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Ensuring the correct use of cell lines is crucial to obtaining reliable experimental results and avoiding unnecessary waste of resources. Raman spectroscopy has been confirmed to be able to identify cell lines, but the collection time is usually 10-30 s. In this study, we acquired Raman spectra of five cell lines with integration times of 0.1 and 8 s, respectively, and the average accuracy of using long-short memory neural network to identify the spectra of 0.1 s was 95%, and the average accuracy of identifying the spectra of 8 s was 99.8%. At the same time, we performed data enhancement of 0.1 s spectral data by real-valued non-volume preserving method, and the recognition average accuracy of long-short memory neural networks recognition of the enhanced spectral data was improved to 96.2%. With this method, we shorten the acquisition time of Raman spectra to 1/80 of the original one, which greatly improves the efficiency of cell identification.

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The chemical recycling of poly(ethylene terephthalate) -PET- fractions, derived from actual household packaging waste streams, using solvolysis, was investigated. This recycling strategy was applied after a previous on-line automatic identification, by near-infrared spectroscopy -NIR-, and a subsequent selective sorting of the different PET materials that were present in the packaging wastes. Using this technology, it was possible to classify fractions exclusively including PET, virtually avoiding the presence of both other plastics and materials, such as paper, cardboard and wood, that are present in the packaging wastes, as they were efficiently recognised and differentiated. The simple PET fractions, including clear and monolayered materials, were adequate to be recycled by mechanical means meanwhile the complex PET fractions, containing highly coloured and multi-layered materials, were suitable candidates to be recycled by chemical routes. The depolymerisation capacity of the catalytic glycolysis, when applied to those complex PET wastes, was studied by evaluating the effect of the process parameters on the resulting formation and recovery of the monomer bis(2-hydroxyethyl) terephthalate -BHET- and the achieved quality of this reaction product. Comparable and reasonable results, in terms of monomer yield and its characteristics, were obtained independently of the type of complex PET waste that was chemically recycled.

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Lead service lines (LSLs), when present, are the largest source of lead in drinking water, and their removal is necessary to reduce public exposure to lead from drinking water. Unfortunately, the composition of many service lines (SLs) is uncertain. The town of Bennington, Vermont, for example, has unreliable SL records, making it challenging to build an inventory and conduct an LSL replacement program. In 2017, Bennington commenced a project to identify SL materials and replace all LSLs. 159 control homes, consisting of 99 LSL and 60 non-LSL sites, were chosen for record reviews, visual SL observations, fully flushed (FF) and sequential profile water sampling, and test excavations to evaluate method accuracies. Of the 159 control homes, records for 90 % of the 99 known LSL homes were accurate. Whereas 3 % of the 60 non-lead SL homes' records accurately identified SL material. Fully flushed and sequential profile samples (SPSs) were 73 % and 95 % accurate for identifying LSLs and 95 % and 83 % accurate for identifying non-LSLs, respectively. Results were 100 % accurate when visual observations, FF samples, and test excavation were used in a stepwise approach. A stepwise approach consisting of visual SL observations, FF samples, and SPSs achieved a 98 % accuracy at identifying LSLs and a 67 % cost reduction compared to performing test excavations at each home. Findings from this control group study are critical for state, tribal, and local officials to inform their decisions about the selected approach to identify unknown SLs.

