Broadening oncological boundaries: the intratumoral microbiota.

The microbiota of solid tumors was identified >100 years ago; however, heterogeneous composition and diversity have been revealed only recently. Growing evidence has suggested that several functional mechanisms of the intratumoral microbiota affect tumorigenesis and progression, suggesting that the intratumoral microbiota is a promising biomarker for multiple cancers. The low biomass of the intratumoral microbiota poses a major challenge to related research, thus necessitating the use of a multiple-modality integrated framework to resolve this dilemma. Advanced techniques such as single-cell sequencing provide significant clues, and the gradual optimization of functional experiments and culture-based methods enables deeper investigation of the underlying mechanisms involved. In this review, we outline the current state of research on the intratumoral microbiota and describe the challenges and comprehensive strategies for future research.

A novel disassembly process of end-of-life lithium-ion batteries enhanced by online sensing and machine learning techniques.

An effective lithium-ion battery (LIB) recycling infrastructure is of great importance to alleviate the concerns over the disposal of waste LIBs and the sustainability of critical elements for producing LIB components. The End-of-life (EOL) LIBs are in various sizes and shapes, which create significant challenges to automate a few unit operations (e.g., disassembly at the cell level) of the recycling process. Meanwhile, hazardous and flammable materials are contained in LIBs, posing great threats to the human exposure. Therefore, it is difficult to dismantle the LIBs safely and efficiently to recover critical materials. Automation has become a competitive solution in manufacturing world, which allows for mass production at outstanding speeds and with great repeatability or quality. It is imperative to develop automatic disassembly solution to effectively disassemble the LIBs while safeguarding human workers against the hazards environment. In this work, we demonstrate an automatic battery disassembly platform enhanced by online sensing and machine learning technologies. The computer vision is used to classify different types of batteries based on their brands and sizes. The real-time temperature data is captured from a thermal camera. A data-driven model is built to predict the cutting temperature pattern and the temperature spike can be mitigated by the close-loop control system. Furthermore, quality control is conducted using a neural network model to detect and mitigate the cutting defects. The integrated disassembly platform can realize the real-time diagnosis and closed-loop control of the cutting process to optimize the cutting quality and improve the safety. Supplementary Information: The online version contains supplementary material available at 10.1007/s10845-022-01936-x.

A New Model of Interval-Valued Intuitionistic Fuzzy Weighted Operators and Their Application in Dynamic Fusion Target Threat Assessment.

Existing missile defense target threat assessment methods ignore the target timing and battlefield changes, leading to low assessment accuracy. In order to overcome this problem, a dynamic multi-time fusion target threat assessment method is proposed. In this method, a new interval valued intuitionistic fuzzy weighted averaging operator is proposed to effectively aggregate multi-source uncertain information; an interval-valued intuitionistic fuzzy entropy based on a cosine function (IVIFECF) is designed to determine the target attribute weight; an improved interval-valued intuitionistic fuzzy number distance measurement model is constructed to improve the discrimination of assessment results. Specifically, first of all, we define new interval-valued intuitionistic fuzzy operation rules based on algebraic operations. We use these rules to provide a new model of interval-valued intuitionistic fuzzy weighted arithmetic averaging (IVIFWAA) and geometric averaging (IVIFWGA) operators, and prove a number of algebraic properties of these operators. Then, considering the subjective and objective weights of the incoming target, a comprehensive weight model of target attributes based on IVIFECF is proposed, and the Poisson distribution method is used to solve the time series weights to process multi-time situation information. On this basis, the IVIFWAA and IVIFWGA operators are used to aggregate the decision information from multiple times and multiple decision makers. Finally, based on the improved TOPSIS method, the interval-valued intuitionistic fuzzy numbers are ordered, and the weighted multi-time fusion target threat assessment result is obtained. Simulation results of comparison show that the proposed method can effectively improve the reliability and accuracy of target threat assessment in missile defense.

Effect of asparagine, corncob biochar and Fe(II) on anaerobic biological treatment under low temperature: Enhanced performance and microbial community dynamic.

To ensure the efficiency of anaerobic biological treatment technology at lower temperature will expand the application of anaerobic reactor in practical industrial wastewater treatment. Through a batch experiment, asparagine, corncob biochar and Fe2+ were selected as strengthening measures to analyze the effects on the anaerobic sludge characteristics, microbial community and functional genes in the low temperature (15 °C). Results showed that after 21 days, asparagine began to promote chemical oxygen demand (COD) removal by the anaerobic treatment, with highest COD removal rate (81.65%) observed when the asparagine concentration was 1 mmol/L. When adding 3 g biochar, 25 mg/L Fe2+, and the combination of biochar and Fe2+, the COD removal rates reached to 82%, 92% and 97%, respectively. In the presence of asparagine, both biochar and Fe2+ alone or in combination increased the activity of protease (16.35%-120.71%) and coenzyme F420 (5.63%-130.2%). The relative abundance of Proteobacteria and Methanobacterium increased in the presence of biochar and Fe2+. In addition, the KEGG results showed that the combined addition of biochar and Fe2+ enhanced bacterial replication and repair and promoted amino acid metabolism of archaea.

