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Huntington's disease (HD) is a fatal neurodegenerative disorder caused by a toxic gain-of-function CAG expansion in the first exon of the huntingtin (HTT) gene. The monogenic nature of HD makes mutant HTT (mHTT) inactivation a promising therapeutic strategy. Single nucleotide polymorphisms frequently associated with CAG expansion have been explored to selectively inactivate mHTT allele using the CRISPR/Cas9 system. One of such allele-selective approaches consists of excising a region flanking the first exon of mHTT by inducing simultaneous double-strand breaks at upstream and downstream positions of the mHTT exon 1. The removal of the first exon of mHTT deletes the CAG expansion and important transcription regulatory sites, leading to mHTT inactivation. However, the frequency of deletion events is yet to be quantified either in vitro or in vivo. Here, we developed accurate quantitative digital polymerase chain reaction-based assays to assess HTT exon 1 deletion in vitro and in fully humanized HU97/18 mice. Our results demonstrate that dual-single guide RNA (sgRNA) strategies are efficient and that 67% of HTT editing events are leading to exon 1 deletion in HEK293T cells. In contrast, these sgRNA actively cleaved HTT in HU97/18 mice, but most editing events do not lead to exon 1 deletion (10% exon 1 deletion). We also showed that the in vivo editing pattern is not affected by CAG expansion but may potentially be due to the presence of multiple copies of wildtype (wt)/mHTT genes HU97/18 mice as well as the slow kinetics of AAV-mediated CRISPR/Cas9 delivery. [ABSTRACT FROM AUTHOR]

Crime has major influences in urban life, from migration and mobility patterns, to housing prices and neighborhood liveability. However, urban crime studies still largely rely on static data reported by the various institutions and organizations dedicated to urban safety. In this paper, we demonstrate how the use of digital technologies enables the fine-grained analysis of specific crimes over time and space. This paper leverages the rise of ubiquitous sensing to investigate the issue of bike theft in Amsterdam—a city with a dominant cycling culture, where reportedly more than 80,000 bikes are stolen every year. We use active location tracking to unveil where stolen bikes travel to and what their temporal patterns are. This is the first study using tracking technologies to focus on two critical aspects of contemporary cities: active mobility and urban crime. [ABSTRACT FROM AUTHOR]

Using the fourth-round database of the Business Environment and Enterprise Performance Survey (2008/09 BEEPS), this study examines the determinants of discouragement in less developed countries in Eastern Europe and Central Asia. The results show that whereas firms' opaqueness, demographic factors, and distance between lenders and borrowers better explain the discouragement due to tough loan prices and/or loan application procedures, firm risk and banking concentration explain the incidence of discouraged borrowers due to the fear of rationing. Innovator status, the legal protection of creditors and lenders in the event of default, and the coverage of information sharing instruments help explain discouragement in a transversal way. [ABSTRACT FROM AUTHOR]

Background Chromobacterium violaceum is a bacterium commonly found in tropical and subtropical regions and is associated with important pharmacological and industrial attributes such as producing substances with therapeutic properties and synthesizing biodegradable polymers. Its genome was sequenced, however, approximately 40% of its genes still remain with unknown functions. Although C. violaceum is known by its versatile capacity of living in a wide range of environments, little is known on how it achieves such success. Here, we investigated the proteomic profile of C. violaceum cultivated in the absence and presence of high iron concentration, describing some proteins of unknown function that might play an important role in iron homeostasis, amongst others. Results Briefly, C. violaceum was cultivated in the absence and in the presence of 9 mM of iron during four hours. Total proteins were identified by LC-MS and through the PatternLab pipeline. Our proteomic analysis indicates major changes in the energetic metabolism, and alterations in the synthesis of key transport and stress proteins. In addition, it may suggest the presence of a yet unidentified operon that could be related to oxidative stress, together with a set of other proteins with unknown function. The protein-protein interaction network also pinpointed the importance of energetic metabolism proteins to the acclimatation of C. violaceum in high concentration of iron. Conclusions This is the first proteomic analysis of the opportunistic pathogen C. violaceum in the presence of high iron concentration. Our data allowed us to identify a yet undescribed operon that might have a role in oxidative stress defense. Our work provides new data that will contribute to understand how this bacterium achieve its capacity of surviving in harsh conditions as well as to open a way to explore the yet little availed biotechnological characteristics of this bacterium with the further exploring of the proteins of unknown function that we showed to be up-regulated in high iron concentration. [ABSTRACT FROM AUTHOR]

