Display omitted
•MES cathode for better bacterial growth and CO2 delivery is reviewed.•Strategies are provided for energy-efficient anodic electron generation.•MES chain-elongation suitable for ...high-value product formation and extraction.•MES integrated with other bioprocesses can be promising to sustain circular economy.
Recycling CO2 into organic products through microbial electrosynthesis (MES) is attractive from the perspective of circular bioeconomy. However, several challenges need to be addressed before scaling-up MES systems. In this review, recent advances in electrode materials, microbe-catalyzed CO2 reduction and MES energy consumption are discussed in detail. Anode materials are briefly reviewed first, with several strategies proposed to reduce the energy input for electron generation and enhance MES bioeconomy. This was followed by discussions on MES cathode materials and configurations for enhanced chemolithoautotroph growth and CO2 reduction. Various chemolithoautotrophs, effective for CO2 reduction and diverse bioproduct formation, on MES cathode were also discussed. Finally, research efforts on developing cost-effective process for bioproduct extraction from MES are presented. Future perspectives to improve product formation and reduce energy cost are discussed to realize the application of the MES as a chemical production platform in the context of building a circular economy.
Travel time estimation (TTE) is an important research topic in many geographic applications for smart city research. However, existing approaches either ignore the impact of transportation modes, or ...assume the mode information is known for each training trajectory and the query input. In this paper, we propose a multi-task learning model for travel time estimation called MTLM, which recommends the appropriate transportation mode for users, and then estimates the related travel time of the path. It integrates transportation-mode recommendation task and travel time estimation task to capture the mutual influence between them for more accurate TTE results. Furthermore, it captures spatio-temporal dependencies and transportation mode effect by learning effective representations for TTE. It combines the transportation-mode recommendation loss and TTE loss for training. Extensive experiments on real datasets demonstrate the effectiveness of our proposed methods.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the worldwide coronavirus (COVID-19) pandemic, has infected an estimated 525 million people with over 6 million deaths. ...Although COVID-19 is primarily a respiratory disease, an escalating number of neurologic symptoms have been reported in humans. Some neurologic symptoms, such as loss of smell or taste, are mild. However, other symptoms, such as meningoencephalitis or stroke, are potentially fatal. Along with surveys and postmortem evaluations on humans, scientists worked with several animal species to try to elucidate the causes of neurologic symptoms. Neurologic sequelae remain challenging to study due to the complexity of the nervous system and difficulties in identification and quantification of neurologic signs. We reviewed animal models used in the study of neurologic COVID-19, specifically research in mice, hamsters, ferrets, and nonhuman primates. We summarized findings on the presence and pathologic effects of SARS-CoV-2 on the nervous system. Given the need to increase understanding of COVID-19 and its effects on the nervous system, scientists must strive to obtain new information from animals to reduce mortality and morbidity with neurologic complications in humans.
The Hippo pathway is emerging as a key evolutionarily conserved signaling mechanism that controls organ size. Three membrane-associated proteins, Kibra, Merlin, and Expanded, regulate pathway ...activity, but the precise molecular mechanism by which they function is still poorly understood. Here we provide evidence that Merlin and Kibra activate Hippo signaling in parallel to Expanded at a spatially distinct cellular domain, the medial apical cortex. Merlin and Kibra together recruit the adapter protein Salvador, which in turn recruits the core kinase Hippo. In addition, we show that Crumbs has a dual effect on Hippo signaling. Crumbs promotes the ability of Expanded to activate the pathway but also sequesters Kibra to downregulate Hippo signaling. Together, our findings elucidate the mechanism of Hippo pathway activation by Merlin and Kibra, identify a subcellular domain for Hippo pathway regulation, and demonstrate differential activity of upstream regulators in different subcellular domains.
•Kibra, Merlin, and Salvador promote Hippo pathway activity from a non-junctional site•Kibra, Merlin, and Salvador recruit Hippo and Warts independently of Expanded•Crumbs sequesters Kibra junctionally to repress its function in growth control
Merlin, Kibra, and Expanded are believed to act in a complex at intercellular junctions to control Hippo pathway activity. Su et al. show that instead Merlin and Kibra function at the Drosophila apical medial cortex separately from Crumbs and Expanded, thereby identifying an additional subcellular domain for Hippo pathway regulation.
