Notes on techniques
Practical application of stereological kidney methods in experimental animal models
Aplicación práctica de métodos estereológicos renales en modelos animales experimentales
María Teresa Fernández Garcíaa,
, Paula Núñez Martínezb, Vanessa García de la Fuentea, Marta Sánchez Pitiota, María del Carmen Muñiz Salgueiroa, Carmen Perillán Méndezb, Juan Argüelles Luisb, Aurora Astudillo Gonzáleza,c
Corresponding author
a Unidad de Histopatología Molecular en Modelos Animales de Cáncer, Instituto Universitario Oncológico del Principado de Asturias, Oviedo, Asturias, Spain
b Área de Fisiología, Departamento de Biología Funcional, Universidad de Oviedo, Oviedo, Asturias, Spain
c Servicio de Anatomía Patológica, Hospital Universitario Central de Asturias, Oviedo, Asturias, Spain
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Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Servicio de Anatomía Patológica, Hospital Universitario Central de Asturias, Oviedo, Asturias, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "<span class="elsevierStyleItalic">Corresponding author</span>." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Aplicación práctica de métodos estereológicos renales en modelos animales experimentales" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 558 "Ancho" => 1501 "Tamanyo" => 230044 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">(A) Photomicrograph with a 1.25× objective of a cross-section of a mouse kidney (haematoxylin–eosin), with a superposed point grid for counting the points and calculating the Cavalieri volume. <span class="elsevierStyleItalic">White arrow</span>: scale present for calculating the magnification. <span class="elsevierStyleItalic">Red line</span>: Δ<span class="elsevierStyleItalic">x</span> or distance between points. (B) Photomicrograph of a histological field with 10× objective of the renal cortex according to the cross section, with superposed grid with 6 dissectors. <span class="elsevierStyleItalic">Red line</span>: Δ<span class="elsevierStyleItalic">x</span> and Δ<span class="elsevierStyleItalic">y</span> (the same since they are a square dissector).</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Kidneys are an essential organ in the maintenance of homeostasis, and nephrons are their structural and functional unit. The number, size, and distribution of nephron components (glomeruli, tubules, …) provide important information about renal function, making their quantification important in studies of traumas, chemicals and/or diseases. In these cases, as well as under normal circumstances, stereological studies allow us to detect and quantify macro- or microscopic changes.<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">1</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Stereology is a part of morphometry that allows three-dimensional information of cells or other biological structures to be collected from two-dimensional, serial, parallel, and equidistant microscopic slices by applying mathematical formulas based on statistically significant geometrical probability.<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">2</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Given the difficulty of stereological studies and the lack of a clear bibliography on their development, the objective of this work is to explain how to calculate the main stereological parameters of the kidney, step by step, in a simple manner and with examples utilising an animal model; the idea is to establish easily understandable bases applicable in experimental studies. This will contribute to the resolution of many pathological, physiological, and biochemical problems.<a class="elsevierStyleCrossRefs" href="#bib0050"><span class="elsevierStyleSup">2,3</span></a></p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Material and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Sample preparation</span><p id="par0020" class="elsevierStylePara elsevierViewall">Rat kidneys are extracted and fixed for 24<span class="elsevierStyleHsp" style=""></span>h in 4% paraformaldehyde at room temperature. They are subsequently washed with water. Will undergo successive ethyl alcohol baths with increasing concentrations; then they are cleared with xylol and embedded in paraffin (each kidney in a separate mould). Once the blocks are made, they are kept in cabinets at room temperature.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Preparation of histological slices</span><p id="par0025" class="elsevierStylePara elsevierViewall">It is best to start with a pilot study that includes one or two animals, to gradually correct errors and adjust the steps (for example, how many fields we will use to measure glomeruli, how many dissectors per histological field, etc.).