Gliomas are the primary malignant brain tumor and characterized as the striking cellular heterogeneity and intricate tumor microenvironment (TME), where chemokines regulate immune cell trafficking by shaping local networks. This study aimed to construct a chemokine‐based gene signature to evaluate the prognosis and therapeutic response in glioma.In this study, 1024 patients (699 from TCGA and 325 from CGGA database) with clinicopathological information and mRNA sequencing data were enrolled. A chemokine gene signature was constructed by combining LASSO and SVM‐RFE algorithm. GO, KEGG, and GSVA analyses were performed for function annotations of the chemokine signature. Candidate mRNAs were subsequently verified through qRT‐PCR in an independent cohort including 28 glioma samples. Then, through immunohistochemical staining (IHC), we detected the expression of immunosuppressive markers and explore the role of this gene signature in immunotherapy for glioma. Lastly, the Genomics of Drug Sensitivity in Cancer (GDSC) were leveraged to predict the potential drug related to the gene signature in glioma.IDH wildtype. It also played an independent prognostic factor in both datasets. Moreover, biological function annotations of the predictive signature indicated the gene signature was positively associated with immune‐relevant pathways, and the immunosuppressive protein expressions  were enriched in the high‐risk group. In an immunotherapy of glioblastoma cohort, we confirmed the chemokine signature showed a good predictor for patients' response. Lastly, we predicted twelve potential agents for glioma patients with higher riskscore.A constructed chemokine gene signature was significantly associated with poorer survival, especially in glioblastoma, In all, our results highlighted a potential 4‐chemokine signature for predicting prognosis in glioma and reflected the intricate immune landscape in glioma. It also threw light on integrating tailored risk stratification with precision therapy for glioblastoma. IDH wild‐type subgroup. Due to the gene signature was positively associated with immune‐relevant pathways and immunosuppressive tumor microenvironment state were enriched in the high‐risk group, the chemokines‐based gene signature was considered as a good predictor for patients' immunotherapeutic response.This study constructed a chemokines‐based gene signature, which was significantly associated with poorer survival, especially in glioblastoma,  Up to now, it remains incurable because of the striking genetic and cellular heterogeneity. According to the fifth edition of the WHO classification of tumors of the central nervous system (WHO CNS5),CXCL1 had been demonstrated as a poor prognostic indicator and induced radio‐resistance via NF‐κB signaling in glioma patients.Chemokines represents the largest subfamily of cytokines, including four main classes: CC‐, CXC‐, C‐, and CX3C‐chemokinesGiven some studies have characterized the expression profiles and functions of chemokines,22.1https://portal.gdc.cancer.gov/) and 325 glioma patients from Chinese Glioma Genome Atlas (CGGA https://www.cgga.org.cn). All data were normalized by log2 transformed. Somatic mutation and copy number variation (CNV) profiles were obtained from TCGA  and analyzed using R package “maftools” and GISTIC 2.0 with a threshold of FDR Q < 0.05. The involved clinical characteristics of patients were summarized in Table http://opendatacommons.org).This study retrospectively enrolled RNA sequencing data and corresponding clinical information of 699 glioma patients from The Cancer Genome Atlas  and the SVM‐RFE method were combined to further determine the variables.2.3To facilitate the prediction of 1‐, 3‐, and 5‐year overall survival (OS) probability in glioma patients, a nomogram was developed using the “rms” R package. Calibration plots were used to validate the performance of the nomogram using 500 bootstrap resamples.2.4R > 0.6, p < 0.05) and the ClusterProfiler (R package) was implemented to conduct the gene ontology (GO) analysis.http://software.broadinstitute.org/gsea/index.jsp).N = 11) were calculated using PROGENy.The patients in two datasets were divided into high‐ and low‐risk groups using the median riskscore as a cut‐off. The positive correlated genes with the riskscore were obtained by Pearson correlation analysis  method.2.6http://tcpaportal.org) was analyzed.The formalin‐fixed, paraffin‐embedded glioma tissue was stained according to our previous procedure,2.7http://tide.dfci.harvard.edu/) score with the timeROC package.To explore the relationship between the gene signature and anti‐PD‐1 immunotherapy, we performed survival analyses in Raul's anti‐PD‐1 treatment dataset.2.8Drug sensitivity was obtained use the R package “pRRophetic.” The predictive model was trained on expression profiles and drug response data of solid cancer cell lines by default 10‐fold cross‐validation. Both datasets provide the estimated concentration for 50% maximal inhibitory concentration (IC50) values as a measure of drug sensitivity.2.9Total RNA of 28 independent glioma samples were extracted using RNeasy Mini Kit (Qiagen). Written informed consent was obtained for all patients. Then, the RNA intensity was assessed using 2100 Bioanalyzer (Agilent Technologies). The expression levels of each gene were analyzed by ABI 7500 Real‐time PCR System. The relative expression levels of target genes mRNA were obtained by comparative CT method.2.10https://www.r‐project.org/). The Kaplan–Meier method was used to assess the survival time and calculate the difference. Spearman correlation analysis was performed to access the existence of a correlation between variables. Wilcoxon test or Student's t‐test was used to compare between two groups for continuous variables. Categorical variables were compared between groups using Chi‐square or Fisher's exact tests. p < 0.05 is considered statistically significant.All statistical analyses were performed in R software , which indicated that younger patients with glioma had lower riskscore. Furthermore, glioma patients with higher riskscore were more likely belong to WHO Grade IV and mesenchymal subtype , suggesting that the 4‐chemokines‐based signature predict malignant progression. Compared with high‐risk group, IDH mutation, 1p/19q codeletion were more occurred in the low‐risk group . Additionally, the MGMT promoter methylation is prognostic and played a powerful predictor of temozolomide sensitivity in gliomas,MGMT promoter methylation and found that the higher riskscore are enriched in the MGMT promoter un‐methylated group in both datasets , while TERT promoter mutation in the high‐risk group (p = 0.010). All above results demonstrated that the 4‐chemokine‐based signature is closely related to clinical and pathological features. Then, we reconfirmed the genes expression in an independent 28 glioma samples by qRT‐PCR, and the higher riskscore were founded in the WHO Grade IV . The patients in the low‐risk group had a significantly better prognosis than that in the high‐risk group   in TCGA dataset Figure . The pa) Figure . For GBMe Figure , which c3.4IDH1, TP53, ATRX, CIC, TTN, MUC16, NOTCH1, EGFR, NF1, and PIK3CA. While 82% of cases in low‐risk group carried IDH1 mutation  accumulated in the high‐risk group  information were collected. According to stratified group above mentioned, the top frequent mutations contain n Figure , which rp Figure , Zhao etp Figure , these c3.5R > 0.6, p < 0.05), 900 and 631 genes were separately identified in TCGA and CGGA datasets, respectively. Then, GO analysis showed that the positively associated genes were mainly immune‐relevant, such as T‐cell activation, neutrophil degranulation, neutrophil activation, and regulation of immune effector process in both databases , GSEA, and PROGENy pathway analysis were performed. First, we carried out principal component analysis to explore the transcriptomic features associated with the gene signature, which showed a strong association between whole transcriptome expression profile and riskscore Figure A, implyis Figure B. Additis Figure C, suggess Figure D.3.6IBA1, TMEM119, CD68, CSF1R, and TGFB1 was found in the high‐risk group . Also, our own glioma tissue IHC analysis confirmed the positive correlation . Finally, in GBM patients receiving anti‐PD‐1 therapy,Recently, immunotherapy is emerging to revolute the classical treatment.3.8in clinic, we explored candidate agents with higher drug sensitivity in high‐risk patients. Through training a predictive model with the cell line data derived from the Genomics of Drug Sensitivity in Cancer (GDSC), the R package “pRRophetic” was used to estimate the chemotherapeutic sensitivity in TCGA and CGGA datasets. First, compounds with a negative correlation between the estimated IC50 value and the riskscore were selected . After intersecting results in TCGA and CGGA datasets, twelve compounds were obtained, including Roscovitine, Bryostatin.1, CGP.60474, BMS.536924, PHA.665752, RDEA119, PD.0325901, Rapamycin, Dasatinib, XMD8.85, CGP.082996, and JW.7.52.1  and mediates GAM infiltration via these two chemokines in glioma.IDH wildtype, and MGMT promoter unmethylated. Also, the patients exhibit a shorter survival time in the high‐risk group, especially for patients with GBM with IDH wild‐type subgroup. Additionally, the gene signature plays an independent prognostic factor. A nomogram that integrates the clinicopathological features and riskscore showed a good accuracy. Collectively, these results indicated that the 4‐chemokine signature has potential clinical application in the future.In the previous study, it had been demonstrated that Second, the high‐risk patients showed an enrichment of immune‐related processes and pathways, which may be the main reason for the difference in survival time of glioma patients. Then, our results confirmed that patients in the high‐risk group not only presented an inflammatory activation state, but also enriched a higher abundance of GAMs and more adaptive immune gene markers. These classical immune regulation pathways imply the complexity of the glioma TME ecosystem Notably, low‐risk patients featured lower infiltration of GAMs and mainly in an immunologically quiet subtype, indicating that these patients may show a better outcome.Third, the interesting finding is the application of 4‐chemokine signature in therapeutic prediction. We found that high‐risk patients presented higher level of TMB and PD‐L1 expression, as well as the activated MAPK pathway. Arrieta et al found that MAPK/ERK pathway activation in recurrent GBM patients is predictive of response to PD‐1 blockade.Lastly, 12 compounds have been obtained as promising therapeutic drugs for high‐risk patients with glioma. Through comprehensive literature mining, we found that these drugs are inhibitors for CDK, PKC, c‐MET, MEK, ERK, and MTOR, which is consistent with the high enrichment of MAPK, WNT, and TNFα signaling pathways in the high‐risk patients. The experimental and clinical evidence of these candidate compounds were listed in WF, YZ, and TJ contributed to conception and design of the study. WF, WM, ZZ, and CR organized the database. WF, GL, ZW, ZS, ZB, and YZ contributed to analysis and interpretation of data. WF, JX, and DW perform the experiments. WF and YZ contributed to the first draft of the manuscript. WF, TJ, and YZ revise the manuscript. All authors contributed to the article and approved the submitted version.This study was supported by funds from the National Natural Science Foundation of China ; the public welfare development and reform pilot project of Beijing Medical Research Institute (JYY 2019–5); the CAMS Innovation Fund for Medical Sciences (2019‐I2M‐5‐021), Beijing Municipal Administration of Hospitals' Mission Plan (SML20180501); the China Postdoctoral Science Foundation ; Beijing Postdoctoral Research Foundation (2021‐ZZ‐022) and Natural Science Foundation of Beijing Municipality .The authors have no conflict of interest.Appendix S1Click here for additional data file.