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Identifying lane markings is a key technology in assisted driving and autonomous driving. The traditional sliding window lane detection algorithm has good detection performance in straight lanes and curves with small curvature, but its detection and tracking performance is poor in curves with larger curvature. Large curvature curves are common scenes in traffic roads. Therefore, in response to the problem of poor lane detection performance of traditional sliding window lane detection algorithms in large curvature curves, this article improves the traditional sliding window algorithm and proposes a sliding window lane detection calculation method, which integrates steering wheel angle sensors and binocular cameras. When a vehicle first enters a bend, the curvature of the bend is not significant. Traditional sliding window algorithms can effectively detect the lane line of the bend and provide angle input to the steering wheel, enabling the vehicle to travel along the lane line. However, as the curvature of the curve increases, traditional sliding window lane detection algorithms cannot track lane lines well. Considering that the steering wheel angle of the car does not change much during the adjacent sampling time of the video, the steering wheel angle of the previous frame can be used as input for the lane detection algorithm of the next frame. By using the steering wheel angle information, the search center of each sliding window can be predicted. If the number of white pixels within the rectangular range centered around the search center is greater than the threshold, the average of the horizontal coordinate values of these white pixels will be used as the horizontal coordinate value of the sliding window center. Otherwise, the search center will be used as the center of the sliding window. A binocular camera is used to assist in locating the position of the first sliding window. The simulation and experimental results show that compared with traditional sliding window lane detection algorithms, the improved algorithm can better recognize and track lane lines with large curvature in bends.

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Cell misuse and cross-contamination can affect the accuracy of cell research results and result in wasted time, manpower and material resources. Thus, cell line identification is important and necessary. At present, the commonly used cell line identification methods need cell staining and culturing. There is therefore a need to develop a new method for the rapid and automated identification of cell lines. Raman spectroscopy has become one of the emerging techniques in the field of microbial identification, with the advantages of being rapid and noninvasive and providing molecular information for biological samples, which is beneficial in the identification of cell lines. In this study, we built a library of Raman spectra for gastric mucosal epithelial cell lines GES-1 and gastric cancer cell lines, such as AGS, BGC-823, HGC-27, MKN-45, MKN-74 and SNU-16. Five spectral datasets were constructed using spectral data and included the full spectrum, fingerprint region, high-wavelength number region and Raman background of Raman spectra. A stacking ensemble learning model, SL-Raman, was built for different datasets, and gastric cancer cell identification was achieved. For the gastric cancer cells we studied, the differentiation accuracy of SL-Raman was 100% for one of the gastric cancer cells and 100% for six of the gastric cancer cells. Additionally, the separation accuracy for two gastric cancer cells with different degrees of differentiation was 100%. These results demonstrate that Raman spectroscopy combined with SL-Raman may be a new method for the rapid and accurate identification of gastric cancer. In addition, the accuracy of 94.38% for classifying Raman spectral background data using machine learning demonstrates that the Raman spectral background contains some useful spectral features. These data have been overlooked in previous studies.

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The proper maintenance of cancer cell lines is critical to maintain the integrity of any experiment. Proper maintenance includes handling of cell lines and maintaining records on usage and confirmation of identity. Cross-contamination of cancer cell lines has been well documented by the ATCC and must be avoided at all costs. In addition, contamination by Mycoplasma sp. is a well-known issue, which, if left unchecked, can affect all data collected as this contamination can affect cell line metabolism and has uncharacterized effects. Considerations and specific recommendations for the proper maintenance of cancer cell lines are presented here.

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Robustness analysis of adaptive control systems, when operating in a certain domain, has been a gulf during the past decades. This problem is more complicated in the case of non-linear dynamic systems including un-modelled dynamics as unstructured uncertainty. To find a clear solution for this famous and interesting problem, limitations and effects of controller operation on performance of on-line model identification procedure (and vice versa) must be determined. In this paper, as the main novelty, we show that it needs some developments and new concepts in robust control theory as the s-gap metric, generalized stability margin (GSM) and modifications on the gain bound calculation. These achievements help us to present an on-line identification method with its convergence proof in sense of the s-gap metric and a relation between GSM and identifier convergence area. Therefore, consideration of GSM in Adaptive Model Predictive Control (AMPC) cost function concludes a systematic solution relating controller robustness and adaptivity, clearly. To this aim, a linear matrix inequality (LMI) representation for GSM constraint is suggested. Also, the stability of AMPC on a certain operating domain is guaranteed in sense of the s-gap metric and GSM. All of these help to determine the attraction area of closed loop system and we show that there exists a trade-off between each two cases of the attraction area size, convergence area size and robustness of closed loop control system. Finally, simulations and experimental results imply on correctness of the proposed method.

