Towards solving the reproducibility crisis in surface-enhanced Raman spectroscopy-based pesticide detection.

Growing concerns about pesticide residues in agriculture are pushing the scientific community to develop innovative and efficient methods for detecting these substances at low concentrations down to the molecular level. In this context, surface-enhanced Raman spectroscopy (SERS) is a powerful analytical method that has so far already undergone some validation for its effectiveness in pesticide detection. However, despite its great potential, SERS faces significant difficulties obtaining reproducible and accurate pesticide spectra, particularly for some of the most widely used pesticides, such as malathion, chlorpyrifos, and imidacloprid. Those inconsistencies can be attributed to several factors, such as interactions between pesticides and SERS substrates and the variety of substrates and solvents used. In addition, differences in the equipment used to obtain SERS spectra and the lack of standards for control experiments further complicate the reproducibility and reliability of SERS data. This review systematically discusses the problems mentioned above, including a comprehensive analysis of the challenges in precisely evaluating SERS spectra for pesticide detection. We not only point out the existing limitations of the method, which can be traced in previous review works, but also offer practical recommendations to improve the quality and comparability of SERS spectra, thereby expanding the potential applications of the method in such an essential field as pesticide detection.

Prognostic Factors Associated with Tumor Recurrence and Overall Survival in Soft Tissue Sarcomas of the Extremities in a Colombian Reference Cancer Center.

Introduction: Soft tissue sarcomas (STS) are low-incidence tumors whose clinical and histopathological factors are associated with adverse oncological outcomes. This study evaluated prognostic factors (PF) associated with tumor recurrence and overall survival (OS) in patients diagnosed with STS of the extremities, treated at the Instituto Nacional de Cancerología (INC), Bogotá, Colombia. Materials and Methods: An analytical observational study of a historical cohort was carried out, including patients diagnosed with STS and managed surgically in the Functional Unit for Breast and Soft Tissue Tumors of the INC from January 2008 to December 2018. Results: A total of 227 patients were included; 74.5% had tumors greater than 5 cm. Most patients (29.1%) were in stage IIIB at diagnosis. Age was associated with higher mortality (HR = 1.01; CI95%: 1-1.02; p = 0.048). Tumor persistence at admission to the INC (HR = 2.34; CI95%: 1.25-4.35; p = 0.007) and histologic grade III (HR = 5.36; CI95%: 2.29-12.56; p = <0.001) showed statistical significance in the multivariate analysis for recurrence of any type, as did the PFs associated with a higher risk of local recurrence (HR = 2.85; CI95%: 1.23-6.57; p = 0.014 and HR = 6.09; CI95%: 2.03-18.2; p = 0.001), respectively. Tumor size (HR = 1.03; CI95%: 1-1.06; p = 0.015) and histologic grade III (HR = 4.53; CI95%: 1.42-14.49; p = 0.011) were associated with a higher risk of distant recurrence. Conclusions: This cohort showed that in addition to histologic grade and tumor size, tumor persistence at the time of admission has an impact on disease recurrence, so STS should be managed by a multidisciplinary team with experience in this pathology in high-volume reference centers.

Smart Graphene Textiles for Biopotential Monitoring: Laser-Tailored Electrochemical Property Enhancement.

While most of the research in graphene-based materials seeks high electroactive surface area and ion intercalation, here, we show an alternative electrochemical behavior that leverages graphene's potential in biosensing. We report a novel approach to fabricate graphene/polymer nanocomposites with near-record conductivity levels of 45 Ω sq-1 and enhanced biocompatibility. This is realized by laser processing of graphene oxide in a sandwich structure with a thin (100 µm) polyethylene terephthalate film on a textile substrate. Such hybrid materials exhibit high conductivity, low polarization, and stability. In addition, the nanocomposites are highly biocompatible, as evidenced by their low cytotoxicity and good skin adhesion. These results demonstrate the potential of graphene/polymer nanocomposites for smart clothing applications.

Synergistic use of deep TMS therapy with IV ketamine infusions for major depressive disorder: a pilot study.

