Proteomic Analysis of Heloderma horridum horridum Venom: Assessment to Its Transcriptome and Newfound Proteins.

Heloderma horridum horridum, a venomous reptile native to America, has a venom with potential applications in treating type II diabetes. In this work, H. h. horridum venom was extracted, lyophilized, and characterized using enzymatic assays for hyaluronidase, phospholipase, and protease. Proteomic analysis of the venom was conducted employing bottom-up/shotgun approaches, SDS-PAGE, high-pH reversed-phase chromatography, and fractionation of tryptic peptides using nano-LC-MS/MS. The proteins found in H. h. horridum venom were reviewed according to the classification of the transcriptome previously reported. The proteomic approach identified 101 enzymes, 36 other proteins, 15 protein inhibitors, 11 host defense proteins, and 1 toxin, including novel venom components such as calcium-binding proteins, phospholipase A2 inhibitors, serpins, cathepsin, subtilases, carboxypeptidase-like, aminopeptidases, glycoside hydrolases, thioredoxin transferases, acid ceramidase-like, enolase, multicopper oxidases, phosphoglucose isomerase (PGI), fructose-1,6-bisphosphatase class 1, pentraxin-related, peptidylglycine α-hydroxylating monooxygenase/peptidyl-hydroxyglycine α-amidating lyase, carbonic anhydrase, acetylcholinesterase, dipeptidylpeptidase, and lysozymes. These findings contribute to understanding the venomous nature of H. h. horridum and highlight its potential as a source of bioactive compounds. Data are available via PRoteomeXchange with the identifier PXD052417.

Genomic Evolution Strategy in SARS-CoV-2 Lineage B: Coevolution of Cis Elements.

In the SARS-CoV-2 lineage, RNA elements essential for its viral life cycle, including genome replication and gene expression, have been identified. Still, the precise structures and functions of these RNA regions in coronaviruses remain poorly understood. This lack of knowledge points out the need for further research to better understand these crucial aspects of viral biology and, in time, prepare for future outbreaks. In this research, the in silico analysis of the cis RNA structures that act in the alpha-, beta-, gamma-, and deltacoronavirus genera has provided a detailed view of the presence and adaptation of the structures of these elements in coronaviruses. The results emphasize the importance of these cis elements in viral biology and their variability between different viral variants. Some coronavirus variants in some groups, depending on the cis element (stem-loop1 and -2; pseudoknot stem-loop1 and -2, and s2m), exhibited functional adaptation. Additionally, the conformation flexibility of the s2m element in the SARS variants was determined, suggesting a coevolution of this element in this viral group. The variability in secondary structures suggests genomic adaptations that may be related to replication processes, genetic regulation, as well as the specific pathogenicity of each variant. The results suggest that RNA structures in coronaviruses can adapt and evolve toward different viral variants, which has important implications for viral adaptation, pathogenicity, and future therapeutic strategies.

Synthesis, Characterization and Photophysical Properties of a New Family of Rare-earth Cluster-based Metal-organic Frameworks.

In this work, nine new rare-earth metal-organic frameworks (RE-MOFs, where RE = Lu(III), Yb(III), Tm(III), Er(III), Ho(III), Dy(III), Tb(III), Gd(III), and Eu(III)) isostructural to Zr-MOF-808 are synthesized, characterized, and studied regarding their photophysical properties. Materials with high crystallinity and surface area are obtained from a reproducible synthetic procedure that involves the use of two fluorinated modulators. At the same time, these new RE-MOFs display tunable photoluminescent properties due to efficient linker-to-metal energy transfer promoted by the antenna effect, resulting in a series of RE-MOFs displaying lanthanoid-based emissions spanning the visible and near-infrared regions of the electromagnetic spectrum.

Visualizing flow dynamics and restart of Carbopol gel solutions in tube and parallel-plates geometries with wall slip.

