In 2017, the provincial government of British Columbia (BC) implemented a mandatory policy outlining Active Play Standards (AP Standards) to increase physical activity (PA) levels, sedentary and motor skills among children attending licensed childcare centers. Concurrently, a capacity-building initiative was launched to help implement policies and practices supporting both PA and healthy eating (HE) in the early years. This study evaluated differences in center-level PA and HE policies and practices before and after the enforcement of the new provincial AP Standards.Using a repeat cross-sectional design, surveys were distributed to managers and staff of licensed childcare facilities serving children aged 2–5 years before (2016–2017 or ‘time 1’) and after (2018–2019 or ‘time 2’) implementation of the AP Standards across BC. The total sample included 1,459 respondents . Hierarchical mixed effects models were used to examine differences in 9 and 7 PA/sedentary policies and practices, respectively, as well as 11 HE policies between time 1 and time 2. Models controlled for childcare size and area-level population size, education, and income.P < 0.01 for all 9 policies examined). Compared to time 1, centers at time 2 reported more frequent practices related to ensuring children engaged in at least 120 min of AP, 60 min of outdoor AP daily, and limiting screen time (P < 0.01 for 3 out of 7 practices examined). Despite no additional policy intervention related to HE, centers were more likely to report having written policies related to: HE education for children, encouraging new foods, having family-style meals, offering only milk or water, limiting the amount of juice served, staff role modeling of HE, limiting the types of foods at parties/celebrations and foods brought from home (P < 0.05 for 9 out of 11 HE policies).Compared to centers surveyed at time 1, centers at time 2 were more likely to report written policies related to: fundamental movement skills, total amount of Active Play (AP) time, staff-led AP, unfacilitated play/free play, total amount of outdoor AP time, limiting screen time, breaking up prolonged sitting, staff role modeling of PA, and training staff about PA (Approximately a year after the implementation of a governmental policy targeting PA supported by a capacity-building initiative, childcare centers reported positive changes in all 9 PA/sedentary policies examined, all 3 out of 7 PA/sedentary practices and 9 out of 11 HE policies evaluated at the center-level. Ensuring sufficient and quality physical activity (PA) and nutrition in the early years is key to preventing excessive weight gain as well supporting healthy children’s physiological, psychosocial, and educational outcomes –3. ProviChildcare settings are an amenable and promising environment to facilitate the delivery of obesity prevention programs as they provide access to large numbers of children during a critical period of their growth and maturation , 10. In Empirical evidence suggests that changes in PA policies can lead to significant improvements in childcare environments and providers’ practices with respect to PA –21 whileIn British Columbia (B.C.) (Canada), regulations guiding PA and nutrition practices for licensed childcare settings have been in place since 2007 and are regularly updated through the Community Care and Assisted Living Act: Child Care Licensing Regulations . In JulyThe objectives of this study were to: 1) describe the level of implementation of the AP Standards in a sample of childcare centers across BC; and, 2) examine differences in the prevalence of centers with written policies and frequency of reported practices related to PA, sedentary and HE behaviours in 2018–19 compared to 2016–17. Following the implementation of the AP Standards and scale-up of ATP training, we hypothesized that a greater proportion of childcare centers would have written PA and report more frequent practices targeted by the AP Standards . Since the implementation of the AP Standards did not focus on nutrition or HE, we did not have an a priori hypothesis regarding changes in centers’ HE policies over time.All methods were performed in accordance with the relevant guidelines and regulations and the study was approved by the University of Victoria and University of British Columbia Harmonized Research Ethics Review Board . Respondents gave their implicit and informed consent by answering the Early Years survey.The study sample for this repeat cross-sectional study included managers and staff of licensed childcare centers serving children 2–5 years of age across British Columbia (BC), Canada. Respondents were eligible to participate if their center cared for children age 2 ½ -5 years old, was licensed for group childcare, preschool (offering full days), and/or multi-age childcare and if the respondent was a manager or a staff caring for children age 2 ½—5 years old, respectively.The first wave of online data collection started from October 2016 and ended in August 2017. At baseline, the only standards in place included the size of the play space and providing opportunities for gross motor movements . The AP n = 910 in 2016–17 (‘time 1’) and n = 549 in 2018–19 (‘time 2’)) were included in our sample. These respondents worked at 592 and 378 centers at time 1 and time 2, respectively. Based on a sampling frame of approximately 1,500 registered licensed childcare centers in BC, our response rate was approximately 41% and 25% in 2016–17 and 2018–19, respectively. At time 1, 39% of the facilities (n = 232 out of 592 centers) had more than one respondent fill out the survey and included between 2 and 6 surveys for a given facility. At time 2, 29% of the facilities (n = 108 out of 378 centers) had more than one respondent fill out the survey and included between 2 and 5 surveys for a given facility.A total of 1,459 participants (n = 7). In 2018–19, some survey items were also developed to ensure that the questions measured the policies and practices targeted by the AP Standards.Respondents completed a self-report survey with items adapted from the validated EPAO-SR  instrument to include survey items about BC-specific childcare center characteristics . QuestioAt time 1, separate versions of the Early Year Surveys were sent to managers and staff in each facility (manager and staff surveys). However, at time 2, a single version of the Early Year survey was sent out to a center and the respondent had a staff position, they were asked to answer additional questions related to PA/sedentary practices on the previous day. At both time points, respondents were asked to choose the position that best described their position/role at the facility. Respondents could select from 5 response options: 1) “Executive director/program manager”, 2) “staff that care for 2 ½ to 5-year-old children”, 3) “staff that care for children younger than 2 ½ or older than 5-year-old children”, 4) “Administrative assistant/office manager” or 5) “other”. Respondents were classified as “eligible managers” if they selected “Executive director/program manager” and/or “Administrative assistant/office manager”. Respondents were classified as “eligible staff” if they selected “staff that care for 2 ½ to 5-year-old children”. Respondents who selected “executive director/program manager”/ “Administrative assistant/office manager” as well as “staff that care for 1 ½ to 5-year-old children” were classified as “eligible manager and staff”. In order to aggregate responses within a center for our outcomes (as many centers had more than one manager or one staff fill out the survey), we also classified each survey as a “manager survey” or a “staff survey” based on the respondent’s position. Any survey from an “eligible manager” or “an eligible manager and staff” was classified as a “manager survey”; otherwise, the survey was classified as a “staff survey”.In 2018–19, both managers and staff were asked about the prevalence of policies related to physical activity and nutrition but in 2016–17, only managers were asked about the prevalence of policies. Managers (as well as staff in 2018–19) were asked: “Does your facility have a policy/guideline that includes a statement about…”: 1) staff provision of activities that addressed fundamental movement skills; 2) the total amount of AP time; 3) the amount of staff-led AP time; 4) the amount of unfacilitated play / free play; 5) the amount of outdoor AP time each day; 6) the amount of time children can play with or watch screens; 7) breaking up prolonged sitting time with activity; 8) staff role modeling of PA and screen time; 9) training staff about PA/developing physical literacy. Respondents could select from the following answer options: “no”, “yes, not written policy”, “Yes, written policy”, or “N/A”. Answers were recoded and dichotomized into: “yes, written policy” or “No written policy” (which included the response options of “yes not written” and “No”).Related to HE policies, managers (as well as staff in 2018–19) were asked: “Does you facility policy include a statement about…”: 1) HE education for children; 2) HE training for staff; 3) encouragement of new foods; 4) family style meals (staff sit with children to enjoy food together); 5) offering drinking water or milk only; 6) type of milk served ; 7) amount of fruit juice served; 8) staff role modeling of eating behaviours; 9) encouraging inclusion of fruit/vegetable when snack/meal is served; 10) limiting types of food and drink brought to parties and celebrations; 11) types of beverages and/or food brought from home. Respondents could select from the following options: “No”, “Yes, not written policy”, or “Yes, written policy”. Responses were recoded into “Yes, written policy” or “No written policy” .When more than one respondent from a center responded to the survey (‘duplicates’), respondents’ answers were aggregated using the following protocol. For each policy item , responses were averaged across respondents by year and position/role (manager or staff). If agreement among managers was greater than 66.7%, their policy score was rounded to either “0” (no written policy) or “1” (written policy). If agreement among managers was below 66%, then the survey response was recoded as missing. To determine the presence of a written policy within a center, we prioritized managers’ responses over staff. However, when manager responses were missing and policy responses were available from a staff, we used staff responses.At both time points, managers and staff were asked to indicate how frequently children in their program: 1) took part in daily activities that develop fundamental movement skills; 2) engaged in at least 120 min of AP and PA per day; 3) engaged in at least 60 min of outdoor active play per day; 4) spent 30 min or less on screens per day; 5) see staff being active; 6) did not sit