Takshan/R1 huggingface dataset:
Effects of tobacco smoke and electronic cigarette vapor exposure on the oral and gut microbiota in humans: a pilot study.

Background: The use of electronic cigarettes (ECs) has increased drastically over the past five years, primarily as an alternative to smoking tobacco cigarettes. However, the adverse effects of acute and long-term use of ECs on the microbiota have not been explored. In this pilot study, we sought to determine if ECs or tobacco smoking alter the oral and gut microbiota in comparison to non-smoking controls. Methods: We examined a human cohort consisting of 30 individuals: 10 EC users, 10 tobacco smokers, and 10 controls. We collected cross-sectional fecal, buccal swabs, and saliva samples from each participant. All samples underwent V4 16S rRNA gene sequencing. Results: Tobacco smoking had a significant effect on the bacterial profiles in all sample types when compared to controls, and in feces and buccal swabs when compared to EC users. The most significant associations were found in the gut, with an increased relative abundance of Prevotella (P = 0.006) and decreased Bacteroides (P = 0.036) in tobacco smokers. The Shannon diversity was also significantly reduced (P = 0.009) in fecal samples collected from tobacco smokers compared to controls. No significant difference was found in the alpha diversity, beta-diversity or taxonomic relative abundances between EC users and controls. Discussion: From a microbial ecology perspective, the current pilot data demonstrate that the use of ECs may represent a safer alternative compared to tobacco smoking. However, validation in larger cohorts and greater understanding of the short and long-term impact of EC use on microbiota composition and function is warranted.
Association of nasopharyngeal microbiota profiles with bronchiolitis severity in infants hospitalised for bronchiolitis.

Little is known about the relationship between the specific airway microbiota composition and severity of bronchiolitis. We aimed to identify nasopharyngeal microbiota profiles and link these profiles to acute severity in infants hospitalised for bronchiolitis. We conducted a multicentre prospective cohort study of 1005 infants (age <1 year) hospitalised for bronchiolitis over three winters, 2011-2014. By applying a 16S rRNA gene sequence and clustering approach to the nasopharyngeal aspirates collected within 24 h of hospitalisation, we determined nasopharyngeal microbiota profiles and their association with bronchiolitis severity. The primary outcome was intensive care use, i.e. admission to an intensive care unit or use of mechanical ventilation. We identified four nasopharyngeal microbiota profiles: three profiles were dominated by one of Haemophilus, Moraxella or Streptococcus, while the fourth profile had the highest bacterial richness. The rate of intensive care use was highest in infants with a Haemophilus-dominant profile and lowest in those with a Moraxella-dominant profile (20.2% versus 12.3%; unadjusted OR 1.81, 95% CI 1.07-3.11, p=0.03). After adjusting for 11 patient-level confounders, the rate remained significantly higher in infants with Haemophilus-dominant profiles (OR 1.98, 95% CI 1.08-3.62, p=0.03). These findings were externally validated in a separate cohort of 307 children hospitalised for bronchiolitis.
Effects from a 90-day inhalation toxicity study with cerium oxide and barium sulfate nanoparticles in rats.

BACKGROUND: Nanomaterials like cerium oxide and barium sulfate are frequently processed in industrial and consumer products and exposure of humans and other organisms is likely. Generally less information is given on health effects and toxicity, especially regarding long-term exposure to low nanoparticle doses. Since inhalation is still the major route of uptake the present study focused on pulmonary effects of CeO2NM-212 (0.1, 0.3, 1.0, 3.0 mg/m(3)) and BaSO4NM-220 nanoparticles (50.0 mg/m(3)) in a 90-day exposure setup. To define particle-related effects and potential mechanisms of action, observations in histopathology, bronchoalveolar lavage and immunohistochemistry were linked to pulmonary deposition and clearance rates. This further allows evaluation of potential overload related effects. RESULTS: Lung burden values increased with increasing nanoparticle dose levels and ongoing exposure. At higher doses, cerium clearance was impaired, suggesting lung overload. Barium elimination was extremely rapid and without any signs of overload. Bronchoalveolar lavage fluid analysis and histopathology revealed lung tissue inflammation with increasing severity and post-exposure persistency for CeO2. Also, marker levels for genotoxicity and cell proliferation were significantly increased. BaSO4 showed less inflammation or persistency of effects and particularly affected the nasal cavity. CONCLUSION: CeO2 nanoparticles penetrate the alveolar space and affect the respiratory tract after inhalation mainly in terms of inflammation. Effects at low dose levels and post-exposure persistency suggest potential long-term effects and a notable relevance for human health. The generated data might be useful to improve nanoparticle risk assessment and threshold value generation. Mechanistic investigations at conditions of non-overload and absent inflammation should be further investigated in future studies.
Factor XIII stiffens fibrin clots by causing fiber compaction.

