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•TrackMate is a software tool for automated, and semi-automated particle tracking.•TrackMate’s major development focus is on usability and extensibility.•TrackMate leverages Fiji to ...help provides its functionality and extensibility.•TrackMate is used for: C. elegans lineaging, NEMO assembly and clathrin dynamics.•Challenging imaging problems can robustly be analyzed using semi-automatic methods.
We present TrackMate, an open source Fiji plugin for the automated, semi-automated, and manual tracking of single-particles. It offers a versatile and modular solution that works out of the box for end users, through a simple and intuitive user interface. It is also easily scriptable and adaptable, operating equally well on 1D over time, 2D over time, 3D over time, or other single and multi-channel image variants. TrackMate provides several visualization and analysis tools that aid in assessing the relevance of results. The utility of TrackMate is further enhanced through its ability to be readily customized to meet specific tracking problems. TrackMate is an extensible platform where developers can easily write their own detection, particle linking, visualization or analysis algorithms within the TrackMate environment. This evolving framework provides researchers with the opportunity to quickly develop and optimize new algorithms based on existing TrackMate modules without the need of having to write de novo user interfaces, including visualization, analysis and exporting tools.
The current capabilities of TrackMate are presented in the context of three different biological problems. First, we perform Caenorhabditis-elegans lineage analysis to assess how light-induced damage during imaging impairs its early development. Our TrackMate-based lineage analysis indicates the lack of a cell-specific light-sensitive mechanism. Second, we investigate the recruitment of NEMO (NF-κB essential modulator) clusters in fibroblasts after stimulation by the cytokine IL-1 and show that photodamage can generate artifacts in the shape of TrackMate characterized movements that confuse motility analysis. Finally, we validate the use of TrackMate for quantitative lifetime analysis of clathrin-mediated endocytosis in plant cells.
Migrant workers, essential work, and COVID‐19 Reid, Alison; Rhonda‐Perez, Elena; Schenker, Marc B.
American journal of industrial medicine,
February 2021, 2021-02-00, 20210201, Letnik:
64, Številka:
2
Journal Article
Recenzirano
Odprti dostop
Globally, migrant and immigrant workers have borne the brunt of the COVID‐19 pandemic as essential workers. They might be a Bulgarian worker at a meat processing plant in Germany, a Central American ...farmworker in the fields of California, or a Filipino worker at an aged‐care facility in Australia. What they have in common is they are all essential workers who have worked throughout the coronavirus pandemic and have been infected with coronavirus at work. COVID‐19 has highlighted the inequitable working conditions of these workers. In many instances, they are employed precariously, and so are ineligible for sick leave or social security, or COVID‐19 special payments. If these are essential workers, they should get at least the same health and safety benefits of all nonessential workers. Improving the working and living conditions of migrant workers can and should be a positive outcome of the coronavirus pandemic.
The achievement gap is a disparity in academic and standardized test performance that exists between White and underrepresented minority (URM) students that begins as early as preschool and worsens ...as students progress through the educational system. Medical education is not immune to this inequality. URM medical students are more likely to experience delayed graduation and course failure, even after accounting for science grade point average and Medical College Admission Test performance. Moreover, URM students are more likely to earn lower scores on licensing examinations, which can have a significant impact on their career trajectory, including specialty choice and residency competitiveness. After the release of preliminary recommendations from the Invitational Conference on USMLE Scoring (InCUS) and public commentary on these recommendations, the National Board of Medical Examiners and Federation of State Medical Boards announced that the United States Medical Licensing Examination (USMLE) Step 1 would transition from a 3-digit numeric score to pass/fail scoring. Given that another of InCUS’s recommendations was to “minimize racial demographic differences that exist in USMLE performance,” it is paramount to consider the impact of this scoring change on URM medical students specifically. Holistic admissions are a step in the right direction of acknowledging that URM students often travel a further distance to reach medical school. However, when residency programs emphasize USMLE performance (or any standardized test score) despite persistent test score gaps, medical education contributes to the disproportionate harm URM students face and bolsters segregation across medical specialties. This Perspective provides a brief explanation of the achievement gap, its psychological consequences, and its consequences in medical education; discusses the potential effect of the Step 1 scoring change on URM medical students; and provides a review of strategies to redress this disparity.
