Death Anxiety During COVID-19 and its Related Factors among Chinese Elderly People.

This study aimed at investigating death anxiety and its related factors in Chinese elderly people during COVID-19. This study totally interviewed 264 participants from four cities in different regions of China. Death anxiety scale (DAS), NEO-Five-Factor Inventory (Neo-FFI) and Brief COPE were scored on the basis of one-on-one interviews. Quarantine experience didn't make significant difference in death anxiety among the elderly; Elderly people with high death anxiety had higher scores of neuroticism, and were more likely to use a Behavior Disengagement coping strategy; Multiple linear regression analysis showed that neuroticism, openness and COVID impact predicted 44.6% of the variance in the death anxiety among elderly people. The results support both theories of vulnerability-stress model and terror management theory (TMT). In the post-epidemic era, we suggest to pay attention to the mental health status of elderly people with personality susceptibility to handling the stress of infection badly.

Feasibility study of stain-free classification of cell apoptosis based on diffraction imaging flow cytometry and supervised machine learning techniques.

This study was to explore the feasibility of prediction and classification of cells in different stages of apoptosis with a stain-free method based on diffraction images and supervised machine learning. Apoptosis was induced in human chronic myelogenous leukemia K562 cells by cis-platinum (DDP). A newly developed technique of polarization diffraction imaging flow cytometry (p-DIFC) was performed to acquire diffraction images of the cells in three different statuses (viable, early apoptotic and late apoptotic/necrotic) after cell separation through fluorescence activated cell sorting with Annexin V-PE and SYTOX® Green double staining. The texture features of the diffraction images were extracted with in-house software based on the Gray-level co-occurrence matrix algorithm to generate datasets for cell classification with supervised machine learning method. Therefore, this new method has been verified in hydrogen peroxide induced apoptosis model of HL-60. Results show that accuracy of higher than 90% was achieved respectively in independent test datasets from each cell type based on logistic regression with ridge estimators, which indicated that p-DIFC system has a great potential in predicting and classifying cells in different stages of apoptosis.

Realistic optical cell modeling and diffraction imaging simulation for study of optical and morphological parameters of nucleus.

Coherent light scattering presents complex spatial patterns that depend on morphological and molecular features of biological cells. We present a numerical approach to establish realistic optical cell models for generating virtual cells and accurate simulation of diffraction images that are comparable to measured data of prostate cells. With a contourlet transform algorithm, it has been shown that the simulated images and extracted parameters can be used to distinguish virtual cells of different nuclear volumes and refractive indices against the orientation variation. These results demonstrate significance of the new approach for development of rapid cell assay methods through diffraction imaging.

Spectrophotometric determination of turbid optical parameters without using an integrating sphere.

Spectrophotometric quantification of turbidity by multiple optical parameters has wide-ranging applications in material analysis and life sciences. A robust system design needs to combine hardware for precise measurement of light signals with software to accurately model measurement configuration and rapidly solve a sequence of challenging inverse problems. We have developed and validated a design approach and performed system validation based on radiative transfer theory for determination of absorption coefficient, scattering coefficient, and anisotropy factor without using an integrating sphere. Accurate and rapid determination of parameters and spectra is achieved for microsphere suspension samples by combining photodiode-based measurement of four signals with the Monte Carlo simulation and perturbation-based inverse calculations. The three parameters of microsphere suspension samples have been determined from the measured signals as functions of wavelength from 400 to 800 nm and agree with calculated results based on the Mie theory. It has been shown that the inverse problems in the cases of microsphere suspension samples are well posed with convex cost functions to yield unique solutions, and it takes about 1 min to obtain the three parameters per wavelength.

Acquisition of cross-polarized diffraction images and study of blurring effect by one time-delay-integration camera.

