Alterations of pathogen transmission patterns and attenuated immune stimulation might be the cause of increased adult respiratory infections cases in 2023, results from a multi-center study in mainland China.

Background: Several respiratory infections outbreaks have been observed in mainland China after reduction of non-pharmaceutical interventions. Other countries have seen increases in respiratory infections outside typical seasons post-COVID-19, warranting investigation into underlying causes. Methods: We established monitoring networks for suspected respiratory infection in 14 tertiary hospitals nationwide. PCR for SARS-CoV-2, influenza A and B were performed on 3708 respiratory specimens and deep sequencing were conducted to identify co-infections or newly emerging microbes in 2023. Viral evolutionary analysis was completed. We retrospectively detected serum antibody level for various respiratory pathogens from 4324 adults without respiratory infections over 7 years to observe its dynamic curves. Findings: SARS-CoV-2 and influenza A were the main pathogens during outbreaks in 2023, bacterial-virus and bacterial-bacterial co-infections were most detected, but community co-infections didn't significantly increase pneumonia incidence. Different SARS-CoV-2 and influenza variants were present in different outbreaks, and no novel pathogens were found. The epidemiological patterns of influenza A, COVID-19 and etc. were altered, exhibiting characteristics of being "staggered" compared to most global regions, and potentially led to "overlapping prevalence". Binding antibody testing showed regular fluctuation, without significant decrease against common respiratory pathogens in adults. Influenza A antibody stimulation was attenuated during the 2023 outbreak. Conclusions: "Misaligned" alteration in seasonal respiratory disease patterns possibly caused combined epidemics, leading to cases spike in China, 2023. In adults, antibody levels didn't show significant decline, but reduced immune response to influenza during 2020-2023 emphasizes the need for consistent vaccination during pandemics.

Transfection of Babesia duncani: A Genetic Toolbox of this Pathogen to Advance Babesia Biology.

Human babesiosis is a tick-borne disease caused by Babesia pathogens. The disease, which presents with malaria-like symptoms, can be life-threatening, especially in individuals with weakened immune systems and the elderly. The worldwide prevalence of human babesiosis has been gradually rising, prompting alarm among public health experts. In other pathogens, genetic techniques have proven to be valuable tools for conducting functional studies to understand the importance of specific genes in development and pathogenesis as well as to validate novel cellular targets for drug discovery. Genetic manipulation methods have been established for several non-human Babesia and Theileria species and, more recently, have begun to be developed for human Babesia parasites. We have previously reported the development of a method for genetic manipulation of the human pathogen Babesia duncani. This method is based on positive selection using the hDHFR gene as a selectable marker, whose expression is regulated by the ef-1aB promoter, along with homology regions that facilitate integration into the gene of interest through homologous recombination. Herein, we provide a detailed description of the steps needed to implement this strategy in B. duncani to study gene function. It is anticipated that the implementation of this method will significantly improve our understanding of babesiosis and facilitate the development of novel and more effective therapeutic strategies for the treatment of human babesiosis. Key features This protocol provides an effective means of transfection of B. duncani, enabling genetic manipulation and editing to gain further insights into its biology and pathogenesis. The protocol outlined here for the electroporation of B. duncani represents an advancement over previous methods used for B. bovis [1]. Improvements include higher volume of culture used during the electroporation step and an enhancement in the number of electroporation pulses. These modifications likely enhance the efficiency of gene editing in B. duncani, allowing for quicker and more effective selection of transgenic parasites.

MIECF: Multi-faceted information extraction and cross-mixture fusion for multimodal aspect-based sentiment analysis.

