Radiomics model based on intravoxel incoherent motion and diffusion kurtosis imaging for predicting histopathological grade and Ki-67 expression level of soft tissue sarcomas.

BACKGROUND: Accurate identification of the histopathological grade and the Ki-67 expression level is important in clinical cases of soft tissue sarcomas (STSs). PURPOSE: To explore the feasibility of a radiomics model based on intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and diffusion kurtosis imaging (DKI) MRI parameter maps in predicting the histopathological grade and Ki-67 expression level of STSs. MATERIAL AND METHODS: In total, 42 patients diagnosed with STSs between May 2018 and January 2020 were selected. The MADC software in Functool of GE ADW 4.7 workstation was used to obtain standard apparent diffusion coefficient (ADC), D, D*, f, mean diffusivity, and mean kurtosis (MK). The histopathological grade and Ki-67 expression level of STSs were identified. The radiomics features of IVIM and DKI parameter maps were used as the dataset. The area under the receiver operating characteristic curve (AUC) and F1-score were calculated. RESULTS: D-SVM achieved the best diagnostic performance for histopathological grade. The AUC in the validation cohort was 0.88 (sensitivity: 0.75 [low level] and 0.83 [high level]; specificity: 0.83 [low level] and 0.75 [high level]; F1-score: 0.75 [low level] and 0.83 [high level]). MK-SVM achieved the best diagnostic performance for Ki-67 expression level. The AUC in the validation cohort was 0.83 (sensitivity: 0.83 [low level] and 0.50 [high level; specificity: 0.50 [low level] and 0.83 [high level]; F1-score: 0.77 [low level] and 0.57 [high level]). CONCLUSION: The proposed radiomics classifier could predict the pathological grade of STSs and the Ki-67 expression level in STSs.

[An epidemiological investigation of chronic kidney disease in children with hearing disorder in Hunan province, China].

OBJECTIVE: To investigate the prevalence of chronic kidney disease (CKD) among the children with hearing disorder in Hunan province, China. METHODS: In this cross-sectional study, the multi-stage cluster sampling method was used to select 1 500 children as subjects. Questionnaire surveys, physical examinations, and laboratory examinations were performed on the spot. RESULTS: Among the 1 500 children, 1 459 with complete data were included in analysis. Among the 1 459 children, 43 had CKD, with a prevalence rate of 2.95%. The <7 years group had a significantly higher prevalence rate than the 7-14 years group [5.8% (35/604) vs 0.9% (8/855); P<0.05]. Among the 43 children with CKD, 31 (72%) had proteinuria, 27 (63%) had hematuria, and 11 (26%) had a decreased glomerular filtration rate. Among the 43 children with CKD, stage 1, 2, 3a, 3b, 4, and 5 CKD accounted for 30% (13 cases), 44% (19 cases), 12% (5 cases), 7% (3 cases), 7% (3 cases), and 0% (0 case) respectively. The prevalence rate of CKD increased with the severity of hearing disorder (P<0.01). CONCLUSIONS: The prevalence rate of CKD is higher among the children with hearing disorder in Hunan province. Most children have early-stage CKD. CKD is commonly seen in preschool children. Severity of hearing disorder is associated with the prevalence of CKD.

Detection of DNA damage caused by cryopreservation using a modified SCGE in large yellow croaker, Pseudosciaena crocea.

We used single-cell gel electrophoresis (SCGE) to detect the integrity of sperm DNA of the teleost large yellow croaker, Pseudosciaena crocea, cryopreserved with Cortland solution and a range of 5% to 30% DMSO concentrations in order to test how sperm cryopreservation affected the DNA stability of nuclei. Electrophoresis was conducted for 60 min at 130 mA and 15 V. The comet images were analyzed with software CometScore 1.5, and parameters such as comet length, tail length and percentage DNA in the tail were obtained. Then the comet rate and damage coefficient were calculated. Results demonstrated that there were no significant differences in motility, comet rate and damage coefficient between fresh sperm and cryopreserved sperm stored in 5%, 10%, 15% and 20% DMSO, while the sperm cryopreserved with 25% and 30% DMSO had a lower motility, higher comet length and damage coefficients than those of fresh sperm. There was a positive correlation between comet rate of cryopreserved sperm and the concentration of DMSO. Our results demonstrate that toxicity of the cryoprotectant is the main cause of DNA damage in cryopreserved sperm nuclei.