BACKGROUND: Factor XIII-induced cross-linking has long been associated with the ability of fibrin blood clots to resist mechanical deformation, but how FXIII can directly modulate clot stiffness is unknown. OBJECTIVES AND METHODS: We hypothesized that FXIII affects the self-assembly of fibrin fibers by altering the lateral association between protofibrils. To test this hypothesis, we studied the cross-linking kinetics and the structural evolution of the fibers and clots during the formation of plasma-derived and recombinant fibrins by using light scattering, and the response of the clots to mechanical stresses by using rheology. RESULTS: We show that the lateral aggregation of fibrin protofibrils initially results in the formation of floppy fibril bundles, which then compact to form tight and more rigid fibers. The first stage is reflected in a fast (10 min) increase in clot stiffness, whereas the compaction phase is characterized by a slow (hours) development of clot stiffness. Inhibition of FXIII completely abrogates the slow compaction. FXIII strongly increases the linear elastic modulus of the clots, but does not affect the non-linear response at large deformations. CONCLUSIONS: We propose a multiscale structural model whereby FXIII-mediated cross-linking tightens the coupling between the protofibrils within a fibrin fiber, thus making the fiber stiffer and less porous. At small strains, fiber stiffening enhances clot stiffness, because the clot response is governed by the entropic elasticity of the fibers, but once the clot is sufficiently stressed, the modulus is independent of protofibril coupling, because clot stiffness is governed by individual protofibril stretching.
Oral Tranexamic Acid for the Treatment of Melasma: A Review.

BACKGROUND: Melasma is a common acquired disorder of hyperpigmentation that commonly affects those with skin of color. Tranexamic acid (TXA) is a novel treatment for melasma that has a multimodal mechanism of action. OBJECTIVE: To provide a comprehensive review of the literature regarding the evidence on the mode of action, safety profile, and efficacy of TXA in the treatment of melasma. MATERIALS AND METHODS: The literature was searched for publications on TXA in the treatment of melasma using MEDLINE, Scopus, and Google Scholar. RESULTS: Oral TXA has clearly demonstrated the efficacy for melasma in Asian skin, even in low doses (e.g., 500 mg daily) over short periods (8-12 weeks). It is also a safe therapeutic option, which is easy to administer with few and mild side effects. Studies have shown that TXA does not increase the thromboembolic risk, although patients should be screened carefully for contraindications and risk factors prior to commencement of the therapy. CONCLUSION: Oral TXA is a safe and efficacious treatment for refractory melasma. It should be considered in cases that are unresponsive to topical hydroquinone and combination topical therapy over a period of approximately 12 weeks and without contraindications to oral TXA.
Feasibility of real-time capture of routine clinical data in the electronic health record: a hospital-based, observational service-evaluation study.