The availability of clinical and therapeutic data drawn from medical records and administrative databases has entailed new opportunities for clinical and epidemiologic research. However, these ...databases present inherent limitations which may render them prone to new biases. We aimed to conduct a structured review of biases specific to observational clinical studies based on secondary databases, and to propose strategies for the mitigation of those biases.
Scoping review of the scientific literature published during the period 2000-2018 through an automated search of MEDLINE, EMBASE and Web of Science, supplemented with manually cross-checking of reference lists. We included opinion essays, methodological reviews, analyses or simulation studies, as well as letters to the editor or retractions, the principal objective of which was to highlight the existence of some type of bias in pharmacoepidemiologic studies using secondary databases.
A total of 117 articles were included. An increasing trend in the number of publications concerning the potential limitations of secondary databases was observed over time and across medical research disciplines. Confounding was the most reported category of bias (63.2% of articles), followed by selection and measurement biases (47.0% and 46.2% respectively). Confounding by indication (32.5%), unmeasured/residual confounding (28.2%), outcome misclassification (28.2%) and "immortal time" bias (25.6%) were the subcategories most frequently mentioned.
Suboptimal use of secondary databases in pharmacoepidemiologic studies has introduced biases in the studies, which may have led to erroneous conclusions. Methods to mitigate biases are available and must be considered in the design, analysis and interpretation phases of studies using these data sources.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Functions to calculate measures of spatial association, especially measures of spatial autocorrelation, have been made available in many software applications. Measures may be global, applying to the ...whole data set under consideration, or local, applying to each observation in the data set. Methods of statistical inference may also be provided, but these will, like the measures themselves, depend on the support of the observations, chosen assumptions, and the way in which spatial association is represented; spatial weights are often used as a representational technique. In addition, assumptions may be made about the underlying mean model, and about error distributions. Different software implementations may choose to expose these choices to the analyst, but the sets of choices available may vary between these implementations, as may default settings. This comparison will consider the implementations of global Moran’s
I
, Getis–Ord
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and Geary’s
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, local
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, available in a range of software including Crimestat, GeoDa, ArcGIS, PySAL and R contributed packages.
OBJECTIVETo assess the rapid implementation of child neurology telehealth outpatient care with the onset of the coronavirus disease 2019 (COVID-19) pandemic in March 2020.
METHODSThis was a cohort ...study with retrospective comparison of 14,780 in-person encounters and 2,589 telehealth encounters, including 2,093 audio-video telemedicine and 496 scheduled telephone encounters, between October 1, 2019 and April 24, 2020. We compared in-person and telehealth encounters for patient demographics and diagnoses. For audio-video telemedicine encounters, we analyzed questionnaire responses addressing provider experience, follow-up plans, technical quality, need for in-person assessment, and parent/caregiver satisfaction. We performed manual reviews of encounters flagged as concerning by providers.
RESULTSThere were no differences in patient age and major ICD-10 codes before and after transition. Clinicians considered telemedicine satisfactory in 93% (1,200 of 1,286) of encounters and suggested telemedicine as a component for follow-up care in 89% (1,144 of 1,286) of encounters. Technical challenges were reported in 40% (519 of 1,314) of encounters. In-person assessment was considered warranted after 5% (65 of 1,285) of encounters. Patients/caregivers indicated interest in telemedicine for future care in 86% (187 of 217) of encounters. Participation in telemedicine encounters compared to telephone encounters was less frequent among patients in racial or ethnic minority groups.
CONCLUSIONSWe effectively converted most of our outpatient care to telehealth encounters, including mostly audio-video telemedicine encounters. Providers rated the vast majority of telemedicine encounters to be satisfactory, and only a small proportion of encounters required short-term in-person follow-up. These findings suggest that telemedicine is feasible and effective for a large proportion of child neurology care. Additional strategies are needed to ensure equitable telemedicine use.