[Spectra and thermal analysis of the arc in activating flux plasma arc welding].

In activating flux plasma arc welding the welding arc was analyzed by spectra analysis technique, and the welding arc temperature field was measured by the infrared sensing and computer image technique. The distribution models of welding arc heat flow density of activating flux PAW welding were developed. The composition of welding arc affected by activated flux was studied, and the welding arc temperature field was studied. The results show that the spectral lines of argon atom and ionized argon atom of primary ionization are the main spectra lines of the conventional plasma welding arc. The spectra lines of weld metal are inappreciable in the spectra lines of the conventional plasma welding arc. The gas particle is the main in the conventional plasma welding arc. The conventional plasma welding arc is gas welding arc. The spectra lines of argon atom and ionized argon atom of primary ionization are intensified in the activating flux plasma welding arc, and the spectra lines of Ti, Cr and Fe elements are found in the activating flux plasma welding arc. The welding arc temperature distribution in activating flux plasma arc welding is compact, the outline of the welding arc temperature field is narrow, the range of the welding arc temperature distribution is concentrated, the welding arc radial temperature gradient is large, and the welding arc radial temperature gradient shows normal Gauss distribution.

Distribution of Karlodinium veneficum in the coastal region of Xiangshan Bay in the East China Sea, as detected by a real-time quantitative PCR assay of ribosomal ITS sequence.

Athecate dinoflagellate Karlodinium veneficum is a universal toxic species possessing karlotoxins recognized especially as ichthyotoxic as well as cytotoxic and hemolytic. Blooms of K. veneficum, both single-species or accompanied with other species, occurred more frequently worldwide in recent years, including the coastal region of China. Normally, K. veneficum present in relatively low abundance in phytoplankton communities in estuary regions. Being small and difficult to identify with light microscopy, it has been ignored for a long time till its blooming and toxins being confirmed. How it presents in background level and what is its relationship with critical geological and hydrological environment factors are basically not clear. In this study, the paper reports the application of a real-time quantitative PCR (qPCR) method to investigate the abundance and distribution of K. veneficum in the coastal waters of Xiangshan Bay in the East China Sea (ECS), a typical bay area of harmful algae blooms and heavily affected by anthropogenic activities. The real-time qPCR assay came out being an efficient method at detecting even low cell densities of K. veneficum of different genotypes. A total of 38 field samples of surface (0.5 m) and bottom water (9-100 m in depth) were analyzed and 12 samples were found positive for K. veneficum. At least 3 genotypes of K. veneficum present in this region. Temperatures in sites of K. veneficum positive ranged from 21.7 to 23.4 °C, and salinity levels were between 21.1 and 26.3. The K. veneficum distributed quite extensively in the waters of Xiangshan Bay, cell abundance varied from a low of 4 cells/L to a maximum of 170 cells/L. Most of the samples containing K. veneficum were collected from bottom water in different sites. At three of the 19 sampling sites, K. veneficum was detected in both surface and bottom water samples. Especially at sampling site near Beilun port, where the water is typically muddy with low transparency, relative high cell numbers of K. veneficum were found in both surface and bottom waters. Mixotrophy and vertical migration of K. veneficum could be important eco-physiological factors to consider in terms of understanding these distribution characteristics. The ideal conditions for K. veneficum growth and aggregation in this area still needs further study.

[Effects of temperature increase on zooplankton size spectra in thermal discharge seawaters near a power plant, China]. / 电厂温排水增温对浮游动物粒径谱的影响.