The present study examines the impact of slip in Carbopol solutions during the restart flow in pipelines utilizing in situ visualization techniques. Rheological tests were conducted using smooth and hatched parallel plate geometries to obtain the rheological characteristics of the solutions. The behavior of the solutions in the creep tests is compared with those in the experimental unit. Three flow regimes were identified through rheological and experimental setup tests: non-flow, slip, and yielded. The slip regime allowed the establishment of a slip static yield stress value, indicating significant deformation states, and a restart pressure decrease of about 61% when compared to the static yield stress. The flow dynamics under the wall slip effect is captured by velocity profiles, velocity contour maps and velocity gradient. Transient correlations of the scaling law type were determined, with wall slip in proportion to the velocity gradient and wall shear stress. Additionally, the concentration of viscoplastic material in the solution increased the scaling law index. This research seeks to provide valuable findings by quantifying the effects of apparent wall slip through in situ measurements. Such insights are crucial for designing and managing pipeline transport systems that handle yield stress fluids, applicable across various industries including cosmetics, food processing, and the production of waxy oils.

Long-term antigen-specific immune response by an oncolytic adenovirus encoding SP-SA-E7-4-1BBL in HPV-16 cancer model.

BACKGROUND: To describe an oncolytic adenovirus (OAd) encoding SP-SA-E7-4-1BBL that is capable of inducing tumor regression in therapeutic assays. Herein, we tested whether the antitumor effect is given by the induction of a tumor-specific immune response, as well as the minimum dose needed to elicit antitumor protection and monitor the OAd biodistribution over time. METHODS AND RESULTS: C57BL/6 mice (n = 5) per group were immunized twice with OAds encoding SP-SA-E7-4-1BBL, SA-E7-4-1BBL, or SP-SA-4-1BBL and challenged with TC-1 cancer cells. The DNA construct SP-SA-E7-4-1BBL was employed as a control via biolistic or PBS injection. Groups without tumor development at 47 days were rechallenged with TC-1 cells, and follow-up lasted until day 90. The minimum dose of OAd to induce the antitumor effect was established by immunization using serial dilution doses. The cytometry bead assay and the ELISpot assay were used to evaluate cytokine release in response to ex vivo antigenic stimulation. The distribution profile of the OAd vaccine was evaluated in the different organs by histological, immunohistochemical and qPCR analyses. The OAd SP-SA-E7-4-1BBL-immunized mice did not develop tumors even in a rechallenge. A protective antitumor effect was observed from a dose that is one hundredth of most reports of adenoviral vaccines. Immunization with OAd increases Interferon-gamma-producing cells in response to antigen stimulation. OAd was detected in tumors over time, with significant morphological changes, contrary to nontumor tissues. CONCLUSIONS: The OAd SP-SA-E7-4-1BBL vaccine confers a prophylactic, safe, long-lasting, and antigen-dependent antitumor effect mediated by a Th1 antitumor immune response.

Hamamelis virginiana L. extract presents antimicrobial and antibiofilm effects, absence of cytotoxicity, anti-inflammatory action, and potential to fight infections through the nitric oxide production by macrophages.

The potential of H. virginiana L. was evaluated against Candida spp. (C. albicans, C. dubliniensis, C. glabrata, C. guilliermondii, C. krusei, and C. tropicalis) and bacteria (Acinetobacter baumannii, Escherichia coli, Enterococcus faecalis, Klebsiella pneumoniae, Staphylococcus aureus, and Streptococcus mutans). Effect on murine macrophages (RAW 264.7) was also evaluated with respect to cytotoxicity and production of cytokines (IL-1ß and TNF-α) and nitric oxide (NO). The most effective concentrations of the extract were determined by microdilution broth. These concentrations were analyzed on biofilms, after 5 min or 24 h exposure. Cytotoxicity was performed by MTT assay and quantification of cytokines and NO by ELISA and Griess reagent, respectively. The extract acted against the planktonic forms and provided significant reductions of all the microbial biofilms; besides, showed no cytotoxic effect, except at 100 mg/mL, after 24 h exposure. There was cytokine production; however, a modulatory effect was observed in groups exposed to lipopolysaccharide (LPS) from E. coli. NO production was similar or higher than the control group. Thus, H. virginiana L. extract showed antimicrobial and antibiofilm effects; absence of cytotoxicity for RAW 264.7; anti-inflammatory action; and potential to fight infections through the NO production.

