Machine learning-based prediction of diabetic patients using blood routine data.

Diabetes stands as one of the most prevalent chronic diseases globally. The conventional methods for diagnosing diabetes are frequently overlooked until individuals manifest noticeable symptoms of the condition. This study aimed to address this gap by collecting comprehensive datasets, including 1000 instances of blood routine data from diabetes patients and an equivalent dataset from healthy individuals. To differentiate diabetes patients from their healthy counterparts, a computational framework was established, encompassing eXtreme Gradient Boosting (XGBoost), random forest, support vector machine, and elastic net algorithms. Notably, the XGBoost model emerged as the most effective, exhibiting superior predictive results with an area under the receiver operating characteristic curve (AUC) of 99.90% in the training set and 98.51% in the testing set. Moreover, the model showcased commendable performance during external validation, achieving an overall accuracy of 81.54%. The probability generated by the model serves as a risk score for diabetes susceptibility. Further interpretability was achieved through the utilization of the Shapley additive explanations (SHAP) algorithm, identifying pivotal indicators such as mean corpuscular hemoglobin concentration (MCHC), lymphocyte ratio (LY%), standard deviation of red blood cell distribution width (RDW-SD), and mean corpuscular hemoglobin (MCH). This enhances our understanding of the predictive mechanisms underlying diabetes. To facilitate the application in clinical and real-life settings, a nomogram was created based on the logistic regression algorithm, which can provide a preliminary assessment of the likelihood of an individual having diabetes. Overall, this research contributes valuable insights into the predictive modeling of diabetes, offering potential applications in clinical practice for more effective and timely diagnoses.

Nanoemulsions Stable against Ostwald Ripening.

Ostwald ripening, the dominant mechanism of droplet size growth for an O/W nanoemulsion at high surfactant concentrations, depends on micelles in the water phase and high aqueous solubility of oil, especially for spontaneously formed nanoemulsions. In our study, O/W nanoemulsions were formed spontaneously by mixing a water phase with an oil phase containing fatty alcohol polyoxypropylene polyoxyethylene ether (APE). By monitoring periodically the droplet size of the nanoemulsions via dynamic light scattering, we demonstrated that the formed O/W nanoemulsions are stable against Ostwald ripening, i.e., droplet growth. In contrast, the nanoemulsion droplets grew with the addition of micelles, demonstrating the pivotal role of the presence of micelles in the water phase in the occurrence of Ostwald ripening. The influence of the initial phase of APE, the oil or water phase in which APE is present, on the micelle formation is discussed by the partition coefficient and interfacial adsorption of APE between the oil and water phase using a surface and interfacial tensiometer. In addition, the spontaneously formed O/W nanoemulsion, which is stable against Ostwald ripening, can be used as a nanocarrier for the delivery of water-insoluble pesticides. These results provide a novel approach for the preparation of stable nanoemulsions and contribute to elucidating the mechanism of instability of nanoemulsions.

Killing capacity analysis of tumor-infiltrating cytotoxic lymphocytes and impact on lymph node metastasis in differentiated papillary carcinoma of thyroid with the BRAF V600E mutation.

BACKGROUND: Cytotoxic lymphocytes (CLs) express potent toxins, including perforin (P) and granzyme-B (G), which brings about target cell death. The purpose of this study was to evaluate the killing capacity of tumor-infiltrating CLs by means of P and G analysis, and explore the association with lymph node metastasis in papillary carcinoma of thyroid (PTC) without Hashimoto's thyroiditis (HT). METHODS: Infiltration of lymphocytes in PTC was observed in frozen sections. Both fresh tumor tissues and paracancerous tissues with lymphocyte infiltration were collected and prepared into a single cell suspension. Flow cytometry was used to detect the percentages of CD3+P+, CD3+G+, CD8+P+, and CD8+G+ T lymphocytes (TLs) and CD16-CD56+P+ and CD16-CD56+G+ natural killer (NK) cells. Finally, we investigated differential expression of P and G in NK cells and cytotoxic T lymphocytes (CTLs) in paired tumor tissues (group T, n = 44) and paracancerous tissues (group N, n = 44) from patients with PTC with the BRAF V600E mutation. Furthermore, patients were divided into two groups according to whether cervical central lymph node metastasis (CCLNM) existed: group A (with lymph node metastases, n = 27) and group B (with nonlymph node metastases, n = 17). Patients were also divided into three groups according to the total number of positive CCLNM: group B, group C (with low-level lymph node metastases, less than 5, n = 17) and group D (with high-level lymph node metastases, no less than 5, n = 10). RESULTS: The percentage of CD3+P+ CTLs was significantly higher in group N than in group T (P < 0.05). The percentage of CD8+G+ CTLs was significantly higher in group T than in group N (P < 0.05). The percentages of CD3+G+, CD16-CD56+P+and CD16-CD56+G+ NK cells showed no significant difference in either group T or group N (P > 0.05). The percentages of CD3+P+ CTLs in group A and group C were significantly higher in the paracancerous tissue than in the tumor tissue (P < 0.05). The percentages of CD8+G+ CTLs in group A and group C were significantly higher in the tumor tissues than in the paracancerous tissues (P < 0.05). The percentage of CD16-CD56+G+ NK cells in group D was significantly higher in the tumor tissues than in the paracancerous tissues (P < 0.05). CONCLUSIONS: The killing capacity of infiltrating CLs in PTC differed between tumor tissues and paracancerous tissues. In cases with CCLNM, higher expression of CD16-CD56+G+ NK cells in tumor tissues may be associated with a high risk of lymph node metastasis.

