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For the performance improvement of microbial fuel cells (MFCs), the anode becomes a breakthrough point due to its influence on bacterial attachment and extracellular electron transfer (EET). On other level, carbon materials possess the following features: low cost, rich natural abundance, good thermal and chemical stability, as well as tunable surface properties and spatial structure. Therefore, the development of carbon materials and carbon‐based composites has flourished in the anode of MFCs during the past years. In this review, the major carbon materials used to decorate MFC anodes have been systematically summarized, based on the differences in composition and structure. Moreover, we have also outlined the carbon material‐based hybrid biofilms and carbon material‐modified exoelectrogens in MFCs, along with the discussion of known strategies and mechanisms to enhance the bacteria‐hosting capabilities of carbon material‐based anodes, EET efficiencies, and MFC performances. Finally, the main challenges coupled with some exploratory proposals are also expounded for providing some guidance on the future development of carbon material‐based anodes in MFCs. The exploitation of carbon material‐based anodes is an important point in the performance improving process of microbial fuel cells. Various carbon materials with sophisticated properties and structures are comprehensively outlined, along with the corresponding strategies for favoring natural biofilm formation and extracellular electron transfer. Moreover, the carbon material‐based anodes using hybrid biofilm and surface‐modified bacteria are also highlighted.

To help inform decision making in the clinical setting, we carried out a systematic review and meta-analysis to estimate the association of thyroid disease risks with obesity. Pubmed, Embase, Web of Science, Cochrane database and Google Scholar electronic databases were searched from inception to October 31, 2018 without language restrictions to explore the relationship between thyroid disorders and obesity. The relative risk (RR) or odds risk (OR) for thyroid disorders were pooled using the SPSS and STATA software. A total of 22 studies were included in the study. (1) Meta-analysis showed that obesity was significantly associated with an increased risk of hypothyroidism (RR = 1.86, 95% CI 1.63-2.11, < 0.001). Meta-analyses after stratification further showed that obese population had increased risks of overt hypothyroidism (RR = 3.21, 95% CI 2.12-4.86, < 0.001) and subclinical hypothyroidism (RR = 1.70, 95% CI 1.42-2.03, < 0.001). (2) Further meta-analysis also showed obesity was clearly associated with Hashimoto's thyroiditis (RR = 1.91, 95% CI 1.10-3.32, = 0.022), but not with Graves' disease. (3) In the meta-analysis of antibodies, obesity was correlated with positive thyroid peroxidase antibody (TPOAb) (RR = 1.93, 95% CI 1.31-2.85, = 0.001), but not with positive thyroglobulin antibody (TGAb). Obesity was significantly related to hypothyroidism, HT, and TPOAb, implying that prevention of obesity is crucial for thyroid disorders. PROSPERO: CRD42018096897.

As the most powerful antigen-presenting cell type, dendritic cells (DCs) can induce potent antigen-specific immune responses in vivo, hence becoming optimal cell population for vaccination purposes. DCs can be derived ex vivo in quantity and manipulated extensively to be endowed with adequate immune-stimulating capacity. After pulsing with cancer antigens in various ways, the matured DCs are administrated back into the patient. DCs home to lymphoid organs to present antigens to and activate specific lymphocytes that react to a given cancer. Ex vivo pulsed DC vaccines have been vigorously investigated for decades, registering encouraging results in relevant immunotherapeutic clinical trials, while facing some solid challenges. With more details in DC biology understood, new theory proposed, and novel technology introduced (featuring recently emerged mRNA vaccine technology), it is becoming increasingly likely that ex vivo pulsed DC vaccine will fulfill its potential in cancer immunotherapy.

Cyanobacteria are photosynthetic prokaryotes that inhabit diverse aquatic and terrestrial environments. However, the evolutionary mechanisms involved in the cyanobacterial habitat adaptation remain poorly understood. Here, based on phylogenetic and comparative genomic analyses of 650 cyanobacterial genomes, we investigated the genetic basis of cyanobacterial habitat adaptation (marine, freshwater, and terrestrial). We show: (1) the expansion of gene families is a common strategy whereby terrestrial cyanobacteria cope with fluctuating environments, whereas the genomes of many marine strains have undergone contraction to adapt to nutrient-poor conditions. (2) Hundreds of genes are strongly associated with specific habitats. Genes that are differentially abundant in genomes of marine, freshwater, and terrestrial cyanobacteria were found to be involved in light sensing and absorption, chemotaxis, nutrient transporters, responses to osmotic stress, etc., indicating the importance of these genes in the survival and adaptation of organisms in specific habitats. (3) A substantial fraction of genes that facilitate the adaptation of Cyanobacteria to specific habitats are contributed by horizontal gene transfer, and such genetic exchanges are more frequent in terrestrial cyanobacteria. Collectively, our results further our understandings of the adaptations of Cyanobacteria to different environments, highlighting the importance of ecological constraints imposed by the environment in shaping the evolution of Cyanobacteria.

