circRUNX2.2, highly expressed in Marek's disease tumor tissues, functions in cis to regulate parental gene RUNX2 expression.

Marek's disease (MD), an immunosuppression disease induced by Marek's disease virus (MDV), is one of the significant diseases affecting the health and productive performance of poultry. The roles of circular RNAs (circRNAs) in MD development were poorly understood. In this study, we found a circRNA derived from exon 6 of RUNX family transcription factor 2 (RUNX2) gene, named circRUNX2.2, was highly expressed in chicken tumorous spleens (TS) induced by MDV. Through fluorescence in situ hybridization and nuclear-cytoplasmic separation assay, we determined circRUNX2.2 was mainly located in the nucleus. Knockout experiments confirmed that the flanking complementary sequences (RCMs) mediated its circularization. Gain of function assay and dual luciferase reporter gene assay revealed that circRUNX2.2 could promote the expression of RUNX2 via binding with its promoter region. RNA antisense purification assay and mass spectrometry assay showed circRUNX2.2 could recruit proteins such as CHD9 protein. Knocking down CHD9 expression decreased the expression of RUNX2 gene, which confirmed the positive regulation that circRUNX2.2 on RUNX2 expression was probably facilitated via recruiting CHD9 protein. Functional experiments showed that circRUNX2.2 promoted the proliferation of the MD lymphoma-derived chicken cell line, MDCC-MSB1, which confirmed the potential oncogenic role of circRNX2.2 in tumor development. In conclusion, we found that the RUNX2-derived circRUNX2.2 can positively regulate the transcription of the parental gene RUNX2 in a cis-acting manner. The high expression of circRUNX2.2 in MD tumor tissues indicated that it might mediate MD lymphoma progression.

Research on the castor oil pressing extraction mechanism based on multi-physics coupling simulation.

Castor oil has been widely used in various fields due to its properties, leading to large attention for its extraction mechanism. To research the castor oil extraction mechanism during pressing, a self-developed uniaxial compression device combined with an in situ observation is established. The effects of pressure, loading speed, and creep time are investigated, and a finite element model coupling with multi-physics is established for castor oil pressing extraction, verified by the seed cake experimental compression strain matching with numerical simulation under the same condition. Simulation results indicated that the pressing oil extraction process can be divided into two stages, Darcy's speed shows the first sharp decreasing stage and the second gradual increasing stage during porosity and pressure interaction. In the first stage, porosity is dominant on Darcy's speed. With porosity decreasing, the pressure effect on Darcy's speed exceeds porosity in the second stage. With seed thickness increasing, Darcy's speed first increases and then decreases. With loading speed increasing, Darcy's speed increases. Darcy's speed decreases constantly with creep time increasing. This study can provide basic theoretical and practical guidance for oil extraction.

Quantifying Plant Signaling Pathways by Integrating Luminescence-Based Biosensors and Mathematical Modeling.

Plants have evolved intricate signaling pathways, which operate as networks governed by feedback to deal with stressors. Nevertheless, the sophisticated molecular mechanisms underlying these routes still need to be comprehended, and experimental validation poses significant challenges and expenses. Consequently, computational hypothesis evaluation gains prominence in understanding plant signaling dynamics. Biosensors are genetically modified to emit light when exposed to a particular hormone, such as abscisic acid (ABA), enabling quantification. We developed computational models to simulate the relationship between ABA concentrations and bioluminescent sensors utilizing the Hill equation and ordinary differential equations (ODEs), aiding better hypothesis development regarding plant signaling. Based on simulation results, the luminescence intensity was recorded for a concentration of 47.646 RLUs for 1.5 µmol, given the specified parameters and model assumptions. This method enhances our understanding of plant signaling pathways at the cellular level, offering significant benefits to the scientific community in a cost-effective manner. The alignment of these computational predictions with experimental results emphasizes the robustness of our approach, providing a cost-effective means to validate mathematical models empirically. The research intended to correlate the bioluminescence of biosensors with plant signaling and its mathematical models for quantified detection of specific plant hormone ABA.

Current multi-scale biomaterials for tissue regeneration following spinal cord injury.

