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We propose a survey of the research contributions on the field of Educational Timetabling with a specific focus on "standard" formulations and the corresponding benchmark instances. We identify six of such formulations and we discuss their features, pointing out their relevance and usability. Other available formulations and datasets are also reviewed and briefly discussed. Subsequently, we report the main state-of-the-art results on the selected benchmarks, in terms of solution quality (upper and lower bounds), search techniques, running times, statistical distributions, and other side settings.

OBJECTIVE: To assess the reproducibility of peripapillary, optic nerve head (ONH-PP) and macular vessel density (VD) by Spectral Domain optical coherence tomography angiography (SD OCT-A) in glaucoma patients and healthy subjects. METHODS: Cross-sectional study assessing 63 eyes of 63 subjects, including 33 glaucoma patients and 30 healthy subjects. Glaucoma was classified in mild, moderate, or advanced. Two consecutive scans were acquired by Spectralis Module OCT-A (Heidelberg, Germany), and provided images of the superficial vascular complex (SVC), nerve fiber layer vascular plexus (NFLVP), superficial vascular plexus (SVP); deep vascular complex (DVC), intermediate capillary plexus (ICP) and deep capillary plexus (DCP). VD (%) was calculated by AngioTool. Intraclass correlation coefficients (ICCs) and coefficients of variation (CV) were calculated. RESULTS: Among ONH-PP VD, better ICC presented advanced (0.83-0.97) and moderate glaucoma (0.86-0.96) compared with mild glaucoma (0.64-0.86). For the macular VD reproducibility, ICC results for superficial retinal layers were better for mild glaucoma (0.94-0.96) followed by moderated (0.88-0.93) and advanced glaucoma (0.85-0.91), and for deeper retinal layers ICC was better for moderate glaucoma (0.96-0.95) followed by advanced (0.80-0.86) and mild glaucoma (0.74-0.91). CVs ranged from 2.2% to 10.94%. Among healthy subjects, ICCs for the ONH-PP VD measurements (0.91-0.99) and for the macular VD measurements (0.93-0.97) were excellent in all layers, with CVs from 1.65% to 10.33%. CONCLUSIONS: SD OCT-A used to quantify macular and ONH-PP VD showed excellent and good reproducibility in most layers of the retina, both in healthy subjects and in glaucoma patients regardless of the severity of the disease.

Total marrow (lymph node) irradiation (TMI/TMLI) delivery requires more time than standard radiotherapy treatments. The patient’s extremities, through the joints, can experience large movements. The reproducibility of TMI/TMLI patients’ extremities was evaluated to find the best positioning and reduce unwanted movements. Eighty TMI/TMLI patients were selected (2013–2022). During treatment, a cone-beam computed tomography (CBCT) was performed for each isocenter to reposition the patient. CBCT-CT pairs were evaluated considering: (i) online vector shift (OVS) that matched the two series; (ii) residual vector shift (RVS) to reposition the patient’s extremities; (iii) qualitative agreement (range 1–5). Patients were subdivided into (i) arms either leaning on the frame or above the body; (ii) with or without a personal cushion for foot positioning. The Mann-Whitney test was considered (p < 0.05 significant). Six-hundred-twenty-nine CBCTs were analyzed. The median OVS was 4.0 mm, with only 1.6% of cases ranked < 3, and 24% of RVS > 10 mm. Arms leaning on the frame had significantly smaller RVS than above the body (median: 8.0 mm/6.0 mm, p < 0.05). Using a personal cushion for the feet significantly improved the RVS than without cushions (median: 8.5 mm/1.8 mm, p < 0.01). The role and experience of the radiotherapy team are fundamental to optimizing the TMI/TMLI patient setup.

Introduction: Since the eight edition of the Union for In-ternational Cancer Control and American Joint Committee on Cancer TNM classification system, the primary tumor pT stage is determined on the basis of presence and size of the invasive components. The aim of this study was to identify histologic features in tumors with lepidic growth pattern which may be used to establish criteria for distinguishing invasive from noninvasive areas.Methods: A Delphi approach was used with two rounds of blinded anonymized analysis of resected nonmucinous lung adenocarcinoma cases with presumed invasive and nonin-vasive components, followed by one round of reviewer de-anonymized and unblinded review of cases with known outcomes. A digital pathology platform was used for measuring total tumor size and invasive tumor size. Results: The mean coefficient of variation for measuring total tumor size and tumor invasive size was 6.9% (range: 1.7%-22.3%) and 54% (range: 14.7%-155%), respectively, with substantial variations in interpretation of the size and location of invasion among pathologists. Following the presentation of the results and further discussion among members at large of the International Association for the Study of Lung Cancer Pathology Committee, extensive epithelial proliferation (EEP) in areas of collapsed lepidic growth pattern is recognized as a feature likely to be associated with invasive growth. The EEP is characterized by multilayered luminal epithelial cell growth, usually with high-grade cytologic features in several alveolar spaces.Conclusions: Collapsed alveoli and transition zones with EEP were identified by the Delphi process as morphologic features that were a source of interobserver variability. Definition criteria for collapse and EEP are proposed to improve reproducibility of invasion measurement.(c) 2022 International Association for the Study of Lung Cancer.

Information on the dimensional changes in maxillary and mandibular dentures made by using computer-aided design and computer-aided manufacturing (CAD-CAM) techniques under uniform testing conditions is lacking.The purpose of this in vitro study was to evaluate the dimensional changes and reproducibility of maxillary and mandibular dentures by using CAD-CAM-milled and 3D-printed techniques.Maxillary and mandibular edentulous models with wax occlusal rims were scanned, and dentures were designed by using a CAD software program and fabricated by using 2 techniques and materials: CAD-CAM-milled (CCM) and 3D-printed (3DP). The 3DP fabrications included 4 subgroups: dentures printed with a 90-degree build angle with UV light polymerization on the reference model (3DP 90M), dentures printed with a 90-degree build angle and light polymerization without the reference model (3DP 90), dentures printed with a 45-degree build angle with light polymerization on the reference model (3DP 45M), and dentures printed with a 45-degree build angle and light polymerization without the reference model (3DP 45). The preprocessing and postprocessing scan files of each denture produced by CCM and 3DP were superimposed by using a surface matching software program. Ten points each on maxillary and mandibular dentures were measured for deviations after processing. Additionally, for each denture, the widths were measured between the canines and molars, the anteroposterior plane from cusp tips between the canines and molars, and the vertical plane from the cusp tip of the canines to the marginal gingiva. They were then compared with those in the denture design CAD cast. The Kruskal-Wallis analysis of variance test was used for statistical analyses (α=.05).According to digital superimposition, CCM had the smallest values of deviation with no statistical difference (P.05), indicating more uniform results from measurement points in both maxillary and mandibular dentures, followed by 3DP 90M, 3DP 90, 3DP 45M, and 3DP 45. Regarding the width measurements, CCM had the smallest values of deviation (P.05). In 3DP, smaller deviation values were observed at the vertical plane from the tip of the canine to the marginal gingiva, and larger values were observed in the intermolar width (P.05).CCM exhibited smaller dimensional changes and better reproducibility among the tested techniques. In 3DP, the build angle and methods of light postprocessing influenced the dimensional stability. The 90-degree build angle with additional light polymerization on the cast improved the dimensional deviations.

