Production of Bio-Energy from Pig Manure: A Focus on the Dynamics Change of Four Parameters under Sunlight-Dark Conditions

This study investigated the effect of sunlight-dark conditions on volatile fatty acids (VFAs), total ammonium nitrogen (TAN), total alkalinity (TA) and pH during pig manure (PM) digestion and then the subsequent influence on biogas yield of PM. PM₁ and PM₂ were performed in a transparent reactor and a non-transparent reactor, respectively. Two sets of experiments were conducted with a temperature of 35.0±2.0 °C and a total solid concentration of 8.0% to the digestion material. The dynamic change of the four parameters in response to sunlight-dark conditions resulted in variations of the physiological properties in the digester and affected the cumulative biogas production (CBP). PM₁ obtained higher CBP (15020.0 mL) with a more stable pH and a lower TAN concentration (1414.5 mg/L) compared to PM₂ (2675.0 mL and 1670.0 mg/L, respectively). The direct path coefficients and indirect path coefficients between the four parameters and CBP were also analyzed.     

Phosphorylation and ubiquitination of dynamin-related proteins (AtDRP3A/3B) synergically regulate mitochondrial proliferation during mitosis

The balance between mitochondrial fission and fusion is disrupted during mitosis, but the mechanism governing this phenomenon in plant cells remains enigmatic. Here, we used mitochondrial matrix‐localized Kaede protein (mt‐Kaede) to analyze the dynamics of mitochondrial fission in BY‐2 suspension cells. Analysis of the photoactivatable fluorescence of mt‐Kaede suggested that the fission process is dominant during mitosis. This finding was confirmed by an electron microscopic analysis of the size distribution of mitochondria in BY‐2 suspension cells at various stages. Cellular proteins interacting with Myc‐tagged dynamin‐related protein 3A/3B (AtDRP3A and AtDRP3B) were immunoprecipitated with anti‐Myc antibody‐conjugated beads and subsequently identified by microcapillary liquid chromatography–quadrupole time‐of‐flight mass spectrometry (CapLC Q‐TOF) MS/MS. The identified proteins were broadly associated with cytoskeletal (microtubular), phosphorylation, or ubiquitination functions. Mitotic phosphorylation of AtDRP3A/AtDRP3B and mitochondrial fission at metaphase were inhibited by treatment of the cells with a CdkB/cyclin B inhibitor or a serine/threonine protein kinase inhibitor. The fate of AtDRP3A/3B during the cell cycle was followed by time‐lapse imaging of the fluorescence of Dendra2‐tagged AtDRP3A/3B after green‐to‐red photoconversion; this experiment showed that AtDRP3A/3B is partially degraded during interphase. Additionally, we found that microtubules are involved in mitochondrial fission during mitosis, and that mitochondria movement to daughter cell was limited as early as metaphase. Taken together, these findings suggest that mitotic phosphorylation of AtDRP3A/3B promotes mitochondrial fission during plant cell mitosis, and that AtDRP3A/3B is partially degraded at interphase, providing mechanistic insight into the mitochondrial morphological changes associated with cell‐cycle transitions in BY‐2 suspension cells.     

A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy

We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing ‘slide-level’ diagnosis by using individual ‘cell-level’ diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform.