Bio-based flame retardant coatings for polyester/cotton fabrics with high physical properties using ammonium vinyl phosphonate-grafted chitosan complexes.

Polyester/cotton (T/C) blended fabrics are widely utilized in textile due to the dimensional stability and high elasticity provided by polyester, combined with the comfort and moisture absorption offered by cotton. However, simultaneously enhancing the flame retardancy and maintaining the physical properties of T/C blended fabrics for clothing and furniture applications remains a big challenge. This study introduces a bio-based flame-retardant coating using polyelectrolyte complexes (PEC) composed of ammonium vinyl phosphonate-grafted chitosan (AMVP-g-CS). The protonation degree of the PEC coating is controlled by adjusting the pH to solidify and stabilize the complex structure, preparing bio-based PEC flame retardant T/C blended fabric. Flame retardant analysis reveals that the coated fabrics achieved a limiting oxygen index of 30.5 % and a char length of 11 mm, indicating significantly improved flame retardancy. The combustible volatile substances are significantly reduced for the coated fabrics, achieving a gas-phase flame retardant effect, and forming an expansive char layer with thermal insulation and oxygen blocking properties. Importantly, physical analysis proves that the PEC deposition improved mechanical properties, satisfactory whiteness index and hand feeling of the fabrics. This work opens up a pragmatic and industrially feasible strategy for the development of CSs in the field of flame retardant coating.

Development of a prognostic model for NSCLC based on differential genes in tumour stem cells.

Non-small cell lung cancer (NSCLC) constitutes a significant portion of lung cancers and cytotoxic drugs (e.g. cisplatin) are currently the first-line treatment. However, NSCLC has developed resistance to this drug, which limits the therapeutic effect and thus affects prognosis. NSCLC sc-RNA-seq data were downloaded from the GEO database and Ku Leuven Laboratory for Functional Epigenetics, and bulk RNA-seq data were obtained from the TCGA database. The "Seurat" package was employed for scRNA-seq data processing, and the uniform manifold approximation and projection (UMAP) were applied for downscaling and cluster identification. Use the FindAllMarkers function to find differential genes (DEGs) for tumor stem cells. Then, we performed univariate regression analyses on the DEGs to identify potential prognostic genes. We created a machine learning framework based on potential prognostic genes, which combines 10 machine learning methods and their 101 combinations to get the optimal prognostic risk model. The model was evaluated in the training set and validation set. A nomogram was developed to provide physicians with a quantitative tool for prognosis prediction. Finally, we evaluated the expression and functionality of SLC2A1. We discovered 22 cell clusters containing 218379 cells by examining single-cell RNA sequencing datasets (GSE148071, KU_lom, GSE131907, GSE136246, GSE127465). Tumour cells were isolated for subpopulation analysis and 162 differential genes from SOX2_cancer were obtained. After univariate Cox analysis, we found 23 genes with prognostic potential prognostic value and utilized them to develop 101­combination machine learning computational framework. We eventually picked the best performing 'StepCox[both] + RSF', which includes 8 genes. The model has a relatively high prediction accuracy in both TCGA and GEO datasets. In in vitro investigations, targeted suppression of the SLC2A1 gene resulted in significant reductions in proliferation, invasion and migration in A549 cells. In addition, a significant reduction in cisplatin resistance was seen in A549/DDP cells. The outcomes demonstrated the precision and credibility of the prognostic model for NSCLC, highlighting its potential significance in the treatment and prognosis of individuals affected by this disease. SLC2A1 may become a promising prognostic marker and a potential therapeutic target, offering valuable insights to inform clinical treatment decisions.

Customized Corneal Cross-Linking with Microneedle-Mediated Riboflavin Delivery for Keratoconus Treatment.