Multicriteria Group Decision Making Based on Intuitionistic Normal Cloud and Cloud Distance Entropy.

The uncertainty of information is an important issue that must be faced when dealing with decision-making problems. Randomness and fuzziness are the two most common types of uncertainty. In this paper, we propose a multicriteria group decision-making method based on intuitionistic normal cloud and cloud distance entropy. First, the backward cloud generation algorithm for intuitionistic normal clouds is designed to transform the intuitionistic fuzzy decision information given by all experts into an intuitionistic normal cloud matrix to avoid the loss and distortion of information. Second, the distance measurement of the cloud model is introduced into the information entropy theory, and the concept of cloud distance entropy is proposed. Then, the distance measurement for intuitionistic normal clouds based on numerical features is defined and its properties are discussed, based on which the criterion weight determination method under intuitionistic normal cloud information is proposed. In addition, the VIKOR method, which integrates group utility and individual regret, is extended to the intuitionistic normal cloud environment, and thus the ranking results of the alternatives are obtained. Finally, the effectiveness and practicality of the proposed method are demonstrated by two numerical examples.

An automatic sorting system for electronic components detached from waste printed circuit boards.

Recycling e-waste makes for eliminating the pollution to environment and recovering critical materials as one of resource. Printed circuit boards (PCBs) serve as the important part in all e-waste, containing valuable but hazardous elements to be recycled when they reach the end of life. For the recycling of waste PCB, the electronic components (ECs) are liberated from base board and to be treated separately for element recovery. Due to the diverse element composition, ECs deserve to be further classified and sorted to improve the efficiency of recycling, achieving the concept of accurate recovery. Currently, the recycling industry only roughly screen the ECs manually by labors, which increases the risk of health for exposure to the hazardous environment. Automatic solutions are necessary for replacing labors to classify and sort the waste ECs, thus safeguarding them against the hazards of factory environment. In this work, the YOLO-V3, an emerging image detection algorithm, is utilized to train the self-made dataset and classify the ECs into specific categories. To avoid surface damage that weakens the accuracy of object detection, the technology process of detaching the ECs is improved by building a nitrogen atmosphere during the desoldering process, which delivers great protection effects on ECs. Results of YOLO-V3 detection model present satisfactory classification capability for all the classes of ECs and a smart on-line sorting system is proposed to automatically separate the ECs detached from WPCB.

Enabling Intelligent Recovery of Critical Materials from Li-Ion Battery through Direct Recycling Process with Internet-of-Things.

The rapid market expansion of Li-ion batteries (LIBs) leads to concerns over the appropriate disposal of hazardous battery waste and the sustainability in the supply of critical materials for LIB production. Technologies and strategies to extend the life of LIBs and reuse the materials have long been sought. Direct recycling is a more effective recycling approach than existing ones with respect to cost, energy consumption, and emissions. This approach has become increasingly more feasible due to digitalization and the adoption of the Internet-of-Things (IoT). To address the question of how IoT could enhance direct recycling of LIBs, we first highlight the importance of direct recycling in tackling the challenges in the supply chain of LIB and discuss the characteristics and application of IoT technologies, which could enhance direct recycling. Finally, we share our perspective on a paradigm where IoT could be integrated into the direct recycling process of LIBs to enhance the efficiency, intelligence, and effectiveness of the recycling process.

Water-Based Electrode Manufacturing and Direct Recycling of Lithium-Ion Battery Electrodes-A Green and Sustainable Manufacturing System.

It is critical to develop a low-cost and environmentally friendly system to manufacture and recycle lithium-ion batteries (LIBs) as the demand on LIBs keeps increasing dramatically. Conventional LIB cathodes are manufactured using N-methyl-2-pyrrolidone as the solvent, which is expensive, highly toxic, flammable, and energy intensive to produce and recover. Ideally, a close-loop industrial supply chain should be built, in which the batteries are manufactured, market harvested, and recycled with minimal external toxic solvent through the whole system. This work demonstrates a green and more sustainable manufacturing method for LIBs where no hazardous organic solvent is used during electrode manufacturing and recycling. The electrodes fabricated via water-based processing demonstrate comparable rate performance and cycle life to the ones from conventional solvent-based processing. Utilization of a water-soluble binder enables recovering the cathode compound from spent electrodes using water, which is successfully regenerated to deliver comparable electrochemical performance to the pristine one.

Easy Applied Gelatin-Based Hydrogel System for Long-Term Functional Cardiomyocyte Culture and Myocardium Formation.