The study aimed to evaluate relative validity and reproducibility of seven WHO indicators of dietary practices in children aged 6-23.9 months. Data from probabilistic sample of children who used primary healthcare services in Rio de Janeiro, Brazil were collected using a 24h dietary recall (24HR) and a closed questionnaire (Q1) on feeding in the day before the study. The last one was reapplied (Q2) around 16 days later. Validity was assessed by comparing the prevalence rates estimated by 24HR and Q1 and calculating the positive (PPV) and negative (NPV) predictive values, sensitivity (Se), specificity (Sp), and accuracy index (AI) for the resulting indicators. For reproducibility, estimated prevalence rates based on Q1 and Q2 were compared and the kappa index and prevalence-adjusted bias-adjusted kappa were estimated. Of the seven estimated indicators, the prevalence of two was overestimated (Continued breastfeeding: 50.0% vs 40.0%; Sweet beverage consumption: 65.1% vs 52.7%) and the prevalence of one was underestimated (Zero vegetable or fruit consumption: 6.5% vs 18.1%). For most indicators, Se and PPV were higher than Sp and NPV. The prevalence rates determined with Q1 and Q2 were similar for 6 indicators. More than half showed good, very good or excellent agreement. Resumo O estudo avaliou a validade relativa e a reprodutibilidade de sete indicadores da OMS sobre alimentação de crianças de 6-23,9 meses. Dados de amostra probabilística de usuários de serviços básicos de saúde na cidade do Rio de Janeiro, Brasil, foram coletados por meio de recordatório alimentar de 24 horas (R24h) e questionário fechado (Q1) sobre alimentação no dia anterior ao estudo. Este último foi reaplicado (Q2) em torno de 16 dias depois. A validade foi avaliada comparando-se as prevalências estimadas pelo R24h e Q1 e calculando-se os valores preditivos positivo (VPP) e negativo (VPN), sensibilidade (Se), especificidade (Esp) e índice de acurácia (IA) dos indicadores resultantes. Para reprodutibilidade, as prevalências estimadas com base em Q1 e Q2 foram comparadas e estimados o índice kappa e o kappa ajustado pela prevalência. Dos sete indicadores estimados, houve superestimação da prevalência de dois (aleitamento continuado: 50,0% versus 40,0%; consumo de bebidas adoçadas: 65,1% vs. 52,7%) e subestimação da prevalência de um (não consumo de frutas e hortaliças: 6,5% vs. 18,1%). Para a maioria deles, Se e VPP foram maiores do que Esp e VPN. As prevalências determinadas com Q1 e Q2 foram semelhantes para seis indicadores. Mais da metade dos indicadores apresentaram concordância boa, muito boa ou excelente.

The verification of analytical methods is a requirement of the standard NF EN ISO 15 189. It consists of evaluating the performance of an analytical method according to a well-defined protocol and then comparing it with pre-established analytical objectives. The mastery of this approach must be the concern of any biologist. Through this work we present the results of the protocol of verification of the method of determination of microalbumin by comparing two automats: Alinity ci®and Architect ci-8200®Abbott. Microalbumin monitoring in urine is an important element in the treatment of diabetes mellitus types I and II. It can also be used to predict diabetic nephropathy, which is the leading cause of death in people with insulin-dependent diabetes.

International audience; Molecular biology amplification enables sensitive detection of most respiratory viruses through nasopharyngeal swabbing. We developed an innovative approach to detect viral genomes on used facial tissues. In 2 communities of children, used tissues were collected once weekly for 1 year. Pooled analysis of tissues enabled detection of successive virus circulation in 4 age groups over time and forecasted by several weeks the circulation of influenza in the general population. At the individual level, in a proof-of-concept study of 30 volunteers with influenza-like signs/symptoms, we identified common respiratory viruses. The signals for SARS-CoV-2 obtained in parallel from 15 facial tissues and swab samples were similar and often higher for the tissues (11/15). Individual analysis of tissues offers a noninvasive, sensitive, and affordable alternative to self-sampling without a medical care requirement. Pooled analyses may be used to detect virus spread in specific communities, predict seasonal epidemics, and alert the population to viral infections. © 2023 Centers for Disease Control and Prevention (CDC). All rights reserved.

International audience; Reducing the energy consumption of the global IT industry requires one to understand and optimize the large software infrastructures the modern data economy relies on. Among them are the data stream processing systems that are deployed in cloud data centers by companies, such as Twitter, to process billion of events per day in real time. However, studying the energy consumption of such infrastructures is difficult because they rely on a complex virtualized software ecosystem where attributing energy consumption to individual software components is a challenge, and because the space of possible configurations is large. We present GreenFlow, a principled methodology and tool designed to automate the deployment of energy measurement experiments for data stream processing systems in cloud environments. GreenFlow is designed to deliver reproducible results while remaining flexible enough to support a wide range of experiments. We illustrate its usage and show in particular that consolidating a DSP system in the smallest number of servers that are capable of processing it is an effective way to reduce energy consumption.