In this study, a novel customized corneal cross-linking (CXL) treatment is explored that utilizes microneedles (MNs) for targeted riboflavin (RF) administration prior to the CXL procedure. Unlike the conventional "one-size-fits-all" approach, this protocol offers an option for more precise and efficacious treatment. To simulate a customized corneal crosslinking technique, four distinct microneedle (MN) molds designs, including circular, semi-circular, annular and butterfly shaped, are crafted for loading an optimized RF-hyaluronic acid solution and for the subsequent fabrication of MN arrays with varying morphologies. These MNs can gently puncture the corneal epithelium while preserving the integrity of the underlying stromal layer. Following the application of these microneedles, RF solution is replenished to enhance the RF content within the stroma through the punctures created by the MNs, resulting in exceptional customized corneal cross-linking effects that are comparable to the conventional epi-off CXL protocol. Additionally, it flattened the corneal curvature within the treated zone and facilitated rapid postoperative recovery of corneal tissue. These findings suggest that the integration of customized microneedle RF delivery with corneal crosslinking technology represents a potential novel treatment modality, holding promise for the tailored treatment of corneal pathologies, and offering a more precise and efficient alternative to traditional methods.

Effect of supplementation with Glycyrrhiza uralensis extract and Lactobacillus acidophilus on growth performance and intestinal health in broiler chickens.

Intestinal microbiota community is an important factor affecting the nutritional and health status of poultry, and its balance is crucial for improving the overall health of poultry. The study aimed to investigate the effect of dietary supplementation with Glycyrrhiza uralensis extract (GUE), Lactobacillus acidophilus (Lac) and their combination (GL) on growth performance and intestinal health in broilers in an 84-day feeding experiment. Supplementary 0.1% GUE and 4.5×107 CFU/g Lac significantly increased average daily gain (ADG), and GL (0.1% GUE and 4.5×107 CFU/g Lac) increased ADG and average daily feed intake (ADFI), and decreased feed conversion rate (FCR) in broilers aged 29 to 84 d and 1 to 84 d. Dietary GUE, Lac and GL increased the superoxide dismutase (SOD) and glutathione peroxidase (GSH-PX) activity and decreased Malondialdehyde (MDA) content in the jejunum mucosa of broilers, and increased secretory IgA (sIgA) content in broilers at 84 d. Moreover, GUE, Lac and GL increased cecal microbial richness and diversity, and modulated microbial community composition. Both GUE and Lac reduced the harmful bacteria Epsilonbacteraeota, Helicobacter, and H. pullorum at 28 d and Proteobacteria, Escherichia, and E. coli at 84 d, while Lac and GL increased beneficial bacteria Lactobacillus and L. gallinarum at 28 d. Compared with individual supplementation, GL markedly increased the SOD activity and the sIgA content, and reduced Helicobacter and Helicobacter pullorum. In conclusion, GUE and Lactobacillus acidophilus as feed additives benefit growth performance and intestinal health, and their combined use shows an even more positive effect in broilers.

Safety and Risk Assessment of No-Prescription Online Semaglutide Purchases.

This qualitative study assesses the quality, amount of active ingredient, and characteristics associated with counterfeiting of semaglutide purchased from illegal online pharmacies without a prescription.

Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study.