Hodgkin lymphoma (HL) is curable in most cases by modern chemotherapy with/without radiotherapy (CT ± RT). Most treatment failures represent either primary refractory disease or early relapses within 1 year (PR/ER). Relapses >1 year from treatment completion are considered “late relapses” (LR) associated with better outcomes  and patiWe attempted to shed light on these questions by analyzing our cohort of 1143 patients in sustained CR > 5 years after CT ± RT initiation, with >90% coming from a single center and treated mostly with ABVD or equivalent regimens (ABVDeq). The median follow-up was 13.8 years . The outcome of VLRs will be reported separately in a wider multicenter study [Patients, treatment strategies and methods are described in detail in the The baseline characteristics of the 1143 patients are shown in Supplementary Table n = 249) or LR 2–5 years (n = 78)  (Supplementary Table p < 0.001) and anemia (p = 0.008) from PR/ER to LR and VLR patients, while MC increased from 17 to 26% and 46% (p < 0.001). IPS was lower in VLRs compared to LRs and PR/ER (p = 0.004); advanced-stage, B-symptoms, leukocytosis, lymphocytopenia and hypoalbuminemia were overrepresented in PR/ER but did not differ between LR and VLR.VLRs occurred in 66/1143 patients (2 as composite lymphoma). VLRs were initially compared to an additional group of 327 patients with PR/ER . The distribution and CumInc of VLRs are presented in Supplementary Table p = 0.11 and 0.13; Table p < 0.001) and elevated ESR , while MC was independent adverse factor . If ESR  was not considered, ABVDeq CT vs. MOPP-type was protective against VLRs  in the presence of other significant predictors (CMT/CT and MC) (data not shown).Univariate and multivariate prognostic factor analysis is provided in Table n = 1042 including 50 VLRs), both MC  and age ≥45 years  entered the final backward model as independent adverse prognostic factors, while elevated ESR  and CT + RT vs. CT  were selected as independent protective factors in multivariate analysis , both MC  and age ≥45 years  were independent prognostic factors (Table p = 0.009) and use of RT was retained in the backward model as a protective factor  (data not shown).In multivariate analysis focusing to patients with cHL treated with anthracycline-based CT , we assigned one point to each unfavorable factor, namely MC, age ≥45 years, ESR < 50 mm/h and omission of RT. The resulting score separated the three cohorts  into four adequate-sized subgroups  with significantly divergent outcomes Table .VLRs of HL have been long recognized since 1985  and recoIn the era of modern CT ± RT, four small-to-medium sized published studies have roughly included 300–450 patients and reported 16–30 VLRs each, with the most delayed ones recorded at 16.5–22 years –10. ThusIn 2017, the GHSG reported a linear VLR risk for 20 years, which was lowest in the advanced-stage trials, suggesting that BEACOPP-based strategies not only reduce PR/ER and LRs but also VLRs, while VLRs were highest in early-stage trials delivering the least intensive approaches, in line with other reports in the 90s , 6, 10. The present study provided novel observations in an attempt to shed light on some of the questions raised above, which remained unanswered even after the large GHSG study.First, we demonstrated that the linear pattern of VLRs continues beyond 20 years up to 25–30 years. Interestingly, we recorded the latest VLR at 35.1 years and recorded 8 cases beyond the 20th year.Second, patients who did not receive RT were more likely to experience VLRs. If this is validated, it may impact the long-term results of recent randomized trials, which are awaited with great interest, because non-inferiority of CT vs. CMT may be affected.Third, elevated ESR ≥ 50 mm/h was associated with lower VLR risk despite the marginally positive association of its strong correlates (stage and B-symptoms) with VLRs HR ~1.2–1.5). Elevated ESR denotes biologically active, more aggressive disease, which may have a different biology related to PR/ER but also with some kind of long-term plateau and lower risk of VLR. Thus, some patients with advanced disease, probably those with delayed diagnosis and less inflammatory background reflected by lower ESR, may be more prone to the development of VLR. This hypothesis is supported by the progressively decreasing percentage of ESR ≥ 50 mm/h in patients with PR/ER, LR and VLR (Supplementary Table .2–1.5. ELastly, our most striking finding was that the MC subtype was by far the most likely to be complicated by VLRs in sharp contrast with NS, with additional increasing MC and decreasing NS frequencies across the PR/ER, LR and VLR categories (Supplementary Table In conclusion, the present study provides new information by revealing the linear pattern of continuing relapses for up to 25–30 years, describing cases with extremely late relapses up to 35 years, confirming these findings in patients specifically treated with ABVDeq and, most importantly, uncovering previously unrecognized prognostic factors for VLRs, which may not only impact the follow-up strategies and patient counseling but also highlight the unique biology of different histologic subtypes, especially MC. Obviously, this information may be modified with PET-driven strategies and the incorporation of novel agents into the first-line therapy.Supplementary Material


Low muscle mass is prevalent among patients with cancer and a predictor of adverse clinical outcomes. To counteract muscle loss, β‐hydroxy β‐methylbutyrate (HMB) supplementation has been proposed as a potential therapy for older adults and various diseases states. This systematic review aimed to investigate the effects and safety of HMB supplementation in relation to muscle mass and function and other clinical outcomes in patients with cancer. A systematic search of MEDLINE, CINAHL, Embase, Cochrane Central Register of Controlled Trials, Scopus, ProQuest, and grey literature for reports published from inception to December 2021 was conducted. Included studies provided supplements containing any dose of HMB to adult patients with active cancer. A synthesis without meta‐analysis was conducted using a vote‐counting approach based solely on the direction of the effect . Risk of bias was assessed for each outcome domain, and evidence from higher‐quality studies (i.e. those with either low or moderate risk of bias) was examined. Safety was evaluated using both lower‐quality and higher‐quality studies. Fifteen studies were included, in which six were randomized controlled trials in patients with various cancer types and treatments. Studies prescribed HMB combined with amino acids (73.3%), HMB in oral nutritional supplements (20.0%), or both supplement types (6.7%); Ca‐HMB doses of 3.0 g/day were provided in 80.0% of the studies. Four studies had high risk of bias across all outcome domains. Considering the higher‐quality studies, evidence of a beneficial effect of HMB supplementation was found in four of four studies for muscle mass, two of two for muscle function, three of three for hospitalization, and five of seven for survival. In contrast, no beneficial effects of HMB on quality of life or body weight was found in two of four and three of five studies, respectively. A limited number of higher‐quality studies evaluating the impact of HMB on cancer therapy‐related toxicity, inflammation, and tumour response were observed. No serious adverse effects directly related to the nutrition intervention were reported. Although limited, current evidence suggests that HMB supplementation has a beneficial effect on muscle mass and function in patients with cancer. Well‐designed trials are needed to further explore the clinical benefit of HMB supplementation in this patient population. Low muscle mass is prevalent in patients with cancer, and it occurs independent of cancer site, disease stage, and weight loss.The pathophysiology of muscle wasting in cancer is multifactorial and not yet fully understood. However, appropriate quality and quantity of nutrients are essential to maintain muscle mass.Several pathways have been proposed to explain the effects of HMB on muscle health, which includes both an increase in muscle protein synthesis and a decrease in muscle protein breakdown. HMB stimulates muscle protein synthesis by activating the mechanistic target of the rapamycin (mTOR) system and the growth hormone/insulin‐like growth hormone factor axis.HMB's anabolic potential is being exploited to address muscle loss in cancer, with potential to improve long‐term outcomes. Yet as reported in oncology guidelines, the lack of consistent clinical evidence is still a challenge for recommending supplements containing branched‐chain amino acids and their metabolites such as HMB.This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta‐analysis (PRISMA)Supporting InformationSupporting InformationThe search strategy was developed combining key terms and medical subject headings relating HMB supplements and oncology patients (Supporting InformationOur primary outcomes included muscle mass and related terms  and health‐related quality of life. Additional outcomes were body weight [or body mass index (BMI)], muscle function , prevalence of muscle‐related abnormalities , inflammatory markers, cancer therapy‐related toxicities, hospitalization rate, length of hospital stay, postoperative complications, tumour response, mortality and survival, and safety. Further details are included in the eligibility criteria . Disagreements were discussed until a consensus was reached. General study information was extracted  as well as study details  and miscellaneous .P‐value, and any reported subgroup analysis. Measures of effect size included change from baseline to follow‐up within the experimental arm [for both controlled (i.e. with intervention and control arms) and uncontrolled  studies], differences in change between the experimental and control arms (for controlled studies only when data were available), and differences between experimental and control arms at follow‐up .For each outcome, we collected the following information, when available: measurement tools, person performing the assessment, measured and reported time points, unit of measure, number of participants with valid measure, baseline and follow‐up data (i.e. time point closest to the end of the nutrition intervention) for experimental and control groups, effect size and corresponding http://plotdigitizer.sourceforge.net).Data available only in figures were extracted using the Plot Digitizer software Findings are organized according to outcome domains, study design (i.e. RCT or NRSI), and HMB supplement type (i.e. HMB/Arg/Gln or HMB‐enriched ONS). Related outcomes were grouped into outcome domains: quality of life, cancer‐related fatigue, and symptom assessment were summarized into the ‘quality of life domain’; muscle strength and physical performance were combined into the ‘muscle function’ domain; and readmission rate, length of stay, and postoperative complications were evaluated into the ‘hospitalization domain’.Because of variation in the methods used to assess and report outcomes across studies, we synthesized the evidence using a vote‐counting approach based solely on the direction of effect , as previously recommended.FigureP‐values for each individual study. We calculated the mean or median differences between baseline and follow‐up within study arms when absolute or percent change values were not reported. To draw conclusions on whether there was an effect of HMB supplementation on muscle mass, function, quality of life, and clinical outcomes, a sensitivity analysis was conducted in which we evaluated findings from studies with low and moderate risk of bias combined.Findings from each individual study were graphically presented using both the Harvest plot and the effect of direction plot  of varied designs met the eligibility criteria, including