtDNA 6mA. Cardiomyocyte-specific deletion of the Mettl4 gene eliminated mtDNA 6mA excess, preserved mitochondrial function, and mitigated the development of HF upon continuous infusion of AngII/PE. In addition, specific silencing of METTL4 in cardiomyocytes restored mitochondrial function and offered therapeutic relief in mice with preexisting HF, irrespective of whether the condition was induced by AngII/PE infusion or myocardial ischemia/reperfusion injury. CONCLUSIONS: Our findings identify a pivotal role of cardiomyocyte mtDNA 6mA and the corresponding methyltransferase, METTL4, in the pathogenesis of mitochondrial dysfunction and HF. Targeted suppression of METTL4 to rectify mtDNA 6mA excess emerges as a promising strategy for developing mitochondria-focused HF interventions.

'Bingo'-a large language model- and graph neural network-based workflow for the prediction of essential genes from protein data.

The identification and characterization of essential genes are central to our understanding of the core biological functions in eukaryotic organisms, and has important implications for the treatment of diseases caused by, for example, cancers and pathogens. Given the major constraints in testing the functions of genes of many organisms in the laboratory, due to the absence of in vitro cultures and/or gene perturbation assays for most metazoan species, there has been a need to develop in silico tools for the accurate prediction or inference of essential genes to underpin systems biological investigations. Major advances in machine learning approaches provide unprecedented opportunities to overcome these limitations and accelerate the discovery of essential genes on a genome-wide scale. Here, we developed and evaluated a large language model- and graph neural network (LLM-GNN)-based approach, called 'Bingo', to predict essential protein-coding genes in the metazoan model organisms Caenorhabditis elegans and Drosophila melanogaster as well as in Mus musculus and Homo sapiens (a HepG2 cell line) by integrating LLM and GNNs with adversarial training. Bingo predicts essential genes under two 'zero-shot' scenarios with transfer learning, showing promise to compensate for a lack of high-quality genomic and proteomic data for non-model organisms. In addition, the attention mechanisms and GNNExplainer were employed to manifest the functional sites and structural domain with most contribution to essentiality. In conclusion, Bingo provides the prospect of being able to accurately infer the essential genes of little- or under-studied organisms of interest, and provides a biological explanation for gene essentiality.

Predicting single-cell cellular responses to perturbations using cycle consistency learning.

SUMMARY: Phenotype-based drug screening emerges as a powerful approach for identifying compounds that actively interact with cells. Transcriptional and proteomic profiling of cell lines and individual cells provide insights into the cellular state alterations that occur at the molecular level in response to external perturbations, such as drugs or genetic manipulations. In this paper, we propose cycleCDR, a novel deep learning framework to predict cellular response to external perturbations. We leverage the autoencoder to map the unperturbed cellular states to a latent space, in which we postulate the effects of drug perturbations on cellular states follow a linear additive model. Next, we introduce the cycle consistency constraints to ensure that unperturbed cellular state subjected to drug perturbation in the latent space would produces the perturbed cellular state through the decoder. Conversely, removal of perturbations from the perturbed cellular states can restore the unperturbed cellular state. The cycle consistency constraints and linear modeling in the latent space enable to learn transferable representations of external perturbations, so that our model can generalize well to unseen drugs during training stage. We validate our model on four different types of datasets, including bulk transcriptional responses, bulk proteomic responses, and single-cell transcriptional responses to drug/gene perturbations. The experimental results demonstrate that our model consistently outperforms existing state-of-the-art methods, indicating our method is highly versatile and applicable to a wide range of scenarios. AVAILABILITY AND IMPLEMENTATION: The source code is available at: https://github.com/hliulab/cycleCDR.

An anthocyanin activation gene underlies the purple central flower pigmentation in wild carrot.

Many organisms have complex pigmentation patterns. However, how these patterns are formed remains largely unknown. In wild carrot (Daucus carota subsp. carota), which is also known as Queen Anne's lace, one or several purple central flowers occur in white umbels. Here, we investigated the unique central flower pigmentation pattern in wild carrot umbels. Using wild and cultivated carrot (Daucus carota subsp. sativus L.) accessions, transcriptome analysis, protein interaction, stable transformation, and CRISPR/Cas9-mediated knockout, a anthocyanin-activating R2R3-myeloblastosis (MYB) gene, Purple Central Flower (DcPCF), was identified as the causal gene that triggers only central flowers to possess the purple phenotype. The expression of DcPCF was only detected in tiny central flowers. We propose that the transition from purple to nonpurple flowers in the center of the umbel occurred after three separate adverse events: insertion of transposons in the promoter region, premature termination of the coding sequence (caused by a C-T substitution in the open reading frame), and the emergence of unknown anthocyanin suppressors. These three events could have occurred either consecutively or independently. The intriguing purple central flower pattern and its underlying mechanism may provide evidence that it is a remnant of ancient conditions of the species, reflecting the original appearance of Umbelliferae (also called Apiaceae) when a single flower was present.