Relevant to co-clinical trials, the goal of this work was to assess repeatability, reproducibility, and bias of the apparent diffusion coefficient (ADC) for preclinical MRIs using standardized procedures for comparison to performance of clinical MRIs. A temperature-controlled phantom provided an absolute reference standard to measure spatial uniformity of these performance metrics. Seven institutions participated in the study, wherein diffusion-weighted imaging (DWI) data were acquired over multiple days on 10 preclinical scanners, from 3 vendors, at 6 field strengths. Centralized versus site-based analysis was compared to illustrate incremental variance due to processing workflow. At magnet isocenter, short-term (intra-exam) and long-term (multiday) repeatability were excellent at within-system coefficient of variance, wCV [±CI] = 0.73% [0.54%, 1.12%] and 1.26% [0.94%, 1.89%], respectively. The cross-system reproducibility coefficient, RDC [±CI] = 0.188 [0.129, 0.343] µm2/ms, corresponded to 17% [12%, 31%] relative to the reference standard. Absolute bias at isocenter was low (within 4%) for 8 of 10 systems, whereas two high-bias (>10%) scanners were primary contributors to the relatively high RDC. Significant additional variance (>2%) due to site-specific analysis was observed for 2 of 10 systems. Base-level technical bias, repeatability, reproducibility, and spatial uniformity patterns were consistent with human MRIs (scaled for bore size). Well-calibrated preclinical MRI systems are capable of highly repeatable and reproducible ADC measurements.

Background Experienced assessors show good intra-rater reproducibility (within-session and between-session agreement and reliability) when using an algometer to determine pressure pain thresholds (PPT). However, it is unknown whether novice assessors perform equally well. This study aimed to determine within and between-session agreement and reliability of PPT measurements performed by novice assessors and explored whether these parameters differed per assessor and algometer type. Methods Ten novice assessors measured PPTs over four test locations (tibialis anterior muscle, rectus femoris muscle, extensor carpi radialis brevis muscle and paraspinal muscles C5-C6) in 178 healthy participants, using either a Somedic Type II digital algometer (10 raters; 88 participants) or a Wagner Force Ten FDX 25 digital algometer (nine raters; 90 participants). Prior to the experiment, the novice assessors practiced PPTs for 3 h per algometer. Each assessor measured a different subsample of ~9 participants. For both the individual assessor and for all assessors combined (i.e., the group representing novice assessors), the standard error of measurement (SEM) and coefficient of variation (CV) were calculated to reflect within and between-session agreement. Reliability was assessed using intraclass correlation coefficients (ICC1,1). Results Within-session agreement expressed as SEM ranged from 42 to 74 kPa, depending on the test location and device. Between-session agreement, expressed as SEM, ranged from 36 to 76 kPa and the CV ranged from 9–16% per body location. Individual assessors differed from the mean group results, ranging from −55 to +32 kPa or from −9.5 to +6.6 percentage points. Reliability was good to excellent (ICC1,1: 0.87 to 0.95). Results were similar for both types of algometers. Conclusions Following 3 h of algometer practice, there were slight differences between assessors, but reproducibility in determining PPTs was overall good.

The prenatal environment may program health and disease susceptibility via epigenetic mechanisms. We evaluated associations of maternal trimester-specific intake of micronutrients with global DNA methylation (%5mC) and 5-hydroxymethylation (%5hmC) at birth in cord blood and tested for persistence into childhood. We quantified global %5mC and %5hmC in cord blood cells (n= 434) and in leukocytes collected in early (n= 108) and mid-childhood (n= 390) from children in Project Viva, a pre-birth cohort from Boston, MA. Validated food frequency questionnaires estimated maternal first- and second-trimester intakes of vitamin B2, vitamin B6, vitamin B12, folate, betaine, choline, methionine, iron, and zinc. Mean (SD) cord blood %5mC and %5hmC was 5.62% (2.04) and 0.25% (0.15), respectively. Each μg increase in first-trimester B12intake was associated with 0.002 lower %5hmC in cord blood (95% CI: −0.005, −0.0003), and this association persisted in early childhood (β= −0.007; 95% CI: −0.01, −0.001) but not mid-childhood. Second-trimester iron (mg) was associated with 0.01 lower %5mC (95% CI: −0.02, −0.002) and 0.001 lower %5hmC (95% CI: −0.01, −0.00001) in cord blood only. Increased second-trimester zinc (mg) intake was associated with 0.003 greater %5hmC in early childhood (β= 0.003; 95% CI: 0.0004, 0.006). Second-trimester folate was positively associated with %5hmC in early childhood only (β= 0.08, 95% CI: 0.003, 0.16). Associations did not survive multiple testing adjustment; future replication is needed. Trimester-specific nutrients may impact various sensitive windows of epigenetic programming some with lasting effects in childhood. Further research is needed to understand the role of gene-specific epigenetic changes and how global DNA methylation measures relate to child health.

Background: Concerns over scientific reproducibility have grown in recent years, leading the National Institutes of Health (NIH) to require researchers to address these issues in research grant applications. Starting in 2020, training grants were required to provide a plan for educating trainees in rigor and reproducibility. Academic medical centers have responded with different solutions to fill this educational need. As experienced instructors with expertise in topics relating to reproducibility, librarians can play a prominent role in providing trainings, classes, and events to educate investigators and trainees, and bolstering reproducibility in their communities. Case Presentations: This special report summarizes efforts at five institutions to provide education in reproducibility to biomedical and life sciences researchers. Our goal is to expand awareness of the range of approaches in providing reproducibility services in libraries. Conclusions: Reproducibility education by medical librarians can take many forms. These specific programs in reproducibility education build upon libraries’ existing collaborations, with funder mandates providing a major impetus. Collaborator needs shaped the exact type of educational or other reproducibility support and combined with each library’s strengths to yield a diversity of offerings based on capacity and interest. As demand for and complexity of reproducibility education increases due to new institutional and funder mandates, reproducibility education will merit special attention.

© The Author(s) 2022 The sports statistics community is rapidly evolving. R is an open-source software in constant development that has gained a lot of popularity within statistical communities and sports analytics. This work presents a systematic review of the available R CRAN sport packages following PRISMA guidelines. We consider all packages active as of 18 February 2021. A total of 81 sport R packages created since 2006 were detected. Of these, 35.9% were authored by an American national, 69.1% include a dataset, 43.2% provide vignettes, and 65.4% have been updated at least once. The sport with the highest representation is basketball (n¿=¿14, 17.3%), followed by soccer (n¿=¿12, 14.8%) and packages related to physical activity (n¿=¿11, 13.6%). There are no sports packages directed solely for the female gender, while 59.3% of packages are focused on professional athletes. Fifty packages (61.7%) are related to the sports performance analysis category, and web scraping (n¿=¿43, 53.1%) was the main functionality in the collected packages. The creation of new R packages in the area of sports could help solve questions and tasks that still remain a challenge in this field, while continuing to help to improve the level of statistical education and computational thinking skills. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by the Ministerio de Ciencia e Innovación (Spain) (PID2019-104830RB-I00) and the Departament d’Economia i Coneixement de la Generalitat de Catalunya (Spain) (2017 SGR 622 (GRBIO)).

