Red Squares Research Articles

Effect of the number and diversity of visual stimuli on the reproduction of short time intervals.

Presenting more items within a space makes the space look and feel bigger. Presenting more tones within a time interval makes the interval seem longer. Does presenting more visual items also make a time interval seem longer? Does it matter what these items are? A series of 2-4 images were presented sequentially on a screen. Participants had to press the spacebar to indicate either the interval between the first and the last item or the intervals between all items. The first and last items were red squares with onset asynchronies of 700, 900, or 1,100 ms. We found that the times between key presses were longer when additional items had different shapes and colors than when they were also red squares. With only red squares, the time may even decrease with the number of items. Whether one had to tap for all targets or only the first and the last hardly mattered.

Color appearance of spatial patterns compared by direct estimation and conjoint measurement.

Perceptual scales of color saturation obtained by direct estimation (DE) and maximum likelihood conjoint measurement (MLCM) were compared for red checkerboard patterns and uniform red squares. For the DE task, observers were asked to rate the saturation level as a percentage, indicating the chromatic sensation for each pattern and contrast. For the MLCM procedure, observers judged on each trial which of two stimuli that varied in chromatic contrast and/or spatial pattern evoked the most salient color. In separate experiments, patterns varying only in luminance contrast were also tested. The MLCM data confirmed previous results reported with DE indicating that the slope of the checkerboard scale with cone contrast levels is steeper than that for the uniform square. Similar results were obtained with patterns modulated only in luminance. DE methods were relatively more variable within an observer, reflecting observer uncertainty, while MLCM scales showed greater relative variability across observers, perhaps reflecting individual differences in the appearance of the stimuli. MLCM provides a reliable scaling method, based only on ordinal judgments between pairs of stimuli and that provides less opportunity for subject-specific biases and strategies to intervene in perceptual judgements.

Heart Rate Complexity and Autonomic Modulation Are Associated with Psychological Response Inhibition in Healthy Subjects

the ability to suppress/regulate impulsive reactions has been identified as common factor underlying the performance in all executive function tasks. We analyzed the HRV signals (power of high (HF) and low (LF) frequency, Sample Entropy (SampEn), and Complexity Index (CI)) during the execution of cognitive tests to assess flexibility, inhibition abilities, and rule learning. we enrolled thirty-six healthy subjects, recording five minutes of resting state and two tasks of increasing complexity based on 220 visual stimuli with 12 × 12 cm red and white squares on a black background. at baseline, CI was negatively correlated with age, and LF was negatively correlated with SampEn. In Task 1, the CI and LF/HF were negatively correlated with errors. In Task 2, the reaction time positively correlated with the CI and the LF/HF ratio errors. Using a binary logistic regression model, age, CI, and LF/HF ratio classified performance groups with a sensitivity and specificity of 73 and 71%, respectively. this study performed an important initial exploration in defining the complex relationship between CI, sympathovagal balance, and age in regulating impulsive reactions during cognitive tests. Our approach could be applied in assessing cognitive decline, providing additional information on the brain-heart interaction.

The Social Movement Archive

The Social Movement Archive

Utility of multimodal imaging in the detection and follow-up of retinal astrocytic hamartomas in a young girl with tuberous sclerosis complex.