for prolonged periods ; and 7) learn about why PA is good for them. Response options for each of the practices included “Daily”, “Most days (3–4)”, “Some days (1–2)”, “infrequently”, and “rarely/never”. Responses were coded on a 1–5-point Likert scale, with a higher score indicating a more frequent practice.When more than one respondent from a center responded to the survey (‘duplicates’), these duplicates were processed as follows. For each practice item, responses were averaged by year and by position/role (managers or staff). Our research team had previously explored consistencies and discrepancies in self-reported policies and practices between managers and staff . We had In addition to their role/position in the facility, care providers were asked about their age, gender, and number of years working at the facility. At the center level, we inquired centers about the current number of number of children enrolled, their food procurement patterns  and about the level of food preparation done at the facility, with response options ranging from “Hot and cold snacks prepared on site on all or most days”, “minimal food preparation , “pre-packaged single portion foods”, “all food supplied by parents” or “Other”. At time 2 (but not time 1), we also asked centers to indicate what food provisioning system was used for AM snack, lunch, and PM snack . Population size, percentage of the population with some post-secondary education and median household income were obtained from the Statistics Canada 2016 Census and linked to childcare site data using postal codes.Descriptive statistics  and proportions/percentages (%)) were used to describe the characteristics of respondents and childcare facilities, their AP Standards and ATP implementation status , prevalence of centers with written policies at each time point, and mean scores for reported practices. Hierarchical mixed effects models were used to assess differences in the prevalence of centers reporting having written policies and frequency of reported practices between 2016–17 and 2018–19. Hierarchical mixed effects models were chosen to account for the unbalanced nature of the dataset: while most childcare centers provided only data at one time point (2016–17 or 2018–19), 146 centers provided data at both time points. Finally, sensitivity analyses were conducted to explore whether the prevalence of policies changed when taking only responses from managers (as opposed to supplementing missing manager responses with staff surveys). The same sensitivity analyses were conducted for practices using only responses from staff (as opposed to supplementing missing staff responses with manager surveys).p-value of less than 0.01 was considered statistically significant.All analyses were conducted in STATA version 16 . Analysen = 1,459 respondents from 970 centers) are shown in Table Participant and childcare center characteristics  reported a mixed childcare food provisioning system . Only 15% and 17% of the centers surveyed at time 1 and time 2, respectively, provided all the food for children in the center. A total of 37% and 36% of centers asked parents to bring in all foods for the day at the center at both time points. The extent to which centers prepared food for children was similar between survey years, with ~ 36% and 37% of centers preparing hot and cold meals and/or snacks on site, 29% and 26% reporting minimal food preparation on site  at time 1 and time 2, respectively. At time 2 , most centers (77%) reporting having children bring in their own packed lunch from home. Having a center provide morning or afternoon snacks was more common than providing lunch, with just over half of centers providing a snack (morning and/or afternoon) to children. Facilities were in communities with similar socioeconomic profiles (62% and 63% of households with some post-secondary education and a median household income of CAN $87 k) in both survey years.n = 119 participants), 83% of participants completed the training in person vs. 17% of participants who reported taking part only in online training.At time 2, most respondents (96%) reported that their facility had been reviewed by a licensing officer within the past year and 89% of respondents confirmed that the licensing officer had reviewed whether their facility met the AP Standards. A total of ~ 18% of respondents reported that the licensing officer had recommended to make some changes to meet the new AP Standards. Just under a quarter of respondents (22%) surveyed in 2018–19 also reported attending the ATP training workshops. Among those who completed the ATP training  to 43% (policies related to amount of daily outdoor active play). After the implementation of the AP Standards, the prevalence of PA/sedentary policies ranged from 17%  to 77% (policies related to daily outdoor active play time). At time 1, average scores for PA/sedentary practices ranged from 3.0 (limiting screen time) to 4.6 (engaging in at least 60 min of outdoor AP daily) . At time 2, practices scores ranged from 3.6 (spending less than 30 min on screens daily) to 4.9  to 52% (policies related to providing HE education to children). At time 2, the prevalence of HE policies ranged from 15% (policies on the type of milk served) to 69% (policies related to HE nutrition education for children).Table In terms of HE, centers were more likely to reporting having written policies for 9 of the 11 policies examined. Compared to time 1, centers at time 2 were more likely to report written policies related to: foods and beverages brought from home (AOR = 5.0), providing nutrition education to children (AOR = 2.3), staff role modeling of HE (AOR = 2.0), the amount of fruit juice served (AOR = 1.9), encouraging children to try new foods (AOR = 1.7), serving family-style meals (AOR = 1.7), encouraging fruit/vegetables at meal & snack times (AOR = 1.6), limiting the types of foods at parties/celebrations (AOR = 1.5), and offering water or milk only (AOR = 1.4).Childcare centers are salient settings to institutionalize comprehensive health promoting policies, which possess the potential to lead to widespread changes in PA and HE . In CanaOur study contributes to a limited body of evidence about the effectiveness of governmental policy change on childcare centers’ PA and HE policies and practices. Limited Canadian research has explored the institutionalization of PA guidelines in early year settings. A 2016–17 survey of childcare providers across Canadian provinces and territories found that less than half of centers surveyed (n = 514) reported having written policies related to PA and fewer (29%) had written policies related to screen time . A recenn = 9 ECE centers). While no statistically significant difference in total EPAO scores were found (p = 0.06), centers improved their EPAO sub-scores for providing more AP opportunities and improving staff behaviors. Another quasi-experimental study examining the effect of mandatory PA standards for ECE centers in South Carolina reported significant improvement in total EPAO scores over a one year period [p = 0.06). In Australia, a longitudinal study assessing centers’ adoption of six PA and HE practices over a 7-year period (n = 358 centers) reported significant increases in the prevalence of services adopting all but one practice [There is limited evidence of the effectiveness of governmental policy change on childcare centers’ PA and HE policies and practices. A 2019 systematic review of natural policy experiments targeting childhood obesity prevention and control reported that of the 33 natural experiments, most (73%) took place in school settings . In the r period . The latpractice . Combinewww.appetitetoplay.com), freely accessible to the public. Some of the respondents who reported not attending the ATP training could have accessed some of the web-based resources promoted by other early year providers who attended the training workshops. Moreover, the timing of the 2018–19 surveys also aligned with the release of the 24-Hour Movement Guidelines for the Early Years [When examining the potential influence of capacity-building on policy implementation we found that a relatively small proportion of respondents (22%) reported attending the ATP workshops (attending either in-person or online), suggesting overall low uptake/adoption of ATP training in this sample of centers. Thus, it may be possible that the monitoring of the policy played a larger role in changing center-level PA/sedentary policies than implementation support strategies. However, a key component of the ATP intervention included a web-based toolkit  and provider-level  could influence the implementation of the AP Standards on PA practices. Previous implementation studies have highlighted the importance of additional resources to help teachers meet new PA regulations such as staff training and helping purchase portable equipment to promote AP . Next stThe early years are an important time for developing eating skills and accepting a variety of healthy foods. Mealtimes should represent supportive environments for practicing skills and trying unfamiliar foods . Our resThis study had several strengths including a large sample of childcare providers across urban and rural sites and the inclusion of both manager and staff responses which may present a more reliable depiction of policy and practice changes since the implementation of the AP Standards. Several limitations deserve consideration. First, all policies and PA practices were reported by managers . Therefore, responses could have been subject to social desirability bias. Yet while the results are expected to be inflated by self-report, it is important to note that this bias was present at both time points and that even with this limitation changes were observed over time. Second, this study was unable to compare the center changes with another province to provide a comparator or control condition for policy comparison. It is therefore possible, as mentioned earlier, that other external contextual factors such as the release of the 24-h Canadian movement guidelines for the early years  could haIn summary, the implementation of AP Standards along with capacity-building appeared to facilitate changes in all PA/sedentary policies and some of the HE policies examined among childcare centers in BC. Although PA practice changes were more modest relative to PA policy changes, centers reported more frequent PA supportive practices such as providing children with at least 120 min of daily of AP, 60 min of daily outdoor play and limiting screen time to 30 min following the implementation of the AP Standards and the delivery of ATP across the province. Previous research has linked changes in the childcare environment with children’s nutrition and PA behaviors , 44. TheThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.