Aspect-level sentiment analysis within multimodal contexts, focusing on the precise identification and interpretation of sentiment attitudes linked to the target aspect across diverse data modalities, remains a focal research area that perpetuates the advancement of discourse and innovation in artificial intelligence. However, most existing methods tend to focus on extracting visual features from only one facet, such as face expression, which ignores the value of information from other key facets, such as the textual information presented by the image modality, resulting in information loss. To overcome the aforementioned constraint, we put forth a novel approach designated as Multi-faceted Information Extraction and Cross-mixture Fusion (MIECF) for Multimodal Aspect-based Sentiment Analysis. Our approach captures more comprehensive visual information in the image and integrates these local and global key features from multiple facets. Local features, such as facial expressions and textual features, provide direct and rich emotional cues. By contrast, the global feature often reflects the overall emotional atmosphere and context. To enhance the visual representation, we designed a Cross-mixture Fusion method to integrate this local and global multimodal information. In particular, the method establishes semantic relationships between local and global features to eliminate ambiguity brought by single-facet information and achieve more accurate contextual understanding, providing a richer and more precise manner for sentiment analysis. The experimental findings indicate that our proposed approach achieves a leading level of performance, resulting in an Accuracy of 79.65 % on the Twitter-2015 dataset, and Macro-F1 scores of 75.90 % and 73.11 % for the Twitter-2015 and Twitter-2017 datasets, respectively.

Identification and characterization of a new species of Taxus - Taxus qinlingensis by multiple taxonomic methods.

BACKGROUND: The taxonomy of Taxus Linn. remains controversial due to its continuous phenotypic variation and unstable topology, thus adversely affecting the formulation of scientific conservation strategies for this genus. Recently, a new ecotype, known as Qinling type, is mainly distributed in the Qinling Mountains and belongs to a monophyletic group. Here, we employed multiple methods including leaf phenotype comparison (leaf shapes and microstructure), DNA barcoding identification (ITS + trnL-trnF + rbcL), and niche analysis to ascertain the taxonomic status of the Qinling type. RESULTS: Multiple comparisons revealed significant differences in the morphological characters (length, width, and length/width ratio) among the Qinling type and other Taxus species. Leaf anatomical analysis indicated that only the Qinling type and T. cuspidata had no papilla under the midvein or tannins in the epicuticle. Phylogenetic analysis of Taxus indicated that the Qinling type belonged to a monophyletic group. Moreover, the Qinling type had formed a relatively independent niche, it was mainly distributed around the Qinling Mountains, Ta-pa Mountains, and Taihang Mountains, situated at an elevation below 1500 m. CONCLUSIONS: Four characters, namely leaf curvature, margin taper, papillation on midvein, and edges were put forward as primary indexes for distinguishing Taxus species. The ecotype Qingling type represented an independent evolutionary lineage and formed a unique ecological niche. Therefore, we suggested that the Qingling type should be treated as a novel species and named it Taxus qinlingensis Y. F. Wen & X. T. Wu, sp. nov.

Isolation and identification of hoylesella marshii causing pleural infection: a case report.

BACKGROUND: Hoylesella marshii can be isolated from human oral cavities affected by dental pulp and periodontal infections, as well as from the dental plaque of healthy individuals, making it a common bacterium within the oral microbiota. However, its role in causing pleural infections in humans is rare. CASE PRESENTATION: A case of purulent pleural effusion occurred shortly after discharge in an elderly patient who had undergone surgery for gastric cancer. The infection was identified as being caused by an obligate anaerobe through laboratory culture, and was further identified as Hoylesella marshii causing pleural infection through 16 S rRNA gene sequence analysis. Susceptibility testing guided precise treatment with cefoperazone-sulbactam and metronidazole. The patient's clinical symptoms improved rapidly, laboratory test indicators gradually returned to normal, and the patient ultimately recovered. CONCLUSION: Hoylesella marshii can cause pleural infections in humans. Clinical microbiology laboratories should pay special attention to the cultivation of obligate anaerobes when routine aerobic cultures do not show bacterial growth but bacteria are visible on smear staining, and when conventional identification methods fail to identify the bacterium, analysis based on the highly conserved 16 S rRNA gene sequence can accurately and specifically identify the bacterium, guiding clinicians in formulating precise anti-infection strategies.

Babesia duncani Pyruvate Kinase Inhibitor Screening and Identification of Key Active Amino Acid Residues.

