Dissolved carbon and CDOM in lake ice and underlying waters along a salinity gradient in shallow lakes of Northeast China

The variations of DOC and DIC concentrations in lake ice and underlying waters were examined in 40 shallow lakes across the Songnen Plain, Northeast China. The lakes, frozen annually during winter, included freshwater and brackish systems (EC > 1000 μS cm−1; range: 171–12607 μS cm−1 in underlying water). Results showed that lake ice contained lower DOC (7.2 mg L−1) and DIC (6.7 mg L−1) concentration compared to the underlying waters (58.2 and 142.4 mg L−1, respectively). Large differences in DOC and DIC concentrations of underlying waters were also observed between freshwater (mean ± SD: 22.3 ± 11.5 mg L−1, 50.7 ± 20.6 mg L−1) and brackish lakes (83.3 ± 138.0 mg L−1, 247.0 ± 410.5 mg L−1). A mass balance model was developed to describe the relative distribution of solutes and chemical attributes between ice and the underlying waters. Results showed that water depth and ice thickness were the key factors regulating the spatial distribution of solutes in the frozen lakes. Chromophoric dissolved organic matter (CDOM) absorption coefficient at 320 nm, aCDOM(320) and specific UV absorbance (SUVA254) were used to characterize CDOM composition and quality. Compared to the underlying waters, CDOM present in ice largely included low aromaticity organic substances, an outcome perhaps facilitated by ice formation and photo-degradation. In ice and underlying freshwaters, CDOM predominantly included organic C fractions of high aromaticity, while low aromaticity organic substances were observed for brackish lakes. Results of this study suggest that, if water salinity increases due to climate change and anthropogenic activities, significant changes can occur in the dissolved carbon and fate of CDOM in these shallow lakes

Etablierung der Echtzeit-Fluoreszenz-PCR zur Bestimmung des BCL-2-Transkriptes bei akuten myeloischen Leukämien

