Characterization of chemical reactions of silver diammine fluoride and hydroxyapatite under remineralization conditions.

Introduction: Silver Diammine Fluoride (SDF) is a clinically used topical agent to arrest dental caries. However, the kinetics of its chemical interactions with hydroxyapatite (HA), the principal inorganic component of dental enamel, are not known. The aim was to characterize the step-wise chemical interactions between SDF and HA powder during the clinically important process of remineralization. Methods: Two grams of HA powder were immersed in 10 ml acetic acid pH = 4.0 for 2 h to mimic carious demineralization. The powder was then washed and dried for 24 h and mixed with 1.5 ml SDF (Riva Star) for 1 min. The treated powder was then air-dried for 3 min, and 0.2 g was removed and stored in individual tubes each containing 10 ml remineralizing solution. Powder was taken from each tube at various times of exposure to remineralization solution (0 min, 10 min, 2 h, 4 h, 8 h, 24 h, and 10 days), and characterized using Magic Angle Spinning-Nuclear Magnetic Resonance (MAS-NMR) spectroscopy. Results and discussion: 19F MAS-NMR spectra showed that calcium fluoride (CaF2) started to form almost immediately after HA was in contact with SDF. After 24 h, the peak shifted to -104.5 ppm suggesting that fluoride substituted hydroxyapatite (FSHA) was formed with time at the expense of CaF2. The 31P MAS-NMR spectra showed a single peak at 2.7 ppm at all time points showing that the only phosphate species present was crystalline apatite. The 35Cl MAS-NMR spectra showed formation of silver chloride (AgCl) at 24 h. It was observed that after the scan, the whitish HA powder changed to black color. In conclusion, this time sequence study showed that under remineralization conditions, SDF initially reacted with HA to form CaF2 which is then transformed to FSHA over time. In the presence of chloride, AgCl is formed which is subsequently photo-reduced to black metallic silver.

BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification.

The accurate classification of non-coding RNA (ncRNA) sequences is pivotal for advanced non-coding genome annotation and analysis, a fundamental aspect of genomics that facilitates understanding of ncRNA functions and regulatory mechanisms in various biological processes. While traditional machine learning approaches have been employed for distinguishing ncRNA, these often necessitate extensive feature engineering. Recently, deep learning algorithms have provided advancements in ncRNA classification. This study presents BioDeepFuse, a hybrid deep learning framework integrating convolutional neural networks (CNN) or bidirectional long short-term memory (BiLSTM) networks with handcrafted features for enhanced accuracy. This framework employs a combination of k-mer one-hot, k-mer dictionary, and feature extraction techniques for input representation. Extracted features, when embedded into the deep network, enable optimal utilization of spatial and sequential nuances of ncRNA sequences. Using benchmark datasets and real-world RNA samples from bacterial organisms, we evaluated the performance of BioDeepFuse. Results exhibited high accuracy in ncRNA classification, underscoring the robustness of our tool in addressing complex ncRNA sequence data challenges. The effective melding of CNN or BiLSTM with external features heralds promising directions for future research, particularly in refining ncRNA classifiers and deepening insights into ncRNAs in cellular processes and disease manifestations. In addition to its original application in the context of bacterial organisms, the methodologies and techniques integrated into our framework can potentially render BioDeepFuse effective in various and broader domains.

Tenofovir diphosphate in dried blood spots and HIV-1 resistance in South Africa.