<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">4</span></a></p><p id="par0030" class="elsevierStylePara elsevierViewall">We place a block with a kidney in the microtome and cut all of it into 5-μm thick sections. Orientation does not influence the calculation of the volume and numerical density<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">1</span></a> (in our laboratory we make cross sections). Another problem that may arise when tackling this objective is whether or not it is necessary for the renal cortex to be isotropic in order to apply the method and whether the size of the particles may lead to an error.</p><p id="par0035" class="elsevierStylePara elsevierViewall">As has been explained previously in classic articles,<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">5</span></a> that problem can be solved with adequate sampling, which gives each particle, in this case glomeruli, the same probability of being counted.</p><p id="par0040" class="elsevierStylePara elsevierViewall">For the stereological study, we will divide the sections or slices number 100 and 106, 200 and 206, … and successively in the same manner until the end.</p><p id="par0045" class="elsevierStylePara elsevierViewall">We will choose only those slices that are not broken or folded when laying them out on the slide. If this happens with the slice that we are supposed to select, we will advance 5<span class="elsevierStyleHsp" style=""></span>μm or whatever is necessary to obtain an optimal slice, as long as we then maintain the distance of 25<span class="elsevierStyleHsp" style=""></span>μm with its corresponding paired section, and we continue with the initially established system.</p><p id="par0050" class="elsevierStylePara elsevierViewall">The sections 100, 200, … are to calculate the total volume of the kidney or the Cavalieri reference volume, and we will call them “volume sections”. They are obtained systematically (there is always the same distance between the slices or <span class="elsevierStyleItalic">T</span>), uniformly (each of the slices are parallel) and randomly (the first slice is chosen arbitrarily between the slices 0 and <span class="elsevierStyleItalic">T</span>, with <span class="elsevierStyleItalic">T</span> being the same as 100 slices in this case). It is important to obtain a minimal number of slices (greater than or equal to 6) needed to obtain a volume with an acceptable error coefficient.<a class="elsevierStyleCrossRefs" href="#bib0045"><span class="elsevierStyleSup">1,3,4</span></a></p><p id="par0055" class="elsevierStylePara elsevierViewall">Sections 106, 206, … are paired sections that will be used to estimate the numerical density (number of glomeruli/mm<span class="elsevierStyleSup">3</span>) according to the physical dissector method. The reason why they are separated 6 slices from their pair section (“volume section”) is because the optimal distance between these sections must be approximately 1/3 of the mean diameter of the structure to be measured (in this case, the glomerulus).<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">6</span></a> In the case of kidney glomeruli in adult rats, this would be about 25<span class="elsevierStyleHsp" style=""></span>μm<a class="elsevierStyleCrossRefs" href="#bib0075"><span class="elsevierStyleSup">7,8</span></a> (at 5 slices with a thickness of 5<span class="elsevierStyleHsp" style=""></span>μm). The 2 paired sections are placed on the same slide.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Stereological analysis</span><p id="par0060" class="elsevierStylePara elsevierViewall">To calculate the total volume we will make photomicrographs of the “volume sections” where the entire kidney can be seen (1× and 1.25× objective). Each photograph must incorporate its corresponding scale. We will superpose a point grid over them with which we will calculate the distance between each point or mark and will call it Δ<span class="elsevierStyleItalic">x</span>, and measure the distance in mm with a gauge (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>A). Once we have the grid over the kidney, we count the number of points or marks that “fall” over the image of the kidney (we will call it ∑<span class="elsevierStyleItalic">P</span>).</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0065" class="elsevierStylePara elsevierViewall">Since the photomicrograph may be larger or smaller depending on the size of the monitor where it is projected, we use the scale of the photograph to keep it from affecting the study, and we measure it on the monitor with a gauge. With that measurement we can calculate the magnification or <span class="elsevierStyleItalic">M</span>:<elsevierMultimedia ident="eq0005"></elsevierMultimedia></p><p id="par0070" class="elsevierStylePara elsevierViewall">Now, we are ready to apply the following formula:<elsevierMultimedia ident="eq0010"></elsevierMultimedia></p><p id="par0075" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">T</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>distance between “volume sections”.