This paper aims to show the grammatical properties that distinguish ergative languages from nominative languages. It is assumed that the parameter that contrasts both types of languages has to do with the activation of the inherent ergative Case, which is assigned only in ergative languages. This means that this Case is never present in nominative languages. Additionally, it is argued that split systems tend to appear only in morphologically ergative languages as opposed to what happens in syntactically ergative languages, which do not exhibit splits. In line with this, tripartite case systems are predictable in morphological ergative languages. On the other hand, syntactically ergative languages tend to be more uniform in the sense that the nominative Case is usually assigned both to transitive objects and to intransitive subjects. This explains the reasons why there is a tendency in syntactically ergative languages for the absolutive arguments to exhibit a syntactic behavior commonly associated with the behavior of subject in accusative languages. [ABSTRACT FROM AUTHOR]

This paper shows that there exists a strong connection between Case evaluation and the assignment of the [AGENT] and [EXPERIENCER] theta roles to the external arguments of unergative and transitive verbs in languages such as Apinajé, Apäniekrá, Parkatêjê, Xavante and Maxacali. Additionally, we investigate whether the ergative Case and the dative Case in these languages correspond to inherent Case or to structural Case. We assume that these Cases are structurally valued by the functional pospositions [mã] and [te] in the vP domain. The strongest evidence that favors this analysis comes from the fact that the functional head T° does not enter in the derivation with abstract Case to value. Furthermore, the distribution of the pospositions [mã] and [te] clearly demonstrates that they behave as adpositions in the sense that they can co-occur with pronominal prefixes and can come enclitic to oblique phrases that appear in passive constructions. [ABSTRACT FROM AUTHOR]

Aim: To test the association between sociodemographic and social characteristics with COVID-19 cases and deaths in small and large Brazilian cities. Methods: This ecological study included COVID-19 data available in State Health Secretaries (managed by brasil.io API) and three national databases (IBGE, DATASUS and Embrapa). Temporal spread of COVID-19 in Brazil during the first year considered as outcome: a) days until 1st case in each city since 1st in the country; b) days until 1,000 cases/100,000 inhabitants since 1st case in each city; c) days until 1st death until 50 deaths/100,000 inhabitants. Covariates included geographic region, city social and environmental characteristics, housing conditions, job characteristics, socioeconomic and inequalities characteristics, and health services and coverage. The analysis were stratified by city size into small (<100,000 inhabitants) and large cities (≥100,00 inhabitants). Multiple linear regressions were performed to test associations of all covariates to adjust to potential confounders. Results: In small cities, the first cases were reported after 82.2 days and 1,000 cases/100,000 were reported after 117.8 days, whereas in large cities these milestones were reported after 32.1 and 127.7 days, respectively. For first death, small and large cities took 121.6 and 36.0 days, respectively. However, small cities were associated with more vulnerability factors to first case arrival in 1,000 cases/100,000 inhabitants, first death and 50 deaths/100,000 inhabitants. North and Northeast regions positively associated with faster COVID-19 incidence, whereas South and Southeast were least. Conclusion: Social and built environment characteristics and inequalities were associated with COVID-19 cases spread and mortality incidence in Brazilian cities. [ABSTRACT FROM AUTHOR]

El paradigma de la sociedad contemporánea es la red, como afirma Manuel Castells (1999) cuándo propone este concepto para que se piense el mundo frente a las tecnologías de información y comunicación. ¿Más como pensar la ciudad en red? Cuándo vemos una imagen aérea de una ciudad, con sus rutas que articulan puntos y regiones, tenemos una imagen perfecta de una red. Pero la evidencia absoluta entre la forma geométrica de una red no puede nos dejar iludirnos: esto no presupone el entendimiento de la sociedad urbana como red. El matemático Nikos Salingaros (2003) argumentó que "las fuerzas que hacen que la ciudad funcione son generadas por la diversidad y necesidad de cambio de información entre diferentes tipos de nodos", y Gabriel Dupuy (1985) escribió que "si buscamos localizar partes de un sistema, debemos hacerlo en espacios abstractos, espacios topológicos, espacios de n dimensiones, inhabituales en el planeamiento y que no corresponden a la percepción inmediata de la 'redes clásicas'. Así, las redes son, más que nada, una manera de pensar. Una manera de leer el mundo, una manera de actuar en el mundo. [ABSTRACT FROM AUTHOR]

Amsterdam is a culturally rich city attracting millions of tourists. Popular activities in Amsterdam consist of museum visits and boat tours. By strategically combining them, this paper presents an innovative approach using waterborne autonomous vehicles (WAVs) to improve the museum visitation in Amsterdam. Multi-source urban data including I Amsterdam card data and Instagram hashtags are used to reveal museum characteristics such as offline and online popularity of museums and visitation patterns. A multi-objective model is proposed to optimize WAV routes by considering museum characteristics and travel experiences. An experiment in the Amsterdam Central area was conducted to evaluate the viability of employing WAVs. By comparing WAVs with land transportation, the results demonstrate that WAVs can enhance travel experience to cultural destinations. The presented innovative WAVs can be extended to a larger variety of points of interest in cities. These findings provide useful insights on embracing artificial intelligence in urban tourism. [ABSTRACT FROM AUTHOR]