Babesia duncani (B. duncani), a protozoan parasite prevalent in North America, is a significant threat for human health. Given the regulatory role of pyruvate kinase I (PyK I) in glycolytic metabolism flux and ATP generation, PyK I has been considered the target for drug intervention for a long time. In this study, B. duncani PyK I (BdPyK I) was successfully cloned, expressed, and purified. Polyclonal antibodies were confirmed to recognize the native BdPyK I protein (56 kDa) using Western blotting. AlphaFold software predicted the three-dimensional structure of BdPyK I, and molecular docking with small molecules was conducted to identify potential binding sites of inhibitor on BdPyK I. Moreover, inhibitory effects of six inhibitors (tannic acid, apigenin, shikonin, PKM2 inhibitor, rosiglitazone, and pioglitazone) on BdPyK I were examined under the optimal enzymatic conditions of 3 mM PEP and 3 mM ADP, and significant activity reduction was found. Enzyme kinetics and growth inhibition assays further confirmed the reliability of these inhibitors, with PKM2 inhibitor, tannic acid, and apigenin exhibiting the highest selectivity index as specific inhibitors for B. duncani. Subsequently, key amino acid residues were mutated in both BdPyK I and Homo sapiens pyruvate kinase I (HPyK I), and two differential amino acid residues (isoleucine and phenylalanine) were identified between HPyK I and BdPyK I through PyK activity detection experiments. These findings lay foundation for understanding the role of PyK I in the growth and development of B. duncani, providing insights for babesiosis prevention and drug development.

PIG: Prompt Images Guidance for Night-Time Scene Parsing.

Night-time scene parsing aims to extract pixel-level semantic information in night images, aiding downstream tasks in understanding scene object distribution. Due to limited labeled night image datasets, unsupervised domain adaptation (UDA) has become the predominant method for studying night scenes. UDA typically relies on paired day-night image pairs to guide adaptation, but this approach hampers dataset construction and restricts generalization across night scenes in different datasets. Moreover, UDA, focusing on network architecture and training strategies, faces difficulties in handling classes with few domain similarities. In this paper, we leverage Prompt Images Guidance (PIG) to enhance UDA with supplementary night knowledge. We propose a Night-Focused Network (NFNet) to learn night-specific features from both target domain images and prompt images. To generate high-quality pseudo-labels, we propose Pseudo-label Fusion via Domain Similarity Guidance (FDSG). Classes with fewer domain similarities are predicted by NFNet, which excels in parsing night features, while classes with more domain similarities are predicted by UDA, which has rich labeled semantics. Additionally, we propose two data augmentation strategies: the Prompt Mixture Strategy (PMS) and the Alternate Mask Strategy (AMS), aimed at mitigating the overfitting of the NFNet to a few prompt images. We conduct extensive experiments on four night-time datasets: NightCity, NightCity+, Dark Zurich, and ACDC. The results indicate that utilizing PIG can enhance the parsing accuracy of UDA. The code is available at https://github.com/qiurui4shu/PIG.

Subclone from CT26 resistant to anti-PD-1 therapy associated with increased expression of genes related to glucocorticoids.

BACKGROUND: Although the use of anti-PD-1 antibodies has fundamentally changed traditional cancer treatment, most patients are resistant to anti-PD-1 treatment. Glucocorticoids (GCs) play an important role in tumorigenesis and tumor progression, but the role of endogenous GCs in resistance to anti-PD-1 antibody therapy remains unclear. METHODS: Single cell-derived cell lines (SCDCLs) were generated from a colorectal cancer cell line (CT26) using limiting dilution. We analyzed tumor tissues from anti-PD-1 antibody-treated and untreated mice inoculated with SCDCLs via transcriptome sequencing and flow cytometry to detect pathway activity and immune cell composition changes in the tumor microenvironment. RESULTS: Five SCDCLs were inoculated into wild-type BALB/c mice (all tumorigenic). Single-cell clone (SCC)-2 exhibited the slowest growth rates both in vivo and in vitro compared to other single-cell clones, and better long-term survival than SCC1 and CT26. Flow cytometry showed that SCC2 tumor-bearing mice exhibited significantly higher infiltration of T cells within the tumor tissue, and higher expression of PD-1 on these T cells than the other groups in vivo. However, the SCC2 group showed no response to anti-PD-1 therapy. Transcriptome analysis revealed that the SCC2 group exhibited increased expression of genes related to GC (Hsd11b1, Sgk3, Tgfbr2, and Il7r) compared to SCC2-anti-PD-1 treated tumors. CONCLUSIONS: GC pathway activation is related to resistance to anti-PD-1 therapy.

