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Tortuous microvessels are characteristic of microvascular remodeling associated with numerous physiological and pathological scenarios. Three‐dimensional (3D) hemodynamics in tortuous microvessels influenced by red blood cells (RBCs), however, are largely unknown, and important questions remain. Is blood viscosity influenced by vessel tortuosity? How do RBC dynamics affect wall shear stress (WSS) patterns and the near‐wall cell‐free layer (CFL) over a range of conditions? The objective of this work was to parameterize hemodynamic characteristics unique to a tortuous microvessel.

RBC‐resolved simulations were performed using an immersed boundary method‐based 3D fluid dynamics solver. A representative tortuous microvessel was selected from a stimulated angiogenic network obtained from imaging of the rat mesentery and digitally reconstructed for the simulations. The representative microvessel was a venule with a diameter of approximately 20 μm. The model assumes a constant diameter along the vessel length and does not consider variations due to endothelial cell shapes or the endothelial surface layer.

Microvessel tortuosity was observed to increase blood apparent viscosity compared to a straight tube by up to 26%. WSS spatial variations in high curvature regions reached 23.6 dyne/cm²over the vessel cross‐section. The magnitudes of WSS and CFL thickness variations due to tortuosity were strongly influenced by shear rate and negligibly influenced by tube hematocrit levels.

New findings from this work reveal unique tortuosity‐dependent hemodynamic characteristics over a range of conditions. The results provide new thought‐provoking information to better understand the contribution of tortuous vessels in physiological and pathological processes and help improve reduced‐order models.

 

Circadian rhythms play a vital role in maintaining a person’s well-being but remain difficult to quantify accurately. Numerous approaches exist to measure these rhythms, but they often suffer from performance issues on the individual level. This work implements a Steady-State Kalman Filter as a method for estimating the circadian phase shifts from biometric signals. Our framework can automatically fit the filter’s parameters to biometric data obtained for each individual, and we were able to consistently estimate the phase shift within 1 hour of melatonin estimates on 100% of all subjects in this study. The estimation method opens up the possibility of real-time control and assessment of the circadian system, as well as chronotherapeutic intervention. 

Solar flares not only pose risks to outer space technologies and astronauts’ well being, but also cause disruptions on earth to our high-tech, interconnected infrastructure our lives highly depend on. While a number of machine-learning methods have been proposed to improve flare prediction, none of them, to the best of our knowledge, have investigated the impact of outliers on the reliability and robustness of those models’ performance. In this study, we investigate the impact of outliers in a multivariate time series benchmark dataset, namely SWAN-SF, on flare prediction models, and test our hypothesis. That is, there exist outliers in SWAN-SF, removal of which enhances the performance of the prediction models on unseen datasets. We employ Isolation Forest to detect the outliers among the weaker flare instances. Several experiments are carried out using a large range of contamination rates which determine the percentage of present outliers. We assess the quality of each dataset in terms of its actual contamination using TimeSeriesSVC. In our best findings, we achieve a 279% increase in True Skill Statistic and 68% increase in Heidke Skill Score. The results show that overall a significant improvement can be achieved for flare prediction if outliers are detected and removed properly. 

For drug discovery, new in vitro cancer models are needed to obtain more translatable study outcomes in a low-cost and high-throughput manner. For this purpose, 3D cancer spheroids have been established as more effective than 2D models. Current commercial techniques, however, rely heavily on self-aggregation of dissociated cells and cannot replicate key features of the native tumor microenvironment, particularly due to a lack of control over extracellular matrix components and heterogeneity in size and aggregate-forming tendencies. Also, current spheroidal techniques are typically limited to one spheroid per well, therefore providing a narrow range of cell numbers per well, disadvantageous for assay development in drug screening. Here, we overcome these challenges by coupling tissue engineering toolsets with microfluidic technologies to create engineered cancer microspheres and sorting desired numbers of microspheres into assay-ready well-plate format. To form the engineered cancer microspheres, MCF7 (non-metastatic) and MDA-MB-231 (metastatic) breast cancer cells were encapsulated within poly(ethylene glycol)-fibrinogen hydrogels using our previously developed microfluidic platform. Highly uniform cancer microspheres (intra and inter-batch coefficient of variation ≤ 5%) with high cell densities (over 20 × 106 cells/ml) were produced rapidly, which is critical for use in drug testing. The microspheres supported the 3D culture of both breast cancer cell lines over at least 14 days in culture. Encapsulated cells displayed cell type-specific differences in morphology, proliferation, metabolic activity, ultrastructure, and overall microsphere size distribution and bulk stiffness. To prepare assay-ready pre-plated microspheres, a COPAS FP flow cytometer was used for its ability to analyze and sort large sample particles such as tumor spheroids and hydrogel cancer microspheres generated in this study. When using a 96-well plate, the sorting rate varied from 2.5 - 6 microspheres per second, depending on the sample concentration. When sorting a desired number of microspheres per well, the accuracy was greater than 95% as verified visually by microscopy. Viability of sorted microspheres was verified 24 hours post-sort. Shipping conditions were established that maintained cell viability for remote use in drug testing. Methods for compound addition by pinning and imaging were tested and optimized. Using these approaches, the microsphere system was shown to be compatible with an automated liquid handling system for administration of drug compounds; MDA-MB-231 microspheres were distributed in 384 well plates and treated with chemotherapeutic drugs. Expected responses were quantitated using CellTiter-Glo® 3D and detected using automated imaging. Overall, our results demonstrate initial applicability for the tissue-engineered cancer microspheres for drug screening. 