Utilizing the plankton 1 (505 Μm), 2 (160 Μm), 3 (77 Μm) nets to seasonally collect zooplankton samples at 10 stations and the corresponding abundance data was obtained. Based on individual zooplankton biovolume, size groups were classified to test the changes in spatiotemporal characteristics of both Sheldon and normalized biovolume size spectra in thermal discharge seawaters near the Guohua Power Plant, so as to explore the effects of temperature increase on zooplankton size spectra in the seawaters. The results showed that the individual biovolume of zooplankton ranged from 0.00012 to 127.0 mm3·ind-1, which could be divided into 21 size groups, and corresponding logarithmic ranges were from -13.06 to 6.99. According to Sheldon size spectra, the predominant species to form main peaks of the size spectrum in different months were Copepodite larvae, Centropages mcmurrichi, Calanus sinicus, fish larvae, Sagitta bedoti, Sagitta nagae and Pleurobrachia globosa, and minor peaks mostly consisted of individuals with smaller larvae, Cyclops and Paracalanus aculeatus. In different warming sections, Copepodite larvae, fish eggs and Cyclops were mostly unaffected by the temperature increase, while the macrozooplankton such as S. bedoti, S. nagae, P. globosa, C. sinicus and Beroe cucumis had an obvious tendency to avoid the outfall of the power plant. Based on the results of normalized size spectra, the intercepts from low to high occurred in November, February, May and August, respectively. At the same time, the minimum slope was found in February, and similarly bigger slopes were observed in May and August. These results indicated that the proportion of small zooplankton was highest in February, while the proportions of the meso- and macro-zooplankton were relatively high in May and August. Among different sections, the slope in the 0.2 km section was minimum, which increased with the increase of section distance to the outfall. The result obviously demonstrated that the closer the distance was from outfall of the power plant, the smaller the zooplankton became. On the whole, the average intercept of normalized size spectrum in Xiangshan Bay was 4.68, and the slope was -0.655.

[Effects of environmental factors on ß diversity of zooplankton community in thermal discharge seawaters near Guohua Power Plant in Xiangshan Bay, Zhejiang, China].

Zooplankton samples were seasonally collected at 10 stations in thermal discharge seawaters near Guohua Power Plant in Xiangshan Bay. The abundance data from these samples were pooled and further combined with field environmental factors, then generalised dissimilarity modelling (GDM) was used to explore the effects of environmental factors on ß diversity of zooplankton community. The results showed that altogether 95 species of zooplankton belonging to 14 taxa were found. In these taxa, small zooplankton with 62.6% of abundance was the main taxa, while copepods dominated in adult groups, which abundance accounted for 35.3%. According to Whittaker's definition and additive partition, a diversity accounted for 36.3% and ß diversity 63.7%. Environmental factors explained 43.8% of ß diversity, and geographical distance between sampling sites had no effect on ß diversity. However, there were still 19.9% of ß diversity remained to be explained. After GDM fitting, there were nine environmental variables affecting zooplankton ß diversity and explaining 68.8% of ß diversity. The variables contributing to ß diversity from high to low were seasonal water temperature, dissolved oxygen, seawater temperature increment, conductivity, suspended particulate matter, salinity, transparency, water depth and redox potential, respectively. Seasonal water temperature, dissolved oxygen and seawater temperature increment were the most important factors for driving ß diversity changes, and accounted for 23.9%, 13.7% and 9.7% of absolute contribution to the interpretable portion of the ß diversity, respectively. When seasonal water temperature, dissolved oxygen and seawater temperature increment were below 25 °C, greater than 5 mg · L(-1) and over 1 °C, respectively, ß diversity rapidly increased with the increasing variable gradients. Furthermore, other predictors had little effect on ß diversity.

[Spatiotemporal characteristics of zooplankton community structure and diversity in the strong temperature increment seawaters near Guohua power plant in Xiangshan Bay].

To explore the spatiotemporal characteristics of the zooplankton community structure and diversity in the strong temperature increment seawaters near a power plant, zooplankton samples were seasonally collected in duplicate by the type II net with mesh size of 160 microm at 10 stations near Guohua power plant in Xiangshan Bay in 2011. The results showed that a total of 62 species (including larvae) were identified in the samples, and the average abundance was 9 531.1 ind x m(-3). In the seawaters, zooplankton communities were mainly composed of copepods and pelagic larvae, and pelagic larvae were the dominant with an average percentage of abundance reached up to 66.6%. Analysis of similarities demonstrated that significant differences existed in zooplankton community structures among different months (P < 0.01). In these zooplankton communities, there were 18 dominant species controlling these community structures, among which the most important discriminating species were Centropages tenuiremis, Oithona similis, Oithona fallax, Acartia clausi, Clausocalanus furcatus, Paracalanus aculeatus and Paracalanus parvwus. GLM analysis indicated that diversity indices were also significantly different among different months (P < 0.01). According to the calculation results, the inflection point, where the diversity index began to decrease with increasing water temperature, fell within 20.31-22.31 degrees C. In sections, the average water temperature in the 0.2 km section (D02), away from the outfall, was 2.16: higher than that in the 2 km section. Driven by temperature, the main dominant species such as C. tenuiremis and O. similis tended to move into the 0.2 km section, while A. clause and especially large zooplankton tended to stay away from the outfall, and then gathered in the 1.2 km section. As a result, the number of species (33 species) and abundance (5 522.8 ind x m(-3)) were minimum in the section D02, while the number of species (53 species) and abundance (16 491.0 ind x m(-3)) reached the highest in the 1.2 km section. Meanwhile, diversity indices in the 0.2 km section were also obviously lower than those in other sections. Linear regression analysis showed that the diversity indices significantly decreased with increasing water temperature (P < 0.01). The zooplankton richness decreased by 12.3% when the water temperature increased by 1 degrees C.