OBJECTIVE: Major Depressive Disorder (MDD) is a pervasive psychiatric condition effecting approximately 21 million adults in the U.S. (8.4%). An estimated 30-60% of patients are resistant to traditional treatment approaches (medications and talk-therapy), alluding to the need for additional options. Two promising treatment modalities include transcranial magnetic stimulation (TMS) and ketamine infusions; both have shown efficacy in standalone studies but have scarcely been investigated synergistically in the same group of participants. METHOD: In the current study, 169 participants with treatment-resistant MDD received 36 treatments of Deep TMS-only (H1 + H7 protocols), while 66 received 36 treatments of Deep TMS (H1 + H7 protocols) and 6 IV infusions of ketamine over the course of 9 weeks. Depressive symptoms were compared pre- and -post treatment in both conditions using the PHQ-9. RESULTS: In both treatment groups, depressive symptoms were significantly reduced from pre-to-post and there were no significant differences in response between the TMS + ketamine condition and the TMS-only condition. The TMS + ketamine condition had an 80.30% response rate (53 out of 66) and 43.42% remission rate (28 out of 66) compared to a 76.92% response (130 out of 169) and 39.64% remission (67 out of 16) in the TMS-only condition. CONCLUSION: These results support the notion that TMS treatments yield high response rates in treatment-resistant cases; however, in this investigation there was no added benefit for including 6 sessions of IV ketamine in conjunction with TMS. Future investigations using randomized-control designs and robust outcome measures are warranted.

Multi-Layer Palladium Diselenide as a Contact Material for Two-Dimensional Tungsten Diselenide Field-Effect Transistors.

Tungsten diselenide (WSe2) has emerged as a promising ambipolar semiconductor material for field-effect transistors (FETs) due to its unique electronic properties, including a sizeable band gap, high carrier mobility, and remarkable on-off ratio. However, engineering the contacts to WSe2 remains an issue, and high contact barriers prevent the utilization of the full performance in electronic applications. Furthermore, it could be possible to tune the contacts to WSe2 for effective electron or hole injection and consequently pin the threshold voltage to either conduction or valence band. This would be the way to achieve complementary metal-oxide-semiconductor devices without doping of the channel material.This study investigates the behaviour of two-dimensional WSe2 field-effect transistors with multi-layer palladium diselenide (PdSe2) as a contact material. We demonstrate that PdSe2 contacts favour hole injection while preserving the ambipolar nature of the channel material. This consequently yields high-performance p-type WSe2 devices with PdSe2 van der Waals contacts. Further, we explore the tunability of the contact interface by selective laser alteration of the WSe2 under the contacts, enabling pinning of the threshold voltage to the valence band of WSe2, yielding pure p-type operation of the devices.

Investigation of the Performance of Various Low-Cost Radon Monitors under Variable Environmental Conditions.

A comparison of low-cost radon monitors was conducted at the Laboratory of Natural Radiation (LNR). The monitors we evaluated were EcoQube, RadonEye, RadonEye Plus2, Spirit, ViewPlus, ViewRadon and WavePlus. An AlphaGUARD monitor calibrated at the Laboratory of Environmental Radioactivity of the University of Cantabria (LaRUC), accredited for testing and calibration according to ISO/IEC 17025, provided the reference value of radon concentration. The temporal stability of the monitors was studied, obtaining a percentage of missing records ranged from 1% to 19% of the data. The main technical characteristics studied were temporal stability, measurement ranges, accuracy, correlation and response time. The main results show that the measurement ranges align with those specified by their manufacturers, with percentage differences with respect to the reference monitor of between 5% and 16%. The diversity found for response time is remarkable, with values ranging from 1 to 15 h, with Pearson correlation factors between 0.63 and 0.90.

In Vitro Propagation of Plants via Organogenesis in Bambusa vulgaris Schrad. ex Wendl Using Temporary Immersion Systems.