Retinal astrocytic hamartomas (RAH) are one of the major diagnostic criteria for tuberous sclerosis complex (TSC) and is conventionally detected by ophthalmoscopy. We describe the utility of multimodal imaging (MMI) with spectral domain optical coherence tomography (SDOCT) and multicolor imaging (MCI) in the detection of hamartomas which may be missed clinically, especially in pediatric patients who may not be able to cooperate for detailed fundus examination. We also present some novel imaging findings which helped to understand the evolution of these lesions. A 5-year-old girl with tuberous sclerosis complex (TSC) was subjected to retinal evaluation and MMI. Fundus examination showed subtle elevation superotemporal to the disc in the right eye (RE) and a circular greyish lesion overlying superotemporal arcade in the left eye (LE) [Fig. 1a, b]. Corresponding OCT showed dome-shaped elevation of the nerve fiber layer (NFL), confirming the lesions as RAH [Fig. 1c, d]. MCI with its component blue and green reflectance (BR, GR) well delineated these superficial lesions with uniform hyporeflectivity. MCI supported by OCT revealed additional lesions in both eyes which were not visible clinically. Right eye was found to have a well-defined superficial lesion along the inferotemporal arcade with minimal elevation of the NFL and intact outer retina on OCT [Fig. 2a]. LE had two small deep lesions, one superiorly and another temporally, with minimal or no elevation of the NFL, outer retinal collapse and ellipsoid zone loss on OCT [Fig. 2b, c]. On BR and GR, superficial lesion in the RE had hyporeflectance [Fig. 3a, b], whereas the deep lesions in the LE were hyperreflective with central hyporeflectance [Fig. 4a]. At review six months later, the temporal lesion in the LE showed an additional hyporeflective outer rim [Fig. 4b]. OCT was unchanged at follow-up.Figure 1: Colour fundus photo (CP) and optical coherence tomography (OCT) of both eyes: CP (a and b) showed retinal astrocytic hamartomas superior to the disc in the right eye (RE) and over the superotemporal arcade in the left eye (LE). OCT through the lesions showed dome-shaped elevation of the nerve fiber layer with back-shadowing in RE (c) and a hyporeflective cavitation in LE (d)Figure 2: Multicolor imaging (MCI) with (OCT) of both eyes: MCI demonstrated additional lesions in both eyes (arrow). On OCT, superficial lesion in the RE (a) showed elevation of the nerve fiber layer with intact outer retina, whereas deeper lesions in the LE (b and c) showed predominant changes in the outer retina with outer retinal collapse and ellipsoid zone loss (arrowheads)Figure 3: Blue (a) and green (b) reflectance (BR, GR) of the right eye: A well-delineated elevated lesion with uniform hyporeflectivity was noted over the temporal vessels (arrow). The confocal high-resolution BR and GR imaging with superior contrast enabled improved detection of the inner retinal lesion which was missed on ophthalmoscopy and colour fundus photographyFigure 4: Blue and green reflectance (BR and GR) of the left eye: At presentation, BR and GR of the deep lesions showed hyperreflectivity with central hyporeflectance (a, white squares). At six months follow-up, the superior lesion remained stable while the temporal lesion showed an additional hyporeflective outer rim in a characteristic Bull’s eye configuration (b, red squares)Discussion OCT features of RAH are well described and improves the detection of these lesions.[1234] A majority of RAH remain stable, but can rarely regress spontaneously.[5] MCI with its component BR and GR is an additional tool to detect and monitor these lesions. We report novel findings on MMI in RAH and correlate lesion characteristics with the evolution of the lesion. We assumed superficial RAH with elevation of NFL on OCT to be active lesions. The deep RAH with predominant changes in the outer retina and progressive changes on BR and GR may be regressing lesions and may require MMI for detection. While BR and GR showed progressive changes on follow-up, OCT features remained stable, thereby indicating that MCI may be more sensitive to monitor the course of RAH in TSC. Although RAH indicates tumor-like growth in inner retinal layers which usually remain constant, the use of BR and GR with OCT could aid in diagnosis and follow-up of RAH. Declaration of patient consent The authors certify that they have obtained all appropriate patient consent forms. In the form the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.

A Smart Molecule Showing Spin Crossover Responsive Aggregation-Induced Emission

A Smart Molecule Showing Spin Crossover Responsive Aggregation-Induced Emission

Inhibition of BMP signaling with LDN 193189 can influence bone marrow stromal cell fate but does not prevent hypertrophy during chondrogenesis.

