Prevalence and predictors of self-medication to prevent or treat COVID-19 among undergraduate students in Southern Brazil.

Self-medication (SM) is the practice of consuming medicines without a prescription. Despite being a potentially dangerous action, SM is practiced globally and has been highlighted during the COVID-19 pandemic. The aim of this study was to evaluate SM for the prevention or treatment of COVID-19 and the factors associated with this practice among undergraduate students in Southern Brazil. A cross-sectional study was conducted between July and November 2020 using an electronic questionnaire to collect information about the practice of SM and the associated sociodemographic characteristics, health perception, and lifestyle. We collected 1,553 responses and identified a prevalence of 14.9% for SM. The risk factors for SM were earning between BRL 2,101 and BRL 5,250, studying at a public university, and studying a distance undergraduate course. The protective factors were age above 30 years, female sex, working or participating in internships, occasionally recommending their own medications to other people, and worsening health during the pandemic. The main drugs or products used were ivermectin, vitamins C and D, tea, azithromycin, zinc, and propolis. Our data could help in the development of health education measures to reduce SM among undergraduate students and guide the population regarding the risks of this practice.

Telocytes: current methods of research, challenges and future perspectives.

Telocytes (TCs) are CD34-positive interstitial cells that have long cytoplasmic projections, called telopodes; they have been identified in several organs and in various species. These cells establish a complex communication network between different stromal and epithelial cell types, and there is growing evidence that they play a key role in physiology and pathology. In many tissues, TC network impairment has been implicated in the onset and progression of pathological conditions, which makes the study of TCs of great interest for the development of novel therapies. In this review, we summarise the main methods involved in the characterisation of these cells as well as their inherent difficulties and then discuss the functional assays that are used to uncover the role of TCs in normal and pathological conditions, from the most traditional to the most recent. Furthermore, we provide future perspectives in the study of TCs, especially regarding the establishment of more precise markers, commercial lineages and means for drug delivery and genetic editing that directly target TCs.

The potential role of artificial intelligence in the clinical management of Hansen's disease (leprosy).

Missed and delayed diagnoses of Hansen's disease (HD) are making the battle against it even more complex, increasing its transmission and significantly impacting those affected and their families. This strains public health systems and raises the risk of lifelong impairments and disabilities. Worryingly, the three countries most affected by HD witnessed a growth in new cases in 2022, jeopardizing the World Health Organization's targets to interrupt transmission. Artificial intelligence (AI) can help address these challenges by offering the potential for rapid case detection, customized treatment, and solutions for accessibility challenges-especially in regions with a shortage of trained healthcare professionals. This perspective article explores how AI can significantly impact the clinical management of HD, focusing on therapeutic strategies. AI can help classify cases, ensure multidrug therapy compliance, monitor geographical treatment coverage, and detect adverse drug reactions and antimicrobial resistance. In addition, AI can assist in the early detection of nerve damage, which aids in disability prevention and planning rehabilitation. Incorporating AI into mental health counseling is also a promising contribution to combating the stigma associated with HD. By revolutionizing therapeutic approaches, AI offers a holistic solution to reduce the burden of HD and improve patient outcomes.

Oil-in-water emulsion loaded with optimized antioxidant blend improved the shelf-life of trout (Oncorhynchus mykiss) fillets: a study with simplex-centroid design.

This study aimed to obtain optimized mixture with three essential oils (EOs) for maximum antioxidant activity through the augmented simplex-centroid mixture design and evaluate the effect of this optimized blend on total aerobic psychrotrophic count (TAPC), lipid and protein oxidation, instrumental color parameters and texture profile in rainbow trout fillets at refrigerated storage for nine days. Considering the DPPH and FRAP assays, the ideal EO blend was 66% lemongrass and 34% oregano. During refrigerated storage, this blend at 2000 ppm was equally effective as BHT (100 ppm) (p > 0.05), mitigating the discoloration (a* and b*), lipid, and protein oxidation in 38.83%, 12.95%, 76.13%, and 35.13%, respectively, besides shows greater effectiveness for preserving texture changes (p < 0.05) and extending the shelf life in 13 h. The lemongrass + oregano EO blend reveals a promising natural alternative to enhance the quality of rainbow trout fillets under refrigerated storage. Furthermore, the multiresponse optimization showed to be a strong ally in enabling the use of these EOs by food industries.