Das BCL-2 Gen wurde als Onkogen der t (14;18)(q32;q21)-Translokation bei follikulären Non- Hodgkin-Lymphomen identifiziert. Die biologische Wirkung des BCL-2 Proteins liegt in der Hemmung der Apoptose. Bei der AML wird eine vermehrte BCL-2 Expression und eine dem- entsprechend verminderte Apoptose bei unreifen malignen myeloischen Vorläuferzellen gefun- den. Diese Krankheit ist teilweise auch chemoresistent. Goldstandard der Induktionstherapie bei AML ist eine Kombination aus Ara-C und Idarubicin, welche Doppel- und Einzelstrang- brüche der DNA induzieren. Apoptose der Leukämiezellen wird durch Schädigung der DNA ausgelöst. BCL-2 kann die Zellen durch Hemmung der Apoptose schützen, indem es die Cy- tochrom-C-Freisetzung blockiert. Darüber hinaus befinden sich die BCL-2- überexprimierenden Zellen in der G0-Phase und sprechen dabei schlecht auf die Chemothera- pie an. Deshalb stellt BCL-2 den Leukämiezellen "doppelten" Schutz zur Verfügung. BCL-2 spielt somit eine wichtige Rolle bei der Chemoresistenz. Ob ein Therapieprotokoll in der Be- handlung der AML effektiv ist, schlägt sich in der Kinetik der zunehmenden oder abnehmen- den BCL-2-Transkripte nieder. Zur Kontrolle des BCL-2-Transkriptes ist die quantitative PCR der qualitativen PCR überlegen. Die Quantifizierung dieses Transkriptes wurde mittels Echtzeit-Fluoreszenz-PCR realisiert. Bei der Echtzeit-Fluoreszenz-PCR wird die Reaktion im geschlossenen Reaktionsgefäß durchge- führt, sodass die Gefahr von Kontamination minimiert werden kann. Da keine Post-PCR Schrit- te nötig sind, wird die Überprüfung zahlreicher Proben durch ein 96-well-Format innerhalb eines Laufes ermöglicht. Die Echtzeit-Fluoreszenz-PCR garantiert ihre Spezifität durch eine spezifi- sche Sonde-Zielsequenz-Bindung und erlaubt eine exakte Quantifizierung der BCL-2- Transkriptzahl. In der vorliegenden Arbeit wurde die BCL-2-Expression in 53 AML-Fällen mittels Echtzeit- Fluoreszenz-PCR untersucht. Das ?-Actin Gen wurde als Referenzgen benutzt. Für die BCL-2- Expression wurde eine Ratio aus der Transkriptzahl des BCL-2 Gens und des ?-Actin Gens ge- bildet. Bei 53 AML-Fällen, die den sieben AML-Subtypen zugeordnet werden konnten(FAB M0-M7), konnte eine BCL-2-Expression nachgewiesen werden. Trotz der unterschiedlich hohen BCL-2-Expression bei diesen Patienten, ergab sich keine signifikante Korrelation zwischen der BCL-2-Expression und den FAB-Subtypen. Außerdem wurde die BCL-2-Expression in T- Zellen, B-Zellen und Granulozyten aus 5 AML-Patienten nachgewiesen. Die BCL-2-Expression wurde nicht von den Subpoplationen der mononukleären Zellen wie z.B. T-Zellen, B-Zellen, Granulozyten beeinflusst. Bei sieben Patienten wurden Proben im Verlauf untersucht. Dabei korrelierte eine hohe oder ansteigende BCL-2-Expression mit einem Rückfall der AML. Die Anzahl der untersuchten Proben im Verlauf ist jedoch zu klein, um definitive Schlußfolgerungen zu ziehen. Eine prospektive Untersuchung von größeren Patientenzahlen erscheint sinnvoll.The bcl-2 oncogene was discovered by virtue of its association with the translocation, t(14;18) (q32;q21), observed in most follicular lymphomas. The bcl-2 protein is a 26 kDa integral membrane protein which functions by enhancing cell viability through the inhibition of apoptotic death. Acute myeloid leukemia is a lethal malignant disease characterized by an abnormal proliferation and differentiation of myeloid progenitor cells. The bcl-2 oncogene contributes to leukemogenesis by prolonging the life span of defected progenitor cells. Although the expression of bcl-2 in blast cells of acute myeloid leukemia is heterogeneous, a significant proportion of blast cells are shown to have high bcl-2 levels. The highest bcl-2 levels are found in cells that grow autonomously in vitro and also in blast cells expressing the CD34 surface antigen. These groups of AML patients are tranditionally the ones in which the prognosis is poor, because most of the chemotherapeutic agents like cytosine-arabinoside (Ara-C) exert their effect by triggering apoptosis. The high level of the bcl-2 gene that inhibits apoptosis is implicated in the resistance of AML blast cells to chemotherapy and leads to unfavorable prognosis. In this study, a real time fluorescence PCR assay was used to monitor the expression of the bcl-2 transcript in the therapeutic course of AML patients. By applying this rapid new developed quantitative method, the changes of the bcl-2 transcript with chemotherapy can help to evaluate the efficacy of therapeutic interventions in AML. The real time fluorescence PCR has many advantages over traditional measures. First, the assay is extremely rapid because post-PCR processing steps are unnecessary. All relevant data are collected real time during the course of a 2h PCR cycle program; data analysis can be completed in less than 10 min. Second, the assay from reaction set-up to data collection and analysis is a closed-tube system, which reduces the risk of false positive resulting from PCR product carry- over contamination and eliminates variation from additional pipetting steps. Finally, the real time fluorescence PCR is highly specific for the gene target of interest. Here the expression levels of the bcl-2 gene were measured in 53 patients with acute myeloid leukemia and normalized by ?-actin, a house-keeping gene expression as endogenous reference. The bcl-2/?-actin ratio from the 53 patients with AML was various, but not related to FAB subtypes. And also, this transcript ratio was not affected by mononucleated cell types. The samples from seven patients were measured to evaluate the association between the bcl-2 expression and the responsiveness of AML patients to the chemotherapy. The high or gradual elevation of the bcl-2 expression demonstrated the loss of effect in update-therapy protocol and the relapse in AML patients. Although the amount of samples are not large enough to reach the final conclusion, it is of significance that a number of patients will be analyzed in the future

Ferritin level prospectively predicts hepatocarcinogenesis in patients with chronic hepatitis B virus infection

Previous studies have detected a higher level of ferritin in patients with hepatocellular carcinoma (HCC), but a potential causal association between serum ferritin level and hepatocarcinogenesis remains to be clarified. Using a well-established prospective cohort and longitudinally collected serial blood samples, the association between baseline ferritin levels and HCC risk were evaluated in 1,152 patients infected with hepatitis B virus (HBV), a major risk factor for HCC. The association was assessed by Cox proportional hazards regression model using univariate and multivariate analyses and longitudinal analysis. It was demonstrated that HBV patients who developed HCC had a significantly higher baseline ferritin level than those who remained cancer-free (188.00 vs. 108.00 ng/ml, P\u3c0.0001). The patients with a high ferritin level (≥200 ng/ml) had 2.43-fold increased risk of HCC compared to those with lower ferritin levels [hazard ratio (HR), 2.43; 95% confidence interval, 1.63-3.63]. A significant trend of increasing HRs along with elevated ferritin levels was observed (P for trend \u3c0.0001). The association was still significant after multivariate adjustment. Incorporating ferritin into the α-fetoprotein (AFP) model significantly improved the performance of HCC prediction (the area under the curve from 0.74 to 0.77, P=0.003). Longitudinal analysis showed that the average ferritin level in HBV patients who developed HCC was persistently higher than in those who were cancer-free during follow-up. HCC risk reached a peak at approximately the fifth year after baseline ferritin detection. Moreover, stratified analyses showed that the association was noted in both males and females, and was prominent in patients with a low AFP value. In short, serum ferritin level could independently predict the risk of HBV-related HCC and may have a complementary role in AFP-based HCC diagnosis. Future studies are warranted to validate these findings and test its clinical applicability in HCC prevention and management. © 2018, Spandidos Publication