a total of 527 patients (mean or median range: 62.3–69.0 years) with diverse cancer types and stages. A supplement containing HMB/Arg/Gln was taken by patients in seven studies.FiguresFour RCTsP = 0.01). HMB supplementation was additionally associated with a lower prevalence of sarcopenia at follow‐up compared with baseline in one NRSI.A beneficial effect of HMB supplementation on muscle mass was found in three of four RCTsOverall, most RCTs showed a beneficial effect of HMB supplementation on muscle mass compared with controls but not within the experimental arm alone in patients with cancer. In contrast, all NRSIs showed a beneficial effect of HMB from baseline to follow‐up in patients consuming HMB supplements.FigureFiguresQuality of life was evaluated in two RCTsFiguresMeasures of handgrip strength were reported in one RCTFiguresCompared with controls Figures and S5, FiguresP‐values were reportedCancer therapy‐related toxicity was evaluated in one RCTFigureset al.et al.Three RCTsFigureFigureA beneficial effect of HMB supplementation on reducing serum C‐reactive protein levels was shown in two NRSIsFiguresFive RCTsSupporting InformationAbsolute number or percentage of adverse events were described in three RCTsSupporting InformationP < 0.01)P < 0.05).Four RCTsTableSupplement adherence data were compiled in nine studies, including four RCTsFiguresTwo RCTset al.P = 0.029 and P = 0.10, respectively).Subgroup analysis performed by Berk FiguresFiguresRisk of bias was low across all outcome domains in three studies and high in four studies Figures and S13.FigureFigureNFκb activation during cancer and other catabolic conditions,This systematic review synthesizes the effects and safety of HMB supplementation on muscle mass and function, quality of life, and other clinical outcomes in patients with cancer Figure. We founThe most studied dose of HMB in oncology is 3.0 g/day delivered as a Ca‐HMB ; however, three of the studies evaluated a lower dose of 1.5 g/day of Ca‐HMB and reported some benefits on muscle function,Most studies  reported no beneficial effects of HMB interventions on body weight. Although adequate energy and protein intakes are key factors for maintenance of muscle health and body weight,Our subgroup analyses showed that potential factors contributing to the increase in muscle mass in the experimental arms could be in fact due to greater energy intake at follow‐up, as well as adherence to the intervention for a period longer than 3 weeks.Previous studies suggested a link between low muscle mass or function and quality of life in older adults as well as patients with cancer.Additional health outcomes of increasing value in nutritional oncology include reducing cancer therapy‐related toxicity and postoperative complications, as low muscle mass may decrease the tolerance to drug and surgical treatments.Noteworthy, some of the non‐muscle‐related benefits observed in some studies may be attributed to the presence of arginine and glutamine in the supplement. Arginine and glutamine are considered immunonutrients associated with improved immune function.Supplementation with HMB, independent of the form, appears to be safe and well tolerated in patients with cancer. None of the included studies reported serious adverse events directly related to this supplementation. Although some studies reported minor gastrointestinal events, it may be challenging to distinguish them from the effects of cancer therapy.In muscle, the mTOR signalling pathway is the predominant metabolic pathway involved in muscle protein accretion.The benefits of exercise and protein, both transient activators of mTOR in muscle, are well evidenced in patients with cancer.Given the potential yet limited evidence on the effects of HMB supplementation in patients with cancer, future studies are needed to advance our understanding. A recent scoping review of registered clinical trials investigating nutrition interventions targeting muscle‐related outcomes revealed that 3 of 22 RCTs are evaluating the effects of HMB supplementation in this population.P‐values in summary figures.Although we reported findings from all included studies, our conclusions were formulated solely based on the best available evidence. We used a robust approach to reduce publication bias by including only higher‐quality RCTs and NRSIs in the sensitivity analysis. A high heterogeneity of methods to assess and report outcome measures precluded a meta‐analysis. As such, we chose to perform a synthesis without meta‐analysis rather than reporting each study using a narrative style.This comprehensive systematic review found some evidence of a beneficial effect of HMB supplementation on muscle mass, function, hospitalization outcomes, and survival but not on quality of life and body weight in patients with cancer. As a limited number of high‐quality studies were included, our findings highlight the need for more well‐designed RCTs to further explore the benefits of HMB supplementation in patients with cancer. Suggestions for future studies include use of more sophisticated techniques for muscle mass assessment vs. anthropometric measures as a primary outcome, reporting whether changes in outcomes are above the minimally detectable change of the method (i.e. are not a result of measurement errors), recording adherence and dietary intake as well as considerations on approaches to improve patient adherence, reporting (and correcting) patient's nutritional status , stratifying the analysis by cancer stage and type, and malnutrition status. Moreover, future clinical trials should always evaluate the effects of HMB supplementation (as with any other nutrition intervention) on patient‐reported outcomes.This is an investigator‐initiated work by C.M.P. C.M.P. has previously received honoraria and/or paid consultancy from Abbott Nutrition, Nutricia, Nestlé Health Science, Fresenius Kabi, Pfizer, and Helsinn. C.E.O. has received honoraria from Abbott Nutrition for assisting C.M.P. with writing of the manuscript. S.L.P. is employed by Abbott Nutrition. N.E.D. has previously received grant funding and paid consultancy from Abbott Nutrition. P.J.A. has previously received grant funding and honoraria from Abbott Nutrition and Fresenius Kabi.C.M.P. is supported by a Canadian Institutes of Health Research (CIHR) New Investigator Salary Award and the Campus Alberta Innovation Research Chair Program.Supporting Information S1. Search StrategySupporting Information S2. Eligibility criteria of studiesSupporting Information S3. Frequency of adverse events reported in studies administering β‐hydroxy β‐methylbutyrate (HMB) supplements in patients with cancerSupporting Information S4. Changes in blood chemistry and hematology within experimental (EG) and control groups (CG) in randomized controlled trials and non‐randomized studies of intervention with β‐hydroxy β‐methylbutyrate (HMB) in patients with cancerClick here for additional data file.Figure S1. Effect direction plot summarizing direction of health impacts from studies administering β‐hydroxy β‐methylbutyrate (HMB) supplements in patients with cancer. Effect direction: upward arrow ▲= beneficial health impact, downward arrow ▼= no beneficial health impact, sideways arrow ◄►= mixed effects. Sample size: Final sample size  in intervention group as large arrow ▲ >50; medium arrow ▲ 20‐50; small arrow ▲ <20. Study quality: denoted by row colour: green = low risk of bias; amber = some concerns; red = high risk of bias. Type of statistical test: A = change from baseline to follow‐up within the experimental  arm; B = difference in change between experimental and control groups; C = difference between experimental and control groups at follow‐up in controlled studies, and difference between baseline to follow‐up within the experimental group in uncontrolled studies. * May et al. 2002 and Rathmacher et al. 2004 described findings from the same study. Abbreviations: Arg, arginine; Gln, glutamine; HMB, β‐hydroxy β‐methylbutyrate; QofL, health‐related quality of life; ONS, oral nutritional supplement; RCT, Randomised Controlled Trial.Figure S2. Changes in muscle mass parameters from baseline to follow‐up within experimental (green bar) and control (gray bar) groups. Δ* indicates absolute or percent mean change, and Δ† represents absolute or percent median change. P‐values reported in black correspond to testing of changes from baseline to follow‐up. P‐values reported in blue and positioned on the right side of figure represent testing of differences between experimental and control groups. Abbreviations: Arg, arginine; BIA, bioelectrical impedance analysis; CT, computed tomography; FFM, fat‐free mass; Gln, glutamine; HMB, β‐hydroxy β‐methylbutyrate; NR, not reported; NS, not significant; ONS, oral nutritional supplement; ↓RoB, low risk of bias; ↔ RoB, moderate risk of bias; ↑ RoB, high risk of bias.Figure S3. Changes in quality of life scores from baseline to follow‐up within experimental (green bar) and control (gray bar) groups. Δ* indicates absolute or percent mean change, and Δ† represents absolute or percent median change. P‐values reported in black correspond to testing of changes from baseline to follow‐up. P‐values reported in blue represent testing of differences between experimental and control groups. Abbreviations: Arg, arginine; Gln, glutamine; HMB, β‐hydroxy β‐methylbutyrate; ONS, oral nutritional supplement; ↓RoB, low risk of bias; ↔ RoB, moderate risk of bias; ↑ RoB, high risk of bias.Figure S4. Changes in measures of muscle function from baseline to follow‐up within experimental (green bar) and control (gray bar) groups. Δ* indicates absolute or percent mean change, and Δ† represents absolute or percent median change. P‐values reported in black correspond to testing of changes from baseline to follow‐up. P‐values reported in blue represent testing of differences between experimental and control groups. Abbreviations: Arg, arginine; Gln, glutamine; HMB, β‐hydroxy β‐methylbutyrate; ↓RoB, low risk of bias; ↔ RoB, moderate risk of bias; ↑ RoB, high risk of bias.Figure S5. Changes in measures of body weight and body mass index (BMI) from baseline to follow‐up within experimental (green bar) and control (gray bar) groups. Δ* indicates absolute or percent mean change, and Δ† represents absolute or percent median change. P‐values reported in black correspond to testing of changes from baseline to follow‐up. P‐values reported in blue represent testing of differences between experimental and control groups. Abbreviations: Arg, arginine; Gln, glutamine; HMB, β‐hydroxy β‐methylbutyrate; NR, not reported; ONS, oral nutritional supplement; ↓RoB, low risk of bias; ↔ RoB, moderate risk of bias; ↑ RoB, high risk of bias.Figure S6. Incidence (in percent) of cancer therapy‐related toxicities at follow‐up within experimental (green bar) and control (gray bar) groups. P‐values represent testing of differences between experimental and control groups. Abbreviations: Arg, arginine; Gln, glutamine; HMB, β‐hydroxy β‐methylbutyrate; ONS, oral nutritional supplement; ↓RoB, low risk of bias; ↔ RoB, moderate risk of bias; ↑ RoB, high risk of bias.Figure S7. Hospital length of stay and rate of readmissions and complications at follow‐up within experimental (green bar) and control (gray bar) groups. P‐values represent testing of differences between experimental and control groups. Abbreviations: Arg, arginine; Gln, glutamine; HMB, β‐hydroxy β‐methylbutyrate; ONS, oral nutritional supplement; ↓RoB, low risk of bias; ↔ RoB, moderate risk of bias; ↑ RoB, high risk of bias.Figure S8. Mortality and survival rates at follow‐up within experimental (green bar) and control (gray bar) groups. P‐values represent testing of differences between experimental and control groups. Studies with data not shown reported zero deaths during the period described in the graph. Abbreviations: Arg, arginine; Gln, glutamine; HMB, β‐hydroxy β‐methylbutyrate; ONS, oral