Genetic screening and multipotency in rhesus monkey haploid neural progenitor cells.

Haploid embryonic stem cells (haESCs) have been extensively applied in forward and reverse genetic screening. However, a mammalian haploid somatic cell line is difficult to achieve because of spontaneous diploidization in differentiation. As a non-human primate species, monkeys are widely used in basic and pre-clinical research in which haploid cells are restricted to ESCs. Here, we report that rhesus monkey haESCs in an optimized culture medium show naïve-state pluripotency and stable haploidy. This model facilitated the derivation of haploid neural progenitor cells (haNPCs), which maintained haploidy and differentiation potential into neurons and glia for a long period in vitro High-throughput trapping mutations can be efficiently introduced into haNPCs via piggyBac transposons. This system proves useful when identifying gene targets of neural toxicants via a proof-of-concept experiment. Using CRISPR/Cas9 editing, we confirmed that B4GALT6, from the candidate gene list, is a resistance gene of A803467 (a tetrodotoxin-like toxicant). This model is the first non-human primate haploid somatic cell line with proliferative ability, multipotency and an intact genome, thus providing a cellular resource for recessive genetic and potential drug screening.

Repolarization of myeloid derived suppressor cells via magnetic nanoparticles to promote radiotherapy for glioma treatment.

Although radiotherapy has been established as a major therapeutic modality for glioma, radical new avenues are critically needed to prevent inevitable tumor recurrence. Herein, we utilized a magnetic nanoparticle-based platform with cationic polymer modification to promote radiotherapy for glioma treatment. We found that the nanoplatform induced cytotoxicity to glioma cells under radiation as well as promoting significant survival benefits in both immunocompetent and aythmic mice with glioma. Utilizing the magnetic properties of the nanoparticles, we were able to ascertain that myeloid derived suppressor cells (MDSC) were taking up nanoparticles in the brain tumor. The observed efficacy was attributed to destruction of glioma cells as well as MDSCs repolarization from immunosuppressive phenotype to a pro-inflammatory phenotype, which promoted antitumor effects and synergistically promoted radio-therapeutic effects. Our nanoparticles provide a robust dual-targeting platform for glioma radiotherapy by simultaneous eradication of tumor cells and manipulation of myeloid phenotypes in the central nervous system.

Nanobiocatalysts with inbuilt cofactor recycling for oxidoreductase catalysis in organic solvents.

The major stumbling block in the implementation of oxidoreductase enzymes in continuous processes is their stark dependence on costly cofactors that are insoluble in organic solvents. We describe a chemical strategy that allows producing nanobiocatalysts, based on an oxidoreductase enzyme, that performs biocatalytic reactions in hydrophobic organic solvents without external cofactors. The chemical design relies on the use of a silica-based carrier nanoparticle, of which the porosity can be exploited to create an aqueous reservoir containing the cofactor. The nanoparticle core, possessing radial-centred pore channels, serves as a cofactor reservoir. It is further covered with a layer of reduced porosity. This layer serves as a support for the immobilisation of the selected enzyme yet allowing the diffusion of the cofactor from the nanoparticle core. The immobilised enzyme is, in turn, shielded by an organosilica layer of controlled thickness fully covering the enzyme. Such produced nanobiocatalysts are shown to catalyse the reduction of a series of relevant ketones into the corresponding secondary alcohols, also in a continuous flow fashion.

Personalized State Anxiety Detection: An Empirical Study with Linguistic Biomarkers and A Machine Learning Pipeline.

Individuals high in social anxiety symptoms often exhibit elevated state anxiety in social situations. Research has shown it is possible to detect state anxiety by leveraging digital biomarkers and machine learning techniques. However, most existing work trains models on an entire group of participants, failing to capture individual differences in their psychological and behavioral responses to social contexts. To address this concern, in Study 1, we collected linguistic data from N=35 high socially anxious participants in a variety of social contexts, finding that digital linguistic biomarkers significantly differ between evaluative vs. non-evaluative social contexts and between individuals having different trait psychological symptoms, suggesting the likely importance of personalized approaches to detect state anxiety. In Study 2, we used the same data and results from Study 1 to model a multilayer personalized machine learning pipeline to detect state anxiety that considers contextual and individual differences. This personalized model outperformed the baseline's F1-score by 28.0%. Results suggest that state anxiety can be more accurately detected with personalized machine learning approaches, and that linguistic biomarkers hold promise for identifying periods of state anxiety in an unobtrusive way.

circadian rhythms are not captured equal: Exploring Circadian metrics extracted by differentcomputational methods from smartphone accelerometer and GPS sensors in daily life tracking.