Spinal cord injury (SCI) may cause loss of motor and sensory function, autonomic dysfunction, and thus disrupt the quality of life of patients, leading to severe disability and significant psychological, social, and economic burden. At present, existing therapy for SCI have limited ability to promote neural function recovery, and there is an urgent need to develop innovative regenerative approaches to repair SCI. Biomaterials have become a promising strategy to promote the regeneration and repair of damaged nerve tissue after SCI. Biomaterials can provide support for nerve tissue by filling cavities, and improve local inflammatory responses and reshape extracellular matrix structures through unique biochemical properties to create the optimal microenvironment at the SCI site, thereby promoting neurogenesis and reconnecting damaged spinal cord tissue. Considering the importance of biomaterials in repairing SCI, this article reviews the latest progress of multi-scale biomaterials in SCI treatment and tissue regeneration, and evaluates the relevant technologies for manufacturing biomaterials.

Atorvastatin exerts a preventive effect against steroid-induced necrosis of the femoral head by modulating Wnt5a release.

Steroid-induced osteonecrosis of the femoral head (SONFH) is a prevalent form of osteonecrosis in young individuals. More efficacious clinical strategies must be used to prevent and treat this condition. One of the mechanisms through which SONFH operates is the disruption of normal differentiation in bone marrow adipocytes and osteoblasts due to prolonged and extensive use of glucocorticoids (GCs). In vitro, it was observed that atorvastatin (ATO) effectively suppressed the impact of dexamethasone (DEX) on bone marrow mesenchymal stem cells (BMSCs), specifically by augmenting their lipogenic differentiation while impeding their osteogenic differentiation. To investigate the underlying mechanisms further, we conducted transcriptome sequencing of BMSCs subjected to different treatments, leading to the identification of Wnt5a as a crucial gene regulated by ATO. The analyses showed that ATO exhibited the ability to enhance the expression of Wnt5a and modulate the MAPK pathway while regulating the Wnt canonical signaling pathway via the WNT5A/LRP5 pathway. Our experimental findings provide further evidence that the combined treatment of ATO and DEX effectively mitigates the effects of DEX, resulting in the upregulation of osteogenic genes (Runx2, Alpl, Tnfrsf11b, Ctnnb1, Col1a) and the downregulation of adipogenic genes (Pparg, Cebpb, Lpl), meanwhile leading to the upregulation of Wnt5a expression. So, this study offers valuable insights into the potential mechanism by which ATO can be utilized in the prevention of SONFH, thereby holding significant implications for the prevention and treatment of SONFH in clinical settings.

Tracing groundwater nitrate sources in an intensive agricultural region integrated of a self-organizing map and end-member mixing model tool.

The traceability of groundwater nitrate pollution is crucial for controlling and managing polluted groundwater. This study integrates hydrochemistry, nitrate isotope (δ15N-NO3- and δ18O-NO3-), and self-organizing map (SOM) and end-member mixing (EMMTE) models to identify the sources and quantify the contributions of nitrate pollution to groundwater in an intensive agricultural region in the Sha River Basin in southwestern Henan Province. The results indicate that the NO3--N concentration in 74% (n = 39) of the groundwater samples exceeded the WHO standard of 10 mg/L. According to the results of EMMTE modeling, soil nitrogen (68.4%) was the main source of nitrate in Cluster-1, followed by manure and sewage (16.5%), chemical fertilizer (11.9%) and atmospheric deposition (3.3%). In Cluster-2, soil nitrogen (60.1%) was the main source of nitrate, with a significant increase in the contribution of manure and sewage (35.5%). The considerable contributions of soil nitrogen may be attributed to the high nitrogen fertilizer usage that accumulated in the soil in this traditional agricultural area. Moreover, it is apparent that most Cluster-2 sampling sites with high contributions of manure and sewage are located around residential land. Therefore, the arbitrary discharge and leaching of domestic sewage may be responsible for these results. Therefore, this study provides useful assistance for the continuous management and pollution control of groundwater in the Sha River Basin.

A novel fish individual recognition method for precision farming based on knowledge distillation strategy and the range of the receptive field.

