Fascin-1 limits myosin activity in microglia to control mechanical characterization of the injured spinal cord.

BACKGROUND: Mechanical softening of the glial scar region regulates axonal regeneration to impede neurological recovery in central nervous system (CNS) injury. Microglia, a crucial cellular component of the glial scar, facilitate neuronal survival and neurological recovery after spinal cord injury (SCI). However, the critical mechanical characterization of injured spinal cord that harmonizes neuroprotective function of microglia remains poorly understood. METHODS: Spinal cord tissue stiffness was assessed using atomic force microscopy (AFM) in a mouse model of crush injury. Pharmacological depletion of microglia using PLX5622 was used to explore the effect of microglia on mechanical characterization. Conditional knockout of Fascin-1 in microglia (Fascin-1 CKO) alone or in combination with inhibition of myosin activity was performed to delve into relevant mechanisms of microglia regulating mechanical signal. Immunofluorescence staining was performed to evaluate the related protein levels, inflammatory cells, and neuron survival after SCI. The Basso mouse scale score was calculated to assess functional recovery. RESULTS: Spinal cord tissue significantly softens after SCI. Microglia depletion or Fascin-1 knockout in microglia limits tissue softening and alters mechanical characterization, which leads to increased tissue pathology and impaired functional recovery. Mechanistically, Fascin-1 inhibits myosin activation to promote microglial migration and control mechanical characterization after SCI. CONCLUSIONS: We reveal that Fascin-1 limits myosin activity to regulate mechanical characterization after SCI, and this mechanical signal should be considered in future approaches for the treatment of CNS diseases.

Synergistic effects of photodynamic therapy and chemotherapy: Activating the intrinsic/extrinsic apoptotic pathway of anoikis for triple-negative breast cancer treatment.

Triple-negative breast cancer (TNBC) is a highly invasive and metastatic subtype of breast cancer that often recurs after surgery. Herein, we developed a cyclodextrin-based tumor-targeted nano delivery system that incorporated the photosensitizer chlorin e6 (Ce6) and the chemotherapeutic agent lonidamine (LND) to form the R6RGD-CMßCD-se-se-Ce6/LND nanoparticles (RCC/LND NPS). This nanosystem could target cancer cells, avoid lysosomal degradation and further localize within the mitochondria. The RCC/LND NPS had pH and redox-responsive to control the release of Ce6 and LND. Consequently, the nanosystem had a synergistic effect by effectively alleviating hypoxia, enhancing the production of cytotoxic reactive oxygen species (ROS) and amplifying the efficacy of photodynamic therapy (PDT). Furthermore, the RCC/LND NPS + light weakened anoikis resistance, disrupted extracellular matrix (ECM), activated both the intrinsic apoptotic pathway (mitochondrial pathway) and extrinsic apoptotic pathway (receptor death pathway) of anoikis. In addition, the nanosystem showed significant anti-TNBC efficacy in vivo. These findings collectively demonstrated that RCC/LND NPS + light enhanced the anticancer effects, induced anoikis and inhibited tumor cell migration and invasion through a synergistic effect of chemotherapy and PDT. Overall, this study highlighted the promising potential of the RCC/LND NPS + light for the treatment of TNBC.

T4SEpp: A pipeline integrating protein language models to predict bacterial type IV secreted effectors.

Many pathogenic bacteria use type IV secretion systems (T4SSs) to deliver effectors (T4SEs) into the cytoplasm of eukaryotic cells, causing diseases. The identification of effectors is a crucial step in understanding the mechanisms of bacterial pathogenicity, but this remains a major challenge. In this study, we used the full-length embedding features generated by six pre-trained protein language models to train classifiers predicting T4SEs and compared their performance. We integrated three modules into a model called T4SEpp. The first module searched for full-length homologs of known T4SEs, signal sequences, and effector domains; the second module fine-tuned a machine learning model using data for a signal sequence feature; and the third module used the three best-performing pre-trained protein language models. T4SEpp outperformed other state-of-the-art (SOTA) software tools, achieving ∼0.98 accuracy at a high specificity of ∼0.99, based on the assessment of an independent validation dataset. T4SEpp predicted 13 T4SEs from Helicobacter pylori, including the well-known CagA and 12 other potential ones, among which eleven could potentially interact with human proteins. This suggests that these potential T4SEs may be associated with the pathogenicity of H. pylori. Overall, T4SEpp provides a better solution to assist in the identification of bacterial T4SEs and facilitates studies of bacterial pathogenicity. T4SEpp is freely accessible at https://bis.zju.edu.cn/T4SEpp.

Combined Photosensitive Gene Therapy Effective Against Triple-Negative Breast Cancer in Mice Model.

