Miracle-dz/UniFAR-FTUs huggingface dataset:
The Milestones of Clinical Research for Young Generalist Physicians: Conducting and Publishing Studies

Abstract Clinical physicians have the potential to contribute to the progress of medicine and healthcare through research based on their diagnostic and treatment practices and supported by their educational background. However, in the field of general medicine in Japan, publication of such research in international journals may be limited by challenges in English proficiency and the lack of opportunities to focus on specific research themes amidst the diverse range of diseases treated in clinical practice. Furthermore, novice researchers without prior research experience may lack a comprehensive understanding of the overall research process, including study design and article publication. To address these challenges, we developed a set of 22 milestones that highlight the necessary skills required to conduct and successfully publish clinical research. This guideline will enable novice researchers to identify and address individual barriers to undertaking a research project. These milestones are categorized into five parts: 1) preparing to undertake research; 2) conducting clinical research; 3) writing the article; 4) submitting and achieving acceptance for publication; and 5) advanced skills. For each part, we provide detailed recommendations on the specific steps and methods involved. By working through these 22 milestones, novice researchers can objectively assess their own level of achievement as researchers and continuously clarify the next step of each round of research. Through this set of milestones, we aim to increase the quality and quantity of research publications in general medicine in academic journals, ideally enhancing the overall research process and advancing the field of medicine and healthcare overall.
Preventing recurrence in Sonic Hedgehog Subgroup Medulloblastoma using the OLIG2 inhibitor CT-179

Recurrence is the primary life-threatening complication for medulloblastoma (MB). In Sonic Hedgehog (SHH)-subgroup MB, OLIG2-expressing tumor stem cells drive recurrence. We investigated the anti-tumor potential of the small-molecule OLIG2 inhibitor CT-179, using SHH-MB patient-derived organoids, patient-derived xenograft (PDX) tumors and mice genetically-engineered to develop SHH-MB. CT-179 disrupted OLIG2 dimerization, DNA binding and phosphorylation and altered tumor cell cycle kinetics in vitro and in vivo, increasing differentiation and apoptosis. CT-179 increased survival time in GEMM and PDX models of SHH-MB, and potentiated radiotherapy in both organoid and mouse models, delaying post-radiation recurrence. Single cell transcriptomic studies (scRNA-seq) confirmed that CT-179 increased differentiation and showed that tumors up-regulated Cdk4 post-treatment. Consistent with increased CDK4 mediating CT-179 resistance, CT-179 combined with CDK4/6 inhibitor palbociclib delayed recurrence compared to either single-agent. These data show that targeting treatment-resistant MB stem cell populations by adding the OLIG2 inhibitor CT-179 to initial MB treatment can reduce recurrence.
Predicting AKI in patients with AMI: Development and assessment of a new predictive nomogram

Acute kidney injury (AKI) is a common complication of acute myocardial infarction (AMI) and is associated with both long- and short-term consequences. This study aimed to investigate relevant risk variables and create a nomogram that predicts the probability of AKI in patients with AMI, so that prophylaxis could be initiated as early as possible. Data were gathered from the medical information mart for the intensive care IV database. We included 1520 patients with AMI who were admitted to the coronary care unit or the cardiac vascular intensive care unit. The primary outcome was AKI during hospitalization. Independent risk factors for AKI were identified by applying least absolute shrinkage and selection operator regression models and multivariate logistic regression analyses. A multivariate logistic regression analysis was used to build a predictive model. The discrimination, calibration, and clinical usefulness of the prediction model were assessed using C-index, calibration plot, and decision curve analysis. Internal validation was assessed using bootstrapping validation. Of 1520 patients, 731 (48.09%) developed AKI during hospitalization. Hemoglobin, estimated glomerular filtration rate, sodium, bicarbonate, total bilirubin, age, heart failure, and diabetes were identified as predictive factors for the nomogram construction (P < .01). The model displayed good discrimination, with a C-index of 0.857 (95% CI:0.807–0.907), and good calibration. A high C-index value of 0.847 could still be reached during interval validation. Decision curve analysis showed that the AKI nomogram was clinically useful when the intervention was determined at an AKI possibility threshold of 10%. The nomogram constructed herein can successfully predict the risk of AKI in patients with AMI early and provide critical information that can facilitate prompt and efficient interventions.
Scrolling Through the COVID-19 Pandemic: Exploring the Perceived Effects of Increased Social Media Use on the Mental Health of Undergraduate University Students

Social media has become increasingly integrated into the lives of students for the past decade; however, the public health restrictions associated with the COVID-19 pandemic have led to a sharp increase in social media use in a short period of time. The purpose of this study was to investigate the effects of social media use on university students during the COVID-19 pandemic. Fifteen students from a mid-sized Canadian city were interviewed to share their experiences with social media during the COVID-19 pandemic. Purposive sampling was conducted to gather a diverse sample of participants, including individuals of various ages, gender and sexual identities, and ethnicities. Thematic analysis on the 15 interviews was completed using NVivo (version 12). Participants experienced both advantages and disadvantages associated with social media use. Ease of communication and stress relief were acknowledged as the strongest benefits. Social comparison, loneliness, development of bad habits, and lack of focus were cited as major disadvantages to social media use during the pandemic. Cost–benefit analysis of social media was common, and participants expressed the importance of using social media with moderation, balance, and awareness. Our study indicates that the focus on health with respect to the pandemic should not be solely based on physical health, rather the potential mental health risks associated with social media use during the pandemic should be recognized and addressed by healthcare providers.
Simulation of Debris Flow Deposit in Mt. Umyeon

Debris flow is a representative natural disaster in Korea and occurs frequently every year. Recently, it has caused considerable damage to property and considerable loss of life in both mountainous and urban regions. Therefore, It is necessary to estimate the scope of damage for a large area in order to predict the debris flow. A response model such as the random walk model(RWM) can be used as a useful tool instead of a physics-based numerical model. RWM is a probability model that simplifies both debris flows and sedimentation characteristics as a factor of slopes for a subjective site and represents a relatively simple calculation method compared to other debris flow behavior calculation models. Although RWM can be used to analyzing and predicting the scope of damage caused by a debris flow, input variables for terrain conditions are yet to be determined. In this study, optimal input variables were estimated using DEM generated from the Aerial Photograph and LiDAR data of Mt. Umyeon, Seoul, where a large-scale debris flow occurred in 2011. Further, the deposition volume resulting from the debris flow was predicted using the input variables for a specific area in which the deposition volume could not be calculated because of work restoration and the passage of time even though a debris flow occurred there. The accuracy of the model was verified by comparing the result of predicting the deposition volume in the debris flow with the result obtained from a debris flow behavior analysis model, Debris 2D.
Regular variation in renewal and Markov renewal theory

The first significant result in transient renewal theory in the context of regular variation is due to Cohen and Callaert [1]. Let X1,X2, . '",Xn, be a sequence of ind. i.d. r.v. with common d.f. F(x) on [0,oo), such that F(0+) 0, and let L(t) be slowly varying. Then F(oo) = y and F(oo) F(t) y(l -y)tL(t) as t oo if and only if U(oo)U(t) Ct-L(t). A consequence of this lemma yields a new type of "quasi-limit theorem" for the residual life time
Delayed Rate Monotonic Algorithm with First-fit Partitioning

The problem of scheduling periodic tasks has been studied extensively since its first introduction by Liu and Layland. They proposed utilization bound, called L&L bound, to guaranty feasibility of task set under rate monotonic policy on a single processor. Recently, some papers have used semi-partitioned scheduling to increase overall system utilization. In semi-partitioned scheduling, most tasks are statically assigned to processors, while a few tasks are split into several subtasks and each assigned to a different processor. In this paper a new semi-partitioned scheduling algorithm called FFDRM, which is based on delayed rate monotonic, is proposed for multiprocessor systems by which the system utilization of most of processors is raised up to L&L bound. Delayed rate monotonic is an improved version of rate monotonic. It is proved that the lower bound of feasibility of a system which includes two tasks under delayed rate monotonic is equal to one. FFDRM uses this ability of delayed rate monotonic to achieve higher system utilization than previous works. The feasibility of tasks which are partitioned by FFDRM is formally proved.
Following 4 months of social distancing during COVID-19 Pandemic in Brazil did not change aspects of functioning in children and adolescents with developmental disabilities: A longitudinal study

The COVID-19 pandemic and its demands of social distancing have created challenges in the lives of children/adolescents with developmental disabilities and their families, which would change aspects of children’s functioning. The objetive of this study was to evaluate changes in some components of functioning of children/adolescents with disabilities following 4 months of social distancing during a period of high contamination rate in the year 2020 in Brazil. Participated 81 mothers of children/adolescents with disabilities, 3-17 years, most of them (80%) diagnosed with Down syndrome, cerebral palsy and autism spectrum disorder. Remote assessments of functioning’ aspects including IPAQ, YC-PEM/ PEM-C, Social Support Scale and PedsQL V.4. 0. Wilcoxon tests compared the measures, with significance level <0.05. No significant changes in participant’s functioning were identified. Social adjustments required to facing the pandemic during two points in time in the midst of the pandemic did not change the evaluated aspects of functioning in our sample of Brazilian.
New ACO algorithm for image edge detection

