A dual computational and experimental strategy to enhance TSLP antibody affinity for improved asthma treatment.

Thymic stromal lymphopoietin is a key cytokine involved in the pathogenesis of asthma and other allergic diseases. Targeting TSLP and its signaling pathways is increasingly recognized as an effective strategy for asthma treatment. This study focused on enhancing the affinity of the T6 antibody, which specifically targets TSLP, by integrating computational and experimental methods. The initial affinity of the T6 antibody for TSLP was lower than the benchmark antibody AMG157. To improve this, we utilized alanine scanning, molecular docking, and computational tools including mCSM-PPI2 and GEO-PPI to identify critical amino acid residues for site-directed mutagenesis. Subsequent mutations and experimental validations resulted in an antibody with significantly enhanced blocking capacity against TSLP. Our findings demonstrate the potential of computer-assisted techniques in expediting antibody affinity maturation, thereby reducing both the time and cost of experiments. The integration of computational methods with experimental approaches holds great promise for the development of targeted therapeutic antibodies for TSLP-related diseases.

Storage Stability of Blood Samples for miRNAs in Glycosylated Extracellular Vesicles.

Extracellular vesicle (EV) miRNAs are promising biomarkers for clinical diagnosis. However, their stability is a crucial concern affecting reliability and accuracy. Factors such as sample collection, processing, storage conditions, and experimental procedures impact EV miRNA stability. Studying EV miRNA stability aims to find optimal handling and storage methods, ensuring integrity and functionality throughout research. In this study, we used RT-qPCR and GlyExo-Capture technology, which can specifically capture glycosylated EVs by lectin, to assess the stability of glycosylated EV miRNAs. We found that slow acceleration centrifugation and two-step centrifugation methods were suitable for subsequent experiments. To ensure uniformity, we recommend using the two-step centrifugation method. We also studied blood storage before serum separation and recommend separation within 2 h at 4 °C or 25 °C. For separated serum samples, higher temperatures accelerated miRNA degradation, and the storage duration should be adjusted based on laboratory conditions. Short-term storage at -20 °C is acceptable for up to 3 months while avoiding repeated freeze-thaw cycles. We developed protective agents to extend the storage time at 25 °C, meeting clinical requirements. Additionally, Lakebio's cfRNA storage tubes effectively preserved the stability of miRNAs in plasma glycosylated EVs. Understanding EV miRNA stability provides insights into optimizing sample handling, storage strategies, and enhancing reliability in clinical applications.

The impact of antibiotic exposure on antibiotic resistance gene dynamics in the gut microbiota of inflammatory bowel disease patients.

Background: While antibiotics are commonly used to treat inflammatory bowel disease (IBD), their widespread application can disturb the gut microbiota and foster the emergence and spread of antibiotic resistance. However, the dynamic changes to the human gut microbiota and direction of resistance gene transmission under antibiotic effects have not been clearly elucidated. Methods: Based on the Human Microbiome Project, a total of 90 fecal samples were collected from 30 IBD patients before, during and after antibiotic treatment. Through the analysis workflow of metagenomics, we described the dynamic process of changes in bacterial communities and resistance genes pre-treatment, during and post-treatment. We explored potential consistent relationships between gut microbiota and resistance genes, and established gene transmission networks among species before and after antibiotic use. Results: Exposure to antibiotics can induce alterations in the composition of the gut microbiota in IBD patients, particularly a reduction in probiotics, which gradually recovers to a new steady state after cessation of antibiotics. Network analyses revealed intra-phylum transfers of resistance genes, predominantly between taxonomically close organisms. Specific resistance genes showed increased prevalence and inter-species mobility after antibiotic cessation. Conclusion: This study demonstrates that antibiotics shape the gut resistome through selective enrichment and promotion of horizontal gene transfer. The findings provide insights into ecological processes governing resistance gene dynamics and dissemination upon antibiotic perturbation of the microbiota. Optimizing antibiotic usage may help limit unintended consequences like increased resistance in gut bacteria during IBD management.

In search of the ratio of miRNA expression as robust biomarkers for constructing stable diagnostic models among multi-center data.

MicroRNAs (miRNAs) are promising biomarkers for the early detection of disease, and many miRNA-based diagnostic models have been constructed to distinguish patients and healthy individuals. To thoroughly utilize the miRNA-profiling data across different sequencing platforms or multiple centers, the models accounting the batch effects were demanded for the generalization of medical application. We conducted transcription factor (TF)-mediated miRNA-miRNA interaction network analysis and adopted the within-sample expression ratios of miRNA pairs as predictive markers. The ratio of the expression values between each miRNA pair turned out to be stable across multiple data sources. A genetic algorithm-based classifier was constructed to quantify risk scores of the probability of disease and discriminate disease states from normal states in discovery, with a validation dataset for COVID-19, renal cell carcinoma, and lung adenocarcinoma. The predictive models based on the expression ratio of interacting miRNA pairs demonstrated good performances in the discovery and validation datasets, and the classifier may be used accurately for the early detection of disease.