Abstract There is a need for new in vitro systems that enable pharmaceutical companies to collect more physiologically-relevant information on drug response in a low-cost and high-throughput manner. For this purpose, three-dimensional (3D) spheroidal models have been established as more effective than two-dimensional models. Current commercial techniques, however, rely heavily on self-aggregation of dissociated cells and are unable to replicate key features of the native tumor microenvironment, particularly due to a lack of control over extracellular matrix components and heterogeneity in shape, size, and aggregate forming tendencies. In this study, we overcome these challenges by coupling tissue engineering toolsets with microfluidics technologies to create engineered cancer microspheres. Specifically, we employ biosynthetic hydrogels composed of conjugated poly(ethylene glycol) (PEG) and fibrinogen protein (PEG-Fb) to create engineered breast and colorectal cancer tissue microspheres for 3D culture, tumorigenic characterization, and examination of potential for high-throughput screening (HTS). MCF7 and MDA-MB-231 cell lines were used to create breast cancer microspheres and the HT29 cell line and cells from a stage II patient-derived xenograft (PDX) were encapsulated to produce colorectal cancer (CRC) microspheres. Using our previously developed microfluidic system, highly uniform cancer microspheres (intra-batch coefficient of variation (CV) ≤ 5%, inter-batch CV < 2%) with high cell densities (>20×106 cells/ml) were produced rapidly, which is critical for use in drug testing. Encapsulated cells maintained high viability and displayed cell type-specific differences in morphology, proliferation, metabolic activity, ultrastructure, and overall microsphere size distribution and bulk stiffness. For PDX CRC microspheres, the percentage of human (70%) and CRC (30%) cells was maintained over time and similar to the original PDX tumor, and the mechanical stiffness also exhibited a similar order of magnitude (103 Pa) to the original tumor. The cancer microsphere system was shown to be compatible with an automated liquid handling system for administration of drug compounds; MDA-MB-231 microspheres were distributed in 384 well plates and treated with staurosporine (1 μM) and doxorubicin (10 μM). Expected responses were quantified using CellTiter-Glo® 3D, demonstrating initial applicability to HTS drug discovery. PDX CRC microspheres were treated with Fluorouracil (5FU) (10 to 500 μM) and displayed a decreasing trend in metabolic activity with increasing drug concentration. Providing a more physiologically relevant tumor microenvironment in a high-throughput and low-cost manner, the PF hydrogel-based cancer microspheres could potentially improve the translational success of drug candidates by providing more accurate in vitro prediction of in vivo drug efficacy. Citation Format: Elizabeth A. Lipke, Wen J. Seeto, Yuan Tian, Mohammadjafar Hashemi, Iman Hassani, Benjamin Anbiah, Nicole L. Habbit, Michael W. Greene, Dmitriy Minond, Shantanu Pradhan. Production of cancer tissue-engineered microspheres for high-throughput screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 175. 

Weak measurement (WM) with state pre- and post-selection can amplify otherwise undetectable small signals and thus has potential in precision measurement applications. Although frequency measurements offer the hitherto highest precision due to the stable narrow atomic transitions, it remains a long-standing interest to develop new schemes to further escalate their performance. Here, we demonstrate a WM-enhanced correlation spectroscopy technique capable of narrowing the resonance linewidth down to 0.1 Hz in a room-temperature atomic vapour cell. The potential of this technique for precision measurement is demonstrated through weak magnetic-field sensing. By judiciously pre- and post-selecting frequency-modulated input and output optical states in a nearly orthogonal manner, a sensitivity of 7 fT Hz^(−1/2) at a low frequency near DC is achieved using only one laser beam with 15 µW of power. Additionally, our results extend the WM framework to a non-Hermitian Hamiltonian and shed new light on metrology and bio-magnetic field sensing.