</p><p id="par0080" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">a</span>/<span class="elsevierStyleItalic">p</span> (area associated with each point), Δ<span class="elsevierStyleItalic">x</span><span class="elsevierStyleSup">2</span> is the distance between two points of the grid and <span class="elsevierStyleItalic">M</span> is the magnification.</p><p id="par0085" class="elsevierStylePara elsevierViewall">∑<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>sum of points falling within the structure to be measured (kidney), superposing a point grid on it, in each of the resulting photographs (for example, if we have 6 “volume sections”, then ∑<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>∑<span class="elsevierStyleItalic">P</span>1<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>⋯<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>∑<span class="elsevierStyleItalic">P</span>6).</p><p id="par0090" class="elsevierStylePara elsevierViewall">In order to calculate the numerical density according to the physical dissector method,<a class="elsevierStyleCrossRefs" href="#bib0045"><span class="elsevierStyleSup">1,6,7</span></a> we apply a grid with the dissectors over the photomicrographs of slices 100, 200, … (“reference sections”) and then we compare them with their pairs 106, 206, … (“<span class="elsevierStyleItalic">look up</span>” sections). To do this, we make 2 photomicrographs (10× objective) of each paired section (always with the scale) that will allow us to simultaneously see the 2 sections. Once we have located the same histological area in both paired slices, we superpose the template with the 6 dissectors (could be more or less) on the reference image (100, 200, …) and count how many glomeruli (∑<span class="elsevierStyleItalic">Q</span><span class="elsevierStyleSup">−</span>) of the reference image (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>A) fall within the counting frame without touching the forbidden lines (straight lines) and do not appear in the “<span class="elsevierStyleItalic">look up</span>” image (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>B).</p><p id="par0095" class="elsevierStylePara elsevierViewall">This should be done on 10 random cortical fields of each “volume section” obtained (looking for histological references to ensure the same location in the 2 paired sections).</p><p id="par0100" class="elsevierStylePara elsevierViewall">For the study to be well done, we have to count between 100 and 200 glomeruli or ∑Q<span class="elsevierStyleSup">−</span>, because thus, when the formula for calculating the error coefficient or estimating the variance error is applied, it would have an approximate value of 0.1.<elsevierMultimedia ident="eq0015"></elsevierMultimedia></p><p id="par0105" class="elsevierStylePara elsevierViewall">Finally, we count the number of dissectors (∑<span class="elsevierStyleItalic">P</span>) used in the glomerular count to calculate on which kidney volume the glomeruli are being counted. In the example case they would be: 60 dissectors for each “volume section” (6 dissectors superposed on 10 histological fields)<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>total number of “volume sections” that we have obtained.</p><p id="par0110" class="elsevierStylePara elsevierViewall">Finally, we apply the following formula to obtain the numerical density:<elsevierMultimedia ident="eq0020"></elsevierMultimedia></p><p id="par0115" class="elsevierStylePara elsevierViewall">a/f(count or dissector framework area)=Δx×ΔyM2.</p><p id="par0120" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">h</span>: distance between paired sections of the dissector (in this case, 25<span class="elsevierStyleHsp" style=""></span>μm).</p><p id="par0125" class="elsevierStylePara elsevierViewall">∑<span class="elsevierStyleItalic">Q</span><span class="elsevierStyleSup">−</span>: sum of particles or glomeruli counted according to the dissector, in every “volume section”.</p><p id="par0130" class="elsevierStylePara elsevierViewall">∑<span class="elsevierStyleItalic">P</span>: sum of dissectors used to measure the glomeruli in every “volume section”.