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Background and Objectives: With the increased prevalence of patients with cancer, the demand for preparing cytotoxic drugs was increased by health-system pharmacists. To reduce the workload and contamination of work areas in pharmacies, compounding robots preparing cytotoxic drugs have been introduced, and the use of the robots has been expanded in recent years. As reports on the comprehensive and quantitative evaluation of compounding robots remain lacking, a systematic review and meta-analysis were conducted to provide descriptive and quantitative evaluations of the accuracy of preparing injectable cytotoxic drugs. Materials and Methods: A systematic review and meta-analysis were conducted using published studies up to 2020. To identify eligible studies, PubMed, EMBASE, and Cochrane Library were used. All studies reporting the outcomes relevant to drug-compounding robots such as accuracy, safety, and drug contamination were included. Outcomes from included studies were descriptively summarized. Drug contamination by the robot was quantitatively analyzed using the odds ratio (OR) with a 95% confidence interval (CI). The risk of bias was assessed using the Risk of Bias Assessment tool for Non-randomized Studies (RoBANS). Results: A total of 14 compounding robot studies were eligible for review and 4 studies were included in the meta-analysis. Robotic compounding showed failure rates of 0.9–16.75%, while the accuracy range was set at 5%. Two studies reported that robotic compounding needed more time than manual compounding, two reported that robotic compounding needed less time, and one just reported preparation time without a control group. In a meta-analysis regarding the contamination of the compounding area, manual compounding was associated with lower contamination, although the result was not statistically significant (OR 4.251, 95% CI 0.439–51.772). For the contamination of infusion bags, the robot was associated with lower contamination (OR 0.176, 95% CI 0.084–0.365). Conclusions: Robotic compounding showed better accuracy than manual compounding and, without control groups, showed a high accuracy rate and also reduced the risk of drug contamination and compounding workload. The preparation time of the robot was not consistent because the type of robot and introduced system were different. In conclusion, robotic compounding showed mixed results compared to the manual compounding of drugs, so the system should be introduced considering the risks and benefits of robots. [ABSTRACT FROM AUTHOR]

We report a precision medicine platform that evaluates the probability of chemotherapy drug efficacy for canine lymphoma by combining ex vivo chemosensitivity and immunophenotyping assays with computational modelling. We isolated live cancer cells from fresh fine needle aspirates of affected lymph nodes and collected post‐treatment clinical responses in 261 canine lymphoma patients scheduled to receive at least 1 of 5 common chemotherapy agents (doxorubicin, vincristine, cyclophosphamide, lomustine and rabacfosadine). We used flow cytometry analysis for immunophenotyping and ex vivo chemosensitivity testing. For each drug, 70% of treated patients were randomly selected to train a random forest model to predict the probability of positive Veterinary Cooperative Oncology Group (VCOG) clinical response based on input variables including antigen expression profiles and treatment sensitivity readouts for each patient's cancer cells. The remaining 30% of patients were used to test model performance. Most models showed a test set ROC‐AUC > 0.65, and all models had overall ROC‐AUC > 0.95. Predicted response scores significantly distinguished (P <.001) positive responses from negative responses in B‐cell and T‐cell disease and newly diagnosed and relapsed patients. Patient groups with predicted response scores >50% showed a statistically significant reduction (log‐rank P <.05) in time to complete response when compared to the groups with scores <50%. The computational models developed in this study enabled the conversion of ex vivo cell‐based chemosensitivity assay results into a predicted probability of in vivo therapeutic efficacy, which may help improve treatment outcomes of individual canine lymphoma patients by providing predictive estimates of positive treatment response. [ABSTRACT FROM AUTHOR]