nutritional supplement; ↓RoB, low risk of bias; ↔ RoB, moderate risk of bias; ↑ RoB, high risk of bias.Figure S9. Changes in energy intake from baseline to follow‐up within experimental (green bar) and control (gray bar) groups. P‐values represent testing of differences between experimental and control groups. Δ* indicates absolute or percent mean change, and Δ† represents absolute median change. Abbreviations: Arg, arginine; Gln, glutamine; HMB, β‐hydroxy β‐methylbutyrate; ONS, oral nutritional supplement; ↓RoB, low risk of bias; ↔ RoB, moderate risk of bias; ↑ RoB, high risk of bias.Figure S10. Changes in protein intake from baseline to follow‐up within experimental (green bar) and control (gray bar) groups. P‐values represent testing of differences between experimental and control groups. Δ* indicates absolute or percent mean change, and Δ† represents absolute median change. Abbreviations: Arg, arginine; Gln, glutamine; HMB, β‐hydroxy β‐methylbutyrate; ONS, oral nutritional supplement; ↓RoB, low risk of bias; ↔ RoB, moderate risk of bias; ↑ RoB, high risk of bias.Figure S11. Colormap depicting the number of studies reporting the effects of β‐hydroxy β‐methylbutyrate (HMB) supplementation on muscle mass and quality of life according to changes in total energy and protein intakes, adherence to the intervention protocol, and presence of nutrition co‐intervention . Effect direction: upward arrow ▲= beneficial effect, downward arrow ▼= no beneficial effect.Figure S12. Risk of bias assessment of randomized controlled trials, stratified by study, outcomes, and domains. D1: Bias arising from the randomization process; D2: Bias due to deviations from intended intervention; D3: Bias due to missing outcome data; D4: Bias in measurement of the outcome; D5: Bias in selection of the reported result.Figure S13. Risk of bias assessment of non‐randomized studies of intervention, stratified by study, outcomes, and domains. D1: Bias due to confounding; D2: Bias due to selection of participants; D3: Bias in classification of interventions; D4: Bias due to deviations from intended interventions; D5: Bias due to missing data; D6: Bias in measurement of outcomes; D7: Bias in selection of the reported result.Click here for additional data file.


Peatlands have their own, specific insect fauna. They are a habitat not only for ubiquistic but also stenotopic moths that feed on plants limited to wet, acid and oligotrophic habitats. In the past, raised bogs and fens were widely distributed in Europe. This has changed since 20th c. Due to irrigation, modern forestry, and increasing human settlement, peatlands have become isolated islands in an agricultural and urban landscape. Here, we analyze the flora in a degraded bog situated in a large Lodz city agglomeration in Poland in relation to the diversity and composition of moth fauna. Over the last 40 years since the bog has become protected as a nature reserve, birch, willow, and alder shrubs replaced the typical raised bog plant communities due to the decreased water level. The analysis of moth communities sampled in 2012 and 2013 indicates dominance of ubiquistic taxa associated with deciduous wetland forests and rushes. Tyrphobiotic and tyrphophile moth taxa were not recorded. We conclude that the absence of moths typical of bog habitats and the dominance of common, woodland species are associated with hydrological changes, the expansion of trees and brushes over typical bog plant communities, and light pollution. Groundwater level decrease in urban wetlands causes the expansion of common tree and shrub species and the degradation of aquatic flora. This leads to the disappearance of tyrphophile moth species and changes in moth communities that start to resemble typical forest assemblages. These processes are often irreversible, especially in the absence of responsible management from local environment protection agencies. They utilize not only the stems and leaves of plants but also their flowers, roots, and seeds . Peat pits were overgrown by Phragmites australis, Typha latifolia, and high sedges. A garbage dump was located in the south‐western part of the depleted bog. It functioned here in the 1960s. In the first period, after cessation of waste storage, annual and biennial plants dominated there. Vegetation here consisted of species of the genera Chenopodium, Sisymbrium, and Atriplex. In subsequent years, they gave way to perennial plants. The area of the community increased, with tansy dominating Artemisio‐Tanacetetum vulgare, in which, apart from the dominant, Urtica dioica, Artemisia vulgaris, and Arctium lappa were noted.The mire in Rąbień near Łódź is located south of a compact range of lowland bogs  were overgrown by alder carr (Sphagno squarrosi‐Alnetum and the Betula pendula community). Settlement entered the areas adjacent to the reserve from the north, east, and south. In the west, the bog borders on a dune, which was largely covered by the Spergulo vernalis‐Corynephoretum and self‐seeding Pinus sylvestris.There were also small areas of grassland from Betula pendula, B. pubescens, and Pinus sylvestris) and Salix cinerea in peat bog vegetation . The forest area surrounding the interior of the peat bog increased at the expense of non‐forest peat vegetation. The areas directly adjacent to the reserve from the north, east, and south have changed further because of urbanization. The dune stretching along the western border of the reserve was overgrown by a young pine forest.Vegetation tests repeated in the years 1999–2000 showed changes occurring in it. They included an increase in participation of young trees  site, a Robinson trap with mercury bulb was used, and sampling took place from spring 2011 to spring 2012. Catching was carried out regularly at two‐week intervals from 9:00 pm to 3:00 am. The catch at Torfowa Street  took place by a standard light trap with mercury‐incandescent bulb and white canvas from spring to autumn 2012 at 2‐week intervals. The light trap at Torfowa st. took place between 10.00 pm and 12.00 pm. The data matrix presenting a list of taxa collected at R and T sites is included in appendices, in Tables 2.3First, SIMPER analysis was conducted to find the main habitats preferred by taxa collected at Tofrowa (T) and Różana (R) sites, and dissimilarities between habitat preferences of taxa reported at R and T sites. For this propose, moth species were classified as “samples” and divided into three groups—(1) collected only at T site, (2) collected only at R site, (3) collected at both sites. The main preferred habitats (up to three) of each moth taxa were classified as “variables,” and one‐way SIMPER analysis using Bray–Curtis similarity and cut‐off of 100% was conducted to define their most preferred habitats.To recognize an assemblage pattern in caterpillar host plants of the reported taxa, a series of analysis was used. (1) NMDS analysis based on Bray–Curtis formula was conducted on all collected moth species as “samples,” and for each species up to three main host plants as “variables.” As NMDS divided taxa into two main moth groups—A and B, and an out‐group O, (2) one‐way SIMPER analysis indicating main host plants for each of these groups was conducted using Bray–Curtis similarity index and 100% cut‐off. (3) For summarizing the pattern of the moth–host plant relations in the nature reserve, PCA was conducted regarding moth species as “samples” and host plants as “variables.” It presents the most important host plants, and the main moth taxa groups related to their occurrence.To identify habitat preferences and main host plants of the species collected, multivariate methods were used—Non‐metric MultiDimensional Scaling (NMDS), SIMilarity PERcentage (SIMPER), and Principal Component Analysis (PCA). NMDS is a very good and widely used method for analysis of similarity, both for abundance and presence/absence data. It allows to find the patterns in community composition or ecological similarity between species groups. SIMPER and NMDS are two complementary methods. SIMPER allows for a more detailed insight into the community composition and selection of the most important taxa responsible for the observed pattern. Principal Component Analysis (PCA) was used to identify how host plants explain the variability in moth communities. As the PRIMER 6 was used, the eigenvectors identify well each host plant  correlation to the PC Axes and Principal Component Scores the location of moth taxa (as samples) at the multivariate space . These are wetland alder forests , meadows and other open grass and herb habitats (17.72% and 19.44%), gardens (13.98% and 10.69%), clumps of trees in the cultural landscape (10.2% and 6.67%). The only difference is that at the R site, there is a 9.67% share of species preferring oak deciduous forests, whereas at the T site (6.27%), there are taxa typical of pine coniferous forests. The difference follows the character of the areas neighboring the light trap plant communities—at R, these are gardens and old mixed forests with oaks and birches, while at T, these are young pine plantations and meadows. For both sites, there are common species preferring aquatic habitats (3.09%) which are in the direct vicinity of T but not R study site.Alnus sp. and Salix spp. are less preferred as host plants than deciduous trees typical of more dry habitats. Group B includes taxa feeding mainly on herbs and grasses—sorrel (18.92%), plantain (18.92%), dandelion (12.90%), nettle (12.77%), grasses (11.69%), bedstraw (7.70%), pigweed (4.48%), and chickweed (3.87%). This group is less specific than A, having an average similarity of only 12.52%. Other taxa not aggregated in A or B were classified as an outgroup and it is not surprising that group O has the lowest average similarity of 7.93%  we can only extrapolate the currently observed patterns to possible scenarios of changes in the studied area. Based on our results, we hypothesize that, as trees expanded in the reserve area from the 1980s to the present time  with pits and ponds created after peat extraction. From the 1980s to 2018, the surface area of these habitats decreased because of the expansion of reeds and trees  that are normally rare or absent in forest ecosystems and peat bogs, but are very common in urbanized areas ; data curation (lead); formal analysis (lead); investigation (lead); methodology (lead); project administration (lead); resources (lead); software (lead); supervision (lead); validation (lead); visualization (supporting); writing – original draft (lead). Krzysztof Pabis: Conceptualization (supporting); methodology (supporting); supervision (supporting); validation (supporting); writing – original draft (supporting). Angelika Zima: Conceptualization (supporting); investigation (supporting); resources (supporting); writing – original draft (supporting). Leszek Kucharski: Conceptualization (supporting); data curation (supporting); investigation (supporting); methodology (supporting); resources (supporting); validation (supporting); writing – original draft (supporting). Robert Sobczyk: Conceptualization (supporting); formal analysis (supporting); methodology (supporting); software (supporting); visualization (lead); writing – original draft (supporting).Table S1: Species occurrence at each site and habitats: . Note that abbreviations of habitats were used: PF ‐ pine forest, OW ‐ oak wood, HB ‐ hornbeam forest, ME ‐ meadows, RI ‐ riparian and alder forest, GA ‐ gardens, AB ‐ near buildings, AW ‐ around water, PA ‐ parks, FA ‐ farmlands, PB ‐ peat bogs.Table S2: Species occurrence at each site and host plants of the collected moths taken from literature.Click here for additional data file.Table S3: Results of SIMPER analysis conducted for three groups of moths according to their host plants A, B, O.Click here for additional data file.Table S4: Moth taxa separated for A, B, O groups based on NMDS.Click here for additional data file.


