Miracle-dz/UniFAR-FTUs huggingface dataset:
Thyroid gland delineation in noncontrast-enhanced CTs using deep convolutional neural networks

The purpose of this study is to develop a deep learning method for thyroid delineation with high accuracy, efficiency, and robustness in noncontrast-enhanced head and neck CTs. The cross-sectional analysis consisted of six tests, including randomized cross-validation and hold-out experiments, tests of prediction accuracy between cancer and benign and cross-gender analysis were performed to evaluate the proposed deep-learning-based performance method. CT images of 1977 patients with suspected thyroid carcinoma were retrospectively investigated. The automatically segmented thyroid gland volume was compared against physician-approved clinical contours using metrics, the Pearson correlation and Bland–Altman analysis. Quantitative metrics included: the Dice similarity coefficient (DSC), sensitivity, specificity, Jaccard index (JAC), Hausdorff distance (HD), mean surface distance (MSD), residual mean square distance (RMSD) and the center of mass distance (CMD). The robustness of the proposed method was further tested using the nonparametric Kruskal–Wallis test to assess the equality of distribution of DSC values. The proposed method’s accuracy remained high through all the tests, with the median DSC, JAC, sensitivity and specificity higher than 0.913, 0.839, 0.856 and 0.979, respectively. The proposed method also resulted in median MSD, RMSD, HD and CMD, of less than 0.31 mm, 0.48 mm, 2.06 mm and 0.50 mm, respectively. The MSD and RMSD were 0.40 ± 0.29 mm and 0.70 ± 0.46 mm, respectively. Concurrent testing of the proposed method with 3D U-Net and V-Net showed that the proposed method had significantly improved performance. The proposed deep-learning method achieved accurate and robust performance through six cross-sectional analysis tests.
Safety and efficacy of double vs. triple antithrombotic therapy in patients with atrial fibrillation with or without acute coronary syndrome undergoing percutaneous coronary intervention: a collaborative meta-analysis of non-vitamin K antagonist oral anticoagulant-based randomized clinical trials

Abstract Aims Safety and efficacy of antithrombotic regimens in patients with atrial fibrillation (AF) undergoing percutaneous coronary intervention (PCI) may differ based on clinical presentation. We sought to compare double vs. triple antithrombotic therapy (DAT vs. TAT) in AF patients with or without acute coronary syndrome (ACS) undergoing PCI. Methods and results A systematic review and meta-analysis was performed using PubMed to search for non-vitamin K antagonist oral anticoagulant (NOAC)-based randomized clinical trials. Data on subgroups of ACS or elective PCI were obtained by published reports or trial investigators. A total of 10 193 patients from four NOAC trials were analysed, of whom 5675 presenting with ACS (DAT = 3063 vs. TAT = 2612) and 4518 with stable coronary artery disease (SCAD; DAT = 2421 vs. TAT = 2097). The primary safety endpoint of ISTH major bleeding or clinically relevant non-major bleeding was reduced with DAT compared with TAT in both ACS (12.2% vs. 19.4%; RR 0.63, 95% CI 0.56–0.71; P < 0.0001; I2 = 0%) and SCAD (14.6% vs. 22.0%; RR 0.68, 95% CI 0.55–0.85; P = 0.0008; I2 = 66%), without interaction (P-int = 0.54). Findings were consistent for secondary bleeding endpoints, including intra-cranial haemorrhage. In both subgroups, there was no difference between DAT and TAT for all-cause death, major adverse cardiovascular events, or stroke. Myocardial infarction and stent thrombosis were numerically higher with DAT vs. TAT consistently in ACS and SCAD (P-int = 0.60 and 0.86, respectively). Findings were confirmed by multiple sensitivity analyses, including a separate analysis on dabigatran regimens and a restriction to PCI population. Conclusions DAT, compared with TAT, is associated with lower bleeding risks, including intra-cranial haemorrhage, and a small non-significant excess of cardiac ischaemic events in both patients with or without ACS.
Computational Studies towards the Identification of Novel Rhodopsin-Binding Compounds as Chemical Chaperones for Misfolded Opsins