Over the last 10 years, ride-hailing companies (such as Uber and Grab) have proliferated in cities around the world. While generally beneficial from an economic viewpoint, having a plurality of operators that serve a given demand for point-to-point trips might induce traffic inefficiencies due to the lack of coordination between operators when serving trips. In fact, the efficiency of vehicle fleet management depends, among other things, density of the demand in the city, and in this sense having multiple operators in the market can be seen as a disadvantage. There is thus a tension between having a plurality of operators in the market, and the overall traffic efficiency. To this date, there is no systematic analysis of this trade-off, which is fundamental to design the best future urban mobility landscape. In this paper, we present the first systematic, data-driven characterization of the cost of non-coordination in urban on-demand mobility markets by proposing a simple, yet realistic, model. This model uses trip density and average traffic speed in a city as its input, and provides an accurate estimate of the additional number of vehicles that should circulate due to the lack of coordination between operators—the cost of non-coordination. We plot such cost across different cities—Singapore, New York (limited to the borough of Manhattan in this work), San Francisco, Vienna and Curitiba—and show that due to non-coordination, each additional operator in the market can increase the total number of circulating vehicles by up to 67%. Our findings could support city policy makers to make data supported decisions when regulating urban on-demand mobility markets in their cities. At the same time, our results outline the need of a more proactive government participation and the need for new, innovative solutions that would enable a better coordination of on-demand mobility operators. [ABSTRACT FROM AUTHOR]

Abstract: Studies on keratinolytic microorganisms have been mainly related to their biotechnological applications and association with animal pathologies. However, these organisms have an ecological relevance to recycling keratinous residues in nature. This work aimed to select and identify new culturable feather-degrading bacteria isolated from soils of Brazilian Amazon forest and Atlantic forest. Bacteria that were isolated from temperate soils and bacteria from Amazonian basin soil were tested for their capability to grow on feather meal agar (FMA). Proteolytic bacteria were tested for feather degradation and were further identified according to their morphological and biochemical characteristics. Also, molecular identification based on 16S rDNA gene sequencing was carried out. A total of 24 proteolytic and 20 feather-degrading isolates were selected; Most of the isolates were from the Bacillus genus (division Firmicutes), but one Aeromonas, two Serratia (γ-Proteobacteria), and one Chryseobacterium (Cytophaga–Flavobacterium group). [ABSTRACT FROM AUTHOR]

Poor air quality is the world's single largest environmental health risk, and air quality monitoring is crucial for developing informed air quality policies. Efforts to monitor air pollution in different countries are uneven, largely due to the high capital costs of reference air quality monitors (AQMs), especially for airborne particulate matter (PM). In sub-Saharan Africa, for example, few cities operate AQM systems. It is thus important to examine the potential of alternative monitoring approaches. Although PM measurements can be obtained from low-cost optical particle counters (OPCs), data quality can be an issue. This paper develops a new method using raw aerosol size distributions from multiple, surface-based low-cost OPCs to constrain the Multiangle Imaging SpectroRadiometer (MISR) component-specific, column aerosol optical depth (AOD) data, which contain some particle-size-resolved information. The combination allows us to derive surface aerosol concentrations for particles as small as ∼0.1 µ m in diameter, which MISR detects but are below the OPC detection limit of ∼0.5 µ m. As such, we obtain better constraints on the near-surface particulate matter (PM) concentration, especially as the smaller particles tend to dominate urban pollution. We test our method using data from five low-cost OPCs deployed in the city of Nairobi, Kenya, from 1 May 2016 to 2 March 2017. As MISR passes over Nairobi only once in about 8 d, we use the size-resolved MISR AODs to scale the more frequent Moderate Resolution Imaging Spectrometer (MODIS)-derived AODs over our sites. The size distribution derived from MISR and MODIS agrees well with that from the OPCs in the size range where the data overlap (adjusted- R2∼0.80). We then calculate surface-PM concentration from the combined data. The situation for this first demonstration of the technique had significant limitations. We thus identify factors that will reduce the uncertainty in this approach for future experiments. Within these constraints, the approach has the potential to greatly expand the range of cities that can afford to monitor long-term air quality trends and help inform public policy. [ABSTRACT FROM AUTHOR]