Blurred diffraction images acquired from flowing particles affect the measurement of fringe patterns and subsequent analysis. An imaging unit with one time-delay-integration (TDI) camera has been developed to acquire two cross-polarized diffraction images. It was shown that selected elements of Mueller matrix of single scatters can be imaged with pixel matching precision in this configuration. With the TDI camera, the effect of blurring on imaging of scattered light propagating along the side directions was found to be much more significant for biological cells than microspheres. Despite blurring, classification of MCF-7 and K562 cells is feasible since the effect has similar influence on extracted image parameters. Furthermore, image blurring can be useful for analysis of the correlations among texture parameters for characterization of diffraction images from single cells. The results demonstrate that with one TDI camera the polarization diffraction imaging flow cytometry can be significantly improved and angular distribution of selected Mueller matrix elements can be accurately measured for rapid and morphology-based assay of particles and cells without fluorescent labeling.

Polarization imaging and classification of Jurkat T and Ramos B cells using a flow cytometer.

Label-free and rapid classification of cells can have awide range of applications in biology. We report a robust method of polarization diffraction imaging flow cytometry (p-DIFC) for achieving this goal. Coherently scattered light signals are acquired from single cells excited by a polarized laser beam in the form of two cross-polarized diffraction images. Image texture and intensity parameters are extracted with a gray level co-occurrence matrix (GLCM) algorithm to obtain an optimized set of feature parameters as the morphological "fingerprints" for automated cell classification. We selected the Jurkat T cells and Ramos B cells to test the p-DIFC method's capacity for cell classification. After detailed statistical analysis, we found that the optimized feature vectors yield accuracies of classification between the Jurkat and Ramos ranging from 97.8% to 100% among different cell data sets. Confocal imaging and three-dimensional reconstruction were applied to gain insights on the ability of p-DIFC method for classifying the two cell lines of highly similar morphology. Based on these results we conclude that the p-DIFC method has the capacity to discriminate cells of high similarity in their morphology with "fingerprints" features extracted from the diffraction images, which may be attributed to subtle but statistically significant differences in the nucleus-to-cell volume ratio in the case of Jurkat and Ramos cells.

Analysis of diffraction imaging in non-conjugate configurations.

Diffraction imaging of scattered light allows extraction of information on scatterer's morphology. We present a method for accurate simulation of diffraction imaging of single particles by combining rigorous light scattering model with ray-tracing software. The new method has been validated by comparison to measured images of single microspheres. Dependence of fringe patterns on translation of an objective based imager to off-focus positions has been analyzed to clearly understand diffraction imaging with multiple optical elements. The calculated and measured results establish unambiguously that diffraction imaging should be pursued in non-conjugate configurations to ensure accurate sampling of coherent light distribution from the scatterer.

[Density functional theory study of surface-enhanced raman spectra and excited state of 1,4-benzenedithiol].

Raman scattering spectra and optimized geometries of the 1,4-benzenedithiol molecule and complexes have been calculated using density functional theory (DFT) with B3LYP functional at the level of 6-311G+(d) basis set for C, H, S atoms and LanL2DZ for Ag, Au atoms, respectively. The optimized 1,4-benzenedithiol molecule was non-planar structure and the angle between benzene ring plane and S-H is 20.20. By means of the simulation of molecule adsorbed on gold and silver cluster, we concluded that gold clusters are nearly parallel to the benzenedithiol molecule and silver clusters are almost perpendicular to the molecular surface. The authors studied the interaction between Raman intensity and molecular properties, such as static polarizablity and charge distribution. The Raman intensity of 1,4-BDT-Au2, 1,4-BDT-Ag2 and Ag2-1,4-BDT-Au2 were in good agreement with static polarizability. The excited states of Ag2-1,4-BDT-Au2 complex were calculated using time-dependent density functional theory (TDDFT). And the simulated absorption spectra and several allowed singlet excited states were analyzed to investigate the surface-enhanced Raman chemical enhancement mechanism.

Study of low speed flow cytometry for diffraction imaging with different chamber and nozzle designs.