Artificial intelligence (AI) will change the face of nuclear medicine and molecular imaging as it will in everyday life. In this review, we focus on the potential applications of AI in the field, both from a physical (radiomics, underlying statistics, image reconstruction and data analysis) and a clinical (neurology, cardiology, oncology) perspective. Challenges for transferability from research to clinical practice are being discussed as is the concept of explainable AI. Finally, we focus on the fields where challenges should be set out to introduce AI in the field of nuclear medicine and molecular imaging in a reliable manner.

In the last decade, industry’s demand for deep learning (DL) has increased due to its high performance in complex scenarios. Due to the DL method’s complexity, experts and non-experts rely on blackbox software packages such as Tensorflow and Pytorch. The frameworks are constantly improving, and new versions are released frequently. As a natural process in software development, the released versions contain improvements/changes in the methods and their implementation. Moreover, versions may be bug-polluted, leading to the model performance decreasing or stopping the model from working. The aforementioned changes in implementation can lead to variance in obtained results. This work investigates the effect of implementation changes in different major releases of these frameworks on the model performance. We perform our study using a variety of standard datasets. Our study shows that users should consider that changing the framework version can affect the model performance. Moreover, they should consider the possibility of a bug-polluted version before starting to debug source code that had an excellent performance before a version change. This also shows the importance of using virtual environments, such as Docker, when delivering a software product to clients.

Biomedical science is rapidly developing in terms of more transparency, openness and reproducibility of scientific publications. This is even more important for all studies that are based on results from basic semen examination. Recently two concordant documents have been published: the 6th edition of the WHO Laboratory Manual for the Examination and Processing of Human Semen, and the International Standard ISO 23162:2021. With these tools, we propose that authors should be instructed to follow these laboratory methods in order to publish studies in peer-reviewed journals, preferable by using a checklist as suggested in an Appendix to this article.

Using a database of open data policies for 199 journals in ecology and evolution, we found no detectable link between data sharing requirements and article retractions or corrections. Despite the potential for open data to facilitate error detection, poorly archived datasets, the absence of open code and the stigma associated with correcting or retracting articles probably stymie error correction. Requiring code alongside data and destigmatizing error correction among authors and journal editors could increase the effectiveness of open data policies at helping science self-correct.

This study aimed to assess the validity and reliability of the Turkish version of the Women’s Perception of Respectful Maternity Care Scale. This methodological, cross-sectional study was conducted between December 2020 and July 2021. The sample of the study consisted of 259 women who had vaginal birth and gave birth to a healthy baby with normal birth weight. Data analysis and evaluation were performed using factor analysis, Cronbach’s alpha, split-half, item-total score correlation, Hotelling T2, Tukey’s test and ceiling and floor effect of the scale. The scale consists of 19 items and three sub-dimensions. The scales explained 76.04 percent of the total variance. In both exploratory and confirmatory factor tests, the overall factor loading was greater than 0.30. In the confirmatory factor analysis, all the goodness-of-fit indexes were greater than 0.90, and the root mean square error of approximation was less than 0.08. The Cronbach’s alpha coefficient of the scale was 0.96, with Cronbach’s alpha values ranging between 0.88 and 0.95 for the subscales. In conclusion, this scale can be used by nurses, midwives and other health professionals as a valid and reliable measurement tool to evaluate women’s perception of respectful maternity care. © 2022 Taylor & Francis Group, LLC.

International audience; Data sharing is gradually becoming a requirement across all fields of science, owing to its key benefits in verifying the reproducibility of findings and reusing existent data for new purposes. Although meta-research studies are complex, time-consuming and hinge on the availability of data produced and curated by others, there has been little focus on how they make their own data available. This is in stark contrast with the heightened attention data sharing has received in clinical research. Yet, as secondary data users par excellence, meta-researchers are ethically bound to both improving and evaluating data sharing practices, as well as correctly sharing their own data. We contrast particularities of data sharing in meta-research and clinical research, such as benefits, barriers, inadequate and potentially pervasive sharing practices. We conclude with an array of concrete and tailored recommendations for improvement.

PURPOSE: To evaluate the association between rates of choroidal microvasculature dropout (MvD) change and rates of circumpapillary retinal nerve fiber layer (cpRNFL) loss in primary open-angle glaucoma (POAG) eyes. DESIGN: Cohort study from clinical trial data METHODS: A total of 91 eyes of 68 POAG patients with and without localized MvD at baseline with at least 4 visits and 2 years follow-up with optical coherence tomography angiography (OCT-A) and OCT scans were included. Area and angular circumference of MvD were evaluated on OCT-A en-face and B-scan choroidal vessel density images during the follow-up period. Joint longitudinal mixed effects models were used to estimate the rates of change in MvD area or angular circumference and RNFL thickness. Univariable and multivariable regressions were completed to identify the factors contributing to cpRNFL thinning. RESULTS: MvD was identified in 53 (58.2%) eyes at baseline. Seventeen eyes (18.6%) eyes that did not show MvD at baseline developed it over the follow-up period. Over a mean follow-up of 4.0 years, the mean rates of change of MvD area and angular circumference (95%CI) were 0.05 (0.04, 0.06) mm2/year, and 13.2 (10.7, 15.8) degree/year, respectively. In multivariable models, the rate of cpRNFL thinning was significantly associated with the rates of change of MvD area and angular circumference (P=0.008 and P=0.009, respectively). CONCLUSIONS: Rates of MvD area and angular circumference change over time were associated with concurrent rates of cpRNFL loss in POAG eyes.