Abstract Objectives Lower socioeconomic status is associated with short or long sleep duration and sleep disturbance (e.g., sleep apnea), which are all related to increased mortality risk. General ...sleep complaints, however, which may better approximate symptoms as they are experienced, have not been examined in a large population sample. Methods Sample consisted of n = 159,856 participants from the Behavioral Risk Factor Surveillance System, representing 36 states/regions across the US. Sleep complaints were measured with a telephone survey item that assessed “trouble falling asleep,” “staying asleep” or “sleeping too much.” Data analysis utilized hierarchical logistic regression and Rao-Schott χ2. Results Asian respondents reported the least complaints, and Hispanic/Latino and Black/African-American individuals reported fewer complaints than Whites. Lower income and educational attainment was associated with more sleep complaints. Employment was associated with less sleep complaints and unemployment with more. Married individuals reported the least sleep complaints. Significant interactions with race/ethnicity indicate that the relationship between sleep complaints and marital status, income and employment differs among groups for men, and the relationship with education differs among groups for women. Conclusions Rates of sleep complaints in African-American, Hispanic/Latino and Asian/Other groups were similar to Whites. Lower socioeconomic status was associated with higher rates of sleep complaint.
This paper presents a new Metropolis-adjusted Langevin algorithm (MALA) that uses convex analysis to simulate efficiently from high-dimensional densities that are log-concave, a class of probability ...distributions that is widely used in modern high-dimensional statistics and data analysis. The method is based on a new first-order approximation for Langevin diffusions that exploits log-concavity to construct Markov chains with favourable convergence properties. This approximation is closely related to Moreau–Yoshida regularisations for convex functions and uses proximity mappings instead of gradient mappings to approximate the continuous-time process. The proposed method complements existing MALA methods in two ways. First, the method is shown to have very robust stability properties and to converge geometrically for many target densities for which other MALA are not geometric, or only if the step size is sufficiently small. Second, the method can be applied to high-dimensional target densities that are not continuously differentiable, a class of distributions that is increasingly used in image processing and machine learning and that is beyond the scope of existing MALA and HMC algorithms. To use this method it is necessary to compute or to approximate efficiently the proximity mappings of the logarithm of the target density. For several popular models, including many Bayesian models used in modern signal and image processing and machine learning, this can be achieved with convex optimisation algorithms and with approximations based on proximal splitting techniques, which can be implemented in parallel. The proposed method is demonstrated on two challenging high-dimensional and non-differentiable models related to image resolution enhancement and low-rank matrix estimation that are not well addressed by existing MCMC methodology.
Fellow involvement in patient care is important for education, but effect on patient care is unclear. Our aim was to compare patient outcomes in gynecologic oncology attending clinics versus a fellow ...training clinic at a large academic medical center.
A retrospective review of consecutive gynecologic oncology patients from six attending clinics and one faculty-supervised fellow clinic was used to analyze differences based on patient demographics, cancer characteristics, and practice patterns. Primary outcome was overall survival (OS); secondary outcomes included recurrence-free survival (RFS), postoperative complications and chemotherapy within the last 30 days of life. Survival analyses were performed using Kaplan-Meier curves with log-rank tests.
Of 159 patients, 76 received care in the attending clinic and 83 in the fellow clinic. Patients in the fellow clinic were younger, less likely to be Caucasian, and more overweight, but cancer site and proportion of advanced stage disease were similar. Both clinics had similar rates of moderate to severe adverse events related to surgery (15% vs. 8%, p = .76), chemotherapy (21% vs. 23%, p = .40), and radiation (14% vs. 17%, p = .73). There was no difference in median RFS in the fellow compared to attending clinic (38 vs. 47 months, p = .78). OS on both univariate (49 months–fellow clinic, 60 months–attending clinic vs. p = .40) and multivariate analysis hazard ratio 1.3 (0.57, 2.75), P = .58 was not significantly different between groups.
A fellow-run gynecologic oncology clinic designed to provide learning opportunities does not compromise patient outcomes and is a safe and feasible option for fellow education.
•A gynecologic oncology fellow-run clinic model allows for graduated autonomy without compromising patient care.•Fellow clinic patients achieved overall and recurrence-free survival that was comparable to patients managed by attendings.•Fellow clinic patients received timely care and had similar rates of surgical, chemotherapy, and radiation adverse events.•Gynecologic oncology fellows prescribed less chemotherapy within the last 30 days of life compared to attendings.
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