Gallbladder microbial species and host bile acids biosynthesis linked to cholesterol gallstone comparing to pigment individuals.

Gallstones are crystalline deposits in the gallbladder that are traditionally classified as cholesterol, pigment, or mixed stones based on their composition. Microbiota and host metabolism variances among the different types of gallstones remain largely unclear. Here, the bile and gallstone microbial species spectra of 29 subjects with gallstone disease (GSD, 24 cholesterol and 5 pigment) were revealed by type IIB restriction site-associated DNA microbiome sequencing (2bRAD-M). Among them (21 subjects: 18 cholesterol and 3 pigment), plasma samples were subjected to liquid chromatography-mass spectrometry (LC-MS) untargeted metabolomics. The microbiome yielded 896 species comprising 882 bacteria, 13 fungi, and 1 archaeon. Microbial profiling revealed significant enrichment of Cutibacterium acnes and Microbacterium sp005774735 in gallstone and Agrobacterium pusense and Enterovirga sp013044135 in the bile of cholesterol GSD subjects. The metabolome revealed 2296 metabolites, in which malvidin 3-(6''-malonylglucoside), 2-Methylpropyl glucosinolate, and ergothioneine were markedly enriched in cholesterol GSD subjects. Metabolite set enrichment analysis (MSEA) demonstrated enriched bile acids biosynthesis in individuals with cholesterol GSD. Overall, the multi-omics analysis revealed that microbiota and host metabolism interaction perturbations differ depending on the disease type. Perturbed gallstone type-related microbiota may contribute to unbalanced bile acids metabolism in the gallbladder and host, representing a potential early diagnostic marker and therapeutic target for GSD.

Effect of the combined binding of topotecan and catechin/protocatechuic acid to a pH-sensitive DNA tetrahedron on release and cytotoxicity: Spectroscopic and calorimetric studies.

The therapeutic efficacy of chemotherapy drugs can be effectively improved through the dual effects of their combination with natural polyphenols and the delivery of targeted DNA nanostructures. In this work, the interactions of topotecan (TPT), (+)-catechin (CAT), or protocatechuic acid (PCA) with a pH-sensitive DNA tetrahedron (MUC1-TD) in the binary and ternary systems at pHs 5.0 and 7.4 were investigated by fluorescence spectroscopy and calorimetry. The intercalative binding mode of TPT/CAT/PC to MUC1-TD was confirmed, and their affinity was ranked in the order of PCA > CAT > TPT. The effects of the pH-sensitivity of MUC1-TD and different molecular structures of CAT and PCA on the loading, release, and cytotoxicity of TPT were discussed. The weakened interaction under acidic conditions and the co-loading of CAT/PCA, especially PCA, improved the release of TPT loaded by MUC1-TD. The targeting of MUC1-TD and the synergistic effect with CAT/PCA, especially CAT, enhanced the cytotoxicity of TPT on A549 cells. For L02 cells, the protective effect of CAT/PCA reduced the damage caused by TPT. The single or combined TPT loaded by MUC1-TD was mainly concentrated in the nucleus of A549 cells. This work will provide key information for the combined application of TPT and CAT/PCA loaded by DNA nanostructures to improve chemotherapy efficacy and reduce side effects.

Carbohydrate-active enzyme annotation in microbiomes using dbCAN.