From imaging to precision: low cost and accurate determination of stereotactic coordinates for brain surgery Sapajus apella using MRI.

The capuchin monkey (Sapajus apella), a New World monkey species, exhibits prominent characteristics that make it an ideal model for neuroscience research. These characteristics include its phylogenetic traits, telencephalization coefficient, anatomical structures and pathways, genetic profile, immune responses, cognitive abilities, and complex behavioral repertoires. Traditionally, methodologies for stereotactic neurosurgery in research models have relied on the use of brain atlases. However, this approach can lead to errors due to the considerable variation in brain size and shape among individual monkeys. To address this issue, we developed a protocol for deriving individual coordinates for each monkey using a straightforward and relatively inexpensive method involving MRI imaging. Our protocol utilizes a specially designed, 3D-printed stereotactic head-holder that is safe to use with an MR magnet, non-invasive placement of fiducial markers, and post-processing with open-source software. This approach enhances MRI data visualization, improves anatomical targeting, and refines the design of neurosurgical experiments. Our technique could also prove beneficial in other areas of neuroscience research that require accurate calculation of stereotaxic coordinates. Furthermore, it could be useful for other nonhuman primate species for which brain atlases are typically unavailable.

Research on the volatility, phase transitions and thermodynamic stability of five organochlorine compounds.

The present investigation describes the experimental evaluation of relevant physicochemical properties of five organochlorine compounds (OCs), including some that are related to their environmental mobility. The vapor pressures of (2,4'-Dichlorodiphenyl)dichloroethane (2,4'-DDD, CASN:53-19-0), 1,1-Dichloro-2,2-bis(4-chlorophenyl)ethane (4,4'-DDD, CASN:72-54-8) and 2,2-Bis(4-chlorophenyl)acetic acid (4,4'-DDA, CASN:83-05-6), as well as of the bactericide Nitrapyrin (CASN:1929-82-4) and of the rodenticide Crimidine (CASN:535-89-7) were determined at different temperatures. The Knudsen mass-loss effusion technique was employed to determine the sublimation vapor pressures of the referred compounds, apart from Crimidine. For the latter compound, a static method using a capacitance diaphragm manometer enabled the measurement of vapor pressures of both condensed (crystalline and liquid) phases. This technique was also used to measure the vapor pressures of the crystalline phase of Nitrapyrin over a larger temperature range, as well as its vaporization vapor pressures. The results of the standard molar enthalpies, entropies, and Gibbs energies of sublimation for all five compounds and of vaporization for Crimidine and Nitrapyrin, at reference temperatures, were derived. For these two compounds the phase diagram representations of the (p,T) results, in the vicinity of the triple point, were obtained. DSC analysis enabled the determination of the crystalline heat capacities of the five OCs studied and also of their temperatures and enthalpies of fusion. Gas-phase thermodynamic properties were estimated using quantum chemical calculations. The thermodynamic stability of the compounds studied was evaluated and compared in the crystalline and gaseous phases, at 298.15 K, in consideration with estimated results of the standard Gibbs energies of formation. Combined with other physical and chemical properties, the results derived from this study can be used to predict the mobility, and environmental fate of these pollutants.

Preoperative lateral lymph node features and impact on local recurrence after neoadjuvant chemoradiotherapy and total mesorectal excision for locally advanced rectal cancer: results from a multicentre international cohort study.

AIM: Locally advanced rectal cancer (LARC) is commonly treated with neoadjuvant chemoradiotherapy (nCRT) and total mesorectal excision (TME) to reduce local recurrence (LR) and improve survival. However, LR, particularly associated with lateral lymph node (LLN) involvement, remains a concern. The aim of this study was to investigate preoperative factors associated with LLN involvement and their impact on LR rates in LARC patients undergoing nCRT and curative surgery. METHOD: This multicentre retrospective study, including four academic high-volume institutions, involved 301 consecutive adult LARC patients treated with nCRT and curative surgery between January 2014 and December 2019 who did not undergo lateral lymph node dissection (LLND). Baseline and restaging pelvic MRIs were evaluated for suspicious LLNs based on institutional criteria. Patients were divided into two groups: cLLN+ (positive nodes) and cLLN- (no suspicious nodes). Primary outcome measures were LR and lateral local recurrence (LLR) rates at 3 years. RESULTS: Among the cohort, 15.9% had suspicious LLNs on baseline MRI, and 9.3% had abnormal LLNs on restaging MRI. At 3 years, LR and LLR rates were 4.0% and 1.0%, respectively. Ten out of 12 (83.3%) patients with LR showed no suspicious LLNs at the baseline MRI. Abnormal LLNs on MRI were not independent risk factors for LR, distant recurrence or disease-free survival. CONCLUSION: Abnormal LLNs on baseline and restaging MRI assessment did not impact LR and LLR rates in this cohort of patients with LARC submitted to nCRT and curative TME surgery.

