ABSTRACT
OBJECTIVES: To explore the changes in the coagulation function of patients newly diagnosed with multiple myeloma (MM) at different stages and with different M protein types, and to analyze the correlation between coagulation indexes and ß2-microglobulin (ß2-MG). METHODS: A total of 371 Patients with newly diagnosed MM (n = 371) and healthy controls (n = 48) were selected from January 2016 to December 2022. Baseline data, ß2-MG and coagulation index values were collected. Indexes included prothrombin time (PT), activated partial thromboplastin time (APPT), fibrinogen (FIB), thrombin time (TT), fibrinogen degradation products (FDP), and D-dimer(D-D). Patients were divided into different groups according to the Durie-Salmon staging system (DS), the International Staging System (ISS) and disease classification (M protein type). The levels of these six indexes were compared among the groups and the correlation between each index and ß2-MG was analyzed. RESULTS: Compared to the normal control group, the levels of PT, FIB, TT, FDP and D-D in the MM group were significantly higher (all P < 0.001). As DS and ISS staging increased, the levels of PT, TT, FDP and D-D also increased significantly (all P < 0.001). ß2-MG was positively correlated with PT, TT, and FDP levels (Spearman r = 0.157, 0.270, 0.108, respectively; all P < 0.05), and negatively correlated with FIB (r = -0.220, P < 0.001). Significant differences existed in the levels of these six indexes among different M protein types (all P < 0.001). Among them, PT and APTT increased significantly in the IgA-κ group, FIB increased in the λ light chain group, TT increased in the IgG-κ group, FDP increased in the κ light chain group, and D-D increased in the IgG-λ group. CONCLUSIONS: The degree of coagulation dysfunction in MM patients increases with disease stage and abnormal increases of various coagulation indicators occur in different M protein types and are closely related to ß2-MG.
Subject(s)
Blood Coagulation , Multiple Myeloma , beta 2-Microglobulin , Humans , Multiple Myeloma/blood , Multiple Myeloma/diagnosis , beta 2-Microglobulin/blood , Female , Male , Middle Aged , Aged , AdultABSTRACT
Rapid acquisition of the data of soil moisture content (SMC) and soil organic matter (SOM) content is crucial for the improvement and utilization of saline alkali farmland soil. Based on field measurements of hyperspectral reflectance and soil properties of farmland soil in the Hetao Plain, we used a competitive adaptive reweighted sampling algorithm (CARS) to screen sensitive bands after transforming the original spectral reflectance (Ref) into a standard normal variable (SNV). Strategies â , â ¡, and â ¢ were used to model the input variables of Ref, Ref SNV, Ref-SNV+ soil covariate (SC), and digital elevation model (DEM). We constructed SMC and SOM estimation models based on random forest (RF) and light gradient boosting machine (LightGBM), and then verified and compared the accuracy of the models. The results showed that after CARS screening, the sensitive bands of SMC and SOM were compressed to below 3.3% of the entire band, which effectively optimized band selection and reduced redundant spectral information. Compared with the LightGBM model, the RF model had higher accuracy in SMC and SOM estimation, and the input variable strategy â ¢ was better than â ¡ and â . The introduction of auxiliary variables effectively improved the estimation ability of the model. Based on comprehensive analysis, the coefficient of determination (Rp2), root mean square error (RMSE), and relative analysis error (RPD) of the SMC estimation model validation based on strategy â ¢-RF were 0.63, 3.16, and 2.01, respectively. The SOM estimation models based on strategy â ¢-RF had Rp2, RMSE, and RPD of 0.93, 1.15, and 3.52, respectively. The strategy â ¢-RF model was an effective method for estimating SMC and SOM. Our results could provide a new method for the rapid estimation of soil moisture and organic matter content in saline alkali farmland.