Interestingly, while the ν(Fe–CN)modes exhibit the same frequencies in both the isolated and RBC-enclosedhemoglobin molecules, small frequency differences are observed inthe δ(Fe–CN) bending modes and the values of their isotopicshifts. These studies show that even though the overall tilted conformationof the Fe–C≡N fragment in the isolated HbCN is preservedin the HbCN enclosed within living cells, there is a small differencein the degree of distortion of the Fe–C≡N fragment.The slight changes in the ligand geometry can be reasonably attributedto the high ordering and tight packing of Hb molecules inside RBCs.The UV–vis absorption, Ramanimaging, and resonance Raman(rR) spectroscopy methods were employed to study cyanohemoglobin (HbCN)adducts inside living functional red blood cells (RBCs). The cyanideligands are especially optically sensitive probes of the active siteenvironment of heme proteins. The rR studies of HbCN and its isotopicanalogues ( Resonance Raman(rR) spectroscopy is a powerful technique for the characterizationof the heme–CN– adducts, allowing the detectionand monitoring of all possible vibrations associated with the Fe–C≡Nfragment, including the ν(Fe–CN) stretching, δ(Fe–CN)bending, and ν(C≡N) stretching modes;20 for example, the rR studies of isolated HbCN protein were previouslypublished.12The X-ray studies of a relaxedquaternary structure of Hb showedthat there is not enough space in the distal heme pocket for a stericallyunhindered linear configuration along the heme axis.18 In cases when the active site perturbs the linkage sufficientlystrong, the Fe–C≡N unit will adopt a tilted  or bent configuration, for which the δ(Fe–CN)bending mode is effectively enhanced.18 In some hemeproteins, such as Mb, Hb, and cytochrome c oxidase(CcO), the active site exerts only a slight disturbance of the axialligand, resulting in the tilted configuration of Fe–C≡N.For a tilted conformer, the ν(Fe–CN) stretching modeis usually seen at around 450 cm–1, whereas theδ(Fe–CN) bending mode is seen around 380 cm–1.15 Analysis ofthe rR spectra of isotopically substituted analogues provides additionalinformation regarding the correct assignment of the Fe–C≡Ngeometry. In the case of the tilted conformer, the ν(Fe–CN)stretching mode decreases in a monotonic manner with the increasein the total mass of CN– in the following order:CN, 13CN, C15N, 13C15N.On the other hand, the δ(Fe–CN) bending modes of thetilted conformer exhibits the so-called zig-zag pattern, where thesignificant frequency decrease is observed only for the 13C isotopologues.16 If active site perturbationsare sufficiently strong, as in the case of lactoperoxidase (LPO) andmyeloperoxidase (MPO) proteins, they can induce a substantial degreeof distortion, resulting in a bent configuration of Fe–C≡Nwith a distinct vibrational behavior. The ν(Fe–CN) stretchingmode is seen at lower frequencies and exhibits an isotopic zig-zagpattern, whereas the δ(Fe–CN) bending mode is observedat a higher frequency, and its isotopic shifts are monotonic withan increased CN– mass.14 It is also noted that in some proteins, such as HRP and P450, theactive site architecture allows the coexistence of both the essentiallylinear and the bent conformers of Fe–C≡N.14Theenhancement of specific vibrational modes, their frequencies,and patterns of isotopic shifts permit a clear distinction betweenthe linear, tilted, and bent configurations of the Fe–C≡Nfragment. The linear geometry of the Fe–CN linkage naturallyabolishes the activation of the δ(Fe–CN) bending mode.12 cytochrome c oxidase,16 and cytochrome P450,18 the goal of this work is to probe cyanide ligand binding to Hb insideliving red blood cells (RBCs) in order to compare the heme activesite properties between isolated and RBC-enclosed Hb molecules. Itwas previously demonstrated that Raman spectroscopy (RS) is extremelyuseful in studying Hb alterations within functional RBCs even on asingle-cell level and it is an excellent tool to study the heme activesite.27 Such structural information is not available using traditional techniques,including X-ray crystallography, electron microscopy, or NMR spectroscopy.Similarly, molecular modeling calculations are not capable to deliversuch insights into proteins encapsulated within RBCs, as a correctassumption of all intercellular interactions would be too overparameterized.Therefore, rR spectroscopy remains unique in assessing the structuralinformation on proteins in complex biological matrixes, and in thiswork is used for the first time to characterize HbCN adducts formedinside functional RBCs. The work presented herein is complementedby simultaneous rR studies of isolated HbCN proteins in buffer solution.The data provide new evidence that studies of isolated proteins cangenerally be translated into physiological cell-based investigations.However, some subtle differences are noted between the active sitestructures of isolated proteins and those within living cells. Thestudies shown here are a continuation of previous works on RBCs, wherethe formation of heme adducts in various experimental conditions wasstudied using RS.28 The spectroscopic studies ofHbCN adducts formed inside RBCs were conducted using UV–visabsorption, Raman imaging (RI), and rR spectroscopy. The isotope-sensitiveexperiments with the use of 13CN–, C15N–, and 13C15N– analogues, as well as careful deconvolution of spectraldata, were carried out to derive the frequencies of the modes associatedwith the Fe–C≡N fragments and to detect the correctvalues of their isotopic shifts.Although all previous studies of the CNadducts were done usingisolated heme proteins or standard compounds, for example, hemoglobinand myoglobin,13N, KC15N and K13C15N—were purchased from CambridgeIsotope Laboratories .Sodium chloride was purchasedfrom Fisher Scientific  and sucrose fromBio Basic . Sodium nitrite, sodium dithionite,potassium ferricyanide(III), and potassium cyanide were purchasedfrom Sigma-Aldrich , whereas the isotopicderivatives of the latter—KC21RBCs werewashed and stored in 0.9% sodium chloride solution supplemented with0.2% sucrose, and the pH was adjusted to 7.4 using 1 M hydrochloricacid in order to keep the cells in functional conditions, as previouslypublished.ex tempore, as described previously,23 with the followingcomposition: 140.5 mM NaCl, 2 mM CaCl2, 4.7 mM KCl, 1.2mM MgSO4, 21 mM Tris base, 5.5 mM glucose,and 76 μM bovine albumin. All reagents were dissolved in distilledwater and filtered through a 0.22 μm pleated filter; the pHwas adjusted to 7.40 using 1 M hydrochloric acid. All the above-mentionedchemicals were purchased from Sigma-Aldrich.The Ringer-Tris buffersolution used to wash RBCs was prepared g, 4 °C, with 0.9%sodium chloride solution supplemented with 0.2% sucrose and the pHadjusted to 7.4. The supernatant and the buffy coat were removed byaspiration (after each spin). RBCs were suspended in the same solutionin hematocrit (Hct), that is, the volume percentage of RBCs in bloodor solution, approximately 0.1% (what corresponds to about 5 μMof Hb and 20 μM of heme).HumanRBCs were purchased from the Interstate Blood Bank, Inc.. The RBC samples were washed by a triplecentrifugation process at 800g for 15 min at 4 °C),followed by the removal of the supernatant and buffy coat each time.After third centrifugation, the RBCs were diluted 1:4 (v/v) with colddeionized water (4 °C), and the samples were then stored for30 min at 4 °C to allow cell lysis. The lysed cells were thensubjected to final centrifugation at an acceleration of 23,000g for 90 min at 4 °C. The supernatant of the isolatedHb was aspirated and stored at 4 °C. The concentration of Hbin the oxygenated form (oxyHb) was determined using UV–visabsorption spectroscopy. The protein concentrations for rR and UV–vismeasurements were approximately 12.5 μM in the Hb tetramer or50 μM in heme.RBCs were diluted 1:1 (v/v)with 0.9% solution of NaCl and subjectedto triple centrifugation .The supernatant and the buffy coat were removed by aspiration aftereach spin, and the RBCs were washed using a Ringer-Tris buffer solutionsupplemented with bovine albumin and glucose. RI was conducted within8 h after collecting the blood samples. RBCs were diluted to approximately0.1% Hct with the Ringer-Tris buffer solution and transferred to aglass-bottom dish with a CaF2 slide.The RBC samples forRI measurements wereprepared as described previously.2 (10 mM) for 15 min at room temperature,to obtain metHb within functional RBCs. The excess of NaNO2 was then removed from the samples by buffer exchange. The samplesof isolated oxyHb were incubated with 1.2 M excess of potassium ferricyanide(III)to form isolated metHb, followed by purification using size-exclusionchromatography . The purity of isolated and RBC-enclosedmetHb molecules was confirmed by their characteristic spectral profilesin rR and UV–vis measurements.21 To prepare HbCN adducts and its isotopic substituents, samples ofmetHb were treated with a 10-fold molar excess of KCN, K13CN, KC15N, and K13C15N with respectto the heme concentration. The cyanide stock solutions of the respectiveKCN salts were freshly prepared in water alkalized with NaOH to pH9. The cyanide excess was not removed from the samples and was presentduring all measurements. The pH of the samples increased from 7.4to 7.8 in the presence of cyanides.The majority of hemoglobininside RBCs is in an oxygenated form, which is oxyhemoglobin (oxyHb).In order to prepare ferric CN adducts of hemoglobin within an RBC,or in its isolated state, the protein was first oxidized to a ferricstate and then treated with an excess of the corresponding KCN salt.oxyHb was reduced anaerobically to deoxyhemoglobin (deoxyHb) usinga 10-fold molar excess of freshly prepared sodium dithionite, followedby treatment with NaNO+ laser  and collectedusing a 1250M-Series II high-resolution spectrometer with 1250 mmfocal length , equipped with a liquid nitrogen-cooledPyLoN:400B CCD detector . Measurements were done using a 180° backscattering geometry,and the laser beam was focused onto the sample using a cylindricallens. The laser power at the sample was adjusted to approximately5 mW. The spectral resolution was equal to 1.5 cm–1. The 5 mm diameter NMR sample tubes were spun to avoid local heatingand ligand photodissociation. All measurements were conducted at roomtemperature. The slit width was set at 150 μm, and 1200 g/mmgrating was used. The spectra were calibrated using fenchone and acetone-d6 and processed with Grams/32 AI software  and OriginPro 2018 . The spectra were postprocessed  and normalized using z-scores in the whole spectral region (200–2300 cm–1), as reported previously.21The rR spectra were recorded usingthe 406.7 nm excitation line produced by Innova 302C KrUV–visabsorption spectra of all the samples were obtained using a Cary 60UV–vis spectrophotometer  in the range of 200–700 nm. The samples werekept in a quartz cuvette of 1 cm path length. All UV–vis datawere collected at room temperature.