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An analytical formula that relates the molecular constants of the Herzberg expression and experimental transition lines is developed herein with a difference algebraic approach (DAA) model. Based on the data-driven strategy, the DAA model is able to deal with the tiny uncertainties that exhibit behind the experimental transition lines, which is applied to the P branch emission spectra of some first overtone bands of the ground electronic state of 12C16O. The relationship can be used to generate transition lines with sufficient accuracy, as evident from the high J of agreement with the HITRAN database, Velichko data, Goorvitch data and quantum-mechanical data. In addition, line intensities, absorption oscillator strengths and Einstein A coefficients of these lines, which are introduced to enhance the dataset and are in good agreement with those of other authors, are also reported to validate our results. These various comparative results show that the proposed data-driven strategy based on the DAA model is expecting to be a good algorithm that relies on relatively limited data for training.

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Cell lines are applied on a large scale in the field of biomedicine, but they are susceptible to issues such as misidentification and cross-contamination. This situation is becoming worse over time due to the rapid growth of the biomedical field, and thus there is an urgent need for a more effective strategy to address the problem. As described herein, a cell coding method is established based on two types of uniform and stable glycan nanoparticles that are synthesized using the graft-copolymerization-induced self-assembly (GISA) method, which further exhibit distinct fluorescent properties due to elaborate modification with fluorescent labeling molecules. The different affinity between each nanoparticle and various cell lines results in clearly distinguishable differences in their endocytosis degrees, thus resulting in distinct characteristic fluorescence intensities. Through flow cytometry measurements, the specific signals of each cell sample can be recorded and turned into a map divided into different regions by statistical processing. Using this sensing array strategy, we have successfully identified six human cell lines, including one normal type and five tumor types. Moreover, cell contamination evaluation of different cell lines with HeLa cells as the contaminant in a semiquantitative analysis has also been successfully achieved. Notably, the whole process of nanoparticle fabrication and fluorescent testing is facile and the results are highly reliable.

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We report the first detection in space of the two doubly deuterated isotopologues of methyl acetylene. The species CHD2CCH and CH2DCCD were identified in the dense core L483 through nine and eight, respectively, rotational lines in the 72-116 GHz range using the IRAM 30m telescope. The astronomical frequencies observed here were combined with laboratory frequencies from the literature measured in the 29-47 GHz range to derive more accurate spectroscopic parameters for the two isotopologues. We derive beam-averaged column densities of (2.7 ± 0.5) × 1012 cm-2 for CHD2CCH and (2.2 ± 0.4) × 1012 cm-2 for CH2DCCD, which translate to abundance ratios CH3CCH/CHD2CCH = 34 ± 10 and CH3CCH/CH2DCCD = 42 ± 13. The doubly deuterated isotopologues of methyl acetylene are only a few times less abundant than the singly deuterated ones, concretely around 2.4 times less abundant than CH3CCD. The abundances of the different deuterated isotopologues with respect to CH3CCH are reasonably accounted for by a gas-phase chemical model in which deuteration occurs from the precursor ions C3H6D+ and C3H5D+, when the ortho-to-para ratio of molecular hydrogen is sufficiently low. This points to gas-phase chemical reactions, rather than grain-surface processes, as responsible for the formation and deuterium fractionation of CH3CCH in L483. The abundance ratios CH2DCCH/CH3CCD = 3.0 ± 0.9 and CHD2CCH/CH2DCCD = 1.25 ± 0.37 observed in L483 are consistent with the statistically expected values of three and one, respectively, with the slight overabundance of CHD2CCH compared to CH2DCCD being well explained by the chemical model.