Ant Colony Optimization (ACO) is a metaheuristic based on real behavior of ants to solve optimization problems. Edge detection plays an important role in image processing. It consists in detecting edges or contours in images which allows to extract information from them. An ACO algorithm to edge detection is proposed. Using heuristic and knowledge information and applying an improvement operator, binary images including edges detected are obtained. The algorithm was tested with several images (real and synthetic, with and without presence of noise). The results reached were competitive in terms of quality of images and required computational time.
Average and Heterogeneous Effects of Class Size on Educational Achievement in Lesotho

Understanding class size effects on educational achievement remains a preoccupation of many economists. But empirical results are, to this far, still inconclusive. I use the two-stage least squares and the instrumental variable quantile regression methods on Lesothoâ€™s grade 6 students maths and reading test scores to estimate, respectively, the mean and distributional effects of class size. I find strong evidence for putative class size effects on reading achievement, but not on maths achievement. Using the bounds methods of Conley et al (2012), I show that these findings are robust to weak violations of the instrumental variable exclusion restriction requirement. I also find that a small class size generally benefits the low-ability students the most.
Regional extreme value index estimation and a test of tail homogeneity

This paper deals with inference on extremes of heavy‐tailed distributions. We assume distribution functions F of Pareto‐type, where the right‐tail behavior of F is characterized by a strictly positive parameter γ, the so‐called extreme value index (EVI). In some applications, observations from closely related variables are available, with possibly identical EVI γ. If these variables are observed for the same time period, a procedure called BEAR estimator has recently been proposed. We modify this approach allowing for different observation periods and pairwise extreme value dependence of the variables. In addition, we present a new test for equality of the EVI. As an application, we discuss regional flood frequency analysis, where we want to combine rather short sequences of univariate observations with very different lengths measured at many gauges for joint inference. We illustrate our findings on peak discharges from 18 river gauges located at the Mulde basin in Germany, which is known for its severe summer floods, and identify relevant heterogeneous tail behavior, which is not detected by other popular methods. Copyright © 2015 John Wiley & Sons, Ltd.
On Games with Imperfect Recall and Games with Perfect Recall

In the context of finite extensive form games, we consider games of imperfect and perfect recall. We look briefly at the famous Kuhn theorem. However we are mainly concerned with imperfect recall games in which paths can intersect information sets in more than one node. Explicit examples are given to examine a number of issues. We explain how optimal behaviour strategies are calculated. It is also argued that mixed behavioural strategies cannot always be captured by a behavioural strategy. We are considering the existence of a Nash equilibrium both in the case of mixed and of behavioural strategies. In order to make the discussion possible, starting with the players expected utilities in behavioural strategies in a polynomial form, a precise construction of a game tree is presented. In the case of existence of NE the solutions can imply identical or different pay-off vectors. A reference is also made to the recent discussion on the paradox of the absent-minded driver.
Associations of blood biomarkers with arterial stiffness in patients with diabetes mellitus: A population‐based study

Arterial stiffness contributes to additional cardiovascular risks in diabetic patients by triggering the loss of vascular and myocardial compliance and promoting endothelial dysfunction. Thus, prevention of arterial stiffness is a public health priority, and the identification of potential biomarkers may provide benefits for early prevention. This study investigates the relationships between serum laboratory tests and pulse wave velocity (PWV) tests. We also investigated the associations between PWV and all‐cause mortality.
Feasibility of Reducing Animal Numbers in Radiation Countermeasure Experiments from Historic Levels when using Sample Size Calculations

Historically, animal numbers have most often been in the hundreds for experiments designed to estimate the dose reduction factor (DRF) of a radiation countermeasure treatment compared to a control treatment. Before 2010, researchers had to rely on previous experience, both from others and their own, to determine the number of animals needed for a DRF experiment. In 2010, a formal sample size formula was developed by Kodell et al. This theoretical work showed that sample sizes for realistic, yet hypothetical, DRF experiments could be less than a hundred animals and still have sufficient power to detect clinically meaningful DRF values. However, researchers have been slow to use the formula for their DRF experiments, whether from ignorance to its existence or hesitancy to depart from “tried and true” sample sizes. Here, we adapt the sample size formula to better fit usual DRF experiments, and, importantly, we provide real experimental evidence from two independent DRF experiments that sample sizes smaller than what have typically been used can still statistically detect clinically meaningful DRF values. In addition, we update a literature review of DRF experiments which can be used to inform future DRF experiments, provide answers to questions that researchers have asked when considering sample size calculations rather than solely relying on previous experience, whether their own or others', and, in the supplementary material, provide R code implementing the formula, along with several exercises to familiarize the user with the adapted formula.
Retrospective chart review of patient socioeconomic status and language preference associated with live video telehealth in a pediatric dermatology practice