–1. The monochromator of the spectrometerwas calibrated with the use of the radiation spectrum from the calibratedxenon lamp (WITec UV light source). Moreover, the standard alignmentprocedure  was performed before each measurementwith the use of the Raman scattering line produced by a silicon plate(520.5 cm–1). Raman measurements and data analysiswere performed using WITec software (WITec Project Plus 2.10) andOriginPro 2018. All the average Raman spectra were postprocessed ,and background subtraction with the asymmetric least-squares method)and normalized using z-scores in the whole spectralregion (200–4000 cm–1). The cluster analysis(CA) presented in this work was carried out after cosmic spike removaland background subtraction in the Manhattan distance formulation.RI was performed using a WITec confocalCRM alpha 300 Raman microscope . The spectrometerwas equipped with an air-cooled solid-state laser operating at 488nm, with the power in the focus spot equal to 100 μW, and anAndor Newton 970 CCD detector cooled to −60 °C. The laser was coupled to the microscopeby an optical fiber with a diameter of 50 μm. A water-immersiveNikon Fluor (60×/1.00 W) objective was used. Spectral resolutionwas equal to 3 cm13CN–, C15N–, and 13C15N– isotopes, tocorrectly determine the frequencies of the modes associated with theFe–C≡N fragment, as well as their isotopic shifts. Whilethe difference traces produced clear CN– isotopepatterns, the isotopic shifts in the low-frequency region are significantlysmaller than the bandwidths of the associated modes. To determinethe frequencies of the ν(Fe–CN) stretching mode and theδ(Fe–CN) bending mode, as well as the values of theirisotopic shifts, the deconvolution procedure had to be employed. Weused a peak fitting procedure provided by OriginPro 2018 and CompareVOA software, and the fitting wasperformed employing the Lorentzian function. The number of peaks wasrestricted only to the modes associated with ν(Fe–CN)or δ(Fe–CN). The intensities and frequencies of the peakswere allowed to change during the iteration cycles, whereas the bandwidthwas fixed at 12 cm–1. This bandwidth was chosenbased on the unrestricted fitting of strong and isolated modes inthe absolute spectra of HbCN, such as the ν7 mode.The details of the peak fitting procedure were previously publishedand are described in detail elsewhere.29The ν(Fe–CN) stretchingor δ(Fe–CN) bending modes has very low intensities inthe absolute rR spectra and overlaps with the heme modes, making itdifficult to obtain the correct frequencies of these modes. We employednaturally abundant CN and its isotopic analogues, namely, the – by different forms of hemoglobinwas studied using electronic absorption spectroscopy. The UV–visabsorption spectra of oxyHb and deoxyHb did not lead to any further spectral changes (data not shown). SimilarUV–vis response to the addition of CN– wasobserved in the experiment performed using isolated metHb are presented in Figure S1 in the Supporting Information and were characterized by the absence of any differences comparedto the spectrum of HbCN itself.The binding of CNin metHb 1C resulted metHb 1D, where– ions. Although in living RBCs, human Hb exists mainly in its oxyform and the metHb accounts only for approximately 1% of the wholeHb content in healthy conditions,34 cyanide poisoning leads to the reaction of CN– with a very small fraction of human Hb. Such hemoglobinCN adducts formed are unable to bind and transport oxygen moleculessimilar to naturally occurring metHb, that is, this physiologicallynonfunctional Hb is not more toxic than metHb itself.9 Actually, the main target of CN– duringcyanide poisoning is another ferric heme protein and one of the majorrespiratory chain enzyme—cytochrome oxidase a3—whoseblockage leads to an impairment of oxidative phosphorylation withinthe mitochondria and in consequence cytotoxic anoxia.35The electronic absorption dataprovide convincing evidence thatthe cyanide ions do not effectively bind to the oxy/CO adducts ofhemoglobin. In fact, oxyHb must first be chemically oxidized to its ferric form to effectively bind CN362 (10 mM) and later exposed to KCN (100-fold molar excess).Although the excitation line used in the RI experiment was 488 nm,away from the Soret band maximum of the CN– adducts,the intense ν4 and ν10 heme modeswere strongly enhanced, allowing effective monitoring of the distributionof the Hb molecules. As can be seen on the visual image ; therefore, the image presentedin panel D shows the distribution of the surrounding buffer solutionand further confirms that the RBC membrane remained intact. The Raman K-means CA image presented in 4 and ν10 modes,together with the CA image, show that the HbCN adducts are presentexclusively inside the RBCs and that there are no detectable amountsof protein in the surrounding buffer solution, that is, the RBCs exposedto high concentrations of CN salt remain intact.The development ofconfocal microscopy and its combination with Raman spectroscopy allowsRI of biological samples, such as RBCs, with high resolution.al image 2A, despi–1 range. In order to investigatethe properties of the Fe–C–N fragments and differencesin their geometries, the rR spectra were measured in the presenceof natural-abundance CN–, as well as in the presenceof 13CN–, C15N–, and 13C15N– isotope substituents.The rR spectra of RBC samplescontaining hemoglobin CN adducts were compared with that of isolatedHbCN protein. The samples were first oxidized, as described in the 38 The high-frequency rR spectra of RBC containing HbCN adducts andCN– isotopes are shown in Figure S2 in Supporting Information, panel A. The 406.7 nmexcitation line used for rR enhancement was in close proximity tothe maximum of the Soret band of the HbCN adducts. The most dominantrR band, the ν4 mode, is seen at 1378 cm–1 and is characteristic of the ferric oxidation state.39 The spin-state marker modes, ν3, ν2, and ν10, at 1509, 1587, and 1644 cm–1, respectively, are typical for low-spin heme species.40 As expected, the CN–13CN, CN–C15N, and CN–13C15N difference traces did not reveal the CN–-sensitive modes in this region. The corresponding rR spectra weremeasured for the samples of isolated HbCN protein , and no differences were observed between the spectra of free proteinand Hb molecules enclosed inside RBCs. It is noted that these rR dataare in good agreement with previous rR studies on isolated Hb protein.12Cyanide is a strong field ligand with a high affinity to ferricHb; thus, HbCN adducts are characterized by high stability and a populationof LS ferric heme.13CN, C15N, and 13C15N isotopic analogues, and the CN–13CN, CN–C15N, and CN–13C15N differencetraces (Panel A). The rR spectra are normalized to the dominant ν7 mode located at 678 cm–1. The ν(Fe–CN)stretching mode is seen around 452 cm–1, in a regionwhere this mode is typically observed in histidine-ligated heme proteins.41 The rR spectra of 13CN-, C15N-, and 13C15N-labeled samples reveal a monotonic downshift of theν(Fe–CN) stretching mode. The monotonic downshift isfurther confirmed by the CN–13CN, CN–C15N, and CN–13C15N differencetraces that are shown in 13CN, C15N, and 13C15N is typically associated with the adoption of theFe–C≡N fragment’s tilted or “essentiallylinear” conformation. This nearly linear geometry is characterizedby the slightly tilted conformation of the Fe–C≡N linkagerelative to the heme normal, which is perpendicular to the heme macrocycleplane. Such distortions are typically induced by steric or electronicfactors present in the heme active site and usually result in theactivation of the δ(Fe–CN) bending mode.–1. The most pronounced differenceis seen at 384 cm–1 in the CN–13CN and CN–13C15N traces. The positiveand negative difference peaks are especially pronounced in the CN–13CN and CN–13C15N traces, meaningthat the mass of carbon has a much more significant effect on Fe–C≡N-associatedvibrations than the mass of nitrogen.12 The frequency and the value of the isotopic shift of this mode furtherwarrant its assignment to the δ(Fe–CN) bending mode.The additional smaller difference patterns observed in this regionarise probably from the vibrational coupling of the δ(Fe–CN)bending mode with the in-plane porphyrin skeletal modes of Eu geometry, as reported previously.15A careful inspection of the difference traces revealedseveraladditional difference patterns with lower intensities in the regionbetween 300 and 450 cm13CN, CN–C15N, and CN–13C15N difference traces reveal that the frequenciesand the apparent isotopic shifts of modes associated with the Fe–C≡Nunit are very similar to those observed in the spectra of HbCN enclosedin the living cells. It is noted that the rR spectra of both HbCNforms, isolated and RBC-enclosed, resemble the rR spectra of previouslypublished protein quite closely. The frequencies of the heme modesand the isotope-sensitive modes are summarized in In order to evaluate the differences in the active site geometrybetween Hb enclosed within a living RBC and that of the isolated protein,the rR spectra of the CN adducts of hemoglobin extracted from theRBC were studied. The low-frequency region of the rR spectra of HbCNand its isotopic analogues are displayed in – is seen at452 cm–1  stretching mode should shift by 5.7, 5.8,and 11.1 cm–1 for 13CN, C15N, and 13C15N, respectively, instead of theobserved corresponding shifts of 8, 9, and 12 cm–1  and isolated protein (panel B)that were fitted with peaks based on the Lorentzian band shape. Thesimulated traces resemble very well the experimental difference traces,allowing to obtain the actual isotopic shifts. The calculated isotopicshifts are now in good agreement with the theoretical values obtainedbased on the diatomic oscillator approximation. While both ν(Fe–CN)frequencies in the HbCN enclosed in RBC and isolated proteins arenow clearly at 454 cm–1, the isotopic shifts ofν(Fe–CN) inside RBCs are slightly smaller (1 cm–1) compared to the adducts of isolated Hb protein. Furthermore, thesmall difference patterns present below 450 cm–1 in the CN–13CN and CN–13C15N traces were reliably reproduced using the fitting procedure.The band located at around 357 cm–1 was not isotope-sensitive;thus, it has to be associated with the porphyrin vibration and wasassigned to the ν50 mode (not shown).41 The extracted frequency of the δ(Fe–CN) mode in theHbCN sample within RBCs was found to be 382 cm–1. This mode shifted to 378 and 377 cm–1 upon substitutionwith 13CN– and 13C15N–, respectively.In order to extract the correct frequenciesand exact values ofthe isotopic shifts of these modes, the difference traces were deconvolutedand fitted with appropriate functions. –1 and exhibitsslightly smaller isotopic shifts of 3 and 4 cm–1 for 13CN– and 13C15N– substitutions, respectively. In summary, althoughboth HbCN samples, isolated and RBC-enclosed, exhibit identical frequenciesof the ν(Fe–CN) stretching modes, their correspondingδ(Fe–CN) bending modes are at a different frequency andexhibit slightly different values of their isotopic shifts. Such deviationsindicate changes in the degree of the distortion of the Fe–C≡Nfragment, resulting most probably from the subtle alterations of theheme active site structures of Hb in isolated form and that of Hbenclosed in the living RBC that might arise from higher ordering andtighter packing of Hb protein inside RBCs. One can envision that asthe quaternary structure of Hb prevents the sterically unhinderedlinear configuration of the exogenous ligands along the heme axis,17 Hb enclosed within RBCs provide even less spacein the heme active site, leading to a higher distortion and tilt ofthe Fe–C≡N linkage. In fact, a relatively