Accumulation of misfolded and mistrafficked rhodopsin on the endoplasmic reticulum of photoreceptor cells has a pivotal role in the pathogenesis of retinitis pigmentosa and a subset of Leber’s congenital amaurosis. One potential strategy to reduce rhodopsin misfolding and aggregation in these conditions is to use opsin-binding compounds as chemical chaperones for opsin. Such molecules have previously shown the ability to aid rhodopsin folding and proper trafficking to the outer cell membranes of photoreceptors. As means to identify novel chemical chaperones for rhodopsin, a structure-based virtual screening of commercially available drug-like compounds (300,000) was performed on the main binding site of the visual pigment chromophore, the 11-cis-retinal. The best 24 virtual hits were examined for their ability to compete for the chromophore-binding site of opsin. Among these, four small molecules demonstrated the ability to reduce the rate constant for the formation of the 9-cis-retinal-rhodopsin complex, while five molecules surprisingly enhanced the formation of this complex. Compound 7, 13, 20 and 23 showed a weak but detectable increase in the trafficking of the P23H mutant, widely used as a model for both retinitis pigmentosa and Leber’s congenital amaurosis, from the ER to the cell membrane. The compounds did not show any relevant cytotoxicity in two different human cell lines, with the only exception of 13. Based on the structures of these active compounds, a series of in silico studies gave important insights on the potential structural features required for a molecule to act either as chemical chaperone or as stabiliser of the 11-cis-retinal-rhodopsin complex. Thus, this study revealed a series of small molecules that represent a solid foundation for the future development of novel therapeutics against these severe inherited blinding diseases.
Dual Process Coding of Recalled Locations in Human Oscillatory Brain Activity

A mental representation of the location of an object can be constructed using sensory information selected from the environment and information stored internally. Human electrophysiological evidence indicates that behaviorally relevant locations, regardless of the source of sensory information, are represented in alpha-band oscillations suggesting a shared process. Here, we present evidence from human subjects of either sex for two distinct alpha-band-based processes that separately support the representation of location, exploiting sensory evidence sampled either externally or internally. SIGNIFICANCE STATEMENT Our sensory environment and our internal trains of thought are coded in patterns of brain activity and are used to guide coherent behavior. Oscillations in the alpha-frequency band are a predominant feature of human brain activity. This oscillation plays a central role in both selective attention and working memory, suggesting that these important cognitive functions are mediated by a unitary mechanism. We show that the alpha oscillation reflects two distinct processes, one that is supported by continuous sampling of the external sensory environment, and one that is based on sampling from internal representations coded in visual short-term memory. This represents a significant change in our understanding of the nature of alpha oscillations and their relationship to attention and memory.
Investigation of House Flies as a Potential Reservoir of Multidrug Resistant Bacteria in Selected Locations within Port Harcourt, Rivers State, Nigeria

resistant to most antibiotics and resulting in therapy failures. One key step in preventing the development of drug resistance involves a knowledge of possible reservoirs of this resistance. This study was aimed at investigating the role houseflies play as reservoirs of multidrug resistance. Abstract The common houseflies are known vectors capable of transmitting organisms from human to human. At present most studies have focused simply on pathogen detection rather than frequency while a few have described antibiogram patterns and multidrug resistance (MDR). This study aimed at analyzing house flies caught in two poultry farms and close-by residential areas using standard microbiological techniques. The house flies were identified by their physical characteristics using standard keys. Of the total bacteria isolated from 80 flies, Salmonella spp. were the most commonly occurring and together with Escherichia coli, Proteus spp. and Klebsiella spp made up 81.4% of total bacteria. Most isolates were resistant to amoxicillin (82.9%) and co-trimoxazole (81.4%), while the least resistance was against ciprofloxacin (6.2%). In total 58 different antibiograms were detected, though nearly 50% of these (29/59) were observed in only a single isolate. This study noted a high degree of MDR (74.4%) among bacterial isolates. In addition to the ability of houseflies to serve as reservoirs for possible bacteria pathogens, this study clearly describes its ability to serve as reservoirs for MDR also. The diversity of bacteria identified points at a possible major public health issue due to the potential difficulty in controlling acquisition of bacteria by flies. Control efforts might therefore need to be more suited to reducing access of these flies to human food and water.
Optimization of 3D bioprinting of human neuroblastoma cells using sodium alginate hydrogel

