Aqueous Dispersion of Aramid Nanofibers Achieved by Using Tannic Acid for Ultrahigh Strength Films.

Polymer nanofibers have established a robust foundation and possess immense potential in various emerging fields such as sensors and biotechnology. In this study, aqueous dispersions of aramid nanofibers (ANFs) were successfully prepared by using tannic acid (TA). Morphological analysis revealed that TA effectively prevented self-aggregation of ANFs, and preserved the nanofiber structure during TA-assisted solvent exchange. Subsequently, the ANF and TA/ANF films were fabricated using casting and vacuum-assisted filtration techniques. Notably, the tensile strength of the casting TA/ANF film reached 393.8 MPa, exhibiting a remarkable improvement of 41.3% compared to that of the pure ANF film. These exceptional mechanical properties can be attributed to the well-dispersed nanostructures, hydrogen-bonding interactions, zigzag structures, and fiber-bridging effects. Furthermore, the TA/ANF film demonstrated superior ultraviolet (UV) shielding capabilities, visible transparency properties, and excellent resistance to chemical reagents. The above-mentioned interesting findings demonstrate its potential as a nanofiber-reinforced material for poly(vinyl alcohol) (PVA) composites.

CFViSA: A comprehensive and free platform for visualization and statistics in omics-data.

INTRODUCTION: The rapid growth of omics technologies has led to the use of bioinformatics as a powerful tool for unravelling scientific puzzles. However, the obstacles of bioinformatics are compounded by the complexity of data processing and the distinct nature of omics data types, particularly in terms of visualization and statistics. OBJECTIVES: We developed a comprehensive and free platform, CFViSA, to facilitate effortless visualization and statistical analysis of omics data by the scientific community. METHODS: CFViSA was constructed using the Scala programming language and utilizes the AKKA toolkit for the web server and MySQL for the database server. The visualization and statistical analysis were performed with the R program. RESULTS: CFViSA integrates two omics data analysis pipelines (microbiome and transcriptome analysis) and an extensive array of 79 analysis tools spanning simple sequence processing, visualization, and statistics available for various omics data, including microbiome and transcriptome data. CFViSA starts from an analysis interface, paralleling a demonstration full course to help users understand operating principles and scientifically set the analysis parameters. Once analysis is conducted, users can enter the task history interface for figure adjustments, and then a complete series of results, including statistics, feature tables and figures. All the graphic layouts were printed with necessary statistics and a traceback function recording the options for analysis and visualization; these statistics were excluded from the five competing methods. CONCLUSION: CFViSA is a user-friendly bioinformatics cloud platform with detailed guidelines for integrating functions in multi-omics analysis with real-time visualization adjustment and complete series of results provision. CFViSA is available at http://www.cloud.biomicroclass.com/en/CFViSA/.

Periodontal ligament cells-derived exosomes promote osteoclast differentiation via modulating macrophage polarization.

Several studies have demonstrated that exosomes (Exos) are involved in the regulation of macrophage polarization and osteoclast differentiation. However, the characteristics as well as roles of exosomes from human periodontal ligament cells (hPDLCs-Exos) in M1/M2 macrophage polarization and osteoclast differentiation remain unclear. Here, periodontal ligament cells were successfully extracted by method of improved Type-I collagen enzyme digestion. hPDLCs-Exos were extracted by ultracentrifugation. hPDLCs-Exos were identified by transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA) and western blotting (WB). Osteoclast differentiation was evaluated by real-time quantitative polymerase chain reaction (RT-qPCR), WB and tartrate-resistant acid phosphatase (TRAP) staining. M1/M2 macrophage polarization were evaluated by RT-qPCR and WB. The results showed hPDLCs-Exos promoted osteoclast differentiation and M2 macrophage polarization, but inhibited M1 macrophage polarization. Moreover, M1 macrophages inhibited osteoclast differentiation, whereas M2 macrophages promoted osteoclast differentiation. It has shown that hPDLCs-Exos promoted osteoclast differentiation by inhibiting M1 and promoting M2 macrophage polarization.

One-Step Method for Fabricating Janus Aramid Nanofiber/MXene Nanocomposite Films with Improved Joule Heating and Thermal Camouflage Properties.