Metformin switches cell death modes to soothe the apical periodontitis via ZBP1.

Apical periodontitis (AP) is a disease caused by pathogenic microorganisms and featured with the degradation of periapical hard tissue. Our recent research showed the crucial role of Z-DNA binding protein 1 (ZBP1)-mediated necroptosis and apoptosis in the pathogenesis of AP. However, the specific regulatory mechanisms of ZBP1 in AP are not fully elucidated. It was found that metformin has a regulatory role in cell necroptosis and apoptosis. But whether and how metformin regulates necroptosis and apoptosis through the ZBP1 in the context of AP remains unknown. This study provided evidence that lipopolysaccharide (LPS) promotes the synthesis of left-handed Z-nucleic acids (Z-NA), which in turn activates ZBP1. Knockout of Zbp1 by CRISPR/Cas9 technology significantly reduced LPS-induced necroptosis and apoptosis in vitro. By using Zbp1-knockout mice, periapical bone destruction was alleviated. Moreover, type I interferon induced the expression of interferon-stimulated genes (ISGs), which serve as a major source of Z-NA. In addition, the RNA-editing enzyme Adenosine Deaminase RNA specific 1 (ADAR1) prevented the accumulation of endogenous Z-NA. Meanwhile, metformin suppressed the ZBP1-mediated necroptosis by inhibiting the expression of ZBP1 and the accumulation of ISGs. Metformin also promoted mitochondrial apoptosis, which is critical for the elimination of intracellular bacterial infection. The enhanced apoptosis further promoted the healing of infected apical bone tissues. In summary, these results demonstrated that the recognition of Z-NA by ZBP1 plays an important role in AP pathogenesis. Metformin suppressed ZBP1-mediated necroptosis and promoted apoptosis, thereby contributing to the soothing of inflammation and bone healing in AP.

DBDNMF: A Dual Branch Deep Neural Matrix Factorization method for drug response prediction.

Anti-cancer response of cell lines to drugs is in urgent need for individualized precision medical decision-making in the era of precision medicine. Measurements with wet-experiments is time-consuming and expensive and it is almost impossible for wide ranges of application. The design of computational models that can precisely predict the responses between drugs and cell lines could provide a credible reference for further research. Existing methods of response prediction based on matrix factorization or neural networks have revealed that both linear or nonlinear latent characteristics are applicable and effective for the precise prediction of drug responses. However, the majority of them consider only linear or nonlinear relationships for drug response prediction. Herein, we propose a Dual Branch Deep Neural Matrix Factorization (DBDNMF) method to address the above-mentioned issues. DBDNMF learns the latent representation of drugs and cell lines through flexible inputs and reconstructs the partially observed matrix through a series of hidden neural network layers. Experimental results on the datasets of Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (GDSC) show that the accuracy of drug prediction exceeds state-of-the-art drug response prediction algorithms, demonstrating its reliability and stability. The hierarchical clustering results show that drugs with similar response levels tend to target similar signaling pathway, and cell lines coming from the same tissue subtype tend to share the same pattern of response, which are consistent with previously published studies.

scGAAC: A graph attention autoencoder for clustering single-cell RNA-sequencing data.

Single-cell RNA-sequencing (scRNA-seq) enables the investigation of intricate mechanisms governing cell heterogeneity and diversity. Clustering analysis remains a pivotal tool in scRNA-seq for discerning cell types. However, persistent challenges arise from noise, high dimensionality, and dropout in single-cell data. Despite the proliferation of scRNA-seq clustering methods, these often focus on extracting representations from individual cell expression data, neglecting potential intercellular relationships. To overcome this limitation, we introduce scGAAC, a novel clustering method based on an attention-based graph convolutional autoencoder. By leveraging structural information between cells through a graph attention autoencoder, scGAAC uncovers latent relationships while extracting representation information from single-cell gene expression patterns. An attention fusion module amalgamates the learned features of the graph attention autoencoder and the autoencoder through attention weights. Ultimately, a self-supervised learning policy guides model optimization. scGAAC, a hypothesis-free framework, performs better on four real scRNA-seq datasets than most state-of-the-art methods. The scGAAC implementation is publicly available on Github at: https://github.com/labiip/scGAAC.

