High content image analysis for human H4 neuroglioma cells exposed to CuO nanoparticles

<p>Abstract</p> <p>Background</p> <p>High content screening (HCS)-based image analysis is becoming an important and widely used research tool. Capitalizing this technology, ample cellular information can be extracted from the high content cellular images. In this study, an automated, reliable and quantitative cellular image analysis system developed in house has been employed to quantify the toxic responses of human H4 neuroglioma cells exposed to metal oxide nanoparticles. This system has been proved to be an essential tool in our study.</p> <p>Results</p> <p>The cellular images of H4 neuroglioma cells exposed to different concentrations of CuO nanoparticles were sampled using IN Cell Analyzer 1000. A fully automated cellular image analysis system has been developed to perform the image analysis for cell viability. A multiple adaptive thresholding method was used to classify the pixels of the nuclei image into three classes: bright nuclei, dark nuclei, and background. During the development of our image analysis methodology, we have achieved the followings: (1) The Gaussian filtering with proper scale has been applied to the cellular images for generation of a local intensity maximum inside each nucleus; (2) a novel local intensity maxima detection method based on the gradient vector field has been established; and (3) a statistical model based splitting method was proposed to overcome the under segmentation problem. Computational results indicate that 95.9% nuclei can be detected and segmented correctly by the proposed image analysis system.</p> <p>Conclusion</p> <p>The proposed automated image analysis system can effectively segment the images of human H4 neuroglioma cells exposed to CuO nanoparticles. The computational results confirmed our biological finding that human H4 neuroglioma cells had a dose-dependent toxic response to the insult of CuO nanoparticles.</p

Visit to the China Qinghai Duoba National Highland Sports Training Base

The Human High Performance doctoral degree program at the University of Tsukuba was established in 2015, and I (Cao Yinhang) am one of the first students in this program. For my doctoral thesis, I have been working on a project aimed at elucidating the factors that determine individual variation in the hypoxia-induced reduction in peak oxygen uptake among endurance athletes during high-altitude exposure. To gain important insight into actual high-altitude training in China, as part of my doctoral research, I visited the Qinghai Duoba National Highland Sports Training Base (Duoba Base) on July 4-7, 2016. Duoba Base is the largest and highest high-altitude training center in China. The director of the Qinghai Institute of Sports Science, Ma Fuhai, extended to me an invitation to come to Duoba Base. During my visit, I met Chinese national race walkers engaged in high-altitude training in preparation for the 2016 Summer Olympic Games. With great support from Liu Haiming, a coach of the Qinghai province race walking team, I learned how Chinese national race walkers train at high altitude, and I assessed the pulmonary function of the race walkers from Qinghai province

Impact of altitude on power output during cycling stage racing

Purpose The purpose of this study was to quantify the effects of moderate-high altitude on power output, cadence, speed and heart rate during a multi-day cycling tour. Methods Power output, heart rate, speed and cadence were collected from elite male road cyclists during maximal efforts of 5, 15, 30, 60, 240 and 600 s. The efforts were completed in a laboratory power-profile assessment, and spontaneously during a cycling race simulation near sea-level and an international cycling race at moderate-high altitude. Matched data from the laboratory power-profile and the highest maximal mean power output (MMP) and corresponding speed and heart rate recorded during the cycling race simulation and cycling race at moderate-high altitude were compared using paired t-tests. Additionally, all MMP and corresponding speeds and heart rates were binned per 1000m (3000m) according to the average altitude of each ride. Mixed linear modelling was used to compare cycling performance data from each altitude bin. Results Power output was similar between the laboratory power-profile and the race simulation, however MMPs for 5–600 s and 15, 60, 240 and 600 s were lower (p ≤ 0.005) during the race at altitude compared with the laboratory power-profile and race simulation, respectively. Furthermore, peak power output and all MMPs were lower (≥ 11.7%, p ≤ 0.001) while racing \u3e3000 m compared with rides completed near sea-level. However, speed associated with MMP 60 and 240 s was greater (p \u3c 0.001) during racing at moderate-high altitude compared with the race simulation near sea-level. Conclusion A reduction in oxygen availability as altitude increases leads to attenuation of cycling power output during competition. Decrement in cycling power output at altitude does not seem to affect speed which tended to be greater at higher altitude

Selective laser melting of tungsten carbide reinforced maraging steel composite

In this work, tungsten carbide (WC) reinforced maraging steel matrix composites were in-situ manufactured by selective laser melting (SLM) from powder mixture. The SLM processed samples presented high relative density (over 99%) with a homogenous distribution of WC. The as-fabricated surface quality of SLM processed samples was improved significantly by the addition of WC. Focused ion beam and transmission electron microscopy were employed to characterize the interfacial properties between tungsten carbide and steel matrix. The elemental analysis indicates that metallurgical bonding appears at interfacial region due to the diffusion. Tensile behavior of SLM processed maraging steel was different from their composite with several WC contents