</p><p id="par0135" class="elsevierStylePara elsevierViewall">Once we have the numerical density (<span class="elsevierStyleItalic">Nv</span>), we can make an estimate of the total number of glomeruli<a class="elsevierStyleCrossRefs" href="#bib0055"><span class="elsevierStyleSup">3,4</span></a>:<elsevierMultimedia ident="eq0025"></elsevierMultimedia></p></span></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Results</span><p id="par0140" class="elsevierStylePara elsevierViewall">We began by sectioning the kidney of an 0F1 adult mouse (Charles River, Barcelona, Spain) in 5-μm thick sections, with a <span class="elsevierStyleItalic">T</span> of 500<span class="elsevierStyleHsp" style=""></span>μm (equivalent to 100 separation slices between “volume sections”).</p><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Total volume calculation according to Cavalieri</span><p id="par0145" class="elsevierStylePara elsevierViewall">Due to the size of the kidney, we obtained 10 “volume sections” and photographed them with a 1.25× objective on the microscope, incorporating the scale (which for this objective corresponds to a scale of 500<span class="elsevierStyleHsp" style=""></span>μm, and measured on the photo are 15.5<span class="elsevierStyleHsp" style=""></span>mm).</p><p id="par0150" class="elsevierStylePara elsevierViewall">We applied the point grid and made the following count (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0155" class="elsevierStylePara elsevierViewall">With this data we are able to calculate:<elsevierMultimedia ident="eq0030"></elsevierMultimedia><elsevierMultimedia ident="eq0035"></elsevierMultimedia><elsevierMultimedia ident="eq0040"></elsevierMultimedia><span class="elsevierStyleItalic">T</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>500<span class="elsevierStyleHsp" style=""></span>μm or 0.5<span class="elsevierStyleHsp" style=""></span>mm.<elsevierMultimedia ident="eq0045"></elsevierMultimedia><elsevierMultimedia ident="eq0050"></elsevierMultimedia><elsevierMultimedia ident="eq0055"></elsevierMultimedia></p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Calculation of the numerical density with the physical dissector</span><p id="par0160" class="elsevierStylePara elsevierViewall">We took 2 photomicrographs (10× objective) of each paired section (scale of 200<span class="elsevierStyleHsp" style=""></span>μm that measured 41<span class="elsevierStyleHsp" style=""></span>mm). We located the same histological area in both paired slices, superposed the template with the 6 dissectors on the “reference image” (100, 200, …) and counted how many glomeruli (∑<span class="elsevierStyleItalic">Q</span><span class="elsevierStyleSup">−</span>) fall within the counting frame without touching the forbidden lines (straight lines) and do not appear in the look up image (paired section). We repeated this action over 10 fields of each “volume or reference section”.</p><p id="par0165" class="elsevierStylePara elsevierViewall">We counted the number of dissectors utilised and applied the formula:<elsevierMultimedia ident="eq0060"></elsevierMultimedia><elsevierMultimedia ident="eq0065"></elsevierMultimedia><elsevierMultimedia ident="eq0070"></elsevierMultimedia><elsevierMultimedia ident="eq0075"></elsevierMultimedia><elsevierMultimedia ident="eq0080"></elsevierMultimedia><elsevierMultimedia ident="eq0085"></elsevierMultimedia><elsevierMultimedia ident="eq0090"></elsevierMultimedia><elsevierMultimedia ident="eq0095"></elsevierMultimedia></p></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Conflicts of interest</span><p id="par0170" class="elsevierStylePara elsevierViewall">The authors declare that they have no conflicts of interest.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:10 [ 0 => array:3 [ "identificador" => "xres818620" "titulo" => "Abstract" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0005" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec815670" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres818621" "titulo" => "Resumen" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0010" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec815669" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Material and methods" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Sample preparation" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Preparation of histological slices" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Stereological analysis" ] ] ] 6 => array:3 [ "identificador" => "sec0030" "titulo" => "Results" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0035" "titulo" => "Total volume calculation according to Cavalieri" ] 1 => array:2 [ "identificador" => "sec0040" "titulo" => "Calculation of the numerical density with the physical dissector" ] ] ] 7 => array:2 [ "identificador" => "sec0045" "titulo" => "Conflicts of interest" ] 8 => array:2 [ "identificador" => "xack274702" "titulo" => "Acknowledgements" ] 