Auditory training remodels hippocampus-related memory in adult rats.

Consequences of perceptual training, such as improvements in discriminative ability, are highly stimulus and task specific. Therefore, most studies on auditory training-induced plasticity in adult brain have focused on the sensory aspects, particularly on functional and structural effects in the auditory cortex. Auditory training often involves, other than auditory demands, significant cognitive components. Yet, how auditory training affects cognition-related brain regions, such as the hippocampus, remains unclear. Here, we found in female rats that auditory cue-based go/no-go training significantly improved the memory-guided behaviors associated with hippocampus. The long-term potentiations of the trained rats recorded in vivo in the hippocampus were also enhanced compared with the naïve rats. In parallel, the phosphorylation level of calcium/calmodulin-dependent protein kinase II and the expression of parvalbumin-positive interneurons in the hippocampus were both upregulated. These findings demonstrate that auditory training substantially remodels the processing and function of brain regions beyond the auditory system, which are associated with task demands.

Application of improved GalNAc conjugation in development of cost-effective siRNA therapies targeting cardiovascular diseases.

N-Acetylgalactosamine (GalNAc)-conjugated small interfering RNA (siRNA) therapies have received approval for treating both orphan and prevalent diseases. To improve in vivo efficacy and streamline the chemical synthesis process for efficient and cost-effective manufacturing, we conducted this study to identify better designs of GalNAc-siRNA conjugates for therapeutic development. Here, we present data on redesigned GalNAc-based ligands conjugated with siRNAs against angiopoietin-like 3 (ANGPTL3) and lipoprotein (a) (Lp(a)), two target molecules with the potential to address large unmet medical needs in atherosclerotic cardiovascular diseases. By attaching a novel pyran-derived scaffold to serial monovalent GalNAc units before solid-phase oligonucleotide synthesis, we achieved increased GalNAc-siRNA production efficiency with fewer synthesis steps compared to the standard triantennary GalNAc construct L96. The improved GalNAc-siRNA conjugates demonstrated equivalent or superior in vivo efficacy compared to triantennary GalNAc-conjugated siRNAs.

APC mutations disrupt ß-catenin destruction complex condensates organized by Axin phase separation.

The Wnt/ß-catenin pathway is critical to maintaining cell fate decisions. Recent study showed that liquid-liquid-phase separation (LLPS) of Axin organized the ß-catenin destruction complex condensates in a normal cellular state. Mutations inactivating the APC gene are found in approximately 80% of all human colorectal cancer (CRC). However, the molecular mechanism of the formation of ß-catenin destruction complex condensates organized by Axin phase separation and how APC mutations impact the condensates are still unclear. Here, we report that the ß-catenin destruction complex, which is constructed by Axin, was assembled condensates via a phase separation process in CRC cells. The key role of wild-type APC is to stabilize destruction complex condensates. Surprisingly, truncated APC did not affect the formation of condensates, and GSK 3ß and CK1α were unsuccessfully recruited, preventing ß-catenin phosphorylation and resulting in accumulation in the cytoplasm of CRCs. Besides, we propose that the phase separation ability of Axin participates in the nucleus translocation of ß-catenin and be incorporated and concentrated into transcriptional condensates, affecting the transcriptional activity of Wnt signaling pathway.

Emergent Three-Dimensional Electric Dipole Sinewave in Bulk Perovskite Oxides.

The magnetic and electric dipoles of ferroics play a central role in their fascinating properties. In particular, topological configurations have shown promising potential for use in novel electromechanical and electronic devices. Magnetic configurations from simple collinear to complex topological are well-documented. In contrast, many complex topological features in the electric counterpart remain unexplored. Here, we report the first example of three-dimensional electric dipole sinewave topological structure in a PbZrO3-based bulk perovskite, which presents an interesting triple-hysteresis loop macroscopically. This polar configuration consists of two orthogonal sinewave electric dipole modulations decoded from a polar incommensurate phase by advanced diffraction and atomic-resolution imaging techniques. The resulting topology is unraveled to be the competition between the antiferroelectric and ferroelectric states, stabilized by the modulation of the Pb 6s2 lone pair and the antiferrodistortive effect. These findings further reinforce the similarity of the magnetic and electric topologies.

Glycogen synthase kinase-3ß: A multifaceted player in ischemia-reperfusion injury and its therapeutic prospects.