recent workby Wood et al., in which Raman spectra were collectedwith parallel and perpendicular polarized excitation lines, suggestedthat the Hb molecules enclosed in RBCs undergo significant ordering47 which might result in an altered conformationof the heme prosthetic group. This proposal is in line with earlierstudies by Pertuz,48 in which the authorsuggested that the high concentration of Hb in RBC (34%) results ina highly packed, semicrystalline state. The small changes observedhere in the active site might also account for the physiologicallyrelevant differences in activity or ligand affinity of Hb moleculeswithin RBCs and in their isolated state.51Interestingly, for samples of isolated HbCN, theδ(Fe–CN)mode is now established to be at 380 cm–1. As can be seen from the inspectionof difference traces, this mode shifts by 47, 31, and 78 cm–1 upon 13CN, C15N, and 13C15N substitutions, respectively. This isotopic zig-zag pattern of theν(C≡N) mode is in agreement with the assignment of theFe–C≡N conformation to the “essentially linear”or tilted geometry. Interestingly, in this region, another isotope-sensitiveline was observed, that is, the mode at around 1825 cm–1 shifts approximately 9 cm–1 to a lower frequencyregion upon 13C15N substitution. We tentativelyassign this band to a combination mode of the ν4 oxidationstate marker and the ν(Fe–CN) stretching mode (1378 +454 = 1822 cm–1). Although the observed 1825 cm–1 mode is seen at a higher frequency than it is expectedfor a ν4 + ν(Fe–CN) combination mode,its apparent upshift arises at relatively small isotopic shifts ascompared to the bandwidths of the Raman bands. Consequently, the peaksare seen at a higher frequency and exhibit larger-than-expected isotopicshifts, vide supra. The spectral parameters of theisotope-sensitive modes for HbCN adducts within RBC and for isolatedproteins are summarized in – does not cause any morphological changesto the studied RBCs. UV–vis absorption spectroscopy showedclearly that the CN– ions bind only to the ferricHb and do not react with either oxyHb or deoxyHb species inside functionalRBCs. The rR studies of HbCN adducts and its isotopic analogues  allowed forthe first time clear characterization of the vibrational modes associatedwith the Fe–C≡N fragment inside living cells. The datawere compared with the spectra of isolated proteins. Deconvolutionof the spectral data allowed deciphering correct frequency valuesof the ν(Fe–CN) stretching and δ(Fe–CN)bending modes. It was found that the ν(Fe–CN) modes havethe same frequencies in both the isolated and RBC-enclosed hemoglobinmolecules. However, small differences were observed in the frequenciesand values of the isotopic shifts of the δ(Fe–CN) bendingmodes. The data indicate that although the overall tilted conformationof the isolated HbCN is preserved in HbCN enclosed within living cells,there is a small difference in the degree of the axial distortionof the Fe–C≡N fragment, which might arise from the highordering and tight packing of Hb molecules inside RBCs.The formation of HbCN adducts inside living functional RBCs wasconfirmed using RI, which shows that the presence of high concentrationsof CN


Single-cell RNA sequencing combined with spatial information on landmark genes enables reconstruction of spatially-resolved tissue cell atlases. However, such approaches are challenging for rare cell types, since their mRNA contents are diluted in the spatial transcriptomics bulk measurements used for landmark gene detection. In the small intestine, enterocytes, the most common cell type, exhibit zonated expression programs along the crypt-villus axis, but zonation patterns of rare cell types such as goblet and tuft cells remain uncharacterized. Here, we present ClumpSeq, an approach for sequencing small clumps of attached cells. By inferring the crypt-villus location of each clump from enterocyte landmark genes, we establish spatial atlases for all epithelial cell types in the small intestine. We identify elevated expression of immune-modulatory genes in villus tip goblet and tuft cells and heterogeneous migration patterns of enteroendocrine cells. ClumpSeq can be applied for reconstructing spatial atlases of rare cell types in other tissues and tumors. Combining scRNA-seq with spatial information to enable the reconstruction of spatially-resolved cell atlases is challenging for rare cell types. Here the authors present ClumpSeq, an approach for sequencing small clumps of tissue attached cells, and apply it to establish spatial atlases for all secretory cell types in the small intestine. Spatially varying concentrations of oxygen, nutrients, and morphogens along these units dictate distinct gene expression signatures for cells residing at different spatial coordinates, a phenomenon termed “zonation”1. Approaches to spatially reconstruct zonation patterns combine scRNAseq with spatial expression profiles of landmark genes characterized by RNA in situ hybridization6. An alternative approach, when no prior knowledge of landmark gene candidates exists, entails the spatial measurements of the complete transcriptome of small tissue regions, isolated using laser capture microdissection (LCMseq)7. While these approaches successfully reconstruct the zonation patterns of the major cell types in a tissue, rare cell types are more challenging, since their transcript contents are diluted in the spatial measurement techniques.Many tissues such as the liver, the intestine, and the kidney, are composed of structured anatomical units8. This approach relies on the prospective isolation of mixed pairs, requiring unique surface markers for the cell types of interest, markers which do not generally exist. Reconstructing zonation patterns of rare tissue cells, therefore, remains an open challenge.A recent approach for sequencing pairs of attached cells enabled reconstructing the zonation patterns of liver endothelial cells, by utilizing the landmark genes of their attached hepatocytes9. Around 90% of the differentiated epithelial cells are absorptive enterocytes. LCMseq-guided single-cell reconstruction revealed profound zonation of enterocyte gene expression along the villus7. Additional secretory epithelial cell types include mucus-producing goblet cells11 (~8%), hormone producing enteroendocrine cells12 (~1%) and chemosensory tuft cells14 (~1%). These rare cell populations are important for the protection of the tissue and for communication with other stromal cell types and with other organs15. Using a reporter mouse model, Clevers and colleagues reconstructed the temporal expression programs of enteroendocrine cells along the crypt-villus axis12, however, zonated expression patterns of goblet and tuft cells are unknown.In the small intestine, epithelial cells operate in repeating crypt-villus units Fig. . Crypt-hTo overcome the limitations in reconstructing spatial expression profiles of rare cells, we present ClumpSeq, an approach for sequencing small clumps of attached tissue cells. Sequencing clumps increases the capture rate of rare cell types without the need for antibody enrichment, and utilizes the spatial information of the major tissue cell type. We use this approach to reconstruct spatial maps of all intestinal secretory epithelial cell types along the crypt-villus axis, revealing zonated immune-modulatory programs and heterogenous migration patterns.ClumpSeq entails the sub-optimal dissociation of the epithelium into small clumps of 2–10 cells Fig.  and sequ16 for sequencing their transcriptomes. The resulting clumps exhibited zonation patterns, as evident by the distinct expression in different clumps of the crypt , and Paneth cells markers were almost exclusively found in crypt clumps  and stained for DNA content using Hoechst dye. We used fluorescence-activated cell sorting (FACS) to select clumps based on the DNA content Fig. . We sortypt Fig. , bottom ypt Fig. , mid-vilypt Fig.  and villypt Fig. . In addiypt Fig. , enteroeypt Fig. , tuft ceypt Fig.  and Paneypt Fig. . The fra7. We next used scRNAseq datasets18 to identify genes that are expressed at high levels in the secretory cells of interest and at low levels in enterocytes. The transcripts of these genes in clumps likely originate from secretory cells rather than from enterocytes. Among these secretory cell-specific genes, we identified sets of landmark genes that decreased or increased in expression from the crypt bottom clumps toward the villus tip clumps .We first applied our approach to goblet cells, the most abundant secretory cell type in the intestineAgr2, a gene hypothesized to be secreted in molar quantities with Muc210, which we found to be inversely zonated toward the crypt. This finding of an anticorrelated zonation profile supports the hypothesis that Agr2 may play additional roles in goblet cells, for example in goblet cell maturation at the crypt19. Our analysis revealed zonation of ligands, receptors20, and transcription factors21 in goblet cells .Tuft cells are rare chemosensory epithelial cells with important functions in mediating type-2 immunity, most notably against intestinal worm infectionsSox4, previously shown to be important for Tuft cell specification25. Tuft cells at the villus tip expressed the fatty acid binding protein 1 (Fabp1) and the succinate receptor 1 (Sucnr1), suggested to act as a sensor for infectious agents26 . The zonated expression patterns conformed with previous observations of crypt-biased expression of Gcg, Tac131, and Reg432, and villus-biased expression of Sct and Nts30  that consist of diverse subtypes of hormone-secreting cells that are essential for physiological homeostasis. We next applied ClumpSeq to extract landmark genes for these cells. We extracted 656 enteroendocrine landmark genes from our 181 enteroendocrine-containing clumps , different enteroendocrine genes exhibited distinct behavior in space-time . The discordant space-time profiles, with crypt retained expression of relatively late appearing genes, suggest that enteroendocrine cell types such as L-cells and D-cells have slower crypt-villus migration rates compared to the Cck+ I-cells and the Gip+ K-cells. We further used smFISH to validate that Pyy and Afp, two enteroendocrine genes with late time stamps are enriched at the crypt and villus bottom . Similarly to ClumpSeq, both methods need to be integrated with scRNAseq datasets in order to properly analyse the rare cells of interest. However, pre-requirements differ, as Slide-seq and HDST both work on fresh-frozen slides and require barcoding beads on a glass surface, while ClumpSeq uses freshly dissociated tissue with the clumps sorted in 384-well capture plates. Unlike Clumpseq, the spatial transcriptomics methods sequence thin tissue sections that often do not include complete cells, potentially posing challenges in the characterization of individual rare cell types.Recently, two powerful methods were developed for measuring spatial information with single-cell resolution, Slide-Seq43 and the zonation patterns of pancreatic endocrine cells along the radial islet axis44. ClumpSeq could also be adapted to assess the range-dependent effects of developmental organizers45 and tumor signaling centers46, thus expanding the toolbox of single cell biology beyond single cells and pairs.ClumpSeq can be applied to