PURPOSE: To evaluate the association between rates of choroidal microvasculature dropout (MvD) change and rates of circumpapillary retinal nerve fiber layer (cpRNFL) loss in primary open-angle glaucoma (POAG) eyes.DESIGN: Cohort study from clinical trial data METHODS: A total of 91 eyes of 68 POAG patients with and without localized MvD at baseline with at least 4 visits and 2 years follow-up with optical coherence tomography angiography (OCT-A) and OCT scans were included. Area and angular circumference of MvD were evaluated on OCT-A en-face and B-scan choroidal vessel density images during the follow-up period. Joint longitudinal mixed effects models were used to estimate the rates of change in MvD area or angular circumference and RNFL thickness. Univariable and multivariable regressions were completed to identify the factors contributing to cpRNFL thinning.RESULTS: MvD was identified in 53 (58.2%) eyes at baseline. Seventeen eyes (18.6%) eyes that did not show MvD at baseline developed it over the follow-up period. Over a mean follow-up of 4.0 years, the mean rates of change of MvD area and angular circumference (95%CI) were 0.05 (0.04, 0.06) mm2/year, and 13.2 (10.7, 15.8) degree/year, respectively. In multivariable models, the rate of cpRNFL thinning was significantly associated with the rates of change of MvD area and angular circumference (P=0.008 and P=0.009, respectively).CONCLUSIONS: Rates of MvD area and angular circumference change over time were associated with concurrent rates of cpRNFL loss in POAG eyes.

A crucial asset in the management of invasive species is the open-access sharing of data on the range of invaders and the progression of their spread. Such data should be current, comprehensive, consistent, and standardized, to support reproducible and comparable forecasting efforts among multiple researchers and managers. Here, we present thelydemaprR package containing spatiotemporal data and mapping functions to visualize the current spread of the spotted lanternfly (Lycorma delicatula, White 1841) in the Western Hemisphere. The spotted lanternfly is a forest and agricultural pest in the eastern Mid-Atlantic region of the U.S., where it was first discovered in 2014. As of 2022, it has been found in 12 states according to state and federal departments of agriculture. However, the lack of easily accessible, fine-scale data on its spread hampers research and management efforts. We obtained multiple memoranda-of-understanding from several agencies and citizen-science projects, gaining access to their internal data on spotted lanternfly point observations. We then cleaned, harmonized, anonymized, and combined the individual data sources into a single comprehensive dataset. The resulting dataset contains spatial data gridded at the 1 km2resolution, with yearly information on the presence/absence of spotted lanternflies, establishment status, and population density across 658,392 observations. Thelydemaprpackage will aid researchers, managers, and the public in their understanding, modeling, and managing of the spread of this invasive pest.

While the calls for reproduction studies in Computational Literary Studies (CLS) have become louder, practical aspects, especially the interplay of the components involved in the research process (code, data, environments, infrastructures, etc.) proves to be a hurdle for reproducing research. We present a way to fully reproducible research using a Docker-based approach: We exemplarily implemented it for a network-analytic study on a corpus of about 3,000 theater plays derived from the DraCor project. We demonstrate that the use of highly portable, self-contained digital artifacts (Docker images) containing runnable research environments not only allow for a full reproduction of the study, but also offer ways to implement different scenarios of repeating research (e.g. same code, different data).

Across the past decade, open science has increased in momentum, making research more openly available and reproducible. Educational data mining, as a subfield of education technology, has been expanding in scope as well, developing and providing better understanding of large amount of data within education. However, open science and educational data mining do not often intersect, causing a bit of difficulty when trying to reuse methodologies, datasets, analyses for replication, reproduction, or an entirely separate end goal. In this tutorial, we will provide an overview of open science principles and their benefits and mitigation within research. In the second part of this tutorial, we will provide an example on using the Open Science Framework to make, collaborate, and share projects. The final part of this tutorial will go over some mitigation strategies when releasing datasets and materials such that other researchers may easily reproduce them. Participants in this tutorial will gain a better understanding of open science, how it is used, and how to apply it themselves.

Despite increased efforts to assess the adoption rates of open science and robustness of reproducibility in sub-disciplines of education technology, there is a lack of understanding of why some research is not reproducible. Prior work has taken the first step toward assessing reproducibility of research, but has assumed certain constraints which hinder its discovery. Thus, the purpose of this study was to replicate previous work on papers within the proceedings of the International Conference on Educational Data Mining to accurately report on which papers are reproducible and why. Specifically, we examined 208 papers, attempted to reproduce them, documented reasons for reproducibility failures, and asked authors to provide additional information needed to reproduce their study. Our results showed that out of 12 papers that were potentially reproducible, only one successfully reproduced all analyses, and another two reproduced most of the analyses. The most common failure for reproducibility was failure to mention libraries needed, followed by non-seeded randomness.

We present a detailed and actionable guide on creating a replication package, relying on our expertise as data editors of leading journals.

The key scientific output of the EATRIS-Plus project is to develop a Multi-omic Toolbox available for researchers in order to have a better understanding of the molecular profiles in personalised medicine. Within work packages 1, 2, and 3, we implement practices based on the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles to ensure reproducibility of our work and to make the multi-omics cohort data reusable for future translational research. The aim of this deliverable (D2.2) is to describe methods developed and applied to the Czech multi-omics cohort 1 that can improve comparability of data when integrating omics data from different sources. Integration of omics data from different sources can be challenging when data and data processing steps are not sufficiently annotated, or sources of biological and technical variation are unknown. The Czech multi-omics demonstrator cohort serves as a demonstrator for the development and application of computational workflows for omics preprocessing and integrative analyses. &nbsp

The FAIR-IMPACT Guidelines for recommended metadata standards for research software within the EOSC present the first proposal of the Research Software MetaData (RSMD) Guidelines, developed by Task 4.3 (T4.3), Standard metadata for research software, as part of Work Package 4, Metadata and ontologies, in the FAIR-IMPACT project. FAIR-IMPACT aims to realize a FAIR (Findable, Accessible, Interoperable, and Reusable) European Open Science Cloud (EOSC) by leveraging community guidelines and existing infrastructures in the scholarly ecosystem. The growing recognition of software's crucial role in research has led to initiatives, infrastructures and research institutions to address the challenges of software findability, accessibility, attribution and reuse. One of these initiatives, the Scholarly Infrastructures for Research Software (SIRS) Task Force (TF), identified in its report (EOSC Executive Board & EOSC Secretariat, 2020) the general need for actionable, standardized guidelines for researchers/developers that self-archive software or submit software for publication. The FAIR-IMPACT project acknowledged the rising need for establishing software metadata guidelines to effectively collect and curate metadata. In response, T4.3’s deliverable provides a comprehensive set of Research Software MetaData (RSMD) Guidelines that offer flexible and adaptable recommendations for end-users that can be used in different disciplines and different software development contexts. This deliverable summarizes a large review and analysis including: a thorough introduction of the goals, methodology and use cases; the state of the art of existing practices and guidelines and the metadata landscape. Following the first introduction and state of the art, T4.3 introduces the RSMD guidelines proposal to collect and curate research software metadata. These guidelines are directly addressed to end users, including software creators and curators in their quest to improve the FAIRness of their software. Lastly, T4.3 will continue its efforts to make the RSMD guidelines normative within the academic community. This includes engaging with stakeholders, gathering feedback, and incorporating best practices and advancements in metadata management within existing infrastructures. By establishing these guidelines as a norm, the aim is to promote widespread adoption and adherence, leading to greater standardization and harmonization of metadata practices across research domains. The ongoing commitment of T4.3 to refining and promoting the RSMD guidelines will contribute to the overall advancement of open and FAIR research practices in the research software community. The purpose of this deliverable in general and of the RSMD guidelines in particular is to provide a concrete and practical resource to support researchers in their endeavors to share and publish their research software creations.