With the continuous development of green and high-quality aquaculture technology, the process of industrialized aquaculture has been promoted. Automation, intelligence, and precision have become the future development trend of the aquaculture industry. Fish individual recognition can further distinguish fish individuals based on the determination of fish categories, providing basic support for fish disease analysis, bait feeding, and precision aquaculture. However, the high similarity of fish individuals and the complexity of the underwater environment presents great challenges to fish individual recognition. To address these problems, we propose a novel fish individual recognition method for precision farming that rethinks the knowledge distillation strategy and the chunking method in the vision transformer. The method uses the traditional convolutional neural network model as the teacher model, introducing the teacher token to guide the student model to learn the fish texture features. We propose stride patch embedding to expand the range of the receptive field, thus enhancing the local continuity of the image, and self-attention-pruning to discard unimportant tokens and reduce the model computation. The experimental results on the DlouFish dataset show that the proposed method in this paper improves accuracy by 3.25% compared to ECA Resnet152, with an accuracy of 93.19%, and also outperforms other vision transformer models.

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Nitrate pollution in groundwater has become a global concern. One of the most important issues in controlling the nitrate pollution of groundwater is to identify the pollution source quickly and accurately. In this review, we firstly summarized the isotopic background values of potential sources of nitrate pollution in groundwater in 17 provinces (cities, autonomous regions) and 29 study areas in China, which could provide the fundamental database for subsequent research. Secondly, we reviewed the research progress of nitrate isotopes combined with multiple tracers for tracing nitrate in groundwater, and discussed their applicable conditions, advantages, and disadvantages. We found that halides and microorganisms combined with nitrate isotopes could accurately trace the pollution sources of domestic sewage, excrement and agricultural activities. The combination of Δ17O and nitrate isotopes could effectively distinguish the source of atmospheric deposition of nitrate in groundwater. The combination of groundwater age and nitrate isotopes could further determine the time scale of nitrate pollution. In addition, we summarized the application cases and compared the characteristics of mass balance mixing model, IsoSource model, Bayesian isotope mixing model, and EMMTE model for quantitative identification of nitrate pollution in groundwater. For the complexity and concealment of groundwater pollution sources, the coupling of nitrate isotopes with other chemical and biological tracing methods, as well as the application of nitrate isotope quantitative models, are effective tools for reliably identifying groundwater nitrate sources and transformation processes.

Sepsis caused by Phytobacter diazotrophicus complicated with galactosemia type 1 in China: a case report.

BACKGROUND: Phytobacter diazotrophicus (P. diazotrophicus) is an opportunistic pathogen that causes nosocomial outbreaks and sepsis. However, there are no reports of P. diazotrophicus isolated from human blood in China. CASE PRESENTATION: A 27-day-old female infant was admitted to our hospital with fever and high bilirubin levels. The clinical features included jaundice, abnormal coagulation, cholestasis, fever, convulsions, weak muscle tension, sucking weakness, ascites, abnormal tyrosine metabolism, cerebral oedema, abnormal liver function, clavicle fracture, and haemolytic anaemia. The strain isolated from the patient's blood was identified as P. diazotrophicus by whole-genome sequencing (WGS). Galactosemia type 1 (GALAC1) was diagnosed using whole-exome sequencing (WES). Based on drug sensitivity results, 10 days of anti-infective treatment with meropenem combined with lactose-free milk powder improved symptoms. CONCLUSION: P. diazotrophicus was successfully identified in a patient with neonatal sepsis combined with galactosemia. Galactosemia may be an important factor in neonatal sepsis. This case further expands our understanding of the clinical characteristics of GALAC1.

Evaluation of agricultural non-point source pollution using an in-situ and automated photochemical flow analysis system.