Hydrogenases are metalloproteins capable of catalyzing the interconversion between molecular hydrogen and protons and electrons. The iron–sulfur clusters within the enzyme enable rapid relay of electrons which are either consumed or generated at the active site. Their unparalleled catalytic efficiency has attracted attention, especially for potential use in H2 production and/or fuel cell technologies. However, there are limitations to using hydrogenases, especially due to their high O2 sensitivity. The subclass, called [FeFe] hydrogenases, are particularly more vulnerable to O2 but proficient in H2 production. In this review, we provide an overview of mechanistic and protein engineering studies focused on understanding and enhancing O2 tolerance of the enzyme. The emphasis is on ongoing studies that attempt to overcome O2 sensitivity of the enzyme while it catalyzes H2 production in an aerobic environment. We also discuss pioneering attempts to utilize the enzyme in biological H2 production and other industrial processes, as well as our own perspective on future applications. [ABSTRACT FROM AUTHOR]

Hydrogenases, ferredoxins, and ferredoxin-NADP+ reductases (FNR) are redox proteins that mediate electron metabolism in vivo, and are also potential components for biological H2 production technologies. A high-throughput H2 production assay device (H2PAD) is presented that enables simultaneous evaluation of 96 individual H2 production reactions to identify components that improve performance. Using a CCD camera and image analysis software, H2PAD senses the chemo-optical response of Pd/WO3 thin films to the H2 produced. H2PAD-enabled discovery of hydrogenase and FNR mutants that enhance biological H2 production is reported. From a library of 10 080 randomly mutated Clostridium pasteurianum [FeFe] hydrogenases, we found a mutant with nearly 3-fold higher H2 production specific activity. From a library of 400 semi-randomly mutated Oryza sativa FNR, the top hit enabled a 60 % increase in NADPH-driven H2 production rates. H2PAD can also facilitate elucidation of fundamental biochemical mechanisms within these systems. [ABSTRACT FROM AUTHOR]

Abstract: We perform the first long-term (>1 year) continuous adjoint simulations with a global atmospheric chemistry–transport model focusing on population exposure to fine particulate matter (PM2.5) and associated risk of early death. Sensitivities relevant to intercontinental and high-altitude PM pollution are calculated with particular application to aircraft emissions. Specifically, the sensitivities of premature mortality risk in different regions to NO x , SO x , CO, VOC and primary PM2.5 emissions as a function of location are computed. We apply the resultant sensitivity matrices to aircraft emissions, finding that NO x emissions are responsible for 93% of population exposure to aircraft-attributable PM2.5. Aircraft NO x accounts for all of aircraft-attributable nitrate exposure (as expected) and 53% of aircraft-attributable sulfate exposure due to the strong “oxidative coupling” between aircraft NO x emissions and non-aviation SO2 emissions in terms of sulfate formation. Of the health risk-weighted human PM2.5 exposure attributable to aviation, 73% occurs in Asia, followed by 18% in Europe. 95% of the air quality impacts of aircraft emissions in the US are incurred outside the US. We also assess the impact of uncertainty or changes in (non-aviation) ammonia emissions on aviation-attributable PM2.5 exposure by calculating second-order sensitivities. We note the potential application of the sensitivity matrices as a rapid policy analysis tool in aviation environmental policy contexts. [Copyright &y& Elsevier]

PDF/A is a version of Portable Document Format designed for archiving and preservation. Due to its popularity, many electronic documents exist in PDF format, and the ability to convert an existing PDF into a conforming PDF/A file is as important, if not more, as being able to produce documents in PDF/A format. The Florida Digital Archive conducted a study to select a PDF to PDF/A conversion application as part of its format normalization strategy in the summer of 2012. This article documents the evaluation process and presents the results in such a way that they provide insight into challenges and potential drawbacks during similar evaluation or implementation. [ABSTRACT FROM AUTHOR]