The integration of ultraflexible and mechanically robust films with electric heaters and camouflage technology provides a promising platform for the development of wearable devices, especially for aerospace and military applications. Herein, we present a facile and efficient one-step vacuum-assisted filtration method for fabricating Janus films based on aramid nanofibers (ANF) and Ti3C2Tx (MXene). The ANF/MXene nanocomposite film exhibits remarkable properties, including high conductivity (23809.5 S/m), excellent mechanical strength (102.54 MPa), and outstanding thermal stability (575 °C). Most notably, the Janus ANF/MXene composite film demonstrates superior Joule heating performance with a low driving voltage (1-5 V), high heating temperature (30-276 °C), and rapid response time (within 5 s). Additionally, the film exhibits effective thermal camouflage (72 °C for objects with temperatures above 163 °C) and excellent electromagnetic interference shielding properties (SSE/t = 32475.6 dB cm2/g). These results demonstrate that Janus ANF/MXene films possess a unique combination of thermal camouflage, Joule heating, and electromagnetic interference shielding properties, making them highly promising for wearable devices, high-performance electrical heating, infrared stealth, and security protection applications.

Analysis of Correlation Between Coronary Heart Disease and Genetic Polymorphism Detected by Gold Magnetic Nanoparticles Chromatography.

It aimed to explore the correlation of Glu504Lys locus mutation of aldehyde dehydrogenase-2 (ALDH2) with coronary heart disease (CHD) based on gold magnetic nanoparticles (GMNPs) chromatography and amplification refractory mutation system-PCR (ARMS-PCR). 120 CHD patients admitted to the cardiovascular Department of Wenling First People's Hospital affiliated to Wenzhou Medical University from December 2020 to December 2021 were selected as Case group and 80 non-CHD patients admitted during the same period were selected as Ctrl group. The venous blood and indexes of Total Cholesterol (TC), Triglyceride (TG), Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Fasting Blood Glucose (FBS) were collected. The ARMS-PCR GMNPs chromatography based on ARMS-PCR and immunochromatography assay was adopted to detect gene polymorphism of ALDH2. Correlation between ALDH2 gene polymorphism and risk factors of CHD was analyzed via logistic regression. In contrast to Ctrl group, the genotypes of GG, GA, and AA in Case group were evidently different (P < 0.05), and the frequency of A allelic gene was obviously increased (P < 0.05). Under the dominant model, frequency of GA + AA genotype in Case group was remarkably higher in contrast to Ctrl group (P < 0.05). Under the recessive model, there was no obvious difference in genotype frequency between two groups. In contrast to Ctrl group, TC, LDL-C, and FBS in Case group were notably increased (P < 0.05), while HDL-C was notably decreased (P < 0.05). The distribution frequency of abnormal LDL-C, HDL-C, and FBS in Case group was notably higher in contrast to Ctrl group (P < 0.05). LDL-C and FBS had no obvious effect on the genotypes and frequency distribution of alleles in CHD patients. However, the frequency distribution of genotypes of GA and AA and A allelic gene in patients with abnormal HDL-C was notably lower in contrast to those with normal HDL-C (P < 0.05). Logistic regression analysis showed that abnormal HDC-C with A allelic gene were independent risk factors for CHD (P = 0.001, OR = 1.934). The gene polymorphism of Glu504Lys locus of ALDH2 was closely related to the pathogenesis of CHD, A allelic gene may be a susceptibility gene for CHD, and patients with abnormal HDC-C and carried A allelic gene had relatively higher incidence of CHD.

T Lymphoblastic Lymphoma Hiding in Mature Plasmacytoid Dendritic Cell Proliferation: A Case Report and Literature Review.

To the best of the author's knowledge, studies of mature plasmacytoid dendritic cell proliferation associated with T lymphoblastic lymphoma were extremely rare in the literature. Here, we report a patient who underwent both mature plasmacytoid dendritic cell proliferation and T lymphoblastic lymphoma. With the findings of lymph node biopsy taken from the right cervical and inguinal regions, we identified eye-catching mature plasmacytoid dendritic cells that were considered to be responsible for this lesion at the beginning, until the immunostaining of Ki67 and TDT showed a small group of positive cells hiding in these plasmacytoid dendritic cells. A bone marrow biopsy was also performed on this patient. Microscopically, the hematopoietic tissue was almost completely replaced by lymphoblastoid cells with condensed chromatin, inconspicuous nucleoli and scanty cytoplasm, which were basically the same as those seen in the lymph nodes in morphology. However, there was no sign of plasmacytoid dendritic cells or Langerhans cells in the bone marrow biopsy. With the help of bone marrow biopsy, our final diagnosis of the lymph node was T lymphoblastic lymphoma coexisting with mature plasmacytoid dendritic cell proliferation. Although accumulations of plasmacytoid dendritic cells may occur in some infections or reactive lymphadenopathy, the presence of extensive nodules or infiltration of plasmacytoid dendritic cells strongly reminds the pathologist to carefully evaluate the bone marrow or peripheral blood status of the patient to exclude a hidden myeloid or other neoplasm.