Field Programmable Gate Array-Based Smart Switch to Avoid Inrush Current in PV Installations.

This paper introduces an FPGA-based implementation of a smart switch designed to avoid inrush currents occurring during the connection of single-phase transformers utilized in grid-connected photovoltaic (PV) systems. The magnitude of inrush currents is notably impacted by the residual flux within the transformer core and the precise moment of energization relative to the wave cycle. Alternative methods frequently hinge on intricate procedures to estimate residual flux. This challenge is adeptly circumvented by the innovative smart control system proposed herein, rendering it a cost-effective solution for grid-connected PV systems. The proposed solution for mitigating inrush current remains effective, even in the face of challenges with current and voltage sensors. This resilience arises from the system's ability to learn and adapt by leveraging information acquired from the network.

Implementation of a Real-Time Brain-to-Brain Synchrony Estimation Algorithm for Neuroeducation Applications.

This study centers on creating a real-time algorithm to estimate brain-to-brain synchronization during social interactions, specifically in collaborative and competitive scenarios. This type of algorithm can provide useful information in the educational context, for instance, during teacher-student or student-student interactions. Positioned within the context of neuroeducation and hyperscanning, this research addresses the need for biomarkers as metrics for feedback, a missing element in current teaching methods. Implementing the bispectrum technique with multiprocessing functions in Python, the algorithm effectively processes electroencephalography signals and estimates brain-to-brain synchronization between pairs of subjects during (competitive and collaborative) activities that imply specific cognitive processes. Noteworthy differences, such as higher bispectrum values in collaborative tasks compared to competitive ones, emerge with reliability, showing a total of 33.75% of significant results validated through a statistical test. While acknowledging progress, this study identifies areas of opportunity, including embedded operations, wider testing, and improved result visualization. Beyond academia, the algorithm's utility extends to classrooms, industries, and any setting involving human interactions. Moreover, the presented algorithm is shared openly, to facilitate implementations by other researchers, and is easily adjustable to other electroencephalography devices. This research not only bridges a technological gap but also contributes insights into the importance of interactions in educational contexts.

Wearable Biosensor Technology in Education: A Systematic Review.

Wearable Biosensor Technology (WBT) has emerged as a transformative tool in the educational system over the past decade. This systematic review encompasses a comprehensive analysis of WBT utilization in educational settings over a 10-year span (2012-2022), highlighting the evolution of this field to address challenges in education by integrating technology to solve specific educational challenges, such as enhancing student engagement, monitoring stress and cognitive load, improving learning experiences, and providing real-time feedback for both students and educators. By exploring these aspects, this review sheds light on the potential implications of WBT on the future of learning. A rigorous and systematic search of major academic databases, including Google Scholar and Scopus, was conducted in accordance with the PRISMA guidelines. Relevant studies were selected based on predefined inclusion and exclusion criteria. The articles selected were assessed for methodological quality and bias using established tools. The process of data extraction and synthesis followed a structured framework. Key findings include the shift from theoretical exploration to practical implementation, with EEG being the predominant measurement, aiming to explore mental states, physiological constructs, and teaching effectiveness. Wearable biosensors are significantly impacting the educational field, serving as an important resource for educators and a tool for students. Their application has the potential to transform and optimize academic practices through sensors that capture biometric data, enabling the implementation of metrics and models to understand the development and performance of students and professors in an academic environment, as well as to gain insights into the learning process.

