Construction of charge-reversible coordination-crosslinked spherical nucleic acids to deliver dual anti-cancer genes and ferroptosis payloads.

Spherical nucleic acids (SNAs) are nanostructures with the DNA arranged radially on the surface, thus allowing specific binding with cancer cells expressing high levels of scavenger receptor-A to enhance cellular uptake. However, conventional carriers for SNAs are cytotoxic, not degradable and difficult to deliver multiple payloads. In this study, we developed charge-reversible coordination-crosslinked SNAs to deliver dual anti-cancer genes and ferroptosis payload for anti-cancer purposes. To this end, we modified poly(lactic acid) (PLA) with functionalized side chains to allow its binding with antisense oligonucleotides (ASOs) and siRNA, annealed two single-stranded RNAs to obtain double-stranded RNA, and introduced a polyethylene glycol (PEG) shell to enhance the circulation time. Additionally, the ferroptosis payload imidazole was coordinated with iron ions as a core-crosslinked group to enhance the stability of SNAs and efficiency to kill cancer cells. We demonstrated that this novel nanocomplex efficiently internalized and killed CT-26 cells in vitro. In vivo data confirmed that the dual gene delivery system successfully targeted CT-26 tumors in tumor-bearing BALB/c mice, and exhibited strong tumor suppression ability, without inducing adverse toxic effects. Taken together, our dual gene therapy system offered an enhanced anti-tumor solution by simultaneously delivering dual anti-cancer genes and ferroptosis payload in tumor microenvironment.

Novel extracellular lipase gene Lip1728 influences nutrient-dependent performance bacterial quorum sensing of Burkholderia pyrrocinia WZ10-3.

Quorum sensing (QS) is a cellular communication mechanism in which bacteria secrete and recognize signaling molecules to regulate group behavior. Lipases provide energy for bacterial cell growth but it is unknown whether they influence nutrient-dependent QS by hydrolyzing substrate. A high-yield lipase-producing strain, Burkholderia pyrrocinia WZ10-3, was previously identified in our laboratory, but the composition of its crude enzymes was not elucidated. Here, we identified a key extracellular lipase, Lip1728, in WZ10-3, which accounts for 99 % of the extracellular lipase activity. Lip1728 prefers to hydrolyze triglycerides at sn-1,3 positions, with pNP-C16 being its optimal substrate. Lip1728 exhibited activity at pH 5.0-10.0 and regardless of the presence of metal ions. It had strong resistance to sodium dodecyl sulfate and short-chain alcohols and was activated by phenylmethanesulfonylfluoride (PMSF). Lip1728 knockout significantly affected lipid metabolism and biofilm formation in the presence of olive oil. Finally, oleic acid, a hydrolysate of Lip1728, influenced the production of the signal molecule N-acyl homoserine lactone (AHL) and biofilm formation by downregulating the AHL synthetase gene pyrI. In conclusion, Lip1728, as a key extracellular lipase in B. pyrrocinia WZ10-3, exhibits superior properties that make it suitable for biodiesel production and plays a crucial role in QS.

Initialization-Free and Magnetic Field-Free Spin-Orbit p-Bits with Backhopping-like Magnetization Switching for Probabilistic Applications.

Probabilistic bits (p-bits) with thermal- and spin torque-induced nondeterministic magnetization switching are promising candidates for performing probabilistic computing. Previously reported spin torque p-bits include volatile low-energy barrier nanomagnets (LBNMs) with spontaneously fluctuating magnetizations and initialization-necessary nonvolatile magnets. However, initialization-free nonvolatile spin torque p-bits are still lacking. Here, we demonstrate moderately thermal stable spin-orbit torque (SOT) p-bits with non-consecutively deposited Pt//Pt/Co/Pt stacks. Backhopping-like (BH) magnetization switching with a wide range current-tunable probability of final up and down magnetization states from 0% to 100% was achieved, regardless of the initial magnetization state, which was attributed to the interplay of SOT and thermal contributions. Integer factorization using such BH-SOT p-bits in zero magnetic field was demonstrated at times that are significantly shorter than those of existing nonvolatile STT or volatile LBNMs p-bits. Our realization of initialization-free and magnetic field-free moderately thermally stable BH-SOT p-bits opens up a new perspective for probabilistic spintronic applications.