An improved deep learning network for image detection and its application in Dendrobii caulis decoction piece.

In recent years, with the increasing demand for high-quality Dendrobii caulis decoction piece, the identification of D. caulis decoction piece species has become an urgent issue. However, the current methods are primarily designed for professional quality control and supervision. Therefore, ordinary consumers should not rely on these methods to assess the quality of products when making purchases. This research proposes a deep learning network called improved YOLOv5 for detecting different types of D. caulis decoction piece from images. In the main architecture of improved YOLOv5, we have designed the C2S module to replace the C3 module in YOLOv5, thereby enhancing the network's feature extraction capability for dense and small targets. Additionally, we have introduced the Reparameterized Generalized Feature Pyramid Network (RepGFPN) module and Optimal Transport Assignment (OTA) operator to more effectively integrate the high-dimensional and low-dimensional features of the network. Furthermore, a new large-scale dataset of Dendrobium images has been established. Compared to other models with similar computational complexity, improved YOLOv5 achieves the highest detection accuracy, with an average mAP@.05 of 96.5%. It is computationally equivalent to YOLOv5 but surpasses YOLOv5 by 2 percentage points in terms of accuracy.

Causal relationship between anti-inflammatory drugs and cancer: a pan-cancer study with Mendelian randomization.

Background: Numerous epidemiological studies have elucidated the intricate connection between inflammation and cancer, highlighting how sustained inflammatory responses can fuel carcinogenesis by fostering proliferation, angiogenesis, and metastasis, while dampening immune responses and sensitivity to chemotherapy. Previous clinical investigations have underscored the potential of anti-inflammatory medications in either preventing or mitigating tumor formation. Here, the causal relationship between anti-inflammatory drugs and cancer was further explored through Mendelian randomization studies. Methods: Employing Mendelian randomization, we scrutinized the causal links between three anti-inflammatory drugs-NSAIDs, Aspirin, and Anilide-and 37 types of cancer. We primarily utilized inverse variance weighting (IVW) as the primary analytical approach to delineate the causal association between these drugs and cancer types. Concurrently, sensitivity analyses were conducted to ascertain the absence of horizontal pleiotropy and heterogeneity. Results: Our investigation revealed a discernible causal relationship between certain anti-inflammatory drugs and a subset of cancers, albeit without a pervasive impact across all cancer types. Specifically, NSAIDs exhibited a risk-reducing effect on non-small cell lung cancer (OR: 0.76, 95% CI: 0.59-0.97, p-value: 0.03) and gastric cancer (OR: 0.57, 95% CI: 0.34-0.98, p-value: 0.04). Conversely, aspirin was associated with an increased risk of oral malignant tumors (OR: 2.18, 95% CI: 1.13-4.21, p-value: 0.02). Notably, no statistically significant findings were observed for anilide drugs (p < 0.05). Conclusion: We identified several cancers with potential causal links to NSAIDs, including non-small cell lung cancer and gastric cancer. Despite our extensive analysis, we did not identify a substantial causal relationship between the use of anti-inflammatory drugs and the development of various cancers.

Can carbon emissions trading policy promote product bargaining power increases for high-carbon enterprises? Evidence from China.