[A comparison of zooplankton communities collected by two types of nets with different mesh sizes in Xiangshan Bay of Zhejiang, East China].

In March (spring), July (summer), September (autumn), and December (winter) 2010, the zooplanktons at six stations in Xiangshan Bay were sampled simultaneously by the nets with a mesh size of 505 microm (net type I) and of 160 microm (net type II), and each sampling had two replicates. The spatiotemporal differences in the zooplanktons communities collected by the two types of nets were compared. There existed great differences in the species number, abundance, biomass, dominant species, and community pattern between the zooplanktons collected by the two types of nets. The species number, average abundance, and average biomass of the zooplanktons collected by net type I (61 species including larvae, 139.0 ind x m(-3), and 86.1 mg x m(-3), respectively) were siginificantly lower than those collected by net II (84 species, 3780.2 ind x m(-3) and 191.1 mg x m(-3), respectively). In the dominant species, except for Acartia pacifica and Centropages mcmurrichi, the others were completely different between the zooplanktons collected by the two types of nets. In the zooplanktons collected by net type I, no species dominating over the year was found, while in the zooplanktons collected by net type II, Paracalanus aculeatus and Copepods larva were dominant over the year. The similarity analysis (ANOSIM) and non-metric multi-dimensional scaling (nMDS) ordination revealed that the community pattern of the zooplanktons collected by the two types of nets had significant spatiotemporal difference, and the community pattern of the zooplanktons collected by net type I was more discrete than that of the zooplanktons collected by net type II. The analysis of similarity percentage (SIMPER) further revealed that the average dissimilarity of the spatiotemporal difference in the community pattern between the zookplanktons collected by the two types of nets exceeded 75%, and the main discriminating species causing this dissimilarity were Paracalanus aculeatus, Copepods larva, Paracalanus crassirostris, and Oithona brevicornis, all of which were the dominant species of the zooplanktons collected by net type II. In a word, the zooplanktons collected by net type II were more representative for the investigation of the zooplanktons in Xiangshan Bay.

[Quantification of fish starvation treatments and randomization test for the contribution rates of treatment factors by BP network].

In this paper, four feeding treatments including continuous feeding (SR00), recycling of 2 days starvation and 2 days refeeding (SR22), recycling of 7 days starvation and 2 days refeeding (SR72), and recycling of 7 days starvation and 7 days refeeding (SR77) were designed, and the feeding treatments were quantified as two treatment factors, i. e., starvation stress (SS) and starvation frequency (CF). Combining these two factors with the factors dry matter feed intake (FI), body weight (BW), water temperature (TE), water salinity (SA), water pH (PH) and growth time (GT), three BP artificial neural networks were constructed to predict the weight gain (WG), specific growth rate (SGR), and feed conversion ratio (FCR) of Lateolabrax japonicus, respectively. The results showed that the WG, SGR and FCR of L. japonicus were significantly affected by different feeding treatments. Throughout a 8-week trial, the WG and SGR of starved fish couldn't catch up to those of control fish. Except for SR72 group whose FCR was markedly higher than that of control group, no differences in FCR were observed between control group and experimental groups SR22 and SR77. The study also indicated that artificial neural network could well predict WG and SGR, but was unavailable for FCR. Among the eight factors, FI, SS, CF and GT had significant contributions to both WG and SGR. Furthermore, WG and SGR were predominantly dependent on FI and SS, respectively. Based on 4999 randomizations, the contribution rate of the treatment factors (including related FI) to WG and SGR was 64.9% and 79.7% , respectively.