While the calls for reproduction studies in Computational Literary Studies (CLS) have become louder, practical aspects, especially the interplay of the components involved in the research process (code, data, environments, infrastructures, etc.) proves to be a hurdle for reproducing research. We present a way to fully reproducible research using a Docker-based approach: We exemplarily implemented it for a network-analytic study on a corpus of about 3,000 theater plays derived from the DraCor project. We demonstrate that the use of highly portable, self-contained digital artifacts (Docker images) containing runnable research environments not only allow for a full reproduction of the study, but also offer ways to implement different scenarios of repeating research (e.g. same code, different data).

Presentation highlighting Open Science principles and how can we adapt them in quantitative/wet lab research projects and using existing resources. Mainly based on materials from The Turing Way

To determine consistent change over time in keratoconus disease, it is necessary to establish progression cut-off values based on intersession variability of the device used to monitor the cornea. The aim of this study was to analyze the accuracy of corneal parameters using Scheimpflug tomography and anterior segment optical coherence tomography in healthy and keratoconic eyes of varying severity to determine the cut-off values that indicate real progression. Three repeated measurements of each cornea of healthy (20 eyes) and keratoconic eyes (mild = 16, moderate = 25 and severe = 20) were recorded using Pentacam and Casia SS-1000 devices, which were repeated 2–3 weeks later. K1, K2, maximal anterior and posterior keratometry, and corneal thickness at the thinnest location (TCT) were collected. The accuracy was excellent with both devices; however, the Casia device presented better repeatability and reproducibility in all parameters in all groups compared to the Pentacam. The cut-off of the Pentacam and Casia in the mild stage were lower (K1 = 0.50 and 0.37 D; K2 = 0.51 and 0.37 D; Kmax-A = 1.24 and 0.65 D; Kmax-P = 0.38 and 0.17 D; TCT = 19.64 and 11.19 µm) than that of the severe stage (K1 = 1.09 and 0.88 D; K2 = 1.41 and 0.87 D; Kmax-A = 2.74 and 2.15 D; Kmax-P = 0.82 and 0.22 D; TCT = 28.68 and 14.83 µm). These results show that the greater the keratoconus severity, the greater the change that must occur for it to be considered real.

This deliverable reflects the data management activities of the TIER2 project. TIER2 emphasises on next-level reproducibility tools, practices & policies across diverse epistemic contexts to increase trust, integrity, & efficiency in research. In this context, TIER2 will itself adhere to radical reproducibility & transparency to ensure best practices, including adherence to Horizon Europe requirements on Research Data Management & Open Science. At the meta-level, the DMP of the project will progressively incorporate elements of reproducible research to realise a prototype of a new concept towards "Reproducibility Management Plans (RMPs)". This enhancement will be equally supported by the development of the Reproducibility Management Plan tool that is expected to be completed at the course of the project's lifetime.

This deliverable reflects the data management activities of the TIER2 project. TIER2 emphasises on next-level reproducibility tools, practices & policies across diverse epistemic contexts to increase trust, integrity, & efficiency in research. In this context, TIER2 will itself adhere to radical reproducibility & transparency to ensure best practices, including adherence to Horizon Europe requirements on Research Data Management & Open Science. At the meta-level, the DMP of the project will progressively incorporate elements of reproducible research to realise a prototype of a new concept towards "Reproducibility Management Plans (RMPs)". This enhancement will be equally supported by the development of the Reproducibility Management Plan tool that is expected to be completed at the course of the project's lifetime.

The keynote presentation from the 1st ACM conference on reproducibility and replicability (ACM REP'23) Please don't hesitate to provide your feedback via the public Discord serverfrom the MLCommons Task Force on Automation and Reproducibility and GitHub issues. [ GitHub project] [ Public Collective Knowledge repository ] [ Related reproducibility initiatives ] [ cTuning.org ] [ cKnowledge.org ] During the past 10 years, we have considerably improved the reproducibility of experimental results from published papers by introducing the artifact evaluation process with a unified artifact appendix and reproducibility checklists, Jupyter notebooks, containers, and Git repositories. On the other hand, our experience reproducing more than 200 papers shows that it can take weeks and months of painful and repetitive interactions between teams to reproduce artifacts. This effort includes decrypting numerous README files, examining ad-hoc artifacts and containers, and figuring out how to reproduce computational results. Furthermore, snapshot containers pose a challenge to optimize algorithms’ performance, accuracy, power consumption and operational costs across diverse and rapidly evolving software, hardware, and data used in the real world. In this talk, Iexplain how our practical artifact evaluation experience and the feedback from researchers and evaluators motivated us to develop a simple, intuitive, technology agnostic, and English-like scripting language called Collective Mind (CM). It helps to automatically adapt any given experiment to any software, hardware, and data while automatically generating unified README files and synthesizing modular containers with a unified API. It is being developed by MLCommons to facilitate reproducible AI/ML Systems research and minimizing manual and repetitive benchmarking and optimization efforts, reduce time and costs for reproducible research, and simplify technology transfer to production. I also present several recent use cases of how CM helps MLCommons, the Student Cluster Competition, and artifact evaluation at ACM/IEEE conferences. I conclude with our development plans, new challenges, possible solutions, and upcoming reproducibility and optimization challenges powered by the MLCommons Collective Knowledge platform and CM:access.cKnowledge.org.

