Microphysiologically Engineered Vessel-Tumor Model to Investigate Vascular Transport Dynamics of Immune Cells.

Cancer immunotherapy has emerged as a promising therapeutic strategy to combat cancer effectively. However, it is hard to observe and quantify how this in vivo process happens. Three-dimensional (3D) microfluidic vessel-tumor models offer valuable capability to study how immune cells transport during cancer progression. We presented an advanced 3D vessel-supported tumor model consisting of the endothelial lumen and vessel network for the study of T cells' transportation. The process of T cell transport through the vessel network and interaction with tumor spheroids was represented and monitored in vitro. Specifically, we demonstrate that the endothelial glycocalyx serving in the T cells' transport can influence the endothelium-immune interaction. Furthermore, after vascular transport, how programmed cell death protein 1 (PD-1) immune checkpoint inhibition influences the delivered activated-T cells on tumor killing was evaluated. Our in vitro vessel-tumor model provides a microphysiologically engineered platform to represent T cell vascular transportation during tumor immunotherapy. The reported innovative vessel-tumor platform is believed to have the potential to explore the tumor-induced immune response mechanism and preclinically evaluate immunotherapy's effectiveness.

Detection of MicroRNAs Using Synthetic Toehold Switch in Mammalian Cells.

Engineering synthetic gene circuits to control cellular functions has a broad application in the field of synthetic biology. Synthetic RNA-based switches that can operate at the transcriptional and posttranscriptional level have also drawn significant interest for the application of next-generation therapeutics and diagnostics. Thus, RNA-based switchable platforms are needed to report dynamic cellular mechanisms which play an important role in cell development and diseases. Recently, several RNA-based switches have been designed and utilized for biosensing and molecular diagnostics. However, miRNA-based switches have not been well established or characterized, especially for eukaryotic translational control. Here, we designed a novel synthetic toehold switch for detection of exogenously and endogenously expressed miRNAs in CHO, HeLa, HEK 293, and MDA-MB-231 breast cancer cells. Multiplex detection of miR-155 and miR-21 was tested using two toehold switches to evaluate the orthogonality and programmability of this synthetic platform.

GGC expansions in NOTCH2NLC contribute to Parkinson disease and dopaminergic neuron degeneration.

BACKGROUND AND PURPOSE: The role of GGC repeat expansions within NOTCH2NLC in Parkinson's disease (PD) and the substantia nigra (SN) dopaminergic neuron remains unclear. Here, we profile the NOTCH2NLC GGC repeat expansions in a large cohort of patients with PD. We also investigate the role of GGC repeat expansions within NOTCH2NLC in the dopaminergic neurodegeneration of SN. METHODS: A total of 2,522 patients diagnosed with PD and 1,085 health controls were analyzed for the repeat expansions of NOTCH2NLC by repeat-primed PCR and GC-rich PCR assay. Furthermore, the effects of GGC repeat expansions in NOTCH2NLC on dopaminergic neurons were investigated by using recombinant adeno-associated virus (AAV)-mediated overexpression of NOTCH2NLC with 98 GGC repeats in the SN of mice by stereotactic injection. RESULTS: Four PD pedigrees (4/333, 1.2%) and three sporadic PD patients (3/2189, 0.14%) were identified with pathogenic GGC repeat expansions (larger than 60 GGC repeats) in the NOTCH2NLC gene, while eight PD patients and one healthy control were identified with intermediate GGC repeat expansions ranging from 41 to 60 repeats. No significant difference was observed in the distribution of intermediate NOTCH2NLC GGC repeat expansions between PD cases and controls (Fisher's exact test p-value = 0.29). Skin biopsy showed P62-positive intranuclear NOTCH2NLC-polyGlycine (polyG) inclusions in the skin nerve fibers of patient. Expanded GGC repeats in NOTCH2NLC produced widespread intranuclear and perinuclear polyG inclusions, which led to a severe loss of dopaminergic neurons in the SN. Consistently, polyG inclusions were presented in the SN of EIIa-NOTCH2NLC-(GGC)98 transgenic mice and also led to dopaminergic neuron loss in the SN. CONCLUSIONS: Overall, our findings provide strong evidence that GGC repeat expansions within NOTCH2NLC contribute to the pathogenesis of PD and cause degeneration of nigral dopaminergic neurons.