Explicit (declarative) memory declines with age, but age effects on implicit (nondeclarative) memory are debated. Some studies have reported null changes in implicit memory  with age, while others have uncovered declines. One factor that may account for these discrepancies is processing. Evidence suggests that conceptual and perceptual processes are not equally affected by ageing, yet processing requirements have varied greatly between studies. Processing may moderate age effects on priming, but no study has systematically examined this issue. This registered report presents an experiment to manipulate processing  during incidental encoding of words, prior to measures of perceptual  and conceptual (category verification) priming. The perceptual and conceptual priming tasks were matched on all characteristics except processing, making them highly comparable. The four orthogonal conditions  were designed to clarify situations in which age effects on implicit memory emerge, which holds important practical and theoretical implications. Significant effects of Age, Test, and an Age × Processing interaction emerged. Priming was greater in young than older adults and on the perceptual than the conceptual test, but in contrast to the predictions, the age difference was only significant when prior encoding was perceptual . Understanding age-related changes in memory is increasingly important in light of the steady rise in age of the global population. Reductions in explicit memory—the conscious retrieval of previously learned information or prior experiences—are well documented, but age effects on implicit memory—facilitation in task performance due to prior exposure to stimuli which does not require conscious recollection—are debated. If, as it is commonly believed, implicit memory is preserved in normal ageing, this could have important practical and theoretical implications. For example, it might provide a valuable diagnostic tool for Alzheimer’s disease  or be usA number of studies have reported statistically equivalent priming in young and older adults on tests such as word-stem completion , some encouraging perceptual encoding , and others requiring no particular strategy . In the latter situation, it is impossible to know what sort of processing strategy was adopted by participants or whether this differed between young and older adults. There is extensive evidence that older adults are impaired in semantic encoding e.g., , so one Age effects on priming remain unclear. The varied outcomes among published studies may be explained by different processing requirements. Age differences may be small or statistically null when the priming task is perceptual in nature and encoding engages participants with perceptual features of the stimuli, and larger when the priming task is conceptual and encoding engages participants with semantic features of the stimuli. To clarify this issue, this registered report presents an experiment to systematically manipulate processing at encoding in young and older adults prior to matched perceptual and conceptual priming tests.Participants witnessed a stream of words in two counterbalanced incidental encoding blocks, one involving perceptual processing and one involving conceptual processing, prior to a blocked test phase to measure perceptual and conceptual priming. This allowed comparison of age effects in the following conditions: perceptual encoding, perceptual test [PP]; conceptual encoding, perceptual test [CP]; perceptual encoding, conceptual test [PC]; conceptual encoding, conceptual test [CC]. Priming tasks were matched on all characteristics except processing, making them highly comparable. The perceptual task employed the continuous identification (CID) paradigm e.g., , in whicA few other points should be noted: (1) Target items were presented in both the CID  and CV  tasks, meaning there was encoding-test perceptual overlap in both and only the type of processing differed. This approach was favoured over a conceptual task that does not present target items, such as CEG, to match tasks as far as possible and rule out age differences not attributed to processing . It was Hypothesis 1) and an Age × Processing  × Test (CID/CV) interaction (Hypothesis 2). This was predicted on the basis of evidence that conceptual processing is affected to a greater extent by ageing than perceptual processing , while on the conceptual test greater priming was expected following conceptual than perceptual encoding in young adults (CC > PC), and vice versa in older adults (PC > CC) (Hypothesis 4).Hypotheses are numbered to correspond to the analyses in the “Results” section. In overview, it was anticipated that age differences in priming would vary across conditions, where CC > PC and CP > PP . In otheng e.g., , and encng e.g., . Thus, oThe task was constructed using Gorilla Experiment Builder (gorilla.sc) (see section “Procedure”), and all participants completed the experiment online using a desktop or laptop computer. Young participants (aged between 18 and 30 years) were recruited through Middlesex University subject pool and Prolific, and older participants (aged 65 years and above) through an existing partnership with the University of the Third Age (see f = 0.15) and alpha at .05. The non-sphericity correction was set to maximum , and a moderate correlation between measures was assumed (r = .5). In total, 96 participants (48 young and 48 older) were required, with an actual power of 0.945, ensuring an equal number of participants in the counterbalance rotations. Additional participants were only tested to replace any who did not meet the inclusion criteria, failed to complete the whole experiment, or failed to follow task instructions (see section “Results”).Processing  during encoding and test was manipulated within participants in a counterbalanced blocked design. The four conditions included PP, CP, PC, and CC. An a priori power analysis (G*Power) was conducted to calculate the required sample size using an estimated effect size  and number of syllables ranging from 1 to 4 (M = 1.70). One hundred and sixty words served as experimental items, arranged into eight lists of 20 items, with 2 items per category per list. Half of the experimental items represented living objects and half non-living objects. In total, 88 words were presented during encoding, that is, two lists in the perceptual block and two in the conceptual block, along with two filler items at the start and end of each block. The eight filler items were from different categories to experimental items and not presented elsewhere in the experiment. One hundred and sixty items were presented at test—80 per block (40 studied [20 from each encoding block] and 40 new). Lists were counterbalanced between participants such that each appeared an equal number of times in the perceptual and conceptual blocks and as studied (old) and new type.Stimuli included 176 concrete nouns from 20 taxonomic categories selected from the updated category norms by Participants were asked to complete the online experiment in a quiet, private space. A link launched the experiment, which was compatible with any browser and operating system, but set up to prohibit the use of tablets and mobile phones. Experimental research is increasingly being conducted online and provides an excellent way of accessing large samples, especially at a time when in-person testing presents risks in relation to the Covid-19 pandemic. The Gorilla platform has demonstrated capability of running sensitive reaction time experiments and has replicated effects from well-known paradigms such as the flanker task . PreciseParticipants were informed that the experiment consisted of separate phases, but they were not informed that stimuli from initial stages were repeated later. In the encoding phase, participants were presented with 88 words, one at a time, in black Open Sans lowercase text in the centre of a white background screen. The default size on Gorilla is 36 pixels, but as screen resolution varies between participants, items are automatically scaled to ensure that they fit within the confines of the zone. On each trial, a black fixation cross was presented for 500 ms, followed by a single word for 1,000 ms and a response screen for 3,000 ms . The 88 In the perceptual block, participants judged whether the first and last letter of the word were in alphabetical order, and in the conceptual block, participants judged whether the item was living or non-living. The judgement in the perceptual block engaged participants with purely perceptual detail about the word, whereas judgements in the conceptual block required more elaborate appraisal of the item to decide whether it is living or non-living. Both decisions are objective and required a yes/no judgement. During the response screen, options “yes” and “no” were presented and participants had a maximum of 3,000 ms to respond using the F and J keyboard keys. RT was captured upon button press. Once pressed, a blank screen was presented for 1,000 ms prior to the next trial. If no response was made within 3,000 ms, the trial was discarded.Following encoding, there was an interval of approximately 3 min while participants received instructions for the test phase and practised the initial priming segment. The test phase also comprised two counterbalanced blocks—the CID task  and the CV task , and the first block performed matched the first encoding block . Each block included 80 experimental trials—40 old words  and 40 new words, presented in a new random order for each participant, plus 2 filler trials at the start and end. On each trial in the CID block, participants performed a speeded perceptual identification of a word, and on each trial in the CV block, participants performed a speeded CV .In the CID task, participants were informed that their task was to identify words as quickly as possible. They were told that the words would initially be difficult to make out, but would appear to gradually emerge. Speed was emphasised, but participants were asked to try to be as accurate as possible. On each trial, a mask was presented for 250 ms, followed by a word for 16 ms (rate of one screen refresh) and the mask again for 234 ms, forming a 250-ms block. The block presentations continued with the word duration increasing by 16 ms on each alternate