The low multiplication and ex vitro survival rates during acclimatization in the culture house limit the in vitro mass propagation of B. vulgaris. Several scientific studies have described the development of different protocols for bamboo; however, not all of them address the effects of these systems on plant morphology, physiology, and biochemistry in vitro. In this chapter, a complete and optimized protocol is described for plants propagated via organogenesis in temporary immersion systems. In addition, the morphophysiological and biochemical characterization of the plants as well as the survival rates of the obtained plants under ex vitro conditions are analyzed. The obtained results will be the basis for the development of a technology for in vitro propagation as an alternative for the production of plants of the species.

Vagus nerve dysfunction in the post-COVID-19 condition: a pilot cross-sectional study.

OBJECTIVES: The post-COVID-19 condition (PCC) is a disabling syndrome affecting at least 5%-10% of subjects who survive COVID-19. SARS-CoV-2 mediated vagus nerve dysfunction could explain some PCC symptoms, such as dysphonia, dysphagia, dyspnea, dizziness, tachycardia, orthostatic hypotension, gastrointestinal disturbances, or neurocognitive complaints. METHODS: We performed a cross-sectional pilot study in subjects with PCC with symptoms suggesting vagus nerve dysfunction (n = 30) and compared them with subjects fully recovered from acute COVID-19 (n = 14) and with individuals never infected (n = 16). We evaluated the structure and function of the vagus nerve and respiratory muscles. RESULTS: Participants were mostly women (24 of 30, 80%), and the median age was 44 years (interquartile range [IQR] 35-51 years). Their most prevalent symptoms were cognitive dysfunction 25 of 30 (83%), dyspnea 24 of 30 (80%), and tachycardia 24 of 30 (80%). Compared with COVID-19-recovered and uninfected controls, respectively, subjects with PCC were more likely to show thickening and hyperechogenic vagus nerve in neck ultrasounds (cross-sectional area [CSA] [mean ± standard deviation]: 2.4 ± 0.97mm2 vs. 2 ± 0.52mm2 vs. 1.9 ± 0.73 mm2; p 0.08), reduced esophageal-gastric-intestinal peristalsis (34% vs. 0% vs. 21%; p 0.02), gastroesophageal reflux (34% vs. 19% vs. 7%; p 0.13), and hiatal hernia (25% vs. 0% vs. 7%; p 0.05). Subjects with PCC showed flattening hemidiaphragms (47% vs. 6% vs. 14%; p 0.007), and reductions in maximum inspiratory pressure (62% vs. 6% vs. 17%; p ≤ 0.001), indicating respiratory muscle weakness. The latter findings suggest additional involvement of the phrenic nerve. DISCUSSION: Vagus and phrenic nerve dysfunction contribute to the complex and multifactorial pathophysiology of PCC.

A robust class decomposition-based approach for detecting Alzheimer's progression.

Computer-aided diagnosis of Alzheimer's disease (AD) is a rapidly growing field with the possibility to be utilized in practice. Deep learning has received much attention in detecting AD from structural magnetic resonance imaging (sMRI). However, training a convolutional neural network from scratch is problematic because it requires a lot of annotated data and additional computational time. Transfer learning can offer a promising and practical solution by transferring information learned from other image recognition tasks to medical image classification. Another issue is the dataset distribution's irregularities. A common classification issue in datasets is a class imbalance, where the distribution of samples among the classes is biased. For example, a dataset may contain more instances of some classes than others. Class imbalance is challenging because most machine learning algorithms assume that each class should have an equal number of samples. Models consequently perform poorly in prediction. Class decomposition can address this problem by making learning a dataset's class boundaries easier. Motivated by these approaches, we propose a class decomposition transfer learning (CDTL) approach that employs VGG19, AlexNet, and an entropy-based technique to detect AD from sMRI. This study aims to assess the robustness of the CDTL approach in detecting the cognitive decline of AD using data from various ADNI cohorts to determine whether comparable classification accuracy for the two or more cohorts would be obtained. Furthermore, the proposed model achieved state-of-the-art performance in predicting mild cognitive impairment (MCI)-to-AD conversion with an accuracy of 91.45%.

