Single-cell Functional Profiling of Lymphocytes for Cancer Immunotherapy

Immunotherapy by harnessing patients’ the immune system has changed the landscape of cancer therapeutics and shown promising and remarkable clinical responses. However, not all the patients would be beneficial from the treatment. Lymphocytes are a significant target in anti-tumor immunotherapy, and the functional assessment of lymphocytes will provide insights on their functional biology and will provide a direct path to the improvement of the treatment efficacy. In the first part of this dissertation, we developed and implemented a methodology based on Timelapse Imaging Microscopy in Nanowell Grids (TIMING) platform that integrates phenotypic profiling and dynamic cytokine secretion with single-cell resolution. Analysis of hundreds of human peripheral nature killer cells (NK cells) suggested that CD56dimCD16+ NK cells are immediate interferon gamma (IFN-γ) secretor upon activation by phorbol 12-myristate 13-acetate (PMA) and ionomycin (< 3 h), and no evidence of cooperation between NK cells to synergistic activation or faster IFN-γ secretion. These results establish our technology as an investigational tool for cellular phenotyping and real-time protein secretion of individual cells in a high-throughput manner and demonstrate that the conventional phenotypic based functional annotation of NK cells might be overly simplistic. In the second part of this dissertation, we performed whole transcriptomic profiling on T cells from acute myeloid leukemia patients (responders and non-responders) who were treated with combination therapy of a hypomethylating agent (5-azacytidine) and an immune checkpoint inhibitor (nivolumab, programmed cell death protein 1/PD-1 inhibitor). Sixty-four patient-derived T cells from peripheral blood or bone marrow (site of disease), which were collected before the initiation of the therapy (baseline, T0) and after the first round of treatment (end of cycle one, EC1), were evaluated. Our results demonstrate (1) treatment-induced gene expression changes on circulating CD8 T cells, and (2) the ratios of effector and exhausted CD8 T cells has the potential to serve as a biomarker for patient stratification.Chemical and Biomolecular Engineering, Department o

The Behavior of a Multi-Story Steel Frame Subject to Measured Fire Using Calibrated Simple Approach

Structural steels are one of the most popular construction materials with a number of merits, such as cost-effectiveness, durability, lightweight, versatility, etc. However, when exposed to a high temperature, their thermal expansion rate is high and the strength reduces substantially, making the steel structures vulnerable to fire. So far, a number of studies have been performed to understand the behavior of steel in fire. Rigorous tests, from the material to structural level, have led the advancement of modeling techniques. Among various analytical techniques, one of the most widely used approaches is the finite element modeling (FEM). While FEM can demonstrate geometrical and material nonlinearities, due to the complexity, the approach may result in high computational loads to ensure the convergence. Thus, in this paper, a simple calculation method is instead used to understand the steel frame subject to fire, in conjunction with experimentally collected temperature and displacement data. Then, at each temperature (before and after critical temperature and the formation of plastic hinges), the effect of elevated temperature on global behavior is examined using frame analysis. Results of the study have demonstrated that when structural integrity is of concern, the critical temperature of the structure must be examined in terms of fundamental characteristics of the structure

Predicting the influence of microblog entries regarding public health emergencies

Predicting the influence of microblog entries regarding public health emergencies can help management departments improve the prospectiveness of decision making. In this study, we measure the influence of microblog entries regarding public health emergencies from their forwarding, comment and favorite counts. A microblog influence prediction model, which is comprised of user, time and content features, is proposed by using the random forest method and the BM25 Latent Dirichlet Allocation model (LDA-BM25). Microblog entries on the Ebola outbreak are selected as test data. Results reveal that the proposed model can accurately predict the influence of microblog entries regarding public health emergencies with the accuracy rate reaching 88.8%. Individual features, which play a role in the influence of microblog entries, and their influence inclination are also analyzed. The findings of the study can help management departments of public health emergencies predict the upcoming salient issues, and take appropriate measures in advance

Simulating Wind Disturbances over Rubber Trees with Phenotypic Trait Analysis Using Terrestrial Laser Scanning