BACKGROUND: Suboptimal antiretroviral (ART) adherence can lead to virologic failure with consequent HIV-1 resistance. Tenofovir diphosphate (TFV-DP) in dried blood spots (DBS) is a powerful biomarker of cumulative adherence, predictive of future viremia. It has been associated with resistance in Persons With HIV (PWH) in South Africa and the US. We explored the relationship of TFV-DP concentrations with antiretroviral drug resistance at the time of treatment failure in SA. METHODS: Adult PWH from health clinics in Cape Town, South Africa on efavirenz-based first-line ART containing tenofovir disoproxil fumarate (TDF) with an undetectable (< 50 copies/mL) HIV-1 viral load (VL) were prospectively enrolled in an observational cohort for 12 months. Monthly study visits included blood collection for HIV-1 VL and DBS for TFV-DP. The first confirmed viral breakthrough (VB) > 400 copies/mL triggered HIV-1 genotyping at the subsequent visit. An electronic adherence (EA) device monitored ART adherence in real-time, estimated as a percent for the 30-days prior to VB. Wilcoxon rank sum test was used to compare median [IQR] TFV-DP by genotype outcome. RESULTS: Of 250 individuals, (n = 195, 78% women), 21 experienced VB, with a median of 5 [4;7] months on study, and a median EA of 33.3 [13.3;53.3]%. Demographic characteristics between those with and without VB were similar. Median VL at VB was 4.0 [3.2;4.5] log copies/mL. TFV-DP concentrations trended down towards the VB visit. Median TFV-DP concentrations were significantly higher in those HIV-1 genotype did not amplify due to being virally suppressed at the subsequent visit (n = 10; 380 [227-661] fmol/punch, p = 0.035; EA 45 [24.9; 59.2]%); than in those who were successfully genotyped with evidence of drug resistance (n = 5, 241 [150-247] fmol/punch, EA 20 [6.7;36.7]%) and in individuals who did not have resistance (n = 3, 39.9 [16.6; 93.9] fmol/punch; EA 33.3 [16-38]%). Three genotype collections were not done. Only non-nucleoside reverse transcriptase inhibitor-associated mutations were identified on resistance testing. (K103N, E138K, Y118H). CONCLUSION: TFV-DP in DBS showed a step-wise inverse relationship with VB and drug resistance, with evidence of low cumulative ART adherence in PWH who developed antiretroviral resistance. Monitoring TFV-DP concentrations could be a valuable tool for predicting future VB and future resistance.

Integrating remote sensing and machine learning to detect turbidity anomalies in hydroelectric reservoirs.

Monitoring water quality in reservoirs is essential for the maintenance of aquatic ecosystems and socioeconomic services. In this scenario, the observation of abrupt elevations of physicochemical parameters, such as turbidity and other indicators, can signal anomalies associated with the occurrence of critical events, requiring operational actions and planning to mitigate negative environmental impacts on water resources. This work aims to integrate Machine Learning methods specialized in anomaly detection with data obtained from remote sensing images to identify with high turbidity events in the surface water of the Três Marias Hydroelectric Reservoir. Four distinct threshold-based scenarios were evaluated, in which the overall performance, based on F1-score, showed decreasing trends as the thresholds became more restrictive. In general, the anomaly identification maps generated through the models ratified the applicability of the methods in the diagnosis of surface water in reservoirs in distinct hydrological contexts (dry and wet), effectively identifying locations with anomalous turbidity values.

Sodium fluoride (Na18F) PET Response Criteria in Solid Tumors (NAFCIST): a framework for response assessment in bone tumors.

The current Response Evaluation Criteria in Solid Tumors for measuring tumor response in osteosarcoma may be sub-optimal, as even responsive bone tumors may show limited change in tumor diameters. This limits the use of traditional imaging assessment tools. Therefore, discerning osteosarcoma response to therapy on magnetic resonance imaging before surgery is often difficult, and it is typically evaluated after surgery by assessing the amount of necrosis in resected surgical specimens. To address these challenges, sodium fluoride (Na18F) positron emission tomography/computed tomography (PET/CT) scans can be utilized to better image bone response to therapy, as, fluoride is avidly taken up by bone. Na18F Response Criteria in Solid Tumors (NAFCIST) has been developed as a novel method to evaluate treatment response using Na18F PET/CT. Current evidence supporting NAFCIST comes from a pilot study that evaluated alpha particle radium-223 in patients with osteosarcoma. In this review, practical guidance for utilizing NAFCIST in the context of bone tumors is illustrated to aid future studies.

Measuring ART Adherence Among Young Adults with Perinatally Acquired HIV: Comparison Between Self-report, Telephone-Based Pill Count, and Objective Pharmacologic Measures.

Tenofovir diphosphate (TVF-DP) can be quantified in red blood cells (RBCs) and dried blood spots (DBS) and can objectively measure ART adherence and predict viral suppression. Data on the association of TFV-DP with viral load are very limited in adolescents and young adults (AYA) living with perinatally-acquired HIV (PHIV), as are data comparing TFV-DP to other measures of ART adherence, such as self-report and unannounced telephone pill count. Viral load and ART adherence (self-report, TFV-DP and unannounced telephone pill count) were assessed and compared among 61 AYAPHIV recruited from an ongoing longitudinal study (CASAH) in New York City.