Objective: To identify the differences between circadian rhythm (CR) metrics characterized by different mobile sensors and computational methods. Methods: We used smartphone tracking and daily survey data from 225 college student participants, applied four methods (survey construct automation, cosinor regression, non-parametric method, Fourier analysis) on two types of smartphone sensor data (GPS, accelerometer) to characterize CR. We explored the inter-relations among the extracted circadian metrics as well as between the circadian metrics and participants' self-reported mood and sleep outcomes. Results: Compared to GPS signals, smartphone accelerometer activity follows an intradaily distribution that starts earlier in the day, winds down later, reaches half cumulative activity about the same time, conforms less to a sinusoidal wave, and exhibits more intradaily fragmentation but higher CR strength and lower interdaily disruption. We found a notable negative correlation between intradaily variability and CR strength especially pronounced in GPS activity. Self-reported sleep and mood outcomes showed significant correlations with particular CR metrics. Conclusions: We revealed significant inter-relations and discrepancies in the circadian metrics discovered from two smartphone sensors and four CR algorithms and their bearings on wellbeing indicators such as sleep quality and loneliness.

Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: A GPS-Focused Smartphone Sensing Study.

With the outbreak of the COVID-19 pandemic in 2020, most colleges and universities move to restrict campus activities, reduce indoor gatherings and move instruction online. These changes required that students adapt and alter their daily routines accordingly. To investigate patterns associated with these behavioral changes, we collected smartphone sensing data using the Beiwe platform from two groups of undergraduate students at a major North American university, one from January to March of 2020 (74 participants), the other from May to August (52 participants), to observe the differences in students' daily life patterns before and after the start of the pandemic. In this paper, we focus on the mobility patterns evidenced by GPS signal tracking from the students' smartphones and report findings using several analytical methods including principal component analysis, circadian rhythm analysis, and predictive modeling of perceived sadness levels using mobility-based digital metrics. Our findings suggest that compared to the pre-COVID group, students in the mid-COVID group generally 1) registered a greater amount of midday movement than movement in the morning (8-10 a.m.) and in the evening (7-9 p.m.), as opposed to the other way around; 2) exhibited significantly less intradaily variability in their daily movement; 3) visited less places and stayed at home more everyday, and; 4) had a significant lower correlation between their mobility patterns and negative mood.

Multi-modal data collection for measuring health, behavior, and living environment of large-scale participant cohorts.

BACKGROUND: As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users' daily lives with unprecedented comprehensiveness and ecological validity. A number of human-subject studies have been conducted to examine the use of mobile sensing to uncover individual behavioral patterns and health outcomes, yet minimal attention has been placed on measuring living environments together with other human-centered sensing data. Moreover, the participant sample size in most existing studies falls well below a few hundred, leaving questions open about the reliability of findings on the relations between mobile sensing signals and human outcomes. RESULTS: To address these limitations, we developed a home environment sensor kit for continuous indoor air quality tracking and deployed it in conjunction with smartphones, Fitbits, and ecological momentary assessments in a cohort study of up to 1,584 college student participants per data type for 3 weeks. We propose a conceptual framework that systematically organizes human-centric data modalities by their temporal coverage and spatial freedom. Then we report our study procedure, technologies and methods deployed, and descriptive statistics of the collected data that reflect the participants' mood, sleep, behavior, and living environment. CONCLUSIONS: We were able to collect from a large participant cohort satisfactorily complete multi-modal sensing and survey data in terms of both data continuity and participant adherence. Our novel data and conceptual development provide important guidance for data collection and hypothesis generation in future human-centered sensing studies.