Employing theranostic nanoparticles, which combine both therapeutic and diagnostic capabilities in one dose, has promise to propel the biomedical field toward personalized medicine. Here we investigate the theranostic properties of topological insulator bismuth selenide (Bi 2 Se 3 ) in in vivo and in vitro system for the first time. We show that Bi 2 Se 3 nanoplates can absorb near-infrared (NIR) laser light and effectively convert laser energy into heat. Such photothermal conversion property may be due to the unique physical properties of topological insulators. Furthermore, localized and irreversible photothermal ablation of tumors in the mouse model is successfully achieved by using Bi 2 Se 3 nanoplates and NIR laser irradiation. In addition, we also demonstrate that Bi 2 Se 3 nanoplates exhibit strong X-ray attenuation and can be utilized for enhanced X-ray computed tomography imaging of tumor tissue in vivo. This study highlights Bi 2 Se 3 nanoplates could serve as a promising platform for cancer diagnosis and therapy.

With massive improvements in technology, astronomers have been uncovering impressive findings of the mysteries of the universe. At the same time, new technology is able to do more and more of the tasks usually given to people, especially when it comes to handling big pieces of data. As such, more jobs are being replaced by machines in the modern industrial age, which may very well include the jobs of astronomers. To investigate the potential of machine learning in astronomy and its effect on the livelihoods of astronomers, this paper aims to demonstrate the capabilities of machine learning algorithms in completing tasks usually done by astronomers, which in this case the identifying pulsar stars. Astronomers study these stars extensively to learn about extreme states of matter and explore different solar systems. This paper introduces various classification algorithms to perform the task of identifying pulsar stars from data of radio wave emissions in the universe. Two distinct methods of dealing with missing values were also used. Once the algorithms were applied to the dataset, the results were recorded and analyzed, mainly focusing on the accuracy of each model. From the results, all the models yielded accuracies above 90%. In addition, the models performed better on average with data preparation using the drop method compared to the average value method. These results provide extensive evidence that machine learning can perform certain tasks commonly performed by astronomers themselves. At the moment they cannot replace astronomers, but in the future, it has a possibility.

Particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) represents a severe environmental problem and is of negative impact on human health. Xi'an City, with a population of 6.5 million, is among the highest concentrations of PM2.5 in China. In 2013, in total, there were 191 days in Xi'an City on which PM2.5 concentrations were greater than 100 μg/m3. Recently, a few studies have explored the potential causes of high PM2.5 concentration using remote sensing data such as the MODIS aerosol optical thickness (AOT) product. Linear regression is a commonly used method to find statistical relationships among PM2.5 concentrations and other pollutants, including CO, NO2, SO2, and O3, which can be indicative of emission sources. The relationships of these variables, however, are usually complicated and non-linear. Therefore, a generalized additive model (GAM) is used to estimate the statistical relationships between potential variables and PM2.5 concentrations. This model contains linear functions of SO2 and CO, univariate smoothing non-linear functions of NO2, O3, AOT and temperature, and bivariate smoothing non-linear functions of location and wind variables. The model can explain 69.50% of PM2.5 concentrations, with R2 = 0.691, which improves the result of a stepwise linear regression (R2 = 0.582) by 18.73%. The two most significant variables, CO concentration and AOT, represent 20.65% and 19.54% of the deviance, respectively, while the three other gas-phase concentrations, SO2, NO2, and O3 account for 10.88% of the total deviance. These results show that in Xi'an City, the traffic and other industrial emissions are the primary source of PM2.5. Temperature, location, and wind variables also non-linearly related with PM2.5.

With the rapid development of society, it is of paramount importance to expeditiously assess environmental pollution and provide early warning of toxicity risks. Microbial fuel cell–based self-powered biosensors (MFC-SPBs) have emerged as a pivotal technology, obviating the necessity for external power sources and aligning with the prevailing trends toward miniaturization and simplification in biosensor development. In this case, vigorous advancements in MFC-SPBs have been acquired in past years, irrespective of whether the target identification event transpires at the anode or cathode. The present article undertakes a comprehensive review of developed MFC-SPBs, categorizing them into substrate effect and microbial activity effect based on the nature of the target identification event. Furthermore, various enhancement strategies to improve the analytical performance like accuracy and sensitivity are also outlined, along with a discussion of future research trends and application prospects of MFC-SPBs for their better developments.