9 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2015-10-15" "fechaAceptado" => "2016-04-19" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec815670" "palabras" => array:3 [ 0 => "Renal stereology" 1 => "Glomerular density" 2 => "Glomeruli" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec815669" "palabras" => array:3 [ 0 => "Estereología renal" 1 => "Densidad glomerular" 2 => "Glomérulos" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:2 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">The kidneys are vital organs responsible for excretion, fluid and electrolyte balance and hormone production. The nephrons are the kidney's functional and structural units. The number, size and distribution of the nephron components contain relevant information on renal function. Stereology is a branch of morphometry that applies mathematical principles to obtain three-dimensional information from serial, parallel and equidistant two-dimensional microscopic sections. Because of the complexity of stereological studies and the lack of scientific literature on the subject, the aim of this paper is to clearly explain, through animal models, the basic concepts of stereology and how to calculate the main kidney stereological parameters that can be applied in future experimental studies.</p></span>" ] "es" => array:2 [ "titulo" => "Resumen" "resumen" => "<span id="abst0010" class="elsevierStyleSection elsevierViewall"><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Los riñones son órganos vitales que realizan funciones de excreción, equilibrio hidroelectrolítico y producción de hormonas. La nefrona es su unidad estructural y funcional. El número, tamaño y distribución de los componentes de la nefrona contienen información relevante sobre la función renal. La estereología es una rama de la morfometría que permite, aplicando reglas matemáticas, obtener información tridimensional de estructuras biológicas a partir de cortes microscópicos bidimensionales, seriados, paralelos y equidistantes. Ante la complejidad de los estudios estereológicos y la carencia de una bibliografía clara sobre el desarrollo de los mismos, el objetivo de este trabajo es explicar de forma sencilla y con ejemplos, utilizando un modelo animal, los conceptos básicos de estereología, así como el cálculo de los principales parámetros estereológicos renales y que estos puedan ser aplicados en futuros estudios experimentales.</p></span>" ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as: Fernández García MT, Núñez Martínez P, García de la Fuente V, Sánchez Pitiot M, Muñiz Salgueiro MdC, Perillán Méndez C, et al. Aplicación práctica de métodos estereológicos renales en modelos animales experimentales. Nefrologia. 2017;37:29–33.</p>" ] ] "multimedia" => array:21 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 558 "Ancho" => 1501 "Tamanyo" => 230044 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">(A) Photomicrograph with a 1.25× objective of a cross-section of a mouse kidney (haematoxylin–eosin), with a superposed point grid for counting the points and calculating the Cavalieri volume. <span class="elsevierStyleItalic">White arrow</span>: scale present for calculating the magnification. <span class="elsevierStyleItalic">Red line</span>: Δ<span class="elsevierStyleItalic">x</span> or distance between points. (B) Photomicrograph of a histological field with 10× objective of the renal cortex according to the cross section, with superposed grid with 6 dissectors. <span class="elsevierStyleItalic">Red line</span>: Δ<span class="elsevierStyleItalic">x</span> and Δ<span class="elsevierStyleItalic">y</span> (the same since they are a square dissector).</p>" ] ] 1 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Histological slice \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Points over cortical \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Points over medullar \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Histological slice \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Number of glomeruli \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Number of dissectors \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">46 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">24 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">107 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">51 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">101 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">39 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">116 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">97 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">111 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">77 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">39 