Publications by authors named "Adnan Shakoor"

Detecting and segmenting unstained living adherent cells in differential interference contrast (DIC) images is crucial in biomedical research, such as cell microinjection, cell tracking, cell activity characterization, and revealing cell phenotypic transition dynamics. We present a robust approach, starting with dataset transformation. We curated 520 pairs of DIC images, containing 12,198 HepG2 cells, with ground truth annotations.

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Biomaterials and biomedical devices induced life-threatening bacterial infections and other biological adverse effects such as thrombosis and fibrosis have posed a significant threat to global healthcare. Bacterial infections and adverse biological effects are often caused by the formation of microbial biofilms and the adherence of various biomacromolecules, such as platelets, proteins, fibroblasts, and immune cells, to the surfaces of biomaterials and biomedical devices. Due to the programmed interconnected networking of bacteria in microbial biofilms, they are challenging to treat and can withstand several doses of antibiotics.

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Introduction: Kochiae Fructus has been widely used in Chinese Herbal medicine to treat various diseases. We report a rapid and eco-friendly approach for cerium oxide (CeO) nanoparticles (NPs) synthesis using the extract of medicinally important plant "Kochiae Fructus", and the synthesized NPs were named KF-CeO NPs.

Methods: Various spectroscopic approaches such as transmission electron microscope (TEM), powder X-ray diffraction (XRD), and energy-dispersive X-Ray (EDX) were used to characterize the KF-CeO NPs effectively.

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Titanium dioxide (TiO) has emerged as a viable choice for several biological and environmental applications because of its high efficiency, cheap cost, and high photostability. In pursuit of this purpose, the research of its many forms has been influenced by these unique aspects. The development of novel TiO-based hybrid materials with enhanced photocatalytically induced anticancer activity has gained tremendous attention.

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Mitochondrial transfer is a spontaneous process to restore damaged cells in various pathological conditions. The transfer of mitochondria to cell therapy products before their administration can enhance therapeutic outcomes. However, the low efficiency of previously reported methods limits their clinical application.

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Highly precise micromanipulation tools that can manipulate and interrogate cell organelles and components must be developed to support the rapid development of new cell-based medical therapies, thereby facilitating in-depth understanding of cell dynamics, cell component functions, and disease mechanisms. This paper presents a literature review on micro/nanomanipulation tools and their control methods for single-cell surgery. Micromanipulation methods specifically based on laser, microneedle, and untethered micro/nanotools are presented in detail.

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Mitochondrial dysfunction is considered to be an important factor that leads to aging and premature aging diseases. Transferring mitochondria to cells is an emerging and promising technique for the therapy of mitochondrial deoxyribonucleic acid (mtDNA)-related diseases. This paper presents a unique method of controlling the quality and quantity of mitochondria transferred to single cells using an automated optical tweezer-based micromanipulation system.

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Combining patterning coculture technique with microfluidics enables the reconstruction of complex in-vivo system to facilitate in-vitro studies on cell-cell and cell-environment interactions. However, simple and versatile approaches for patterning coculture of cells on microfluidic platforms remain lacking. In this study, a novel gravitational sedimentation-based approach is presented to achieve ultra-simple and flexible cell patterning coculture on a microfluidic platform, where multiple cell types can be patterned simultaneously to form a well-organized cell coculture.

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Single cell surgery such as manipulation or removal of subcellular components or/and organelles from single cells is increasingly used for the study of diseases and their causes in precision medicine. This paper presents a robotic surgery system to achieve automated organelle biopsy of single cells with dimensions of less than 20 μm in diameter. The complexity of spatial detection of the organelle position is reduced by patterning the cells using a microfluidic chip device.

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This article reviews the autonomous manipulation strategies of biological cells utilizing optical tweezers, mainly including optical direct and indirect manipulation strategies. The typical and latest achievements in the optical manipulation of cells are presented, and the existing challenges for autonomous optical manipulation of biological cells are also introduced. Moreover, the integrations of optical tweezers with other manipulation tools are presented, which broadens the applications of optical tweezers in the biomedical manipulation areas and will also foster new developments in cell-based physiology and pathology studies, such as cell migration, single cell surgery, and preimplantation genetic diagnosis (PGD).

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In many cell surgery applications, cell must be oriented properly such that the microsurgery tool can access the target components with minimum damage to the cell. In this paper, a scheme for out of image plane orientation control of suspended biological cells using robotic controlled optical tweezers is presented for orientation-based cell surgery. Based on our previous work on planar cell rotation using optical tweezers, the dynamic model of cell out-of-plane orientation control is formulated by using the T-matrix approach.

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High dimensionality and small sample sizes, and their inherent risk of overfitting, pose great challenges for constructing efficient classifiers in microarray data classification. Therefore a feature selection technique should be conducted prior to data classification to enhance prediction performance. In general, filter methods can be considered as principal or auxiliary selection mechanism because of their simplicity, scalability, and low computational complexity.

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