Subject(s)
Algorithms , Organic Chemicals , Soil , Water , Soil/chemistry , Organic Chemicals/analysis , Water/analysis , Crops, Agricultural/growth & development , Crops, Agricultural/chemistry , Alkalies/analysis , Alkalies/chemistry , China , EcosystemABSTRACT
Transposable elements (TEs) and satellite DNAs, two major categories of repetitive sequences, are expected to accumulate in non-recombining genome regions, including sex-linked regions, and contribute to sex chromosome evolution. The dioecious plant, Humulus scandens, can be used for studying the evolution of the XX/XY1Y2 sex chromosomes. In this study, we thoroughly examined the repetitive components of male and female H. scandens using next-generation sequencing data followed by bioinformatics analysis and florescence in situ hybridization (FISH). The H. scandens genome has a high overall repetitive sequence composition, 68.30% in the female and 66.78% in the male genome, with abundant long terminal repeat (LTR) retrotransposons (RTs), including more Ty3/Gypsy than Ty1/Copia elements, particularly two Ty3/Gypsy lineages, Tekay and Retand. Most LTR-RT lineages were found dispersed across the chromosomes, though CRM and Athila elements were predominately found within the centromeres and the pericentromeric regions. The Athila elements also showed clearly higher FISH signal intensities in the Y1 and Y2 chromosomes than in the X or autosomes. Three novel satellite DNAs were specifically distributed in the centromeric and/or telomeric regions, with markedly different distributions on the X, Y1, and Y2 chromosomes. Combined with FISH using satellite DNAs to stain chromosomes during meiotic diakinesis, we determined the synapsis pattern and distinguish pseudoautosomal regions (PARs). The results indicate that the XY1Y2 sex chromosomes of H. scandens might have originated from a centric fission event. This study improves our understanding of the repetitive sequence organization of H. scandens genome and provides a basis for further analysis of their chromosome evolution process.
ABSTRACT
DNA methylation plays a critical role in the modulation of gene expression. The role of DNA methylation in sex determination was investigated in spinach. The differentiated cytosine CpG methylation profiles of CCGG motifs were assessed with methylation sensitivity amplification polymorphism (MSAP) in spinach. Among 442 DNA fragments from four plants, 134 methylated fragments were found. Relative proportions of methylation sites were 28.8% in male plants and 31.8% in female plants. At the same time, cytosine methylation levels were higher in females than in males in CCGG motifs of genomes in the spinach. These findings suggest that methylation of CG islands is involved in sex determination and differentiation in spinach.
ABSTRACT
Accurately obtaining soil water and organic matter content is of great significance for improving soil qua-lity in croplands with medium to low yield. We explored the estimation effect of fractional order differentiation (FOD) combined with different spectral indices on soil water and organic matter content in medium and low yield croplands of Ningxia Yellow River Irrigation Area. After root mean square transformation of field measured hyperspectral reflectance, we used 0-2 FOD (with a step length of 0.25) to construct difference index (DI), ratio index (RI), product index (PI), sum index (SI), generalized difference index (GDI), and nitrogen planar domain index (NPDI) and to select the optimal spectral index based on the correlation coefficients between six spectral indices with soil water and organic matter contents. We constructed a model for estimating soil water and organic matter content based on partial least squares regression (PLSR) and support vector machine (SVM). The results showed that the correlation between soil water and organic matter content and spectral information was effectively improved after FOD transformation compared with the original spectrum, with maximum increases of 0.1785 and 0.1713, respectively. The soil water content sensitive bands were mainly in the range of 400-630 and 1350-1940 nm, while the sensitive bands of organic matter content were mainly at 460-850, 1530-1910, and 2060-2310 nm. The accuracy of SVM model was significantly higher than that of PLSR, and the soil water content estimation model based on 1.75-order NPDI-SVM reached the highest precision, with a validation determination coefficient (Rp2) of 0.970, root mean square error (RMSE) of 1.615, and relative percent deviation (RPD) of 4.211. The organic matter content estimation model based on 0.5 order DI-SVM had the best performance, with Rp2, RMSE and RPD of 0.983, 0.701 and 5.307, respectively. Our results could provide data and technological support for soil water and nutrient monitoring, quality improvement, and graphics creating in similar area with medium to low yield fields.