Microfluidic Droplet-Assisted Fabrication of Vessel-Supported Tumors for Preclinical Drug Discovery.

High-fidelity in vitro tumor models are important for preclinical drug discovery processes. Currently, the most commonly used model for in vitro drug testing remains the two-dimensional (2D) cell monolayer. However, the natural in vivo tumor microenvironment (TME) consists of extracellular matrix (ECM), supporting stromal cells and vasculature. They not only participate in the progression of tumors but also hinder drug delivery and effectiveness on tumor cells. Here, we report an integrated engineering system to generate vessel-supported tumors for preclinical drug screening. First, gelatin-methacryloyl (GelMA) hydrogel was selected to mimic tumor extracellular matrix (ECM). HCT-116 tumor cells were encapsulated into individual micro-GelMA beads with microfluidic droplet technique to mimic tumor-ECM interactions in vitro. Then, normal human lung fibroblasts were mingled with tumor cells to imitate the tumor-stromal interaction. The tumor cells and fibroblasts reconstituted in the individual GelMA microbead and formed a biomimetic heterotypic tumor model with a core-shell structure. Next, the cell-laden beads were consociated into a functional on-chip vessel network platform to restore the tumor-tumor microenvironment (TME) interaction. Afterward, the anticancer drug paclitaxel was tested on the individual and vessel-supported tumor models. It was demonstrated that the blood vessel-associated TME conferred significant additional drug resistance in the drug screening experiment. The reported system is expected to enable the large-scale fabrication of vessel-supported heterotypic tumor models of various cellular compositions. It is believed to be promising for the large-scale fabrication of biomimetic in vitro tumor models and may be valuable for improving the efficiency of preclinical drug discovery processes.

Subtyping of early-onset Parkinson's disease using cluster analysis: A large cohort study.

Background: Increasing evidence suggests that early-onset Parkinson's disease (EOPD) is heterogeneous in its clinical presentation and progression. Defining subtypes of EOPD is needed to better understand underlying mechanisms, predict disease course, and eventually design more efficient personalized management strategies. Objective: To identify clinical subtypes of EOPD, assess the clinical characteristics of each EOPD subtype, and compare the progression between EOPD subtypes. Materials and methods: A total of 1,217 patients were enrolled from a large EOPD cohort of the Parkinson's Disease & Movement Disorders Multicenter Database and Collaborative Network in China (PD-MDCNC) between January 2017 and September 2021. A comprehensive spectrum of motor and non-motor features were assessed at baseline. Cluster analysis was performed using data on demographics, motor symptoms and signs, and other non-motor manifestations. In 454 out of total patients were reassessed after a mean follow-up time of 1.5 years to compare progression between different subtypes. Results: Three subtypes were defined: mild motor and non-motor dysfunction/slow progression, intermediate and severe motor and non-motor dysfunction/malignant. Compared to patients with mild subtype, patients with the severe subtype were more likely to have rapid eye movement sleep behavior disorder, wearing-off, and dyskinesia, after adjusting for age and disease duration at baseline, and showed a more rapid progression in Unified Parkinson's Disease Rating Scale (UPDRS) total score (P = 0.002), UPDRS part II (P = 0.014), and III (P = 0.001) scores, Hoehn and Yahr stage (P = 0.001), and Parkinson's disease questionnaire-39 item version score (P = 0.012) at prospective follow-up. Conclusion: We identified three different clinical subtypes (mild, intermediate, and severe) using cluster analysis in a large EOPD cohort for the first time, which is important for tailoring therapy to individuals with EOPD.

Probing Notch1-Dll4 signaling in regulating osteogenic differentiation of human mesenchymal stem cells using single cell nanobiosensor.