Predicting cutaneous malignant melanoma patients' survival using deep learning: a retrospective cohort study.

BACKGROUND: Cutaneous malignant melanoma (CMM) has the worst prognosis among skin cancers, especially metastatic CMM. Predicting its prognosis accurately could direct clinical decisions. METHODS: The Surveillance, Epidemiology, and End Results database was screened to collect CMM patients' data. According to diagnosed time, patients were subdivided into three cohorts, train cohort (diagnosed between 2010 and 2013), validation cohort (diagnosed in 2014), and test cohort (diagnosed in 2015). Train cohort was used to train deep learning survival model for cutaneous malignant melanoma (DeepCMM). DeepCMM was then evaluated in train cohort and validation cohort internally, and validated in test cohort externally. RESULTS: DeepCMM showed 0.8270 (95% CI, confidence interval, CI 0.8260-0.8280) as area under the receiver operating characteristic curve (AUC) in train cohort, 0.8274 (95% CI 0.8286-0.8298) AUC in validation cohort, and 0.8303 (95% CI 0.8289-0.8316) AUC in test cohort. Then DeepCMM was packaged into a Windows 64-bit software for doctors to use. CONCLUSION: Deep learning survival model for cutaneous malignant melanoma (DeepCMM) can offer a reliable prediction on cutaneous malignant melanoma patients' overall survival.

Single-cell RNA-seq reveals a microenvironment and an exhaustion state of T/NK cells in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a heterogeneous blood cancer. Effective immunotherapies for AML are hindered by a lack of understanding of the tumor microenvironment (TME). Here, we retrieved published single-cell RNA sequencing data for 128,688 cells derived from 29 bone marrow aspirates, including 21 AML patients and eight healthy donors. We established a global tumor ecosystem including nine main cell types. Myeloid, T, and NK cells were further re-clustered and annotated. Developmental trajectory analysis indicated that exhausted CD8+ T cells might develop via tissue residual memory T cells (TRM) in the AML TME. Significantly higher expression levels of exhaustion molecules in AML TRM cells suggested that these cells were influenced by the TME and entered an exhausted state. Meanwhile, the upregulation of checkpoint molecules and downregulation of granzyme were also observed in AML NK cells, suggesting an exhaustion state. In conclusion, our comprehensive profiling of T/NK subpopulations provides deeper insights into the AML immunosuppressive ecosystem, which is critical for immunotherapies.

A novel 5-gene prognostic signature to improve risk stratification of cytogenetically normal acute myeloid leukemia.

PURPOSE: Prognostic prediction is a challenging task in cytogenetically normal acute myeloid leukemia (CN-AML) patients. In this study, we aimed at developing a novel prognostic signature to predict and stratify the survival of CN-AML patients. METHODS: Using a training dataset (GSE12417), 5-gene prognostic signature was established to predict survival of CN-AML patients. The prognostic performance of this prognostic signature was further validated in testing dataset (TCGA CN-AML cohort) and validation dataset (GSE6891 CN-AML cohort). RESULTS: In training, testing and validation datasets, the increased 5-gene risk score was significantly related with inferior overall survival (OS) of patients, and the area under the receiver operating characteristic curve (AUC) demonstrated that our prognostic signature had overall prediction accuracy. The excellent prognostic value of the 5-gene prognostic signature was also supported by the comparison with three previously proposed prognostic models. For the intermediate-risk CN-AML patients and the CN-AML patients with FLT3 or NPM1 mutation, our model could also well dichotomize them into two subgroups with distinct prognosis. Multivariate analysis demonstrated that 5-gene risk score was the only independent risk factor in TCGA CN-AML cohort. Nomogram including the 5-gene risk score performed well in predicting 1-year, 2-year and 3-year OS. CONCLUSION: In summary, our novel 5-gene prognostic signature facilitated the improvement in risk stratification of CN-AML patients.

A novel privacy-preserving biometric authentication scheme.

Most existing secure biometric authentication schemes are server-centric, and users must fully trust the server to store, process, and manage their biometric data. As a result, users' biometric data could be leaked by outside attackers or the service provider itself. This paper first constructs the EDZKP protocol based on the inner product, which proves whether the secret value is the Euclidean distance of the secret vectors. Then, combined with the Cuproof protocol, we propose a novel user-centric biometric authentication scheme called BAZKP. In this scheme, all the biometric data remain encrypted during authentication phase, so the server will never see them directly. Meanwhile, the server can determine whether the Euclidean distance of two secret vectors is within a pre-defined threshold by calculation. Security analysis shows BAZKP satisfies completeness, soundness, and zero-knowledge. Based on BAZKP, we propose a privacy-preserving biometric authentication system, and its evaluation demonstrates that it provides reliable and secure authentication.