There are many parameters in extrusion-based three-dimensional (3D) bioprinting of different materials that require fine-tuning to obtain the optimal print resolution and cell viability. To standardize this process, methods such as parameter optimization index (POI) have been introduced. The POI aims at pinpointing the optimal printing speed and pressure to achieve the highest accuracy keeping theoretical shear stress low. Here we applied the POI to optimize the process of 3D bioprinting human neuroblastoma cell-laden 2% sodium alginate (SA) hydrogel using freeform reversible embedding of suspended hydrogels (FRESH). Our results demonstrate a notable difference between optimal parameters for printing 2% SA with and without cells in the hydrogel. We also detected a significant influence of long-term cell culture on the printed constructs. This observation suggests that the POI has to be evaluated in the perspective of the final application. When taking these conditions into consideration, we could define a set of parameters that resulted in good quality prints maintaining high neuroblastoma cell viability (83% viable cells) during 7 days of cell culture using 2% SA and FRESH bioprinting. These results can be further used to manufacture neuroblastoma in vitro 3D culture systems to be used for cancer research.
Elevational richness patterns of sphingid moths support area effects over climatic drivers in a near‐global analysis

AIM: We test hypotheses on the environmental control of elevational richness patterns of sphingid moths for their global applicability and generality. Specifically, we compare effects of area with climate‐related drivers, such as primary productivity and temperature, while also considering direct effects of precipitation. MAJOR TAXA: Sphingid moths (Lepidoptera). LOCATION: Eighty‐six mountain ranges of the Old World and the Australia/Pacific region, from Scandinavia and Siberia through the African and Australasian tropics to South Africa and Southern Australia. METHODS: We used a large compilation of point locality records for 744 species, in addition to fine‐grained range maps derived from species distribution modelling of these records, to characterize the elevational pattern of species richness in 86 custom‐delineated mountain regions. For both types of data, we compared the effects of environmental drivers on richness by comparing standardized coefficients of multivariate models for pooled data after accounting for between‐region variation in richness. RESULTS: We observed varying patterns of elevational richness across the research region, with a higher prevalence of midpeaks in arid regions. We found overwhelming support for area as a main determinant of richness, modulated by temperature and productivity, whereas we detected no effect of precipitation. MAIN CONCLUSIONS: Area, productivity and temperature are the main environmental predictors explaining a large proportion of variability in sphingid richness. This is consistent not only with other elevational studies, but also with empirical and theoretical biodiversity research in a non‐elevational context (with the caveat of some unresolved issues in elevational area effects). However, distinct differences in elevational patterns remain even within the same mountain ranges when comparing with other Lepidoptera, that is, geometrid moths, which highlights the importance of understanding higher clade differentiation in ecological responses, within insects and in other groups.
Accuracy of image analysis tools for functional root traits: A comment on Delory et al. (2017)

Root traits get increasing attention as functional equivalents of above‐ground traits. Image analysis software such as WinRhizo™ and IJ_Rhizo facilitate root trait analyses. Delory et al. ( ) presented a comparison between the accuracy of WinRhizo™ and IJ_Rhizo for measuring root length. We complement their analyses with a comparison of diameter and volume estimates and a comparison of different image resolutions with manual and automatic threshold. We analysed 100 images of fibrous and taproot systems, which were obtained using the root model ArchiSimple. As a result, for each image, diameter, length and volume were known. The images were analysed with WinRhizo™ and IJ_Rhizo and we compared the estimates of diameter, length and volume to ground‐truth values. We further computed relative errors and their magnitude and analysed their dependency on image characteristics and root system properties. At 1,200 and 800 dpi, diameter and length estimates provided by WinRhizo™ and IJ_Rhizo were of comparable accuracy. Diameter errors were balanced. Volume estimates were subjected to a systematic error caused by the assumption of constant diameter. WinRhizo™, however, provides the opportunity to calculate correctly computed volumes from diameter classes. At 1,200 dpi, IJ_Rhizo failed to automatically find an appropriate threshold for pixel classification, which fundamentally decreased accuracy. The magnitude of diameter errors increased with root overlap for IJ_Rhizo. The length errors increased with increasing root length, overlap and root length density for WinRhizo™. The magnitude of underestimation of the volume (WinRhizo™) decreased with volume. It was higher for taproot than for fibrous root systems. All errors increased with lower resolution. Our results confirm the results of Delory et al. ( ) regarding the accuracy for length. They further confirm that estimates derived from different software packages or at different resolution should not be compared directly. The characteristics of root systems should be standardized for image analysis. The dependency of errors on the response variable of interest can influence the effect size and increase the probability of errors. Validation of methods should be conducted for each analysed dataset. New image analysis tools should be validated against a real ground‐truth.
Physical Activity and Sedentary Behavior among Young Adolescents in 68 LMICs, and Their Relationships with National Economic Development