Differential metabolites of bronchoalveolar lavage fluid from coal worker's pneumoconiosis patients

Background It is a research hotspot to study the changes of metabolites and metabolic pathways in the process of coal worker's pneumoconiosis (CWP) by metabonomics and to explore its pathogenesis. ObjectiveTo study the change of metabolites in bronchoalveolar lavage fluid (BALF) of patients with CWP and explore the metabolic regulation mechanism of the disease. MethodsPatients with CWP who met the national diagnostic criteria according to Diagnosis of occupational pneumoconiosis (GBZ 70-2015) and underwent massive whole lung lavage were selected as the case group, and patients with tracheostenosis who underwent bronchoscopy were selected as the control group. BALF samples were collected from the cases and the controls. After filtering out large particles and mucus, the supernatant was stored in a −80 ℃ refrigerator. The samples were detected and analyzed by liquid chromatography-mass spectrometry after adding extraction solution, cold bath ultrasonication, and high-speed centrifugation, and the metabolic profiles and related data of CWP patients were obtained. The differential metabolites related to the occurrence and development of CWP were screened by multiple statistical analysis; furthermore, we searched the Kyoto Encyclopedia of Genes and Genomes (KEGG) database for potential metabolic pathways involved in the progression. ResultsThere was no significant difference in the general conditions of the subjects, such as weight, height, age, and length of service among the stage I group, the stage II group, the stage III group, and the control group (P˃0.05). When comparing the CWP stage I group with the control group, 48 differential metabolites were screened out, among which 14 were up-regulated and 34 were down-regulated. A total of 66 differential metabolites were screened out between the patients with CWP stage II and the controls, 14 up-regulated and 52 down-regulated differential metabolites. Compared with the control group, 63 differential metabolites were screened out in the patients with CWP stage III, including 11 up-regulated and 52 down-regulated differential metabolites. There were 36 differential metabolites that may be related to the occurrence of CWP, among which 11 differential metabolites were up-regulated, and 25 were down-regulated. Four significant differential metabolic pathways were identified through KEGG database query: linoleic acid metabolic pathway, alanine metabolic pathway, sphingolipid metabolic pathway, and glycerophospholipid metabolic pathway. ConclusionThe metabolomic study of BALF show that there are 36 different metabolites in the occurrence and development of CWP, mainly associating with linoleic acid metabolism, alanine metabolism, sphingolipid metabolism, and glycerophospholipid metabolism pathways

Changes in intestinal flora of coal workers' pneumoconiosis patients after tetrandrine intervention

BackgroundPneumoconiosis is a widespread occupational disease in China at present. As a type of lung diseases, its pathological damage is mainly irreversible fibrotic changes in the lungs. Several studies have shown that the occurrence and development of lung diseases such as coal workers' pneumoconiosis are closely related to intestinal flora. ObjectiveTo observe intestinal flora of coal workers' pneumoconiosis patients based on the results of 16SrDNA high-throughput sequencing and evaluate the changes of intestinal flora after treatment with tetrandrine tablets. MethodsA total of 80 patients with coal workers' pneumoconiosis attending the outpatient clinic of the Department of Occupational Diseases of the Emergency General Hospital from April to July 2022 were enrolled. All patients were treated with tetrandrine tablets for 4 weeks, with group A before the treatment of tetrandrine tablets and group B after the treatment. In the same period, 24 healthy controls (group C) were set up. Stool samples were collected before and after the treatment. Using 16SrDNA high-throughput sequencing, gene V3-V4 sequencing technology, and bioinformatic analysis platform, we evaluated the intestinal flora after treatment by groups. ResultsThe dominant flora at the phylum level and genus level were the same across three groups. The relative abundances of phylum Bacteroidetes, Bifidobacterium, Bacteroides, and Facealibacterium in groups B and C were higher than those in group A, and the relative abundances of phy-lum Actinobacteria, genus Blautia, and genus Romboutsia in groups B and C were lower than those in group A (P＜0.05). The relative abundances of genus Clostridium, genus Megamonas, and genus Lactobacillus in group C was lower than that in groups A and B (P＜0.05). The alpha diversity analysis showed that the Chao1 index was higher in group A than in group C (P＜0.01). Compared with group A, the Shannon index was higher in group B, and the increases of Simpson index were all statistically significant in stage I patients (P＜0.05), but the differences in Chao1 index were not statistically significant (P＞0.05). The differences in the values of Chao1 index, Shannon index, and Simpson index in stage Ⅱ and stage III patients were not statistically significant (P＞0.05). The beta diversity analysis showed that the difference in flora structure between group A and group C was statistically significant (P＜0.05); the differences in flora structure before and after treatment in the same stage patients were statistically significant (P＜0.05). The partial least squares discriminant analysis (PLS-DA) showed that there were significant differences between group A and group C, and between group A and group B. The LEfSe analysis showed that the significant markers contributing to the differences were basically the same in stage I, stage Ⅱ, and stage Ⅲ after treatment, which were mainly phylum Bacteroidetes and its subordinate groups, class Negativicutes, or-der Selenomonas, and genus Facealibacterium. ConclusionThere are differences in the distribution of flora between coal workers' pneumoconiosis patients and healthy individuals, and the structure and relative abundance of intestinal flora are changed and the number of beneficial flora is increased after treatment with tetrandrine tablets

