Dose-Duration Reciprocity for G protein activation: Modulation of kinase to substrate ratio alters cell signaling

In animal cells, activation of heterotrimeric G protein signaling generally occurs when the system’s cognate signal exceeds a threshold, whereas in plant cells, both the amount and the exposure time of at least one signal, D-glucose, are used toward activation. This unusual signaling property called Dose-Duration Reciprocity, first elucidated in the genetic model Arabidopsis thaliana, is achieved by a complex that is comprised of a 7-transmembrane REGULATOR OF G SIGNALING (RGS) protein (AtRGS1), a Gα subunit that binds and hydrolyzes nucleotide, a Gβγ dimer, and three WITH NO LYSINE (WNK) kinases. D-glucose is one of several signals such as salt and pathogen-derived molecular patterns that operates through this protein complex to activate G protein signaling by WNK kinase transphosphorylation of AtRGS1. Because WNK kinases compete for the same substrate, AtRGS1, we hypothesize that activation is sensitive to the AtRGS1 amount and that modulation of the AtRGS1 pool affects the response to the stimulant. Mathematical simulation revealed that the ratio of AtRGS1 to the kinase affects system sensitivity to D-glucose, and therefore illustrates how modulation of the cellular AtRGS1 level is a means to change signal-induced activation. AtRGS1 levels change under tested conditions that mimic physiological conditions therefore, we propose a previously-unknown mechanism by which plants react to changes in their environment

A shadow detector for photosynthesis efficiency

Plants tolerate large variations in the intensity of the light environment by controlling the efficiency of solar to chemical energy conversion. To do this, plants have a mechanism to detect the intensity, duration, and change in light as they experience moving shadows, flickering light, and cloud cover. Sugars are the primary products of CO2 fixation, a metabolic pathway that is rate limited by this solar energy conversion. We propose that sugar is a signal encoding information about the intensity, duration and change in the light environment. We previously showed that the Arabidopsis heterotrimeric G protein complex including its receptor-like Regulator of G signaling protein, AtRGS1, detects both the concentration and the exposure time of sugars [Fu, et al 2014 Cell 156: 1084–1095]. This unique property, designated dose-duration reciprocity, is a behavior that emerges from the system architecture / system motif. Here, we show that another property of the signaling system is to detect large changes in light while at the same time, filtering types of fluctuation in light that do not affect photosynthesis efficiency. When AtRGS1 is genetically ablated, photosynthesis efficiency is reduced in a changing-but not a constant-light environment. Mathematical modeling revealed that information about changes in the light environment is encoded in the amount of free AtRGS1 that becomes compartmentalized following stimulation. We propose that this property determines when to adjust photosynthetic efficiency in an environment where light intensity changes abruptly caused by moving shadows on top of a background of light changing gradually from sun rise to sun set and fluctuating light such as that caused by fluttering leaves

A nondestructive method to estimate the chlorophyll content of Arabidopsis seedlings

Abstract Background Chlorophyll content decreases in plants under stress conditions, therefore it is used commonly as an indicator of plant health. Arabidopsis thaliana offers a convenient and fast way to test physiological phenotypes of mutations and treatments. However, chlorophyll measurements with conventional solvent extraction are not applicable to Arabidopsis leaves due to their small size, especially when grown on culture dishes. Results We provide a nondestructive method for chlorophyll measurement whereby the red, green and blue (RGB) values of a color leaf image is used to estimate the chlorophyll content from Arabidopsis leaves. The method accommodates different profiles of digital cameras by incorporating the ColorChecker chart to make the digital negative profiles, to adjust the white balance, and to calibrate the exposure rate differences caused by the environment so that this method is applicable in any environment. We chose an exponential function model to estimate chlorophyll content from the RGB values, and fitted the model parameters with physical measurements of chlorophyll contents. As proof of utility, this method was used to estimate chlorophyll content of G protein mutants grown on different sugar to nitrogen ratios. Conclusion This method is a simple, fast, inexpensive, and nondestructive estimation of chlorophyll content of Arabidopsis seedlings. This method lead to the discovery that G proteins are important in sensing the C/N balance to control chlorophyll content in Arabidopsis

Clinical risk factors of carbohydrate antigen-125, cytokeratin fragment 19, and neuron-specific enolase in liver metastases from elderly lung cancer patients