Explainable hierarchical clustering for patient subtyping and risk prediction.

We present a pipeline in which machine learning techniques are used to automatically identify and evaluate subtypes of hospital patients admitted between 2017 and 2021 in a large UK teaching hospital. Patient clusters are determined using routinely collected hospital data, such as those used in the UK's National Early Warning Score 2 (NEWS2). An iterative, hierarchical clustering process was used to identify the minimum set of relevant features for cluster separation. With the use of state-of-the-art explainability techniques, the identified subtypes are interpreted and assigned clinical meaning, illustrating their robustness. In parallel, clinicians assessed intracluster similarities and intercluster differences of the identified patient subtypes within the context of their clinical knowledge. For each cluster, outcome prediction models were trained and their forecasting ability was illustrated against the NEWS2 of the unclustered patient cohort. These preliminary results suggest that subtype models can outperform the established NEWS2 method, providing improved prediction of patient deterioration. By considering both the computational outputs and clinician-based explanations in patient subtyping, we aim to highlight the mutual benefit of combining machine learning techniques with clinical expertise.

Universal Approach to Integrating Reduced Graphene Oxide into Polymer Electronics.

Flexible electronics have sparked significant interest in the development of electrically conductive polymer-based composite materials. While efforts are being made to fabricate these composites through laser integration techniques, a versatile methodology applicable to a broad range of thermoplastic polymers remains elusive. Moreover, the underlying mechanisms driving the formation of such composites are not thoroughly understood. Addressing this knowledge gap, our research focuses on the core processes determining the integration of reduced graphene oxide (rGO) with polymers to engineer coatings that are not only flexible and robust but also exhibit electrical conductivity. Notably, we have identified a particular range of laser power densities (between 0.8 and 1.83 kW/cm2), which enables obtaining graphene polymer composite coatings for a large set of thermoplastic polymers. These laser parameters are primarily defined by the thermal properties of the polymers as confirmed by thermal analysis as well as numerical simulations. Scanning electron microscopy with elemental analysis and X-ray photoelectron spectroscopy showed that conductivity can be achieved by two mechanisms-rGO integration and polymer carbonization. Additionally, high-speed videos allowed us to capture the graphene oxide (GO) modification and melt pool formation during laser processing. The cross-sectional analysis of the laser-processed samples showed that the convective flows are present in the polymer substrate explaining the observed behavior. Moreover, the practical application of our research is exemplified through the successful assembly of a conductive wristband for wearable devices. Our study not only fills a critical knowledge gap but also offers a tangible illustration of the potential impact of laser-induced rGO-polymer integration in materials science and engineering applications.

Noncovalent Dualism in Perylene-Diimide-Based Keggin Anion Complexes: Theoretical and Experimental studies.

We report the synthesis and comprehensive characterization of organic-inorganic hybrid salts formed by bis-cationic N,N'-bis(2-(trimethylammonium)ethylene)perylene-3,4,9,10-tetracarboxylic acid bisimide (PTCD2+) and Keggin-type [XW12O40]n- (X = Si, n = 4; X = P, n = 3) polyoxometalates. (PTCD)3[PW12O40]2·3DMSO·2H2O (2) and (PTCD)2[SiW12O40]·DMSO·2H2O (3) were structurally characterized by single crystal X-ray diffraction. The cations in both structures exhibited infinite chainlike arrangements through π-π interactions, contrasting with the previously reported cation-anion stacking observed in naphthalene diimide derivatives. A detailed theoretical study employing topological analysis of the electron density distribution within the quantum theory of atoms in molecules approach provided further insights into this structural dualism. Atomic force microscopy analyses revealed the formation of self-assembled supramolecular structures on graphite from molecular monolayers (3 nm of thick) to submicrometer aggregates for 2. Hyperspectral Raman spectroscopy imaging revealed that such heterostructures are likely formed by an enhanced π-π interactions. Both complexes demonstrated interesting electrochemical behavior, photoluminescence and X-ray-induced luminescence. Electron spin resonance analysis confirmed charge separation in both compounds, with enhanced efficiency observed in compound 2. Our findings of these perylene-based organic-inorganic hybrid salts offer the potential for their application in optoelectronic devices and functional materials.