Hurricanes often devastate trees throughout coastal China; accordingly, developing a method to quantitatively evaluate the changes in tree phenotypic characteristics under continuous strong winds is of great significance for guiding forest cultivation practices and mitigating wind hazards. For this research, we built a lifting steel truss carrying a large forced draft fan near a rubber plantation on Hainan Island, and we aligned three selected small rubber trees in a row in front of the fan (with separation distances from the forced draft fan outlet of approximately 1.3, 3.3, and 5.3 m) to explore the susceptibility of rubber trees to the mechanical loading of hurricane-level winds. By adjusting the power of the forced draft fan, four wind speeds were emitted: 0 m/s, 10.5 m/s, 13.5 m/s, and 17.5 m/s. Meanwhile, point clouds of the three rubber trees under different continuous wind speeds were acquired using two terrestrial laser scanners. Computer algorithms were applied to derive the key parameters of the three rubber trees, namely, the zenith and azimuth angles of each leaf, effective leaf area index (LAI), windward area of each tree, volume of the tree canopy, and trunk tilt angle, from these point clouds under all four wind speeds. The results show that by increasing the wind speed from 0 m/s to 17.5 m/s, the leaf zenith angles of the three rubber trees were unimodally distributed with the peak concentrated at 0&deg;, while the leaf azimuth angles were bimodally distributed with the peaks concentrated at 0&deg; and 360&deg;. The effective LAI values of the three trees increased from 2.97, 4.77, and 3.63 (no wind) to 3.84, 5.9, and 4.29 (wind speed of 17.5 m/s), respectively, due to a decrease in the vertical crown projection area caused by the compression of the tree canopy. We also found that the effective LAI, windward area, and canopy volume of the third rubber tree (the tree farthest from the forced draft fan) varied less than those of the other two trees, reflecting the attenuation of the wind speed by the crowns of the two trees closer to the fan. The experimental results also indicate that the joint use of light detection and ranging (LiDAR) data with computer graphics algorithms to analyse the dynamic changes in tree phenotypic characteristics during the passage of a hurricane is promising, enabling the development of a novel strategy for mitigating wind hazards. The proposed method with the designed device capable of producing an adjustable wind speed also has the potential to study the impacts of wind damage under various forest conditions by further modifying the tree spacing and tree species

Simulating Wind Disturbances over Rubber Trees with Phenotypic Trait Analysis Using Terrestrial Laser Scanning

Hurricanes often devastate trees throughout coastal China; accordingly, developing a method to quantitatively evaluate the changes in tree phenotypic characteristics under continuous strong winds is of great significance for guiding forest cultivation practices and mitigating wind hazards. For this research, we built a lifting steel truss carrying a large forced draft fan near a rubber plantation on Hainan Island, and we aligned three selected small rubber trees in a row in front of the fan (with separation distances from the forced draft fan outlet of approximately 1.3, 3.3, and 5.3 m) to explore the susceptibility of rubber trees to the mechanical loading of hurricane-level winds. By adjusting the power of the forced draft fan, four wind speeds were emitted: 0 m/s, 10.5 m/s, 13.5 m/s, and 17.5 m/s. Meanwhile, point clouds of the three rubber trees under different continuous wind speeds were acquired using two terrestrial laser scanners. Computer algorithms were applied to derive the key parameters of the three rubber trees, namely, the zenith and azimuth angles of each leaf, effective leaf area index (LAI), windward area of each tree, volume of the tree canopy, and trunk tilt angle, from these point clouds under all four wind speeds. The results show that by increasing the wind speed from 0 m/s to 17.5 m/s, the leaf zenith angles of the three rubber trees were unimodally distributed with the peak concentrated at 0°, while the leaf azimuth angles were bimodally distributed with the peaks concentrated at 0° and 360°. The effective LAI values of the three trees increased from 2.97, 4.77, and 3.63 (no wind) to 3.84, 5.9, and 4.29 (wind speed of 17.5 m/s), respectively, due to a decrease in the vertical crown projection area caused by the compression of the tree canopy. We also found that the effective LAI, windward area, and canopy volume of the third rubber tree (the tree farthest from the forced draft fan) varied less than those of the other two trees, reflecting the attenuation of the wind speed by the crowns of the two trees closer to the fan. The experimental results also indicate that the joint use of light detection and ranging (LiDAR) data with computer graphics algorithms to analyse the dynamic changes in tree phenotypic characteristics during the passage of a hurricane is promising, enabling the development of a novel strategy for mitigating wind hazards. The proposed method with the designed device capable of producing an adjustable wind speed also has the potential to study the impacts of wind damage under various forest conditions by further modifying the tree spacing and tree species

Single-Cell Cloning of Breast Cancer Cells Secreting Specific Subsets of Extracellular Vesicles