Cold-hot Janus electrochemical aptamer-based sensor for calibration-free determination of biomolecules.

Real-time, high-frequency measurements of pharmaceuticals, metabolites, exogenous antigens, and other biomolecules in biological samples can provide critical information for health management and clinical diagnosis. Electrochemical aptamer-based (EAB) sensor is a promising analytical technique capable of achieving these goals. However, the issues of insufficient sensitivity, frequent calibration and lack of adapted portable electrochemical device limit its practical application in immediate detection. In response we have fabricated an on-chip-integrated, cold-hot Janus EAB (J-EAB) sensor based on the thermoelectric coolers (TECs). Attributed to the Peltier effect, the enhanced/suppressed current response can be generated simultaneously on cold/hot sides of the J-EAB sensor. The ratio of the current responses on the cold and hot sides was used as the detection signal, enabling rapid on-site, calibration-free determination of small molecules (procaine) as well as macromolecules (SARS-CoV-2 spike protein) in single step, with detection limits of 1 µM and 10 nM, respectively. We have further demonstrated that the J-EAB sensor is effective in improving the ease and usability of the actual detection process, and is expected to provide a universal, low-cost, fast and easy potential analytical tool for other clinically important biomarkers, drugs or pharmaceutical small molecules.

TopMarker: Computational screening biomarkers of hepatocellular carcinoma from transcriptome and interactome based on differential network topological parameters.

Identifying diagnostic biomarkers for cancer is crucial in the field of personalized medicine. The available transcriptome and interactome provide unprecedented opportunities and challenges for biomarker screening. From a systematic perspective, network-based medicine methods provide alternative approaches to organizing the available high-throughput omics data for deciphering molecular interactions and their associations with phenotypic states. In this work, we propose a bioinformatics strategy named TopMarker for discovering diagnostic biomarkers by comparing the network topology differences in control and disease samples. Specifically, we build up gene-gene interaction networks in the two states of control and disease respectively. The network rewiring status across the two networks results in differential network topologies reflecting dynamics and changes in normal samples when compared with those in disease. Thus, we identify the potential biomarker genes with differential network topological parameters between the control and disease gene networks. For a proof-of-concept study, we introduce the computational pipeline of biomarker discovery in hepatocellular carcinoma (HCC). We prove the effectiveness of the proposed TopMarker method using these candidate biomarkers in classifying HCC samples and validate its signature capability across numerous independent datasets. We also compare the discriminant power of biomarker genes identified by TopMarker with those identified by other baseline methods. The higher classification performances and functional implications indicate the advantages of our proposed method for discovering biomarkers from differential network topology.

Rapid nanomolar detection of cocaine in biofluids by electrochemical aptamer-based sensor with low-temperature effect for drugged driving screening.

Cocaine is one of the most abused illicit drugs, and its abuse damages the central nervous system and can even lead directly to death. Therefore, the development of simple, rapid and highly sensitive detection methods is crucial for the prevention and control of drug abuse, traffic accidents and crime. In this work, an electrochemical aptamer-based (EAB) sensor based on the low-temperature enhancement effect was developed for the direct determination of cocaine in bio-samples. The signal gain of the sensor at 10 °C was greatly improved compared to room temperature, owing to the improved affinity between the aptamer and the target. Additionally, the electroactive area of the gold electrode used to fabricate the EAB sensor was increased 20 times by a simple electrochemical roughening method. The porous electrode possesses more efficient electron transfer and better antifouling properties after roughening. These improvements enabled the sensor to achieve rapid detection of cocaine in complex bio-samples. The low detection limits (LOD) of cocaine in undiluted urine, 50% serum and 50% saliva were 70 nM, 30 nM and 10 nM, respectively, which are below the concentration threshold in drugged driving screening. The aptasensor was simple to construct and reusable, which offers potential for drugged driving screening in the real world.

The Dimensionality of Hydrogen Bond Networks Induces Diverse Physical Properties of Peptide Crystals.