Most of the current methods for the synthesis of two-dimensional materials (2DMs) require temperatures not compatible with traditional back-end-of-line (BEOL) processes in semiconductor industry (450 °C). Here, we report a general BiOCl-assisted chemical vapor deposition (CVD) approach for the low-temperature synthesis of 27 ultrathin 2DMs. In particular, by mixing BiOCl with selected metal powders to produce volatile intermediates, we show that ultrathin 2DMs can be produced at 280–500 °C, which are ~200–300 °C lower than the temperatures required for salt-assisted CVD processes. In-depth characterizations and theoretical calculations reveal the low-temperature processes promoting 2D growth and the oxygen-inhibited synthetic mechanism ensuring the formation of ultrathin nonlayered 2DMs. We demonstrate that the resulting 2DMs exhibit electrical, magnetic and optoelectronic properties comparable to those of 2DMs grown at much higher temperatures. The general low-temperature preparation of ultrathin 2DMs defines a rich material platform for exploring exotic physics and facile BEOL integration in semiconductor industry. Chemical vapor deposition (CVD) is a versatile method to synthesize 2D materials, but usually requires high growth temperatures. Here, the authors report a BiOCl-assisted CVD approach to grow 2D nanosheets from 27 different layered and nonlayered materials at temperatures <500 °C, which are compatible with back-end-of-the-line industrial processes.

Background It is proposed that the development of parenteral nutrition-associated cholestasis (PNAC) was significantly associated with preterm birth, low birth weight, infection, etc.; however, the etiology and pathogenesis of PNAC are not fully understood. Most of the studies examining PNAC-associated risk factors were single-center studies with relatively small sample sizes. Objective To analyze the risk factors associated with PNAC in preterm infants in China. Methods This is a retrospective multicenter observational study. Clinical data on the effect of multiple oil-fat emulsions (soybean oil-medium chain triglycerides-olive oil-fish oil, SMOF) in preterm infants were collected from a prospective multicenter randomized controlled study. A secondary analysis was performed in which preterm infants were divided into the PNAC group and the non-PNAC group based on the PNAC status. Results A total of 465 cases very preterm infants or very low birth weight infants were included in the study in which 81 cases were assigned to the PNAC group and 384 cases were assigned to the non-PNAC group. The PNAC group had a lower mean gestational age, lower mean birth weight, longer duration of invasive and non-invasive mechanical ventilation, a longer duration oxygen support, and longer hospital stay ( P  < 0.001 for all). The PNAC group had higher respiratory distress syndrome, hemodynamically significant patent ductus arteriosus, necrotizing enterocolitis (NEC) with stage II or higher, surgically treated NEC, late-onset sepsis, metabolic bone disease, and extrauterine growth retardation (EUGR) compared to the non-PNAC group ( P <  0.05 for all). In contrast with the non-PNAC group, the PNAC group received a higher maximum dose of amino acids and fat emulsion, more medium/long-chain fatty emulsion, less SMOF, had a longer duration of parenteral nutrition, lower rates of breastfeeding, higher incidence of feeding intolerance (FI), more accumulated days to achieve total enteral nutrition, less accumulated days of total calories up to standard 110 kcal/kg/day and slower velocity of weight growth ( P <  0.05 for all). Logistic regression analysis indicated that the maximum dose of amino acids ( OR , 5.352; 95% CI , 2.355 to 12.161), EUGR ( OR , 2.396; 95% CI , 1.255 to 4.572), FI ( OR , 2.581; 95% CI , 1.395 to 4.775), surgically treated NEC ( OR , 11.300; 95% CI , 2.127 ~ 60.035), and longer total hospital stay ( OR , 1.030; 95% CI , 1.014 to 1.046) were independent risk factors for the development of PNAC. SMOF ( OR , 0.358; 95% CI , 0.193 to 0.663) and breastfeeding ( OR , 0.297; 95% CI , 0.157 to 0.559) were protective factors for PNAC. Conclusions PNAC can be reduced by optimizing the management of enteral and parenteral nutrition and reducing gastrointestinal comorbidities in preterm infants.