SummaryBone morphogenetic protein (BMP) cascades are upregulated during bone marrow-derived stromal cell (BMSC) chondrogenesis, contributing to hypertrophy and preventing effective BMSC-mediated cartilage repair. Previous work demonstrated that a proprietary BMP inhibitor prevented BMSC hypertrophy, yielding stable cartilage tissue. Because of the significant therapeutic potential of a molecule capable of hypertrophy blockade, we evaluated the capacity of a commercially available BMP type I receptor inhibitor with similar properties, LDN 193189, to prevent BMSC hypertrophy. Using 14-day microtissue chondrogenic induction cultures we found that LDN 193189 permitted BMSC chondrogenesis but did not prevent hypertrophy. LDN 193189 was sufficiently potent to counter mineralization and adipogenesis in response to exogenous BMP-2 in osteogenic induction cultures. LDN 193189 did not modify BMSC behavior in adipogenic induction cultures. Although LDN 193189 is effective in countering BMP signaling in a manner that influences BMSC fate, this blockade is insufficient to prevent hypertrophy.

Abstract 10881: Graph-Based Analysis of Cardiomyocyte Network Connectivity

Introduction: Cardiomyocytes branch and interconnect with one another, allowing for mechanical and electrochemical coupling. Despite being an essential structural feature enabling coordinated contraction, analysis of this branching structure has been limited. Herein, we use graph-based methods to analyze the cardiomyocyte network structure. Hypothesis: Cardiomyocytes are fully-connected, rather than being bundled into discrete, tract-bundles. We therefore expect that the size of connected graph components will increase with graph size, rather than tending towards a constant tract-bundle size. Methods: Rodent myocardium (n = 4) was stained for collagen and imaged using extended volume confocal microscopy. A sheetlet portion was segmented (~150 cells). The centerline of each cardiomyocyte was tracked. Vertices were identified where the cell bodies of adjacent cardiomyocytes merged. From the connected network (Fig 1A), an adjacency matrix was determined and the shortest-paths between all vertices calculated. The largest component was recorded as a function of graph size. Simulated fully-connected and tract-bundle networks (Fig 1B) were then compared to cardiomyocyte networks (Fig 1C). Results: For the simulated fully-connected network, the largest component increased with graph size, while the tract-bundle network levelled-off based on tract size (Fig 1B). In the cardiomyocyte networks (Fig 1C, red squares), the largest component continued to increase with graph size. Myocardial connectivity appears to lie between a tract-bundle and fully-connected simulated networks (Fig 1C). This suggests that the myocardium tends towards being a fully-connected network, although confirmation requires a larger image volume. Conclusion: Graph-based analysis of cardiomyocyte network structure distinguished between simulated fully-connected and tract-bundle networks. Cardiomyocyte networks are more similar to the fully-connected networks.

Bariatric surgery on obese walking: mass(ive) changes akin to load carrying and hypogravity for normal-weight adults.

Bariatric surgery on obese walking: mass(ive) changes akin to load carrying and hypogravity for normal-weight adults.

The homeschooling timetable blanket

The homeschooling timetable blanket is a visualization of the 8 weeks that I spent supporting my 13-year-old son with home learning during January and February 2021. Each multi-colored crochet “granny” square represents 1 day of schooling. The red squares are weekend days, and the lime green ones are half-term holidays. Each treble crochet row within the multi-colored squares represents a 1 h lesson and is color coded per subject, e.g., red for science, yellow for history, burnt umber for PE, and so on.

Thermoelectric materials with crystal-amorphicity duality induced by large atomic size mismatch

Summary Discovering novel materials and attaining higher performance are the eternal pursuit of thermoelectric materials research. Here, we report a material series, (Cu1−xAgx)2(Te1−ySy) (0.16 ≤ x ≤ 0.24, 0.16 ≤ y ≤ 0.24), which adopts a complex orthorhombic structure differing from any known crystal structure of (Cu/Ag)2(S/Te). This material series is featured by the crystal-amorphicity duality induced by the large anionic size mismatch: a crystalline sublattice of highly size-mismatched anions Te/S coexists with an amorphous-like sublattice of cations Cu/Ag. In the context of structure-property correlation, the crystal-amorphicity duality gave rise to not only interesting electrical properties but also exceptionally low lattice thermal conductivities from 300 to 1,000 K. A state-of-the-art figure of merit zT of 2.0 is obtained in the x = y = 0.22 sample at 1,000 K. These results give insights into crystal-amorphicity duality as a paradigm-shifting materials design approach to develop high-performance thermoelectric materials.