Off-line leachate collection from agricultural landscapes cannot guarantee precise evaluation of agricultural non-point source (ANPS) due to geospatial variations, time, and transportation from the field to the laboratory. Implementing an in-situ nitrogen and phosphorous monitoring system with a robust photochemical flow analysis is imperative for precision agriculture, enabling real-time intervention to minimize non-point source pollution and overcome the limitations posed by conventional analysis in laboratory. A reliable, robust and in-situ approach was proposed to monitor nitrogen and phosphorous for determining ANPS pollution. In this study, a home-made porous ceramic probe and the frequency domain reflectometer (FDR) based water content sensors were strategically placed at different soil depths to facilitate the collection of leachates. These solutions were subsequently analyzed by in-situ photochemical flow analysis monitoring system built across the field to estimate the concentrations of phosphorus and nitrogen. After applying both natural and artificial irrigation to the agricultural landscape, at least 10 mL of soil leachates was consistently collected using the porous ceramic probe within 20 min, regardless of the depth of the soil layers when the volumetric soil water contents are greater than 19%. The experimental results showed that under different weather conditions and irrigation conditions, the soil water content of 50 cm and 90 cm below the soil surface was 19.58% and 26.08%, respectively. The average concentrations of NH4+-N, NO3--N, PO43- are 0.584 mg/L, 15.7 mg/L, 0.844 mg/L, and 0.562 mg/L, 16.828 mg/L and 0.878 mg/L at depths of 50 cm and 90 cm below the soil surface, respectively. Moreover, the comparison with conventional laboratory spectroscopic analysis confirmed R2 values of 0.9951, 0.9943, 0.9947 average concentration ranges of NH4+-N, NO3--N, and PO43-, showcasing the accuracy and reliability of robust photochemical flow analysis in-situ monitoring system. The suggested monitoring system can be helpful in the assessment of soil nutrition for precision agriculture.

Functionalized Single Crystal Perovskite Materials for SERS and Their Potential Detection Applications.

Recent advances in detection and diagnostic tools have improved understanding and identification of plant physiological and biochemical processes. Effective and safe Surface Enhanced Raman Spectroscopy (SERS) can find objects quickly and accurately. Raman enhancement amplifies the signal by 1014-1015 to accurately quantify plant metabolites at the molecular level. This paper shows how to use functionalized perovskite substrates for SERS. These perovskite substrates have lots of surface area, intense Raman scattering, and high sensitivity and specificity. These properties eliminate sample matrix component interference. This study identified research gaps on perovskite substrates' effectiveness, precision, and efficiency in biological metabolite detection compared to conventional substrates. This article details the synthesis and use of functionalized perovskites for plant metabolites measurement. It analyzes their pros and cons in this context. The manuscript analyzes perovskite-based SERS substrates, including single-crystalline perovskites with enhanced optoelectronic properties. This manuscript aims to identify this study gap by comprehensively reviewing the literature and using it to investigate plant metabolite detection in future studies.

GUGA-based MRCI approach with core-valence separation approximation (CVS) for the calculation of the core-excited states of molecules.

We develop and demonstrate how to use the Graphical Unitary Group Approach (GUGA)-based MRCISD with Core-Valence Separation (CVS) approximation to compute the core-excited states. First, perform a normal Self-Consistent-Field (SCF) or valence MCSCF calculation to optimize the molecular orbitals. Second, rotate the optimized target core orbitals and append to the active space, form an extended CVS active space, and perform a CVS-MCSCF calculation for core-excited states. Finally, construct the CVS-MRCISD expansion space and perform a CVS-MRCISD calculation to optimize the CI coefficients based on the variational method. The CVS approximation with GUGA-based methods can be implemented by flexible truncation of the Distinct Row Table. Eliminating the valence-excited configurations from the CVS-MRCISD expansion space can prevent variational collapse in the Davidson iteration diagonalization. The accuracy of the CVS-MRCISD scheme was investigated for excitation energies and compared with that of the CVS-MCSCF and CVS-CASPT2 methods using the same active space. The results show that CVS-MRCISD is capable of reproducing well-matched vertical core excitation energies that are consistent with experiments by combining large basis sets and a rational reference space. The calculation results also highlight the fact that the dynamic correlation between electrons makes an undeniable contribution in core-excited states.

Correlation between the cardiometabolic index and arteriosclerosis in patients with type 2 diabetes mellitus.