Carbon emissions trading policies play a crucial role in facilitating the transition to high-end products within high-carbon enterprises. Nevertheless, current empirical analyses of the carbon emissions trading market exhibit a lack of precision and are susceptible to bias in their findings. Limited research has been conducted on the influence of product quality as a potential constraint on the impact of carbon trading on product bargaining power. This study presents a double-difference model utilizing data on emission-control enterprises in China's carbon market to examine the influence of the carbon emissions trading mechanism on the bargaining power of high-carbon products. Empirical analysis is conducted using financial data from listed companies in China spanning the years 2010 to 2020. The findings indicate that the implementation of carbon emissions trading policies has a dampening impact on the product bargaining power of high-carbon enterprises. Moreover, carbon emissions trading policies have heterogeneous effects on the product bargaining power of high-carbon firms with different life cycles, with mature high-carbon firms receiving a boost and declining high-carbon firms receiving a dampening effect. Mechanism test finds that the incomplete transmission effect of cost shocks resulting from carbon emissions trading policies has negatively affect the product bargaining power of high-carbon enterprises. Further research finds that product quality is a key factor in determining the effect of the carbon emissions trading policy, and that the impact of the carbon emissions trading policy on the bargaining power of products of high-carbon firms takes on a "U" shape due to product quality. Once the product quality exceeds the bottleneck value of 0.5956, the policy significantly increases the bargaining power of products. The study confirms that the establishment of carbon markets can effectively increase the bargaining power of superior products. These results offer a comprehensive theoretical and practical foundation for nations to advance the development of carbon markets and facilitate the achievement of sustainable development by high-carbon enterprises.

HortGenome Search Engine, a universal genomic search engine for horticultural crops.

Horticultural crops comprising fruit, vegetable, ornamental, beverage, medicinal and aromatic plants play essential roles in food security and human health, as well as landscaping. With the advances of sequencing technologies, genomes for hundreds of horticultural crops have been deciphered in recent years, providing a basis for understanding gene functions and regulatory networks and for the improvement of horticultural crops. However, these valuable genomic data are scattered in warehouses with various complex searching and displaying strategies, which increases learning and usage costs and makes comparative and functional genomic analyses across different horticultural crops very challenging. To this end, we have developed a lightweight universal search engine, HortGenome Search Engine (HSE; http://hort.moilab.net), which allows for the querying of genes, functional annotations, protein domains, homologs, and other gene-related functional information of more than 500 horticultural crops. In addition, four commonly used tools, including 'BLAST', 'Batch Query', 'Enrichment analysis', and 'Synteny Viewer' have been developed for efficient mining and analysis of these genomic data.

MT1G induces lipid droplet accumulation through modulation of H3K14 trimethylation accelerating clear cell renal cell carcinoma progression.

BACKGROUND: Lipid droplet formation is a prominent histological feature in clear cell renal cell carcinoma (ccRCC), but the significance and mechanisms underlying lipid droplet accumulation remain unclear. METHODS: Expression and clinical significance of MT1G in ccRCC were analyzed by using TCGA data, GEO data and scRNASeq data. MT1G overexpression or knockdown ccRCC cell lines were constructed and in situ ccRCC model, lung metastasis assay, metabolomics and lipid droplets staining were performed to explore the role of MT1G on lipid droplet accumulation in ccRCC. RESULTS: Initially, we observed low MT1G expression in ccRCC tissues, whereas high MT1G expression correlated with advanced disease stage and poorer prognosis. Elevated MT1G expression promoted ccRCC growth and metastasis both in vitro and in vivo. Mechanistically, MT1G significantly suppressed acylcarnitine levels and downstream tricarboxylic acid (TCA) cycle activity, resulting in increased fatty acid and lipid accumulation without affecting cholesterol metabolism. Notably, MT1G inhibited H3K14 trimethylation (H3K14me3) modification. Under these conditions, MT1G-mediated H3K14me3 was recruited to the CPT1B promoter through direct interaction with specific promoter regions, leading to reduced CPT1B transcription and translation. CONCLUSIONS: Our study unveils a novel mechanism of lipid droplet accumulation in ccRCC, where MT1G inhibits CPT1B expression through modulation of H3K14 trimethylation, consequently enhancing lipid droplet accumulation and promoting ccRCC progression. Graphical abstract figure Schematic diagram illustrating MT1G/H3K14me3/CPT1B-mediated lipid droplet accumulation promoted ccRCC progression via FAO inhibition.