Simultaneous estimation of the intermediate correlation matrix for arbitrary marginal densities.

A popular approach to the simulation of multivariate, non-normal data in the social sciences is to define a multivariate normal distribution first, and then alter its lower-dimensional marginals to achieve the shape of the distribution intended by the researchers. A consequence of this process is that the correlation structure is altered, so further methods are needed to specify an intermediate correlation matrix in the multivariate normal distribution step. Most of the techniques available in the literature estimate this intermediate correlation matrix bivariately (i.e., correlation by correlation), risking the possibility of generating a non-positive definite matrix. The present article addresses this issue by offering an algorithm that estimates all elements of the intermediate correlation matrix simultaneously, through stochastic approximation. A small simulation study demonstrates the feasibility of the present method to induce the correlation structure both in simulated and empirical data.

Outcomes after treatment of nonsevere gram-negative clinical mastitis with ceftiofur hydrochloride for 2 or 5 days compared with negative control.

A study was conducted at 3 commercial dairies in California to compare outcomes of treating nonsevere (mild and moderate) gram-negative (GN) clinical mastitis (CM) with intramammary (IMM) ceftiofur HCl (125 mg of ceftiofur HCl per tube) in either 2-d (SP2) or 5-d (SP5) treatment programs compared with nontreatment (CON). In addition, we contrasted results from cases classified as mild and moderate. Four hundred fifteen cases were included in the final dataset, including 135 CON, 133 SP2, and 147 SP5. Milk from quarters with CM was sampled for on-farm culture (OFC) to differentiate gram-positive (GP) and GN bacteria, with results known within 24 h. Those with GN infections were randomly assigned to experimental groups, while those with GP, mixed infections, and contaminated samples did not continue in the study and received standard farm therapy. For cows with GN infections, a sample was submitted for MALDI-TOF assay. Only nonsevere cases were enrolled, and all quarters yielded monocultures of GN species. Clinical scores were obtained 0, 1, 2, 3, 4, 5, 14, 21, and 28 ± 3 d relative to enrollment. Milk samples were collected from quarters 14, 21, and 28 ± 3 d after enrollment, and submitted for routine culture and, when appropriate, submitted to MALDI-TOF evaluation. For many response criteria, there were significant interactions between treatments and CM severity scores at the time of enrollment, with effectiveness of ceftiofur HCl treatment being more beneficial compared with CON as mastitis clinical severity increased. While most treatment responses were significant for animals with mild or moderate GN mastitis, the largest responses were noted among cows with moderate CM cases.

A multi-descriptor analysis of substituent effects on the structure and aromaticity of benzene derivatives: π-Conjugation versus charge effects.

This work provides a detailed multi-component analysis of aromaticity in monosubstituted (X = CH3, C H 2 - , C H 2 + , NH2, NH-, NH+, OH, O-, and O+) and para-homodisubstituted (X = CH3, CH2, NH2, NH, OH, and O) benzene derivatives. We investigate the effects of substituents using single-reference (B3LYP/DFT) and multireference (CASSCF/MRCI) methods, focusing on structural (HOMA), vibrational (AI(vib)), topological (ELFπ), electronic (MCI), magnetic (NICS), and stability (S0-T1 splitting) properties. The findings reveal that appropriate π-electron-donating and π-electron-accepting substituents with suitable size and symmetry can interact with the π-system of the ring, significantly influencing π-electron delocalization. While the charge factor has a minimal impact on π-electron delocalization, the presence of a pz orbital capable of interacting with the π-electron delocalization is the primary factor leading to a deviation from the typical aromaticity characteristics observed in benzene.

Wood-based superblack.

