Analysis of groundwater ion abnormality and its cause of centralized drinking water sources in Jieshou City, China

Groundwater provides drinking water to city and rural residents; which is also one of the chief water sources for commercial and agricultural activities in Jieshou City. We collected and analyzed the samples of 18 underground water source wells in Jieshou. We investigated whether the water was of acceptable quality and had characteristics that exceeded the standard. This study was conducted to determine the chemical characteristics of groundwater and abnormally high super-standard ions found in groundwater. The hydrogeological conditions of the study area were analyzed through data collection; through sample collection and sample testing, the characteristics and types of water chemistry were analyzed by means of mathematical statistics analysis and the Piper chart. The genesis of water chemistry was discussed using the Gibbs chart and correlation analysis; the proportional coefficient of ion molar concentration was used to judge the source, origin, and forming process of groundwater chemical composition. The results show that the groundwater is classified as marginally alkaline water, with a composition of Na-HCO3. The cations are mainly Na+, and the anions are mainly HCO3−. According to the Ⅲ water standard of groundwater quality standard and comparing the content of each ion, Na+ and F− are the primary abnormal super-standard ions, and ions and compounds are the main occurrence states. The concentrations of Na+ and F− exceed the standard for class Ⅲ water. There was a positive correlation between the abnormal Na+ and F−, and the concentration of F− increased with the increase in monitoring depth. The causes of abnormal ions were mainly determined by the lithology of the aquifer in the study area, and most of them are fluorine-containing rocks, which are transferred into groundwater through leaching or hydration. The enrichment of Na+ and F− is influenced by the local primary geological setting, hydrochemical type, hydrogeological conditions, pH and artificial activities, and the primary geological setting is the main influencing factor

Neural Population-Level Memory Traces in the Mouse Hippocampus

One of the fundamental goals in neurosciences is to elucidate the formation and retrieval of brain's associative memory traces in real-time. Here, we describe real-time neural ensemble transient dynamics in the mouse hippocampal CA1 region and demonstrate their relationships with behavioral performances during both learning and recall. We employed the classic trace fear conditioning paradigm involving a neutral tone followed by a mild foot-shock 20 seconds later. Our large-scale recording and decoding methods revealed that conditioned tone responses and tone-shock association patterns were not present in CA1 during the first pairing, but emerged quickly after multiple pairings. These encoding patterns showed increased immediate-replay, correlating tightly with increased immediate-freezing during learning. Moreover, during contextual recall, these patterns reappeared in tandem six-to-fourteen times per minute, again correlating tightly with behavioral recall. Upon traced tone recall, while various fear memories were retrieved, the shock traces exhibited a unique recall-peak around the 20-second trace interval, further signifying the memory of time for the expected shock. Therefore, our study has revealed various real-time associative memory traces during learning and recall in CA1, and demonstrates that real-time memory traces can be decoded on a moment-to-moment basis over any single trial

Perioperative nutritional risk and its influencing factors in patients with oral cancer: a longitudinal study

IntroductionWe aimed to investigate the nutritional risk status and dynamic changes in patients with perioperative oral cancer at different stages and analyze the factors influencing nutritional risk and the correlation among body mass index, nutrition-related symptoms, and nutritional risk.MethodsIn total, 198 patients with oral cancer who were hospitalized in the Head & Neck Surgery Departments of a tertiary cancer hospital in Hunan Province, China, from May 2020 to January 2021, were selected as participants. The Nutritional Risk Screening 2002 scale and Head and Neck Patient Symptom Checklist were used to assess patients on admission day, 7 days post-surgery, and 1 month post-discharge. Multivariate analysis of variance, paired t-test, and generalized estimating equation were used to analyze the trajectory and influencing factors of nutritional risk in patients with perioperative oral cancer. Spearman’s correlation analysis was used to explore the correlation among body mass index, symptoms, and nutritional risk.ResultsThe nutritional risk scores of patients with oral cancer at the three time points were 2.30 ± 0.84, 3.21 ± 0.94, and 2.11 ± 0.84, respectively, and the differences were significant (p < 0.05). The incidences of nutritional risk were 30.3, 52.5, and 37.9%, respectively. The factors influencing nutritional risk included education level, smoking status, clinical stage, flap repair, and tracheotomy (β = −0.326, 0.386, 0.387, 0.336, and 0.240, respectively, p < 0.05). Nutritional risk was negatively correlated with body mass index (rs = −0.455, p < 0.01) and positively correlated with pain, loss of appetite, sore mouth, bothersome smells, swallowing difficulty, taste changes, depression, chewing difficulty, thick saliva, and anxiety (rs = 0.252, 0.179, 0.269, 0.155, 0.252, 0.212, 0.244, 0.384, 0.260, and 0.157, respectively, p < 0.05).ConclusionThe incidence of nutritional risk in patients with perioperative oral cancer was high, and the trajectory of nutritional risk changed over time. Strengthening the nutritional monitoring and management of postoperative patients or those with low education level, advanced-stage cancer, flap repair, tracheotomy, and low body mass index; strengthening tobacco control management; and controlling nutrition-related discomfort symptoms in perioperative oral cancer patients are necessary