MicroRNAs involved in neoplastic transformation of liver cancer stem cells

<p>Abstract</p> <p>Background</p> <p>The existence of cancer stem cells in hepatocellular carcinoma (HCC) has been verified by characterizing side population (SP) cells based on efflux of Hoechst 33342 dye from stem cells. Recent advances in microRNA (miRNA) biology have revealed that miRNAs play an important role in embryonic development and tumorigenesis. However, it is still unclear which miRNAs participate in the neoplastic transformation of liver cancer stem cells (LCSCs) during hepatocarcinogenesis.</p> <p>Methods</p> <p>To identify the unique set of miRNAs differentially regulated in LCSCs, we applied SP sorting to primary cultures of F344 rat HCC cancer cells treated with diethylnitrosamine (DEN) and normal syngenic fetal liver cells, and the stem-like characteristics of SP cells were verified through detecting expression of CD90.1, AFP and CK-7. Global miRNA expression profiles of two groups of SP cells were screened through microarray platform.</p> <p>Results</p> <p>A total of 68 miRNAs, including miR-10b, miR-21, miR-470*, miR-34c-3p, and let-7i*, were identified as overexpressed in SP of HCC cells compared to fetal liver cells. Ten miRNAs were underexpressed, including miR-200a* and miR-148b*. These miRNAs were validated using stem-loop real-time reverse transcriptase polymerase chain reaction (RT-PCR).</p> <p>Conclusions</p> <p>Our results suggest that LCSCs may have a distinct miRNA expression fingerprint during hepatocarcinogenesis. Dissecting these relationships will provide a new understanding of the function of miRNA in the process of neoplastic transformation of LCSCs.</p

Characterization of CDOM in saline and freshwater lakes across China using spectroscopic analysis

Colored dissolved organic matter (CDOM) is a major component of DOM in waters, and plays a vital role in carbon cycling in inland waters. In this study, the light absorption and three-dimensional excitation-emission matrix spectra (EEMs) of CDOM of 936 water samples collected in 2014–2017 from 234 lakes in five regions across China were examined to determine relationships between lake water sources (fresh versus saline) and their fluorescence/absorption characteristics. Results indicated significant differences regarding DOC concentration and aCDOM(254) between freshwater (6.68 mg C L−1, 19.55 m-1) and saline lakes (27.4 mg C L−1, 41.17 m-1). While humic-like (F5) and fulvic-like (F3) compounds contributed to CDOM fluorescence in all lake waters significantly, their contribution to total fluorescence intensity (FT) differed between saline and freshwater lakes. Significant negative relationships were also observed between lake altitude with either F5 (R2 = 0.63, N = 306) or FT (R2 = 0.64, N = 306), suggesting that the abundance of humic-like materials in CDOM tends to decrease with increased in lakes altitude. In high-altitude lakes, strong solar irradiance and UV exposure may have induced photo-oxidation reactions resulting in decreased abundance of humic-like substances and the formation of low molecular weight compounds. These findings have important implications regarding our understanding of C dynamics in lacustrine systems and the contribution of these ecosystems to the global C cycle

Dissolved carbon in a large variety of lakes across five limnetic regions in China

Dissolved carbon in lakes play a vital role in the global carbon cycling. The concentration and dynamics of lake dissolved carbon can be influenced by both the surrounding landscape and a combination of physical, chemical and biological processes within the lakes themselves. From 2009 to 2016, we conducted a large-scale assessment of dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) in 249 lakes across a diverse range of climatic, geopedologic, topographical and hydrological conditions in five Chinese limnetic regions: the East Limnetic Region (ELR), the Northeast Limnetic Region (NLR), the Inner Mongolia-Xinjiang Limnetic Region (MXR), the Yungui Limnetic Region (YGR), and the Tibet-Qinghai Limnetic Region (TQR). We found that the density of the organic matter in the soil in the surrounding landscape plays an important role in the DOC and DIC in lake water, as was evidenced by the high DOC and DIC levels in the NLR, where the soil is respectively organically rich. Conditions in the arid and semi-arid environments (i.e. TQR and MXR) have created a number of brackish/saline lakes and here we found that, DOC and DIC levels (median: 21.79 and 93.72 mg/L, respectively) are significantly higher than those in the freshwater lakes (median: 5.80 and 29.38 mg/L). It also appears to be the case that the trophic state of freshwater lakes influences the spatial variation of DOC. This can be seen in the relationships between DOC and trophic state index (TSI) in agriculturally-dominated regions such as the ELR (R2 = 0.59, p < 0.01), NLR (R2 = 0.65, p < 0.001), and YGR (R2 = 0.78, p < 0.001). Additionally, a close relationship between DOC and DIC can be found in lake waters with different trophic states (eutrophic: slp = 0.63, R2= 0.69; mesotrophic: slp = 1.03, R2 = 0.65; oligotrophic: slp = 1.00, R2 = 0.64). This indicates that human activities influence the quantity and quality of dissolved carbon in inland water across China. This study is able to provide insights regarding the potential effects of climate change and changes in land-use upon the amount of dissolved carbon in lake water