cycle and the mask duration decreasing by the same amount, with the result that the word appears to gradually emerge. RT was captured upon spacebar press, at which point the word disappeared and participants were prompted to type it into a box on the screen. If the spacebar was not pressed by 7,500 ms , the trial was discarded. Participants were prompted to press enter when they had finished typing the word to initiate the next trial. A fixation cross was presented for 500 ms prior to the next trial.In the CV task, participants were informed that their task was to decide whether or not a word matches a given category as quickly as possible on each trial. As with the CID task, speed was emphasised, but participants were asked to try to be as accurate as possible. On each trial, a word was presented, along with a category label , and participants judged whether the word matched the category by selecting “yes” or “no” using the F and J keyboard keys. For half of the words, the correct category was presented, and for the other half, an incorrect category was presented, meaning that the correct response was “yes” for half of all trials. The word and response cue remained on the screen until response (RT captured), at which point the category and prompt disappeared. For consistency with the CID task, if no response was made by 7,500 ms the trial was discarded. To match the timings in the CID task as far as possible, after response a blank screen was presented for 2,000 ms, followed by a fixation cross for 500 ms prior to the next trial.What do you think was the purpose of the identification and category selection tasks you just performed? (2) Did you notice anything about these tasks? If participants failed to specify that some words were previously studied, they were classified as unaware and not required to complete the rest of the questionnaire. If they noticed that some words were previously studied, they were asked: (3) Were you aware that some words had been shown previously in the experiment as you were performing the tasks, or did you become aware of this afterwards/in hindsight? (4) Did you suspect prior to the start of the second phase of the experiment that you would be tested on your memory of the words shown in the first phase? (5) Did you try to use your memory of the words to help you in the tasks in the second phase? (6) If yes, do you think this strategy helped you, and how so? Participants who stated they became aware in hindsight were classified as unaware at the time of testing, and all other participants were classed as aware.Immediately after the test phase, participants completed a short awareness questionnaire. Similar to that developed by excellent to very poor), and upon completion of the experimental task, participants performed the multiple-choice part of the Mill Hill Vocabulary Test. This involved selecting an acronym from a choice of 6 to best describe a target word. This test includes 33 items in total, and each correct response is given a score of 1   cognitive screening appropriate for self-administration and was distributed to participants electronically. The questionnaire consists of 20 statements that participants must respond to on a Likert-type scale taking into account the previous 2 years, for example, “require checklist as memory support” “never (0),” “seldom (1),” “sometimes (2),” “always (3).” The numbers in parenthesis are summed to provide an overall score , and a score of 8 or more indicates possible early dementia. Only participants scoring ⩽7 were invited to take part in the experiment. The first part of the online task collected background information from all participants, including age, sex, years of education, and self-rated health  was conducted and BF10 values of less than 1/3 were considered support for the null hypothesis (https://osf.io/z7vua/The experiment was pre-registered on the Open Science Framework (osf.io/anfby). All steps and analyses were as per the pre-registered protocol. Participants were excluded if it was apparent that they did not meet the eligibility criteria, if they failed to complete the experimental task in full or follow instructions, or if they did not meet performance thresholds specified below. In total, there were 45 exclusions (19 young and 26 older adults), and additional participants were tested to achieve the required sample size of 96 usable participants. Ten exclusions (3 young and 7 older adults) were due to missing data , and 35 (16 young and 19 older adults) were due to performance thresholds not being met (detailed in the relevant sections below). Analyses on the final sample were conducted using JASP (Version 0.9.2), using an alpha level of .05. All pre-registered analyses are reported, with partial eta squared for analysis of variance (ANOVA) effects and Cohen’s pothesis . Raw datF = 32.29, p < .001, F = 26.08, p < .001, F = 0.77, p = .383, F = 106.17, p < .001, F = 33.99, p < .001, F = 0.07, p = .787, The proportion of discarded trials due to time-out was low . Mean accuracy  and RTs  can be found in SDs from the mean were trimmed. Trials associated with incorrect identifications were removed . Two young and seven older adults with insufficient accuracy (>20% incorrect) were excluded. In the CV task, RTs to be studied and new trials necessitating a “yes” response  or a “no” response  were collapsed. Priming in each condition was calculated by subtracting each participant’s mean old-item RT from their mean new-item RT, expressed in proportion to their mean baseline (new-item) RT: (RTnew−RTold)/RTnew. Priming proportional to baseline was favoured because slower responding in older than young adults can artificially elevate priming when RT difference scores are used  = 5.75, p < .001, d = 0.83; CP: t(47) = 3.86, p < .001, d = 0.56; PC: t(47) = 3.98, p < .001, d = 0.57; CC: t(47) = 1.59, p = .118, d = 0.23 (BF10 = 0.508), but was only significantly above zero in older adults in the PP and CP conditions—PP: t(47) = 2.67, p = .010, d = 0.39; CP: t(47) = 4.73, p < .001, d = 0.68; PC: t(47) = 0.06, p = .951, d = 0.01 (BF10 = 0.157); CC: t(47) = 0.05, p = .965, d = 0.01 (BF10 = 0.157) . The 2 (Age) × 2 (Processing) × 2 (Test) ANOVA revealed a main effect of Age, F = 9.83, p = .002, Hypothesis 1), and a main effect of Test, F = 14.52, p < .001, F = 0.22, p = .644, Hypothesis 2) was not significant, F = 2.19, p = .143, F = 10.01, p = .002, F = 0.009, p = .924, F = 1.34, p = .250, Priming  in youngr(94) = .27, p = .009, as were Mill Hill scores and encoding phase accuracy in the perceptual block, r(94) = .35, p = .001, and conceptual block, r(94) = .22, p = .034. Therefore, years of education and encoding phase accuracy in the perceptual and conceptual blocks were entered into the model as covariates, and Mill Hill vocabulary scores were not included. The analysis of covariance (ANCOVA) revealed a main effect of Age, F = 4.90, p = .029, F = 4.37, p = .039, F = 7.95, p = .006, Years of education, Mill Hill vocabulary scores , and encF = 3.06, p = .087, F = 0.29, p = .593, F = 1.76, p = .191, F = 0.001, p = .975, The post-test awareness questionnaire revealed that 17 young and 9 older adults were aware during the experiment that items from the encoding phase were repeated in later phases . The pret(94) = 3.14, p = .002, d = 0.64, PC: t(94) = 2.81, p = .006, d = 0.57; CP: t(94) = 0.05, p = .961, d = 0.01 (BF10 = 0.215), CC: t(94) = 1.33, p = .188, d = 0.27 (BF10 = 0.466) .The main analysis revealed effects of Age, Test, and an Age × Processing interaction. Priming was generally greater in young than older adults and on the perceptual (CID) than the conceptual (CV) priming task. However, follow-up tests for the interaction confirmed significant age differences in priming following perceptual encoding (PP and PC) but not conceptual encoding (CP and CC), with the largest effect size for the age difference in the PP condition—PP: t(47) = 2.42, p = .019, d = 0.35; CP = CC, t(47) = 1.71, p = .094, d = 0.25, BF10 = 0.603, but the opposite was true in older adults—their priming was significantly greater on the perceptual than the conceptual test only following conceptual encoding—that is, CP > CC, t(47) = 3.83, p < .001, d = 0.55; PP = PC, t(47) = 1.80, p = .078, d = 0.26, BF10 = 0.695 . However, it should be noted that the BF10 values greater than 1/3 do not provide strong support for the null hypothesis of no difference between these comparison conditions.Although the expected Age × Processing × Test interaction was not significant, the observed BF10 value greater than 1/3 does not provide strong support in favour of the null hypothesis of no interaction. Interestingly, priming in young adults was significantly greater on the perceptual than the conceptual test only when encoding was perceptual—that is, PP > PC, Processing requirements have varied considerably between studies examining age effects on priming, and this may have contributed to the mixed outcomes. Put simply, if ageing does not equally affect the ability to engage in perceptual and conceptual processing, this may explain why age differences in priming have emerged in some studies and not others. In an attempt to clarify this issue, this study systematically manipulated processing requirements  at encoding prior to matched perceptual and conceptual priming tasks. Main effects of Age and Task, and an Age × Processing interaction emerged, demonstrating reliably greater priming in young than older adults when encoding was perceptual—that is, on the PP  and PC  conditions, and equivalent priming in the CP  and CC  conditions.To be able to unpack age differences in priming as a function of processing characteristics, it is important that tasks are appropriately classified. The continuous identification  and category verification  tasks were selected based on their established processing requirements and matched as closely as possible on all characteristics except processing. Both captured an RT measure, and all within-trial events and durations were aligned (see sections “Introduction” and “Method”). Priming was generally lower on the conceptual than the perceptual task, but age effects did not interact with the type of task, pointing to a decline in both perceptual and conceptual priming with age. The findings are consistent with several prior studies reporting reliable age-related