Hyperprolactinemia modifies extracellular matrix components associated with collagen fibrillogenesis in harderian glands of non- and pregnant female mice.

The harderian gland (HG) is a gland located at the base of the nictating membrane and fills the inferomedial aspect of the orbit in rodents. It is under the influence of the hypothalamic-pituitary-gonadal axis and, because of its hormone receptors, it is a target tissue for prolactin (PRL) and sex steroid hormones (estrogen and progesterone). In humans and murine, the anterior surface of the eyes is protected by a tear film synthesized by glands associated with the eye. In order to understand the endocrine changes caused by hyperprolactinemia in the glands responsible for the formation of the tear film, we used an animal model with metoclopramide-induced hyperprolactinemia (HPRL). Given the evidences that HPRL can lead to a process of cell death and tissue fibrosis, the protein expression of small leucine-rich proteoglycans (SLRPs) was analyzed through immunohistochemistry in the HG of the non- and the pregnant female mice with hyperprolactinemia. The SRLPs are related to collagen fibrillogenesis and they participate in pro-apoptotic signals. Our data revealed that high prolactin levels and changes in steroid hormones (estrogen and progesterone) can lead to an alteration in the amount of collagen, and in the structure of type I and III collagen fibers through changes in the amounts of lumican and decorin, which are responsible for collagen fibrillogenesis. This fact can lead to the impaired functioning of the HG by excessive apoptosis in the HG of the non- and the pregnant female mice with HPRL and especially in the HG of pregnancy-associated hyperprolactinemia.

Axial vs equatorial: Capturing the intramolecular charge transfer state geometry in conformational polymorphic crystals of a donor-bridge-acceptor dyad in nanosecond-time-scale.

Two conformational polymorphs of a donor-bridge-acceptor (D-B-A) dyad, p-(CH3)2N-C6H4-(CH2)2-(1-pyrenyl)/PyCHDMA, were studied, where the electron donor (D) moiety p-(CH3)2N-C6H4/DMA is connected through a bridging group (B), -CH2-CH2-, to the electron acceptor (A) moiety pyrene. Though molecular dyads like PyCHDMA have the potential to change solar energy into electrical current through the process of photoinduced intramolecular charge transfer (ICT), the major challenge is the real-time investigation of the photoinduced ICT process in crystals, necessary to design solid-state optoelectronic materials. The time-correlated single photon counting (TCSPC) measurements with the single crystals showed that the ICT state lifetime of the thermodynamic form, PyCHDMA1 (pyrene and DMA: axial), is ∼3 ns, whereas, for the kinetic form, PyCHDMA20 (pyrene and DMA: equatorial), it is ∼7 ns, while photoexcited with 375 nm radiation. The polymorphic crystals were photo-excited and subsequently probed with a pink Laue x-ray beam in time-resolved x-ray diffraction (TRXRD) measurements. The TRXRD results suggest that in the ICT state, due to electron transfer from the tertiary N-atom in DMA moiety to the bridging group and pyrene moiety, a decreased repulsion between the lone-pair and the bond-pair at N-atom induces planarity in the C-N-(CH3)2 moiety, in both polymorphs. The Natural Bond Orbital calculations and partial atomic charge analysis by Hirshfeld partitioning also corroborated the same. Although the interfragment charge transfer (IFCT) analysis using the TDDFT results showed that for the charge transfer excitation in both conformers, the electrons were transferred from the DMA moiety to mostly the pyrene moiety, the bridging group has little role to play in that.

FPGA-Based Smart Sensor to Detect Current Transformer Saturation during Inrush Current Measurement.