PH Overpotential for Unveiling the pH Gradient Effect of H + /OH − Transport in Electrode Reaction Kinetics

pH Overpotential for Unveiling the pH Gradient Effect of H ⁺ /OH ⁻ Transport in Electrode Reaction Kinetics

Sex differences in deterioration of sleep properties associated with aging: a 12-year longitudinal cohort study.

The sleep patterns of humans are greatly influenced by age and sex and have various effects on overall health as they change continuously during the lifespan. We investigated age-dependent changes in sleep properties and their relation to sex in middle-aged individuals. We analyzed data from 2,640 participants (mean age of 49.8 ± 6.8 years at baseline, 50.6% women) in the Korean Genome and Epidemiology Study, which assessed sleep habits using the Pittsburgh Sleep Quality Index and other clinical characteristics. We analyzed the sleep habit changes that occurred between baseline and a follow-up point (mean interval: 12.00 ± 0.16 years). Associations of age and sex with 9 sleep characteristics were evaluated. Age was associated with most of the sleep characteristics cross-sectionally and longitudinally (P < .05), except for the time in bed at baseline (P = .455) and change in sleep duration (P = .561). Compared with men, women had higher Pittsburgh Sleep Quality Index scores, shorter time in bed, shorter sleep duration, and longer latency at baseline (P ≤ .001). Longitudinal deterioration in Pittsburgh Sleep Quality Index score, habitual sleep efficiency, duration, and latency was more prominent in women (P < .001). The sex differences in these longitudinal sleep changes were mainly noticeable before age 60 years (P < .05). Worsening of Pittsburgh Sleep Quality Index scores, habitual sleep efficiency, and latency was most evident in perimenopausal women. Men presented with greater advancement of chronotype (P = .006), with the peak sex-related difference occurring when they were in their late 40s (P = .048). Aging is associated with substantial deterioration in sleep quantity and quality as well as chronotype advancement, with the degree and timing of these changes differing by sex.

Reliability of 3D Cs2M+M3+X6 type absorbers for perovskite solar cells: assessing the figures of merit

Figures of merit analysis of Cs2M+M3+X6 type absorbers for perovskite solar cells. Specific material properties (blue squares), a few merits (green squares), demerits (red squares) and possible solutions (grey squares) are indicated.

Conditioned place aversion of caustic paste and hot-iron disbudding in dairy calves

Cauterization by hot iron and application of caustic paste are 2 common methods of disbudding calves. In this study, we compared the affective experience of these 2 procedures on young dairy calves using conditioned place aversion. Male dairy calves (n = 14; 7 ± 2 d old) were disbudded by both thermal and chemical methods (1 horn bud at a time, 48 h apart). Calves received treatments in pens made visually distinct with either red squares or blue triangles on the walls. Calves were restricted to these treatment pens for 6 h following disbudding. For all treatments, calves received a sedative (xylazine, 0.2 mg/kg), local anesthetic (lidocaine, 5 mL), and analgesic (meloxicam, 0.5 mg/kg). Calves were then tested for conditioned place aversion at 48, 72, and 96 h after their last treatment. During tests, calves were placed in a neutral pen connected to both treatment pens where they had previously been disbudded. Time spent in each treatment pen was recorded until calves chose to lie down for 1 min (latency to lie down: 31.0 ± 8.6 min). During the first test (48 h after last disbudding), calves spent more time in the pen associated with hot-iron disbudding compared with what would be expected by chance (intercept: 73.5%, 95% CI: 56.5, 90.5) and fewer calves lay down in the caustic paste pen than in the hot-iron pen (3 vs. 10 lying events). No evidence of preference for the hot-iron pen was found in the following test sessions (72 and 96 h since last disbudding). These results suggest that calves initially remember caustic paste disbudding as a more negative experience than hot-iron disbudding, even with the use of sedation, local anesthesia, and analgesia.