Evaluation of biocidal properties of biodegradable nanofiber filters and their use in face masks.

Due to the recent coronavirus-2019 pandemic, several studies have emerged looking for new materials, especially with biocidal characteristics. Thus, the present research investigates the antibacterial properties of biodegradable cellulose acetate (CA) / cetylpyridinium bromide (CPB) electrospun nanofibers, their aerosol filtration, and the possible use as a filter media of surgical face masks. Then, samples of these nanofibers were produced over a nonwoven substrate, using different volumes of polymeric solution during the electrospinning process. The evaluation of the antibacterial properties of the nanofibers was performed for Escherichia coli and Staphylococcus aureus using quantitative methods. The aerosol filtration performance was evaluated in these samples for NaCl nanoparticles (from 7-300 nm) and with 8 mL min-1 of air flow rate. The results show that the single use of the surfactant has antibacterial properties from a concentration of 39 µg mL-1 of solution. The nanofibers presented a reduction of 100% for both bacteria. Air filtration tests showed 126.03 and 207.73 Pa cm-² of pressure drops and 63 and 77% of aerosol filtration efficiency (FE) for samples with 0.13 and 0.15 mL, respectively. Regarding the nanofiber produced with 0.35 mL, the value obtained was 115.13 ± 33.64 Pa cm-2 and 3.15% of particle penetration. These breathability values are higher than those required for the surgical face mask standard, indicating that improvements in the porosity and thickness are necessary to meet the Brazilian requirements. However, the nanofibers could be applied as filter media for indoor air conditioning systems due to their FE and biocidal properties.

Kidney functions adaptations of professional soccer players in response to an entire game season.

This study investigated the renal function of soccer players after an entire game-season. Thirty-five athletes recruited to play for the Macae Futebol Clube were invited for this study, of which 18 athletes completed the entire game season. Blood and 24-hour urine were collected at the beginning (Pre-Season) and the end of the game season (Post-Season). Kidney functions were assessed by calculating the urinary excretion, clearance, and fractional excretion of the selected solutes. Plasma creatinine, sodium, total protein, and osmolality were lower in the Post-Season . In contrast, plasma urea was higher in the Post-Season period. Urinary excretion of urea was reduced while albumin excretion was higher in comparison to Pre-Season. The clearances of creatinine, total proteins, and albumin were higher in the Post-Season period. In accordance, the fractional excretion of albumin increased. On the other hand, the clearance and fractional excretion of urea was lower in the Post-Season period. These results show that soccer-associated exercise throughout the entire game-season induces kidney functions adaptations that may prevent dehydration in these athletes through increased urea reabsorption to conserve water. In addition, this data corroborates to increased glomerular permeability to plasma proteins, such as albumin, that soccer players may experience.

MarineMetagenomeDB: a public repository for curated and standardized metadata for marine metagenomes.

BACKGROUND: Metagenomics is an expanding field within microbial ecology, microbiology, and related disciplines. The number of metagenomes deposited in major public repositories such as Sequence Read Archive (SRA) and Metagenomic Rapid Annotations using Subsystems Technology (MG-RAST) is rising exponentially. However, data mining and interpretation can be challenging due to mis-annotated and misleading metadata entries. In this study, we describe the Marine Metagenome Metadata Database (MarineMetagenomeDB) to help researchers identify marine metagenomes of interest for re-analysis and meta-analysis. To this end, we have manually curated the associated metadata of several thousands of microbial metagenomes currently deposited at SRA and MG-RAST. RESULTS: In total, 125 terms were curated according to 17 different classes (e.g., biome, material, oceanic zone, geographic feature and oceanographic phenomena). Other standardized features include sample attributes (e.g., salinity, depth), sample location (e.g., latitude, longitude), and sequencing features (e.g., sequencing platform, sequence count). MarineMetagenomeDB version 1.0 contains 11,449 marine metagenomes from SRA and MG-RAST distributed across all oceans and several seas. Most samples were sequenced using Illumina sequencing technology (84.33%). More than 55% of the samples were collected from the Pacific and the Atlantic Oceans. About 40% of the samples had their biomes assigned as 'ocean'. The 'Quick Search' and 'Advanced Search' tabs allow users to use different filters to select samples of interest dynamically in the web app. The interactive map allows the visualization of samples based on their location on the world map. The web app is also equipped with a novel download tool (on both Windows and Linux operating systems), that allows easy download of raw sequence data of selected samples from their respective repositories. As a use case, we demonstrated how to use the MarineMetagenomeDB web app to select estuarine metagenomes for potential large-scale microbial biogeography studies. CONCLUSION: The MarineMetagenomeDB is a powerful resource for non-bioinformaticians to find marine metagenome samples with curated metadata and stimulate meta-studies involving marine microbiomes. Our user-friendly web app is publicly available at https://webapp.ufz.de/marmdb/ .