A haplotype-resolved genome assembly of Malus domestica 'Red Fuji'.

The 'Red Fuji' apple (Malus domestica), is one of the most important and popular economic crops worldwide in the fruit industry. Using PacBio HiFi long reads and Hi-C reads, we assembled a high-quality haplotype-resolved genome of 'Red Fuji', with sizes of 668.7 and 668.8 Mb, and N50 sizes of 34.1 and 31.4 Mb. About 97.2% of sequences were anchored in 34 chromosomes. We annotated both haploid genomes, identifying a total of 95,439 protein-coding genes in the two haplotype genomes, with 98% functional annotation. The haplotype-resolved genome of 'Red Fuji' apple stands as a precise benchmark for an array of analyses, such as comparative genomics, transcriptomics, and allelic expression studies. This comprehensive resource is paramount in unraveling variations in allelic expression, advancing quality improvements, and refining breeding efforts.

The genomes of Dahlia pinnata, Cosmos bipinnatus, and Bidens alba in tribe Coreopsideae provide insights into polyploid evolution and inulin biosynthesis.

BACKGROUND: The Coreopsideae tribe, a subset of the Asteraceae family, encompasses economically vital genera like Dahlia, Cosmos, and Bidens, which are widely employed in medicine, horticulture, ecology, and food applications. Nevertheless, the lack of reference genomes hinders evolutionary and biological investigations in this tribe. RESULTS: Here, we present 3 haplotype-resolved chromosome-level reference genomes of the tribe Coreopsideae, including 2 popular flowering plants (Dahlia pinnata and Cosmos bipinnatus) and 1 invasive weed plant (Bidens alba), with assembled genome sizes 3.93 G, 1.02 G, and 1.87 G, respectively. We found that Gypsy transposable elements contribute mostly to the larger genome size of D. pinnata, and multiple chromosome rearrangements have occurred in tribe Coreopsideae. Besides the shared whole-genome duplication (WGD-2) in the Heliantheae alliance, our analyses showed that D. pinnata and B. alba each underwent an independent recent WGD-3 event: in D. pinnata, it is more likely to be a self-WGD, while in B. alba, it is from the hybridization of 2 ancestor species. Further, we identified key genes in the inulin metabolic pathway and found that the pseudogenization of 1-FEH1 and 1-FEH2 genes in D. pinnata and the deletion of 3 key residues of 1-FFT proteins in C. bipinnatus and B. alba may probably explain why D. pinnata produces much more inulin than the other 2 plants. CONCLUSIONS: Collectively, the genomic resources for the Coreopsideae tribe will promote phylogenomics in Asteraceae plants, facilitate ornamental molecular breeding improvements and inulin production, and help prevent invasive weeds.

Novel aptasensor based on polyaniline functionalized carboxylated dobby carbon nanotubes and molybdenum disulfide for endotoxin detection.

Endotoxins, also known as lipopolysaccharides (LPS), are present within the cell walls of Gram-negative bacteria and are released upon cellular death, which can pose a significant risk to human and animal health. Due to the minimal amount of endotoxin required to trigger an inflammatory response in human body, the demand for sensitive methods with low endotoxin detection limits is essential necessary. This paper presents a straightforward aptamer sensor which can enhance the conductivity and specific surface area of molybdenum disulfide (MoS2) by incorporating carboxylated multi-walled carbon nanotubes (MWCNTs-COOH) and polyaniline (PANI). Doping with gold nanoparticles (AuNPs) improves biocompatibility and sensitivity while providing binding sites for thiolated endotoxin-binding aptamers (LBA). This biosensor achieved a remarkable detection limit as low as 0.5 fg mL-1, enabling trace-level identification of LPS. It also exhibits excellent repeatability, selectivity, and stability, facilitating rapid and accurate LPS detection. Moreover, this method demonstrates high recovery rates and specificity for LPS analysis in food samples, showcasing its promising application prospects in trace-level LPS detection within the food industry.

FOXP4-mediated induction of PTK7 activates the Wnt/ß-catenin pathway and promotes ovarian cancer development.