Short peptides are attractive building blocks for the fabrication of self-assembled materials with significant biological, chemical, and physical properties. The microscopic and macroscopic properties of assemblies are usually closely related to the dimensionality of formed hydrogen bond networks. Here, two completely different supramolecular architectures connected by distinct hydrogen bond networks were obtained by simply adding a hydroxyl group to switch from cyclo-tryptophan-alanine (cyclo-WA) to cyclo-tryptophan-serine (cyclo-WS). While hydroxyl-bearing cyclo-WS molecules provided an additional hydrogen bond donor that links to adjacent molecules, forming a rigid three-dimensional network, cyclo-WA arranged into a water-mediated zipper-like structure with a softer two-dimensional layer template. This subtle alteration resulted in a 14-fold enhancement of Young's modulus values in cyclo-WS compared to cyclo-WA. Both cyclo-dipeptides exhibit biocompatibility, high fluorescence, and piezoelectricity. The demonstrated role of dimensionality of hydrogen bond networks opens new avenues for rational design of materials with precise morphologies and customizable properties for bioelectronic applications.

First report of Pseudopithomyces palmicola causing leaf spot on tobacco in China.

In July 2023, a new leaf spot disease emerged on tobacco leaves in Meitan County, Guizhou Province, China (27°20'18" - 28°12'30"N, 107°15'36" - 107°41'08"E, average altitude 972 meters). Initially, the symptoms showed raised yellow-brown spots; subsequently, the lesions expanded and became broken and perforated, leading to a significant loss of economic value, the prevalence rate exceeded 30%. For isolation, two tissue fragments (0.2 × 0.2 cm) of symptomatic leaves were sterilized in 75% ethanol for 30 s, 3% NaClO for 2 min, and were washed 3 times in sterilized distilled water, and were subsequently inoculated on potato dextrose agar (PDA), and incubated at 28°C for 9 days in the dark. The two strains CW16 and CW28 were isolated using the single hyphae method (Nouri et al. 2023). Both strains formed pale to yellow white colonies on PDA. Conidia had three constricted transverse septa and 1 to 2 longitudinal septa in the central cells, with thick and hyaline conidiophores and mostly globose, pale brown conidia with slightly constricted septa, their average size were measured as 13.4-22.4×8.358-13.347 µm (n = 50). Genomic DNA was extracted from the isolated strains CW16 and CW28. The internal transcribed spacer regions 1 and 2 as well as 5.8S nuclear ribosomal RNA (ITS), large subunit nrRNA (LSU), and partial DNA-directed RNA polymerase II second largest subunit (RPB2) genes were amplified using primers (Cui et al. 2023). The sequences had been deposited in GenBank under accession numbers ITS: PP024201, PP024205; LSU: PP024207, PP024209; RPB2: PP060480, PP060481. The sequences analysis revealed a high similarity of 99.74 to 100% between strains CW16 and CW28 with P. palmicola isolate KM42 (ITS OQ875842, LSU OQ875844, RPB2 OQ883943) in GenBank. Using BLAST for homology matching, two isolates (CW16, CW28) and with the sequences of the ten type isolates from GenBank, phylogenetic analysis was conducted using the Maximum Likelihood method in MEGA (11.0) software based on ITS, LSU and RPB2 sequences, which showed that strains CW16, CW28 clustered in the same score as the Pseudopithomyces palmicola, confirming the morphological and molecular characteristics identification. The pathogenicity tests were conducted on healthy tobacco plants with 4-5 leaves (Fig. S1B), the isolated strains, CW16 and CW28, were used to inoculate the healthy tobacco leaves, while blank PDA was used as a control. All plants were maintained in a greenhouse at 28°C with a relative humidity of 90%. After 9 days, necrotic spots were observed on all tobacco leaves inoculated with CW16 and CW28 fungal plugs, while the blank PDA-inoculated tobacco leaves showed no symptoms. Based on morphological and molecular characteristics, the same pathogen P. palmicola was identified from the inoculated leaves, fulfilling Koch's postulates. This study represents the first reported of tobacco leaf spot caused by P. palmicola in China and provides a theoretical basis for future prevention and control measures.

A "Dual-Key-and-Lock" MRI Contrast Agent with T1-T2 Switchable Function for Accurate Diagnosis of Tumors.