Subject(s)
Soil , Water , Rivers , Least-Squares Analysis , NutrientsABSTRACT
Accurate diagnosis of water and salt information in saline agricultural lands is crucial for long-term soil quality improvement and arable land conservation. In this study, we extracted field-scale vegetation canopy spectral information by UAV hyperspectral information, transforming the reflectance (R) to standard normal variate transformation (SNV), multiplicative scatter correction (MSC), first derivative of reflectance (FDR) and second derivative of reflectance (SDR). We determined the optimal spectral transformation forms of soil water content (SWC), soil pH, and soil salt content (SSC) by the maximum absolute correlation coefficient (MACC), and extracted the feature bands by competitive adaptive reweighted sampling (CARS). We constructed an inversion model of soil water and salt information by partial least squares regression (PLSR), random forest (RF), and extreme gradient boosting (XGBoost). The results showed that R, FDR and MSC were the best spectral transformation types for soil water content, soil pH, and soil salt content, and the corresponding MACC were 0.730, 0.472 and 0.654, respectively. The CARS algorithm effectively eliminated the irrelevant variables, optimally selecting 16-17 feature bands from 150 spectral bands. Both soil water content and soil pH performed best with XGBoost model, achieving determination coefficient of validation (Rp2) 0.927 and 0.743, and the relative percentage difference (RPD) amounted to 3.93 and 2.45. For soil salt content, the RF model emerged as the best inversion method with Rp2 and RPD of 0.427 and 1.64, respectively. The study could provide a reference solution for the integrated remote sensing monitoring of soil water and salt information in space and sky, serving as a scientific guide for the amelioration and sustainable management of saline lands.
Subject(s)
Hyperspectral Imaging , Soil , Soil/chemistry , Water , Sodium Chloride , Remote Sensing TechnologyABSTRACT
AIMS: There has been an increasing tendency to abandon crop cultivation and farming in old Lycium barbarum (wolfberry) stands to allow for natural restoration. However, little research has been dedicated to deciphering how soil quality changes in L. barbarum fields following abandonment from a physicochemical and microbiological perspective. Here we assessed the effects of farmland abandonment on anthropogenic-alluvial soil microbiota and contaminant residues in L. barbarum fields in Ningxia, China. METHODS AND RESULTS: Soil microbiota, heavy metal, and neonicotinoid pesticide profiles in L. barbarum fields abandoned for one to four years were characterized. Microbial community analysis was performed by high-throughput sequencing of the bacterial 16S ribosomal RNA genes and the fungal nuclear ribosomal internal transcribed spacer region. Soil bacterial diversity increased from before abandonment to year three after abandonment, and fungal diversity peaked in year one after abandonment. Enrichment of potentially beneficial taxa (e.g. Limnobacter, Cavicella) as well as pathogenic taxa (e.g. Ilyonectria) was observed in the abandoned field soils, along with depletion of other taxa (e.g. Planococcus, Bipolaris). Soil copper, zinc, cadmium, imidacloprid, and acetamiprid concentrations all decreased with increasing time since abandonment and had varied correlations with soil quality, microbial diversity, and the relative abundances of major phyla. Soil available phosphorus, nitrate-nitrogen, and pH were the key factors shaping bacterial communities. The structuring of fungal communities was strongly influenced by soil pH, available phosphorus, and available nitrogen contents. CONCLUSIONS: There were positive consequences of farmland abandonment in L. barbarum fields, such as optimized microbial community structure, reduced heavy metal accumulation, and enhanced pesticide degradation.
Subject(s)
Lycium , Microbiota , Farms , Soil , AgricultureABSTRACT
Background: Post-Traumatic Stress Disorder (PTSD) is a severe psychological disorder characterized by intrusive thoughts, heightened arousal, avoidance, and flashbacks. Cognitive flexibility dysfunction has been linked with the emergence of PTSD, including response inhibition deficits and impaired attentional switching, which results in difficulties for PTSD patients when disengaging attention from trauma-related stimuli. However, the molecular mechanisms of cognitive flexibility deficits remain unclear. Methods: The animals were exposed to a single prolonged stress and electric foot shock (SPS&S) procedure to induce PTSD-like features. Once the model was established, the changes in cognitive flexibility were assessed using an attentional set-shifting task (ASST) in order to investigate the effects of traumatic stress on cognitive flexibility. Additionally, the molecular alterations of certain proteins (AMPA Receptor 1 (GluA1), brain-derived neurotrophic factor (BDNF), and Postsynaptic density protein 95 (PSD95) in the medial prefrontal cortex (mPFC) were measured using Western blot and immunofluorescence. Results: The SPS&S model exhibited PTSD-like behaviors and induced reversal learning and set-shifting ability deficit in the ASST. These behavioral changes are accompanied by decreased GluA1, BDNF, and PSD95 protein expression in the mPFC. Further analysis showed a correlative relationship between the behavioral and molecular alterations. Conclusions: The SPS&S model induced cognitive flexibility deficits, and the potential underlying mechanism could be mediated by GluA1-related BDNF signaling in the mPFC.