Realist analysis of whether emergency departments with primary care services generate 'provider-induced demand'.

BACKGROUND: It is not known whether emergency departments (EDs) with primary care services influence demand for non-urgent care ('provider-induced demand'). We proposed that distinct primary care services in EDs encourages primary care demand, whereas primary care integrated within EDs may be less likely to cause additional demand. We aimed to explore this and explain contexts (C), mechanisms (M) and outcomes (O) influencing demand. METHODS: We used realist evaluation methodology and observed ED service delivery. Twenty-four patients and 106 staff members (including Clinical Directors and General Practitioners) were interviewed at 13 EDs in England and Wales (240 hours of observations across 30 days). Field notes from observations and interviews were analysed by creating 'CMO' configurations to develop and refine theories relating to drivers of demand. RESULTS: EDs with distinct primary care services were perceived to attract demand for primary care because services were visible, known or enabled direct access to health care services. Other influencing factors included patients' experiences of accessing primary care, community care capacity, service design and population characteristics. CONCLUSIONS: Patient, local-system and wider-system factors can contribute to additional demand at EDs that include primary care services. Our findings can inform service providers and policymakers in developing strategies to limit the effect of potential influences on additional demand when demand exceeds capacity.

BioAutoML: automated feature engineering and metalearning to predict noncoding RNAs in bacteria.

Recent technological advances have led to an exponential expansion of biological sequence data and extraction of meaningful information through Machine Learning (ML) algorithms. This knowledge has improved the understanding of mechanisms related to several fatal diseases, e.g. Cancer and coronavirus disease 2019, helping to develop innovative solutions, such as CRISPR-based gene editing, coronavirus vaccine and precision medicine. These advances benefit our society and economy, directly impacting people's lives in various areas, such as health care, drug discovery, forensic analysis and food processing. Nevertheless, ML-based approaches to biological data require representative, quantitative and informative features. Many ML algorithms can handle only numerical data, and therefore sequences need to be translated into a numerical feature vector. This process, known as feature extraction, is a fundamental step for developing high-quality ML-based models in bioinformatics, by allowing the feature engineering stage, with design and selection of suitable features. Feature engineering, ML algorithm selection and hyperparameter tuning are often manual and time-consuming processes, requiring extensive domain knowledge. To deal with this problem, we present a new package: BioAutoML. BioAutoML automatically runs an end-to-end ML pipeline, extracting numerical and informative features from biological sequence databases, using the MathFeature package, and automating the feature selection, ML algorithm(s) recommendation and tuning of the selected algorithm(s) hyperparameters, using Automated ML (AutoML). BioAutoML has two components, divided into four modules: (1) automated feature engineering (feature extraction and selection modules) and (2) Metalearning (algorithm recommendation and hyper-parameter tuning modules). We experimentally evaluate BioAutoML in two different scenarios: (i) prediction of the three main classes of noncoding RNAs (ncRNAs) and (ii) prediction of the eight categories of ncRNAs in bacteria, including housekeeping and regulatory types. To assess BioAutoML predictive performance, it is experimentally compared with two other AutoML tools (RECIPE and TPOT). According to the experimental results, BioAutoML can accelerate new studies, reducing the cost of feature engineering processing and either keeping or improving predictive performance. BioAutoML is freely available at https://github.com/Bonidia/BioAutoML.

Pseudomonas aeruginosa Infection Modulates the Immune Response and Increases Mice Resistance to Cryptococcus gattii.