BACKGROUND: The cardiometabolic index (CMI) is a new metric derived from the triglyceride-glucose index and body mass index and is considered a potential marker for cardiovascular risk assessment. This study aimed to examine the correlation between the CMI and the presence and severity of arteriosclerosis in patients with type 2 diabetes mellitus (T2DM). METHODS: This study involved 2243 patients with T2DM. The CMI was derived by dividing the triglyceride level (mmol/L) by the high-density lipoprotein level (mmol/L) and then multiplying the quotient by the waist-to-height ratio. Multivariate logistic regression was used to analyze the correlations between the CMI and BMI blood biomarkers, blood pressure, and brachial-ankle pulse wave velocity (baPWV). RESULTS: Patients were categorized into three groups based on their CMI: Group C1 (CMI < 0.775; n = 750), Group C2 (CMI: 0.775-1.355; n = 743), and Group C3 (CMI > 1.355; n = 750). Increased BMI, fasting glucose, insulin (at 120 min), total cholesterol (TC), and baPWV values were observed in Groups C2 and C3, with statistically significant trends (all trends P < 0.05). The CMI was positively correlated with systolic blood pressure (r = 0.74, P < 0.001). Multivariate analysis revealed that an increased CMI contributed to a greater risk for arteriosclerosis (OR = 1.87, 95%CI: 1.66-2.10, P < 0.001). Compared to the C1 group, the C2 group and C3 group had a greater risk of developing arteriosclerosis, with ORs of 4.55 (95%CI: 3.57-5.81, P<0.001) and 5.56 (95%CI: 4.32-7.17, P<0.001), respectively. The association was notably stronger in patients with a BMI below 21.62 kg/m² than in those with a BMI of 21.62 kg/m² or higher (OR = 4.53 vs. OR = 1.59). CONCLUSIONS: These findings suggest that the CMI is a relevant and independent marker of arteriosclerosis in patients with T2DM and may be useful in the risk stratification and management of these patients.

Temperature-dependent effects of microplastics on sediment bacteriome and metabolome.

The increasing prevalence of microplastics in the environment has become a concern for various ecosystems, including wetland ecosystems. Here, we investigated the effects of three popular microplastic types: polyethylene, polylactic acid, and tire particles at 5 °C and 25 °C on the sediment microbiome and metabolome at the 3% (w/w) level. Results indicated that temperature greatly influenced catalase and neutral phosphatase activities, whereas the type of microplastic had a more significant impact on urease and dehydrogenase activities. The addition of microplastic, especially tire particles, increased microbial diversity and significantly altered the microbial community structure and metabolic profile, leading to the formation of different clusters of microbial communities depending on the temperature. Nonetheless, the effect of temperature on the metabolite composition was less significant. Functional prediction showed that the abundance of functional genes related to metabolism and biogeochemical cycling increased with increasing temperature, especially the tire particles treatment group affected the nitrogen cycling by inhibiting ureolysis and nitrogen fixation. These observations emphasize the need to consider microplastic type and ambient temperature to fully understand the ecological impact of microplastics on microbial ecosystems.

Salinization of groundwater in shale gas extraction area in the Sichuan Basin, China: Implications for water protection in shale regions with well-developed faults.

The expanding growth of shale gas development has sparked global concern over water-related environmental issues. However, research on groundwater contamination in shale gas areas in China remains limited, impeding environmentally friendly industry practices. To address this gap, we investigated the Wufeng-Longmaxi shale region in the Sichuan Basin, encompassing both operational and prospective shale gas extraction sites, to assess the effects of shale gas operations on shallow groundwater quality. We found there was no significant correlation between groundwater quality and the minimum distance from the shale gas well pads, and some groundwater samples located far from shale gas well pads, rather than those close to pads, were salinized. These findings suggest minimal impacts from shale gas drilling and hydraulic fracturing. The salinized groundwater samples are characterized by high salinity levels and ion concentrations, and are located near fault zones. The primary source of shallow groundwater salinization was derived from the Triassic formation brines confirmed through the assessment of the sensitivity and conservative mixing models. Faults in the study area were identified as pathways for the upward migration of Triassic brines, evidenced by the proximity of salinized samples to fault zones. However, further investigation is required to ascertain whether shale gas extraction activities have induced the migration of formation brines. The occurrence and reactivation of faults, induced by microseismic activities, may pose an increased risk of groundwater contamination in tectonically complex fault zones during shale gas extraction. Therefore, it is imperative to enhance extraction strategies and technologies, particularly in shale regions with well-developed faults, such as optimizing well placement regulation, controlling hydraulic fracturing scale, and strengthening environmental monitoring. By shedding light on potential environmental ramifications of shale gas extraction, especially in fault-rich regions, our study informs water protection strategies and the sustainable advancement of the shale gas industry.