The landscape of extrachromosomal circular DNA (eccDNA) in the normal hematopoiesis and leukemia evolution.

Elevated extrachromosomal circular DNA (eccDNA) has been reported to accelerate tumor pathogenesis. Although the eccDNA profiles of other tumors have been established, the landscape of the eccDNA of acute myeloid leukemia (AML) has not been revealed. Our study first depicted the eccDNA profile of normal hematopoiesis and AML evolution by exploiting the ATAC-seq and RNA-seq data from nine healthy donors and 12 AML patients, which contained a total of 137 cell samples and 96 RNA-seq samples (including 16 blood cell types of the normal hematopoietic and AML hierarchies). We found the number of eccDNAs generally increased with the evolution of normal hematopoiesis and AML. The ecDNAs and ring chromosomes were found to reappear both in normal hematopoiesis and AML cells. Furthermore, we compared the eccDNAs of AML with normal cells. There were almost 300 AML-specific genes, including the known oncogenes NRAS, MCL1, EVI1, GATA2, WT1, and PAK1. And the ecDNA (chr11: 58668376-58826008) occurred in five out of 17 AML evolution-related cells, which was associated with the high expression of the GLYATL1 gene and the high expressed GLYATL1 was a poor prognostic factor. In conclusion, the eccDNA profiles of normal hematopoiesis and AML evolution were depicted and the recurrent eccDNAs we revealed might be utilized in the treatment of AML as biomarkers.

Preparation and Properties of Sulfonated Poly(phthalazinone ether ketone) Membranes for Electrodialysis.

Sulfonated poly(phthalazinone ether ketones) (SPPEK) with ion exchange capacities from 0.77 to 1.82 mmol·g-1 are synthesized via an electrophilic substitution reaction. Nuclear magnetic resonance and infrared absorption spectroscopy are used to characterize the chemical structure of the obtained polymers for confirming the successful introduction of sulfonic groups. SPPEKs show excellent thermal stability; their temperature required to achieve 5% weight loss is about 360 °C. Accordingly, the obtained membranes possess high ion perm-selectivity, proton conductivity, and low area resistance. Regarding the electrodialysis-related performance of the membranes, the SPPEK-4 membrane has the highest limiting current density (39.8 mA·cm2), resulting from its high content of sulfonic groups. In a desalination test of standard solution, SPPEK-3 and SPPEK-4 membranes exhibit both better salt removal rate and acceptable energy consumption than commercial membrane. Additionally, SPPEK-3 membrane shows outstanding performance in terms of high concentration rate and low energy consumption during saline water treatment, which indicates the feasibility of novel membranes in electrodialysis application.

The coupling effect of cellulose nanocrystal and strong shear field achieved the strength and toughness balance of Polylactide.

Up to now, unbalanced mechanical properties and poor heat resistance have become two major problems of polylactic acid (PLA). In this study, the coupling between Cellulose nanocrystal (CNC) and strong shearing field formed a unique hierarchical structure. Compared with pure PLA, the tensile strength of DPIM PLA/CNC increased from 57.9 MPa to 79.6 MPa without sacrificing the toughness of PLA, and the vicat softening temperature of DPIM PLA/CNC increased from 60 °C to 155 °C. The microstructure of PLA/CNC composites was analyzed by SEM, SAXS and WAXD, and it was found that the coupling effect of CNC and strong shear flow field could significantly change the crystallization behavior of PLA. CNC could increase PLA shish length from 251 nm to 889 nm under the action of shear field. At the same time, due to this coupling effect, more PLA shish-kebab structures were induced at the interface. This special hierarchical structure composed of CNC and PLA Shish-Kebab is of great significance and can provide important guidance for achieving the balance of strength and toughness of polymer materials.

Cuproof: Range Proof with Constant Size.

Zero-Knowledge Proof is widely used in blockchains. For example, zk-SNARK is used in Zcash as its core technology to identifying transactions without the exposure of the actual transaction values. Up to now, various range proofs have been proposed, and their efficiency and range-flexibility have also been improved. Bootle et al. used the inner product method and recursion to construct an efficient Zero-Knowledge Proof in 2016. Later, Benediky Bünz et al. proposed an efficient range proof scheme called Bulletproofs, which can convince the verifier that a secret number lies in [0,2κ-1] with κ being a positive integer. By combining the inner-product and Lagrange's four-square theorem, we propose a range proof scheme called Cuproof. Our Cuproof can make a range proof to show that a secret number v lies in an interval [a,b] with no exposure of the real value v or other extra information leakage about v. It is a good and practical method to protect privacy and information security. In Bulletproofs, the communication cost is 6+2logκ, while in our Cuproof, all the communication cost, the proving time and the verification time are of constant sizes.