CAZymes or carbohydrate-active enzymes are critically important for human gut health, lignocellulose degradation, global carbon recycling, soil health, and plant disease. We developed dbCAN as a web server in 2012 and actively maintain it for automated CAZyme annotation. Considering data privacy and scalability, we provide run_dbcan as a standalone software package since 2018 to allow users perform more secure and scalable CAZyme annotation on their local servers. Here, we offer a comprehensive computational protocol on automated CAZyme annotation of microbiome sequencing data, covering everything from short read pre-processing to data visualization of CAZyme and glycan substrate occurrence and abundance in multiple samples. Using a real-world metagenomic sequencing dataset, this protocol describes commands for dataset and software preparation, metagenome assembly, gene prediction, CAZyme prediction, CAZyme gene cluster (CGC) prediction, glycan substrate prediction, and data visualization. The expected results include publication-quality plots for the abundance of CAZymes, CGCs, and substrates from multiple CAZyme annotation routes (individual sample assembly, co-assembly, and assembly-free). For the individual sample assembly route, this protocol takes ∼33h on a Linux computer with 40 CPUs, while other routes will be faster. This protocol does not require programming experience from users, but it does assume a familiarity with the Linux command-line interface and the ability to run Python scripts in the terminal. The target audience includes the tens of thousands of microbiome researchers who routinely use our web server. This protocol will encourage them to perform more secure, rapid, and scalable CAZyme annotation on their local computer servers.

The association between insomnia symptoms and cognitive flexibility among undergraduates: An event-related potential study.

OBJECTIVE: To explore the association between insomnia symptoms and cognitive flexibility among undergraduates, along with its potential neural mechanisms. METHOD: A total of 102 participants were divided into insomnia (n = 55) and control (n = 47) groups based on sleep status. Cognitive flexibility was assessed using the Cognitive Flexibility Inventory (CFI) and the Number-Letter Task (N-L task). EEG data were recorded during the N-L task. RESULTS: The insomnia group exhibited lower CFI scores and higher switch costs in reaction time and accuracy compared to the control group. ERP analysis showed differences in P2, N2, and P3 component amplitudes between the two groups, with reduced N2 amplitude in the insomnia group under repeat trials. Time-frequency analysis revealed larger theta band event related synchronization in the frontal region and smaller theta band ERS in the parietal region under switch trials in the control group; the alpha band event-related desynchronization in the parietal region under repeat trials was significantly smaller in the control group compared to switch trials. CONCLUSION: Compared to undergraduates with normal sleep, those with insomnia symptoms exhibited reduced cognitive flexibility, which may be associated with some alterations in brain electrophysiological activities.

Constructing a Size-Controllable Spherical P2-Type Layered Oxides Cathode That Achieves Practicable Sodium-Ion Batteries.

P2-type layered metal oxides are regarded as promising cathode materials for sodium-ion batteries due to their high voltage platform and rapid Na+ diffusion kinetics. However, limited capacity and unfavorable cycling stability resulting from inevitable phase transformation and detrimental structure collapse hinder their future application. Herein, based on P2-type Na0.67Ni0.18Mn0.67Cu0.1Zn0.05O2, we synthesized a series of secondary spherical morphology cathodes with different radii derived from controlling precursors prepared by a coprecipitation method, which can be promoted to large-scale production. Consequently, the synthesized materials possessed a high tap density of 1.52 g cm-3 and a compacted density of 3.2 g cm-3. The half cells exhibited a specific capacity of 111.8 mAh g-1 at a current density of 0.1 C as well as an 82.64% capacity retention with a high initial capacity of 85.80 mAh g-1 after 1000 cycles under a rate of 5 C. Notably, in situ X-ray diffraction revealed a reversible P2-OP4 phase transition and displayed a tiny volume change of 6.96% during the charge/discharge process, indicating an outstanding cycling stability of the modified cathode. Commendably, the cylindrical cell achieved a capacity of 4.7 Ah with almost no change during 1000 cycles at 2 C, suggesting excellent potential for future applications.

Research advances of coloring mechanism regulated by MicroRNAs in plants.

In plants, microRNAs (miRNAs) are a class of important small RNAs involved in their growth and development, and play a very significant role in regulating their tissue coloring. In this paper, the mechanisms on miRNA regulation of plant coloring are mainly reviewed from three aspects: macroscopic physiological and molecular foundations related to tissue coloring, miRNA biosynthesis and function, and specific analysis of miRNA regulation studies on leaf color, flower color, fruit color, and other tissue color formation in plants. Furthermore, we also systematically summarize the miRNA regulatory mechanisms identified on pigments biosynthesis and color formation in plants, and the regulatory mechanisms of these miRNAs mentioned on the existing researches can be divided into four main categories: directly targeting the related transcription factors, directly targeting the related structural genes, directly targeting the related long noncoding RNAs (LncRNAs) and miRNA-mediated production of trans-acting small interfering RNAs (ta-siRNAs). Together, these research results aim to provide a theoretical reference for the in-depth study of plant coloring mechanism and molecular breeding study of related plants in the future.