Extremely small iron oxide nanoparticle (ESIONP)-based stimuli-responsive switchable MRI contrast agents (CAs) show great promise for accurate detection of tumors due to their outstanding advantages of high specificity and low background signal. However, currently developed ESIONP-based switchable CAs often suffer single-biomarker-induced responses, which lack absolute specificity to pathological tissues, potentially diminishing diagnostic accuracy. In this study, weak acidity and hypoxia, two of the most remarkable characteristics of tumors, are introduced as dual biomarker stimuli to construct an ESIONP-based switchable MRI CA (DKL-CA), with its signal switch controlled by a "dual-key-and-lock" strategy. Only when DKL-CA is exposed to a coexisting weakly acidic and hypoxic environment can monodispersed ESIONPs form nanoclusters, thereby realizing a switch from the T1 to T2 contrast. Moreover, DKL-CA exhibits favorable biosafety and the capacity for precise tumor diagnosis in tumor-bearing mice. Overall, DKL-CA paves the way for designing highly accurate ESIONP-based MRI CAs for tumor diagnosis.

Comparative assessment of the capability of machine learning-based radiomic models for predicting omental metastasis in locally advanced gastric cancer.

The study aims to investigate the predictive capability of machine learning algorithms for omental metastasis in locally advanced gastric cancer (LAGC) and to compare the performance metrics of various machine learning predictive models. A retrospective collection of 478 pathologically confirmed LAGC patients was undertaken, encompassing both clinical features and arterial phase computed tomography images. Radiomic features were extracted using 3D Slicer software. Clinical and radiomic features were further filtered through lasso regression. Selected clinical and radiomic features were used to construct omental metastasis predictive models using support vector machine (SVM), decision tree (DT), random forest (RF), K-nearest neighbors (KNN), and logistic regression (LR). The models' performance metrics included accuracy, area under the curve (AUC) of the receiver operating characteristic curve, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). In the training cohort, the RF predictive model surpassed LR, SVM, DT, and KNN in terms of accuracy, AUC, sensitivity, specificity, PPV, and NPV. Compared to the other four predictive models, the RF model significantly improved PPV. In the test cohort, all five machine learning predictive models exhibited lower PPVs. The DT model demonstrated the most significant variation in performance metrics relative to the other models, with a sensitivity of 0.231 and specificity of 0.990. The LR-based predictive model had the lowest PPV at 0.210, compared to the other four models. In the external validation cohort, the performance metrics of the predictive models were generally consistent with those in the test cohort. The LR-based model for predicting omental metastasis exhibited a lower PPV. Among the machine learning algorithms, the RF predictive model demonstrated higher accuracy and improved PPV relative to LR, SVM, KNN, and DT models.

HIV broadly neutralizing antibody escapability drives the therapeutic efficacy of vectored immunotherapy.

Broadly neutralizing antibodies (bNAbs) have shown great promise for prevention and treatment of HIV infection. Breadth of bNAb neutralization, measured in vitro across panels of diverse viral isolates, is often used as a predictor of clinical potential. However, recent prevention studies demonstrate that the clinical efficacy of a broad and potent bNAb (VRC01) is undermined by neutralization resistance of circulating strains. Using HIV-infected humanized mice, we find that therapeutic efficacy of bNAbs delivered as Vectored ImmunoTherapy (VIT) is a function of both the fitness cost and resistance benefit of mutations that emerge during viral escape, which we term 'escapability'. Applying this mechanistic framework, we find that the sequence of the envelope V5-loop alters the resistance benefits of mutants that arise during escape, thereby impacting the therapeutic efficacy of VIT-mediated viral suppression. We also find that an emtricitabine-based antiretroviral drug regimen dramatically enhances the efficacy of VIT, by reducing the fitness of mutants along the escape path. Our findings demonstrate that bNAb escapability is a key determinant to consider in the rational design of antibody regimens with maximal efficacy and illustrates a tractable means of minimizing viral escape from existing bNAbs.

The TAK1/JNK axis participates in adaptive immunity by promoting lymphocyte activation in Nile tilapia.