Achieving effective hydrodynamic focusing and flow stability at low speed presents a challenging design task in flow cytometry for studying phenomena such as cell adhesion and diffraction imaging of cells with low-cost cameras. We have developed different designs of flow chamber and sheath nozzle to accomplish the above goal. A 3D computational model of the chambers has been established to simulate the fluid dynamics in different chamber designs and measurements have been performed to determine the velocity and size distributions of the core fluid from the nozzle. Comparison of the simulation data with experimental results shows good agreement. With the computational model significant insights were gained for optimization of the chamber design and improvement of the cell positioning accuracy for study of slow moving cells. The benefit of low flow speed has been demonstrated also by reduced blurring in the diffraction images of single cells. Based on these results, we concluded that the new designs of chamber and sheath nozzle produce stable hydrodynamic focusing of the core fluid at low speed and allow detailed study of cellular morphology under various rheological conditions using the diffraction imaging method.

Analysis of cellular objects through diffraction images acquired by flow cytometry.

It was found that the diffraction images acquired along the side scattering directions with objects in a cell sample contain pattern variations at both the global and local scales. We show here that the global pattern variation is associated with the categorical size and morphological heterogeneity of the imaged objects. An automated image processing method has been developed to separate the acquired diffraction images into three types of global patterns. Combined with previously developed method for quantifying local texture pattern variations, the new method allows fully automated analysis of diffraction images for rapid and label-free classification of cells according to their 3D morphology.

Fast method for inverse determination of optical parameters from two measured signals.

Solving inverse problems requires multiple forward calculations of measured signals. We present a fast method combining graphic processing unit-accelerated Monte Carlo simulations of individual photons and a new perturbation scheme for a 300-fold speedup in comparison to conventional CPU-based approaches. The method allows rapid calculations of the diffuse reflectance and transmittance signals from a turbid sample of absorption coefficient µ(a), scattering coefficient µ(s), and anisotropy factor g based on the principle of correlated sampling. To demonstrate its strong utility, we have applied the method for determining the optical parameters of diluted intralipid samples with satisfactory results.

A mathematical model of tumor volume changes during radiotherapy.

PURPOSE: To develop a clinically viable mathematical model that quantitatively predicts tumor volume change during radiotherapy in order to provide treatment response assessment for prognosis, treatment plan optimization, and adaptation. METHOD AND MATERIALS: The correction factors containing hypoxia, DNA single strand breaks, potentially lethal damage, and other factors were used to develop an improved cell survival model based on the popular linear-quadratic model of cell survival in radiotherapy. The four-level cell population model proposed by Chvetsov et al. was further simplified by removing the initial hypoxic fraction and reoxygenation parameter, which are hard to obtain in routine clinics, such that an easy-to-use model can be developed for clinical applications. The new model was validated with data of nine lung and cervical cancer patients. RESULTS: Out of the nine cases, the new model can predict tumor volume change in six cases with a correlation index R (2) greater than 0.9 and the rest of three with R (2) greater than 0.85. CONCLUSION: Based on a four-level cell population model, a more practical and simplified cell survival curve was proposed to model the tumor volume changes during radiotherapy. Validation study with patient data demonstrated feasibility and clinical usefulness of the new model in predicting tumor volume change in radiotherapy.

A novel method of diffraction imaging flow cytometry for sizing microspheres.

We report a novel method of diffraction imaging flow cytometry to measure and analyze size distribution of microspheres. An automated and robust image processing software based on the short-time-Fourier-transform algorithm has been developed to analyze the characteristic and spatially varying oscillations of side scatters recorded as a diffraction image. Our results demonstrate that the new method allows accurate and rapid determination of single microspheres' diameters ranging from 1 to 100 µm. The capacity for analysis of light scattering by two-sphere aggregates has been demonstrated but analytical tools for characterization of aggregates by multiple microspheres remain to be developed.

[The application of stereology in radiology imaging and cell biology fields].