Introduction: Tumor hypoxia and invasion present significant challenges for the efficacy of photodynamic therapy (PDT) in triple-negative breast cancer (TNBC). This study developed a mitochondrial targeting strategy that combined PDT and gene therapy to promote each other and address the challenges. Methods: The positively charged amphiphilic material triphenylphosphine-tocopherol polyethylene glycol succinate (TPP-TPGS, TPS) and the photosensitizer chloride e6 (Ce6) formed TPS@Ce6 nanoparticles (NPs) by hydrophobic interaction. They electrostatically condensed microRNA-34a (miR-34a) to form stable TPS@Ce6/miRNA NPs. Results: Firstly, Ce6 disrupted the lysosomal membrane, followed by successful delivery of miR-34a by TPS@Ce6/miRNA NPs. Meanwhile, miR-34a reduced ROS depletion and further enhanced the effectiveness of PDT. Consequently, the mutual promotion between PDT and gene therapy led to enhanced anti-tumor effects. Furthermore, the TPS@Ce6/miRNA NPs promoted apoptosis by down-regulating Caspase-3 and inhibited tumor cell migration and invasion by down-regulating N-Cadherin. In addition, in vitro and in vivo experiments demonstrated that the TPS@Ce6/miRNA NPs achieved excellent anti-tumor effects. These findings highlighted the enhanced anticancer effects and reduced migration of tumor cells through the synergistic effects of PDT and gene therapy. Conclusion: Taken together, the targeted co-delivery of Ce6 and miR-34a will facilitate the application of photodynamic and genic nanomedicine in the treatment of aggressive tumors, particularly TNBC.

Glutathione Programmed Mitochondria Targeted Delivery of Lonidamine for Effective Against Triple Negative Breast Cancer.

Introduction: Mitochondria are a significant target of lonidamine (LND). However, its limited solubility and inability to specifically target mitochondria, LND can lead to hepatic toxicity and has shown only modest anticancer activity. The objective of this study is to establish a glutathione programmed mitochondria targeted delivery of LND for the effective treatment of triple negative breast cancer (TNBC). Methods: In this study, LND was encapsulated in poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) wrapped with mitochondria-targeting short-chain triphenylphosphonium-tocopherol polyethylene glycol succinate (TPP-TPGS, TPS) and tumor-targeting long-chain 1, 2-distearoyl-sn-glycero-3-phosphoethanolamine-S-S-polyethylene glycol-R6RGD (DSPE-S-S-PEG2000-R6RGD, DSSR), which were designated as LND-PLGA/TPS/DSSR NPs. The release behavior was evaluated, and cellular uptake, in vitro and in vivo antitumor activity of nanoparticles were investigated. The mechanism, including apoptosis of tumor cells and mitochondrial damage and respiratory rate detection, was also further investigated. Results: LND-PLGA/TPS/DSSR NPs were successfully prepared, and characterization revealed that they are globular particles with smooth surfaces and an average diameter of about 250 nm. Long-chain DSSR in LND-PLGA/TPS/DSSR NPs prevented positively charged LND-PLGA/TPS NPs from being cleared by the reticuloendothelial system. Furthermore, LND release rate from NPs at pH 8.0 was significantly higher than that at pH 7.4 and 5.5, which demonstrated specific LND release in mitochondria and prevented LND leakage in cytoplasm and lysosome. NPs could locate in mitochondria, and the released LND triggered apoptosis of tumor cells by damaging mitochondria and releasing apoptosis-related proteins. In addition, in TNBC mice model, programmed mitochondria targeted NPs improved efficacy and reduced LND toxicity. Conclusion: LND-PLGA/TPS/DSSR NPs may be a useful system and provide an effective approach for the treatment of TNBC.

Features and algorithms: facilitating investigation of secreted effectors in Gram-negative bacteria.

Gram-negative bacteria deliver effector proteins through type III, IV, or VI secretion systems (T3SSs, T4SSs, and T6SSs) into host cells, causing infections and diseases. In general, effector proteins for each of these distinct secretion systems lack homology and are difficult to identify. Sequence analysis has disclosed many common features, helping us to understand the evolution, function, and secretion mechanisms of the effectors. In combination with various algorithms, the known common features have facilitated accurate prediction of new effectors. Ensemblers or integrated pipelines achieve a better prediction of performance, which combines multiple computational models or modules with multidimensional features. Natural language processing (NLP) models also show the merits, which could enable discovery of novel features and, in turn, facilitate more precise effector prediction, extending our knowledge about each secretion mechanism.

Co-delivery of immunochemotherapeutic by classified targeting based on chitosan and cyclodextrin derivatives.

Herein, a cyclodextrin derivative (R6RGD-CMßCD) with tumor target and a carboxymethyl chitosan derivative (M2pep-CMCS) with tumor-associated macrophages 2 (TAM2) target were successfully synthesized, respectively. DOX-loaded nanoparticles (R6RGD-CMßCD@DOX NPs, RCNPDOX) and R848-loaded nanoparticles (M2pep-CMCS@R848 NPs, MCNPR848) were prepared. Furthermore, the RCNPDOX and MCNPR848 exhibited good DOX and R848 absorption. Meanwhile, the synergetic cell toxicity of RCNPDOX and MCNPR848 was found. Additionally, RCNPDOX + MCNPR848 nanoparticles greatly promoted the expression levels of cleaved Caspase3, which indicated that the nanoparticles could induce cell apoptosis. At the same time, the immunohistochemical images exhibited that RCNPDOX + MCNPR848 group could effectively transform the phenotype of tumor-associated macrophages. Importantly, in vivo experiments revealed that RCNPDOX + MCNPR848 NPs exerted excellent anticancer effects in tumor-bearing mice. To summarize, RCNPDOX + MCNPR848 NPs are effective anticancer treatment combining chemotherapy and immunotherapy, M2pep-CMCS and R6RGD-CMßCD are good delivery materials.