BACKGROUND: Manually analyzing public health-related content from social media provides valuable insights into the beliefs, attitudes, and behaviors of individuals, shedding light on trends and patterns that can inform public understanding, policy decisions, targeted interventions, and communication strategies. Unfortunately, the time and effort needed from well-trained human subject matter experts makes extensive manual social media listening unfeasible. Generative large language models (LLMs) can potentially summarize and interpret large amounts of text, but it is unclear to what extent LLMs can glean subtle health-related meanings in large sets of social media posts and reasonably report health-related themes. OBJECTIVE: We aimed to assess the feasibility of using LLMs for topic model selection or inductive thematic analysis of large contents of social media posts by attempting to answer the following question: Can LLMs conduct topic model selection and inductive thematic analysis as effectively as humans did in a prior manual study, or at least reasonably, as judged by subject matter experts? METHODS: We asked the same research question and used the same set of social media content for both the LLM selection of relevant topics and the LLM analysis of themes as was conducted manually in a published study about vaccine rhetoric. We used the results from that study as background for this LLM experiment by comparing the results from the prior manual human analyses with the analyses from 3 LLMs: GPT4-32K, Claude-instant-100K, and Claude-2-100K. We also assessed if multiple LLMs had equivalent ability and assessed the consistency of repeated analysis from each LLM. RESULTS: The LLMs generally gave high rankings to the topics chosen previously by humans as most relevant. We reject a null hypothesis (P<.001, overall comparison) and conclude that these LLMs are more likely to include the human-rated top 5 content areas in their top rankings than would occur by chance. Regarding theme identification, LLMs identified several themes similar to those identified by humans, with very low hallucination rates. Variability occurred between LLMs and between test runs of an individual LLM. Despite not consistently matching the human-generated themes, subject matter experts found themes generated by the LLMs were still reasonable and relevant. CONCLUSIONS: LLMs can effectively and efficiently process large social media-based health-related data sets. LLMs can extract themes from such data that human subject matter experts deem reasonable. However, we were unable to show that the LLMs we tested can replicate the depth of analysis from human subject matter experts by consistently extracting the same themes from the same data. There is vast potential, once better validated, for automated LLM-based real-time social listening for common and rare health conditions, informing public health understanding of the public's interests and concerns and determining the public's ideas to address them.

A gene regulatory network-aware graph learning method for cell identity annotation in single-cell RNA-seq data.

Cell identity annotation for single-cell transcriptome data is a crucial process for constructing cell atlases, unraveling pathogenesis, and inspiring therapeutic approaches. Currently, the efficacy of existing methodologies is contingent upon specific data sets. Nevertheless, such data are often sourced from various batches, sequencing technologies, tissues, and even species. Notably, the gene regulatory relationship remains unaffected by the aforementioned factors, highlighting the extensive gene interactions within organisms. Therefore, we propose scHGR, an automated annotation tool designed to leverage gene regulatory relationships in constructing gene-mediated cell communication graphs for single-cell transcriptome data. This strategy helps reduce noise from diverse data sources while establishing distant cellular connections, yielding valuable biological insights. Experiments involving 22 scenarios demonstrate that scHGR precisely and consistently annotates cell identities, benchmarked against state-of-the-art methods. Crucially, scHGR uncovers novel subtypes within peripheral blood mononuclear cells, specifically from CD4+ T cells and cytotoxic T cells. Furthermore, by characterizing a cell atlas comprising 56 cell types for COVID-19 patients, scHGR identifies vital factors like IL1 and calcium ions, offering insights for targeted therapeutic interventions.

Phillyrin and its metabolites exert antipyretic effects by targeting the NAD+ binding domain of GAPDH, MDH2 and IDH2.