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">32 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">105 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">58 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">77 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">29 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">65 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="6" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Total (∑<span class="elsevierStyleItalic">P</span>) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">935 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">589 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Total \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">175 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">294 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Cortical<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>medullar \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " colspan="2" align="center" valign="top">1524</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1375950.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Values of the points on the cortex and renal medulla for calculating the total volume of the example. And number of glomeruli and dissectors used to calculate the numerical density of the example.</p>" ] ] 2 => array:5 [ "identificador" => "eq0005" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "M=volar resultante de medir nosotros la escala sobre la fotografía en mmmedida expresada en la escala (que pasaremos a mm)." "Fichero" => "STRIPIN_si1.jpeg" "Tamanyo" => 8534 "Alto" => 37 "Ancho" => 484 ] ] 3 => array:5 [ "identificador" => "eq0010" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "V total(mm3)=T×a/p×∑P." "Fichero" => "STRIPIN_si2.jpeg" "Tamanyo" => 1929 "Alto" => 23 "Ancho" => 214 ] ] 4 => array:5 [ "identificador" => "eq0015" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "CE ∑Q−=1∑Q−=1200=0.1." "Fichero" => "STRIPIN_si3.jpeg" "Tamanyo" => 3091 "Alto" => 39 "Ancho" => 271 ] ] 5 => array:5 [ "identificador" => "eq0020" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "Nv=1(a/f)xh×∑Q−∑P." "Fichero" => "STRIPIN_si4.jpeg" "Tamanyo" => 2060 "Alto" => 37 "Ancho" => 157 ] ] 6 => array:5 [ "identificador" => "eq0025" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "Total number of particles=total volume×numerical density (Nv)." "Fichero" => "STRIPIN_si6.jpeg" "Tamanyo" => 4021 "Alto" => 16 "Ancho" => 429 ] ] 7 => array:5 [ "identificador" => "eq0030" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "V total cortical=Txa/px∑P=0.5 mm × 0.04 mm2×935=18.7 mm3 (18.7×109 mm3)." "Fichero" => "STRIPIN_si7.jpeg" "Tamanyo" => 5448 "Alto" => 53 "Ancho" => 401 ] ] 8 => array:5 [ "identificador" => "eq0035" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "V total medular=Txa/px∑P=0.5×0.04×589=11.78 mm3." "Fichero" => "STRIPIN_si8.jpeg" "Tamanyo" => 3585 "Alto" => 23 "Ancho" => 430 ] ] 9 => array:5 [ "identificador" => "eq0040" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "V total renal=Txa/px∑P=0.5×0.04×1524=30.48 mm3,donde:" "Fichero" => "STRIPIN_si9.jpeg" "Tamanyo" => 4327 "Alto" => 51 "Ancho" => 322 ] ] 10 => array:5 [ "identificador" => "eq0045" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "M=15.50.5=31." "Fichero" => "STRIPIN_si10.jpeg" "Tamanyo" => 1252 "Alto" => 31 "Ancho" => 105 ] ] 11 => array:5 [ "identificador" => "eq0050" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "a/p=ΔX2M2=6.22312=38.44961=0.04 mm2." "Fichero" => "STRIPIN_si11.jpeg" "Tamanyo" => 2923 "Alto" => 36 "Ancho" => 274 ] ] 12 => array:5 [ "identificador" => "eq0055" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "∑P=935." "Fichero" => "STRIPIN_si12.jpeg" "Tamanyo" => 908 "Alto" => 23 "Ancho" => 82 ] ] 13 => array:5 [ "identificador" => "eq0060" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "Nv=1(a/f)xh×∑Q−∑P=10.019×0.025×175294=1252.631 glomérulos/mm3." "Fichero" => "STRIPIN_si13.jpeg" "Tamanyo" => 5493 "Alto" => 67 "Ancho" => 315 ] ] 14 => array:5 [ "identificador" => "eq0065" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "N total glomérulos=18.7 mm3×1237.89 glomérulos/mm3=23,424.199." "Fichero" => "STRIPIN_si14.jpeg" "Tamanyo" => 4503 "Alto" => 46 "Ancho" => 405 ] ] 15 => array:5 [ "identificador" => "eq0070" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "a/f=Δx×ΔyM2=29.5×29.542,025=0.020 mm2(20,707.91 μm2)." "Fichero" => "STRIPIN_si15.jpeg" "Tamanyo" => 4620 "Alto" => 33 "Ancho" => 406 ] ] 16 => array:5 [ "identificador" => "eq0075" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "M=410.2=205." "Fichero" => "STRIPIN_si16.jpeg" "Tamanyo" => 1206 "Alto" => 31 "Ancho" => 105 ] ] 17 => array:5 [ "identificador" => "eq0080" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "h=25 μm   or   0.025 mm." "Fichero" => "STRIPIN_si17.jpeg" "Tamanyo" => 1649 "Alto" => 14 "Ancho" => 181 ] ] 18 => array:5 [ "identificador" => "eq0085" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "∑Q−=173." "Fichero" => "STRIPIN_si18.jpeg" "Tamanyo" => 956 "Alto" => 23 "Ancho" => 94 ] ] 19 => array:5 [ "identificador" => "eq0090" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "∑P=294." "Fichero" => "STRIPIN_si19.jpeg" "Tamanyo" => 905 "Alto" => 23 "Ancho" => 82 ] ] 20 => array:5 [ "identificador" => "eq0095" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "CE∑Q−=1∑Q−=1175=0.07." "Fichero" => "STRIPIN_si20.jpeg" "Tamanyo" => 3231 "Alto" => 39 "Ancho" => 277 ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:8 [ 0 => array:3 [ "identificador" => "bib0045" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Stereologic methods and their application in kidney research" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "J.R. 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Cruz-Orive, of the Universidad de Santander [Santander University].</p>" "vista" => "all" ] ] ] "idiomaDefecto" => "en" "url" => "/20132514/0000003700000001/v1_201703230033/S2013251417300159/v1_201703230033/en/main.assets" "Apartado" => array:4 [ "identificador" => "64580" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Notes on techniques" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/20132514/0000003700000001/v1_201703230033/S2013251417300159/v1_201703230033/en/main.pdf?idApp=UINPBA000064&text.app=https://revistanefrologia.com/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2013251417300159?idApp=UINPBA000064" ]
| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 6 | 3 | 9 |
| 2024 October | 49 | 48 | 97 |
| 2024 September | 63 | 31 | 94 |
| 2024 August | 69 | 58 | 127 |
| 2024 July | 66 | 37 | 103 |
| 2024 June | 62 | 45 | 107 |
| 2024 May | 81 | 34 | 115 |
| 2024 April | 79 | 26 | 105 |
| 2024 March | 55 | 35 | 90 |
| 2024 February | 49 | 34 | 83 |
| 2024 January | 46 | 22 | 68 |
| 2023 December | 25 | 27 | 52 |
| 2023 November | 66 | 31 | 97 |
| 2023 October | 63 | 30 | 93 |
| 2023 September | 48 | 32 | 80 |
| 2023 August | 54 | 25 | 79 |
| 2023 July | 56 | 23 | 79 |
| 2023 June | 53 | 22 | 75 |
| 2023 May | 46 | 29 | 75 |
| 2023 April | 49 | 23 | 72 |
| 2023 March | 71 | 27 | 98 |
| 2023 February | 61 | 25 | 86 |
| 2023 January | 56 | 27 | 83 |
| 2022 December | 62 | 38 | 100 |
| 2022 November | 86 | 36 | 122 |
| 2022 October | 74 | 45 | 119 |
| 2022 September | 67 | 32 | 99 |
| 2022 August | 72 | 46 | 118 |
| 2022 July | 74 | 39 | 113 |
| 2022 June | 49 | 45 | 94 |
| 2022 May | 46 | 34 | 80 |
| 2022 April | 50 | 48 | 98 |
| 2022 March | 54 | 57 | 111 |
| 2022 February | 54 | 52 | 106 |
| 2022 January | 71 | 38 | 109 |
| 2021 December | 77 | 50 | 127 |
| 2021 November | 46 | 45 | 91 |
| 2021 October | 71 | 40 | 111 |
| 2021 September | 74 | 41 | 115 |
| 2021 August | 68 | 45 | 113 |
| 2021 July | 53 | 31 | 84 |
| 2021 June | 53 | 37 | 90 |
| 2021 May | 64 | 40 | 104 |
| 2021 April | 166 | 78 | 244 |
| 2021 March | 86 | 57 | 143 |
| 2021 February | 70 | 40 | 110 |
| 2021 January | 47 | 26 | 73 |
| 2020 December | 54 | 23 | 77 |
| 2020 November | 47 | 14 | 61 |
| 2020 October | 43 | 17 | 60 |
| 2020 September | 43 | 20 | 63 |
| 2020 August | 50 | 9 | 59 |
| 2020 July | 56 | 19 | 75 |
| 2020 June | 47 | 20 | 67 |
| 2020 May | 51 | 12 | 63 |
| 2020 April | 46 | 22 | 68 |
| 2020 March | 53 | 4 | 57 |
| 2020 February | 62 | 26 | 88 |
| 2020 January | 62 | 24 | 86 |
| 2019 December | 54 | 27 | 81 |
| 2019 November | 64 | 22 | 86 |
| 2019 October | 42 | 12 | 54 |
| 2019 September | 44 | 21 | 65 |
| 2019 August | 34 | 15 | 49 |
| 2019 July | 44 | 25 | 69 |
| 2019 June | 41 | 19 | 60 |
| 2019 May | 62 | 24 | 86 |
| 2019 April | 116 | 56 | 172 |
| 2019 March | 54 | 26 | 80 |
| 2019 February | 38 | 19 | 57 |
| 2019 January | 34 | 26 | 60 |
| 2018 December | 165 | 46 | 211 |
| 2018 November | 283 | 24 | 307 |
| 2018 October | 241 | 24 | 265 |
| 2018 September | 136 | 28 | 164 |
| 2018 August | 60 | 14 | 74 |
| 2018 July | 62 | 17 | 79 |
| 2018 June | 76 | 15 | 91 |
| 2018 May | 86 | 12 | 98 |
| 2018 April | 144 | 13 | 157 |
| 2018 March | 112 | 12 | 124 |
| 2018 February | 98 | 5 | 103 |
| 2018 January | 54 | 8 | 62 |
| 2017 December | 93 | 7 | 100 |
| 2017 November | 58 | 16 | 74 |
| 2017 October | 38 | 5 | 43 |
| 2017 September | 72 | 7 | 79 |
| 2017 August | 119 | 10 | 129 |
| 2017 July | 79 | 6 | 85 |
| 2017 June | 107 | 6 | 113 |
| 2017 May | 98 | 11 | 109 |
| 2017 April | 46 | 6 | 52 |
| 2017 March | 52 | 8 | 60 |
| 2017 February | 24 | 6 | 30 |
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