Extracellular vesicles (EVs) mediate communication in health and disease. Conventional assays are limited in profiling EVs secreted from large populations of cells and cannot map EV secretion onto individual cells and their functional profiles. We developed a high-throughput single-cell technique that enabled the mapping of dynamics of EV secretion. By utilizing breast cancer cell lines, we established that EV secretion is heterogeneous at the single-cell level and that non-metastatic cancer cells can secrete specific subsets of EVs. Single-cell RNA sequencing confirmed that pathways related to EV secretion were enriched in the non-metastatic cells compared with metastatic cells. We established isogenic clonal cell lines from non-metastatic cells with differing propensities for CD81+CD63+EV secretion and showed for the first time that specificity in EV secretion is an inheritable property preserved during cell division. Combined in vitro and animal studies with these cell lines suggested that CD81+CD63+EV secretion can impede tumor formation. In human non-metastatic breast tumors, tumors enriched in signatures of CD81+CD63+EV have a better prognosis, higher immune cytolytic activity, and enrichment of pro-inflammatory macrophages compared with tumors with low CD81+CD63+EVs signatures. Our single-cell methodology enables the direct integration of EV secretion with multiple cellular functions and enables new insights into cell/disease biology

Association between multiple comorbidities and self-rated health status in middle-aged and elderly Chinese: the China Kadoorie Biobank study

Abstract Background Understanding the correlates of self-rated health (SRH) can help public health professionals prioritize health-promotion and disease-prevention interventions. This study aimed to investigate the association between multiple comorbidities and global SRH and age-comparative SRH. Methods A total of 512,891 participants aged 30–79 years old were recruited into the China Kadoorie Biobank study from ten regions between 2004 and 2008. Multivariate logistic regression models were used to estimate the odds ratios (ORs) for the associations between comorbidities (including diabetes, hypertension, coronary heart disease, rheumatic heart disease, stroke, tuberculosis, emphysema/bronchitis, asthma, cirrhosis/chronic hepatitis, peptic ulcer, gallbladder disease, kidney disease, fracture, rheumatic arthritis, psychiatric disorders, depressive symptoms, neurasthenia, head injury and cancer) and SRH. Population attributable risks (PARs) were used to estimate the contribution of multiple comorbidities to poor global SRH and worse age-comparative SRH. Results After adjusting for covariates, suffering from various diseases increased the chance of reporting a poor global SRH [OR (95% CI) ranged from 1.10 (1.07, 1.13) for fracture to 3.21 (2.68, 3.83) for rheumatic heart disease] and a worse age-comparative SRH [OR (95% CI) ranged from 1.18 (1.13, 1.23) for fracture to 7.56 (6.93, 8.25) for stroke]. From the population perspective, 20.23% of poor global SRH and 45.12% of worse age-comparative SRH could attributed to the cardiometabolic diseases, with hypertension (7.84% for poor global SRH and 13.79% for worse age-comparative SRH), diabetes (4.35% for poor global SRH and 10.71% for worse age-comparative SRH), coronary heart disease (4.44% for poor global SRH and 9.51% for worse age-comparative SRH) and stroke (3.20% for poor global SRH and 10.19% for worse age-comparative SRH) making the largest contribution. Conclusions Various diseases were major determinants of global and age-comparative SRH, and cardiometabolic diseases had the strongest impact on both global SRH and age-comparative SRH at the population level. Prevention measures concentrated on these conditions would greatly reduce the total burden of poor SRH and its consequences such as poor quality of life and use of health care services

Single-cell profiling of dynamic cytokine secretion and the phenotype of immune cells

<div><p>Natural killer (NK) cells are a highly heterogeneous population of innate lymphocytes that constitute our first line of defense against several types of tumors and microbial infections. Understanding the heterogeneity of these lymphocytes requires the ability to integrate their underlying phenotype with dynamic functional behaviors. We have developed and validated a single-cell methodology that integrates cellular phenotyping and dynamic cytokine secretion based on nanowell arrays and bead-based molecular biosensors. We demonstrate the robust passivation of the polydimethylsiloxane (PDMS)-based nanowells arrays with polyethylene glycol (PEG) and validated our assay by comparison to enzyme-linked immunospot (ELISPOT) assays. We used numerical simulations to optimize the molecular density of antibodies on the surface of the beads as a function of the capture efficiency of cytokines within an open-well system. Analysis of hundreds of individual human peripheral blood NK cells profiled <i>ex vivo</i> revealed that CD56^dimCD16⁺ NK cells are immediate secretors of interferon gamma (IFN-γ) upon activation by phorbol 12-myristate 13-acetate (PMA) and ionomycin (< 3 h), and that there was no evidence of cooperation between NK cells leading to either synergistic activation or faster IFN-γ secretion. Furthermore, we observed that both the amount and rate of IFN-γ secretion from individual NK cells were donor-dependent. Collectively, these results establish our methodology as an investigational tool for combining phenotyping and real-time protein secretion of individual cells in a high-throughput manner.</p></div