Current transformer saturation affects measurement accuracy and, consequently, protection reliability. One important concern in the case of overcurrent protections is the discrimination between faults and inrush current in power transformers. This paper presents an FPGA-based smart sensor to detect current transformer saturation, especially during inrush current conditions. Several methods have been proposed in the literature, but some are unsuitable for inrush currents due to their particular waveform. The proposed algorithm implemented on the smart sensor uses two time-domain features of the measured secondary current: the second-order difference function and the third-order statistic central moment. The proposed smart sensor presents high effectiveness and immunity against noise with accurate results in different conditions: different residual flux, resistive burdens, sampling frequency, and noise levels. The points at which saturation starts are detected with an accuracy of approximately 100%. Regarding the end of saturation, the proposed method detects the right ending points with a maximum error of a sample. The smart sensor has been tested on experimental online and real-time conditions (including an anti-aliasing filter) with accurate results. Unlike most existing methods, the proposed smart sensor operates efficiently during inrush conditions. The smart sensor presents high-speed processing despite its simplicity and low computational cost.

Driving Sustainability: Carbon Footprint, 3D Printing, and Legislation concerning Electric and Autonomous Vehicles.

In recent years, there has been a remarkable development in the technology and legislation related to electric and autonomous vehicles (i.e., EVs/AVs). This technological advancement requires the deployment of the most up-to-date supporting infrastructure to achieve safe operation. Further infrastructure is needed for Level 5 vehicles, namely the introduction of super-fast wireless 5G technology. To achieve harmony between the rapid technological advancement of EVs/AVs and environmental preservation, enacting legislation related to their sustainable use is vital. Thus, this manuscript provides a review of the technological development of EVs/AVs, with a special focus on carbon footprints and the implementation of additive manufacturing using recycled materials. While EVs have a 12.13% increased carbon footprint compared to conventional vehicles, AVs with basic and advanced intelligence features have an increased carbon footprint of 41.43% and 99.65%, respectively. This article emphasizes that the integration of 3D-printed components has the potential to offset this impact with a substantial 60% reduction. As a result, custom-made solutions involving 3D printing are explored, leading to greater speed, customization, and cost-effectiveness for EVs/AVs. This article also lists the advantages and disadvantages of the existing legislation in Spain, the United Kingdom, and the western Balkans, demonstrating various approaches to promoting electric mobility and the development of autonomous vehicles. In Spain, initiatives like the MOVES program incentivize EV adoption, while the UK focuses on expanding the EV market and addressing concerns about EVs' quiet operation. In the western Balkans, the adoption of legislation lags behind, with limited incentives and infrastructure for EVs. To boost sales, legal mechanisms are necessary to reduce costs and improve accessibility, in addition to offering subsidies for the purchase of EVs. To this end, an analysis of the incentive measures proposed for the development and use of renewable power sources for the supply of energy for EVs/AVs is presented.

Vehicle and Driver Monitoring System Using On-Board and Remote Sensors.

This paper presents an integrated monitoring system for the driver and the vehicle in a single case of study easy to configure and replicate. On-board vehicle sensors and remote sensors are combined to model algorithms for estimating polluting emissions, fuel consumption, driving style and driver's health. The main contribution of this paper is the analysis of interactions among the above monitored features highlighting the influence of the driver in the vehicle performance and vice versa. This analysis was carried out experimentally using one vehicle with different drivers and routes and implemented on a mobile application. Compared to commercial driver and vehicle monitoring systems, this approach is not customized, uses classical sensor measurements, and is based on simple algorithms that have been already proven but not in an interactive environment with other algorithms. In the procedure design of this global vehicle and driver monitoring system, a principal component analysis was carried out to reduce the variables used in the training/testing algorithms with objective to decrease the transfer data via Bluetooth between the used devices: a biometric wristband, a smartphone and the vehicle's central computer. Experimental results show that the proposed vehicle and driver monitoring system predicts correctly the fuel consumption index in 84%, the polluting emissions 89%, and the driving style 89%. Indeed, interesting correlation results between the driver's heart condition and vehicular traffic have been found in this analysis.

Quantum Information Entropy for Another Class of New Proposed Hyperbolic Potentials.