BACKGROUND: Fever is one of the main pathophysiological reactions that occurs during the acute phase of various diseases. Excessive body temperature can lead to various adverse consequences such as brain tissue damage and abnormal immune responses. Phillyrin (Phr) is the main active ingredient in Forsythia suspensa (Thunb.) Vahl (Lian Qiao) and has antipyretic effects; however, its antipyretic mechanism of action remains unclear. PURPOSE: This study aimed to explore the antipyretic mechanisms of Phr and provide a new treatment plan for fever. METHODS: The antipyretic effects of Phr were evaluated using a mouse model of pneumonia fever. The main metabolites of Phr involved in its antipyretic function were identified using a mitochondrial temperature-sensitive probe. Further synthesis of the main metabolite, phillygenin (Phg), an alkynylated probe, was performed, and chemical proteomics was used to capture and analyze its direct target for antipyretic effects. The mechanism of action of Phg and its antipyretic targets was explored using metabolomics and various molecular biology methods. RESULTS: Phr showed significant antipyretic and anti-inflammatory effects in a mouse model of lipopolysaccharide-induced fever. Phg reversibly targeted the nicotinamide adenine dinucleotide (NAD+) binding domain of glyceraldehyde-3-phosphate dehydrogenase (GAPDH), malate dehydrogenase 2 (MDH2), and isocitrate dehydrogenase 2 (IDH2) to inhibit their enzymatic activity. In-depth analysis of cellular metabolomics and mitochondrial stress testing indicated that inhibition of GAPDH, MDH2, and IDH2 enzyme activity by Phg led to a decrease in cellular energy supply and heat production regulated by glycolysis, tricarboxylic acid cycle, and oxidative phosphorylation signaling pathways. Phg specifically targeted macrophages and inhibited LPS-induced macrophage activation by downregulating GAPDH enzyme activity, thereby exerting anti-inflammatory effects. In vivo experiments also confirmed that the antipyretic effect of Phr in LPS-induced fever model mice was related to its main metabolites, Phg and Phg-sulfonate (Phg-S), which directly targeted the NAD+ binding domain of GAPDH, IDH2, and MDH2, inhibiting the activity of these enzymes, thereby reducing energy supply and regulating febrile-related inflammatory factors. CONCLUSION: This study reported for the first time that the antipyretic effect of Phr is produced by targeting GAPDH, IDH2, and MDH2 to regulate energy supply and febrile-related inflammatory factors through its main metabolites Phg and Phg-S. This study not only provides potential drugs for fever treatment but also provides new ideas for improving clinical fever treatment plans.

The pineapple reference genome: Telomere-to-telomere assembly, manually curated annotation, and comparative analysis.

Pineapple is the third most crucial tropical fruit worldwide and available in five varieties. Genomes of different pineapple varieties have been released to date; however, none of them are complete, with all exhibiting substantial gaps and representing only two of the five pineapple varieties. This significantly hinders the advancement of pineapple breeding efforts. In this study, we sequenced the genomes of three varieties: a wild pineapple variety, a fiber pineapple variety, and a globally cultivated edible pineapple variety. We constructed the first gap-free reference genome (Ref) for pineapple. By consolidating multiple sources of evidence and manually revising each gene structure annotation, we identified 26,656 protein-coding genes. The BUSCO evaluation indicated a completeness of 99.2%, demonstrating the high quality of the gene structure annotations in this genome. Utilizing these resources, we identified 7,209 structural variations across the three varieties. Approximately 30.8% of pineapple genes were located within ±5 kb of structural variations, including 30 genes associated with anthocyanin synthesis. Further analysis and functional experiments demonstrated that the high expression of AcMYB528 aligns with the accumulation of anthocyanins in the leaves, both of which may be affected by a 1.9-kb insertion fragment. In addition, we developed the Ananas Genome Database, which offers data browsing, retrieval, analysis, and download functions. The construction of this database addresses the lack of pineapple genome resource databases. In summary, we acquired a seamless pineapple reference genome with high-quality gene structure annotations, providing a solid foundation for pineapple genomics and a valuable reference for pineapple breeding.

Structural Quality Factor of Flo-TENG under Stochastic Wave Excitation.

Triboelectric nanogenerators (TENGs) have recently emerged as a promising technology for efficient water wave energy harvesting. However, there is a paucity of clear guidance regarding the optimal designs of TENGs and their shells to achieve efficient absorption and conversion of water wave energy in real random waves. Herein, from the perspective of wave-body interaction and energy transfer, this paper proposes a structural quality factor (Qunit) for the quantitative evaluation of both the motion of floating triboelectric nanogenerator (Flo-TENG) shells and their capability to absorb and convert water wave energy efficiently. The factor is further subdivided into the amplitude structural quality factor (Qacc), which characterizes shell motion amplitude, and the frequency structural quality factor (Qf), which describes shell motion frequency. This paper systematically investigates the impact of various shell parameters such as bow shapes, curvatures, inclinations, and immersion ratios on Qacc and Qf. The findings indicate that variations in shell shape result in distinct Qunit values along different axial directions of wave propagation. These variations directly influence energy absorption efficiency in these directions. These results provide fundamental guidance for the design of high-performance Flo-TENG shells and the selection of internal energy harvesting directions to enable more efficient energy conversion.