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We report the detection of the oxygen-bearing complex organic molecules propenal (C2H3CHO), vinyl alcohol (C2H3OH), methyl formate (HCOOCH3), and dimethyl ether (CH3OCH3) toward the cyanopolyyne peak of the starless core TMC-1. These molecules are detected through several emission lines in a deep Q-band line survey of TMC-1 carried out with the Yebes 40m telescope. These observations reveal that the cyanopolyyne peak of TMC-1, which is the prototype of cold dark cloud rich in carbon chains, contains also O-bearing complex organic molecules like HCOOCH3 and CH3OCH3, which have been previously seen in a handful of cold interstellar clouds. In addition, this is the first secure detection of C2H3OH in space and the first time that C2H3CHO and C2H3OH are detected in a cold environment, adding new pieces in the puzzle of complex organic molecules in cold sources. We derive column densities of (2.2 ± 0.3) × 1011 cm™2, (2.5 ± 0.5) × 1012 cm-2, (1.1 ± 0.2) × 1012 cm-2, and (2.5 ± 0.7) × 1012 cm-2 for C2H3CHO, C2H3OH, HCOOCH3, and CH3OCH3, respectively. Interestingly, C2H3OH has an abundance similar to that of its well known isomer acetaldehyde (CH3CHO), with C2H3OH/CH3CHO ~ 1 at the cyanopolyyne peak. We discuss potential formation routes to these molecules and recognize that further experimental, theoretical, and astronomical studies are needed to elucidate the true mechanism of formation of these O-bearing complex organic molecules in cold interstellar sources.

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We report the first detection in space of the cumulene carbon chain l-H2C5. A total of eleven rotational transitions, with Jup = 7-10 and Ka = 0 and 1, were detected in TMC-1 in the 31.0-50.4 GHz range using the Yebes 40m radio telescope. We derive a column density of (1.8±0.5)×1010 cm-2. In addition, we report observations of other cumulene carbenes detected previously in TMC-1, to compare their abundances with the newly detected cumulene carbene chain. We find that l-H2C5 is ~4.0 times less abundant than the larger cumulene carbene l-H2C6, while it is ~300 and ~500 times less abundant than the shorter chains l-H2C3 and l-H2C4. We discuss the most likely gas-phase chemical routes to these cumulenes in TMC-1 and stress that chemical kinetics studies able to distinguish between different isomers are needed to shed light on the chemistry of C n H2 isomers with n > 3.

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We present the discovery in TMC-1 of allenyl acetylene, H2CCCHCCH, through the observation of nineteen lines with a signal-to-noise ratio ~4-15. For this species, we derived a rotational temperature of 7±1K and a column density of 1.2±0.2×1013 cm-2. The other well known isomer of this molecule, methyl diacetylene (CH3C4H), has also been observed and we derived a similar rotational temperature, Tr=7.0±0.3 K, and a column density for its two states (A and E) of 6.5±0.3×1012 cm-2. Hence, allenyl acetylene and methyl diacetylene have a similar abundance. Remarkably, their abundances are close to that of vinyl acetylene (CH2CHCCH). We also searched for the other isomer of C5H4, HCCCH2CCH (1.4-Pentadiyne), but only a3σ upper limit of 2.5×1012 cm-2 to the column density can be established. These results have been compared to state-of-the-art chemical models for TMC-1, indicating the important role of these hydrocarbons in its chemistry. The rotational parameters of allenyl acetylene have been improved by fitting the existing laboratory data together with the frequencies of the transitions observed in TMC-1.