Direct Ink Writing of SiCN/RuO2/TiB2 Composite Ceramic Ink for High-Temperature Thin-Film Sensors.

Direct ink writing (DIW) of high-temperature thin-film sensors holds significant potential for monitoring extreme environments. However, existing high-temperature inks face a trade-off between cost and performance. This study proposes a SiCN/RuO2/TiB2 composite ceramic ink. The added TiB2, after annealing in a high-temperature atmospheric environment, forms B2O3 glass, which synergizes with the SiO2 glass phase formed from the SiCN precursor to effectively encapsulate RuO2 particles. This enhances the film's density and adhesion to the substrate, preventing RuO2 volatilization at high temperatures. Additionally, the high conductivity of TiB2 improves the film's overall conductivity. Test results indicate that the SiCN/RuO2/TiB2 film exhibits high linearity from room temperature to 900 °C, high stability (resistance drift rate of 0.1%/h at 800 °C), and high conductivity (4410 S/m). As a proof of concept, temperature sensors and a heat flux sensor were successfully fabricated on a metallic hemispherical surface. Performance tests in extreme environments using high-power lasers and flame guns verified that the conformal thin-film sensor can accurately measure spherical temperature and heat flux, with a heat flux sensor response time of 53 ms. In conclusion, the SiCN/RuO2/TiB2 composite ceramic ink developed in this study offers a high-performance and cost-effective solution for high-temperature conformal thin-film sensors in extreme environments.

Conformal Fabrication of Thick Film Platinum Strain Gauge Via Error Regulation Strategies for In Situ High-Temperature Strain Detection.

Monitoring high-temperature strain on curved components in harsh environments is a challenge for a wide range of applications, including in aircraft engines, gas turbines, and hypersonic vehicles. Although there are significant improvements in the preparation of high-temperature piezoresistive film on planar surfaces using 3D printing methods, there are still difficulties with poor surface compatibility and high-temperature strain testing on curved surfaces. Herein, a conformal direct ink writing (CDIW) system coupled with an error feedback regulation strategy was used to fabricate high-precision, thick films on curved surfaces. This strategy enabled the maximum amount of error in the distance between the needle and the substrate on a curved surface to be regulated from 155 to 4 µm. A conformal Pt thick-film strain gauge (CPTFSG) with a room-temperature strain coefficient of 1.7 was created on a curved metallic substrate for the first time. The resistance drift rate at 800 °C for 1 h was 1.1%, which demonstrated the excellent stability and oxidation resistance of the CPTFSG. High-temperature dynamic strain tests up to 769 °C revealed that the sensor had excellent high-temperature strain test performance. Furthermore, the CPTFSG was conformally deposited on an aero-engine turbine blade to perform in situ tensile and compressive strain testing at room temperature. High-temperature strain tests were conducted at 100 and 200 °C for 600 and 580 µÎµ, respectively, demonstrating a high steady-state response consistent with the commercial high-temperature strain transducer. In addition, steady-state strain tests at high temperatures up to 496 °C were tested. The CDIW error modulation strategy provides a highly promising approach for the high-precision fabrication of Pt thick films on complex surfaces and driving in situ sensing of high-temperature parameters on curved components toward practical applications.

Rapid laser fabrication of indium tin oxide and polymer-derived ceramic composite thin films for high-temperature sensors.

Thin-film sensors are essential for real-time monitoring of components in high-temperature environments. Traditional fabrication methods often involve complicated fabrication steps or require prolonged high-temperature annealing, limiting their practical applicability. Here, we present an approach using direct ink writing and laser scanning (DIW-LS) to fabricate high-temperature functional thin films. An indium tin oxide (ITO)/preceramic polymer (PP) ink suitable for DIW was developed. Under LS, the ITO/PP thin film shrank in volume. Meanwhile, the rapid pyrolysis of PP into amorphous precursor-derived ceramic (PDC) facilitated the faster sintering of ITO nanoparticles and improved the densification of the thin film. This process realized the formation of a conductive network of interconnected ITO nanoparticles. The results show that the ITO/PDC thin film exhibits excellent stability, with a drift rate of 4.7 % at 1000 °C for 25 h, and withstands temperatures up to 1250 °C in the ambient atmosphere. It is also sensitive to strain, with a maximum gauge factor of -6.0. As a proof of concept, we have used DIW-LS technology to fabricate a thin-film heat flux sensor on the surface of the turbine blade, capable of measuring heat flux densities over 1 MW/m2. This DIW-LS process provides a viable approach for the integrated, rapid, and flexible fabrication of thin film sensors for harsh environments.