Exploring GPCR-arrestin interfaces with genetically encoded crosslinkers.

β‐arrestins (βarr1 and βarr2) are ubiquitous regulators of G protein‐coupled receptor (GPCR) signaling. Available data suggest that β‐arrestins dock to different receptors in different ways. However, the structural characterization of GPCR‐arrestin complexes is challenging and alternative approaches to study GPCR‐arrestin complexes are needed. Here, starting from the finger loop as a major site for the interaction of arrestins with GPCRs, we genetically incorporate non‐canonical amino acids for photo‐ and chemical crosslinking into βarr1 and βarr2 and explore binding topologies to GPCRs forming either stable or transient complexes with arrestins: the vasopressin receptor 2 (rhodopsin‐like), the corticotropin‐releasing factor receptor 1, and the parathyroid hormone receptor 1 (both secretin‐like). We show that each receptor leaves a unique footprint on arrestins, whereas the two β‐arrestins yield quite similar crosslinking patterns. Furthermore, we show that the method allows defining the orientation of arrestin with respect to the GPCR. Finally, we provide direct evidence for the formation of arrestin oligomers in the cell.

In Situ Resistance Monitoring during Flame-Aerosol Deposition of Metal Oxide Gas Sensing Layers

Introduction Chemo-resistive sensors are highly promising for the detection of trace-level compounds in medical diagnostics[1] or indoor air monitoring[2]. In particular, gas sensors made by direct flame-aerosol synthesis are attractive due to their highly porous and crack-free sensing films[3]. They are composed of high-surface area nanoparticles with diverse composition tuned for ppb-level sensitivity and high selectivity towards key analytes such as Si-doped WO3 for acetone[1] or Ti-doped ZnO for isoprene[4]. Fabrication development has also led to the ability to process flame-made sensors by techniques compatible with standard silicon-wafer micromachining[5]. This enables the preparation of low power sensors that are attractive for portable handheld devices. So far, the development of such sensors has been focused mostly on material composition and, to a lesser extent, on film morphology and design. However, optimizing the latter could improve the sensor sensitivity as well as response and recovery times. Measuring the resistance during flame-deposition of nanostructured films in situ offers fabrication control by providing immediate feedback when an interconnected film is created[6]. This ultimately allows the fabrication of sensing films of minimal thickness and optimal resistance in a reproducible and economical manner. In situ resistance monitoring This work focuses on in situ monitoring the resistance of nanostructured films fabricated by direct deposition of flame-made Sb-doped SnO2 nanoparticles[6]. The sensing film morphology was tuned by a substrate-impinging particle flame, fed by a precursor solution containing varying metal ion concentrations. In situ resistance monitoring enabled control over final film resistance as well as direct insight into network formation and nanoparticle growth, necking and coalescence. The performance of these films as ethanol vapor sensors was assessed and related to their in situ resistance and nanoparticle film characteristics. Method Gas sensing nanoparticle films were prepared by direct deposition of flame-made Sb-doped (12 at%) SnO2 onto alumina substrates with interdigitated platinum electrodes. Deposition was carried-out for up to 6 min. Substrate preheating, film deposition and cooling to room temperature was closely monitored by the in situ resistance (Ri) between the interdigitated electrodes with a multimeter (Tektronix DMM4050). Nanoparticle sensing films were imaged by scanning electron microscopy (Hitachi S-4800 FE-SEM) after particle deposition for 2 min. Results and Conclusions Figure 1a shows the formation of Sb-doped SnO2 nanoparticles in a flame, followed by direct deposition onto the sensor substrate and in situ film resistance (Ri) read out. Figure 1b shows the in situ film resistance as a function of deposition duration using 1 (red squares), 10 (blue circles) or 100 (green triangles) mM FSP precursor solution concentrations (PSC). At low PSC (1 mM), the Ri remains at first (up to ca. 1 min) rather indifferent to nanoparticle deposition as it takes some time to build the interconnected particle bridges. But as deposition is prolonged (t >1.5 min), the Ri starts to drop. This clearly indicates the formation of an interconnected network of nanoparticles. Also quite notable is the strong oscillation of Ri by more than an order of magnitude during network formation. This stems from the constant formation (by deposition) and break-up of necked nanoparticles (by coalescence) on the substrate (i.e., repeatedly from lace-like to cauliflower-like structures) during flame-deposition. Increasing the PSC from 1 to 10 mM or 100 mM leads naturally to a higher generation rate of nanoparticles and, therefore, faster drop in resistance. This is confirmed by SEM imaging after 2 minute deposition time for 1, 10 and 100 mM (Figure 2 a-c). As expected, nanoparticles are assembled more densely at higher PSC. As a result, the film formation and morphology of Sb-doped SnO2 can be monitored during direct flame-deposition. This monitored Ri is correlated to its evolving particle size and necking, enabling the ability to optimize material quantity, fabrication time and the final film resistance. This leads to the ability to rapidly synthesize thin flame-made gas sensors with improved sensitivity and reduced response/recovery times.