Light is a powerful and sustainable resource, but it can be detrimental to the performance and longevity of optical devices. Materials with near-zero light reflectance, i.e. superblack materials, are sought to improve the performance of several light-centered technologies. Here we report a simple top-down strategy, guided by computational methods, to develop robust superblack materials following metal-free wood delignification and carbonization (1500 °C). Subwavelength severed cells evolve under shrinkage stresses, yielding vertically aligned carbon microfiber arrays with a thickness of ~100 µm and light reflectance as low as 0.36% and independent of the incidence angle. The formation of such structures is rationalized based on delignification method, lignin content, carbonization temperature and wood density. Moreover, our measurements indicate a laser beam reflectivity lower than commercial light stoppers in current use. Overall, the wood-based superblack material is introduced as a mechanically robust surrogate for microfabricated carbon nanotube arrays.

Solar-pumped dual-rod Ce:Nd:YAG laser with 58 W continuous-wave output power and 5.1° tracking error compensation width.

The pursuit of high-power solar laser systems with high efficiency and capacity for large tracking error compensation is determinant for the applicability of this renewable technology. A side-pumped dual-rod Ce:Nd:YAG solar laser was developed and tested at the focus of a 2 m diameter parabolic concentrator. Maximum continuous-wave total solar laser power of 58 W was measured. To the best of our knowledge, this is the highest laser power from a Ce:NdYAG solar laser. Moreover, wide tracking error compensation width of 5.1° in the azimuthal direction was reached, being 4.25 times higher than the previous measurement without solar tracking assistance.

Discovery of 5-Azaquinoxaline Derivatives as Potent and Orally Bioavailable Allosteric SHP2 Inhibitors.

SHP2 has emerged as an important target for oncology small-molecule drug discovery. As a nonreceptor tyrosine phosphatase within the MAPK pathway, it has been shown to control cell growth, differentiation, and oncogenic transformation. We used structure-based design to find a novel class of potent and orally bioavailable SHP2 inhibitors. Our efforts led to the discovery of the 5-azaquinoxaline as a new core for developing this class of compounds. Optimization of the potency and properties of this scaffold generated compound 30, that exhibited potent in vitro SHP2 inhibition and showed excellent in vivo efficacy and pharmacokinetic profile.

Establishment and Comprehensive Molecular Characterization of an Immortalized Glioblastoma Cell Line from a Brazilian Patient.

Glioblastoma (GBM) is the most common and aggressive primary brain tumor in adults, with few effective treatment strategies. The research on the development of new treatments is often constrained by the limitations of preclinical models, which fail to accurately replicate the disease's essential characteristics. Herein, we describe the obtention, molecular, and functional characterization of the GBM33 cell line. This cell line belongs to the GBM class according to the World Health Organization 2021 Classification of Central Nervous System Tumors, identified by methylation profiling. GBM33 expresses the astrocytic marker GFAP, as well as markers of neuronal origin commonly expressed in GBM cells, such as ßIII-tubulin and neurofilament. Functional assays demonstrated an increased growth rate when compared to the U87 commercial cell line and a similar sensitivity to temozolamide. GBM33 cells retained response to serum starvation, with reduced growth and diminished activation of the Akt signaling pathway. Unlike LN-18 and LN-229 commercial cell lines, GBM33 is able to produce primary cilia upon serum starvation. In summary, the successful establishment and comprehensive characterization of this GBM cell line provide researchers with invaluable tools for studying GBM biology, identifying novel therapeutic targets, and evaluating the efficacy of potential treatments.

Aortoenteric Fistula: A Differential Diagnosis of Anemia.

Aortoenteric fistulas (AEFs) are a rare and deadly cause of gastrointestinal bleeding that can be easily overlooked, leading to massive bleeding. Secondary AEFs are more common than primary AEFs. An example of a secondary cause of anemia is postoperative hemorrhage due to a surgically placed aortic graft or after endovascular aneurysm repair. This report aims to increase the awareness of AEF as a differential diagnosis when anemia is detected. The clinical report presents a case of anemia in a 79-year-old man due to a secondary AEF, which occurred in a patient who had undergone abdominal aortic aneurysm surgery 10 years before. Surgical repair is considered the gold standard for AEF treatment; however, in this case, the patient was managed with medical therapy and discharged after two months.

Predictors of changes in running and smoking identity among individuals in the Run to Quit smoking cessation program.