Allergic reactions associated with medically relevant arthropods.

OBJECTIVE: Vector-borne diseases are a growing burden worldwide. In particular, the risks of allergic reactions to bites are associated with growing arthropod populations in contact with the public. The diversity of allergic reactions associated with host and arthropod factors difficult disease diagnosis, prognosis and prevention. Therefore, arthropod-associated allergies are underdiagnosed and require better surveillance of arthropod populations and disease diagnosis and management. METHODS: To face these challenges, in this study, we describe five cases to illustrate arthropod-associated allergies with different symptomatology, including alpha-gal syndrome (AGS) associated with anti-alpha-gal IgE antibody titres. Information on symptoms in response to arthropod bites was collected from patients and medical doctors. RESULTS: The five cases included patients bitten by a robber fly and different tick species. Cases were in Spain or U.S.A. Two cases were diagnosed with AGS and one case was diagnosed with anaphylaxis in response to tick bite with high anti-alpha-gal IgE levels. The symptoms in response to arthropod bites vary between different cases. CONCLUSION: Allergic reactions and symptoms in response to arthropod bites vary in association with host and arthropod factors. Herein we propose recommendations to control allergic symptoms, associated disease risk factors and the way forward to advance in the prevention and control of arthropod-associated allergies.

Single Nucleotide Variants in the TLR1, TLR2 and TLR6 Genes: A Case-Control Study in a Colombian Population.

BACKGROUND: Single nucleotide variants in toll-like receptor genes play a crucial role in leprosy susceptibility or resistance. METHODS: With an epidemiology case-control study, associations between SNVs rs5743618 in TLR1, rs5743708 in TLR2, and rs5743810 in TLR6 and overall susceptibility for leprosy were estimated in 114 cases and 456 controls. Following that, stratified analysis was performed. DNA was extracted from peripheral blood. Genotyping was performed using predesigned TaqMan probes. RESULTS: The A/G genotype of rs5743810 behaved as a protective factor for the development of leprosy in the codominant (OR= 0.37; 95% CI = 016-0.86, p = 0.049) and over-dominant (OR = 0.38; 95% CI = 0.16-0.88, p = 0.019) inheritance models. The A/G and A/A genotypes behaved as a protective factor (OR = 0.39; 95% CI = 0.17-0.87, p = 0.016) in the dominant model. The SNVs rs5743618 and rs5743708 showed no association with any of the models. The CGG haplotype (rs5743618-rs5743708-rs5743810) behaved as a susceptibility factor for developing leprosy (OR = 1.86; 95% CI = 1.11-3.10, p = 0.019). The latter haplotype behaved as a susceptibility factor for leprosy development in women (OR = 2.39; 95% CI = 1.21-4.82, p = 0.013). CONCLUSIONS: The identified variants in the genes encoding TLRs, specifically rs5743810 in TLR6 and CGG (rs5743618-rs5743708-rs5743810) haplotypes, may somehow explain leprosy susceptibility in the studied population in a leprosy endemic region in Colombia.

Sex differences in a murine model of asthma are time and tissue compartment dependent.

CONCLUSION: Sexual dimorphism in lung inflammation is both time and tissue compartment dependent. Spatiotemporal variability in sex differences in a murine model of asthma must be accounted for when planning experiments to model the sex bias in allergic inflammation.

Design and Evaluation of an Intensive Care Unit Dashboard Built in Response to the COVID-19 Pandemic: Semistructured Interview Study.