Poor air quality is the world's single largest environmental health risk, and air quality monitoring is crucial for developing informed air quality policies. Efforts to monitor air pollution in different countries are uneven, largely due to the high capital costs of reference air quality monitors (AQMs), especially for airborne particulate matter (PM). In sub-Saharan Africa, for example, few cities operate AQM systems. It is thus important to examine the potential of alternative monitoring approaches. Although PM measurements can be obtained from low-cost optical particle counters (OPCs), data quality can be an issue. This paper develops a new method using raw aerosol size distributions from multiple, surface-based low-cost Optical Particle Counters (OPCs) to calibrate the Multi-angle Imaging SpectroRadiometer (MISR) component-specific, column aerosol optical depth (AOD) data, that contain some particle-size-resolved information. The combination allows us to derive surface aerosol concentrations for particles as small as ~ 0.1 µm in diameter that MISR detects but are below the OPC detection limit of ~ 0.5 µm. As such, we obtain better constraints on the near-surface particulate matter (PM) concentration, especially as the smaller particles tend to dominate urban pollution. We test our method using data from five low-cost OPCs deployed in the city of Nairobi, Kenya, from May 1 2016 to March 2 2017. As MISR passes over Nairobi only once in about eight days, we use the size-resolved MISR AODs to scale the more frequent Moderate Resolution Imaging Spectrometer (MODIS)-derived AODs over our sites. The size distribution derived from MISR and MODIS agrees well with that from the OPCs in the size range where the data overlap (adjusted-R² ~ 0.80). We then calculate surface-PM concentration from the combined data. The situation for this first demonstration of the technique had significant limitations. We thus identify factors that will reduce the uncertainty in this approach for future experiments. Within these constraints, the approach has the potential to greatly expand the range of cities that can afford to monitor long-term air quality trends and help inform public policy. [ABSTRACT FROM AUTHOR]

Low-cost air sensing is changing the paradigm of ambient air quality management research and practices. However, consensus on a structured low-cost sensor calibration and performance evaluation framework is lacking. Our study aims to devise a standardized low-cost sensor calibration protocol and evaluate the performance of various calibration algorithms. Extensive collocation data were collected in stationary and mobile settings in two American cities, New York and Boston. We trained the calibration models using stationary data aggregated at various intervals to examine the performance of several commonly used calibration algorithms described in the literature. Linear models provide consistently satisfactory calibration results, indicating linear responses from the low-cost sensors in our stationary test environment. Its simplicity is recommended for citizen science and education usages. Models that can account for non-linear relationships, especially random forest, perform well and transfer between sensors better than generalized linear regression models for PM 2.5 calibration, which should be adopted for regulatory and scientific purposes. Data collected in a mobile validation campaign in Boston were passed through the best-performing calibration models to assess their transferability. The results indicate that models trained with data from a different urban environment and season in the stationary setting did not transfer well to a mobile setting. It is recommended that low-cost sensors should be calibrated more often than suggested in Environmental Protection Agency's air sensor performance evaluation guidelines and used in an environment that is as similar as possible to the calibration environment. [Display omitted] • Our work pilots the standardized EPA sensor performance evaluation guidelines. • We examined factors that affect low-cost sensor and calibration algorithm performance. • We observed better transferraiblity of machine learning algorithm in a stationary setting. • We demonstrated the risk of using low-cost sensors without a local calibration. [ABSTRACT FROM AUTHOR]

A four-week mini-project for teaching is described for an experimental physical chemistry or organic chemistry course. The activities included synthesis of a Pd catalyst, PdCl 2 supported on calcined coconut shell fiber, and its use in the preparation of 4-methylbiphenyl via Suzuki-Miyaura cross-coupling reaction. The technical skills and concepts that are typically presented in practical chemistry courses were covered, including notions of surface chemistry – development of new catalysts, modern organic synthesis, gas chromatography techniques, separation of mixtures, and stoichiometric calculations. [ABSTRACT FROM AUTHOR]

The aim of this research paper was to characterize coagulase-positive and coagulase-negative staphylococci from raw milk, Minas cheese, and production lines of Minas cheese processing. One hundred isolates from 3 different cheese producers were characterized using molecular approaches, such as PCR, molecular typing, and DNA sequencing. Staphylococcus aureus (88% of the isolates) was the most abundant followed by Staphylococcus epidermidis, Staphylococcus hyicus, and Staphylococcus warneri. Among the 22 enterotoxin genes tested, the most frequent was seh (62% of the isolates), followed by selx and ser. Hemolysin genes were widely distributed across isolates, and Panton-Valentine leukocidin and toxic shock syndrome toxin genes were also identified. Methicillin-resistant S. aureus were staphylococcal cassette chromosome mec III, IVa, IVd, and others nontypeable. In the phenotypic antibiotic resistance, multiresistant isolates were detected and resistance to penicillin was the most observed. Using spa typing, we identified several types and described a new one, t14969, isolated from cheese. These findings suggest that antibiotic resistance and potentially virulent strains from different sources can be found in the Brazilian dairy processing environment. Further research should be conducted with collaboration from regulatory agencies to develop programs of prevention of virulent and resistant strain dissemination in dairy products and the processing environment. [ABSTRACT FROM AUTHOR]