OBJECTIVES: The electronic health record (EHR) is underused in the hospital setting. The aim of this service evaluation study was to respond to National Health Service (NHS) Digital's ambition for a paperless NHS by capturing routinely collected cardiac outpatient data in the EHR to populate summary patient reports and provide a resource for audit and research. DESIGN: A PowerForm template was developed within the Cerner EHR, for real-time entry of routine clinical data by clinicians attending a cardiac outpatient clinic. Data captured within the PowerForm automatically populated a SmartTemplate to generate a view-only report that was immediately available for the patient and for electronic transmission to the referring general practitioner (GP). RESULTS: During the first 8 months, the PowerForm template was used in 61% (360/594) of consecutive outpatient referrals increasing from 42% to 77% during the course of the study. Structured patient reports were available for immediate sharing with the referring GP using Cerner Health Information Exchange technology while electronic transmission was successfully developed in a substudy of 64 cases, with direct delivery by the NHS Data Transfer Service in 29 cases and NHS mail in the remainder. In feedback, the report's immediate availability was considered very or extremely important by >80% of the patients and GPs who were surveyed. Both groups reported preference of the patient report to the conventional typed letter. Deidentified template data for all 360 patients were successfully captured within the Trust system, confirming availability of these routinely collected outpatient data for audit and research. CONCLUSION: Electronic template development tailored to the requirements of a specialist outpatient clinic facilitates capture of routinely collected data within the Cerner EHR. These data can be made available for audit and research. They can also be used to enhance communication by populating structured reports for immediate delivery to patients and GPs.
Multidrug-resistant gram-negative bacterial infections in a teaching hospital in Ghana.

Background: Multidrug-resistant Gram-negative bacteria have emerged as major clinical and therapeutic dilemma in hospitals in Ghana. To describe the prevalence and profile of infections attributable to multidrug-resistant Gram-negative bacteria among patients at the Komfo Anokye Teaching Hospital in the Ashanti region of Ghana. Methods: Bacterial cultures were randomly selected from the microbiology laboratory from February to August, 2015. Bacterial identification and minimum inhibitory concentrations were conducted using standard microbiological techniques and the Vitek-2 automated system. Patient information was retrieved from the hospital data. Results: Of the 200 isolates, consisting of K. pneumoniae, A. baumannii, P. aeruginosa, Enterobacter spp., E. coli, Yersinia spp., Proteus mirabilis, Pasteurella spp., Chromobacterium violaceum, Salmomella enterica, Vibrio spp., Citrobacter koseri, Pantoea spp., Serratia spp., Providencia rettgeri Burkholderia cepacia, Aeromonas spp., Cadecea lapagei and Sphingomonas paucimobilis, 101 (50.5%) and 99 (49.5%) recovered from male and female patients respectively The largest proportion of patients were from age-group ≥60 years (24.5%) followed by < 10 years (24.0%) and least 10-19 years (9.5%) with a mean patient age of 35.95 ± 27.11 (0.2-91) years. The decreasing order of specimen source was urine 97 (48.5%), wound swabs 47 (23.5%), sputum 22 (11.0%) bronchial lavage, nasal and pleural swabs 1 (0.50%). Urinary tract infection was diagnosed in 34.5% of patients, sepsis in 14.5%, wound infections (surgical and chronic wounds) in 11.0%, pulmonary tuberculosis in 9.0% and appendicitis, bacteremia and cystitis in 0.50%. The isolates showed high resistance to ampicillin (94.4%), trimethoprim/sulfamethoxazole (84.5%), cefuroxime (79.0%) and cefotaxime (71.3%) but low resistance to ertapenem (1.5%), meropenem (3%) and amikacin (11%). The average multi-drug resistance was 89.5%, and ranged from 53.8% in Enterobacter spp. to 100.0% in Acinetobacter spp. and P. aeruginosa. Conclusion: Bacterial infections caused by multi-drug resistant (isolates resistant to at least one agent in three or more antibiotic classes) Gram-negative pathogens among patients at Komfo Anokye Teaching Hospital in Kumasi, Ghana are rife and interventions are necessary for their containment.
Analyzing large scale genomic data on the cloud with Sparkhit.