Cryptococcosis is an invasive mycosis caused by Cryptococcus spp. that affects the lungs and the central nervous system (CNS). Due to the severity of the disease, it may occur concomitantly with other pathogens, as a coinfection. Pseudomonas aeruginosa (Pa), an opportunistic pathogen, can also cause pneumonia. In this work, we studied the interaction of C. gattii (Cg) and Pa, both in vitro and in vivo. Pa reduced growth of Cg by the secretion of inhibitory molecules in vitro. Macrophages previously stimulated with Pa presented increased fungicidal activity. In vivo, previous Pa infection reduced morbidity and delayed the lethality due to cryptococcosis. This phenotype was correlated with the decreased fungal burden in the lungs and brain, showing a delay of Cg translocation to the CNS. Also, there was increased production of IL-1ß, CXCL-1, and IL-10, together with the influx of iNOS-positive macrophages and neutrophils to the lungs. Altogether, Pa turned the lung into a hostile environment to the growth of a secondary pathogen, making it difficult for the fungus to translocate to the CNS. Further, iNOS inhibition reverted the Pa protective phenotype, suggesting its important role in the coinfection. Altogether, the primary Pa infection leads to balanced pro-inflammatory and anti-inflammatory responses during Cg infection. This response provided better control of cryptococcosis and was decisive for the mild evolution of the disease and prolonged survival of coinfected mice in a mechanism dependent on iNOS.

Effect of degeneration on bone mineral density, trabecular bone score and CT Hounsfield unit measurements in a spine surgery patient population.

This study investigated the impact of spinal degeneration on bone mineral density (BMD), trabecular bone score (TBS), and CT Hounsfield units in an at-risk population. We found that BMD was increased by degeneration, whereas TBS and HU were unaffected. These findings support that TBS is not adversely affected by spinal degeneration. INTRODUCTION: This study evaluated the impact of spinal degeneration on BMD and TBS measured by dual-energy x-ray absorptiometry (DXA) and on CT HU in a spine surgery patient population. METHODS: A retrospective study of 63 patients referred for consideration of spine surgery or with history of spine surgery was performed. Patients were included if a DXA scan and a CT containing the lumbar spine were obtained within 18 months of each other. DXA data were collected and analyzed by vertebral level. Individual vertebrae were assessed for degenerative changes by qualitative evaluation of the anterior and posterior elements using CT. Degeneration scores were compared to BMD T-scores, TBS and CT HU at individual vertebral levels L1-4, and after applying International Society for Clinical Densitometry (ISCD) criteria for excluding vertebrae from diagnostic consideration. RESULTS: Mean patient age and BMI were 67.2 years and 27.8 kg/m2, respectively; 79.4% were female. Mean (SD) lowest T-scores of the hip, spine, and lowest overall T-score were - 1.3 (1.4), - 1.7 (0.9), and - 1.9 (1.0), respectively. Osteoporosis was present by T-score in 38% and osteopenia in 52%; 10% had a history of osteoporotic fracture. The mean degeneration score of individual vertebrae was 4.1 on a 0-6 scale. T-score correlated moderately with degeneration score (Spearman's rho 0.484, p < 0.001), whereas TBS and HU were unrelated. ISCD excluded vertebrae had a higher degeneration score than included vertebrae (p = < 0.001). CONCLUSIONS: In a spine surgery population, TBS and CT HU values are unrelated to degeneration score and thus appear unaffected by lumbar vertebral degenerative changes. Additionally, these data support the ISCD criteria for vertebral exclusion.

Effect of topically applied silver compounds on the demineralisation of hydroxyapatite.