To convert wastes into sustainable liquid fuels and chemicals, new resource recovery technologies are required. Chain elongation is a carboxylate-platform bioprocess that converts short-chain ...carboxylates (SCCs) (e.g., acetate C2 and n-butyrate C4) into medium-chain carboxylates (MCCs) (e.g., n-caprylate C8 and n-caproate C6) with hydrogen gas as a side product. Ethanol or another electron donor (e.g., lactate, carbohydrate) is required. Competitive MCC productivities, yields (product vs. substrate fed), and specificities (product vs. all products) were only achieved previously from an organic waste material when exogenous ethanol had been added. Here, we converted a real organic waste, which inherently contains ethanol, into MCCs with n-caprylate as the target product. We used wine lees, which consisted primarily of settled yeast cells and ethanol from wine fermentation, and produced MCCs with a reactor microbiome. We operated the bioreactor at a pH of 5.2 and with continuous in-line extraction and achieved a MCC productivity of 3.9 g COD/L-d at an organic loading rate of 5.8 g COD/L-d, resulting in a promising MCC yield of 67% and specificities of 36% for each n-caprylate and n-caproate (72% for both). Compared to all other studies that used complex organic substrates, we achieved the highest n-caprylate-to-ncaproate product ratio of 1.0 (COD basis), because we used increased broth-recycle rates through the forward membrane contactor, which improved in-line extraction rates. Increased recycle rates also allowed us to achieve the highest reported MCC production flux per membrane surface area thus far (20.1 g COD/m
-d). Through microbial community analyses, we determined that an operational taxonomic unit (OTU) for Bacteroides spp. was dominant and was positively correlated with increased MCC productivities. Our data also suggested that the microbiome may have been shaped for improved MCC production by the high broth-recycle rates. Comparable abiotic studies suggest that further increases in the broth-recycle rates could improve the overall mass transfer coefficient and its corresponding MCC production flux by almost 30 times beyond the maximum that we achieved. With improved in-line extraction, the chain-elongation biotechnology production platform offers new opportunities for resource recovery and sustainable production of liquid fuels and chemicals.
Map inference algorithm aims to construct a digital map from other data sources automatically. Due to the labour intensity of traditional map creation and the frequent road change nowadays, map ...inference is deemed to be a promising solution to automatic map construction and update. However, existing map inference from GPS trajectories suffers from low GPS data quality, which makes the quality of the constructed map unsatisfactory. In this paper, we study the existing map inference algorithms using GPS trajectories. Different from previous surveys, we (1) include the most recent solutions and propose a new categorisation of method; (2) study how different types of GPS errors affect the quality of inference results; (3) evaluate the existing map inference quality measures regarding their ability to identify map quality issues. To achieve these goals, we conduct a comprehensive experimental study on several representative algorithms using both real-world datasets and synthetic datasets, which are generated from our proposed synthetic trajectory generator and artificial map generator. Overall, our study provides insightful observations regarding (1) which inference method performs better in each working scenario, (2) the general data quality requirements for map inference, (3) the direction of future works for quantitative map quality measures.
Papillary thyroid carcinoma (PTC) is the most common malignancy of the thyroid gland, with a relatively high cure rate. Distant metastasis (DM) of PTC is uncommon, but when it occurs, it ...significantly decreases the survival of PTC patients. The molecular mechanisms of DM in PTC have not been systematically studied. We performed whole exome sequencing and GeneseeqPrime (425 genes) panel sequencing of the primary tumor, plasma and matched white blood cell samples from 20 PTC with DM and 46 PTC without DM. We identified somatic mutations, gene fusions and copy number alterations and analyzed their relationships with DM of PTC. BRAF‐V600E was identified in 73% of PTC, followed by RET fusions (14%) in a mutually exclusive manner (P < 0.0001). We found that gene fusions (RET, ALK or NTRK1) (P < 0.01) and chromosome 22q loss (P < 0.01) were independently associated with DM in both univariate and multivariate analyses. A nomogram model consisting of chromosome 22q loss, gene fusions and three clinical variables was built for predicting DM in PTC (C‐index = 0.89). The plasma circulating tumor DNA (ctDNA) detection rate in PTC was only 38.9%; however, it was significantly associated with the metastatic status (P = 0.04), tumor size (P = 0.001) and invasiveness (P = 0.01). In conclusion, gene fusions and chromosome 22q loss were independently associated with DM in PTC and could serve as molecular biomarkers for predicting DM. The ctDNA detection rate was low in non–DM PTC but significantly higher in PTC with DM.
The study identified gene fusion and somatic copy number alterations, particularly chromosome 22q loss, to be risk factors for distance metastasis (DM) of PTC and provided a convenient tool for the prediction of PTC DM.