It is unclear whether physical activity and sedentary behavior are associated with economic development in low- and middle-income countries (LMICs). We aimed to assess the association between these two behaviors and country economic development among young adolescents in LMICs. Data came from the Global School-based Student Health Survey (GSHS) conducted between 2009 and 2016 in 68 LMICs. A total of 180,298 adolescents aged 12–15 years were included; 15.3% of young adolescents achieved the recommended level for sufficient physical activity (≥60 min/day of physical activity of any kind per week according to WHO) and 64.6% achieved a low sedentary behavior (≤2 h of sitting activities/day according to some guidelines, not accounting for sitting time at school or for doing homework). However, only 9.1% of young adolescents met the recommended levels of both behaviors. Comparing the lowest to the highest quintiles of a country’s purchasing power parity per capita (PPP), mean values of both physical activity (boys: 2.55 to 2.96 days/week; girls: 2.10 to 2.31 days/week) and sedentary behavior(boys: 1.86 to 3.13 h/day; girls: 1.83 to 3.53 h/day) increased. The prevalence of having both recommended behaviors decreased among boys (12.0% to 10.0%) and girls (9.6% to 4.9%) (p < 0.001). Although there might be an ecological fallacy, the findings emphasize the need for interventions to increase physical activity and reduce sedentary behavior among children and young adolescents.
Enrichment Environment Positively Influences Depression- and Anxiety-Like Behavior in Serotonin Transporter Knockout Rats through the Modulation of Neuroplasticity, Spine, and GABAergic Markers

The serotonin transporter (5-HTT in humans, SERT in rodents) is the main regulator of serotonergic transmission in the brain. The short allelic variant of the 5-HTT gene is in humans associated with psychopathologies and may enhance the vulnerability to develop depression after exposure to stressful events. Interestingly, the short allele also increases the sensitivity to a positive environment, which may buffer the vulnerability to depression. Since this polymorphism does not exist in rodents, male SERT knockout (SERT−/−) rats were tested to explore the molecular mechanisms based on this increased predisposition. This article investigates the influences of a positive manipulation, namely, enriched environment (EE), on the depressive-like behavior observed in SERT−/− rats. We found that one month of EE exposure normalized the anhedonic and anxious-like phenotype characteristics of this animal model. Moreover, we observed that EE exposure also restored the molecular alterations in the prefrontal cortex by positively modulating the expression of the neurotrophin Bdnf, and of spines and gamma-aminobutyric acid (GABA)ergic markers. Overall, our data confirm the depression-like phenotype of SERT−/− rats and highlight the ability of EE to restore behavioral and molecular alterations, thus promoting the opportunity to use EE as a supporting non-pharmacological approach to treat mood disorders.
Monitoring of PM2.5 Concentrations by Learning from Multi-Weather Sensors

This paper aims to monitor the ambient level of particulate matter less than 2.5 μm (PM2.5) by learning from multi-weather sensors. Over the past decade, China has established a high-density network of automatic weather stations. In contrast, the number of PM monitors is much smaller than the number of weather stations. Since the haze process is closely related to the variation of meteorological parameters, it is possible and promising to calculate the concentration of PM2.5 by studying the data from weather sensors. Here, we use three machine learning methods, namely multivariate linear regression, multivariate nonlinear regression, and neural network, in order to monitor PM2.5 by exploring the data of multi-weather sensors. The results show that the multivariate linear regression method has the root mean square error (RMSE) of 24.6756 μg/m3 with a correlation coefficient of 0.6281, by referring to the ground truth of PM2.5 time series data; and the multivariate nonlinear regression method has the RMSE of 24.9191 μg/m3 with a correlation coefficient of 0.6184, while the neural network based method has the best performance, of which the RMSE of PM2.5 estimates is 15.6391 μg/m3 with the correlation coefficient of 0.8701.
Forms and reactions of organic sulfur compounds in soils.