Vanadium Transport through Cation and Anion Exchange Membranes

Transport of redox active molecules across the separator in a flow battery represents an important source of inefficiency and electrolyte-imbalance-induced capacity fade [1]. This transport can occur by diffusion, migration, and convection, with driving forces that change as cells are charged and discharged. The negative electrolyte in a vanadium redox flow battery, for example, contains V2+ and V3+ in proportions that depend on state of charge, but these species are absent from the positive side, leading to ever present concentration driving forces for diffusion across the separator. Migration alternately enhances and diminishes crossover since the electric field in the membrane orients in opposite directions during charge and discharge. Finally, hydraulic and osmotic pressure differences between the positive and negative electrolytes cause solvent flow that carries redox ions.Rigorous theoretical treatment of transport across membranes in flow batteries with concentrated-solution theory is complicated by the large number of species. For example, Nafion in a vanadium redox flow battery may contain: V2+, V3+, VO2+, VO2 +, H+, HSO4 -, SO4 2-, H2O, and fixed SO3 - anions (8). The number of multicomponent diffusion coefficients required to characterize a systems is , where n is the number of species present (after accounting for species coupled by rapid chemical equilibrium). The n multicomponent diffusion coefficients define one conductivity, transference numbers or ratios, , and diffusion coefficients of neutral combinations of species. The experimental and theoretical complexities associated with the multicomponent framework when many species are present motivates exploration of the applicability of the simpler, but less generally valid dilute-solution framework. In particular, we seek to understand how well do the relationships between diffusion coefficients, transference numbers, and conductivity predicted by dilute solution theory hold in practical membranes exposed to application-relevant electrolyte solutions? Do transference numbers predicted from conductivity and permeability measurements agree with independently measured values?Figure 1 shows measured transference numbers for the four vanadium ions relevant to flow batteries in N211 and N212 as blue and red squares, respectively. The measurements were made using a cell with three membranes and four flow compartments [2, 3]. Good agreement between the two data sets is apparent. The averages of the N211 and N212 values are plotted as crosses and reported in boxes to the right of the symbols. Transference numbers for V(IV) and V(V) are approximately an order of magnitude lower than transference numbers for V(II) and V(III). The grey squares with blue and red perimeters are the transference numbers calculated from the formula using measured conductivities and permeabilities. The average calculated values are given to the left of the data symbols, to facilitate comparison with the measured values. The measured and calculated transference numbers agree in magnitude, and no systemic differences are evident. The calculated transference number for V(III) appears to be off the experimental trend with one exception: a relatively large transference number is calculated for V(III) because it has a charge number of 3. The disagreement between the measured and calculated transference numbers for V(III) could arise from ion pairing effectively lowering the charge number. The calculated transference numbers are higher for V(II) and V(III) than V(IV) and V(V) because their permeabilities are higher while their conductivity is lower. All these results indicate the value of the study: dilute solution theory accurately predicts transference numbers for all species except perhaps V(III) in Nafion, and this deviation from the model for V(III) may inform the solvated behavior of V(III) ions.AcknowledgementsThis work was supported as part of the Joint Center for Energy Storage Research, an Energy Innovation Hub funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences. The submitted manuscript has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory (“Argonne”). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357.