Motivation: The increasing amount of next-generation sequencing data poses a fundamental challenge on large scale genomic analytics. Existing tools use different distributed computational platforms to scale-out bioinformatics workloads. However, the scalability of these tools is not efficient. Moreover, they have heavy run time overheads when pre-processing large amounts of data. To address these limitations, we have developed Sparkhit: a distributed bioinformatics framework built on top of the Apache Spark platform. Results: Sparkhit integrates a variety of analytical methods. It is implemented in the Spark extended MapReduce model. It runs 92-157 times faster than MetaSpark on metagenomic fragment recruitment and 18-32 times faster than Crossbow on data pre-processing. We analyzed 100 terabytes of data across four genomic projects in the cloud in 21 h, which includes the run times of cluster deployment and data downloading. Furthermore, our application on the entire Human Microbiome Project shotgun sequencing data was completed in 2 h, presenting an approach to easily associate large amounts of public datasets with reference data. Availability and implementation: Sparkhit is freely available at: https://rhinempi.github.io/sparkhit/. Contact: asczyrba@cebitec.uni-bielefeld.de. Supplementary information: Supplementary data are available at Bioinformatics online.
Comparing the Effectiveness of Three Ergonomic Risk Assessment Methods-RULA, LUBA, and NERPA-to Predict the Upper Extremity Musculoskeletal Disorders.

Background: Musculoskeletal disorders are a major problem in all jobs. Several methods are available for assessing the exposure to risk factors associated with musculoskeletal disorders. This study is aimed at comparing three different ergonomic risk assessment methods-rapid upper limb assessment (RULA), loading on the upper body assessment (LUBA), and new ergonomic posture assessment (NERPA) method-to predict upper extremity musculoskeletal disorders. Materials and Methods: The study was conducted on 210 workers from three different industries including pharmaceutical, automotive, and assembly in the Isfahan province. A Nordic questionnaire was used for determining the levels of musculoskeletal disorders. Then, selected postures were evaluated with RULA, LUBA, and NERPA methods. Finally, data were analyzed with Kolmogorov-Smirnov test to check the normality distribution of data, Spearman's correlation test to investigate the correlation between the assessed levels with musculoskeletal disorders, and Wilcoxon test to identify significant differences between the values with SPSS version 16. Results: Wilcoxon test revealed a significant difference between the values related to NERPA and RULA (P < 0.001), whereas no significant relation between LUBA and RULA was shown by this test (P = 0.914). The correlation coefficients of the musculoskeletal disorders' level with RULA level, NERPA level, and LUBA level were 0.74, 0.73, and 0.69, respectively. Conclusion: Low-risk levels in NERPA, medium-risk levels in LUBA, and high-risk levels in RULA are evaluated better. The results showed that RULA was the best method for assessing musculoskeletal disorders among the three methods.
A pooled analysis of on-the-road highway driving studies in actual traffic measuring standard deviation of lateral position (i.e., "weaving") while driving at a blood alcohol concentration of 0.5 g/L.

INTRODUCTION: The on-the-road highway driving test is generally regarded as a gold standard for assessing drug-induced driving impairment. The primary outcome measure is the standard deviation of lateral position (SDLP), a measure of road tracking error or "weaving". The test has been calibrated for incremental doses of alcohol almost 30 years ago in order to define the impact of drug-induced impairment in terms of blood alcohol concentration (BAC) equivalents. Drug-induced changes in SDLP exceeding 2.4 cm have been evaluated as clinically relevant ever since. The present analysis was conducted to assess the robustness of the alcohol effect in a range of on-the-road driving studies which have been conducted since the initial alcohol calibration study. METHODS: The present study pooled data of 182 participants from nine placebo-controlled crossover studies who performed the highway driving test, while their BAC was at or just below the legal limit for drivers (i.e., 0.5 g/L). RESULTS: Overall, mean SDLP increased with 2.5 cm (95% CI 2.0-2.9 cm). Equivalence testing showed that the clinical relevance criterion value of 2.4 cm fell well within the 95% CI in each individual study. Gender did not affect alcohol-induced changes in SDLP. DISCUSSION: These results demonstrate the robustness and validity of the clinical relevance criterion for SDLP as measured during on-the-road driving.
Predictive potential of macrophage migration inhibitory factor (MIF) in patients with heart failure with preserved ejection fraction (HFpEF).