ABSTRACT
Soil salinization is one of key drivers for the degradation of soil quality and yield in arable land. To accurately and quickly evaluate soil salt content in Yinchuan Plain, field and indoor hyperspectral data were processed with first order differential (FDR) transformation, then the feature bands were identified by stepwise regression (SR). Partial least squares regression (PLSR) and support vector machines (SVM) were used to build models, which were verified to figure out the optimal hyperspectral type for the study area. Moreover, segmented and global corrections were performed to process poor hyperspectral, aiming to improve the accuracy of soil salt content inversion. The results showed that the accuracy of soil salt content inversion model based on field hyperspectral data was 58.9% higher than that of the indoor hyperspectral data. The accuracy of the inversion was improved through the segmented and global correction of the indoor hyperspectral. We found that the segmented correction is more accurate for the PLSR model (Rc2=0.790, Rp2=0.633, RPD=1.64) and the global correction is more accurate for the SVM model (Rc2=0.927, Rp2=0.947, RPD=3.87). The SVM models' inversion accuracy was higher than that of PLSR, with the field hyperspectral model fitted the best, followed by the indoor hyperspectral processed with the global correction and the indoor hyperspectral processed with the segmented correction, while the indoor hyperspectral the worst. Our results suggest that field hyperspectral data could contribute to the quantitative inversion of soil salt content in Yinchuan Plain. The corrected indoor hyperspectral could significantly enhance the inversion accuracy of soil salt content, which could guarantee food security and ecological quality development.
Subject(s)
Sodium Chloride , Soil , China , Least-Squares AnalysisABSTRACT
BACKGROUND: The transfer of chloroplast DNA into nuclear genome is a common process in plants. These transfers form nuclear integrants of plastid DNAs (NUPTs), which are thought to be driving forces in genome evolution, including sex chromosome evolution. In this study, NUPTs in the genome of a dioecious plant Asparagus officinalis L. were systematically analyzed, in order to investigate the characteristics of NUPTs in the nuclear genome and the relationship between NUPTs and sex chromosome evolution in this species. RESULTS: A total of 3155 NUPT insertions were detected, and they represented approximated 0.06% of the nuclear genome. About 45% of the NUPTs were organized in clusters. These clusters were derived from various evolutionary events. The Y chromosome contained the highest number and largest proportion of NUPTs, suggesting more accumulation of NUPTs on sex chromosomes. NUPTs were distributed widely in all of the chromosomes, and some regions preferred these insertions. The highest density of NUPTs was found in a 47 kb region in the Y chromosome; more than 75% of this region was occupied by NUPTs. Further cytogenetic and sequence alignment analysis revealed that this region was likely the centromeric region of the sex chromosomes. On the other hand, the male-specific region of the Y chromosome (MSY) and the adjacent regions did not have NUPT insertions. CONCLUSIONS: These results indicated that NUPTs were involved in shaping the genome of A. officinalis through complicated process. NUPTs may play important roles in the centromere shaping of the sex chromosomes of A. officinalis, but were not implicated in MSY formation.
Subject(s)
Asparagus Plant/genetics , Cell Nucleus/genetics , Chromosomes, Plant/genetics , DNA, Chloroplast/genetics , Genome, Plant/genetics , Biological Evolution , Evolution, MolecularABSTRACT
Based on the analysis of the spectral reflectance of the typical Takyr Solonetzs soil in Ningxia, the relationship of soil water content and spectral reflectance was determined, and a quantitative model for the prediction of soil water content was constructed. The results showed that soil spectral reflectance decreased with the increasing soil water content when it was below the water holding capacity but increased with the increasing soil water content when it was higher than the water holding capacity. Soil water content presented significantly negative correlation with original reflectance (r), smooth reflectance (R), logarithm of reflectance (IgR), and positive correlation with the reciprocal of R and logarithm of reciprocal [lg (1/R)]. The correlation coefficient of soil water content and R in the whole wavelength was 0.0013, 0.0397 higher than r and lgR, respectively. Average correlation coefficient of soil water content with 1/R and [lg (1/R)] at the wavelength of 950-1000 nm was 0.2350 higher than that of 400-950 nm. The relationships of soil water content with the first derivate differential (R') , the first derivate differential of logarithm (lgR)' and the first derivate differential of logarithm of reciprocal [lg(1/R)]' were unstable. Base on the coefficients of r, lg(1/R), R' and (lgR)', different regression models were established to predict soil water content, and the coefficients of determination were 0.7610, 0.8184, 0.8524 and 0.8255, respectively. The determination coefficient for power function model of R'. reached 0.9447, while the fitting degree between the predicted value based on this model and on-site measured value was 0.8279. The model of R' had the highest fitted accuracy, while that of r had the lowest one. The results could provide a scientific basis for soil water content prediction and field irrigation in the Takyr Solonetzs region.