diverse tissues and cell types, for example, the analysis of lung goblet and tuft cell diversity in spatially-distinct airwaysad libitum. All experiments were performed on the same region of the Jejunum. Mice were sacrificed by cervical dislocation.All mouse experiments were approved by the Institutional Animal Care and Use Committee of the Weizmann Institute of Science and performed in accordance with institutional guidelines (Protocol number 13000419-2). Experiments were conducted on 8–12 weeks old C57BL/6 mice, obtained from Envigo. Mice were housed at 4–5 per cage, maintained at a constant temperature of 22 ± 2 °C and humidity of 55 ± 15%, exposed at all times to a 12 h light/12 h dark cycle and had access to food and water g for 5 min at 4 °C. Pellet was resuspended and incubated for nuclear staining for 5 min at RT in a solution of DMEM + 10% FBS + 10 mM HEPES + Hoechst 33342 (15 μg ml−1). To prevent the cells from pumping out the Hoechst dye, Reserpine (5 μM) was also added. Cells were resuspended in PBS and Alexa Fluo 488 Zombie Green (BioLegend) was added at a dilution of 1:500, to later enable the detection of viable cells by FACS. Cells were kept in a rotator in the dark at room temperature for 15 min. After spinning down (500 × g. for 5 min at 4 °C), cells were resuspended in FACS buffer  at a concentration of 106 cells in 100 μl.The Jejunum was harvested, flushed with cold 1× DPBS, laterally cut, and incubated for 20 min on ice in a 10 mM EDTA solution. Afterward, the tissue was cut into 1 cm pieces, moved in a pre-warmed 10 mM EDTA solution for 5 min and shaked vigorously at the end of the incubation time. Dissociated cells were collected and filtered through a 100 μm cell strainer. Cells were spun down at 300 × g for 5 min at 4 °C. Cells were resuspended in FACS buffer and stained with combination of APC-anti-Epcam  and PE/Cy7-anti-CD45  or APC-anti-Epcam and PE/Cy7-anti-CD24 . FcX blocking solution (BioLegend) was added at a dilution of 1:50.To obtain single cell suspension, rather than clumps, the tissue was incubated for 10 min on ice in a 10 mM EDTA solution, before to be cut in small pieces and moved for other 10 min in a pre-warmed 10 mM EDTA solution. The tissue was shaked vigorously every 2 min. Cells were filtered through a 70 μm cell strainer and spun down at 300 × TM software (BD Biosciences) using a 100 μm nozzle. For clumps sorting, dead cells were excluded using the Zombie green staining and clumps were sorted based on Hoechst histogram  reverse-transcription (RT) primers for single-cell RNA-seq. Barcoded single cell capture plates were prepared with a Bravo automated liquid handling platform (Agilent) as described previously16 Briefly, mRNA from cells sorted into MARS-Seq capture plates were barcoded and converted into cDNA by reverse transcription reaction and pooled using an automated pipeline. The pooled sample was cleaned using 0.9X SPRI beads and then linearly amplified by T7 in vitro transcription. The resulting RNA was fragmented and converted into sequencing-ready library by tagging the samples with pool barcodes and Illumina i7 barcode sequences during ligation, reverse transcription, and PCR. Each pool of cells was tested for library quality and concentration was assessed as described in Keren-Shaul et al.16 Machine raw files were converted to fastq files using bcl2fastq package, to obtain the UMI counts. Using STAR (v.2.5.3a) reads were aligned to the mouse reference genome (GRCm38.84) using zUMI packge4547 with the following flags that fit the barcode length and the library strandedness: -c 1-7, -m 8-15, -l 66, -B 1, -s 1, -p 16.Single cell libraries for both single cells and clumps were prepared, as described in Keren-Shaul et al.For each single cell or clump and for each gene we performed background subtraction. The background was calculated for each 384-well plate separately, as the mean gene expression in the four empty wells. After subtraction, negative values were set to zero. We used Seurat v3.2 package in R v3.6.1 and R studio v1.2.2019 to cluster the clumps and single cell RNAseq datasets, retaining only clumps or cells containing at least 200 genes. We used Seurat to regress out cell-cell variation driven by the fraction of mitochondrial genes. For clumps, we excluded clumps with over 30% mitochondrial genes. Clustering was based on PCA dimensionality reduction using the first 18 PCs, and a resolution value of 1.Epcam in the epithelial cells clusters, Ptprc in immune clusters, Muc2 in the goblet cluster, Dclk1 in the tuft cluster, Chga in the enteroendocrine cluster  and aspect ratio (the Minor Axis divided by the Major Axis of the best-fit ellipse). To distinguish between large cells and small clumps with similar size, the circularity feature was used —high circularity was correlated with large cells rather than cell clumps. This was calculated using the Object cell mask , to better delineate cell morphology. To distinguish between pairs and larger clumps, objects were gated according to the area and aspect ratio  of the Hoechst staining. To validate that cell clumps contain more than one EpCAM positive cell, two features were calculated—the area of the EpCAM staining divided by the bright-field area, and the distance between the geometrical centers of the EpCAM staining and the bright-field image, using the Delta Centroid XY feature. Clumps with higher area ratio and lower distance were eventually chosen.Cells were imaged by an Imaging Flow Cytometer . Data were acquired using a ×40 lens, and lasers used were 405 nm (10 mW), 488 nm (100 mW), 642 nm (100 mW), and 785 nm (5 mW). Data were analyzed using the manufacturer’s image analysis software IDEAS 6.2 (AMNIS corp.). Images were compensated for spectral overlap using single stained controls. Viable cells were first gated as negative for the dead cell marker Zombie-Green. To eliminate out-of-focus cells, cells were further gated using the Gradient RMS and contrast features . Then, cell were gated for single cells and cell clumps according to their area  and washed twice with 2× SSC (Ambion AM9765). Tissues were incubated in wash buffer  for 5 min and mounted with the hybridization buffer  mixed with 1:3000 dilution of probes. Hybridization mix was incubated with tissues overnight in a 30 °C incubator. SmFISH probe libraries . The intestinal sections were hybridized with smFISH probe sets according to a previously published protocol48. Goblet cells were manually segmented based on Muc2 or Clca1 expression. Each transcript quantification was based on at least 5 entire villi from at least 2 mice. Tuft cells were manually segmented using Dclk1 mRNA expression. Results were based on at least 20 cells from bottoms and tips of villi and from at least 2 mice. Enteroendocrine cells were identified based on the expression of the specific gene measured. Each villus was divided into bottom, middle and tip as follow: Ada+ area is defined as “villus tip”, the remaing villus length is divided equally in two zones, middle and bottom. Fisher exact test was calculated on the number of crypt-villus units with and without cells expressing the analyzed gene. mRNA concentration  or mRNA signal intensity  was computed per cell.Quantification of smFISH was done using ImageM18, using cell type annotations by the papers’ authors. Gene expression measurements (UMIs per gene) were normalized for each cell by the sum of its UMIs and then averaged across single cells by type. For enterocytes, we averaged cells from each villus zone using Moor et al. annotation7. The same single cell data source was also used for generating the crypt stem cells columns of Supplementary Data 618. For other secretory cell types: goblet, enteroendocrine, tuft and paneth cells, we used the data from Fig. 17.In order to find genes specific to the intestinal epithelial cell types, we comprised a table of mean expression of genes across cell types and the percentage of single cells of each cell type expressing each gene . 4,788 clumps with over 500 UMIs were retained and expression values per gene were calculated as UMIs per gene normalized for each clump by the total sum of its UMIs.UMI counts table for all 5,297 clumps was exported from Seurat7. There, gene zonation was reconstructed for the crypt and 6 villus zones (V1–V6) using single enterocytes. Candidate landmark genes were required to satisfy the following requirements: (1) Abundance—having a mean normalized expression across zones of 5 × 10−4 or more. (2) Enterocyte specific: having mean expression in any enterocyte/stem-cell population higher than 10-fold the maximal mean expression in all secretory cell types and expressed in at least 10% of that enterocyte population. (3) Zonated—having at least 70% difference between maximal and minimal expression along the crypt-tip axis.Enterocyte landmark genes for clumps zonation reconstruction were based on the enterocyte zonation table in Moor et al.In order to select an informative set of landmark genes which includes crypt, mid-villus and villus tip markers, we calculated for all candidate landmark genes the Euclidean distances to “ideal” land mark profiles as follows: Ideal crypt landmark profile: expression value 1 in the crypt and 0 for all other zones; Ideal mid-villus land mark profile: expression value 1 in the middle of the villus (V3) and 0 for all other zones; Ideal tip land mark profile: expression value 1 in the tip and 0 for all other zones. Finally, three lists of enterocyte landmark genes were comprised: the crypt list with the 30 candidate landmarks with lowest distance from “ideal” profile 1, the mid-villus list with the 30 candidate landmarks with lowest distance from “ideal” profile 2 and the tip-villus list with the 30 candidate landmarks with lowest distance from “ideal” profile 3. If genes overlapped between the lists, they were assigned to the list of the “ideal” profile they were closest to. The selected landmark genes are shown in Supplementary Data 7 as a spatial reference as follows.Based on Supplementary Data P values were calculated with the Kruskal–Wallis test . q values were calculated using the Benjamini and Hochberg method (implemented in the MATLAB function mafdr), applied to all genes for which maximal expression across zones exceeded 5 × 10−6 . For each secretory type, all genes meeting these criteria were ordered by their specificity ratio in descending order and up to 50 first genes were selected as type markers. Enterocyte markers , the expression levels of its classification markers were summed in each clump. These sums were converted to Z scores by subtracting the mean and dividing by the standard deviation across clumps. This process projected the clumps into a 4-dimensional space spanned by the sums of secretory cell type markers. We next performed principal component analysis on these shifted and scaled sums (implemented in the MATLAB function pca). This resulted in three principal components (PCs) that define a 3D position for each clump in PC space. For each PC, the median was subtracted in order to shift the origin of the PCs to the origin of axes. In PC space, the clumps were now arranged on four lines or rays emanating from the origin Fig. . Clumps We fitted a line to each of the secretory type rays. For the fit, we sorted clumps according to their distance from