Stereology is an interdisciplinary method for 3D morphological study developed from mathematics and morphology. It is widely used in medical image analysis and cell biology studies. Because of its unbiased, simple, fast, reliable and non-invasive characteristics, stereology has been widely used in biomedical areas for quantitative analysis and statistics, such as histology, pathology and medical imaging. Because the stereological parameters show distinct differences in different pathology, many scholars use stereological methods to do quantitative analysis in their studies in recent years, for example, in the areas of the condition of cancer cells, tumor grade, disease development and the patient's prognosis, etc. This paper describes the stereological concept and estimation methods, also illustrates the applications of stereology in the fields of CT images, MRI images and cell biology, and finally reflects the universality, the superiority and reliability of stereology.

Four-dimensional intensity-modulated radiation therapy planning for dynamic tracking using a direct aperture deformation (DAD) method.

PURPOSE: Planning for the delivery of intensity-modulated radiation therapy (IMRT) to a moving target, referred to as four-dimensional (4D) IMRT planning, is a crucial step for achieving the treatment objectives for sites that move during treatment delivery. The authors proposed a simplistic method that accounts for both rigid and nonrigid respiration-induced target motion based on 4D computed tomography (4DCT) data sets. METHODS: A set of MLC apertures and weights was first optimized on a reference phase of a 4DCT data set. At each beam angle, the apertures were morphed from the reference phase to each of the remaining phases according to the relative shape changes in the beam's eye view of the target. Three different planning schemes were evaluated for two lung cases and one pancreas patient: (1) Individually optimizing each breathing phase; (2) optimizing the reference phase and shifting the optimized apertures to other breathing phases based on a rigid-body image registration; and (3) optimizing the reference phase and deforming the optimized apertures to the other phases based on the deformation and translation of target contours. Planning results using scheme 1 serves as the "gold standard" for plan quality assessment; scheme 2 is the method previously proposed in the literature; and scheme 3 is the method the authors proposed in this article. The optimization results were compared between the three schemes for all three cases. RESULTS: The proposed scheme 3 is comparable to scheme 1 in plan quality, and provides improved target coverage and conformity with similar normal tissue dose compared with scheme 2. CONCLUSIONS: Direct aperture deformation method for 4D IMRT planning improves upon methods that only consider rigid-body motion and achieves a plan quality close to that optimized for each of the phases.

Identification of genes of four malignant tumors and a novel prediction model development based on PPI data and support vector machines.

Triple-negative breast cancer (TNBC), colon adenocarcinoma (COAD), ovarian cancer (OV), and glioblastoma multiforme (GBM) are common malignant tumors, in which significant challenges are still faced in early diagnosis, treatment, and prognosis. Therefore, further identification of genes related to those malignant tumors is of great significance for the improvement of management of the diseases. The database of the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) repository was used as the data source of gene expression profiles in this study. Malignant tumors genes were selected using a feature selection algorithm of maximal relevance and minimal redundancy (mRMR) and the protein-protein interaction (PPI) network. And finally selected 20 genes as potential related genes. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on the potential related genes, and different tumor-specific genes and similarities and differences between network modules and pathways were analyzed. Further, using the potential cancer-related genes found above in this study as features, a support vector machine (SVM) model was developed to predict high-risk malignant tumors. As a result, the prediction accuracy reached more than 85%, indicating that such a model can effectively predict the four types of malignant tumors. It is demonstrated that such genes found above in this study indeed play important roles in the differentiation of the four types of malignant tumors, providing basis for future experimental biological validation and shedding some light on the understanding of new molecular mechanisms related to the four types of tumors.

Identification of Triple-Negative Breast Cancer Genes and a Novel High-Risk Breast Cancer Prediction Model Development Based on PPI Data and Support Vector Machines.