In this work, we investigate the Shannon entropy of four recently proposed hyperbolic potentials through studying position and momentum entropies. Our analysis reveals that the wave functions of the single-well potentials U0,3 exhibit greater localization compared to the double-well potentials U1,2. This difference in localization arises from the depths of the single- and double-well potentials. Specifically, we observe that the position entropy density shows higher localization for the single-well potentials, while their momentum probability density becomes more delocalized. Conversely, the double-well potentials demonstrate the opposite behavior, with position entropy density being less localized and momentum probability density showing increased localization. Notably, our study also involves examining the Bialynicki-Birula and Mycielski (BBM) inequality, where we find that the Shannon entropies still satisfy this inequality for varying depths u¯. An intriguing observation is that the sum of position and momentum entropies increases with the variable u¯ for potentials U1,2,3, while for U0, the sum decreases with u¯. Additionally, the sum of the cases U0 and U3 almost remains constant within the relative value 0.01 as u¯ increases. Our study provides valuable insights into the Shannon entropy behavior for these hyperbolic potentials, shedding light on their localization characteristics and their relation to the potential depths. Finally, we extend our analysis to the Fisher entropy F¯x and find that it increases with the depth u¯ of the potential wells but F¯p decreases with the depth.

An Entropy-Based Condition Monitoring Strategy for the Detection and Classification of Wear Levels in Gearboxes.

Gears are reliable and robust elements that are found in any power transmission system. However, gears are prone to present incipient faults, such as wear, since they are constantly subjected to contact forces. Due to gears playing a key role in many industrial processes, it is important to develop condition monitoring strategies that ensure the proper functioning of the related power transmission system and the overall components. In this regard, the data on entropy provide relevant information that allow us to identify and quantify the effect of different wear levels in gears. Therefore, in this work, we proposed the use of seven entropy-related features to perform the identification of different wear severities in a gearbox. The novelty of this proposal lies in the use of the entropy features to carry out a high-performance characterization of the available vibration signals that are acquired from experimental tests. The novelty of this proposal lies in the fusion of three different techniques: entropy features, linear discriminant analysis, and artificial neural networks to obtain a machine learning approach for improving the detection of different wear severities in gears compared to other reported methodologies. This situation is achieved due to the high-performance characterization of the available vibration signals that are acquired from experimental tests. Additionally, the entropy features are subjected to a feature space transformation by means of linear discriminant analysis to obtain a 2D representation and, finally, the set of features extracted by linear discriminant analysis are used as inputs of a neural network-based classifier to determine the severity of wear that is present in the gears. The proposed methodology is validated and compared with a conventional statistical approach to show the improvement in the classification.

Microorganisms isolated in patients with post-cardiac surgery mediastinitis at a cardiology hospital of Mexico City.

INTRODUCTION: Mediastinitis after cardiovascular surgery gives rise to prolonged hospital stay and increased medical care costs, and is associated with high in-hospital mortality. OBJECTIVE: To describe the clinical characteristics of patients with post-surgical mediastinitis, including the isolated microorganisms, resistance profile, and in-hospital survival. METHODS: Cross-sectional study of patients with bacteriologically-confirmed post-surgical mediastinitis cared for at a cardiology hospital in Mexico City between January 2017 and March 2019. RESULTS: Fifty-eight cases of mediastinitis were included. Median age was 67 years. Most subjects were males who underwent myocardial revascularization. During in-hospital follow-up, all-cause and mediastinitis-related mortality were 27.6% and 20.7%, respectively. Staphylococcus aureus, Staphylococcus epidermidis and Escherichia coli were the most commonly isolated microorganisms. High resistance to methicillin was found in coagulase-negative staphylococci, as well as high expression of extended-spectrum beta-lactamases in Escherichia coli and Klebsiella pneumoniae strains. CONCLUSIONS: High mortality and significant antimicrobial resistance were found in patients with post-cardiac surgery mediastinitis.