the origin and considered only clumps with distance above the 99 percentile. Fit was performed using a least square fit method implemented in a custom MATLAB script. Each ray was assigned to the secretory type, the markers of which peaked along it , were defined as genes for which the mean expression in the secretory cell type was higher than 3-fold the maximal mean expression in all enterocyte populations and were expressed in at least 1% among cells in that secretory cell type. Calculation of zonation table proceeded as previously described for all clumps  and of the tip landmark genes (denoted Y) was calculated. These sums were than used to calculate a unit-less spatial coordinate: (1) η = Y/(X + Y) for each clump. This yielded a distribution of η values for each zone in secretory cell-containing clumps.For each single secretory cell used for reconstruction, the spatial coordinate η was calculated as in step 3.We performed single cell zonation reconstruction as described in steps 7–8For each secretory specific gene (defined in step 1), the zonation profile in the current reconstruction was compared to the zonation profile in clumps: the Euclidean distance between the two profiles was calculated after both were normalized by their maximal values.Euc.The median over genes of this distance was calculated and denoted as MedEuc was selected as optimal.The set of η limits yielding the smallest MedIn order to assign each single cell to a zone based on it’s η, η limits for the zones were calculated using an optimization method—reconstruction was performed using a wide range of possible η limits options (see step 6 for details). The set of η limits that yielded zonation profiles of secretory specific genes which best fit the clumps profiles was selected. Specifically, for each possible set of η limits:minThe lowest possible upper bound on η for crypt was set to the median of η values of crypt clumps—calculated in step 3. We denote this number as ηη, was determined.The resolution of η optimization denoted DVec, was created: a regularly-spaced vector starting at ηmin and ending in 1, using Dη as the increment between elements. ηVec elements were therefore:  where m = (1 −η min)/Dη).A vector of all considered η limit values, ηVec taken Nzones−1 (Nzones is the number of desired zones for the reconstruction) at a time were calculated. Each such combination is an optional set of η limits, with a zero added in the beginning and one appended at the end. For example, if the reconstruction is to be done for 4 zones, each such optional set of η limits would be: 0, ηVec1, ηVec2, ηVec3,, 1. With ηVec1, ηVec2, ηVec3 being one of the combinations of ηVec values- such that ηVec1 < ηVec2 < ηVec3.All possible combinations of the elements of ηAll sets of η limits which yielded less than 10 single cells in some zone were discarded and not considered in the optimization described in step 5.All η limit sets that were considered in the optimization described in step 5 were calculated as follows:Each single cell was assigned to a zone based on the optimal η limits selected as described in step 5.The expression values of all the single secretory cells in each zone were averaged for each gene, to obtain the zonation table of genes in the secretory cells.P values for zonation per gene were calculated with the Kruskal–Wallis test . q values were calculated using the Benjamini and Hochberg method (implemented in the MATLAB function mafdr), for all genes for which expression exceeded 5 × 10−6.For goblet, enteroendocrine and tuft cells, we used the clump-based zonation tables to find zonated, secretory-specific landmark genes. We then used the expression patterns of these landmark genes to assign single sequenced secretory cells to crypt-villus zones, grouped them and averaged their expression, thus obtaining zonation tables of all genes for each secretory cell type. The method we used for single cell reconstruction is similar for all three secretory types, with slight differences in landmark gene selection criteria and the spatial resolution of the reconstruction between goblet cells and the other secretory cell types. The reason for these differences stemmed from the substantially higher goblet cell abundance in the tissue and therefore in clumps, compared to other secretory cell. This enabled performing the reconstruction with finer spatial resolution for goblet cells. For all secretory types, single cell reconstruction consisted of the following steps, secretory type specific parameters and variations on this general method are detailed in the next sections:50.Single cells used for zonation reconstruction were from scRNA-seq experiments on intestinal cells, performed using the MARS-seq protocol  of a gene’s spatial expression profile across the zones 1,2,..N with respective expression values per zone of E−5.Maximal expression across zones in clumps zonation Supplementary Data Crypt markers: COM < = 3, expressed in at least 2 clumps in the crypt.Tip markers: COM > = 4.7, expressed in at least 2 clumps in the tip most zone.Goblet cell specific landmark genes based on clumps data (steps 3–4 in the previous section) were selected based on the following criteria:η (step 6b in the previous section) was set to 0.05.This resulted in 309 crypt markers and 62 tip markers listed in Supplementary Data 12. UMI count table for the single cells was downloaded from Gehart et al.12 (GEO: GSE113561) and parsed in MATLAB. Expression values per cell were normalized by dividing by the overall sum of UMI for each cell. Cells marked as excluded in the metadata supplied by the authors were removed. Enteroendocrine specific landmark genes based on clumps data (steps 3–4 in previous section) were selected based on the following criteria:−5.Maximal expression in clumps zonation Supplementary Data Crypt markers: COM < = 1.8, expressed in at least 2 clumps in the crypt.Tip markers: COM > = 4.2, expressed in at least 2 clumps in the tip most zone.Single cells used for zonation reconstruction were taken from Gehartη (step 6b in the previous section) was set to 0.02.This resulted in 636 crypt markers and 20 tip markers listed in Supplementary Data P values for temporal profiles per gene were calculated with the Kruskal–Wallis test . q values were calculated using the Benjamini and Hochberg method (implemented in the MATLAB function mafdr).To obtain the temporal profile of enteroendocrine gene expression Fig. , time st17. Zonation reconstruction was performed separately for these two single cell datasets and consequently merged. Tuft cell-specific landmark genes based on clumps data (steps 3-4 in previous section) were selected based on the following criteria:−5.Maximal expression in clumps zonation Supplementary Data Crypt markers: COM < = 1.8, expressed in at least 2 clumps in the crypt.Tip markers: COM > = 4.2, expressed in at least 2 clumps in the tip most zone.Our single cell MARS-seq protocol yielded mainly villus tuft cells. We, therefore, combined our cells with tuft cells from Fig. η (step 6b in previous section) was set at 0.02. The merged zonation table was calculated as the weighted mean of the two zonation tables derived separately from the two datasets with the weights reflecting the relative contribution of each data set per zone in terms of amount of expressing cells.This resulted in 323 crypt markers and 29 tip markers listed in Supplementary Data The single cell reconstruction using only cells from our data was computed.17 was computed.The single cell reconstruction using only cells from Haber et al.−6.i.If there were no mutual zones-and the gene was expressed only in one dataset, the expression in that data set was retained for the merged zonation table.ii.If both data sets had cells expressing the gene, but without sufficient overlap in a single zone the gene was excluded from the merged zonation table.iii.If there were several mutual zones, the mutual zone in which the data sets had the most similar amount of expressing cells was selected.For each gene, the mutual zones between data sets were identified. Mutual zones were defined as zones in which both data sets had 5 or more cells expressing the gene above the expression threshold, set at 5 × 10For each gene, the zonation expression profile in each data set was normalized by the value in the mutual zone.−6).These two scaled profiles were averaged with weights per zone. The weights per dataset per zone were the amount of cells expressing the gene above the expression threshold .For the merged zonation table, the p values were calculated per gene as the minimal 7 zonation table was linearly interpolated for the smaller number of equally spaced zones prior to reconstruction.In order to further validate the single cell reconstructions, we computed the correlation of centers of mass (COM) between single cell and clump-based reconstructions. For this puropose, we coarse-grained the 7-zone clumps zonation tables into the same number of zones as the respective single cell reconstruction. These coarse grained zonation tables were calculated the same way as described for clump to zone assignment, with one difference: the spatial ref. −5) and secretory specific . We further limited ourselves to genes for which the SEM of reconstruction was small enough for both single cells and clumps based reconstructions (below 0.4 for goblet and below 0.5 for tuft). This yielded a similar quantity of genes for goblet and tuft: 30 and 28, respectively.For the validation, we chose genes that were not used as landmarks for single-cell reconstruction and were both highly expressed .For Enteroendocrine cells, such validation was infeasible, due to the various enteroendocrine cell sub-types and their relatively sparse representation in clumps. Instead, single cell reconstruction of spatial zonation was validated against the temporal gene expression patterns derived from the same single cells in Gehart et al.−6), between each reconstruction and the original. We denote this quantity for parameter i and perturbed value j − Pij. We then plotted for each parameter i, the values Pij for j = 1:75. The plotted curves  between the original and perturbed zonation tables as a function of the size of introduced parameter perturbation. To this end, we performed the following for all parameters pertaining to clump secretory type assignment and subsequent single cell reconstructions  and plotted the original and the perturbed reconstructed zonation profiles for 10 selected genes: 5 crypt genes and 5 tip genes . For each gene g and each cluster c we calculated the average expression C1, and C2. The resulting list of interactions was filtered per fraction of cells expressing either the ligand or the receptor (>0.05) and the Ligand-receptor analysis was performed similar to Bahar-Halpern et al.52 was used to visualize bottom and tip interactions. We selected only ligands and receptors with an average expression of either the ligand or the receptor above 2 × 10−5 and CytoscapeFurther information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Supplementary Data 9Supplementary Data 10Supplementary Data 11Reporting Summary