Abstract: This paper studies economics of renewable energy systems with consideration of future prospects on costs and uncertain external conditions that may affect competitiveness in the power plant market. The concept of learning curve is adopted to compute estimates on the costs of installing and operating renewable energy systems in the future; fuel costs and carbon price are modeled as scenario-dependent variables to analyze their impact on total costs under different scenarios. The proposed approach allows evaluation and comparison of total costs necessary in implementing renewable energy plans under varying technological, and/or economical conditions that face uncertainty at present. Moreover, analyzing the evaluation results further with techniques like sensitivity analysis can identify factors central to reducing the total costs. As an illustrative case-study, the Korean government’s renewable energy plan has been evaluated accordingly, under three different scenarios defined by International Energy Agency (IEA). The evaluation results indicate minor changes in total costs of achieving the plan among three scenarios, mainly due to counterbalancing between the price of fossil fuels and carbon price. Further analyses revealed factors central to lowering the total costs necessary in implementing the plan—hybridization between renewable energy systems, reduction of biomass production costs via technological innovation, increasing learning rates by focusing on R&D and international cooperation. [Copyright &y& Elsevier]

Abstract: The modification of the electrical characteristics of field-effect transistors (FETs) with channels composed of n- or p-type silicon nanowires (SiNWs) by oxygen plasma treatment is investigated in this study. The SiNWs obtained from silicon bulk wafers are <111> surface-oriented and their doping concentrations are ∼1021 and ∼1017 cm−3 for the n- and p-type SiNWs, respectively. After the back-gate SiNWFETs were subjected to oxygen plasma treatment, the magnitude of the drain current of the n-type SiNWs was decreased, whereas that of the p-type SiNWs was increased, while the gate-dependent characteristics of both of types of SiNWs were improved. The changes in the electrical characteristics are due to the adsorption of oxygen ions on the surface of the SiNWs. To verify the effect of the oxygen ions, the SiNWFETs were kept in a vacuum for 24h whereupon their electrical characteristics tended to revert to their inherent state. [Copyright &y& Elsevier]

Top-gate field-effect transistors (FETs) based on triangular silicon nanowires (SiNWs) obtained from a silicon bulk wafer using a conventional silicon manufacturing technology are constructed on flexible plastic substrates. Their field-effect mobility and peak transconductance are enhanced by 10% in the upwardly bent state and by 29% in the downwardly bent state at a strain of 1.02%, compared with the flat state. The strain effect resulting from the bending of the flexible substrates is higher in the downward state than in the upward state, and the increase in strain improves the performance of SiNW-based FETs. Moreover, their device performance is stable even after bending the substrate several thousand times. [ABSTRACT FROM AUTHOR]

This study aimed to validate the new European Leukemia Net (ELN) 2022 criteria for genetic risk stratification in older adults with acute myeloid leukemia (AML) and to determine the most likely set of clusters of similar cytogenetic and mutation properties correlated with survival outcomes in three treatment groups: intensive chemotherapy (IC), hypomethylating agents (HMA) alone, and HMA plus venetoclax (HMA/VEN). The study included 279 patients (aged ≥60 years) who received IC (N=131), HMA (N=76), and HMA/VEN (N=72) between July 2017 and October 2021. No significant differences were observed in survival among the groups according to ELN 2022 risk stratification. Unsupervised hierarchical clustering analysis identified nine genomic clusters (C1-9) with varying survival outcomes depending on treatment type. For example, C4 (predominant for core binding factor-AML) displayed a favorable prognosis in the IC group, but not in the HMA or HMA/VEN groups. The HMA/VEN group had better outcomes than the HMA group in many clusters (C1, 2, 3, and 5); however, the addition of VEN to HMA or IC did not improve the survival outcomes compared with those of HMA alone in C7 and C9 (predominant for -5, del(5q), -7, -17/abn(17p), complex karyotypes, and mutated TP53). The study highlights the limitations of ELN genetic risk stratification in older adults with AML. It emphasizes the need for a more comprehensive approach that considers co-occurring somatic mutations to guide treatment selection in older adults with AML.