The transforming growth factor beta-activated kinase 1 (TAK1)/c-Jun N-terminal kinase (JNK) axis is an essential MAPK upstream mediator and regulates immune signaling pathways. However, whether the TAK1/JNK axis harnesses the strength in regulation of signal transduction in early vertebrate adaptive immunity is unclear. In this study, by modeling on Nile tilapia (Oreochromis niloticus), we investigated the potential regulatory function of TAK1/JNK axis on lymphocyte-mediated adaptive immune response. Both OnTAK1 and OnJNK exhibited highly conserved sequences and structures relative to their counterparts in other vertebrates. Their mRNA was widely expressed in the immune-associated tissues, while phosphorylation levels in splenic lymphocytes were significantly enhanced on the 4th day post-infection by Edwardsiella piscicida. In addition, OnTAK1 and OnJNK were significantly up-regulated in transcriptional level after activation of lymphocytes in vitro by phorbol 12-myristate 13-acetate plus ionomycin (P + I) or PHA, accompanied by a predominant increase in phosphorylation level. More importantly, inhibition of OnTAK1 activity by specific inhibitor NG25 led to a significant decrease in the phosphorylation level of OnJNK. Furthermore, blocking the activity of OnJNK with specific inhibitor SP600125 resulted in a marked reduction in the expression of T-cell activation markers including IFN-γ, CD122, IL-2, and CD44 during PHA-induced T-cell activation. In summary, these findings indicated that the conserved TAK1/JNK axis in Nile tilapia was involved in adaptive immune responses by regulating the activation of lymphocytes. This study enriched the current knowledge of adaptive immunity in teleost and provided a new perspective for understanding the regulatory mechanism of fish immunity.

Genome-Wide Identification and Characterization of CCT Gene Family from Microalgae to Legumes.

The CCT (CO, COL and TOC1) gene family has been elucidated to be involved in the functional differentiation of the products in various plant species, but their specific mechanisms are poorly understood. In the present investigation, we conducted a genome-wide identification and phylogenetic analysis of CCT genes from microalgae to legumes. A total of 700 non-redundant members of the CCT gene family from 30 species were identified through a homology search. Phylogenetic clustering with Arabidopsis and domain conservation analysis categorized the CCT genes into three families. Multiple sequence alignment showed that the CCT domain contains important amino acid residues, and each CCT protein contains 24 conserved motifs, as demonstrated by the motif analysis. Whole-genome/segment duplication, as well as tandem duplication, are considered to be the driving forces in the evolutionary trajectory of plant species. This comprehensive investigation into the proliferation of the CCT gene family unveils the evolutionary dynamics whereby WGD/segment duplication is the predominant mechanism contributing to the expansion of the CCT genes. Meanwhile, the examination of the gene expression patterns revealed that the expression patterns of CCT genes vary in different tissues and at different developmental stages of plants, with high expression in leaves, which is consistent with the molecular regulation of flowering in photosynthesis by CCT. Based on the protein-protein interaction analysis of CCT genes in model plants, we propose that the CCT gene family synergistically regulates plant development and flowering with light-signaling factors (PHYs and PIFs) and MYB family transcription factors. Understanding the CCT gene family's molecular evolution enables targeted gene manipulation for enhanced plant traits, including optimized flowering and stress resistance.

ProPept-MT: A Multi-Task Learning Model for Peptide Feature Prediction.

In the realm of quantitative proteomics, data-independent acquisition (DIA) has emerged as a promising approach, offering enhanced reproducibility and quantitative accuracy compared to traditional data-dependent acquisition (DDA) methods. However, the analysis of DIA data is currently hindered by its reliance on project-specific spectral libraries derived from DDA analyses, which not only limits proteome coverage but also proves to be a time-intensive process. To overcome these challenges, we propose ProPept-MT, a novel deep learning-based multi-task prediction model designed to accurately forecast key features such as retention time (RT), ion intensity, and ion mobility (IM). Leveraging advanced techniques such as multi-head attention and BiLSTM for feature extraction, coupled with Nash-MTL for gradient coordination, ProPept-MT demonstrates superior prediction performance. Integrating ion mobility alongside RT, mass-to-charge ratio (m/z), and ion intensity forms 4D proteomics. Then, we outline a comprehensive workflow tailored for 4D DIA proteomics research, integrating the use of 4D in silico libraries predicted by ProPept-MT. Evaluation on a benchmark dataset showcases ProPept-MT's exceptional predictive capabilities, with impressive results including a 99.9% Pearson correlation coefficient (PCC) for RT prediction, a median dot product (DP) of 96.0% for fragment ion intensity prediction, and a 99.3% PCC for IM prediction on the test set. Notably, ProPept-MT manifests efficacy in predicting both unmodified and phosphorylated peptides, underscoring its potential as a valuable tool for constructing high-quality 4D DIA in silico libraries.