INTRODUCCIÓN: La mediastinitis posterior a cirugía cardiovascular deriva en estancia hospitalaria prolongada e incremento de los costos de la atención médica, y se asocia a elevada letalidad hospitalaria. OBJETIVO: Describir las características clínicas de los pacientes con mediastinitis posquirúrgica, incluyendo los microorganismos aislados, perfil de resistencia y supervivencia hospitalaria. MÉTODOS: Estudio transversal de pacientes con mediastinitis posquirúrgica bacteriológicamente confirmada, atendidos en un hospital de cardiología de la Ciudad de México entre enero de 2017 y marzo de 2019. RESULTADOS: Se incluyeron 58 casos de mediastinitis. La mediana de edad fue de 67 años. La mayoría de los sujetos fueron varones sometidos a revascularización miocárdica. Durante el seguimiento hospitalario, la letalidad por todas las causas y la secundaria a la mediastinitis fueron de 27.6 y 20.7 %, respectivamente. Los microorganismos más frecuentemente aislados fueron Staphylococcus aureus, Staphylococcus epidermidis y Escherichia coli. Se encontró alta resistencia a meticilina en los estafilococos coagulasa negativos y alta expresión de betalactamasas de espectro extendido en cepas de Escherichia coli y Klebsiella pneumoniae. CONCLUSIONES: En los pacientes con mediastinitis posquirúrgica analizados se observó alta letalidad e importante resistencia antimicrobiana.

Domestic Dogs as Sentinels for West Nile Virus but not Aedes-borne Flaviviruses, Mexico.

We tested 294 domestic pet dogs in Mexico for neutralizing antibodies for mosquito-borne flaviviruses. We found high (42.6%) exposure to West Nile virus in Reynosa (northern Mexico) and low (1.2%) exposure in Tuxtla Gutierrez (southern Mexico) but very limited exposure to Aedes-borne flaviviruses. Domestic dogs may be useful sentinels for West Nile virus.

Direct X-ray and electron-beam lithography of halogenated zeolitic imidazolate frameworks.

Metal-organic frameworks (MOFs) offer disruptive potential in micro- and optoelectronics because of the unique properties of these microporous materials. Nanoscale patterning is a fundamental step in the implementation of MOFs in miniaturized solid-state devices. Conventional MOF patterning methods suffer from low resolution and poorly defined pattern edges. Here, we demonstrate the resist-free, direct X-ray and electron-beam lithography of MOFs. This process avoids etching damage and contamination and leaves the porosity and crystallinity of the patterned MOFs intact. The resulting high-quality patterns have excellent sub-50-nm resolution, and approach the mesopore regime. The compatibility of X-ray and electron-beam lithography with existing micro- and nanofabrication processes will facilitate the integration of MOFs in miniaturized devices.

The use of readily available laboratory tests for the identification of the emerging yeast Candida auris in Mexico.

Identification of the emerging multidrug-resistant yeast Candida auris is challenging. Here, we describe the role of the Mexico national reference laboratory Instituto de Diagnóstico y Referencia Epidemiológicos Dr. Manuel Martínez Báez (InDRE) and the Mexican national laboratory network in the identification of C. auris. Reference identification of six suspected isolates was done based on phenotypic and molecular laboratory methods, including growth in special media, evaluation of isolate micromorphology, and species-specific PCR and pan-fungal PCR and sequencing. The four C. auris isolates identified were able to grow on modified Sabouraud agar with 10% NaCl incubated at 42 °C. With one exception, isolates of C. auris were spherical to ovoid yeast-like cells and blastoconidia, with no hyphae or pseudohyphae on cornmeal agar. C. auris isolates were resistant to fluconazole. Species-specific and pan-fungal PCR confirmed isolates as C. auris. Sequence analysis revealed the presence of two different C. auris clades in Mexico, clade I (South Asia) and clade IV (South America).