reductions in perceptual priming e.g., , and conTo the best of this author’s knowledge, all adequately powered studies using the CID task have uncovered a reliable reduction with age  than young adults (5.83%) due to time-out and inaccuracies, while the level of discarded trials in the perceptual task was equivalent in young and older adults . Second, RTs were slower in the CID than the CV task in both groups, no doubt reflecting the fact that words were gradually clarified in the CID task but were fully presented in the CV task. This is unlikely to have distorted the age effect because the slowing was observed in both age groups and did not disproportionately affect baseline  RTs. Furthermore, priming scores proportional to baseline were calculated. Finally, 17 young and 9 older participants were aware during testing that items from encoding were represented. More young than older adults may therefore have attempted to use an explicit strategy in the CID and/or CV tasks. Although analysis revealed no statistically significant difference in priming between aware and unaware young participants, priming was numerically greater in aware participants and the BF10 value of 0.524 does not provide strong evidence of there being no difference.The present data suggest that age effects on priming are dependent upon the manner of encoding. Priming was greater in young than older adults only following perceptual encoding—that is, in the PP and PC conditions. Of particular note, the largest age difference was observed in the PP condition while priming was equivalent in the CP condition, both involving an identical priming task. Thus, the type of encoding was responsible for the emergence or elimination of a reliable age difference. Given evidence that older adults are impaired in semantic encoding e.g., , it was No prior study has fully crossed processing requirements at encoding and test to examine interactions with age effects on priming. However, the present PP and CC conditions are similar to those in A final point concerns the interesting paired comparisons of priming across the perceptual and conceptual tasks. Young adults achieved greater priming on the perceptual than the conceptual priming task when encoding was perceptual , but the opposite was true of older adults—their priming was greater on the perceptual than the conceptual priming task following conceptual encoding . These observations concern exploratory analyses and should be interpreted with caution given the BF10 values greater than 1/3, but nevertheless are interesting and worthy of further investigation in future studies. High priming in young adults in the PP condition is predicted by accounts that specify a benefit of an overlap in processing characteristics between encoding and test e.g., —in this To conclude, this study set out to clarify age effects in priming by systematically manipulating processing requirements at encoding and test. There was an age-related decline in both perceptual and conceptual priming, significant only when encoding was perceptual in nature. Priming was lower in both age groups on the conceptual than the perceptual priming task. The observed age effects have important implications for our theoretical understanding of the structure of memory. Given well-documented declines in explicit memory with age, reports of spared priming have often been cited as key evidence for a functionally independent implicit memory system e.g., . However


The aim was to assess the reproductive efficiency of different techniques used to preserve spermatozoa in artificial insemination semen doses (AI‐doses) by evaluating refrigeration at 15°C, cryopreservation and encapsulation. Forty‐two hyperprolific sows were treated with buserelin and inseminated once at a single fixed time. The fertility rate, embryonic vesicles viability and the early embryonic mortality (arrested conceptuses) evaluated post‐mortem at 24th day of pregnancy, were analysed in order to assess the effectiveness of each proposed technique. Results show an overall reduction on fertility using the three proposal sperm preservation techniques . Total number of embryonic vesicles was very similar among the three treatments; yet, the number of viable vesicles was numerically different among groups, and thus, embryonic viability was 79.25%, 80.0% and 87.15% for refrigerated, frozen–thawed and encapsulated AI‐doses, respectively. Refrigeration at 15°C is the most widely used technique for sperm preservation in swine, which allows semen storage for 1 to 7 days depending on extender used, intrinsic semen quality of the boar and handling laboratory conditions of semen samples. Yet, the use of frozen–thawed AI‐doses is less frequent  on hyperprolific sows, which allowed us to evaluate fertility and embryo viability in the early stages of pregnancy.22.1The study was carried out in a commercial farm on a total of 42 hyperprolific DanBred sows, distributed in the three experimental groups as shown in Table 2.29 sperm/dose. The methodology used in each group was as follows:Frozen–thawed AI‐doses Ejaculates were collected, evaluated for quality and frozen 30 days before AIs. After collection, samples were diluted  in the extender and transported to the laboratory  for further cryopreservation using the extenders and freezing protocol described by Gil et al.  the day of AIs as usually are prepared for routine distribution to commercial farms. After collection, ejaculates from the two boars were pooled, and the resulting sample was split a half for preparing refrigerated and encapsulated AI‐doses.Liquid refrigerated AI‐doses After semen quality evaluation, samples were diluted in Duragen® extender (Magapor) and placed in a portable cooler at 15°C until use in AI.Encapsulated AI‐doses After semen quality evaluation, pooled sperm samples were encapsulated following the methodology previously described by Vigo et al.  and frozen–thawed AI‐doses, respectively.Semen was obtained from two boars from the ‘Cinco Villas’ AI Center, and pool of ejaculates from these boars were used for preparing AI‐doses for post‐cervical AI. The AI‐doses of the three experimental groups  were prepared in a volume of 50 ml with a total sperm concentration of 1.5 × 102.3At 85 h after weaning, sows received 10 μg of intramuscular buserelin , and treated sows were inseminated once 30 h after buserelin injection using a single fixed time AI with a post‐cervical catheter.2.4Sows were slaughtered on day 24 after AI. Genital tracts were transported to the Veterinary Faculty of the ‘Universidad de Zaragoza’ for further processing. After washing, uterine horns were detached from the mesometrium and longitudinally extended in order to make a longitudinal incision along the entire length of each uterine horn, and the number and viability of embryonic vesicles were assessed according to Martinez et al. . Only ve2.5p < .05.Statistical analysis was performed using SAS® 9.1 (SAS Inst. Inc.). The effect of semen treatment on fertility, total number of embryonic vesicles, total viable and non‐viable vesicles, percentage of viable and non‐viable  vesicles at D24 was analysed using Least Square Means (SAS MIXED procedure). Data are presented as Mean ± Standard Error of the Mean (SEM). Statistical significance was set at 3p > .05) and 18.75% higher with encapsulated AI‐doses than with frozen–thawed ones . Percentage of embryonic viability was also numerically higher with encapsulated AI‐doses than with refrigerated (7.90%) or frozen–thawed AI‐doses (7.15%), but differences were not significant . Yet, semen cryopreservation is not a common semen preservation system in pig AI Centers, since reproductive results are lower and show a great variability among sires due to inter‐individual differences in semen freezability. Regarding encapsulated spermatozoa, not many results are published at farm level, but our research group maintains a line of studies to evaluate the efficacy of this technique under field conditions using different AI protocols , and our results have been similar to those obtained with traditional methods and comparable with those published in previous studies using encapsulated AI‐doses , results are controversial. Thus, similar results have been previously reported with respect routine AI techniques . Yet, viable embryonic vesicles were numerically higher with the use of encapsulated AI‐doses (18.88) compared with the found when using refrigerated AI‐doses (17.11) or frozen–thawed (17.00), but differences did not reach statistical significance.The low fertility results obtained with the three treatments could be explained by an inadequate response to ovulation synchronization treatment with the use of a single AI, since the pooled AI‐doses used were prepared from two proven fertility studs, and the study was carried out in multiparous females. Yet, this did not seem to affect the number of embryonic vesicles obtained at D24, since the results correspond to those described for hyperprolific sows. It is important to highlight the higher fertility and embryo viability results obtained when encapsulated AI‐doses were used when compared with the other two treatments, although the differences were not significant. Frozen–thawed AI‐doses provided low fertility, but an acceptable embryo viability that could have been reached by the use of excellent quality ejaculates or by its special resistance to the freezing–thawing protocol (Gil et al., In conclusion, with the methodologies that have been used, fertility was reduced regardless of the semen preservation method used, although the reduction was more pronounced with the use of frozen–thawed AI‐doses than with the other two treatments. Embryo viability at 24 days of gestation varies according to the AI‐doses preservation methodology, obtaining better results with encapsulated AI‐doses, since with this treatment a greater number of viable embryonic vesicles were present.R.S.S. contributed to conceptualization; R.S.S., S.S.P.G., M.M.L., P.C.V., E.G.F., M.V.F., J.G.T., O.M., A.E.S., T.A., T.M. and J.G.A. contributed to methodology; R.S.S. and T.A. contributed to resources; A.C.I., R.S.S., S.S.P.G. and E.G.F. contributed to review; R.S.S. and E.G.F contributed to writing—original draft; S.S.P.G. contributed to writing—review and editing.The authors declare that they have no competing interests.