BACKGROUND: Dashboards and interactive displays are becoming increasingly prevalent in most health care settings and have the potential to streamline access to information, consolidate disparate data sources and deliver new insights. Our research focuses on intensive care units (ICUs) which are heavily instrumented, critical care environments that generate vast amounts of data and frequently require individualized support for each patient. Consequently, clinicians experience a high cognitive load, which can translate to suboptimal performance. The global COVID-19 pandemic exacerbated this problem by generating a large number of additional hospitalizations, which necessitated a new tool that would help manage ICUs' census. In a previous study, we interviewed clinicians at the University Hospitals Bristol and Weston National Health Service Foundation Trust to capture the requirements for bespoke dashboards that would alleviate this problem. OBJECTIVE: This study aims to design, implement, and evaluate an ICU dashboard to allow for monitoring of the high volume of patients in need of critical care, particularly tailored to high-demand situations, such as those seen during the COVID-19 pandemic. METHODS: Building upon the previously gathered requirements, we developed a dashboard, integrated it within the ICU of a National Health Service trust, and allowed all staff to access our tool. For evaluation purposes, participants were recruited and interviewed following a 25-day period during which they were able to use the dashboard clinically. The semistructured interviews followed a topic guide aimed at capturing the usability of the dashboard, supplemented with additional questions asked post hoc to probe themes established during the interview. Interview transcripts were analyzed using a thematic analysis framework that combined inductive and deductive approaches and integrated the Technology Acceptance Model. RESULTS: A total of 10 participants with 4 different roles in the ICU (6 consultants, 2 junior doctors, 1 nurse, and 1 advanced clinical practitioner) participated in the interviews. Our analysis generated 4 key topics that prevailed across the data: our dashboard met the usability requirements of the participants and was found useful and intuitive; participants perceived that it impacted their delivery of patient care by improving the access to the information and better equipping them to do their job; the tool was used in a variety of ways and for different reasons and tasks; and there were barriers to integration of our dashboard into practice, including familiarity with existing systems, which stifled the adoption of our tool. CONCLUSIONS: Our findings show that the perceived utility of the dashboard had a positive impact on the clinicians' workflows in the ICU. Improving access to information translated into more efficient patient care and transformed some of the existing processes. The introduction of our tool was met with positive reception, but its integration during the COVID-19 pandemic limited its adoption into practice.

Beyond Tissue replacement: The Emerging role of smart implants in healthcare.

Smart implants are increasingly used to treat various diseases, track patient status, and restore tissue and organ function. These devices support internal organs, actively stimulate nerves, and monitor essential functions. With continuous monitoring or stimulation, patient observation quality and subsequent treatment can be improved. Additionally, using biodegradable and entirely excreted implant materials eliminates the need for surgical removal, providing a patient-friendly solution. In this review, we classify smart implants and discuss the latest prototypes, materials, and technologies employed in their creation. Our focus lies in exploring medical devices beyond replacing an organ or tissue and incorporating new functionality through sensors and electronic circuits. We also examine the advantages, opportunities, and challenges of creating implantable devices that preserve all critical functions. By presenting an in-depth overview of the current state-of-the-art smart implants, we shed light on persistent issues and limitations while discussing potential avenues for future advancements in materials used for these devices.

Identificación de Mycobacteria no pigmenteda de crecimiento rápido por el Método Molecular de Micobacterium de Genotipo CM / Identification of Fast-Growing Non-Pigmented Mycobacteria by the Genotype® Mycobacterium CM Molecular Method