BACKGROUND: Prognostication in heart failure with preserved ejection fraction (HFpEF) is challenging and novel biomarkers are urgently needed. Macrophage migration inhibitory factor (MIF) is a pro-inflammatory cytokine that plays a crucial role in cardiovascular and various inflammatory diseases. Whether MIF is involved in HFpEF is unknown. METHODS AND RESULTS: Sixty-two patients with HFpEF were enrolled and followed up for 180 days. MIF plasma levels as well as natriuretic peptide (NP) levels were assessed. High MIF levels significantly predicted the combined end-point of all-cause death or hospitalization at 180 days in the univariate analysis (HR 2.41, 95% CI 1.12-5.19, p = 0.025) and after adjustment for relevant covariates in a Cox proportional hazard regression model (HR 2.35, 95% CI 1.05-5.27, p = 0.0374). Furthermore, MIF levels above the median were associated with higher pulmonary artery systolic pressure (PASP) as assessed by echocardiography (PASP 31 mmHg vs 48 mmHg in the low- and high-MIF group, respectively, p = 0.017). NPs significantly correlated with MIF in HFpEF patients (BNP p = 0.011; r = 0.32; NT-proBNP p = 0.027; r = 0.28). CONCLUSION: MIF was associated with clinical outcomes and might be involved in the pathophysiology of pulmonary hypertension in patients with HFpEF. These first data on MIF in HFpEF should stimulate further research to elucidate the role of this cytokine in heart failure. Trial registration NCT03232671.
Ex-vivo HRMAS of adult brain tumours: metabolite quantification and assignment of tumour biomarkers.

BACKGROUND: High-resolution magic angle spinning (HRMAS) NMR spectroscopy allows detailed metabolic analysis of whole biopsy samples for investigating tumour biology and tumour classification. Accurate biochemical assignment of small molecule metabolites that are "NMR visible" will improve our interpretation of HRMAS data and the translation of NMR tumour biomarkers to in-vivo studies. RESULTS: 1D and 2D 1H HRMAS NMR was used to determine that 29 small molecule metabolites, along with 8 macromolecule signals, account for the majority of the HRMAS spectrum of the main types of brain tumour (astrocytoma grade II, grade III gliomas, glioblastomas, metastases, meningiomas and also lymphomas). Differences in concentration of 20 of these metabolites were statistically significant between these brain tumour types. During the course of an extended 2D data acquisition the HRMAS technique itself affects sample analysis: glycine, glutathione and glycerophosphocholine all showed small concentration changes; analysis of the sample after HRMAS indicated structural damage that may affect subsequent histopathological analysis. CONCLUSIONS: A number of small molecule metabolites have been identified as potential biomarkers of tumour type that may enable development of more selective in-vivo 1H NMR acquisition methods for diagnosis and prognosis of brain tumours.
Comparison of normalization methods for the analysis of metagenomic gene abundance data.

BACKGROUND: In shotgun metagenomics, microbial communities are studied through direct sequencing of DNA without any prior cultivation. By comparing gene abundances estimated from the generated sequencing reads, functional differences between the communities can be identified. However, gene abundance data is affected by high levels of systematic variability, which can greatly reduce the statistical power and introduce false positives. Normalization, which is the process where systematic variability is identified and removed, is therefore a vital part of the data analysis. A wide range of normalization methods for high-dimensional count data has been proposed but their performance on the analysis of shotgun metagenomic data has not been evaluated. RESULTS: Here, we present a systematic evaluation of nine normalization methods for gene abundance data. The methods were evaluated through resampling of three comprehensive datasets, creating a realistic setting that preserved the unique characteristics of metagenomic data. Performance was measured in terms of the methods ability to identify differentially abundant genes (DAGs), correctly calculate unbiased p-values and control the false discovery rate (FDR). Our results showed that the choice of normalization method has a large impact on the end results. When the DAGs were asymmetrically present between the experimental conditions, many normalization methods had a reduced true positive rate (TPR) and a high false positive rate (FPR). The methods trimmed mean of M-values (TMM) and relative log expression (RLE) had the overall highest performance and are therefore recommended for the analysis of gene abundance data. For larger sample sizes, CSS also showed satisfactory performance. CONCLUSIONS: This study emphasizes the importance of selecting a suitable normalization methods in the analysis of data from shotgun metagenomics. Our results also demonstrate that improper methods may result in unacceptably high levels of false positives, which in turn may lead to incorrect or obfuscated biological interpretation.