Impacts of climate change on Tibetan lakes: patterns and processes

High-altitude inland-drainage lakes on the Tibetan Plateau (TP), the earth’s third pole, are very sensitive to climate change. Tibetan lakes are important natural resources with important religious, historical, and cultural significance. However, the spatial patterns and processes controlling the impacts of climate and associated changes on Tibetan lakes are largely unknown. This study used long time series and multi-temporal Landsat imagery to map the patterns of Tibetan lakes and glaciers in 1977, 1990, 2000, and 2014, and further to assess the spatiotemporal changes of lakes and glaciers in 17 TP watersheds between 1977 and 2014. Spatially variable changes in lake and glacier area as well as climatic factors were analyzed. We identified four modes of lake change in response to climate and associated changes. Lake expansion was predominantly attributed to increased precipitation and glacier melting, whereas lake shrinkage was a main consequence of a drier climate or permafrost degradation. These findings shed new light on the impacts of recent environmental changes on Tibetan lakes. They suggest that protecting these high-altitude lakes in the face of further environmental change will require spatially variable policies and management measures

Convolutional neural network model for soil moisture prediction and its transferability analysis based on laboratory Vis-NIR spectral data

Laboratory visible near infrared reflectance (Vis-NIR, 400–2500 nm) spectroscopy has the advantages of simplicity, fast and non-destructive which was used for SM prediction. However, many previously proposed models are difficult to transfer to unknown target areas without recalibration. In this study, we first developed a suitable Convolutional Neutral Network (CNN) model and transferred the model to other target areas for two situations using different soil sample backgrounds under 1) the same measurement conditions (DSSM), and 2) under different measurement conditions (DSDM). We also developed the CNN models for the target areas based on their own datasets and traditional PLS models was developed to compare their performances. The results show that one dimensional model (1D-CNN) performed strongly for SM prediction with average R2 up to 0.989 and RPIQ up to 19.59 in the laboratory environment (DSSM). Applying the knowledge-based transfer learning method to an unknown target area improved the R2 from 0.845 to 0.983 under the DSSM and from 0.298 to 0.620 under the DSDM, which performed better than data-based spiking calibration method for traditional PLS models. The results show that knowledge-based transfer learning was suitable for SM prediction under different soil background and measurement conditions and can be a promising approach for remotely estimating SM with the increasing amount of soil dataset in the future

Individual risk and prognostic value prediction by machine learning for distant metastasis in pulmonary sarcomatoid carcinoma: a large cohort study based on the SEER database and the Chinese population

BackgroundThis study aimed to develop diagnostic and prognostic models for patients with pulmonary sarcomatoid carcinoma (PSC) and distant metastasis (DM).MethodsPatients from the Surveillance, Epidemiology, and End Results (SEER) database were divided into a training set and internal test set at a ratio of 7 to 3, while those from the Chinese hospital were assigned to the external test set, to develop the diagnostic model for DM. Univariate logistic regression was employed in the training set to screen for DM-related risk factors, which were included into six machine learning (ML) models. Furthermore, patients from the SEER database were randomly divided into a training set and validation set at a ratio of 7 to 3 to develop the prognostic model which predicts survival of patients PSC with DM. Univariate and multivariate Cox regression analyses have also been performed in the training set to identify independent factors, and a prognostic nomogram for cancer-specific survival (CSS) for PSC patients with DM.ResultsFor the diagnostic model for DM, 589 patients with PSC in the training set, 255 patients in the internal and 94 patients in the external test set were eventually enrolled. The extreme gradient boosting (XGB) algorithm performed best on the external test set with an area under the curve (AUC) of 0.821. For the prognostic model, 270 PSC patients with DM in the training and 117 patients in the test set were enrolled. The nomogram displayed precise accuracy with AUC of 0.803 for 3-month CSS and 0.869 for 6-month CSS in the test set.ConclusionThe ML model accurately identified individuals at high risk for DM who needed more careful follow-up, including appropriate preventative therapeutic strategies. The prognostic nomogram accurately predicted CSS in PSC patients with DM