Novel Operation Mechanism and Multifunctional Applications of Bubble Microrobots.

Microrobots have emerged as powerful tools for manipulating particles, cells, and assembling biological tissue structures at the microscale. However, achieving precise and flexible operation of arbitrary-shaped microstructures in 3D space remains a challenge. In this study, three novel operation methods based on bubble microrobots are proposed to enable delicate and multifunctional manipulation of various microstructures. These methods include 3D turnover, fixed-point rotation, and 3D ejection. By harnessing the combined principles of the effect of the heat flow field and surface tension of an optothermally generated bubble, the bubble microrobot can perform tasks such as flipping an SIA humanoid structure, rotating a bird-like structure, and launching a hollow rocket-like structure. The proposed multi-mode operation of bubble microrobots enables diverse attitude adjustments of microstructures with different sizes and shapes in both 2D and 3D spaces. As a demonstration, a biological microenvironment of brain glioblastoma is constructed by the bubble microrobot. The simplicity, versatility, and flexibility of this proposed method hold great promise for applications in micromanipulation, assembly, and tissue engineering.

Effects of polyethylene, polylactic acid, and tire particles on the sediment microbiome and metabolome at high and low temperatures.

Global warming has led to a high incidence of extreme heat events, and the frequent occurrence of extreme heat events has had extensive and far-reaching impacts on wetland ecosystems. The widespread distribution of plastics in the environment, including polyethylene (PE), polylactic acid (PLA), and tire particles (TPs), has caused various environmental problems. Here, high-throughput sequencing techniques and metabolomics were used for the first time to investigate the effects of three popular microplastic types: PE, PLA, and TP, on the sediment microbiome and the metabolome at both temperatures. The microplastics were incorporated into the sediment at a concentration of 3% by weight of the dry sediment (wt/wt), to reflect environmentally relevant conditions. Sediment enzymatic activity and physicochemical properties were co-regulated by both temperatures and microplastics producing significant differences compared to controls. PE and PLA particles inhibited bacterial diversity at low temperatures and promoted bacterial diversity at high temperatures, and TP particles promoted both at both temperatures. For bacterial richness, only PLA showed inhibition at low temperature; all other treatments showed promotion. PE, PLA, and TP microplastics changed the community structure of sediment bacteria, forming two clusters at low and high temperatures. Furthermore, PE, PLA, and TP changed the sediment metabolic profiles, producing differential metabolites such as lipids and molecules, organic heterocyclic compounds, and organic acids and their derivatives, especially TP had the most significant effect. These findings contribute to a more comprehensive understanding of the potential impact of microplastic contamination.IMPORTANCEIn this study, we added 3% (wt/wt) microplastic particles, including polyethylene, polylactic acid, and tire particles, to natural sediments under simulated laboratory conditions. Subsequently, we simulated the sediment microbial and ecosystem responses under different temperature conditions by incubating them for 60 days at 15°C and 35°C, respectively. After synthesizing these results, our study strongly suggests that the presence of microplastics in sediment ecosystems and exposure under different temperature conditions may have profound effects on soil microbial communities, enzyme activities, and metabolite profiles. This is important for understanding the potential hazards of microplastic contamination on terrestrial ecosystems and for developing relevant environmental management strategies.

Dual-Responsive Nanorobot-Based Marsupial Robotic System for Intracranial Cross-Scale Targeting Drug Delivery.