Observation of topological frequency combs.

On-chip generation of optical frequency combs using nonlinear ring resonators has enabled numerous applications of combs that were otherwise limited to mode-locked lasers. Nevertheless, on-chip frequency combs have relied predominantly on single-ring resonators. In this study, we experimentally demonstrate the generation of a novel class of frequency combs, the topological frequency combs, in a two-dimensional lattice of hundreds of ring resonators that hosts fabrication-robust topological edge states with linear dispersion. By pumping these edge states, we demonstrate the generation of a nested frequency comb that shows oscillation of multiple edge state resonances across ≈40 longitudinal modes and is spatially confined at the lattice edge. Our results provide an opportunity to explore the interplay between topological physics and nonlinear frequency comb generation in a commercially available nanophotonic platform.

Rapid discrimination of Bifidobacterium longum subspecies based on MALDI-TOF MS and machine learning.

Although MALDI-TOF mass spectrometry (MS) is widely known as a rapid and cost-effective reference method for identifying microorganisms, its commercial databases face limitations in accurately distinguishing specific subspecies of Bifidobacterium. This study aimed to explore the potential of MALDI-TOF MS protein profiles, coupled with prediction methods, to differentiate between Bifidobacterium longum subsp. infantis (B. infantis) and Bifidobacterium longum subsp. longum (B. longum). The investigation involved the analysis of mass spectra of 59 B. longum strains and 41 B. infantis strains, leading to the identification of five distinct biomarker peaks, specifically at m/z 2,929, 4,408, 5,381, 5,394, and 8,817, using Recurrent Feature Elimination (RFE). To facilate classification between B. longum and B. infantis based on the mass spectra, machine learning models were developed, employing algorithms such as logistic regression (LR), random forest (RF), and support vector machine (SVM). The evaluation of the mass spectrometry data showed that the RF model exhibited the highest performace, boasting an impressive AUC of 0.984. This model outperformed other algorithms in terms of accuracy and sensitivity. Furthermore, when employing a voting mechanism on multi-mass spectrometry data for strain identificaton, the RF model achieved the highest accuracy of 96.67%. The outcomes of this research hold the significant potential for commercial applications, enabling the rapid and precise discrimination of B. longum and B. infantis using MALDI-TOF MS in conjunction with machine learning. Additionally, the approach proposed in this study carries substantial implications across various industries, such as probiotics and pharmaceuticals, where the precise differentiation of specific subspecies is essential for product development and quality control.

A community study of neutralizing antibodies against SARS-CoV-2 in China.

Background: The immune background of the overall population before and after the outbreak of SARS-CoV-2 in China remains unexplored. And the level of neutralizing antibodies is a reliable indicator of individual immunity. Objectives: This study aimed to assess the immune levels of different population groups during a viral outbreak and identify the factors influencing these levels. Methods: We measured the levels of neutralizing antibodies in 12,137 participants using the COVID19 Neutralizing Antibody Detection kit. The dynamics of neutralizing antibodies were analyzed using a generalized additive model, while a generalized linear model and multi-factor analysis of variance were employed to investigate the influencing factors. Additionally, statistical methods were used to compare neutralizing antibody levels among subgroups of the real-world population. Results: Participants who received booster doses exhibited significantly higher levels of neutralizing antibodies compared to those who received only one or two doses (p<0.001). Both elderly [22.55 (5.12, 62.03) IU/mL, 55%] and minors [21.41 (8.15, 45.06) IU/mL, 56%] showed lower positivity rates and neutralizing antibody levels compared to young adults [29.30 (9.82, 188.08) IU/mL, 62%] (p<0.001). Furthermore, the HIV-positive group demonstrated a slightly lower seropositivity rate compared to the healthy group across the three vaccination time points. Notably, three months after the large-scale infection, both the neutralizing antibody level and positivity rate in real-world populations were higher than the previous record [300 (300, 300) IU/mL, 89%; 27.10 (8.77, 139.28) IU/mL, 60%], and this difference was statistically significant. Conclusions: Increasing vaccine dosage enhances neutralizing antibody levels, resulting in greater and longer-lasting immunity. Monitoring immune levels in older individuals and those with AIDS is crucial. Additionally, the neutralizing antibodies generated from vaccination have not yet reached the threshold for achieving herd immunity, while individuals exhibit higher immune levels following a large-scale infection. These findings provide valuable insights for guiding new strategies in vaccine administration.