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We present the first identification in interstellar space of the propargyl radical (CH2CCH). This species was observed in the cold dark cloud TMC-1 using the Yebes 40m telescope. The six strongest hyperfine components of the 20,2-10,1 rotational transition, lying at 37.46 GHz, were detected with signal-to-noise ratios in the range 4.6-12.3 σ. We derive a column density of 8.7 × 1013 cm-2 for CH2CCH, which translates to a fractional abundance relative to H2 of 8.7 × 10-9. This radical has a similar abundance to methyl acetylene, with an abundance ratio CH2CCH/CH3CCH close to one. The propargyl radical is thus one of the most abundant radicals detected in TMC-1, and it is probably the most abundant organic radical with a certain chemical complexity ever found in a cold dark cloud. We constructed a gas-phase chemical model and find calculated abundances that agree with, or fall two orders of magnitude below, the observed value depending on the poorly constrained low-temperature reactivity of CH2CCH with neutral atoms. According to the chemical model, the propargyl radical is essentially formed by the C + C2H4 reaction and by the dissociative recombination of C3Hn + ions with n = 4-6. The propargyl radical is believed to control the synthesis of the first aromatic ring in combustion processes, and it probably plays a key role in the synthesis of large organic molecules and cyclization processes to benzene in cold dark clouds.

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We report the detection of the sulfur-bearing species NCS, HCCS, H2CCS, H2CCCS, and C4S for the first time in space. These molecules were found towards TMC-1 through the observation of several lines for each species. We also report the detection of C5S for the first time in a cold cloud through the observation of five lines in the 31-50 GHz range. The derived column densities are N(NCS) = (7.8±0.6)×1011 cm-2, N(HCCS) = (6.8±0.6)×1011 cm-2, N(H2CCS) = (7.8±0.8)×1011 cm-2, N(H2CCCS) = (3.7±0.4)×1011 cm-2, N(C4S) = (3.8±0.4)×1010 cm-2, and N(C5S) = (5.0±1.0)×1010 cm-2. The observed abundance ratio between C3S and C4S is 340, that is to say a factor of approximately one hundred larger than the corresponding value for CCS and C3S. The observational results are compared with a state-of-the-art chemical model, which is only partially successful in reproducing the observed abundances. These detections underline the need to improve chemical networks dealing with S-bearing species.

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We present the discovery in TMC-1 of vinyl acetylene, CH2CHCCH, and the detection, for the first time in a cold dark cloud, of HCCN, HC4N, and CH3CH2CN. A tentative detection of CH3CH2CCH is also reported. The column density of vinyl acetylene is (1.2±0.2)×1013 cm-2, which makes it one of the most abundant closed-shell hydrocarbons detected in TMC-1. Its abundance is only three times lower than that of propylene, CH3CHCH2. The column densities derived for HCCN and HC4N are (4.4±0.4)×1011 cm-2 and (3.7±0.4)×1011 cm-2, respectively. Hence, the HCCN/HC4N abundance ratio is 1.2±0.3. For ethyl cyanide we derive a column density of (1.1 ±0.3)×1011 cm-2. These results are compared with a state-of-the-art chemical model of TMC-1, which is able to account for the observed abundances of these molecules through gas-phase chemical routes.

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Using the Yebes 40m and IRAM 30m radiotelescopes, we detected two series of harmonically related lines in space that can be fitted to a symmetric rotor. The lines have been seen towards the cold dense cores TMC-1, L483, L1527, and L1544. High level of theory ab initio calculations indicate that the best possible candidate is the acetyl cation, CH3CO+, which is the most stable product resulting from the protonation of ketene. We have produced this species in the laboratory and observed its rotational transitions Ju = 10 up to Ju = 27. Hence, we report the discovery of CH3CO+ in space based on our observations, theoretical calculations, and laboratory experiments. The derived rotational and distortion constants allow us to predict the spectrum of CH3CO+ with high accuracy up to 500 GHz. We derive an abundance ratio N(H2CCO)/N(CH3CO+)~44. The high abundance of the protonated form of H2CCO is due to the high proton affinity of the neutral species. The other isomer, H2CCOH+, is found to be 178.9 kJ mol-1 above CH3CO+. The observed intensity ratio between the K=0 and K=1 lines, ~2.2, strongly suggests that the A and E symmetry states have suffered interconversion processes due to collisions with H and/or H2, or during their formation through the reaction of H 3 + with H2CCO.