Obtaining a relevant dataset is central to conducting empirical studies in software engineering. However, in the context of mining software repositories, the lack of appropriate tooling for large scale mining tasks hinders the creation of new datasets. Moreover, limitations related to data sources that change over time (e.g., code bases) and the lack of documentation of extraction processes make it difficult to reproduce datasets over time. This threatens the quality and reproducibility of empirical studies. In this paper, we propose a tool-supported approach facilitating the creation of large tailored datasets while ensuring their reproducibility. We leveraged all the sources feeding the Software Heritage append-only archive which are accessible through a unified programming interface to outline a reproducible and generic extraction process. We propose a way to define a unique fingerprint to characterize a dataset which, when provided to the extraction process, ensures that the same dataset will be extracted. We demonstrate the feasibility of our approach by implementing a prototype. We show how it can help reduce the limitations researchers face when creating or reproducing datasets.

Radiomics involves the extraction of information from medical images that are not visible to the human eye. There is evidence that these features can be used for treatment stratification and outcome prediction. However, there is much discussion about the reproducibility of results between different studies. This paper studies the reproducibility of CT texture features used in radiomics, comparing two feature extraction implementations, namely the MATLAB toolkit and Pyradiomics, when applied to independent datasets of CT scans of patients: (i) the open access RIDER dataset containing a set of repeat CT scans taken 15 min apart for 31 patients (RIDER Scan 1 and Scan 2, respectively) treated for lung cancer; and (ii) the open access HN1 dataset containing 137 patients treated for head and neck cancer. Gross tumor volume (GTV), manually outlined by an experienced observer available on both datasets, was used. The 43 common radiomics features available in MATLAB and Pyradiomics were calculated using two intensity-level quantization methods with and without an intensity threshold. Cases were ranked for each feature for all combinations of quantization parameters, and the Spearman’s rank coefficient, rs, calculated. Reproducibility was defined when a highly correlated feature in the RIDER dataset also correlated highly in the HN1 dataset, and vice versa. A total of 29 out of the 43 reported stable features were found to be highly reproducible between MATLAB and Pyradiomics implementations, having a consistently high correlation in rank ordering for RIDER Scan 1 and RIDER Scan 2 (rs > 0.8). 18/43 reported features were common in the RIDER and HN1 datasets, suggesting they may be agnostic to disease site. Useful radiomics features should be selected based on reproducibility. This study identified a set of features that meet this requirement and validated the methodology for evaluating reproducibility between datasets.

This presentation explains the Reproducibility Package and its use for computational research.

In research fields with complex scientific and technical infrastructures that generate large volumes of research data, Artificial Intelligence (AI) and Machine Learning (ML) methods are ubiquitous and hold promising possibilities to reuse these unique data treasures. In this endeavour, it is ever more important that these methods are trustworthy and reliable. This includes transparency and openness of the infrastructure, tools, workflows, and resources that are used to enable (computational) reproducibility of research results. Research is reproducible when sufficient detail (about data, code, software, hardware, and implementation details) is provided to run the analysis again, re-creating the results. This is a key quality indicator in research, which is also in line with established principles of good scientific practice. In Data Science, reproducibility is an important requirement for the integrity of model results and building of trust towards the overwhelming expansion of AI systems applications. However, the field of Machine Learning (e.g. Large Language Models and others) experiences what is called a reproducibility crisis and it is difficult to reproduce important results. Experience reports refer to many publications as being not replicable, being statistically insignificant, or suffering from narrative fallacy. The endeavour of Open Science, of making scientific outputs as easily accessible as possible for everyone, closely links to the reproducibility of research. The application of open and reproducible practices in ML research has the potential to promote responsible use of AI by openly describing the procedures and applications, thus promoting the overall integrity of the scientific output and applications. Open and reproducible practices are therefore essential pillars of the democratization of AI sciences. This presentation focuses on Open Science practices to improve reproducibility at Helmholtz and highlight its importance for robust, reproducible and trustworthy research in ML.

Ein Datenmanagementplan (DMP) ist für jedes Forschungsprojekt von entscheidender Bedeutung. Er hilft unter anderem Forschungsdaten effektiv zu organisieren, das Risiko des Datenverlusts zu minimieren und den Anforderungen von Förderorganisationen gerecht zu werden. In diesem Beitrag erfahren Sie, wie Sie einen umfassenden Plan erstellen können, der Ihre spezifischen Anforderungen erfüllt. Dazu stellen wir die wichtigsten Bestandteile eines DMPs, Best Practices und Hilfsmittel wie den Research Data Management Organiser (RDMO) vor. Die dreitägige HeFDI Data Week ermöglicht es Forschenden, Lehrenden und allen weiteren Interessierten, Themen und Angebote des Forschungsdatenmanagements kennenzulernen und zu erproben. Darüber hinaus werden den Teilnehmenden Daten- und Coding-Kompetenzen vermittelt sowie Dienste und Angebote verschiedener hessischer Infrastruktur-Einrichtungen und Zentren vorgestellt., Die HeFDI Data Week ist ein Angebot der Landesinitiative HeFDI - Hessische Forschungsdateninfrastrukturen, welche vom Hessischen Ministerium für Wissenschaft und Kunst (HMWK) finanziert wird.

The project aims to support the modern scientific values, including, but not limited to, universalism and communality. The project aims to rause awareness of important statistical concepts including p-value and false positive, and the connection of these concepts with certain negative trends in research publication like publication bias and specification searching. The project also aims to promote the importance of robustness and reproducibility for scientific research., https://github.com/anafinovas/Raising-awareness-about-Open-Science-movement-in-Central-Asia, {"references":["Acharya, A. (2004). How ideas spread: Whose norms matter? Norm localization and institutional change in Asian regionalism. International organization, 58(2), 239-275.","Christensen, G., Freese, J., & Miguel, E. (2019). Transparent and reproducible social science research: How to do open science. University of California Press."]}

Metabolomics is a powerful tool that can provide a comprehensive insight into the complexity of human biology and the pathophysiology of diseases. By analyzing the metabolome, which refers to the complete set of small (endogenous) molecules (with a mass

To determine the short-term intra-operator precision and inter-operator repeatability of radiofrequency echographic multi-spectrometry (REMS) at the lumbar spine (LS) and proximal femur (FEM). All patients underwent an ultrasound scan of the LS and FEM. Both precision and repeatability, expressed as root-mean-square coefficient of variation (RMS-CV) and least significant change (LSC) were obtained using data from two consecutive REMS acquisitions by the same operator or two different operators, respectively. The precision was also assessed in the cohort stratified according to BMI classification. The mean (±SD) age of our subjects was 48.9 ± 6.8 for LS and 48.3 ± 6.1 for FEM. Precision was assessed on 42 subjects at LS and 37 subjects on FEM. Mean (±SD) BMI was 24.71 ± 4.2 for LS and 25.0 ± 4.84 for FEM. Respectively, the intra-operator precision error (RMS-CV) and LSC resulted in 0.47% and 1.29% at the spine and 0.32% and 0.89% at the proximal femur evaluation. The inter-operator variability investigated at the LS yielded an RMS-CV error of 0.55% and LSC of 1.52%, whereas for the FEM, the RMS-CV was 0.51% and the LSC was 1.40%. Similar values were found when subjects were divided into BMI subgroups. REMS technique provides a precise estimation of the US-BMD independent of subjects’ BMI differences.

