Identification of a c-type heme oxygenase and its function during acclimation of cyanobacteria to nitrogen fluctuations.

The mechanisms of acclimating to a nitrogen-fluctuating environment are necessary for the survival of aquatic cyanobacteria in their natural habitats, but our understanding is still far from complete. Here, the synthesis of phycobiliprotein is confirmed to be much earlier than that of photosystem components during recovery from nitrogen chlorosis and an unknown protein Ssr1698 is discovered to be involved in this synthetic process. The unknown protein is further identified as a c-type heme oxygenase (cHO) in tetrapyrrole biosynthetic pathway and catalyzes the opening of heme ring to form biliverdin IXα, which is required for phycobilin production and ensuing phycobiliprotein synthesis.

Identification of distinct clinical phenotypes of acute respiratory distress syndrome with differential responses to treatment.

Background: Acute respiratory distress syndrome (ARDS) is a heterogeneous syndrome, and the identification of homogeneous subgroups and phenotypes is the first step toward precision critical care. We aimed to explore whether ARDS phenotypes can be identified using clinical data, are reproducible and are associated with clinical outcomes and treatment response.

Methods: This study is based on a retrospective analysis of data from the telehealth intensive care unit (eICU) collaborative research database and three ARDS randomized controlled trials (RCTs) (ALVEOLI, FACTT and SAILS trials).

Pathways and Kinetics for Autocatalytic Reduction of CO into Formic Acid with Fe under Hydrothermal Conditions.

The utilization of CO, as a cheap and abundant carbon source to produce useful chemicals or fuels, has been regarded as one of the promising ways to reduce CO emissions and minimize the green-house effect. Previous studies have demonstrated that CO (or HCO ) can be efficiently reduced to formic acid with metal Fe under hydrothermal conditions without additional hydrogen and any catalyst. However, the pathways and kinetics of the autocatalytic CO reduction remain unknown.

Degradation of PVC waste into a flexible polymer by chemical modification using DINP moieties.

In consideration of the toxicity and high migration capacity of plasticizers, the possibility to obtain flexible PVC chemical modification of PVC was investigated for feedstock recycling. In this work, some Cl atoms of PVC were substituted with fragments of the common plasticizer DINP (diisononyl phthalate) in the presence of KCO (potassium carbonate) or DIEA (,-diisopropylethylamine), and the simultaneous elimination of PVC was suppressed. H NMR (H nuclear magnetic resonance spectroscopy) and H-H COSY (H-H correlation spectroscopy) were used to evaluate the substitution while a novel method of calculating the substitution and elimination ratios was developed using a combination of H NMR and elemental analysis.

Controlling the selectivity to chemicals from catalytic depolymerization of kraft lignin with in-situ H.

Catalytic depolymerization of kraft lignin was successfully carried out in isopropanol/water mixture system over Rh/LaO/CeO-ZrO catalyst at 373 °C for 2 h with Fe as reductant. The selectivity of in-situ H was increasing from 67 wt% to 98 wt% by changing the proportion of isopropanol and water with metal Fe. A one-to-one correspondence was established between liquid products distribution and H.

A hybrid solution for extracting structured medical information from unstructured data in medical records via a double-reading/entry system.

Background: Healthcare providers generate a huge amount of biomedical data stored in either legacy system (paper-based) format or electronic medical records (EMR) around the world, which are collectively referred to as big biomedical data (BBD). To realize the promise of BBD for clinical use and research, it is an essential step to extract key data elements from unstructured medical records into patient-centered electronic health records with computable data elements. Our objective is to introduce a novel solution, known as a double-reading/entry system (DRESS), for extracting clinical data from unstructured medical records (MR) and creating a semi-structured electronic health record database, as well as to demonstrate its reproducibility empirically.