PRSS50-mediated inhibition of MKP3/ERK signaling is crucial for meiotic progression and sperm quality.

Serine protease 50 (PRSS50/TSP50) is highly expressed in spermatocytes. Our study investigated its role in testicular development and spermatogenesis. Initially, PRSS50 knockdown was observed to impair DNA synthesis in spermatocytes. To further explore this, we generated PRSS50 knockout ( Prss50 -/- ) mice ( Mus musculus), which exhibited abnormal spermatid nuclear compression and reduced male fertility. Furthermore, dysplastic seminiferous tubules and decreased sex hormones were observed in 4-week-old Prss50 -/- mice, accompanied by meiotic progression defects and increased apoptosis of spermatogenic cells. Mechanistic analysis indicated that PRSS50 deletion resulted in increased phosphorylation of extracellular signal-regulated protein kinases 1 and 2 (ERK1/2) and elevated levels of MAP kinase phosphatase 3 (MKP3), a specific ERK antagonist, potentially accounting for testicular dysplasia in adolescent Prss50 -/- mice. Taken together, these findings suggest that PRSS50 plays an important role in testicular development and spermatogenesis, with the MKP3/ERK signaling pathway playing a significant role in this process.

Ruthenium Single-Atom Modulated Protonated Iridium Oxide for Acidic Water Oxidation in Proton Exchange Membrane Electrolysers.

Proton exchange membrane water electrolysers promise to usher in a new era of clean energy, but they remain a formidable obstacle in designing active and durable electrocatalysts for the acidic oxygen evolution reaction (OER). In this study, a protonated iridium oxide embedded with single-atom dispersed ruthenium atoms (H3.8Ir1- xRuxO4) that demonstrates exceptional activity and stability in acidic water oxidation is introduced. The single Ru dopants favorably induce localized oxygen vacancies in the Ir─O lattice, synergistically strengthening the adsorption of OOH* intermediates and enhancing the intrinsic OER activity. In addition, the preferential oxidation of Ru and the electronegativity of the oxygen vacancies significantly stabilize the Ir─O active sites, improving the OER stability. Consequently, the H3.8Ir1─ xRuxO4 catalyst shows an overpotential of 255 mV at 10 mA cm-2 and displays exceptional catalytic endurance in acidic electrolytes, surpassing 1100 h, representing a remarkable one-order-of-magnitude increase in stability compared to that of pristine H3.8IrO4. A proton exchange membrane electrolyser utilizing the H3.8Ir1- xRuxO4 catalyst as an anode exhibits stable performance for more than 1280 h under a high current density of 2 A cm-2.

The OsSRO1c-OsDREB2B complex undergoes protein phase transition to enhance cold tolerance in rice.

Cold stress is one of the major abiotic stress factors affecting rice growth and development, leading to significant yield loss in the context of global climate change. Exploring natural variants that confer cold resistance and the underlying molecular mechanism responsible for this is the major strategy to breed cold tolerant rice varieties. Here, we show that the natural variations of a SIMILAR to RCD ONE (SRO) gene, OsSRO1c, confer cold tolerance in rice at both seedling and booting stages. OsSRO1c possesses intrinsic liquid-liquid phase separation ability in vivo and in vitro and recruits an AP2/ERF transcription factor and positive cold stress regulator, OsDREB2B, into its biomolecular condensates in the nucleus, resulting in elevated transcriptional activity of OsDREB2B. The OsSRO1c-OsDREB2B complex directly responds to low temperature through dynamic phase transitions and regulates key cold response genes, including COLD1. Furthermore, introgression of an elite haplotype of OsSRO1c into a cold susceptible indica rice significantly increases its cold resistance. Collectively, our work reveals a novel cold tolerance regulatory module in rice and provides promising genetic targets for molecular breeding of cold-tolerant rice varieties.

Deciphering the Genetic Landscape: Insights Into the Genomic Signatures of Changle Goose.

The Changle goose (CLG), a Chinese indigenous breed, is celebrated for its adaptability, rapid growth, and premium meat quality. Despite its agricultural value, the exploration of its genomic attributes has been scant. Our study entailed whole-genome resequencing of 303 geese across CLG and five other Chinese breeds, revealing distinct genetic diversity metrics. We discovered significant migration events from Xingguo gray goose to CLG and minor gene flow between them. We identified genomic regions through selective sweep analysis, correlating with CLG's unique traits. An elevated inbreeding coefficient in CLG, alongside reduced heterozygosity and rare single nucleotide polymorphisms (RSNPs), suggests a narrowed genetic diversity. Genomic regions related to reproduction, meat quality, and growth were identified, with the GATA3 gene showing strong selection signals for meat quality. A non-synonymous mutation in the Sloc2a1 gene, which is associated with reproductive traits in the CLG, exhibited significant differences in allelic frequency. The roles of CD82, CDH8, and PRKAB1 in growth and development, alongside FABP4, FAF1, ESR1, and AKAP12 in reproduction, were highlighted. Additionally, Cdkal1 and Mfsd14a may influence meat quality. This comprehensive genetic analysis underpins the unique genetic makeup of CLG, providing a basis for its conservation and informed breeding strategies.

The immunoregulatory role of gut microbiota in the incidence, progression, and therapy of breast cancer.

Breast cancer (BrCa) is the most prevalent malignant tumor in women and one of the leading causes of female mortality. Its occurrence and progression are influenced by various factors, including genetics, environment, lifestyle, and hormones. In recent years, the gut microbiota has been identified as a significant factor affecting BrCa. The gut microbiota refers to the collective population of various microorganisms in the human gastrointestinal tract. Gut microbiota is closely associated with human health and disease development, participating in crucial physiological functions such as digestion, metabolism, immune response, and neural regulation. It has been found to influence the occurrence and treatment of BrCa through a variety of mechanisms. This article aims to review the immunomodulatory role of the gut microbiota in the development and treatment of BrCa.

Large-scale bidirectional Mendelian randomization study identifies new gut microbiome significantly associated with immune thrombocytopenic purpura.

Introduction: A variety of studies have shown a link between the gut microbiota and autoimmune diseases, but the causal relationship with Henoch-Schönlein purpura (HSP) and immune thrombocytopenic purpura (ITP) is unknown. Methods: This study investigated the bidirectional causality between gut microbiota and HSP and ITP using Mendelian randomization (MR). Large-scale genetic data of gut microbiota at phylum to species level from the MiBioGen consortium and the Dutch Microbiome Project were utilized. Genome-wide association studies (GWAS) summary statistics for HSP and ITP came from FinnGen R10. Various MR methods were applied to infer causal relationships, including inverse variance weighted (IVW), maximum likelihood (ML), cML-MA, MR-Egger, weighted median, weighted model, and MR-PRESSO. Multiple sensitivity analyses and Bonferroni correction were conducted to enhance robustness and reliability. Results: Based on the IVW estimates, 23 bacterial taxa were identified to have suggestive associations with HSP and ITP. Remarkably, after Bonferroni correction, family Alcaligenaceae (OR = 2.86, 95% CI = 1.52-5.37; IVW, p = 1.10 × 10-3, ML, p = 1.40 × 10-3) was significantly associated with ITP as a risk factor, while family Bacteroidales S24 7group (OR = 0.46, 95% CI = 0.29-0.74; IVW, p = 1.40 × 10-3) was significantly associated with ITP as a protective factor. No significant associations between HSP and ITP and gut microbiota were found in reverse analyses. Conclusion: Our study provides evidence of causal effects of gut microbiota on HSP and ITP, highlighting the importance of further research to clarify the underlying mechanisms and develop targeted therapeutic interventions for these autoimmune diseases.