Pediatric teledermatology rapidly expanded with the COVID‐19 pandemic, and the impacts of this expansion on patients' access to care have not yet been entirely defined. In this retrospective study of 3027 patients in an academic pediatric dermatology practice, patients who identified as having a primary language other than English were less likely to access pediatric dermatology care during the COVID lockdown. This study did not identify a significant or meaningful difference in age, geography, socioeconomic status, ethnicity, or race between patients who were offered pediatric dermatology care that was either in‐person or via synchronous telehealth. These findings are overall reassuring that there were not major disparities in telehealth utilization during the COVID shelter‐in‐place mandate, although highlight the need for institutions to ensure systems are in place to enhance telehealth access for patients with non‐English primary language.
Closed Form Expressions for Processes after the Initial Stage of the One-Step Outflow Method

The one-step outflow process was numerically analyzed for a soil in which water diffusivity was an exponential function of volumetric water content especially for durations after the initial stage. 1) The soil water diffusivity ratio was well expressed with a one-term power function of distance from the open end. The power was greater than 2 in the initial stage, came down to 2.00 quickly and was maintained at this value throughout the middle stage, and then gradually decreased to 1.75 during the final stage. 2) The reciprocal of the soil water diffusivity at the open end was almost a linear function of time during the middle stage. 3) The time course of the cumulative volume outflow was expressed parametrically with two algebraic functions of the open end water diffusivity ratio. 4) The equilibrium soil water content can be estimated from the outflow data with the algebraic functions.
Universal features of particle motion in ac electric fields

Mobile particles present as contaminants in high voltage gas insulated switchgear (GIS) may constitute a risk for insulation failure. The understanding of their motion in the electric field of the insulation gap is therefore essential for quality control in manufacturing, commissioning and in service monitoring. Published research on particle motion in ac electric fields has shown that this rather complex process depends on numerous parameters, many of which remain unknown under practical conditions. This renders modelling, generalization of experimental data and practical application difficult. The scope of this paper therefore is to develop a unified description of particle motion which minimizes the number of controlling parameters, enables the comparison of experimental data and allows simple interpretation relations to be derived. This is achieved by making the controlling equations dimensionless with an appropriate choice of reference values and by using simplifying assumptions for the specific conditions prevailing in GIS. The resulting generalized description of the process can then be summarized in the form of 2D patterns (dynamic maps). Approximate scaling relations are derived between specific features of these patterns and particle-related parameters. A reference case is discussed in detail. The non-linear character of the equation of motion suggests that the particle motion may be a deterministic process with chaotic features. This is confirmed by a preliminary chaos-theoretical analysis of the process.
The sorting platform in the type III secretion pathway: From assembly to function

The type III secretion system (T3SS) is a specialized nanomachine that enables bacteria to secrete proteins in a specific order and directly deliver a specific set of them, collectively known as effectors, into eukaryotic organisms. The core structure of the T3SS is a syringe‐like apparatus composed of multiple building blocks, including both membrane‐associated and soluble proteins. The cytosolic components organize together in a chamber‐like structure known as the sorting platform (SP), responsible for recruiting, sorting, and initiating the substrates destined to engage this secretion pathway. In this article, we provide an overview of recent findings on the SP's structure and function, with a particular focus on its assembly pathway. Furthermore, we discuss the molecular mechanisms behind the recruitment and hierarchical sorting of substrates by this cytosolic complex. Overall, the T3SS is a highly specialized and complex system that requires precise coordination to function properly. A deeper understanding of how the SP orchestrates T3S could enhance our comprehension of this complex nanomachine, which is central to the host‐pathogen interface, and could aid in the development of novel strategies to fight bacterial infections.
Prevalence of juvenile systemic lupus erythematosus in Colombia: An approach from the national health registry data

Background Systemic lupus erythematosus (SLE) is a chronic, systemic, autoimmune disease of multifactorial origin. There are no previous studies in Colombia describing juvenile SLE (jSLE) prevalence, prompting this demographic description. Objective This study aimed for prevalence calculation and epidemiologic analysis of jSLE) in Colombian patients, ages 0–19, from 2015 to 2019. Methods This descriptive, cross-sectional study searched the Colombian Ministry of Health database for codes of the International Classification of Diseases, 10th revision (ICD-10) associated with jSLE to estimate the disease prevalence for the total population and for specific age groups at national and regional levels. Calculations used intercensal estimates of population based on the projections of the national statistics administrative department (DANE) from the most recent census. This paper presents a sociodemographic analysis of patients with jSLE. Results The study identified in Colombia, from 2015 to 2019, 3680 cases with jSLE as the principal diagnosis. Calculated prevalence of jSLE was 25 cases per 100,000 population, with highest frequency in ages 15–19 and females (84%), with a female:male ratio of 5.1:1. Conclusion Estimated prevalence of jSLE in Colombia is at the highest limit of worldwide findings. Consistent with reports in the literature, the disease involves females more frequently than males.