Ischemia-reperfusion injury (IRI) results in irreversible metabolic dysfunction and structural damage to tissues or organs, posing a formidable challenge in the field of organ implantation, cardiothoracic surgery, and general surgery. Glycogen synthase kinase-3ß (GSK-3ß) a multifunctional serine/threonine kinase, is involved in a variety of biological processes, including cell proliferation, apoptosis, and immune response. Phosphorylation of its tyrosine 216 and serine 9 sites positively and negatively regulates the activation and inactivation of the enzyme. Significantly, inhibition or inactivation of GSK-3ß provides protection against IRI, making it a viable target for drug development. Though numerous GSK-3ß inhibitors have been identified to date, the development of therapeutic treatments remains a considerable distance away. In light of this, this review summarizes the complicated network of GSK-3ß roles in IRI. First, we provide an overview of GSK-3ß's basic background. Subsequently, we briefly review the pathological mechanisms of GSK-3ß in accelerating IRI, and highlight the latest progress of GSK-3ß in multiorgan IRI, encompassing heart, brain, kidney, liver, and intestine. Finally, we discuss the current development of GSK-3ß inhibitors in various organ IRI, offering a thorough and insightful reference for GSK-3ß as a potential target for future IRI therapy.

Identification and expression analysis of Sox family genes in echinoderms.

The Sox gene family, a collection of transcription factors widely distributed throughout the animal kingdom, plays a crucial role in numerous developmental processes. Echinoderms occupy a pivotal position in many research fields, such as neuroscience, sex determination and differentiation, and embryonic development. However, to date, no comprehensive study has been conducted to characterize and analyze Sox genes in echinoderms. In the present study, the evolution and expression of Sox family genes across 11 echinoderms were analyzed using bioinformatics methods. The results revealed a total of 70 Sox genes, with counts ranging from 5 to 8 across different echinoderms. Phylogenetic analysis revealed that the identified Sox genes could be categorized into seven distinct classes: the SoxB1 class, SoxB2 class, SoxC class, SoxD class, SoxE class, SoxF class and SoxH class. Notably, the SoxB1, SoxB2, and SoxF genes were ubiquitously present in all the echinoderms studied, which suggests that these genes may be conserved in echinoderms. The spatiotemporal expression patterns observed for Sox genes in the three echinoderms indicated that various Sox members perform distinct functional roles. Notably, SoxB1 is likely involved in echinoderm ovary development, while SoxH may play a crucial role in testis development in starfish and sea cucumber. In general, the present investigation provides a molecular foundation for exploring the Sox gene in echinoderms, providing a valuable resource for future phylogenetic and genomic studies.

Identification of circRNAs expression profiles and functional networks in parotid gland of type 2 diabetes mouse.

BACKGROUND: Circular RNAs (circRNAs) are a novel kind of non-coding RNAs proved to play crucial roles in the development of multiple diabetic complications. However, their expression and function in diabetes mellitus (DM)-impaired salivary glands are unknown. RESULTS: By using microarray technology, 663 upregulated and 999 downregulated circRNAs companied with 813 upregulated and 525 downregulated mRNAs were identified in the parotid glands (PGs) of type2 DM mice under a 2-fold change and P < 0.05 cutoff criteria. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analysis of upregulated mRNAs showed enrichments in immune system process and peroxisome proliferator-activated receptor (PPAR) signaling pathway. Infiltration of inflammatory cells and increased inflammatory cytokines were observed in diabetic PGs. Seven differently expressed circRNAs validated by qRT-PCR were selected for coding-non-coding gene co-expression (CNC) and competing endogenous RNA (ceRNA) networks analysis. PPAR signaling pathway was primarily enriched through analysis of circRNA-mRNA networks. Moreover, the circRNA-miRNA-mRNA networks highlighted an enrichment in the regulation of actin cytoskeleton. CONCLUSION: The inflammatory response is elevated in diabetic PGs. The selected seven distinct circRNAs may attribute to the injury of diabetic PG by modulating inflammatory response through PPAR signaling pathway and actin cytoskeleton in diabetic PGs.

Redox Reactions of Organic Molecules Using Rotating Magnetic Field and Metal Rods.

In recent years, redox reactions have harnessed light or mechanical energy to enable the formation of chemical bonds. We postulated a complementary approach that electromagnetic induction could promote the redox reaction of organic molecules using a rotating magnetic field and metal rods. Here, we report that electromotive force activates the redox-active trifluoromethylating reagents. This magnetoredox system can be applied to the trifluoromethylation of heteroarenes with high regioselectivity and hydrotrifluoromethylation of alkenes without the need for catalysts and organic additives.