Toward Practical Applications of Engineered Living Materials with Advanced Fabrication Techniques.

Engineered Living Materials (ELMs) are materials composed of or incorporating living cells as essential functional units. These materials can be created using bottom-up approaches, where engineered cells spontaneously form well-defined aggregates. Alternatively, top-down methods employ advanced materials science techniques to integrate cells with various kinds of materials, creating hybrids where cells and materials are intricately combined. ELMs blend synthetic biology with materials science, allowing for dynamic responses to environmental stimuli such as stress, pH, humidity, temperature, and light. These materials exhibit unique "living" properties, including self-healing, self-replication, and environmental adaptability, making them highly suitable for a wide range of applications in medicine, environmental conservation, and manufacturing. Their inherent biocompatibility and ability to undergo genetic modifications allow for customized functionalities and prolonged sustainability. This review highlights the transformative impact of ELMs over recent decades, particularly in healthcare and environmental protection. We discuss current preparation methods, including the use of endogenous and exogenous scaffolds, living assembly, 3D bioprinting, and electrospinning. Emphasis is placed on ongoing research and technological advancements necessary to enhance the safety, functionality, and practical applicability of ELMs in real-world contexts.

Ferroelectric polarization and magnetic structure at domain walls in a multiferroic film.

Domain walls affect significantly ferroelectric and magnetic properties of magnetoelectric multiferroics. The stereotype is that the ferroelectric polarization will reduce at the domain walls due to the incomplete shielding of depolarization field or the effects of gradient energy. By combining transmission electron microscopy and first-principles calculations, we demonstrate that the ferroelectric polarization of tail-to-tail 180° domain walls in ε-Fe2O3 is regulated by the bound charge density. A huge enhancement (43%) of ferroelectric polarization is observed in the type I domain wall with a low bound charge density, while the ferroelectric polarization is reduced to almost zero at the type II domain wall with a high bound charge density. The magnetic coupling across the type I and type II ferroelectric domain walls are antiferromagnetic and ferromagnetic, respectively. Revealing mechanisms for enhancing ferroelectric polarization and magnetic behaviors at ferroelectric domain walls may promote the fundamental research and potential applications of magnetoelectric multiferroics.

Global insights from local actions: a case study on enhancing flood disaster management efficiency in China's Greater Bay Area.

This study examines the flood disaster management network within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2015 to 2021, identifying government department involvement and influence shifts. Key findings indicate a decrease in the centrality of the Public Security Office and Department of Transportation, suggesting a strategic shift toward more specialized, technology-driven disaster management. Conversely, the Science Bureau's increased engagement, from 8.43% to 12.84%, highlights a policy shift toward scientific research and technological innovation in managing flood risks. The analysis reveals underutilized communication between the Central Committee, the Poverty Alleviation Office, and the Publicity Department, highlighting opportunities for improved integration in disaster management and public communication strategies. To address these issues, the study suggests strengthening inter-departmental collaboration to leverage technological advancements in disaster management. It also recommends integrating flood disaster management with poverty alleviation initiatives to support affected populations comprehensively. Increasing the involvement of the Publicity Department is crucial for improving timely and transparent communication of flood-related data to the public. The conclusions advocate for an adaptive, strategically planned network approach to flood disaster management in the GBA, aiming to bolster responsiveness and preparedness for future flood events.

Structurally and mechanically tuned macroporous hydrogels for scalable mesenchymal stem cell-extracellular matrix spheroid production.

Mesenchymal stem cells (MSCs) are essential in regenerative medicine. However, conventional expansion and harvesting methods often fail to maintain the essential extracellular matrix (ECM) components, which are crucial for their functionality and efficacy in therapeutic applications. Here, we introduce a bone marrow-inspired macroporous hydrogel designed for the large-scale production of MSC-ECM spheroids. Through a soft-templating approach leveraging liquid-liquid phase separation, we engineer macroporous hydrogels with customizable features, including pore size, stiffness, bioactive ligand distribution, and enzyme-responsive degradability. These tailored environments are conducive to optimal MSC proliferation and ease of harvesting. We find that soft hydrogels enhance mechanotransduction in MSCs, establishing a standard for hydrogel-based 3D cell culture. Within these hydrogels, MSCs exist as both cohesive spheroids, preserving their innate vitality, and as migrating entities that actively secrete functional ECM proteins. Additionally, we also introduce a gentle, enzymatic harvesting method that breaks down the hydrogels, allowing MSCs and secreted ECM to naturally form MSC-ECM spheroids. These spheroids display heightened stemness and differentiation capacity, mirroring the benefits of a native ECM milieu. Our research underscores the significance of sophisticated materials design in nurturing distinct MSC subpopulations, facilitating the generation of MSC-ECM spheroids with enhanced therapeutic potential.