OBJECTIVES: Multiple health behaviour change is a viable strategy to promote health outcomes. An example is the use of running behaviour to support smoking cessation in the group-mediated Run to Quit program. On the basis that changes in running and smoking identity were related to changes in running and smoking behaviour among individuals in the Run to Quit program, the purpose of this study was to extend these findings by examining key predictors of change in both running and smoking identity. METHODS: We analyzed data collected from 450 adult individuals (70.67% female, and 92.44% white) during the program evaluation of Run to Quit from 2016 to 2018. Participants completed assessments at week 1 (baseline), week 3 (mid-program), and week 10 (follow-up) of the program. Relevant predictor variables for change in identity were identified by drawing from theory (identity theory, identity control theory, physical activity self-definition model, social identity theory) and past research regarding exercise and smoking identity. Potential predictors of changes in running and smoking identity included changes in behaviour, self-efficacy, perceptions of the social environment (task and social cohesion, descriptive norms), as well as smoking identity and running identity, respectively. Two regression models, using residualized change scores (for each variable) and relative Pratt indices, were constructed for both running and smoking identity. RESULTS: Changes in running self-efficacy, running frequency, and individual attractions to the group exercise tasks were significant and meaningful predictors of change in running identity, whereas changes in objectively measured smoking behaviour and running identity were significant and meaningful predictors of change in smoking identity. CONCLUSION: Consistent with identity theories and past research, ensuring individuals develop a sense of efficacy and enjoy group exercise tasks both represent viable strategies to enhance exercise identity. Including an exercise component within smoking cessation programs may help individuals replace their existing smoking identity with a healthier exercise identity.

New frontiers of soil fungal microbiome and its application for biotechnology in agriculture.

The fungi-based technology provided encouraging scenarios in the transition from a conventionally based economic system to the potential security of sources closely associated with the agricultural sphere such as the agriculture. In recent years, the intensification of fungi-based processes has generated significant gains, additionally to the production of materials with significant benefits and strong environmental importance. Furthermore, the growing concern for human health, especially in the agriculture scenario, has fostered the investigation of organisms with high biological and beneficial potential for use in agricultural systems. Accordingly, this study offered a comprehensive review of the diversity of the soil fungal microbiome and its main applications in a biotechnological approach aimed at agriculture and food chain-related areas. Moreover, the spectrum of opportunities and the extensive optimization platform for obtaining fungi compounds and metabolites are discussed. Finally, future perspectives regarding the insurgency of innovations and challenges on the broad rise of visionary solutions applied to the biotechnology context are provided.

Using residual regressions to quantify and map signal leakage in genomic prediction.

BACKGROUND: Most genomic prediction applications in animal breeding use genotypes with tens of thousands of single nucleotide polymorphisms (SNPs). However, modern sequencing technologies and imputation algorithms can generate ultra-high-density genotypes (including millions of SNPs) at an affordable cost. Empirical studies have not produced clear evidence that using ultra-high-density genotypes can significantly improve prediction accuracy. However, (whole-genome) prediction accuracy is not very informative about the ability of a model to capture the genetic signals from specific genomic regions. To address this problem, we propose a simple methodology that detects chromosome regions for which a specific model (e.g., single-step genomic best linear unbiased prediction (ssGBLUP)) may fail to fully capture the genetic signal present in such segments-a phenomenon that we refer to as signal leakage. We propose to detect regions with evidence of signal leakage by testing the association of residuals from a pedigree or a genomic model with SNP genotypes. We discuss how this approach can be used to map regions with signals that are poorly captured by a model and to identify strategies to fix those problems (e.g., using a different prior or increasing marker density). Finally, we explored the proposed approach to scan for signal leakage of different models (pedigree-based, ssGBLUP, and various Bayesian models) applied to growth-related phenotypes (average daily gain and backfat thickness) in pigs. RESULTS: We report widespread evidence of signal leakage for pedigree-based models. Including a percentage of animals with SNP data in ssGBLUP reduced the extent of signal leakage. However, local peaks of missed signals remained in some regions, even when all animals were genotyped. Using variable selection priors solves leakage points that are caused by excessive shrinkage of marker effects. Nevertheless, these models still miss signals in some regions due to low linkage disequilibrium between the SNPs on the array used and causal variants. Thus, we discuss how such problems could be addressed by adding sequence SNPs from those regions to the prediction model. CONCLUSIONS: Residual single-marker regression analysis is a simple approach that can be used to detect regional genomic signals that are poorly captured by a model and to indicate ways to fix such problems.