Objective: Lung cancer is a common malignant tumor characterized by challenging detection and lack of specificity in clinical manifestations. To investigate the correlation of tumor markers in the serum with liver metastasis and prognosis of lung cancer. Methods: A total of 3,046 elderly lung cancer patients were retrospectively studied between September 1999 and July 2020. Divided into liver metastasis group and non-liver metastasis group. We compared a series of serum biomarkers between the two groups of elderly patients to predict the prognosis in patients with lung cancer by fluorescence in situ hybridization (FISH), advanced flow cytometry (FCM) and multi tumor marker protein chip, including tumor markers in the serum included alkaline phosphatase (ALP), serum calcium, hemoglobin (HB), alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cytokeratin fragment 19 (Cyfra21-1), carbohydrate antigen-125 (CA-125), carbohydrate antigen-153 (CA-153), carbohydrate antigen-199 (CA-199), and free prostate specific antigen (free PSA). We used binary logistic regression analysis to determine risk factors, and used receiver operating curve (ROC) analysis to evaluate the diagnostic value of liver metastases in elderly patients with lung cancer. Results: The proportion of lung cancer in the liver metastasis group was higher than that observed in the non-liver metastases group. The expression levels of CA-125, Cyfra21-1, and NSE in the liver metastasis group of lung cancer were significantly higher than those reported in the non-liver metastases group (p < 0.05). ROC curve analysis shows that the area under the curve of CA-125, Cyfra21-1, and NSE are 0.614, 0.616 and 0.608, respectively. The sensitivity and specificity of CA-125 were 45.70% and 76.20%, the sensitivity and specificity of Cyfra21-1 were 60.10% and 57.10%, and the sensitivity and specificity of NSE were 44.10% and 75.00%, respectively. Conclusion: High levels of CA-125, Cyfra21-1, and NSE in the serum may be associated with liver metastasis in elderly patients with lung cancer. CA-125 and NSE are factors influencing the prognosis of elderly patients with liver metastasis of lung cancer

Altered spontaneous brain activity patterns of meibomian gland dysfunction in severely obese population measured using the fractional amplitude of low-frequency fluctuations

Objective: Utilizing the fractional amplitude of low-frequency fluctuations (fALFF) technique, this study sought to correlate spontaneous cerebral abnormalities with the clinical manifestations of meibomian gland dysfunction (MGD) in severely obese (SO) population. Subjects and Methods: Twelve MGD patients in SO population (PATs) (4 males and 8 females) and twelve healthy controls (HCs) (6 males and 6 females) matched by gender and age were enrolled. Every participant underwent resting-state functional magnetic resonance imaging (rs-MRI) scanning. Spontaneous cerebral activity alterations were examined using the fALFF method. Receiver operating characteristic (ROC) curves were utilized to classify the medial fALFF values of the PATs and HCs. PATs were also asked to complete anxiety and depression score forms, permitting a correlation analysis. Results: In contrast with HCs, PATs had prominently increased fALFF values in the left lingual gyrus, the right globus pallidus, the right anterior cingulate and paracingulate gyri and the left middle occipital lobe (P < 0.05), and decreased fALFF values in the right cerebellum, the left fusiform gyrus, the right medial orbitofrontal gyrus, the left triangle inferior frontal gyrus and the left inferior parietal gyrus (P < 0.05). The results of the ROC curve indicated that changes in regional fALFF values might help diagnose MGD in SO population. Moreover, fALFF values in the right cerebellum of PATs were positively correlated with hospital anxiety and depression scores (HADS) (r = 0.723, P = 0.008). The fALFF values in the left triangle inferior frontal gyrus of PAT were negatively correlated with HADS (r = −0.651, P = 0.022). Conclusions: Aberrant spontaneous activity was observed in multiple regions of the cerebrum, offering helpful information about the pathology of MGD in SO population. Aberrant fALFF values in these regions likely relates to the latent pathologic mechanisms of anomalous cerebral activities in PATs

Potential factors of cytokeratin fragment 21-1 and cancer embryonic antigen for mediastinal lymph node metastasis in lung cancer