Triple-negative breast cancer (TNBC) is a special subtype of breast cancer that is difficult to treat. It is crucial to identify breast cancer-related genes that could provide new biomarkers for breast cancer diagnosis and potential treatment goals. In the development of our new high-risk breast cancer prediction model, seven raw gene expression datasets from the NCBI gene expression omnibus (GEO) database (GSE31519, GSE9574, GSE20194, GSE20271, GSE32646, GSE45255, and GSE15852) were used. Using the maximum relevance minimum redundancy (mRMR) method, we selected significant genes. Then, we mapped transcripts of the genes on the protein-protein interaction (PPI) network from the Search Tool for the Retrieval of Interacting Genes (STRING) database, as well as traced the shortest path between each pair of proteins. Genes with higher betweenness values were selected from the shortest path proteins. In order to ensure validity and precision, a permutation test was performed. We randomly selected 248 proteins from the PPI network for shortest path tracing and repeated the procedure 100 times. We also removed genes that appeared more frequently in randomized results. As a result, 54 genes were selected as potential TNBC-related genes. Using 14 out the 54 genes, which are potential TNBC associated genes, as input features into a support vector machine (SVM), a novel model was trained to predict high-risk breast cancer. The prediction accuracy of normal tissues and TNBC tissues reached 95.394%, and the predictions of Stage II and Stage III TNBC reached 86.598%, indicating that such genes play important roles in distinguishing breast cancers, and that the method could be promising in practical use. According to reports, some of the 54 genes we identified from the PPI network are associated with breast cancer in the literature. Several other genes have not yet been reported but have functional resemblance with known cancer genes. These may be novel breast cancer-related genes and need further experimental validation. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to appraise the 54 genes. It was indicated that cellular response to organic cyclic compounds has an influence in breast cancer, and most genes may be related with viral carcinogenesis.

Dosimetric effects of the prone and supine positions on image guided localized prostate cancer radiotherapy.

PURPOSE: To compare target coverage and doses to rectum and bladder in IMRT of localized prostate cancer in the supine versus prone position, with the inclusion of image guidance. MATERIALS AND METHODS: Twenty patients with early stage localized prostate carcinoma who received external beam radiotherapy in the supine and prone positions underwent approximately 10 serial CT examinations in their respective treatment position in non-consecutive days, except for one patient who was treated prone but serially imaged supine. The prostate, bladder and rectum were contoured on all CT scans. A PTV was generated on the first scan of each patient's CT series by expanding the prostate with a 5mm margin and an IMRT plan was created. The resultant IMRT plan was then applied to that patient's remaining serial CT scans by aligning the initial CT image set with the subsequent serial CT image sets using (1) skin marks, (2) bony anatomy and (3) center of mass of the prostate. The dosimetric results from these three alignments were compared between the supine and prone groups. To account for the uncertainties associated with prostate delineation and intra-fractional geometric changes, a fictional "daily PTV" was generated by expanding the prostate with a 3mm margin on each serial CT scan. Thus, a more realistic target coverage index, V95, was quantified as the fraction of the daily PTV receiving at least 95% of the prescription dose. Dose-volume measures of the organs at risk were also compared. The fraction of the daily PTV contained by the initial PTV after each alignment method was quantified on each patient's serial CT scan, and is defined as PTV overlap index. RESULTS: As expected, alignment based on skin marks yielded unacceptable dose coverage for both groups of patients. Under bony alignment, the target coverage index, V95, was 97.3% and 93.6% for prone and supine patients (p<0.0001), respectively. The mean PTV overlap indices were 90.7% and 84.7% for prone and supine patients (p<0.0002), respectively. In the supine position 36% of cases showed a V95<95% after bony alignment, while only 12.5% of prone patients with V95<95% following bony alignment. Under soft-tissue alignment matching the center of mass of the prostate, the mean V95 was 99.3% and 98.6% (p<0.03) and the PTV overlap index was 97.7% and 94.8% (p<0.0002) for prone and supine groups, respectively. CONCLUSIONS: Soft-tissue alignment combined with 5mm planning margins is appropriate in minimizing treatment planning and delivery uncertainties in both the supine and prone positions. Alignment based on bony structures showed improved results over the use of skin marks for both supine and prone setups. Under bony alignment, the dose coverage and PTV overlap index for prone setup were statistically better than for supine setup, illustrating a more consistent geometric relationship between the prostate and the pelvic bony structures when patients were treated in the prone position.