The Pediatric Acute Leukemia Fusion Oncogene ETO2‐GLIS2 Increases Self‐Renewal and Alters Differentiation in a Human Induced Pluripotent Stem Cells‐Derived Model

Supplemental Digital Content is available in the text.

Descriptive Statistics in Medical Research

Related Article, see p 1474KEY POINT: “…the object of statistical methods is the reduction of data. A quantity of data …is to be replaced by relative few quantities which shall adequately represent the whole.” —Sir Ronald Fisher, 1922In this issue of Anesthesia & Analgesia, Meersch et al1 report results of an observational study on the role of vascular adhesion protein (VAP)-1 in the development of acute kidney injury (AKI) after cardiac surgery. The authors are commended for applying a range of descriptive statistics to characterize the patients and appropriately using and clearly reporting these statistics (Figure).Figure.: Excerpt of Table 1 from Meersch et al.1 Nominal (sex) and ordinal (ASA physical status score) data are reported as counts (absolute frequencies) and percentages (relative frequencies). Note that the numerators (counts per category per group: inside red squares) and denominators (total number of patients per group: inside blue squares) are appropriately presented. Quantitative data are reported as the mean (SD)—which is generally preferred to mean ± SD—or as the median with the Q1, Q3 values. ASA indicates American Society of Anesthesiologists; SD, standard deviation.The choice of the most appropriate summary statistic depends on the type and distribution of data. The following data types are distinguished:2 Nominal data have 2 (eg, sex) or more (eg, blood type) nonordered categories. Ordinal data have categories with a logical order (eg, American Society of Anesthesiologists [ASA] physical status score). Interval data are numeric and have an arbitrary zero point (eg, temperature in Celsius), while ratio data have an absolute zero point (eg, weight). Nominal and ordinal data are correctly summarized with the counts (absolute frequencies) and proportions or percentages (relative frequencies) of observations within the categories. When reporting relative frequencies, the numerator and denominator should both be presented. Interval and ratio data can also be summarized by frequencies within specific strata of the quantitative data (eg, number of patients with age 0–10 years, 11–20 years, etc). These frequencies are commonly reported as a histogram, providing a useful visual display of the data distribution. Two key characteristics of an interval or ratio dataset are (a) its central tendency characteristic—the “average” location of the data and (b) its variability—the extent to which individual values vary around the center. Both should be reported. For approximately normally distributed data, the arithmetic mean appropriately describes the center of the data.3 It is the sum of all observed values, divided by the number of observations. The mean is commonly accompanied by the standard deviation (SD), which describes how far the data points are dispersed around the mean. For normally distributed data, 68% are within 1 SD, 95% are within 2 SDs, and >99% are within 3 SDs on both sides of the mean.3 The median is the value that divides a dataset into 2 equal-sized parts, with the same number of datapoints above and below it.3 It is relatively robust to asymmetric (skewed) distributions, and extreme values (outliers). Therefore, the median is preferred to the mean for non-normally distributed data, and it can also be used for ordinal data.3 The median is commonly reported with the first and third quartiles (Q1, Q3), often loosely referred to as interquartile range. Quartiles divide the dataset into4 equally sized parts, and the interval between Q1 and Q3 contains the middle 50% of the data points. Descriptive statistics are also sometimes used as point estimates of population parameters (eg, using a sample to estimate a proportion or a mean in the population). In this case, they should be accompanied by a confidence interval as a measure of the estimate precision.4