Subject(s)
Models, Theoretical , Soil/chemistry , Spectrum Analysis , Water/analysis , Agricultural IrrigationABSTRACT
The relationship between alkalinity and pH of the soil, reflectance spectra and red-edge parameters of the sunflower canopy in different growth periods under different alkalinity soil were analyzed, respectively. The results showed that the spectral reflectance of the sunflower canopy in different stage under different alkalinity soil is the same as the spectral reflectance characters of the other greenery canopy. Along with the advancement of the sunflower growth period, sunflower canopy spectral reflectance increases gradually at different stages, the spectral reflectance is higher at flowering stage than 7-leaf stage and budding stage, and there exists a high reflection peak at 809nm at flowering period. At the same time, the spectral reflectance is affected by salinity-alkalinity stress at different stages, in the near infrared shortwave band, the spectral reflectance of the sunflower canopy in different stage increases with the decreases in soil alkalinity. When the derivatives are applied to determine the wavelength of the red-edge, there is a shift phenomenon of the red edge. The red edges were at 702-720 nm during every growth period of the sunflower. The "blue shift" phenomenon is also emerged for red edge position and red edge sloped with the increase in the soil alkalinity. Conversely, at the same growth periods, the red edge positions and red edge slope move to longer wave bands with the decrease in soil alkalinity. There is a "red shift" phenomenon before flowering period and "blue shift" phenomenon after flowering period for the red edge position and red edge slope of canopy spectrum at the same soil alkalinity. Respectively. The red edges at different growth stages of the sunflower show very significant positive correlation and quadratic polynomial to alkalinity and pH of the soil. Therefore, we thought used the red edge features of greenery could indicate the soil alkalization degree, it providing scientific basis for monitoring soil alkalization degree by remote sensing.
Subject(s)
Plant Leaves , Soil/chemistry , Spectrum Analysis , Helianthus/growth & development , Remote Sensing TechnologyABSTRACT
OBJECTIVE: To explore the suitable level and action time of 17-beta estradiol and fluid shear stress (FSS) and their combined effect on the proliferation of rat osteoblasts in vitro. METHODS: MC3T3-E1 osteoblasts were adopted after subcultured and different concentrations of 17-beta estradiol and FSS values were applied respectively on MC3T3-E1, the suitable level of 17-beta estradiol and FSS were selected through MTT and alkaline phosphatase (ALP). Then the two factors at the suitable level were applied simultaneously to MC3T3-E1 to detect the proliferation activity. RESULTS: Seventeen-beta estradiol(10(-8) mol x L(-1) for 5 d and 12 x 10(-5) N FSS for 60 min exhibited better effects on the proliferation activity than the other groups respectively, and the combined effect of both factors was better than any single-factor treated group. CONCLUSION: Both 17-beta estradiol and FSS have a suitable threshold in promoting proliferation of osteoblasts, and two-factor treated group exhibits better effect than any other single-factor treated groups. Therefore 17-beta estradiol and FSS have a synergetic action on differentiation and proliferation of osteoblasts.
Subject(s)
Estradiol , Osteoblasts , Alkaline Phosphatase , Animals , Cell Differentiation , Rats , Stress, MechanicalABSTRACT
By using the 1986, 1993 and 2003 Landsat TM images and with the help of GIS, the dynamic changes of land desertification landscape pattern in agriculture and pasturage interlaced zone of northern Shaanxi in 1986-2003 were analyzed. The results showed that in the past 17 years, the desertification area in the zone decreased by 206,655.2 hm2, with the patches in landscape structure reduced and fragmentation abated. Fortunately, the desertification degree decreased obviously, and moderate and light desertification took the leading position. From 1986 to 2003, the spatial centroid of desertification landscape patches expanded southwestward and northeastward, giving serious threat to the ecological safety of the southeast and northeast loess gully and hilly areas.