Influences of TiO2 nanoparticle and fipronil co-exposure on metabolite profiles in mouse intestines.

Food contaminates, such as insecticide, may influence the toxicity of nanoparticles (NPs) to intestine. The present study investigated the combined toxicity of TiO2 NPs and fipronil to male mouse intestine. Juvenile mice (8 weeks) were orally exposed to 5.74 mg/kg TiO2 NPs, 2.5 mg/kg fipronil, or both, once a day, for 5 days. We found that both TiO2 NPs and fipronil induced some pathological changes in intestines, accompanying with defective autophagy, but these effects were not obviously enhanced after TiO2 NP and fipronil co-exposure. Fipronil promoted Ti accumulation but induced minimal impact on other trace elements in TiO2 NP-exposed intestines. Metabolomics data revealed that the exposure altered metabolite profiles in mouse intestines, and two KEGG pathways, namely, ascorbate and aldarate metabolism (mmu00053) and glutathione metabolism (mmu00480), were only statistically significantly changed after TiO2 NP and fipronil co-exposure. Five metabolites, including 2-deoxy-D-erythro-pentofuranose 5-phosphate, 5alpha-cholestanol, beta-D-glucopyranuronic acid, elaidic acid, and isopentadecanoic acid, and maltotriose, were more significantly up-regulated after the co-exposure, whereas trisaccharide and xylonolactone were only significantly down-regulated by the co-exposure. We concluded that fipronil had minimal impact to enhance the toxicity of TiO2 NPs to mouse intestines but altered metabolite profiles.

Exploring the nematicidal mechanisms and control efficiencies of oxalic acid producing Aspergillus tubingensis WF01 against root-knot nematodes.

Background and aims: Root-knot nematodes (RKN; Meloidogyne spp.) are among the highly prevalent and significantly detrimental pathogens that cause severe economic and yield losses in crops. Currently, control of RKN primarily relies on the application of chemical nematicides but it has environmental and public health concerns, which open new doors for alternative methods in the form of biological control. Methods: In this study, we investigated the nematicidal and attractive activities of an endophytic strain WF01 against Meloidogyne incognita in concentration-dependent experiments. The active nematicidal metabolite was extracted in the WF01 crude extract through the Sephadex column, and its structure was identified by nuclear magnetic resonance and mass spectrometry data. Results: The strain WF01 was identified as Aspergillus tubingensis based on morphological and molecular characteristics. The nematicidal and attractive metabolite of A. tubingensis WF01 was identified as oxalic acid (OA), which showed solid nematicidal activity against M. incognita, having LC50 of 27.48 µg ml-1. The Nsy-1 of AWC and Odr-7 of AWA were the primary neuron genes for Caenorhabditis elegans to detect OA. Under greenhouse, WF01 broth and 200 µg ml-1 OA could effectively suppress the disease caused by M. incognita on tomatoes respectively with control efficiency (CE) of 62.5% and 70.83%, and promote plant growth. In the field, WF01-WP and 8% OA-WP formulations showed moderate CEs of 51.25%-61.47% against RKN in tomato and tobacco. The combined application of WF01 and OA resulted in excellent CEs of 66.83% and 69.34% toward RKN in tomato and tobacco, respectively. Furthermore, the application of WF01 broth or OA significantly suppressed the infection of J2s in tomatoes by upregulating the expression levels of the genes (PAL, C4H, HCT, and F5H) related to lignin synthesis, and strengthened root lignification. Conclusion: Altogether, our results demonstrated that A. tubingensis WF01 exhibited multiple weapons to control RKN mediated by producing OA to lure and kill RKN in a concentration-dependent manner and strengthen root lignification. This fungus could serve as an environmental bio-nematicide for managing the diseases caused by RKN.