Soil is not just an inert inorganic medium, but a dynamic ecosystem supporting the life of microorganisms, plants, and animals. Due to their requirements for structure and metabolism, Sis continuously being cycled between inorganic and organic forms and as a result, a variety of organic and inorganic compounds is added to or produced in soil. The nature of the compounds formed and the transformations which occur, depend to some extent on the environmental conditions; e.g., the reactions occurring in flooded soils may be different from those operating in upland soils. The main purpose of this chapter is to summarize present knowledge concerning the nature and transformations of organic S in soils and the effect of environmental conditions on them.
Untangling the Factors that Affect Student Retention: A Quantitative Study of the Relationships among First-Year Seminar Program Characteristics and Instructor Type (Full-Time and Part-Time)

i Acknowledgements . iii List of Tables . vii List of Figures . viii Chapter 1: INTRODUCTION.1 Background of the Problem . 2 Statement of Research Problem . 14 Significance of the Problem . 15 Presentation of Methods and Research Question.17 Definition of Terms.18 Conclusion . 24 Chapter 2: REVIEW OF LITERATURE . 25 Current Challenges.27 Theoretical Framework . 31 Review of Research Literature . 47 Conclusion . 66 Chapter 3: METHODS . 69 Purpose of the Study . 69 Research Method . 71 Participants . 71 Research Procedures . 72 Instrument and Measures: Reliability and Validity . 76 Data Analysis . 77 Conclusion . 78 Chapter 4: RESULTS . 79 Data Analysis . 80 Presentation of Results . 81 Conclusion . 106 Chapter 5: CONCLUSION . 108 Synthesis of Findings . 110 Situated in the Larger Context . 117 Limitations . 121 Implications.123 Future Research . 124 Conclusion . 125 vi References . 127 Appendix A: 2009 National Survey on First-Year Seminars. 141 Appendix B: Application for Obtaining Data. 158 Appendix C: Agreement for the Use of Data . 161 Appendix D: Research Proposal Outline for Data Access.166 Appendix E: Security Pledge for Data Access . 168 Appendix F: 2009 Comprehensive Table of all Results . 170 vii List of Tables Table 1. First-Year Seminar Characteristics and Sample Questions . 14 Table 2. Examples of the Institutional Characteristics . 57 Table 3. Examples of the Structural Characteristics . 59 Table 4. First-Year Seminar Program Characteristics and Their Subcategories . 74 Table 5. Significant Results . 82 Table 6. Significant Institutional Characteristics . 83 Table 7. Significant Objective Characteristics.88 Table 8. Significant Structural Characteristics . 94 Table 9. Significant Instructional Characteristics . 105 viii List of Figures Figure 1. Tinto’s Departure Theory . 34 Figure 2. Astin’s Input-Environment-Outputs (I-E-O) Model . 44 Figure 3. Four-Year and Two-Year Institutions . 84 Figure 4. Percentage of First-Year Students’ Enrollment . 85 Figure 5. Number of Years First-Year Seminar was Offered . 85 Figure 6. Required Students to Take First-Year Seminar . 89 Figure 7. Develop Connection with Institution.91 Figure 8. Develop Academic Skills . 91 Figure 9. More Than One First-Year Seminar Type: Which has Highest Enrollment? 97 Figure 10. How is the First-Year Seminar Graded? 99 Figure 11. Does the First-Year Seminar Carry Academic Credit? 99 Figure 12. Dean/Director/Coordinator for the First-Year Seminar? 100 Figure 13. Persistence to Sophomore Year Outcome . 102 Figure 14. Satisfaction with Instructor Outcome . 103 Figure 15. Is Training Required for First-Year Seminar Instructors? 106