Metalloproteins, proteins containing metal atoms or clusters within their structures, are critical for various biological functions across all domains of life. More than hundreds of different types have been discovered, which conduct various roles such as transportation of O 2 , catalyzing chemical reactions, sensing environmental changes, and relaying electrons. Metalloprotein molecules incorporate a variety of metal atoms, coordinated to specific amino acid residues that affect their conformation and functionality. The process of metal incorporation typically occurs during or post-protein folding, often requiring chaperones for metal ion delivery and quality control. Progress in understanding metal incorporation and metalloprotein functionality has been enhanced by cell-free protein synthesis (CFPS) methods that offer direct control over the synthesis environment. This chapter reviews the diverse applications of CFPS methods in metalloprotein research, encompassing structure-function studies, protein engineering, and creation of artificial metalloproteins. Examples demonstrating the utility and advances brought about by CFPS in synthetic biology, electrochemistry, and drug discovery are highlighted. Despite remarkable progress, challenges remain in optimizing and advancing the CFPS methods, underscoring the need for future explorations in this transformative approach to metalloprotein study and engineering., (© 2023. The Author(s), under exclusive license to Springer Nature Switzerland AG.)

First-line treatments of cancer do not always work, and even when they do, they cure the disease at unequal rates mostly owing to biological and clinical heterogeneity across patients. Accurate prediction of clinical outcome and survival following the treatment can support and expedite the process of comparing alternative treatments. We describe the methodology to dynamically determine remission probabilities for individual patients, as well as their prospects of progression-free survival (PFS). The proposed methodology utilizes the ex vivo drug sensitivity of cancer cells, their immunophenotyping results, and patient information, such as age and breed, in training machine learning (ML) models, as well as the Cox hazards model to predict the probability of clinical remission (CR) or relapse across time for a given patient. We applied the methodology using the three types of data obtained from 242 canine lymphoma patients treated by (L)-CHOP chemotherapy. The results demonstrate substantial enhancement in the predictive accuracy of the ML models by utilizing features from all the three types of data. They also highlight superior performance and utility in predicting survival compared to the conventional stratification method. We believe that the proposed methodology can contribute to improving and personalizing the care of cancer patients.

Ferredoxins are metalloproteins that deliver electrons to several redox partners, including [FeFe] hydrogenases that are potentially a component of biological H 2 production technologies. Reduced ferredoxins can also lose electrons to molecular oxygen, which may lower the availability of electrons for cellular or synthetic reactions. Ferredoxins thus play a key role in diverse kinds of redox biochemistry, especially the enzymatic H 2 production catalyzed by [FeFe] hydrogenases. We investigated how the yield of anaerobic and aerobic H 2 production vary among the four different types of ferredoxins that are used to deliver electrons extracted from NADPH within the synthetic, fermentative pathway. We also assessed the electron loss due to O 2 reduction by reduced ferredoxins within the pathway, for which the difference was as high as five-fold. Our findings provide valuable insights for further improving biological H 2 production technologies and can also facilitate elucidation of mechanisms governing interactions between Fe-S cluster(s) and molecular oxygen., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor declared a past co-authorship with one of the authors, JK., (Copyright © 2021 Koo and Cha.)

Hydrogenases are metalloproteins capable of catalyzing the interconversion between molecular hydrogen and protons and electrons. The iron-sulfur clusters within the enzyme enable rapid relay of electrons which are either consumed or generated at the active site. Their unparalleled catalytic efficiency has attracted attention, especially for potential use in H 2 production and/or fuel cell technologies. However, there are limitations to using hydrogenases, especially due to their high O 2 sensitivity. The subclass, called [FeFe] hydrogenases, are particularly more vulnerable to O 2 but proficient in H 2 production. In this review, we provide an overview of mechanistic and protein engineering studies focused on understanding and enhancing O 2 tolerance of the enzyme. The emphasis is on ongoing studies that attempt to overcome O 2 sensitivity of the enzyme while it catalyzes H 2 production in an aerobic environment. We also discuss pioneering attempts to utilize the enzyme in biological H 2 production and other industrial processes, as well as our own perspective on future applications., (© 2019 Wiley Periodicals, Inc.)