Combining hybrid cell membrane modified magnetic nanoparticles and inverted microfluidic chip for in situ CTCs capture and inactivation.

Circulating tumor cells (CTCs) serve as crucial indicators for tumor occurrence, progression, and prognosis monitoring. However, achieving high sensitivity and high purity capture of CTCs remains challenging. Additionally, in situ capture and synchronous clearance hold promise as methods to impede tumor metastasis, but further exploration is needed. In this study, biomimetic cell membrane-coated magnetic nanoparticles (NPs) were designed to address the issue of nonspecific adsorption of capture probes by the immune system during blood circulation. Membranes from human breast cancer cells (tumor cell membranes, TMs) and leukocytes (white blood cell membranes, WMs) were extracted and fused to form a hybrid membrane (HM), which was further modified onto the surface of porous magnetic NPs loaded with indocyanine green (ICG). The incorporation of TM enhanced the material's target specificity, thus increasing capture efficiency, while WM coating reduced interference from homologous white blood cells (WBCs), further enhancing capture purity. Additionally, in conjunction with our novel inverted microfluidic chip, this work introduces the first use of polymer photonic crystals as the capture interface for CTCs. Besides providing an advantageous surface structure for CTC attachment, the 808 nm photonic bandgap effectively amplifies the 808 nm excitation light at the capture surface position. Therefore, upon capturing CTCs, the ICG molecules in the probes facilitate enhanced photothermal (PTT) and photodynamic (PDT) synergistic effects, directly inactivating the captured CTCs. This method achieves capture efficiency and purity exceeding 95% and permits in situ inactivation post-capture, providing an important approach for future research on impeding tumor metastasis in vivo.

CRISPR/Cas12a-coupled multiplexed strand displacement amplification for miRNA155 one-tube detection: via a dual-cavity PCR tube.

A CRISPR/Cas12a-coupled multiplexed strand displacement amplification (CMSDA) for the detection of miR155 has been developed. Non-specific amplification was avoided by designing a single-stranded DNA template with a hairpin structure. The detection target miR155 was used as a primer to initiate a multiple-strand displacement reaction to produce abundant ssDNA. ssDNA was recognized by the Cas12a/CrRNA binary complex, activating the trans-cleaving activity of Cas12a. The multiple-strand displacement reaction is more efficiently detected compared with a single-strand displacement reaction. The detection range is from 250 pM to 1 nM, and the limit of the detection is 6.5 pM. The proposed method showed a good applicability in complex serum environments, indicating that the method has a broad prospect for disease detection and clinical application. In addition, we designed a dual-cavity PCR tube, which realized one-tube detection of miRNA155 and avoided open-cap contamination.

Pulmonary delivery of magnolol-loaded nanostructured lipid carriers for COPD treatment.

Chronic obstructive pulmonary disease (COPD) is a prevalent lung condition characterized by airflow obstruction, disability, and high mortality rates. Magnolol (MA), known for its anti-inflammatory and antioxidant properties, holds the potential for alleviating COPD symptoms. However, MA faces challenges like poor aqueous solubility and low bioavailability. Herein MA-loaded nanostructured lipid carriers (MA-NLC) were prepared using emulsification and solvent evaporation. These carriers exhibited a particle size of (19.67 ± 0.36) nm, a polydispersity index of (0.21 ± 0.01), and a zeta potential of (-5.18 ± 0.69) mV. The fine particle fraction of MA-NLC was (68.90 ± 0.07)%, indicating minimal lung irritation and enhanced safety. Pulmonary delivery of MA-NLC via nebulizer actively targeted the diseased lung tissues, facilitated slow release, and overcame the challenges of low oral absorption and bioavailability associated with MA. This formulation prolonged the residence time of MA and optimized its therapeutic effect in pulmonary tissues. Upon pulmonary administration, MA-NLC effectively regulated inflammatory and oxidative stress markers in COPD models, demonstrating its potential as a promising therapeutic platform for COPD management.