Clinical and radiobiological evaluation of a method for planning target volume generation dependent on organ-at-risk exclusions in magnetic resonance imaging-based prostate radiotherapy.

BACKGROUND AND PURPOSE: Due to a smaller target volume when delineating prostate on magnetic resonance imaging (MRI), margins may be too tight as compared to computed tomography (CT) delineation, potentially reducing tumor control probability (TCP) in prostate radiotherapy. This study evaluated a clinically implemented MRI-based target expansion method to provide adequate margins yet limit organ-at-risk (OAR) dose as compared to CT-based delineation. METHODS AND MATERIALS: Patients in this study were treated to 79.2 Gy in 44 fractions via intensity modulated radiotherapy using an MRI-based expansion method, which excluded OARs when performing a 5 mm isotropic (except 4 mm posterior) expansion from gross tumor volume to clinical target volume (CTV), followed by an isotropic 5 mm expansion to generate the planning target volume (PTV). Ten cases were re-planned using CT-delineated prostate with CTV-to-PTV expansion of isotropic 8 mm, except for a 5 mm posterior expansion, with comparison of PTV volumes, TCP and normal tissue complication probability (NTCP) to the MRI-based method. Under IRB approved protocol, we retrospectively evaluated 51 patients treated with the MRI-based method for acute bladder and rectal toxicity with CTC-AE version 4.0 used for scoring. RESULTS: MRI-based PTV volume differed by 4% compared to CT-based PTV volume. Radiobiological calculated TCP of the MRI-based method was found comparable to CT-based methods with an average equivalent uniform dose of 80.5 Gy and 80.1 Gy respectively. Statistically significant decrease in bladder NTCP (toxicity Grade 2 and above for 5% complications within 5 years post radiotherapy) was observed in the MRI-based method. Outcomes data collected showed 65% and 100% of patients studied experienced Grade 0/1 bladder and rectal acute toxicity respectively. Grade 2 bladder toxicity was indicated in the remaining 35% of patients studied with no Grade 3 toxicity reported. CONCLUSIONS: Results showed comparable PTV volume with MRI-based method, and NTCP was reduced while maintaining TCP. Clinically, bladder and rectal toxicities were observed to be minimal.

Thoracic Organ Doses and Cancer Risk from Low Pitch Helical 4-Dimensional Computed Tomography Scans.

PURPOSE: To investigate the dose depositions to organs at risk (OARs) and associated cancer risk in cancer patients scanned with 4-dimensional computed tomography (4DCT) as compared with conventional 3DCT. METHODS AND MATERIALS: The radiotherapy treatment planning CT image and structure sets of 102 patients were converted to CT phantoms. The effective diameters of those patients were computed. Thoracic scan protocols in 4DCT and 3DCT were simulated and verified with a validated Monte Carlo code. The doses to OARs (heart, lungs, esophagus, trachea, spinal cord, and skin) were calculated and their correlations with patient effective diameter were investigated. The associated cancer risk was calculated using the published models in BEIR VII reports. RESULTS: The average of mean dose to thoracic organs was in the range of 7.82-11.84 cGy per 4DCT scan and 0.64-0.85 cGy per 3DCT scan. The average dose delivered per 4DCT scan was 12.8-fold higher than that of 3DCT scan. The organ dose was linearly decreased as the function of patients' effective diameter. The ranges of intercept and slope of the linear function were 17.17-30.95 and -0.0278--0.0576 among patients' 4DCT scans, and 1.63-2.43 and -0.003--0.0045 among patients' 3DCT scans. Relative risk of cancer increased (with a ratio of 15.68:1) resulting from 4DCT scans as compared to 3DCT scans. CONCLUSIONS: As compared to 3DCT, 4DCT scans deliver more organ doses, especially for pediatric patients. Substantial increase in lung cancer risk is associated with higher radiation dose from 4DCT and smaller patients' size as well as younger age.