Harnessing biomaterials for in vitro tissue construction has long been a research focus because of its powerful potentials in tissue engineering and pharmaceutical industry. Myocardium is a critical cardiac tissue with complex multiple muscular layers. Considering the specific characters of native cardiac tissues, it is necessary to design a biocompatible and biomimetic platform for cardiomyocyte culture and myocardium formation with sustained physiological function. In this study, we developed gelatin-based hydrogels chemically cross-linked by genipin, a biocompatible cross-linker, as cell culture scaffolds. Moreover, to achieve and maintain the functionality of myocardium, for instance, well-organized cardiomyocytes and synchronized contractile behavior, we fabricated gelatin-based hydrogels with patterned microstructure using a microcontact printing technique. Furthermore, graphene oxide (GO), with unprecedented physical and chemical properties, has also been incorporated into gelatin for culturing cardiomyocytes. Our results show that micropatterned genipin-cross-linked gelatin hydrogels are very helpful to promote alignment and maturation of neonatal rat ventricular cardiomyocytes. More interestingly, the presence of GO significantly enhances the functional performance of cardiomyocytes, including an increase in contraction amplitude and cardiac gene expression. The cultured cardiomyocytes reach a well-synchronized contraction within 48 h of cell seeding and keep beating for up to 3 months. Our study provides a new and easy-to-use gelatin-based scaffold for improving physiological function of engineered cardiac tissues, exhibiting promising applications in cardiac tissue engineering and drug screening.

Comparisons of Effects on Intestinal Short-Chain Fatty Acid Concentration after Exposure of Two Glycosidase Inhibitors in Mice.

Acarbose and voglibose are the most widely used diabetes drugs as glycosidase inhibitors. In this study, the use of these two inhibitors significantly increased the content of starch in large intestine, and altered the concentration of short-chain fatty acids (SCFAs) by affecting the intestinal microbiota. However, there are some differences in the intestinal microbiome of the two groups of mice, mainly in bacteria such as Bacteroidaceae bacteroides and Desulfovibrionaceae desulfovibrio. The productions of acetate and propionate in caecum in voglibose group were significantly higher than those in acarbose group and two kinds of glycosidase inhibitors were close in the production of butyrate in caecum. The Tax4Fun analysis based on Kyoto Encyclopedia of Genes and Genomes (KEGG) data indicated that different productions of acetate and propionate between acarbose group and voglibose group may be related to 2-oxoisovalerate dehydrogenase and pyruvate oxidase. In addition, in-vitro experiments suggested that voglibose had less effect on epithelial cells than acarbose after direct stimulation. According to the recent researches of SCFAs produced by intestinal microbiota, our comparative study shown higher concentration of these beneficial fatty acids in the lumen of voglibose-treated mice, which implied a lower level of inflammation.

MicroRNA-34a modulates the Notch signaling pathway in mice with congenital heart disease and its role in heart development.

The objective of the study was to elucidate the mechanism by which microRNA-34a (miR-34a) influences heart development and participates in the pathogenesis of congenital heart disease (CHD) by targeting NOTCH-1 through the Notch signaling pathway. Forty D7 pregnant mice were recruited for the purposes of the study and served as the CHD (n=20, successfully established as CHD model) and normal (n=20) groups. The positive expression of the NOTCH-1 protein was evaluated by means of immunohistochemistry. Embryonic endocardial cells (ECCs) were assigned into the normal, blank, negative control (NC), miR-34a mimics, miR-34a inhibitors, miR-34a inhibitors+siRNA-NOTCH-1, siRNA-NOTCH-1, miR-34a mimics+NOTCH-1 OE and miR-34a mimics+crispr/cas9 (mutant NOTCH-1) groups. The expressions of miR-34a, NOTCH-1, Jagged1, Hes1, Hey2 and Csx in cardiac tissues and ECCs were determined by both RT-qPCR and western blotting methods. MTT assay and flow cytometry were conducted for cell proliferation and apoptosis measurement. A dual luciferase reporter assay was applied to demonstrate that NOTCH-1 was the target gene of miR-34a. In comparison to the normal group, the expressions of miR-34a, Jagged1, Hes1 and Hey2 displayed up-regulated levels, while the expressions of NOTCH-1 and Csx were down-regulated in the CHD group. Compared with the blank and NC groups, the miR-34a mimics and siRNA-NOTCH-1 groups displayed reduced expressions of NOTCH-1 and Csx as well as a decreased proliferation rate, higher miR-34a, Jagged1, Hes1 and Hey2 expressions and an increased rate of apoptosis; while an reverse trend was observed in the miR-34a inhibitors group. The expressions of MiR-34a recorded increased levels in the miR-34a mimics+NOTCH-1 OE and miR-34a mimics+crispr/cas9 (mutant NOTCH-1) groups, however no changes in the expressions of NOTCH-1, Jagged1, Hes1, Hey2, Csx, as well as cell proliferation and apoptosis were observed when compared to the blank and NC groups. The results of our study demonstrated that miR-34a increases the risk of CHD through its downregulation of NOTCH-1 by modulating the Notch signaling pathway.