Human mesenchymal stem cells (hMSCs) have great potential in cell-based therapies for tissue engineering and regenerative medicine due to their self-renewal and multipotent properties. Recent studies indicate that Notch1-Dll4 signaling is an important pathway in regulating osteogenic differentiation of hMSCs. However, the fundamental mechanisms that govern osteogenic differentiation are poorly understood due to a lack of effective tools to detect gene expression at single cell level. Here, we established a double-stranded locked nucleic acid (LNA)/DNA (LNA/DNA) nanobiosensor for gene expression analysis in single hMSC in both 2D and 3D microenvironments. We first characterized this LNA/DNA nanobiosensor and demonstrated the Dll4 mRNA expression dynamics in hMSCs during osteogenic differentiation. By incorporating this nanobiosensor with live hMSCs imaging during osteogenic induction, we performed dynamic tracking of hMSCs differentiation and Dll4 mRNA gene expression profiles of individual hMSC during osteogenic induction. Our results showed the dynamic expression profile of Dll4 during osteogenesis, indicating the heterogeneity of hMSCs during this dynamic process. We further investigated the role of Notch1-Dll4 signaling in regulating hMSCs during osteogenic differentiation. Pharmacological perturbation is applied to disrupt Notch1-Dll4 signaling to investigate the molecular mechanisms that govern osteogenic differentiation. In addition, the effects of Notch1-Dll4 signaling on hMSCs spheroids differentiation were also investigated. Our results provide convincing evidence supporting that Notch1-Dll4 signaling is involved in regulating hMSCs osteogenic differentiation. Specifically, Notch1-Dll4 signaling is active during osteogenic differentiation. Our results also showed that Dll4 is a molecular signature of differentiated hMSCs during osteogenic induction. Notch inhibition mediated osteogenic differentiation with reduced Alkaline Phosphatase (ALP) activity. Lastly, we elucidated the role of Notch1-Dll4 signaling during osteogenic differentiation in a 3D spheroid model. Our results showed that Notch1-Dll4 signaling is required and activated during osteogenic differentiation in hMSCs spheroids. Inhibition of Notch1-Dll4 signaling mediated osteogenic differentiation and enhanced hMSCs proliferation, with increased spheroid sizes. Taken together, the capability of LNA/DNA nanobiosensor to probe gene expression dynamics during osteogenesis, combined with the engineered 2D/3D microenvironment, enables us to study in detail the role of Notch1-Dll4 signaling in regulating osteogenesis in 2D and 3D microenvironment. These findings will provide new insights to improve cell-based therapies and organ repair techniques.

The association between LIN28A gene rare variants and Parkinson's disease in Chinese population.

Parkinson's disease (PD) is a neurodegenerative disease caused by aging, environmental and genetic factors, and many susceptibility genes have been found to increase the risk for PD. Lin28a, an RNA binding protein, is expressed prominently in neural progenitor cells. The expression of Lin28a is decreased gradually with neural differentiation and is implicated in oncogenesis, glucose metabolism, neurogenesis, and neurogliogenesis. However, few genetic studies have explored the association between rare variants of the LIN28A gene and PD yet. Our study recruited 3,879 PD patients and 2,931 controls, and they were divided into two cohorts, including the EOPD & FPD cohort and the LOPD cohort, separately sequenced by whole-exome sequencing and whole-genome sequencing. We found nine rare nonsynonymous variants in the coding region of the LIN28A gene, but the rare variants of this gene were not enriched in PD patients in both cohorts. Thence, our study did not support the association between the LIN28A gene and the PD risk in the Chinese mainland population.

Performance comparison of computational methods for the prediction of the function and pathogenicity of non-coding variants.

Non-coding variants in the human genome significantly influence human traits and complex diseases via their regulation and modification effects. Hence, an increasing number of computational methods are developed to predict the effects of variants in human non-coding sequences. However, it is difficult for inexperienced users to select appropriate computational methods from dozens of available methods. To solve this issue, we assessed 12 performance metrics of 24 methods on four independent non-coding variant benchmark datasets: (1) rare germline variants from clinical relevant sequence variants (ClinVar), (2) rare somatic variants from catalogue of somatic mutations in cancer (COSMIC), (3) common regulatory variants from curated expression quantitative trait loci (eQTL) data, and (4) disease-associated common variants from curated genome-wide association studies (GWAS). All 24 tested methods performed differently under various conditions, indicating varying strengths and weaknesses under different scenarios. Importantly, the performance of existing methods was acceptable for rare germline variants from ClinVar with the area under the curve (AUC) of 0.4481-0.8033 and poor for rare somatic variants from COSMIC (AUC: 0.4984-0.7131), common regulatory variants from curated eQTL data (AUC: 0.4837-0.6472), and disease-associated common variants from curated GWAS (AUC: 0.4766-0.5188). We also compared the prediction performance of 24 methods for non-coding de novo mutations in autism spectrum disorder and found that the combined annotation-dependent depletion (CADD) and context-dependent tolerance score (CDTS) methods showed better performance. Summarily, we assessed the performance of 24 computational methods under diverse scenarios, providing preliminary advice for proper tool selection, guiding the development of new techniques in interpreting non-coding variants.