OBJECTIVES: This study investigates the demineralization inhibitory mechanisms of AgNO3, AgF and silver diamine fluoride (SDF) using a previously used hydroxyapatite (HAP) caries demineralization model system. METHODS: HAP discs were allocated into three groups (n = 3) and immersed in demineralization solution (buffered pH 4.0, 0.1 mol/L acetic acid) for 4 h. Each disc was treated topically with either 3.16 M AgNO3, 3.16 M AgF or 3.16 M SDF using a micro-brush. The discs were then demineralized for a further 4 h. Calcium, silver, and fluoride ion selective electrodes (ISEs) were used to monitor the changes in each ion concentration at 1 min intervals throughout. Demineralization inhibition was calculated as the percentage reduction in the rate of calcium ion loss from HAP (PRCLHAP). Characterization of similarly treated HAP powder was carried out with Magic Angle Spinning-Nuclear Magnetic Resonance RESULTS: The mean PRCLHAP for each treatment group was; AgF (72.3 + 4.8%), SDF (69.7 + 5.3%) and AgNO3 (14.9 + 2.7%). Ag3PO4 was detected in all HAP powders. CaF2 and fluorohydroxyapatite (FHA) were detected only in powders treated with either AgF or SDF. The demineralization inhibitory efficacy of topically applied AgNO3 results from the formation of a Ag3PO4 barrier. Whereas, the demineralization inhibitory efficacy of topically applied AgF, and SDF, results from the formation of a barrier composed of Ag3PO4, CaF2, and FHA. SIGNIFICANCE: In addition to their anti-microbial properties, clinical topical application of silver compounds for caries preventative treatment is due to their ability to form acid-resistant barriers composed of silver phosphate. When fluoride is present, this barrier also contains CaF2 and FHA, additionally protecting the mineral.

Changes in serum neurofilament light chain levels following narrowband ultraviolet B phototherapy in clinically isolated syndrome.

OBJECTIVE: To determine whether serum neurofilament light chain (sNfL) levels are suppressed in patients with the clinically isolated syndrome (CIS) following narrowband ultraviolet B phototherapy (UVB-PT). METHODS: sNfL levels were measured using a sensitive single-molecule array assay at baseline and up to 12 months in 17 patients with CIS, 10 of whom received UVB-PT, and were compared with healthy control (HC) and early relapsing remitting multiple sclerosis (RRMS) group. sNfL levels were correlated with magnetic resonance imaging total lesion volume (LV) determined using icobrain version 4.4.1 and with clinical outcomes. RESULTS: Baseline median sNfL levels were significantly higher in the CIS (20.6 pg/mL, interquartile range [IQR] 13.7-161.4) and RRMS groups (36.6 pg/ml [IQR] 16.2-212.2) than in HC (10.7 pg/ml [IQR] 4.9-21.5) (p = .012 and p = .0002, respectively), and were strongly correlated with T2 and T1 LV at 12 months (r = .800; p = .014 and r = .833; p = .008, respectively) in the CIS group. Analysis of changes in sNfL levels over time in the CIS group showed a significant cumulative suppressive effect of UVB-PT in the first 3 months (UVB-PT -10.6% vs non-UVB-PT +58.3%; p = .04) following which the levels in the two groups converged and continued to fall. CONCLUSIONS: Our findings provide the basis for further studies to determine the utility of sNfL levels as a marker of neuro-axonal damage in CIS and early MS and for assessing the efficacy of new therapeutic interventions such as UVB-PT.

Information Theory for Biological Sequence Classification: A Novel Feature Extraction Technique Based on Tsallis Entropy.

In recent years, there has been an exponential growth in sequencing projects due to accelerated technological advances, leading to a significant increase in the amount of data and resulting in new challenges for biological sequence analysis. Consequently, the use of techniques capable of analyzing large amounts of data has been explored, such as machine learning (ML) algorithms. ML algorithms are being used to analyze and classify biological sequences, despite the intrinsic difficulty in extracting and finding representative biological sequence methods suitable for them. Thereby, extracting numerical features to represent sequences makes it statistically feasible to use universal concepts from Information Theory, such as Tsallis and Shannon entropy. In this study, we propose a novel Tsallis entropy-based feature extractor to provide useful information to classify biological sequences. To assess its relevance, we prepared five case studies: (1) an analysis of the entropic index q; (2) performance testing of the best entropic indices on new datasets; (3) a comparison made with Shannon entropy and (4) generalized entropies; (5) an investigation of the Tsallis entropy in the context of dimensionality reduction. As a result, our proposal proved to be effective, being superior to Shannon entropy and robust in terms of generalization, and also potentially representative for collecting information in fewer dimensions compared with methods such as Singular Value Decomposition and Uniform Manifold Approximation and Projection.

Opportunistic Use of Lumbar Magnetic Resonance Imaging for Osteoporosis Screening.