T1SEstacker: A Tri-Layer Stacking Model Effectively Predicts Bacterial Type 1 Secreted Proteins Based on C-Terminal Non-repeats-in-Toxin-Motif Sequence Features.

Type 1 secretion systems play important roles in pathogenicity of Gram-negative bacteria. However, the substrate secretion mechanism remains largely unknown. In this research, we observed the sequence features of repeats-in-toxin (RTX) proteins, a major class of type 1 secreted effectors (T1SEs). We found striking non-RTX-motif amino acid composition patterns at the C termini, most typically exemplified by the enriched "[FLI][VAI]" at the most C-terminal two positions. Machine-learning models, including deep-learning ones, were trained using these sequence-based non-RTX-motif features and further combined into a tri-layer stacking model, T1SEstacker, which predicted the RTX proteins accurately, with a fivefold cross-validated sensitivity of ∼0.89 at the specificity of ∼0.94. Besides substrates with RTX motifs, T1SEstacker can also well distinguish non-RTX-motif T1SEs, further suggesting their potential existence of common secretion signals. T1SEstacker was applied to predict T1SEs from the genomes of representative Salmonella strains, and we found that both the number and composition of T1SEs varied among strains. The number of T1SEs is estimated to reach 100 or more in each strain, much larger than what we expected. In summary, we made comprehensive sequence analysis on the type 1 secreted RTX proteins, identified common sequence-based features at the C termini, and developed a stacking model that can predict type 1 secreted proteins accurately.

Assessing the metabolic effects of aromatherapy in human volunteers.

Aromatherapy, a form of complementary and alternative medicine (CAM) that uses essential oils through inhalation, is believed to enhance physical and spiritual conditions. Although clinical studies suggest that the use of essential oils may have therapeutic potential, evidence for the efficacy of aromatherapy in treating medical conditions remains poor, with a particular lack of studies employing rigorous analytical methods that capture its identifiable impact on human biology. Here, we report a comprehensive metabolomics study that reveals metabolic changes in people after exposed to aroma inhalation for 10 continuous days. In this study, the metabolic alterations in urine of 31 females with mild anxiety symptoms exposed to aerial diffusion of aromas were measured by GC-TOF-MS and UPLC-Q-TOF-MS analyses. A significant alteration of metabolic profile in subjects responsive to essential oil was found, which is characterized by the increased levels of arginine, homocysteine, and betaine, as well as decreased levels of alcohols, carbohydrates, and organic acids in urine. Notably, the metabolites from tricarboxylic acid (TCA) cycle and gut microbial metabolism were significantly altered. This study demonstrates that the metabolomics approach can capture the subtle metabolic changes resulting from exposure to essential oils, which may lead to an improved mechanistic understanding of aromatherapy.

The metabolic responses to aerial diffusion of essential oils.

Anxiety disorders are the most prevalent psychiatric disorders and affect a great number of people worldwide. Essential oils, take effects through inhalation or topical application, are believed to enhance physical, emotional, and spiritual well-being. Although clinical studies suggest that the use of essential oils may have therapeutic potential, evidence for the efficacy of essential oils in treating medical conditions remains poor, with a particular lack of studies employing rigorous analytical methods that capture its identifiable impact on human biology. Here, we report a comprehensive gas chromatography time-of-flight mass spectrometry (GC-TOFMS) based metabonomics study that reveals the aromas-induced metabolic changes and the anxiolytic effect of aromas in elevated plus maze (EPM) induced anxiety model rats. The significant alteration of metabolites in the EPM group was attenuated by aromas treatment, concurrent with the behavioral improvement with significantly increased open arms time and open arms entries. Brain tissue and urinary metabonomic analysis identified a number of altered metabolites in response to aromas intervention. These metabolic changes included the increased carbohydrates and lowered levels of neurotransmitters (tryptophan, serine, glycine, aspartate, tyrosine, cysteine, phenylalanine, hypotaurine, histidine, and asparagine), amino acids, and fatty acids in the brain. Elevated aspartate, carbohydrates (sucrose, maltose, fructose, and glucose), nucleosides and organic acids such as lactate and pyruvate were also observed in the urine. The EPM induced metabolic differences observed in urine or brain tissue was significantly reduced after 10 days of aroma inhalation, as noted with the loss of statistical significance on many of the metabolites in the aroma-EPM group. This study demonstrates, for the first time, that the metabonomics approach can capture the subtle metabolic changes resulting from exposure to essential oils and provide the basis for pinpointing affected pathways in anxiety-related behavior, which will lead to an improved mechanistic understanding of anxiolytic effect of essential oils.