Introducción: la micobacteria no terberculosa (NTM) forma un grupo heterogéneo de microorganismos que pueden causar infección en humanos. Las micobacterias no pigmentadas de rápido crecimiento (MNPCR) son de interés clínico debido al creciente número de pacientes infectados por ellos y a la dificultad del tratamiento. Dentro de este grupo, Mycobacterium fortuitum, Mycobacterium abscessus y Mycobacterium chelonae son reconocidos como patógenos potenciales; estas especies se han aislado de infecciones pulmonares y extrapulmonares. Objetivo: el objetivo de este trabajo es encontrar la frecuencia de aislamiento de especies micobacterianas de rápido crecimiento, específicamente el complejo Mycobacterium fortuitum, de muestras clínicas utilizando la técnica molecular de diagnóstico GenoType Mycobacterium CM. Material y Método: se analizaron 249 aislados de micobacterias no tuberculosas obtenidas de muestras pulmonares y extrapulmonares de pacientes sintomáticos en el período enero 2018-diciembre de 2022. La técnica molecular GenoType Mycobacterium CM se utilizó para identificar la especie. Resultados: Se obtuvieron 77 (3,9%) aislados de especies no pigmentadas de rápido crecimiento, estas se identificaron en orden decreciente: Mycobacterium fortuitum 65 (84,41%), Mycobacterium abcessus 9 (11,68%) y Mycobacterium chelonae 3 (4%). Conclusiones: los resultados reafirman que el complejo Mycobacterium fortuitum es responsable de la mayoría de las infecciones causadas por la micobacteria en rápido crecimiento en humanos. La técnica diagnóstica GenoType Mycobacterium CM es una herramienta útil para la rápida identificación de micobacterias; proporciona resultados precisos en menos tiempo, acortando significativamente el tiempo diagnóstico, permite la aplicación temprana de tratamiento específico, evitando así la propagación de la infección.

Introduction: non-tuberculous mycobacteria (NTM) form a heterogeneous group of mi-croorganisms that can cause infection in humans. Fast-growing non-pigmented my-cobacteria (MNPCR) are of clinical interest due to the increasing number of patients infected by them and the difficulty of treatment. Within this group, Mycobacterium fortuitum, Mycobacterium abscessus and Mycobacterium chelonae are recognized as potential pathogens; these species have been isolated from both pulmonary and ex-trapulmonary infections. Objective: the objective of this work is to find the frequency of isolation of fast-growing non-pigmented mycobacterial species, specifically the Myco-bacterium fortuitum complex, from clinical samples using the GenoType® Mycobacteri-um CM diagnostic molecular technique. Material and Method: 249 isolates of non-tu-berculous mycobacteria obtained from pulmonary and extrapulmonary samples from symptomatic patients in the period January 2018-December 2022 were analyzed. The G e n oTy p e® Mycobacterium CM molecular technique was used to identify the species. Results: 77 (30.9%) isolates of fast-growing non-pigmented species were obtained, these were identified in decreasing order: Mycobacterium fortuitum 65 (84.41%), Myco-bacterium abcessus 9 (11.68%) and Mycobacterium chelonae 3 (4%). Conclusions: the results reaffirm that the Mycobacterium fortuitum complex is responsible for most in-fections caused by fast-growing mycobacteria in humans. The GenoType® Mycobacte-riumCM diagnostic technique is a useful tool for the rapid identification of mycobacte-ria; it provides accurate results in less time, significantly shortening the diagnostic time, it allows the early application of specific treatment, thus avoiding the spread of infec-tion.

SARS-CoV-2 accessory proteins involvement in inflammatory and profibrotic processes through IL11 signaling.

SARS-CoV-2, the cause of the COVID-19 pandemic, possesses eleven accessory proteins encoded in its genome. Their roles during infection are still not completely understood. In this study, transcriptomics analysis revealed that both WNT5A and IL11 were significantly up-regulated in A549 cells expressing individual accessory proteins ORF6, ORF8, ORF9b or ORF9c from SARS-CoV-2 (Wuhan-Hu-1 isolate). IL11 is a member of the IL6 family of cytokines. IL11 signaling-related genes were also differentially expressed. Bioinformatics analysis disclosed that both WNT5A and IL11 were involved in pulmonary fibrosis idiopathic disease and functional assays confirmed their association with profibrotic cell responses. Subsequently, data comparison with lung cell lines infected with SARS-CoV-2 or lung biopsies from patients with COVID-19, evidenced altered profibrotic gene expression that matched those obtained in this study. Our results show ORF6, ORF8, ORF9b and ORF9c involvement in inflammatory and profibrotic responses. Thus, these accessory proteins could be targeted by new therapies against COVID-19 disease.