Mesoscale eddy modulation of subsurface chlorophyll maximum layers in the South China Sea

Subsurface chlorophyll maximum (SCM) layers contribute considerably to the integrated biomass of the water column and can be strongly modulated by mesoscale eddies that are ubiquitous in the global ocean. The mechanisms of eddy-induced surface chlorophyll concentration have been extensively examined in the South China Sea (SCS). However, the potential impact of mesoscale eddies on SCM layers remains unclear. We examined the influence of mesoscale eddies on the depth, thickness and magnitude of SCM layers in the SCS using output from an eddy-permitting biological–physical coupled model over a 22-year period. Our study shows that nutrient distribution is largely driven by eddy dynamics, with cyclonic eddies enhancing the supply of inorganic nutrients in the upper layers by uplifting the thermocline, and downward displacement of the thermocline in anticyclonic eddies, reducing the nutrient supply into the euphotic zone from the depth. We found that anticyclonic (cyclonic) eddies are responsible for increased (decreased) SCM depth and decreased (increased) SCM magnitude; SCM thickness decreased in cyclonic eddies but slightly increased in anticyclonic eddies. The effects of mesoscale eddies depend on eddy amplitude. Maximal anomalies in depth, thickness and magnitude always occur near the center of eddies. Phytoplankton community structure at SCM layers is also affected by eddies, with more diatoms in cyclonic eddies and more coccolithophores in anticyclonic eddies. Our study will advance our understanding of mesoscale physical–biogeochemical interactions

Considering Genetic Heterogeneity in the Association Analysis Finds Genes Associated With Nicotine Dependence

While substantial progress has been made in finding genetic variants associated with nicotine dependence (ND), a large proportion of the genetic variants remain undiscovered. The current research focuses have shifted toward uncovering rare variants, gene-gene/gene-environment interactions, and structural variations predisposing to ND, the impact of genetic heterogeneity in ND has been nevertheless paid less attention. The study of genetic heterogeneity in ND not only could enhance the power of detecting genetic variants with heterogeneous effects in the population but also improve our understanding of genetic etiology of ND. As an initial step to understand genetic heterogeneity in ND, we applied a newly developed heterogeneity weighted U (HWU) method to 26 ND-related genes, investigating heterogeneous effects of these 26 genes in ND. We found no strong evidence of genetic heterogeneity in genes such as CHRNA5. However, results from our analysis suggest heterogeneous effects of CHRNA6 and CHRNB3 on nicotine dependence in males and females. Following the gene-based analysis, we further conduct a joint association analysis of two gene clusters, CHRNA5-CHRNA3-CHRNB4 and CHRNB3-CHRNA6. While both CHRNA5-CHRNA3-CHRNB4 and CHRNB3-CHRNA6 clusters are significantly associated with ND, there is a much stronger association of CHRNB3-CHRNA6 with ND when considering heterogeneous effects in gender (p-value = 2.11E-07)

Dynamic genome evolution in a model fern

The large size and complexity of most fern genomes have hampered efforts to elucidate fundamental aspects of fern biology and land plant evolution through genome-enabled research. Here we present a chromosomal genome assembly and associated methylome, transcriptome and metabolome analyses for the model fern species Ceratopteris richardii. The assembly reveals a history of remarkably dynamic genome evolution including rapid changes in genome content and structure following the most recent whole-genome duplication approximately 60 million years ago. These changes include massive gene loss, rampant tandem duplications and multiple horizontal gene transfers from bacteria, contributing to the diversification of defence-related gene families. The insertion of transposable elements into introns has led to the large size of the Ceratopteris genome and to exceptionally long genes relative to other plants. Gene family analyses indicate that genes directing seed development were co-opted from those controlling the development of fern sporangia, providing insights into seed plant evolution. Our findings and annotated genome assembly extend the utility of Ceratopteris as a model for investigating and teaching plant biology

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Research on Intelligent Decision of Pulmonary Tuberculosis Disease Based on Data Mining

International audienceAiming at the problem that the low diagnostic efficiency and low accuracy of the single data mining method for Diagnosis of pulmonary tuberculosis, In this study, the electronic records of 1203 cases of tuberculosis patients in Changping District City, Beijing City of Beijng and Beijing Institute of tuberculosis control and tuberculosis control were build, Tuberculosis disease diagnosis model is built by application of rough set and decision tree method, On the basis of this, the diagnosis system of pulmonary tuberculosis was constructed. In this study, the combining method of rough set and decision tree was approached to attribute reduction, the model reduced redundant 57 attributes and remained 22 attributes, and articled 7 the decision rules. The model accuracy is 89.46%. Compared with the non reduction method, the decision rule was reduced by 128%, and the accuracy of the model remained unchanged. The research results showed that the algorithm can reduce the time and space complexity of the algorithm while ensuring the accuracy of the model, so as to improve the efficiency of the mining, and provide some references for clinical diagnosis