N = 69; 36 female; mostly non‐Hispanic White) observed characters acting inclusively or exclusively. All ages viewed excluders more negatively than includers, but only five‐ and six‐year‐olds preferred includers as play partners. Despite easily detecting and remembering exclusion events, younger children expressed no play partner preference. Children's verbal justifications revealed that older children choose partners more carefully and draw on a richer understanding of exclusion. More generally, the initial dissociation between social evaluation and preference formation underscores that these are distinct processes with different developmental trajectories.When facing social exclusion, children seek to strengthen existing social connections and form new ones. This study asked whether they also make strategic choices about the targets of their affiliative goals. Three‐ to six‐year‐olds ( What is already known on this subject?Children who observe exclusion adjust their behavior to become more attractive social partners.Prior work has investigated children’s preferences and evaluations toward excluders and includers.This prior work found surprising developmental trends, but methodology constrained conclusions.What does this study add?By 5 years, children who observe exclusion strategically select partners likely to include them.Younger children evaluate excluders negatively, but this does not guide their partner selections.With age, children justify preferences with abstract, meaningful reasoning about exclusion.Social exclusion puts young children at risk for a host of negative outcomes. Chronically excluded preschoolers are more likely to develop poor self‐regulation and internalizing problems, and they may become maladjusted, acting more aggressively and less cooperatively . Because this study was initiated prior to the publication of Hwang and Markson  and older  groups.Per our pre‐registration, we aimed to test 64 3‐ to 6‐year‐old children, but continued testing until all scheduled children had visited our laboratory. This sample size was determined using an Children were recruited to the lab from the nearby community, tested at an on‐campus preschool, or tested onsite at a local children's museum in a small mid‐Atlantic city. All children were typically developing, had normal or corrected‐to‐normal vision and hearing, and heard English at least 50% of the time. Due to the rapid nature of on‐site testing, we did not collect additional demographic information. Recent research by our group has determined that these testing locations draw samples composed of children who are primarily non‐Hispanic White (70%) with a modal family income above $100,000. Parents of all participating children provided informed consent.An additional 28 children participated, but were not included in the final sample. Three did not complete the study, three experienced technology errors, and two did not meet eligibility requirements. Twenty children were excluded due to an experimenter error resulting from a misunderstanding of the scripted procedure; this decision was made prior to coding or analysing their responses.Children viewed video stimuli on two 10.1 Lenovo tablet computers. A trio of hand‐puppets appeared in an inclusion game, and another trio in an exclusion game. Each trio wore different matching colours and included a dog  and two mice (the includers or excluders). All characters had pronouns that matched the child's own.In both games, two mice introduced themselves  and stated that they would play a game of catch; the dog replied affirmatively. In the inclusion video, the three characters received the ball 12 times each. In the exclusion video, the two mice only threw the ball to each other; consequently, they each received the ball 18 times, and the dog never received it. Thus, both games lasted for 36 throws, long enough to induce feelings of exclusion . Children's replies on the 3‐point scales were combined to form a 6‐point bipolar niceness scale ranging from 1 = ‘very not nice’ to 6 = ‘very nice’.The experimenter displayed one trio on each tablet. Each image featured the dog and mice just before the game of catch had begun. The experimenter asked, ‘Which dog got to play more’?The experimenter displayed one mouse from each game and asked, ‘Which mouse would you want to play with’? Following children's selections, the experimenter probed their justifications in two ways. First, the experimenter asked, ‘Why do you want to play with [the preferred partner]’? Second, the experimenter asked a follow‐up question. Using a new display board to reference each mouse, the experimenter asked children whether their partner preference was driven by a motivation to approach their preferred partner (i.e. ‘because that mouse would play with you’) or to avoid their dispreferred partner (i.e. ‘because the other mouse would not play with you’). The experimenter also asked children to explain this response, but these comments were not analysed.The relative order of the exclusion and inclusion games, the colour of the outfits worn by excluders and the side on which the exclusion game was presented were all counterbalanced. The including and excluding puppets were always the mice, and the dog was always the puppet who was included or excluded. All questions were asked in a fixed order.Two coders, blind to which dog was excluded, recorded children's responses from study session videos. Reliability was close to perfect (Cronbach's kappa = .99). Discrepancies were resolved through discussion with the blinded first author.N = 2; failed exclusion detection N = 4). When these participants are removed, the results are consistent with those reported below.Per our pre‐registration, we conducted analyses on the overall sample and on the younger (3‐ and 4‐year‐old) and older (5‐ and 6‐year‐old) age groups separately. Although our pre‐registration indicated that we would only include participants who accurately answered the memory check and first exclusion detection question in the final analyses, we chose to include all participants, as very few answered these questions inaccurately (inaccurate memory check mu = 0.50). We expected children to remember who excluded the dog, prefer the includer and use an approach (vs. avoidance) motivation more often than chance.We used non‐parametric analyses to understand children's responses to each question type. As all questions had clearly hypothesized answers, we used pre‐registered one‐tailed tests. To determine whether children were more likely to report having detected exclusion after it occurred, we used a McNemar test to compare children's detection responses after watching exclusion and inclusion games. To determine whether children's niceness ratings for excluders were lower than their ratings for includers, we conducted a paired Wilcoxon signed‐rank test. We used binomial tests to examine whether children's memory check responses, play preferences and reasoning for play partner preferences differed from chance  to assess how age related to children's responses to each question type. For the exclusion detection and social evaluation questions, we fit a model for each measure, featuring our predictors of interest , and using random intercepts for each child to compare across game types. For the memory check and play preference questions, which were not repeated measures, we fit logistic regression models featuring only age as a predictor. For both model types, we also fit preliminary models that included gender and all counterbalancing factors. If a counterbalancing factor significantly predicted the outcome, we included the significant predictor in the logistic regression with age.2(1) = 59.02, p < .01. This pattern was present in both younger, χ2(1) = 27.03, p < .01, and older, χ2(1) = 30.03, p < .01, age groups. Convergent results were obtained in the GLMM: Only game type predicted children's reports that exclusion had occurred, b = −27.41, z = −4.57, p < .01.Children accurately reported that social exclusion occurred after observing the exclusion event but not after observing the inclusion event, 61 of 69, χM = 5.29, SD =1.32) as nicer than excluders , V = 65.5, p < .01. This pattern was present in both younger  and older  children. In the GLMM, however, both Age, b = −0.05, t(131) = −3.43, p < .001, and the Age × Game Type interaction, b = 0.06, t(67) = 3.11, p = .003, were significant. Simple slope analyses revealed that evaluations of includers remained strongly positive across all ages, b = 0.01, t(67) = 0.75, p = .46. With increasing age, children rated social excluders as less nice, b = −0.05, t(67) = −2.97, p = .004.Children viewed includers (p < .01). This pattern was present in both younger  and older children . In the logistic regression, age was not associated with children's memory check responses, b = 0.20, z = 1.43, p = .15.Nearly all children answered the memory check correctly . However, this effect was driven by older children . Younger children showed no play partner preference . The logistic regression supported this pattern: Age significantly predicted children's partner preferences, b = 0.07, z = 2.09, p = .03. The preliminary logistic regression indicated that outfit colour predicted children's preferences, such that children were more likely to choose the blue mouse as a play partner, b = 1.26, z = 1.97, p = .04. However, when shirt colour, age, and their interaction were entered into the main model, shirt colour  and its interaction with age  did not predict children's play preferences.Overall, children preferred the includer as a play partner , rather than to avoid the mouse they did not choose. This pattern was found in both younger  and older children .We also examined children's reasons for choosing a specific play partner. One child gave both possible responses and was excluded from this analysis. The remaining children indicated that they chose their play partner because they thought that the chosen mouse would play with them ; however, older children did . Two‐tailed binomial tests found no evidence that 3‐ and 4‐year‐olds preferred either character (padjusted's < .05); however, 5‐ and 6‐year‐olds preferred the includer (both padjusted's < .04).Figure 2(1) = 8.35, p = .003 predicted play partner preferences, but the difference score and interaction term did not (both p's > .18).We next considered whether there was an association between how differently children evaluated includers versus excluders and their subsequent play preferences. We constructed a difference score for children's evaluations by subtracting their niceness ratings for excluders from their ratings for includers, and then fit a logistic regression predicting play partner preferences from this difference score, age in months and their interaction. Age, χFinally, we examined the justifications that children provided for their play preferences. First, while being blind to children's age and stated preferences, we inductively generated content categories capturing clusters of response types from transcriptions of their comments. Second, two blind coders recorded non‐exclusive occurrences of each category (κ = .90); Table The categories were: social evaluation of the mice , preference towards the mice (i.e. referencing children's own feelings towards them), explicit mention of inclusive or exclusive acts or events, evidence for more complex decision‐making  or the invocation of more abstract concepts. This final category comprised several additional sub‐categories: future‐oriented strategizing about how a mouse would treat the child (e.g. ‘…he won't pass it to me’), using morally laden terminology (e.g. ‘…the green one doesn't share’), and describing a mouse's power to grant or deny access to gameplay (e.g. ‘he let the green dog play’).p < .01); however, all of these responses were simple statements that offered little insight into their partner preferences (e.g. ‘Because I like him’). Older children were more likely to compare the two characters and to provide responses revealing more abstract reasoning (both p's < .01). However, none of these justification classifications was associated with children's play partner preferences (p's > .09). The remaining categories, referencing game play and offering social evaluations, were not associated with age group or with play partner preferences (p's > .09).Three justification categories were associated with age group. Younger children were more likely to reference their own feelings towards the mice (To ensure healthy development, children must avoid social exclusion and the harm it can bring. This study found that, around 5 years of age, children incorporate information about a potential partner's history of inclusive or exclusive behaviour into their social preferences. These preferences appear to reflect children's expectations that people who have previously included others are likely to include them. This work complements earlier research showing that children who are worried about exclusion adjust their behaviour to become more attractive social partners (Watson‐Jones et al., This work also addresses a critical open question about whether even younger children consider information about past play behaviour when making plans for future affiliation. Like older children, children as young as 3.5 years detected exclusive behaviour and evaluated excluders negatively. However, they did not consistently prefer to play with includers over excluders. This discrepancy between younger children's social evaluations and partner preferences replicates an unpredicted observation reported by Hwang and Markson . The conWhat might account for the dissociation between younger children's social evaluations and partner preferences? After observing a similar dissociation, Hwang and Markson  noted thDissociations between measures may arise when one task is more cognitively demanding than another, or when they rely on different cognitive processes. The evaluation measure required children to evaluate characters separately, but the preference measure involved comparing both characters. It is possible that this format was more demanding for younger children. However, the preference measure used an identical format to the memory check, which younger children answered easily. Thus, if younger children found it more difficult to express a partner preference than to share an evaluation, it is unlikely due to the question format.We suggest that the separate trajectories of children's evaluations and preferences may instead reflect differences in how these decisions are made and the social information children at different ages find most relevant. Younger children's social preferences can be idiosyncratic, and they may fixate on features unrelated to play experiences, such as the colour of a person's outfit (as seen here; also reported by Van de Vondervoort & Hamlin, Why might older children have approached a decision about potential playmates more carefully than younger children? In the United States, where this research was conducted, children generally begin formal schooling in kindergarten at age 5 (National Center for Education Statistics, Furthermore, kindergartners exhibit different play styles than younger children, directly engaging in more group play and spending less time as onlookers or play observers (Rubin et al., Advances in cognitive ability and social understanding may further support older children's consideration of a partner's play history in additional ways. For instance, older children may use more intricate social processes when forming peer preferences and weigh both positive and negative factors. Some children may be viewed as more popular because they are well liked by their peers and act in prosocial ways. Other children may be perceived as popular, but not well liked. This can occur when children are sociable, but exhibit relationally aggressive behaviour, such as bullying others (Nelson et al., More generally, this study provides an important reminder for broader research in social cognitive development: Social preferences do not always align with social evaluations. Children may recognize an individual as less nice, yet nevertheless wish to be their friend Hawley, . In the The authors declare that they have no conflicts of interest.Amanda Mae Woodward: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Resources; Supervision; Visualization; Writing – original draft; Writing – review & editing. Lindsay A. Horen: Conceptualization; Investigation; Methodology; Project administration; Visualization; Writing – review & editing. Sarah J. Knoll: Conceptualization; Investigation; Methodology; Project administration; Writing – review & editing. Jonathan S. Beier: Conceptualization; Investigation; Methodology; Supervision; Writing – review & editing.https://osf.io/wpu2v/?view_only=4faa9f36f8fa445a8d0caa6192b6e068].This article has been awarded Open Data, Preregistered Research Designs Badges. All materials and data are publicly accessible via the Open Science Framework at [