Hydrogenases, ferredoxins, and ferredoxin-NADP + reductases (FNR) are redox proteins that mediate electron metabolism in vivo, and are also potential components for biological H 2 production technologies. A high-throughput H 2 production assay device (H 2 PAD) is presented that enables simultaneous evaluation of 96 individual H 2 production reactions to identify components that improve performance. Using a CCD camera and image analysis software, H 2 PAD senses the chemo-optical response of Pd/WO 3 thin films to the H 2 produced. H 2 PAD-enabled discovery of hydrogenase and FNR mutants that enhance biological H 2 production is reported. From a library of 10 080 randomly mutated Clostridium pasteurianum [FeFe] hydrogenases, we found a mutant with nearly 3-fold higher H 2 production specific activity. From a library of 400 semi-randomly mutated Oryza sativa FNR, the top hit enabled a 60 % increase in NADPH-driven H 2 production rates. H 2 PAD can also facilitate elucidation of fundamental biochemical mechanisms within these systems., (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

[FeFe] hydrogenases catalyze rapid H 2 production but are highly O 2 -sensitive. Developing O 2 -tolerant enzymes is needed for sustainable H 2 production technologies, but the lack of a quantitative and predictive assay for O 2 tolerance has impeded progress. We describe a new approach to provide quantitative assessment of O 2 sensitivity by using an assay employing ferredoxin NADP + reductase (FNR) to transfer electrons from NADPH to hydrogenase via ferredoxins (Fd). Hydrogenase inactivation is measured during H 2 production in an O 2 -containing environment. An alternative assay uses dithionite (DTH) to provide reduced Fd. This second assay measures the remaining hydrogenase activity in periodic samples taken from the NADPH-driven reaction solutions. The second assay validates the more convenient NADPH-driven assay, which better mimics physiological conditions. During development of the NADPH-driven assay and while characterizing the Clostridium pasteurianum (Cp) [FeFe] hydrogenase, CpI, we detected significant rates of direct electron loss from reduced Fd to O 2 However, this loss does not interfere with measurement of first order hydrogenase inactivation, providing rate constants insensitive to initial hydrogenase concentration. We show increased activity and O 2 tolerance for a protein fusion between Cp ferredoxin (CpFd) and CpI mediated by a 15-amino acid linker but not for a longer linker. We suggest that this precise, solution phase assay for [FeFe] hydrogenase O 2 sensitivity and the insights we provide constitute an important advance toward the discovery of the O 2 -tolerant [FeFe] hydrogenases required for photosynthetic, biological H 2 production., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

A technique to implement silicon nanowire (SiNW)-based tunneling field-effect transistors (TFETs) on flexible plastic substrates is developed for the first time. The p-i-n configured Si NWs are obtained from an Si wafer using a conventional top-down CMOS-compatible technology, and they are then transferred onto the plastic substrate. Based on gate-controlled band-to-band tunneling (BTBT) as their working principle, the SiNW-based TFETs show normal p-channel switching behavior with a threshold voltage of -1.86 V and a subthreshold swing of 827 mV/dec. In addition, ambipolar conduction is observed due to the presence of the BTBT between the heavily doped p+ drain and n+ channel regions, indicating that our TFETs can operate in the n-channel mode as well. Furthermore, the BTBT generation rates for both the p-channel and n-channel operating modes are nearly independent of the bending state (strain = 0.8%) of the plastic substrate.

The memory characteristics of ZnO nanowire-based nano-floating gate memory (NFGM) with Pt nanocrystals acting as the floating gate nodes were investigated in this work. Pt nanocrystals were embedded between Al(2)O(3) tunneling and control oxide layers deposited on ZnO nanowire channels. For a representative ZnO nanowire-based NFGM with embedded Pt nanocrystals, a threshold voltage shift of 3.8 V was observed in its drain current versus gate voltage (I(DS)-V(GS)) measurements for a double sweep of the gate voltage, revealing that the deep effective potential wells built into the nanocrystals provide our NFGM with a large charge storage capacity. Details of the charge storage effect observed in this memory device are discussed in this paper.