Anthocyanin stability and degradation in plants.

Anthocyanins, a flavonoid group of polyphenolic compounds, have evolved in plants since the land was colonized by plants. These bioactive compounds play critical roles in diverse physiological processes. They are synthesized in the cytosol and transported into the vacuole for storage or to other destinations, where they function as bioactive molecules. The mechanisms of anthocyanin synthesis and transport have been well studied. However, the precise regulation of the mechanisms of anthocyanin degradation remains to be elucidated. In this review, we highlight recent progress in the understanding of the characteristics and functions of anthocyanins and class III peroxidases, as well as of the existing evidence of the effects of class III peroxidases on the degradation of anthocyanins and the possible regulatory mechanisms involved.

Assessment of the association between NUS1 variants and essential tremor.

BACKGROUND: A recent study on early onset Parkinson's disease (PD) revealed that NUS1 is a risk gene for PD. Clinically, essential tremor (ET) is closely related to PD. In this study, we aimed to detect NUS1 variants and assess the effect of those variants on patients with ET. METHODS: The 5 coding regions and the exon-intron boundaries of NUS1 were directly sequenced in 395 patients with ET and an equal number of healthy controls, matched for age and sex. The function of variants was assessed by pathogenic predictive software programs. Genetic analysis of variants was used to evaluate susceptibility to ET. RESULTS: A total of 6 exonic variants were identified, including 3 synonymous and 3 missense variants. The non-synonymous variants were predicted to be tolerable. No variants had significant association with ET (none of the p-values were less than 0.05, using Fisher's exact test). CONCLUSION: Our study suggested that NUS1 variants may not contribute to the risk of ET.

Development and Application of Aptamer-Based Surface-Enhanced Raman Spectroscopy Sensors in Quantitative Analysis and Biotherapy.

Surface-enhanced Raman scattering (SERS) is one of the most special and important Raman techniques. An apparent Raman signal can be observed when the target molecules are absorbed onto the surface of the SERS substrates, especially on the "hot spots" of the substrates. Early research focused on exploring the highly active SERS substrates and their detection applications in label-free SERS technology. However, it is a great challenge to use these label-free SERS sensors for detecting hydrophobic or non-polar molecules, especially in complex systems or at low concentrations. Therefore, antibodies, aptamers, and antimicrobial peptides have been used to effectively improve the target selectivity and meet the analysis requirements. Among these selective elements, aptamers are easy to use for synthesis and modifications, and their stability, affinity and specificity are extremely good; they have been successfully used in a variety of testing areas. The combination of SERS detection technology and aptamer recognition ability not only improved the selection accuracy of target molecules, but also improved the sensitivity of the analysis. Variations of aptamer-based SERS sensors have been developed and have achieved satisfactory results in the analysis of small molecules, pathogenic microorganism, mycotoxins, tumor marker and other functional molecules, as well as in successful photothermal therapy of tumors. Herein, we present the latest advances of the aptamer-based SERS sensors, as well as the assembling sensing platforms and the strategies for signal amplification. Furthermore, the existing problems and potential trends of the aptamer-based SERS sensors are discussed.

[Progress in genetic research on essential tremor].

Essential tremor (ET) is one of the most common movement disorders. Its clinical manifestations not only include typical kinetic and/or postural tremors, but also other non-motor symptoms such as cognitive dysfunction, sleep disturbance, and dysosmia. The exact etiology and pathogenesis of ET is still unknown. Approximately 60% of ET patients have a family history, and genetic factor plays an important role in the onset of the disease. Researchers have so far identified 3 genetic loci (ETM 1-3) through family studies, and proposed additional causative genes such as FUS, HTRA2, TENM4, NOS3 and susceptibility genes such as LINGO, SLC1A2, and GABA. This review focuses on the progress made in genetic research on ET.