The paper presents the results of tensile adhesion strength measurements of ceramic tile adhesive (CTA) stored in various conditions performed by ten operators in one laboratory using the same equipment and auxiliary materials. The obtained results allowed the authors to estimate the repeatability and reproducibility of the tensile adhesion strength measurement method using the methodology following ISO 5725-2:1994+AC1:2002. Standard deviations of repeatability ranging from 0.09 to 0.15 for the general means value in the range of 0.89–1.76 MPa and standard deviations of reproducibility ranging from 0.14 to 0.21 for the same general means content indicate that the accuracy of tensile adhesion strength measurement method is not high enough. From the group of ten operators, five perform tensile adhesion strength measurements daily, the remaining five perform other measures, and the results obtained by professionals and non-professionals showed no significant differences. In light of the obtained results, compliance assessment with this method with the criteria set out in the harmonized standard EN 12004:2007+A1:2012 carried out by different operators may be divergent, and there is a significant risk of incorrect assessments. This risk is additionally increasing in the case of the evaluation conducted by market surveillance authorities, which use the simple acceptance rule that does not consider measurement variability.

The "How to Document Your Research Data" poster series provides a comprehensive overview of essential documentation practices for research data. Created with the goal of promoting transparency and reproducibility, these posters highlight key aspects of data documentation and guide researchers in effectively managing their data throughout the research lifecycle. The posters cover Electronic Laboratory Notebooks (ELNs), Codebooks, Model Cards for Machine Learning and Artificial Intelligence models, Datasheets for Machine Learning datasets, Data Nutrition Labels for Artificial Intelligence datasets, and Readme Files. Each poster provides insights into the background, functions, and essential components of these documentation tools. The posters can be used by scientists looking for the right documentation tool for their research project and by research data management support services at research institutions providing information about documentation in trainings and consultations., It is recommended to print the posters on DinA0., {"references":["Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, and Timnit Gebru (2019) Model cards for model reporting. In Proceedings of the Conference on Fairness, Accountability, and Transparency. 220–229. https://dl.acm.org/doi/pdf/10.1145/3287560.3287596","Sarah Holland, Ahmed Hosny, Sarah Newman, Joshua Joseph, and Kasia Chmielinski (2018) The Dataset Nutrition Label: A Framework To Drive Higher Data Quality Standards. https://doi.org/10.48550/arXiv.1805.03677","Briney, Kristin A.(2022). Documentation methods for research data. https://resolver.caltech.edu/CaltechAUTHORS:20221121-220219246","Dryad. Good data practices. https://datadryad.org/stash/best_practices#describe","Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé, and Kate Crawford (2018). Datasheets for Datasets. http://arxiv.org/abs/1803.09010","DataWiz Knowledge Base. Codebooks. https://datawizkb.leibniz-psychology.org/index.php/during-data-collection/what-should-i-know-about-codebooks/","Finnish Social Science Data Archive. Descriptive metadata in DDI format. https://www.fsd.tuni.fi/en/services/depositing-data/ddi/","Biernacka, Katarzyna, Buchholz, Petra, Danker, Sarah Ann, Dolzycka, Dominika, Engelhardt, Claudia, Helbig, Kerstin, Jacob, Juliane, Neumann, Janna, Odebrecht, Carolin, Petersen, Britta, Slowig, Benjamin, Trautwein-Bruns, Ute, Wiljes, Cord, & Wuttke, Ulrike (in preparation). Train-the-Trainer-Konzept zum Thema Forschungsdatenmanagement (version 5)"]}

L’étude de la production du photographe suisse Gaston de Jongh montre combien les années 1930 sont une période charnière de l'histoire de la photographie en couleurs. À cette époque, scientifiques, photographes et imprimeurs travaillent en étroite collaboration à la recherche d'un procédé accessible et de haute qualité, alors que ‒ entre l’ère de l’Autochrome et celle du Kodachrome ‒ aucune technique ne s’impose. Une attention particulière sera portée au rôle joué par la publicité comme moteur de cette recherche. The study of the Swiss professional photographer Gaston de Jongh’s production shows that the 1930s were a pivotal period in the history of colour photography. At that time, scientists, photographers and printers were working closely in the search for a high‑quality and accessible colour process, while ‒ between the Autochrome and the Kodachrome eras ‒ no process seemed to establish itself. Particular attention will be paid to the role of advertising as a driving force behind this technical advancement.

International audience; Reproducibility is a cornerstone of science, as the replication of findings is the process through which they become knowledge. It is widely considered that many fields of science are undergoing a reproducibility crisis. This has led to the publications of various guidelines in order to improve research reproducibility. This didactic chapter intends at being an introduction to reproducibility for researchers in the field of machine learning for medical imaging. We first distinguish between different types of reproducibility. For each of them, we aim at defining it, at describing the requirements to achieve it and at discussing its utility. The chapter ends with a discussion on the benefits of reproducibility and with a plea for a non-dogmatic approach to this concept and its implementation in research practice.

Recent years have seen exciting progress across human embryo research, including new methods for culturing embryos, transcriptional profiling of embryogenesis and gastrulation, mapping lineage trajectories, and experimenting on stem cell-based embryo models. These advances are beginning to define the dynamical principles of development across stages, tissues and organs, enabling a better understanding of human development before birth in health and disease, and potentially leading to improved treatments for infertility and developmental disorders. However, there are still significant roadblocks en route to this goal. Here, we highlight technical challenges to studying early human development and propose ways and means to overcome some of these constraints.