Magnetic resonance imaging (MRI) is a routine assessment before spine surgery. We found that the opportunistic use of MRI with the vertebral bone quality (VBQ) score has good diagnostic ability, with a threshold value of VBQ > 3.0, in recognizing patients who may need further osteoporosis evaluation. INTRODUCTION: The purpose of this study was to determine whether the opportunistic use of magnetic resonance imaging (MRI) is useful for identifying spine surgical patients who need further osteoporosis evaluation. METHODS: This retrospective study evaluated 83 thoracolumbar spine surgery patients age ≥ 50 who received T1-weighted MRI. Opportunistic MRI was evaluated with the vertebral bone quality (VBQ) score, VBQ (fat) score, and signal-to-noise ratio (SNR). Each uses the median L1-L4 vertebral body signal intensities (SI) divided by either the L3 cerebrospinal fluid (CSF) SI, average SI of the L1 and S1 dorsal fat, or standard deviation (SD) of the background SI dorsal to the skin. Single-level VBQ was calculated as the ratio of the L1 vertebral body and L1 CSF SIs. Receiver-operator curve analysis was performed to determine diagnostic ability. RESULTS: The mean age was 70.10, 80% were female, and 96% were Caucasian. The mean ± SD VBQ, single-level VBQ, VBQ (fat), and SNR were 3.39 ± 0.68, 3.56 ± 0.81, 3.95 ± 1.89, and 113.18 ± 77.26, respectively. Using area under the curve, the diagnostic ability of VBQ, single-level VBQ, VBQ (fat), and SNR for clinical osteoporosis were 0.806, 0.779, 0.608, and 0.586, respectively. Diagnostic threshold values identified with optimal sensitivity and specificity were VBQ of 2.95 and single-level VBQ of 3.06. CONCLUSION: Opportunistic use of MRI is a simple, effective tool that may help recognize patients who are at risk for complications related to bone disease. A VBQ > 3.0 can identify patients who need additional diagnostic evaluation.

Chemical characterization of PM2.5 from region highly impacted by hailstorms in South America.

The chemical composition of particulate material plays an important role in the atmosphere, providing cloud and ice nuclei for storm development. This study aims to evaluate and infer the sources of ions, metals, and metalloids in the fine atmospheric particulate matter (PM2.5) from triple border Paraná, Santa Catarina (Brazil), and northeastern Argentina, which is among those with the highest hail incidence in the world. Among the ions, the concentrations presented the following sequence in decreasing order: [Formula: see text]> K+> [Formula: see text]> [Formula: see text]> Ca2+> Cl-> Na+> Mg2+. Regarding the metals and metalloid concentrations, the order was of S > Si > Al > Fe > P > Ti, Cr, Cu, and Zn > Br > Mn, and Ni. The main sources, supported by positive matrix factorization results, are soil and agricultural activities, as well as vehicular emissions due to the agricultural machinery and the displacement of residents. Besides, the influence of aerosols from biomass burning and industrial activities was observed, possibly come from long-distance transport. The composition of PM2.5 presents one or more elements considered present ice nuclei (IN) activity, such as Al, Mn, Cu, Co, Ni, and V (in form of oxides), corroborating with other studies, also, with high hail incidence. However, further studies are needed to verify the role of aerosol characteristics in the formation of IN and, consequently, hail.

Metabolome fingerprints, performance and carcass quality of beef calves supplemented with antibiotic free additive.

The aim of this study was to investigate the effects of probiotics on pre-weaning performance, muscle, and fat deposition and serum metabolite profiles in male and female Senepol calves. Thirty new-born Senepol calves, 15 males and 15 females, were randomly allocated to the following treatments: CON a control group that received the basal creep feeding diet and PRO animals that received the basal diet with addition of 2 g/100 kg of body weight (BW) of probiotic. PRO supplementation did not change the DMI but increased average BW, final BW, ADG relative to animals fed CON. Additionally, PRO improved LMA and marbling. Regardless of the serum metabolite profile, the important metabolites for discriminating PRO and CON were glutamine, leucine, creatine, acetate, creatinine, arginine, glutamate, hippurate, glycerol, carnitine, lactate, carnosine, myo-inositol and histidine. According to gender, males had an overabundance of glutamine, glycerol, isoleucine, creatinine and glucose, whereas females had an overabundance of acetyl carnitine, glutamate and carnitine. In conclusion, the addition of PRO in the pre-weaning diet of calves increases performance, weight at weaning and muscle and fat deposition on the carcass, improving proteins and fatty acid metabolism, the immune system response and rumen development.