Microalgae are undergoing intense study as feedstock to produce biodiesel. However, due to the relatively low price of biodiesel, microalgae have recently been considered a novel source of food and ...functional products because they contain valuable natural products. Lipid extraction from wet microalgae slurries is considered an energy-saving extraction technique and often includes the use of liquid CO2, switchable solvent, organic solvent, dimethyl ether, and other pre-treatment methods. These methods led to either low extraction efficiencies additional treatment of the residue, or both. Therefore, super-high hydrostatic pressure (100–1000 MPa) is a processing technology mainly applied in the food industry for non-thermal sterilization that could offer several benefits: 1) a super-high pressure can disrupt cells and increase extraction yield; 2) non-thermal treatment will guarantee the extraction of biofunctional products without limited destruction; and 3) a super-high pressure saves energy costs for sterilization and denaturation of the residue, which could be used as a commercial edible protein or animal feed. However, there are no previous reports about lipid extraction by super-high hydrostatic pressure from wet microalgae slurries or regarding considerable challenges. In this study, we investigated two types of extraction from wet microalgae slurries by super-high hydrostatic pressure: one-step extraction and two-step extraction. We also compared the super-high hydrostatic pressure technique with high-pressure homogenization, ultrasonication and microwave extraction by evaluating cell disruption and lipid extraction yields. The highest cell disruption of 92.8 ± 2.7% and lipid extraction yield of 11.4 ± 0.4% were obtained when super-high hydrostatic pressure (SHHP) was applied in the one-step extraction process. In the two-step extraction process, the highest cell disruption of 87.8 ± 2.3% and lipid extraction yield of 10.1 ± 0.7% were obtained by SHHP treatment which was higher than those achieved by the other three treatments with the same wet microalgae slurry. Thus, SHHP can achieve high cell disruption and lipid extraction yields from wet microalgae slurries through the one-step extraction method.
•Super-high hydrostatic pressure was used to extract lipids from wet microalgae.•High cell disruption obtained by a one-step extraction process.•High lipid extraction yield obtained by a one-step extraction process.
► Multifunctional nanoparticles with a gold plasmonic shell and Fe3O4 magnetic core for simultaneous fast concentration and identification of bacteria using surface-enhanced Raman spectroscopy ...(SERS). ► Multifunctional nanoparticles condensed to a highly compact dot serving as a sensitive SERS-active substrate. ► Quick concentration of bacteria by applying an external point magnetic field to a mixture of bacteria and nanoparticles. ► Efficient differentiation of bacteria via principle component analysis of SERS spectra acquired from the dot area.
Multifunctional magnetic–plasmonic Fe3O4–Au core–shell nanoparticles (Au-MNPs) were prepared for simultaneous fast concentration of bacterial cells by applying an external point magnetic field, and sensitive detection and identification of bacteria using surface-enhanced Raman spectroscopy (SERS). We demonstrated that a spread of a 10μL drop of a mixture of 105cfu/mL bacteria and 3μg/mL Au-MNPs on a silicon surface can be effectively condensed into a highly compact dot within 5min by applying an external point magnetic field, resulting in 60 times more concentrated bacteria in the dot area than on the spread area without concentration. Surrounded by dense uniformly packed Au-MNPs, bacteria can be sensitively and reproducibly detected directly using SERS. The principle component analysis (PCA) showed that three different Gram-negative bacterial strains can be clearly differentiated. We also demonstrated that the condensed multifunctional Au-MNPs dot can be used as a highly sensitive SERS-active substrate and a limit of detection better than 0.1ppb was obtained in detection of small molecules such as 4-mercaptopyrine. This novel platform significantly simplifies the concentration and detection process, which holds great promise for applications in food safety, environmental monitoring, medical diagnoses, and chemical and biological threat detections.
Multi-objective spatial keyword query aims to find a set of objects that are reasonably distributed in spatial, with all query objectives to be satisfied. However, existing approaches mainly take the ...coverage of query keywords into account, while leaving the semantics of the textual data to be largely ignored. This limits us to return those rational results that are synonyms but morphologically different. To address this problem, this paper studies the problem of multi-objective spatial keyword query with semantics, and targets to return the object set that is optimum regarding to both spatial proximity and semantic relevance. Specifically, we take advantage of the probabilistic topic model and locality sensitive hashing (LSH), so that all query objectives can be satisfied in terms of their semantics. Afterwards, a novel indexing structure called LIR-tree is designed to integrate the spatial and semantic information of all objects in a balanced way. On top of the LIR-tree, we further propose a distance-owner based query processing algorithm, which provides tight bounds to achieve superb pruning effect in the searching phase. To speed up the processing, a distance owners based replacement strategy can be used to conduct approximate querying more efficiently. Empirical study based on a real dataset demonstrates the good effectiveness and efficiency of our proposed algorithms.
PDF