Complete Genome Sequencing and Comparative Analysis of the Clinically-Derived Apiotrichum mycotoxinivorans Strain GMU1709.

Over the past decade, Apiotrichum mycotoxinivorans has been recognized globally as a source of opportunistic infections. It is a yeast-like fungus, and its association as an uncommon pulmonary pathogen with cystic fibrosis patients has been previously reported. Immunocompromised patients are at the highest risk of A. mycotoxinivorans infections. Therefore, to investigate the genetic basis for the pathogenicity of A. mycotoxinivorans, we performed whole-genome sequencing and comparative genomic analysis of A. mycotoxinivorans GMU1709 that was isolated from sputum specimens of a pneumonia patient receiving cardiac repair surgery. The assembly of Oxford Nanopore reads from the GMU1709 strain and its subsequent correction using Illumina paired-end reads yielded a high-quality complete genome with a genome size of 30.5 Mb in length, which comprised six chromosomes and one mitochondrion. Subsequently, 8,066 protein-coding genes were predicted based on multiple pieces of evidence, including transcriptomes. Phylogenomic analysis indicated that A. mycotoxinivorans exhibited the closest evolutionary affinity to A. veenhuisii, and both the A. mycotoxinivorans strains and the formerly Trichosporon cutaneum ACCC 20271 strain occupied the same phylogenetic position. Further comparative analysis supported that the ACCC 20271 strain belonged to A. mycotoxinivorans. Comparisons of three A. mycotoxinivorans strains indicated that the differences between clinical and non-clinical strains in pathogenicity and drug resistance may be little or none. Based on the comparisons with strains of other species in the Trichosporonaceae family, we identified potential key genetic factors associated with A. mycotoxinivorans infection or pathogenicity. In addition, we also deduced that A. mycotoxinivorans had great potential to inactivate some antibiotics (e.g., tetracycline), which may affect the efficacy of these drugs in co-infection. In general, our analyses provide a better understanding of the classification and phylogeny of the Trichosporonaceae family, uncover the underlying genetic basis of A. mycotoxinivorans infections and associated drug resistance, and provide clues into potential targets for further research and the therapeutic intervention of infections.

The establishment of a prognostic scoring model based on the new tumor immune microenvironment classification in acute myeloid leukemia.

BACKGROUND: The high degree of heterogeneity brought great challenges to the diagnosis and treatment of acute myeloid leukemia (AML). Although several different AML prognostic scoring models have been proposed to assess the prognosis of patients, the accuracy still needs to be improved. As important components of the tumor microenvironment, immune cells played important roles in the physiological functions of tumors and had certain research value. Therefore, whether the tumor immune microenvironment (TIME) can be used to assess the prognosis of AML aroused our great interest. METHODS: The patients' gene expression profile from 7 GEO databases was normalized after removing the batch effect. TIME cell components were explored through Xcell tools and then hierarchically clustered to establish TIME classification. Subsequently, a prognostic model was established by Lasso-Cox. Multiple GEO databases and the Cancer Genome Atlas dataset were employed to validate the prognostic performance of the model. Receiver operating characteristic (ROC) and the concordance index (C-index) were utilized to assess the prognostic efficacy. RESULTS: After analyzing the composition of TIME cells in AML, we found infiltration of ten types of cells with prognostic significance. Then using hierarchical clustering methods, we established a TIME classification system, which clustered all patients into three groups with distinct prognostic characteristics. Using the differential genes between the first and third groups in the TIME classification, we constructed a 121-gene prognostic model. The model successfully divided 1229 patients into the low and high groups which had obvious differences in prognosis. The high group with shorter overall survival had more patients older than 60 years and more poor-risk patients (both P< 0.001). Besides, the model can perform well in multiple datasets and could further stratify the cytogenetically normal AML patients and intermediate-risk AML population. Compared with the European Leukemia Net Risk Stratification System and other AML prognostic models, our model had the highest C-index and the largest AUC of the ROC curve, which demonstrated that our model had the best prognostic efficacy. CONCLUSION: A prognostic model for AML based on the TIME classification was constructed in our study, which may provide a new strategy for precision treatment in AML.