Zastosowanie sieci bayesowskiej do analizy niezawodności złożonych systemów wielostanowych w warunkach niepewności

Reliability analysis of complex multi-state system has uncertainty, which is caused by complex structures, limited test samples, and insufficient reliability data. By introducing fuzzy mathematics and grey system theory into the Bayesian network, the model of the grey fuzzy Bayesian network is built, and the reliability analysis method of complex uncertainty multi-state system with the non-deterministic membership function and the interval characteristic quantity is proposed in this paper. Using the trapezoidal membership function with fuzzy support radius variable to describe the fault state of the component, it can effectively avoid the influence of human subjective factors on the selection of the membership function and solve the problem that the fault states of the system and its components are difficult to define accurately. And the conditional probability table containing interval grey numbers is constructed to effectively express the uncertain fault logic relationship between the system and its components. Moreover, a parameter planning model of the system reliability characteristic quantities is constructed, and the system reliability characteristic quantities are expressed as the form of interval values. Finally, two sets of numerical experiments are conducted and discussed, and the results show that the proposed method is an effective and a promising approach to reliability analysis for complex uncertainty multi-state systems.Analiza niezawodności złożonych systemów wielostanowych obarczona jest niepewnością związaną ze złożonością ich struktury, ograniczoną liczbą próbek badawczych i niewystarczającymi danymi dotyczącymi niezawodności. W przedstawionej pracy, wprowadzenie elementów matematyki rozmytej i teorii szarych systemów do sieci bayesowskiej umożliwiło budowę modelu szarej rozmytej sieci bayesowskiej i zaproponowanie metody analizy niezawodności złożonych systemów wielostanowych w warunkach niepewności, która wykorzystuje niedeterministyczną funkcję przynależności oraz pojęcie interwałowej wielkości charakterystycznej. Zastosowanie trapezoidalnej funkcji przynależności z rozmytą zmienną promienia nośnego do opisu stanu uszkodzenia komponentu, pozwala zniwelować wpływ subiektywnego czynnika ludzkiego na wybór funkcji przynależności i eliminuje konieczność precyzyjnego definiowania stanu uszkodzenia systemu i jego elementów składowych. Opracowana tabela prawdopodobieństw warunkowych zawierająca szare liczby interwałowe pozwala wyrazić niepewne zależności logiki uszkodzeń między systemem a jego składnikami. Ponadto, w pracy skonstruowano model planowania parametrów charakterystycznych wielkości niezawodności systemu wyrażonych w postaci wartości interwałowych. W ostatniej części artykułu omówiono dwie serie eksperymentów numerycznych, których wyniki pokazują, że proponowana metoda stanowi skuteczne i obiecujące podejście do analizy niezawodności złożonych systemów wielostanowych w warunkach niepewności

Multiple nuclei tracking using integer programming for quantitative cancer cell cycle analysis

Abstract—Automated cell segmentation and tracking are critical for quantitative analysis of cell cycle behavior using time-lapse fluorescence microscopy. However, the complex, dynamic cell cycle behavior poses new challenges to the existing image segmentation and tracking methods. This paper presents a fully automated tracking method for quantitative cell cycle analysis. In the proposed tracking method, we introduce a neighboring graph to characterize the spatial distribution of neighboring nuclei, and a novel dissimilarity measure is designed based on the spatial distribution, nuclei morphological appearance, migration, and intensity information. Then, we employ the integer programming and division matching strategy, together with the novel dissimilarity measure, to track cell nuclei. We applied this new tracking method for the tracking of HeLa cancer cells over several cell cycles, and the validation results showed that the high accuracy for segmentation and tracking at 99.5 % and 90.0%, respectively. The tracking method has been implemented in the cell–cycle analysis software package, DCELLIQ, which is freely available. Index Terms—Anti-cancer drug screening, cell cycle analysis, segmentation and tracking, time-lapse fluorescence microscopy. I