Derivation of Haploid Trophoblast Stem Cells via Conversion In Vitro.

Owing to their single genome, haploid cells are powerful to uncover unknown genes by performing genetic screening in mammals. However, no haploid cell line from an extraembryonic lineage has been achieved yet, which limits the application of haploid cells in placental genetic screening. Here, we show that overexpression of Cdx2 can convert haploid embryonic stem cells to trophoblast stem cells (TSCs). p53 deletion reduces diploidization during the conversion and guarantees the generation of haploid-induced TSCs (haiTSCs). haiTSCs not only share the same molecular characterization with trophoderm-derived TSCs but also possess multipotency to placental lineages in various procedures. In addition, haiTSCs can maintain haploidy in the long term, assisted by periodic sorting and with reliance on FGF4 and heparin. Finally, we perform piggyBac-mediated high-throughput mutation in haiTSCs and use them in trophoblast lineage genetic screening. Deep sequencing analysis and validation experiments prove that Htra1 is a blocker for spongiotrophoblast specification.

Recent Advances in Magnetic-Nanomaterial-Based Mechanotransduction for Cell Fate Regulation.

Remote control of cells and the regulation of cell events at the molecular level are of great interest in the biomedical field. In addition to chemical compounds and genes, mechanical forces play a pivotal role in regulating cell fate, which have prompted the rapid growth of mechanobiology. From a perspective of nanotechnology, magnetic nanomaterials (MNs) are an appealing option for mechanotransduction due to their capabilities in spatiotemporal manipulation of mechanical forces via the magnetic field. As a newly developed paradigm, magneto-mechanotransduction is harnessed to physically regulate cell fate for biomedical applications. Here, the critical factors that determine the magnetomechanical forces induced by MNs in mechanotransduction are briefly reviewed. Recent innovative approaches and their underlying mechanisms for controlling cell fate are highlighted, which offer possibilities for the remote mechanical manipulation of cells and biomolecules in a precise manner. Promising applications including regenerative medicine and cancer treatment based on magnetomechanical stimulation through MNs are also addressed. Perspectives and challenges in MN-based mechanotransduction are commented.

Elongated Nanoparticle Aggregates in Cancer Cells for Mechanical Destruction with Low Frequency Rotating Magnetic Field.

Magnetic nanoparticles (MNPs) functionalized with targeting moieties can recognize specific cell components and induce mechanical actuation under magnetic field. Their size is adequate for reaching tumors and targeting cancer cells. However, due to the nanometric size, the force generated by MNPs is smaller than the force required for largely disrupting key components of cells. Here, we show the magnetic assembly process of the nanoparticles inside the cells, to form elongated aggregates with the size required to produce elevated mechanical forces. We synthesized iron oxide nanoparticles doped with zinc, to obtain high magnetization, and functionalized with the epidermal growth factor (EGF) peptide for targeting cancer cells. Under a low frequency rotating magnetic field at 15 Hz and 40 mT, the internalized EGF-MNPs formed elongated aggregates and generated hundreds of pN to dramatically damage the plasma and lysosomal membranes. The physical disruption, including leakage of lysosomal hydrolases into the cytosol, led to programmed cell death and necrosis. Our work provides a novel strategy of designing magnetic nanomedicines for mechanical destruction of cancer cells.

Vacuolization in Cytoplasm and Cell Membrane Permeability Enhancement Triggered by Micrometer-Sized Graphene Oxide.

A deep understanding of the interaction of a graphene oxide (GO) sheet with cells at the molecular level may expedite its biomedical application and predict its new functions and adverse effects. Herein we inspect the interaction between micrometer-sized GO (mGO), commonly used in biomedical research, and cells at the molecular level through a variety of techniques. A major finding is that, instead of direct cellular penetration, the mGO sheets can stimulate the cellular response by interacting with the membrane protein and the membrane. Specifically, it is illustrated that even within a short exposure time the mGO sheets can induce the formation of vacuoles in the cytosolic compartment and enhance the cell permeability. The vacuolization is only observed in the cells that strongly express aquaporin (AQP1), indicating the specific interaction of the mGO with AQP1. Moreover, inhibition of the AQP1 activity prevents the formation of vacuoles, revealing that the interaction of the mGO with AQP1 occurs most probably at the vestibule of AQP1 at the extracellular side. Additionally, though the cell permeability was enhanced, it only improves the penetration of small molecules, not for macromolecules such as proteins. These findings are potentially valuable in cancer therapy because AQPs are strongly expressed in tumor cells of different origins, particularly aggressive tumors, and it will also be beneficial for drug transport across barrier membranes.