Nanorobots capable of active movement are an exciting technology for targeted therapeutic intervention. However, the extensive motion range and hindrance of the blood-brain barrier impeded their clinical translation in glioblastoma therapy. Here, a marsupial robotic system constructed by integrating chemical/magnetic hybrid nanorobots (child robots) with a miniature magnetic continuum robot (mother robot) for intracranial cross-scale targeting drug delivery is reported. For primary targeting on macroscale, the continuum robot enters the cranial cavity through a minimally invasive channel (e.g., Ommaya device) in the skull and transports the nanorobots to pathogenic regions. Upon circumventing the blood-brain barrier, the released nanorobots perform secondary targeting on microscale to further enhance the spatial resolution of drug delivery. In vitro experiments against primary glioblastoma cells derived from different patients are conducted for personalized treatment guidance. The operation feasibility within organisms is shown in ex vivo swine brain experiments. The biosafety of the treatment system is suggested in in vivo experiments. Owing to the hierarchical targeting method, the targeting rate, targeting accuracy, and treatment efficacy have improved greatly. The marsupial robotic system offers a novel intracranial local therapeutic strategy and constitutes a key milestone in the development of glioblastoma treatment platforms.

Catheter-Assisted Bioinspired Adhesive Magnetic Soft Millirobot for Drug Delivery.

Soft millirobots have evolved into various therapeutic applications in the medical field, including for vascular dredging, cell transportation, and drug delivery, owing to adaptability to their surroundings. However, most soft millirobots cannot quickly enter, retrieve, and maintain operations in their original locations after removing the external actuation field. This study introduces a soft magnetic millirobot for targeted medicine delivery that can be transported into the body through a catheter and anchored to the tissues. The millirobot has a bilayer adhesive body with a mussel-inspired hydrogel layer and an octopus-inspired magnetic structural layer. It completes entry and retrieval with the assistance of a medical catheter based on the difference between the adhesion of the hydrogel layer in air and water. The millirobot can operate in multiple modes of motion under external magnetic fields and underwater tissue adhesion after self-unfolding with the structural layer. The adaptability and recyclability of the millirobots are demonstrated using a stomach model. Combined with ultrasound (US) imaging, operational feasibility within organisms is shown in isolated small intestines. In addition, a highly efficient targeted drug delivery is confirmed using a fluorescence imaging system. Therefore, the proposed soft magnetic millirobots have significant potential for medical applications.

Triptolide inhibits the proliferation and induces ferroptosis of osteosarcoma U2OS cells via the miR-34b-5p/Notch1 axis / 中国肿瘤生物治疗杂志

@#[摘 要] 目的：探究雷公藤甲素（TPL）通过miR-34b-5p调控Notch1表达对骨肉瘤U2OS细胞铁死亡影响的机制。方法：常规培养U2OS细胞，将其分为对照组、TPL（10 μmol/L）组、TPL（10 μmol/L）+Fer-1（铁死亡抑制剂，20 μmol/L） 组、miR-NC组、miR-34b-5p组、miR-34b-5p+Fer-1（20 μmol/L）组、TPL（10 μmol/L）+anti-miR-34b-5p组、anti-miR-34b-5p+Fer-1（20 μmol/L）组。qPCR法、CCK-8法、铁离子检测试剂、DHE-荧光探针和WB法分别检测各组U2OS细胞中miR-34b-5p的表达、增殖能力、Fe2+水平、ROS水平以及铁死亡相关蛋白（GPX4、SLC7A11及Notch1蛋白）的表达，双萤光素酶报告基因实验验证miR-34b-5p与Notch1的靶向结合关系。结果： TPL可促进U2OS细胞中miR-34b-5p表达，Fer-1和anti-miR-34b-5p则抑制miR-34b-5p的表达（均P<0.05）。TPL明显抑制U2OS细胞的增殖、GPX4、SLC7A11、Notch1蛋白的表达、增加细胞中Fe2+和ROS的含量，Fer-1可逆转TPL对U2OS细胞的作用（均P<0.05）。过表达miR-34b-5p与TPL对U2OS细胞的作用相似（均P<0.05）。miR-34b-5p可靶向结合Notch1（均P<0.05）。miR-34b-5p抑制剂可明显抑制TPL对U2OS细胞的影响，Fer-1可增强miR-34b-5p抑制剂的作用（均P<0.05）。结论：TPL可抑制U2OS细胞的增殖能力并促进其铁死亡，其作用机制可能与miR-34a-5p靶向调节Notch1表达有关。