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CONTEXT: Yebes 40m radio telescope is the main and largest observing instrument at Yebes Observatory and it is devoted to Very Long Baseline Interferometry (VLBI) and single dish observations since 2010. It has been covering frequency bands between 2 GHz and 90 GHz in discontinuous and narrow windows in most of the cases, to match the current needs of the European VLBI Network (EVN) and the Global Millimeter VLBI Array (GMVA). AIMS: Nanocosmos project, a European Union funded synergy grant, opened the possibility to increase the instantaneous frequency coverage to observe many molecular transitions with single tunnings in single dish mode. This reduces the observing time and maximises the output from the telescope. METHODS: We present the technical specifications of the recently installed 31.5 - 50GHz (Q band) and 72 - 90.5 GHz (W band) receivers along with the main characteristics of the telescope at these frequency ranges. We have observed IRC+10216, CRL 2688 and CRL 618, which harbour a rich molecular chemistry, to demonstrate the capabilities of the new instrumentation for spectral observations in single dish mode. RESULTS: The results show the high sensitivity of the telescope in the Q band. The spectrum of IRC+10126 offers a signal to noise ratio never seen before for this source in this band. On the other hand, the spectrum normalised by the continuum flux towards CRL 618 in the W band demonstrates that the 40 m radio telescope produces comparable results to those from the IRAM 30 m radio telescope, although with a smaller sensitivity. The new receivers fulfil one of the main goals of Nanocosmos and open the possibility to study the spectrum of different astrophysical media with unprecedented sensitivity.

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It is of vital importance to identify the pleural line when performing lung ultrasound, as the pleural line not only indicates the interface between the chest wall and lung, but offers additional diagnostic information. In the current clinical practice, the pleural line is visually detected and evaluated by clinicians, which requires experiences and skills with challenges for the novice. In this study, we developed a computer-aided technique for automated pleural line detection using ultrasound. The method first utilized the Radon transform to detect line objects in the ultrasound images. The relation of the body mass index and chest wall thickness was then applied to estimate the range of the pleural thickness, based on which the pleural line was detected together with the consideration of the ultrasonic properties of the pleural line. The proposed method was validated by testing 83 ultrasound data sets collected from 21 pneumothorax patients. The pleural lines were successfully identified in 76 data sets by the automated method (successful detection rate 91.6%). In those successful cases, the depths of the pleural lines measured by the automated method agreed with those manually measured as confirmed with the Bland-Altman test. The measurement errors were below 5% in terms of the pleural line depth. As a conclusion, the proposed method could detect the pleural line in an automated manner in the defined data set. In addition, the method may potentially act as an alternative to visual inspection after further tests on more diverse data sets are performed in future studies.

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Cancer cell lines serve as invaluable model systems for cancer biology research and help in evaluating the efficacy of new therapeutic agents. However, cell line contamination and misidentification have become one of the most pressing problems affecting biomedical research. Available methods of cell line authentication suffer from limited access, time-consuming and often costly for many researchers, hence a new and cost-effective approach for cell line authentication is needed. In this regard, we developed a new method called CeL-ID for cell line authentication using genomic variants as a byproduct derived from RNA-seq data. CeL-ID was trained and tested on publicly available more than 900 RNA-seq dataset derived from the Cancer Cell Line Encyclopedia (CCLE) project; including most frequently used adult and pediatric cancer cell lines. We generated cell line specific variant profiles from RNA-seq data using our in-house pipeline followed by pair-wise variant profile comparison between cell lines using allele frequencies and depth of coverage values of the entire variant set. Comparative analysis of variant profiles revealed that they differ significantly from cell line to cell line whereas identical, synonymous and derivative cell lines share high variant identity and their allelic fractions are highly correlated, which is the basis of this cell line authentication protocol. Additionally, CeL-ID also includes a method to estimate the possible cross-contamination using a linear mixture model with any possible CCLE cells in case no perfect match was detected.