Objective: Lung cancer is a common malignant tumor, characterized by being difficult to detect and lacking specific clinical manifestations. This study aimed to find out the risk factors of mediastinal lymph node metastasis and explore the correlation between serum tumor markers and mediastinal lymph node metastasis and lung cancer prognosis. Methods: A retrospective study of 3,042 lung cancer patients (330 patients with mediastinal lymph node metastasis and 2,712 patients without mediastinal lymph node metastasis) collected from the First Affiliated Hospital of Nanchang University from April 1999 to July 2020. The patients were divided into two groups, namely, mediastinal lymph node metastasis group and non-mediastinal lymph node metastasis group. Student’s t test, non-parametric rank sum test and chi-square test were used to describe whether there is a significant difference between the two groups. We compared the serum biomarkers of the two groups of patients, including exploring serum alkaline phosphatase (ALP), calcium hemoglobin (HB), alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), CA125, CA-199, CA -153, cytokeratin fragment 19 (CYFRA 21-1), total prostate specific antigen (TPSA), neuron-specific enolase (NSE) levels and the incidence and prognosis of lung cancer mediastinal lymph node metastasis. Binary logistic regression analysis was used to determine its risk factors, and receiver operating curve (ROC) analysis was used to evaluate its diagnostic value for mediastinal lymph node metastasis. Results: Binary logistic regression analysis showed that carcinoembryonic antigen and CYFRA 21-1 were independent risk factors for mediastinal lymph node metastasis in patients with lung cancer (p < 0.001 and p = 0.002, respectively). The sensitivity and specificity of CEA for the diagnosis of mediastinal lymph node metastasis were 90.2 and 7.6%, respectively; CYFRA 21-1 were 0.6 and 99.0%, respectively. Conclusion: Serum CEA and CYFRA 21-1 have predictive value in the diagnosis of mediastinal lymph node metastasis in patients with lung cancer

MicroRNAs in pulmonary arterial remodeling

Pulmonary arterial remodeling is a presently irreversible pathologic hallmark of pulmonary arterial hypertension (PAH). This complex disease involves pathogenic dysregulation of all cell types within the small pulmonary arteries contributing to vascular remodeling leading to intimal lesions, resulting in elevated pulmonary vascular resistance and right heart dysfunction. Mutations within the bone morphogenetic protein receptor 2 gene, leading to dysregulated proliferation of pulmonary artery smooth muscle cells, have been identified as being responsible for heritable PAH. Indeed, the disease is characterized by excessive cellular proliferation and resistance to apoptosis of smooth muscle and endothelial cells. Significant gene dysregulation at the transcriptional and signaling level has been identified. MicroRNAs are small non-coding RNA molecules that negatively regulate gene expression and have the ability to target numerous genes, therefore potentially controlling a host of gene regulatory and signaling pathways. The major role of miRNAs in pulmonary arterial remodeling is still relatively unknown although research data is emerging apace. Modulation of miRNAs represents a possible therapeutic target for altering the remodeling phenotype in the pulmonary vasculature. This review will focus on the role of miRNAs in regulating smooth muscle and endothelial cell phenotypes and their influence on pulmonary remodeling in the setting of PAH

Prediction model of ocular metastasis from primary liver cancer: Machine learning‐based development and interpretation study

Background: Ocular metastasis (OM) is a rare metastatic site of primary liver cancer (PLC). The purpose of this study was to establish a clinical predictive model of OM in PLC patients based on machine learning (ML). Methods: We retrospectively collected the clinical data of 1540 PLC patients and divided it into a training set and an internal test set in a 7:3 proportion. PLC patients were divided into OM and non‐ocular metastasis (NOM) groups, and univariate logistic regression analysis was performed between the two groups. The variables with univariate logistic analysis p < 0.05 were selected for the ML model. We constructed six ML models, which were internally verified by 10‐fold cross‐validation. The prediction performance of each ML model was evaluated by receiver operating characteristic curves (ROCs). We also constructed a web calculator based on the optimal performance ML model to personalize the risk probability for OM. Results: Six variables were selected for the ML model. The extreme gradient boost (XGB) ML model achieved the optimal differential diagnosis ability, with an area under the curve (AUC) = 0.993, accuracy = 0.992, sensitivity = 0.998, and specificity = 0.984. Based on these results, an online web calculator was constructed by using the XGB ML model to help clinicians diagnose and treat the risk probability of OM in PLC patients. Finally, the Shapley additive explanations (SHAP) library was used to obtain the six most important risk factors for OM in PLC patients: CA125, ALP, AFP, TG, CA199, and CEA. Conclusion: We used the XGB model to establish a risk prediction model of OM in PLC patients. The predictive model can help identify PLC patients with a high risk of OM, provide early and personalized diagnosis and treatment, reduce the poor prognosis of OM patients, and improve the quality of life of PLC patients