Ovarian cancer (OV) poses a significant challenge in clinical settings due to its difficulty in early diagnosis and treatment resistance. FOXP4, belonging to the FOXP subfamily, plays a pivotal role in various biological processes including cancer, cell cycle regulation, and embryonic development. However, the specific role and importance of FOXP4 in OV have remained unclear. Our research showed that FOXP4 is highly expressed in OV tissues, with its elevated levels correlating with poor prognosis. We further explored FOXP4's function through RNA sequencing and functional analysis in FOXP4-deficient cells, revealing its critical role in activating the Wnt signaling pathway. This activation exacerbates the malignant phenotype in OV. Mechanistically, FOXP4 directly induces the expression of protein tyrosine kinase 7 (PTK7), a Wnt-binding receptor tyrosine pseudokinase, which causes abnormal activation of the Wnt signaling pathway. Disrupting the FOXP4-Wnt feedback loop by inactivating the Wnt signaling pathway or reducing FOXP4 expression resulted in the reduction of the malignant phenotype of OV cells, while restoring PTK7 expression reversed this effect. In conclusion, our findings underscore the significance of the FOXP4-induced Wnt pathway activation in OV, suggesting the therapeutic potential of targeting this pathway in OV treatment.

Structural optimization of Moracin M as novel selective phosphodiesterase 4 inhibitors for the treatment of idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and high mortality lung disease. Although the antifibrotic drugs pirfenidone and nintedanib could slow the rate of lung function decline, the usual course of the condition is inexorably to respiratory failure and death. Therefore, new approaches and novel therapeutic drugs for the treatment of IPF are urgently needed. And the selective PDE4 inhibitor has in vivo and in vitro anti-fibrotic effects in IPF models. But the clinical application of most PDE4 inhibitors are limited by their unexpected and severe side effects such as nausea, vomiting, and diarrhea. Herein, structure-based optimizations of the natural product Moracin M resulted in a novel a novel series of 2-arylbenzofurans as potent PDE4 inhibitors. The most potent inhibitor L13 has an IC50 of 36 ± 7 nM with remarkable selectivity across the PDE families and administration of L13·citrate (10.0 mg/kg) exhibited comparable anti-pulmonary fibrosis effects to pirfenidone (300 mg/kg) in a bleomycin-induced IPF mice model, indicate that L13 is a potential lead for the treatment of IPF.

Nanofiber-induced hierarchically-porous magnesium phosphate bone cements accelerate bone regeneration by inhibiting Notch signaling.

Magnesium phosphate bone cements (MPC) have been recognized as a viable alternative for bone defect repair due to their high mechanical strength and biodegradability. However, their poor porosity and permeability limit osteogenic cell ingrowth and vascularization, which is critical for bone regeneration. In the current study, we constructed a novel hierarchically-porous magnesium phosphate bone cement by incorporating extracellular matrix (ECM)-mimicking electrospun silk fibroin (SF) nanofibers. The SF-embedded MPC (SM) exhibited a heterogeneous and hierarchical structure, which effectively facilitated the rapid infiltration of oxygen and nutrients as well as cell ingrowth. Besides, the SF fibers improved the mechanical properties of MPC and neutralized the highly alkaline environment caused by excess magnesium oxide. Bone marrow stem cells (BMSCs) adhered excellently on SM, as illustrated by formation of more pseudopodia. CCK8 assay showed that SM promoted early proliferation of BMSCs. Our study also verified that SM increased the expression of OPN, RUNX2 and BMP2, suggesting enhanced osteogenic differentiation of BMSCs. We screened for osteogenesis-related pathways, including FAK signaing, Wnt signaling and Notch signaling, and found that SM aided in the process of bone regeneration by suppressing the Notch signaling pathway, proved by the downregulation of NICD1, Hes1 and Hey2. In addition, using a bone defect model of rat calvaria, the study revealed that SM exhibited enhanced osteogenesis, bone ingrowth and vascularization compared with MPC alone. No adverse effect was found after implantation of SM in vivo. Overall, our novel SM exhibited promising prospects for the treatment of critical-sized bone defects.