High-Throughput Screening of Acyl-CoA Thioesterase I Mutants Using a Fluid Array Platform

Screening target microorganisms from a mutated recombinant library plays a crucial role in advancing synthetic biology and metabolic engineering. However, conventional screening tools have several limitations regarding throughput, cost, and labor. Here, we used the fluid array platform to conduct high-throughput screening (HTS) that identified Escherichia coli ???TesA thioesterase mutants producing elevated yields of free fatty acids (FFAs) from a large (106) mutant library. A growth-based screening method using a TetA-RFP fusion sensing mechanism and a reporter-based screening method using high-level FFA producing mutants were employed to identify these mutants via HTS. The platform was able to cover >95% of the mutation library, and it screened target cells from many arrays of the fluid array platform so that a post-analysis could be conducted by gas chromatography. The ???TesA mutation of each isolated mutant showing improved FFA production in E. coli was characterized, and its enhanced FFA production capability was confirmed

Inhomogeneous Defect Distribution in Mixed-Polytype Metal Halide Perovskites

The competition between corner, edge and face-sharing octahedral networks is a cause of phase inhomogeneity in metal halide perovskite thin-films. Here we probe the charged iodine vacancy distribution and transport at the junction between cubic and hexagonal polytypes of CsPbI$_3$ from first-principles materials modelling. We predict a lower defect formation energy in the face-sharing regions, which correlates with a longer Pb$-$I bond length and causes a million-fold increase in local defect concentration. These defects are predicted to be more mobile in the face-sharing regions with a reduced activation energy for vacancy-mediated diffusion. We conclude that hexagonal phase inclusions or interfaces will act as defect sinks that could trap charges and enhance current-voltage hysteresis in perovskite-based solar cells and electrical devices

Synchronous double primary malignant tumor of the gallbladder and liver: a case report

We report a case of synchronous double primary tumor of gallbladder and liver. A 63-year-old male was admitted to the hospital complaining of abdominal discomfort. Enhanced computed tomography of the abdomen showed acute cholecystitis with tiny gallbladder stones and a 2.2 cm size enhanced nodule in the left lobe of the liver. Under the impression of acute cholecystitis with gall bladder stones and hepatocellular carcinoma of the left Liver, the patient underwent a laparotomy. At laparotomy, a mass was palpated on the surface of the neck portion of the gall bladder. Intraoperative frozen diagnosis revealed adenocarcinoma of the gall bladder. The patient was diagnosed as having gall bladder cancer and hepatocellular carcinoma, so extended cholecystectomy with dissection of regional lymph nodes and left hemihepatectomy were performed. Histological examination revealed moderated differentiated adenocarcinoma of gallbladder and hepatocellular carcinoma of liver. To our knowledge, the simultaneous occurrence of primary malignant tumor of the gallbladder and liver has never been published before. The patient is doing well with no evidence of recurrence 17 months after surgery

Improvement of retinoids production in recombinant E. coli using glyoxylic acid

Isoprenoids are the most chemically diverse compounds found in nature. They are present in all organisms and have essential roles in membrane structure, redox chemistry, reproductive cycles, growth regulation, signal transduction and defense mechanisms. In spite of their diversity of functions and structures, all isoprenoids are derived from the common building blocks of isopentenyl diphosphate (IPP) and its isomer dimethylallyl diphosphate (DMAPP). Optimization of IPP synthesis pathway is of benefit to mass production of various isoprenoids. There are two pathways of 2-C-Methyl-D-erythritol-4-phosphate (MEP) and mevalonate (MVA) for IPP synthesis. Prokaryotes including E. coli generally use MEP pathway whereas MVA pathway is used in eukaryotes. To improve isoprenoid production, it was performed the deletion of genes in E. coli, which are involved in both formation of fermentation by-products such as organic acids and alcohols, and consumption of precursors of MEP and MVA pathways, pyruvate and acetyl-CoA. As a result, we were able to develop a strain with improved fermentation productivity and carbon source utilization efficiency, the mutant strain was called AceCo. Higher lycopene production was achieved in the AceCo strain compared to the wild type MG1655 strain due to no formation of the inhibitory by-products. However, retinoids production of AceCo strain decreased to a half of that of MG1655 strain. Please click Additional Files below to see the full abstract

Influence of Mg Deficiency on the Superconductivity in MgB2 Thin Films Grown by using HPCVD

The effects of Mg deficiency in MgB2 films grown by using hybrid physical-chemical vapor deposition were investigated after vacuum annealing at various temperatures. High-quality MgB2 films grown on c-cut Al2O3 substrates with different superconducting transition temperatures (Tc) of 40.2 and 41 K were used in this study. As the annealing temperature was increased from 200 to 800 C, the Mg contents in the MgB2 films systemically decreased, but the Tc's did not change, within 0.12 K, until the annealing temperature reached 700 C. For MgB2 films annealed at 800 C for 30 min, however, no superconductivity was observed, and the temperature dependence of the resistivity showed a semiconducting behavior. We also found that the residual resistivity ratio decreased with increasing annealing temperature.Comment: 7 pages including 4 figure

Distribution of Abdominal Obesity and Fitness Level in Overweight and Obese Korean Adults

Background. Abdominal obesity and its relative distribution are known to differ in association with metabolic characteristics and cardiorespiratory fitness. This study aimed to determine an association between fitness level and abdominal adiposity in overweight and obese adults. Methods. 228 overweight and obese individuals were classified as either cardiorespiratory unfit or fit based on their recovery heart rate. Visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), the visceral-to-subcutaneous adipose tissue ratio (VAT/SAT ratio), and cardiometabolic characteristics were analyzed to examine the relationship between recovery heart rate and abdominal adiposity components. Results. After adjustments for age and sex, significant relationships of recovery heart rate and VAT, SAT, and VAT/SAT ratio were found; however, SAT was not significantly associated after further adjustment for body mass index (BMI) (r=0.045, P=0.499), whereas VAT (r=0.232, P<0.001) and VAT/SAT ratio (r=0.214, P=0.001) remained associated. Through stepwise multiple regression analyses after adjustment for age, sex, BMI, lifestyle factors, mean blood pressure, fasting glucose, HOMA-IR, lipid profiles, and hsCRP, recovery heart rate was identified as an independent variable associated with VAT (β=0.204, P<0.001) and VAT/SAT ratio (β=0.163, P=0.008) but not with SAT (β=0.097, P=0.111). Conclusions. Cardiorespiratory fitness level is independently associated with VAT and the VAT/SAT ratio but not with SAT in overweight and obese adults

Brain-Driven Representation Learning Based on Diffusion Model

Interpreting EEG signals linked to spoken language presents a complex challenge, given the data's intricate temporal and spatial attributes, as well as the various noise factors. Denoising diffusion probabilistic models (DDPMs), which have recently gained prominence in diverse areas for their capabilities in representation learning, are explored in our research as a means to address this issue. Using DDPMs in conjunction with a conditional autoencoder, our new approach considerably outperforms traditional machine learning algorithms and established baseline models in accuracy. Our results highlight the potential of DDPMs as a sophisticated computational method for the analysis of speech-related EEG signals. This could lead to significant advances in brain-computer interfaces tailored for spoken communication