Audiovisual n-Back Training Alters the Neural Processes of Working Memory and Audiovisual Integration: Evidence of Changes in ERPs

(1) Background: This study investigates whether audiovisual n-back training leads to training effects on working memory and transfer effects on perceptual processing. (2) Methods: Before and after training, the participants were tested using the audiovisual n-back task (1-, 2-, or 3-back), to detect training effects, and the audiovisual discrimination task, to detect transfer effects. (3) Results: For the training effect, the behavioral results show that training leads to greater accuracy and faster response times. Stronger training gains in accuracy and response time using 3- and 2-back tasks, compared to 1-back, were observed in the training group. Event-related potentials (ERPs) data revealed an enhancement of P300 in the frontal and central regions across all working memory levels after training. Training also led to the enhancement of N200 in the central region in the 3-back condition. For the transfer effect, greater audiovisual integration in the frontal and central regions during the post-test rather than pre-test was observed at an early stage (80-120 ms) in the training group. (4) Conclusion: Our findings provide evidence that audiovisual n-back training enhances neural processes underlying a working memory and demonstrate a positive influence of higher cognitive functions on lower cognitive functions

Soil Moisture Retrieval Using SAR Backscattering Ratio Method during the Crop Growing Season

Soil moisture content (SMC) is an indispensable basic element for crop growth and development in agricultural production. Obtaining accurate information on SMC in real time over large agricultural areas has important guiding significance for crop yield estimation and production management. In this study, the paper reports on the retrieval of SMC from RADARSAT-2 polarimetric SAR data. The proposed SMC retrieval algorithm includes vegetation correction based on a ratio method and roughness correction based on the optimal roughness method. Three vegetation description parameters (i.e., RVI, LAI, and NDVI) serve as vegetation descriptors in the parameterization of the algorithm. To testify the vegetation correction result of the algorithm, the water cloud model (WCM) was compared with the algorithm. The calibrated integrated equation model (CIEM) was employed to describe the backscattering from the underlying soil. To improve the accuracy of SMC retrieval, the CIEM model was optimized by using the optimal roughness parameter and the normalization method of reference incidence angle. Validation against ground measurements showed a high correlation between the measured and estimated SMC when the NDVI serves as vegetation descriptor (R2 = 0.68, RMSE = 4.15 vol.%, p < 0.01). The overall estimation performance of the proposed SMC retrieval algorithm is better than that of the WCM. It demonstrates that the proposed algorithm has an operational potential to estimate SMC over wheat fields during the growing season

Estimating Soil Moisture over Winter Wheat Fields during Growing Season Using RADARSAT-2 Data

Soil moisture content (SMC) is a significant factor affecting crop growth and development. However, SMC estimation, based on synthetic aperture radar (SAR), is influenced by a variety of surface parameters, such as vegetation cover and surface roughness. As a result, determining the SMC across agricultural areas (e.g., wheat fields) remotely (i.e., without ground measurement) is difficult to achieve. In this study, a model-based polarization decomposition method was used to decompose the original SAR signal into different scattering components that represented different scattering mechanisms. The different volume scattering models were applied, and then the results were compared in order to remove the scattering contribution from vegetation canopy, and extract the surface scattering components related to the soil moisture. Finally, by combining extensively used surface scattering models (e.g., CIEM and Dubois), and a method of roughness parameters optimization, a lookup table was developed to estimate the soil moisture during the wheat growth period. When CIEM is applied, the R2 and RMSE of the SMC are 0.534, 5.62 vol.%, and for the Dubois model, 0.634, 5.16 vol.%, respectively, which indicates that this approach provides good estimation performance for measuring soil moisture during the wheat growing season

CPT1A promotes anoikis resistance in esophageal squamous cell carcinoma via redox homeostasis

Anoikis resistance was a prominent hallmark of cancer metastasis, and lipo-genic characteristics have been identified as another metabolic alteration during tumorigenesis. However, their crosstalk has not been fully elucidated, especially in advanced esophageal squamous cell carcinoma (ESCC). In this study, we showed, for the first time, that the key enzyme carnitine O-palmitoyl transferase 1 (CPT1A), which is involved in fatty acid oxidation (FAO), was markedly upregulated in ESCC cells upon detached culture via a metabolism PCR array. Overexpression of CPT1A was associated with poor survival of ESCC patients and could protect ESCC cells from apoptosis via maintaining redox homeostasis through supply of GSH and NADPH. Mechanistically, detached culture conditions enhanced the expression of the transcription factor ETV4 and suppressed the expression of the ubiquitin enzyme RNF2, which were responsible for the elevated expression of CPT1A at the mRNA and protein levels, respectively. Moreover, genetic or pharmacologic disruption of CPT1A switched off the NADPH supply and therefore prevented the anchorage-independent growth of ESCC cells in vitro and lung metastases of xenografted tumor models in vivo. Collectively, our results provide novel insights into how ESCC cancer cells exploit metabolic switching to form distant metastases and some evidence for the link between anoikis and FAO

Cytokine and Antibody Based Diagnostic Algorithms for Sputum Culture-Positive Pulmonary Tuberculosis.

Tuberculosis (TB) is one of the most serious infectious diseases globally and has high mortality rates. A variety of diagnostic tests are available, yet none are wholly reliable. Serum cytokines, although significantly and frequently induced by different diseases and thus good biomarkers for disease diagnosis and prognosis, are not sufficiently disease-specific. TB-specific antibody detection, on the other hand, has been reported to be highly specific but not sufficiently sensitive. In this study, our aim was to improve the sensitivity and specificity of TB diagnosis by combining detection of TB-related cytokines and TB-specific antibodies in peripheral blood samples.TB-related serum cytokines were screened using a human cytokine array. TB-related cytokines and TB-specific antibodies were detected in parallel with microarray technology. The diagnostic performance of the new protocol for active TB was systematically compared with other traditional methods.Here, we show that cytokines I-309, IL-8 and MIG are capable of distinguishing patients with active TB from healthy controls, patients with latent TB infection, and those with a range of other pulmonary diseases, and that these cytokines, and their presence alongside antibodies for TB-specific antigens Ag14-16kDa, Ag32kDa, Ag38kDa and Ag85B, are specific markers for active TB. The diagnostic protocol for active TB developed here, which combines the detection of three TB-related cytokines and TB-specific antibodies, is highly sensitive (91.03%), specific (90.77%) and accurate (90.87%).Our results show that combining detection of TB-related cytokines and TB-specific antibodies significantly enhances diagnostic accuracy for active TB, providing greater accuracy than conventional diagnostic methods such as interferon gamma release assays (IGRAs), TB antibody Colloidal Gold Assays and microbiological culture, and suggest that this diagnostic protocol has potential for clinical application

Additional file 1 of PACS-2 deficiency in tubular cells aggravates lipid-related kidney injury in diabetic kidney disease

Additional file 1: Fig. S1. The expression of PACS-2 in other organs of two groups of Mice. (A and B) Western blot and quantification of PACS-2 in the heart, skeletal muscle and liver of Pacs-2fl/fl mice and PT-Pacs-2-/- mice. ns, not significant. n = 4. Fig. S2. Gene silencing of PACS-2 increases the expression of SOAT1 in HK-2 cells. (A and B) A representative western blot and quantification of PACS-2 and SOAT1 in HK-2 cells under control environment. *p < 0.05, **p < 0.01. n = 4

Additional file 2 of PACS-2 deficiency in tubular cells aggravates lipid-related kidney injury in diabetic kidney disease

Additional file 2: Table S1. The sequences of primer pairs