A frozen section diagnosis of a borderline ovarian tumor with suspicious features of invasive carcinoma (“at least borderline” or synonymous descriptions) presents us with the dilemma of whether or not to perform a full ovarian cancer staging procedure. Quantification of this dilemma may help us with the issue of this clinical decision. The present study assessed and compared both the prevalence of straightforward borderline and “at least borderline” frozen section diagnoses and the proportion of these women with a final histopathological diagnosis of invasive carcinoma, with a special interest in histologic subtypes.A retrospective cohort study was performed in three hospitals in The Netherlands. All women that underwent ovarian surgery with perioperative frozen section evaluation in one of these hospitals between January 2007 and July 2018 were identified and included in case of a borderline or “at least borderline” frozen section diagnosis and a borderline ovarian tumor or invasive carcinoma as a final diagnosis.p < 0.001). When compared to straightforward borderline frozen section diagnoses, the proportion of women diagnosed with invasive carcinoma increased from 3.1 to 35.7% for serous tumors (p = 0.001), 10.0 to 21.7% for mucinous tumors (p = 0.129) and 50.0 to 75.0% (p = 0.452) in case of other histologic subtypes following an “at least borderline” frozen section diagnosis.A total of 223 women were included, of which 41 women (18.4%) were diagnosed with “at least borderline” at frozen section. Thirteen of forty-one women (31.7%) following “at least borderline” frozen section diagnosis and 14 of 182 women (7.7%) following a straightforward borderline frozen section diagnosis were diagnosed with invasive carcinoma at paraffin section evaluation . Especially in the serous subtype, full staging during initial surgery might be considered after preoperative consent to prevent a second surgical procedure or chemotherapy in unstaged women. Further studies are needed to evaluate whether additional sampling in case of an “at least borderline” diagnosis may decrease the risk of surgical over-treatment. Borderline ovarian tumors  are composed of mild to moderately atypical epithelial cells that show proliferation greater than that seen in benign tumors, but less than their malignant counterparts. Although usually absent in borderline ovarian tumors, one or more foci of stromal invasion of < 5 mm in the largest linear area might be present and should be classified and treated as borderline ovarian tumor. Mucinous borderline tumors account for approximately 40% of all borderline tumors and serous borderline tumors for approximately 50% , 2. AdeqAnother difficulty of intraoperative consultation in case of ovarian neoplasms may be the fact that it is not always possible for the pathologist to classify frozen section slides as a borderline ovarian tumor or an invasive carcinoma according to the World Health Organization (WHO) criteria . In caseThe data of the present retrospective study was obtained from three hospitals in the Netherlands  after the Medical Ethical Review Committee approved conducting the study. All women who underwent ovarian surgery with perioperative frozen section analysis because of a suspicious adnexal mass in one of these hospitals from January 2007 to July 2018 were identified by searching the PALGA database (the Dutch nationwide histo- and cytopathology data network and archive) .Women were included in case of a borderline ovarian tumor at frozen section and, at final pathology, a borderline ovarian tumor or invasive ovarian cancer. Women with a proven secondary tumor of the ovary  were excluded. Women’s baseline characteristics, the frozen section result and final histopathological diagnosis were retrieved from the patient files and saved into an encrypted database. Regarding the frozen section results, surgical procedure and pathology reports were carefully examined to verify whether the borderline frozen section result could or could not rule out invasive carcinoma. Women with a “rule out borderline” (maximum borderline ovarian tumor) or a decisive borderline ovarian tumor frozen section result (no suspicion of carcinoma) were reported as “borderline”, and women with a borderline ovarian tumor frozen section result in which the pathologist could not rule out invasive carcinoma were reported as “at least borderline”.p-values < 0.05 were considered to indicate statistically significant differences.The data were analyzed with SPSS . The Fisher’s exact test and Fisher-Freeman-Halton test were executed to compare proportions of categorical outcomes according to different independent groups, and In total, 223 women with a median age of 58 years (18–82) were included. Experienced gynaecopathologists are involved in the three participating hospitals. There was clear and extensive communication about the patients’ medical history and the intraoperative findings between gynecologist and pathologist at the time of frozen section. At least 2 samples and slides  and 3 samples and slides  were evaluated during frozen section irrespective of a straightforward diagnosis of a borderline tumor or an “at least borderline” tumor diagnosis.p = 0.033, Fisher-Freeman-Halton test).Based on frozen section analysis, a straightforward diagnosis of a borderline tumor was observed in 182 of 223 women (81.6%) and an “at least borderline” tumor in 41 women (18.4%). When divided based on the histological subtype, 14 of 110 women (12.7%) with a serous tumor, 23 of 103 women (22.3%) with a mucinous tumor and 4 of 10 (40.0%) women with a tumor of a different histologic subtype were diagnosed with “at least borderline” at frozen section .Final diagnosis, based on formalin fixated and paraffin embedded (FFPE) samples, revealed that 27 of these 223 women (12.1%) were diagnosed with invasive carcinoma as a final diagnosis. Of the 196 patients diagnosed with a borderline tumor, 171 (87.2%) had FIGO stage I disease and 25 (12.8%) were diagnosed with stage II disease. Twenty-one of twenty-seven patients (77.8%) with invasive carcinoma as a final diagnosis had FIGO stage I disease, 4 patients (14.8%) stage II and 2 patients (7.4%) stage III. Data on the gross examination of the tumor was available for all 27 upgraded tumors. Twenty of the upgraded tumors contain multiple solid and papillary areas, and most of these areas were sampled extensively. Irrespective of the frozen section result, 8 of 110 women (7.3%) with a serous tumor, 13 of 103 women (12.6%) with a mucinous tumor and 6 of 10 women (60.0%) with a tumor of a different histologic subtype were diagnosed with invasive carcinoma on paraffin section evaluation   and not in case of “at least borderline” frozen section diagnoses . The increase in the risk of discordance was considered significant only in the case of serous tumors   with a borderline frozen section diagnoses and 13 of 41 women (31.7%) with an “at least borderline” frozen section diagnosis (The group of women having tumors with a histologic subtype other than serous or mucinous consisted of 6 endometrioid tumors (3 “at least borderline” at frozen section), 2 Brenner tumors (both straightforward borderline at frozen section), 1 clear cell tumor (“at least borderline” at frozen section) and 1 seromucinous tumor (straightforward borderline at frozen section). Of the six women that showed invasive carcinoma as a final diagnosis, 5 women were diagnosed with an endometrioid carcinoma (3 preceded by an “at least borderline” frozen section diagnosis) and 1 woman with a malignant Brenner tumor (straightforward borderline frozen section). In total, five of 6 endometrioid tumors (83.3%) turned out to be invasive carcinoma on paraffin section evaluation.n = 80), 8 women (10.0%) were diagnosed with mucinous ovarian carcinoma diagnosis and 5 of these tumors (62.5%) showed an infiltrative growth pattern. Following an “at least borderline” frozen section diagnosis of mucinous histology (n = 23), 5 women (21.7%) were diagnosed with mucinous ovarian carcinoma, of which three (60.0%) had shown an infiltrative growth pattern. There was no relation between frozen section result and growth pattern in case of mucinous ovarian carcinoma (p = 1.000).Thirteen women were diagnosed with mucinous ovarian cancer, of which 5 showed the expansile growth pattern (38.5%) and 8 the infiltrative growth pattern (61.5%). Following a straightforward mucinous borderline frozen section . Subclassification of all borderline ovarian tumor frozen section diagnoses into straightforward borderline and “at least borderline” frozen section diagnoses seems to reduce the discordance rate of (straightforward) borderline frozen section diagnoses when compared to the literature (21% vs 7.7%) . When suBecause of the considerable and increased chance of a final diagnosis of carcinoma following a frozen section diagnosis of “at least borderline”, especially in the serous subtype, full surgical staging at the initial surgery in these cases might be considered. Irrespective of the frozen section result (straightforward borderline or “at least borderline”), all but one (5 of 6) endometrioid tumors were diagnosed with invasive carcinoma on paraffin section analysis. However, the number of cases is too low for drawing definitive conclusions. In cases where final diagnosis shows invasive cancer, incomplete staging and the subsequent indication for adjuvant chemotherapy or a second surgical staging procedure, with all its potential consequences, may be avoided by this strategy , 14. HowThere may be some additional reasons to question whether one should perform full staging in cases of a frozen section diagnosis of an “at least borderline” ovarian tumor with a mucinous histologic subtype. The prevalence of women with positive lymph nodes is low in cases of suspected FIGO stage I mucinous carcinoma with an expansile growth pattern 0.9–2.6%). Therefore, some surgeons do not perform a lymph node sampling in these tumors with an expansile growth pattern –12. In t%. TherefHowever, additional sampling in case of an “at least borderline” diagnosis was not performed routinely. Additional sampling might avoid unnecessary full staging surgery, and may indeed prolong the time of intraoperative consultation. The prevalence of “at least borderline” tumor diagnosis in our study was similar as found in the recent systematic review and meta-analysis . In the In conclusion, this study shows that the overall risk of carcinoma following an “at least borderline” frozen section diagnosis is comparable to a recent review and systematic analysis (31.7%), but also that it varies by histologic subtype . Especially in case of serous “at least borderline” frozen section results and endometrioid frozen section diagnoses, there was an increased risk of finding invasive carcinoma as final diagnosis. Furthermore, a considerable number of cases of invasive mucinous carcinomas showed the expansile growth pattern, which have a low change of positive lymph nodes. Thus, full staging at the time of initial surgery might be considered in order to prevent a second procedure for the serous histologic subtype. However, future studies are needed to evaluate whether improvement of sampling protocols  during frozen section examination, as well as finding more differentiating criteria what will lead to specific training of pathologists with respect to discrimination of these tumor categories, could improve the reporting of frozen section diagnostics.