Antimicrobial Activity and Synergistic Effect of Cinnamon with Sodium Benzoate or Potassium Sorbate in Controlling Escherichia coli O157:H7 in Apple Juice

ABSTRACT: Antimicrobial effects of cinnamon, sodium benzoate, potassium sorbate, and combinations were examined against Escherichia coli O157:H7 in apple juice at 8°C and 25°C. E. coli O157:H7 was reduced by 1.6 log colony-forming units (CFU)/mL at 8°C and 2.0 log CFU/mL at 25°C by 0.3% cinnamon. At 8°C, 5.2 log CFU/mL of E. coli O157:H7 was eliminated in 11 d by 0.3% cinnamon with 0.1% sodium benzoate, and in 14 d by 0.3% cinnamon with 0.1% potassium sorbate. At 25°C, 5.3 log CFU/mL E. coli O157:H7 was eliminated in 3 d by the same combinations. A synergistic effect was observed between cinnamon and preservatives against E. coli O157:H7 at 8°C and 25°C.     

Single-Nucleotide Variations,Insertions/Deletions and Copy Number Variations in Myelodysplastic Syndrome during Disease Progression Revealed by a Single-Cell DNA Sequencing Platform

Simple SummaryMyelodysplastic syndrome (MDS) is a myeloid neoplasm associated with complex clonal architecture. The application of single-cell sequencing is capable of revealing the clonal dynamics of MDS during disease progression and treatment resistance. This has advantages over bulk-tumor sequencing which is limited by its resolution. In this study, we evaluated two patients with MDS for the clonal dynamics of pathogenic mutations at the single-cell level of disease progression and resistance to hypomethylating agents (HMAs). There were two key observations. First, changes in the clonal heterogeneity of the pathogenic FLT3-ITD, IDH2, EZH2, or GATA2 mutations was associated with disease progression and resistance to HMA. Secondly, disease progression and resistance to HMA was accompanied by the acquisition of copy number variations of DNMT3A, TET2, and GATA2.AbstractMyelodysplastic syndrome (MDS) is a clonal myeloid neoplasm characterized by ineffective hematopoiesis, cytopenia, dysplasia, and clonal instability, leading to leukemic transformation. Hypomethylating agents are the mainstay of treatment in higher-risk MDS. However, treatment resistance and disease transformation into acute myeloid leukemia (AML) is observed in the majority of patients and is indicative of a dismal outcome. The residual cell clones resistant to therapy or cell clones acquiring new genetic aberrations are two of the key events responsible for drug resistance. Bulk tumor sequencing often fails to detect these rare subclones that confer resistance to therapy. In this study, we employed a single-cell DNA (sc-DNA) sequencing approach to study the clonal heterogeneity and clonal evolution in two MDS patients refractory to HMA. In both patients, different single nucleotide variations (SNVs) or insertions and deletions (INDELs) were detected with bulk tumor sequencing. Rare cell clones with mutations that are undetectable by bulk tumor sequencing were detected by sc-DNA sequencing. In addition to SNVs and short INDELs, this study also revealed the presence of a clonal copy number loss of DNMT3A, TET2, and GATA2 as standalone events or in association with the small SNVs or INDELs detected during HMA resistance and disease progression.     

Minimizing deviations of input and output weights from their means in data envelopment analysis

In this paper, we propose a model that minimizes deviations of input and output weights from their means for efficient decision-making units in data envelopment analysis. The mean of an input or output weight is defined as the average of the maximum and the minimum attainable values of the weight when the efficient decision making unit under evaluation remains efficient. Alternate optimal weights usually exist in the linear programming solutions of efficient decision-making units and the optimal weights obtained from most of the linear programming software are somewhat arbitrary. Our proposed model can yield more rational weights without a priori information about the weights. Input and output weights can be used to compute cross-efficiencies of decision-making units in peer evaluations or group decision-making units, which have similar production processes via cluster analysis. If decision makers want to avoid using weights with extreme or zero values to access performance of decision-making units, then choosing weights that are close to their means, may be a rational choice.     

A data-driven ensemble ranking system of production quality across manufacturers—A case study for risk assessment in the solar industry

In many production industries, quality assurance and risk analysis are important aspects of the procurement of products. Such analysis often takes the form of during and after production inspections performed by quality assurance companies. These inspections give insight into the quality level of each individual production batch; however, it is also often important to understand a manufacturer's overall production quality and how its quality compares to other manufacturers. Therefore, in this paper, we propose a data-driven method to rank the production quality across manufacturers. The method is based on data from quality assurance inspections and consists of three steps. In the first step, a failure mode and effects analysis is applied for each individual manufacturer. This results in a risk assessment for identified failure modes. In the second step, the risk assessments are combined to create an overall failure index for each manufacturer. Step 2 can be designed in various ways. To ensure our final ranking is robust to the selected method, in step 3 we combine all methods into a unified rank of each manufacturer. We validate our proposed ensemble ranking method using a case study from the solar industry, where we compare our final ranking with the experts’ knowledge of manufacturer quality. It is shown that our data-driven method identifies the high-risk manufacturers in accordance with experts’ knowledge.     

Multidentate Molecule Anchoring Halide Perovskite Surface and Regulating Crystallization Kinetics toward Efficient Light-Emitting Diodes

Functional passivators are conventionally utilized in modifying the crystallization properties of perovskites to minimize the non-radiative recombination losses in perovskite light-emitting diodes (PeLEDs). However, the weak anchor ability of some commonly adopted molecules has limited passivation ability to perovskites and even may desorb from the passivated defects in a short period of time, which bring about plenty of challenges for further development of high-performance PeLEDs. Here, a multidentate molecule, formamidine sulfinic acid (FSA), is introduced as a novel passivator to perovskites. FSA has multifunctional groups ( S≐O,  C≐N and  NH₂) where the  S≐O and  C≐N groups enable coordination with the lead ions and the  NH₂ interacts with the bromide ions, thus providing the most effective chemical passivation for defects and in turn the formation of highly stable perovskite emitters. Moreover, the interaction between the FSA and octahedral [PbBr₆]⁴⁻ can inhibit the formation of unfavorable low-n domains to further minimize the inefficient energy transfer inside the perovskite emitters. Therefore, the FSA passivated green-emitting PeLED exhibits a high external quantum efficiency (EQE) of 26.5% with fourfold enhancement in operating lifetime as compared to the control device, consolidating that the multidentate molecule is a promising strategy to effectively and sustainably passivate the perovskites.