Insight into the cellular internalization and cytotoxicity of graphene quantum dots.

Graphene quantum dots (GQDs), owing to their unique morphology, ultra-small lateral sizes, and exceptional properties, hold great promise for many applications, especially in the biomedical field. In this work, the cellular internalization, distribution, and cytotoxicity of the GQDs are explored complementarily using transmission electron microscopy, confocal laser scanning microscopy, UV-vis, and fluorescence spectroscopies, and flow cytometry with human gastric cancer MGC-803 and breast cancer MCF-7 cells. It is demonstrated that the GQDs are internalized primarily through caveolae-mediated endocytosis. The effects of GQDs on the cell viability, internal cellular reactive oxygen species (ROS) level, mitochondrial membranes potential, and cell cycles show that the cytotoxicity of GQDs is lower than that of the micrometer-sized graphene oxide (GO). The low cytotoxicity and size consistence render GQDs appropriate for biomedical application.

Graphene quantum dots/gold electrode and its application in living cell H2O2 detection.

Due to the high peroxidase-like activity and small lateral size of graphene quantum dots (GQDs), the covalently assembled GQDs/Au electrode exhibits great performance and stability in H(2)O(2) detection. It is better or comparable to some enzyme-immobilized electrodes, and thus could be useful in sensing H(2)O(2) changes in biological systems.

Enhancing cell nucleus accumulation and DNA cleavage activity of anti-cancer drug via graphene quantum dots.

Graphene quantum dots (GQDs) maintain the intrinsic layered structural motif of graphene but with smaller lateral size and abundant periphery carboxylic groups, and are more compatible with biological system, thus are promising nanomaterials for therapeutic applications. Here we show that GQDs have a superb ability in drug delivery and anti-cancer activity boost without any pre-modification due to their unique structural properties. They could efficiently deliver doxorubicin (DOX) to the nucleus through DOX/GQD conjugates, because the conjugates assume different cellular and nuclear internalization pathways comparing to free DOX. Also, the conjugates could enhance DNA cleavage activity of DOX markedly. This enhancement combining with efficient nuclear delivery improved cytotoxicity of DOX dramatically. Furthermore, the DOX/GQD conjugates could also increase the nuclear uptake and cytotoxicity of DOX to drug-resistant cancer cells indicating that the conjugates may be capable to increase chemotherapy efficacy of anti-cancer drugs that are suboptimal due to the drug resistance.

A gold nanoshell with a silica inner shell synthesized using liposome templates for doxorubicin loading and near-infrared photothermal therapy.

Gold (Au) nanoshells with solid silica cores have great potential for cancer photothermal therapy. However, this nanostructure cannot carry enough drugs. Here, we report a Au nanoshell with a hollow silica core for drug loading and cancer therapy. The silica shells were synthesized using nanoliposome templates, and then Au nanoshells were grown on the outer surface of the silica shells. Transmission-electron and scanning-electron microscopy showed that the Au nanoshells were successfully fabricated, and that the liposome/SiO(2)/Au core-shell nanocomposites were spherical with a narrow size distribution. Images of several broken spheres, and the fact that hollow templates (liposomes) were used, suggest that the fabricated Au nanoshells were hollow. After doxorubicin (DOX) was incorporated into liposome/SiO(2)/Au, the DOX-loaded Au nanoshells killed cancer cells with high therapeutic efficacy when irradiated with near-infrared light, suggesting that the Au nanoshells delivered both DOX chemotherapy and photothermal therapy with a synergistic effect.