P < 0.05). Validation cohort results were consistent . At a 20% risk threshold, the false positive rate in the MRI model was lower when compared with the baseline model : 9–39%] vs. 44% [95% CI: 15–64%]), with the true positive rate only decreasing by a little (83% [95% CI: 63–94%] vs. 87% [95% CI: 75–100%]). 32 of 100 RPs can been performed, with no raise in quantity of patients with missed BF. We developed and verified a MRI-based model to predict BF incidence in patients after RP using preoperative clinical and MRI-related variables. This model could be used in clinical settings.To investigate if a magnetic resonance imaging (MRI)-based model reduced postoperative biochemical failure (BF) incidence in patients with prostate cancer (PCa). From June 2018 to January 2020, we retrospectively analyzed 967 patients who underwent prostate bi-parametric MRI and radical prostatectomy (RP). After inclusion criteria were applied, 446 patients were randomized into research (n = 335) and validation cohorts (n = 111) at a 3:1 ratio. In addition to clinical variables, MRI models also included MRI parameters. The area under the curve (AUC) of receiver operating characteristic and decision curves were analyzed. The risk of postoperative BF, defined as persistently high or re-elevated prostate serum antigen (PSA) levels in patients with PCa with no clinical recurrence. In the research (age 69 [63–74] years) and validation cohorts (age 69 [64–74] years), the postoperative BF incidence was 22.39% and 27.02%, respectively. In the research cohort, the AUC of baseline and MRI models was 0.780 and 0.857, respectively, with a significant difference ( Generally, radical prostatectomy (RP) is a valid treatment method for localized PCa 2. Elevated prostate serum antigen (PSA) levels are the most sensitive and specific early indicator of PCa recurrence after RP. Biochemical failure (BF) is defined as persistent, detectable PSA levels after RP  or two consecutive PSA level increases of 0.2 ng/mL or more after a period of PSA normalization . This scenario occurs in 30–40% of patients within 10 years after RP, and is associated with poorer cancer-specific outcomes 3.Globally, prostate cancer (PCa) is the second most frequent cancer and was the fifth leading cause of cancer death in men in 2020, with an estimated 1.4 million new cases and 375,000 deaths worldwide 5. The approach also detects adverse pathological features in PCa patients, such as extracapsular invasion or lymph node metastasis 10. Some studies have reported that bi-parametric MRI (bpMRI), in contrast to mpMRI without dynamic enhancement, demonstrated a similar PCa diagnostic accuracy as mpMRI 11. Also, bpMRI is highly cost-effective when compared with mpMRI, and helps with diagnostic processes and risk stratification in PCa patients 12. In our study, we evaluated the added value of bpMRI for BF prediction in PCa patients. We developed and validated a pre-surgical model, which included bpMRI parameters and clinical variables, to predict BF.Multi-parametric magnetic resonance imaging (mpMRI) is a highly sensitive tool for detecting clinically significant PCa 13. If a patient had multiple lesions in the same PI-RADS category, the lesion with the largest diameter was taken as an exponential lesion.From June 2018 to January 2020, we retrospectively and consecutively analyzed 967 patients who underwent prostate bpMRI and RP. Exclusion criteria: (1) Patients who did not receive standardized MRI scans or underwent MRI scans at other centers; (2) Patients on neoadjuvant therapies; (3) Patients with transurethral resection of the prostate; (4) Patients who received hormone or radiotherapy after RP before BF; and (5) Patients with insufficient clinical data and undetermined PSA results from postoperative follow-up. Finally, 446 patients met our inclusion criteria , which were the dominant sequences used to characterize transitional and peripheral zones, respectively 13. The prostate volume was measured by bpMRI. All lesions were evaluated by senior personnel using PI-RADSv2.1 scores. The prostate MRI regional model was defined using the following four-zone method. To trisect the prostate along its axis, the lower third was defined as the apex zone while the upper third was the basal zone. The middle third was further divided into peripheral and non-peripheral zones. According to the four-zone method, a positive zone was defined as the major part of the lesion located or a lesion involved more than half of the zone. Therefore, patients with multiple lesions may also have multiple positive zones. Also, extracapsular extension (EPE) and seminal vesicle invasion (SVI) indices were recorded.BpMRI was performed using a 3 T MRI system , involving only T2WI and DWI , PSA at diagnosis, PSA density, suspicious digital rectal examination (DRE) (yes/no), biopsy pathology (ISUP grade), and surgical technique type . The MRI model included these predictors, plus PI-RADS scores , EPE at bpMRI (yes/no), SVI at bpMRI (yes/no), the zonal location of suspected lesions , maximum diameter of the suspected lesion, and clinical stage . The outcome was BF. Postoperative PSA levels were initially measured at 1–2 months after RP, then at 3 month intervals in the second year, and intervals exceeding 6 months were deemed lost to follow-up.14. A calibration slope near 1 indicated the correct predictive model fitting. The diagnostic correctness of both models was surveyed and balanced by the area under the curve (AUC) of the receiver operating characteristic (ROC). Model fitting was evaluated using calibration plots 14. False positive rates (FPR) and true positive rates (TPR) were used to evaluate the prediction accuracy of postoperative BF. The TPR indicated the ratio of patients with BF above the threshold, while FPR indicated the proportion of patients with non-BF values above the same threshold. The clinical value of the prediction model was weighed using the ratio of avoided BFs, the net benefit (NB), and a net reduction (NR) in false positives (FPs) 15.We developed and validated two multivariable logistic regression models to predict BF after RP. We recalibrated the risk model in the validation cohort by matching logistic regression with the logit of the predictive risk 2 tests, and we used Wilcoxon tests to analyze continuous variables. These tests were bilateral and a P < 0.05 value indicated statistical significance.We analyzed 95% confidence interval (CI) and SE values of prediction ability estimator in every predictive models, and the difference between the two models which from 2000 samples by stochastically selecting patients with substitution. We readjusted the prediction model and recalculated the prediction risk of every model in every sample in the research cohort. The 95% CIs came from 2.5% and 97.5% of the re-sampling distribution. Data for the resampling process included outcome (whether there was postoperative BF) and the unregulated predicted risk analyzed according to every risk models in the validation cohort. In every sample, the simple model for recalibration was readjusted, and then the predicted risk after calibration was recalculated. We compared variable distributions between research and validation cohorts. Categorical variables were assessed using χAll methods were performed in accordance with relevant guidelines and regulations. This retrospective study received ethical approval from the Hospital Ethics Committee of the First Affiliated Hospital of Nanjing Medical University. Written informed consent was obtained from all subjects.In accordance with our exclusion criteria, we finally selected 446 consecutive patients. Then, we randomly divided 335 patients into the research cohort and 111 patients into the validation cohort, and both separately included in the model. Patient demographics in both cohorts are shown in Table P > 0.05).The MRI characteristics for both cohorts are shown in Table Table In the baseline model, PSA, GG3, GG4, and GG5 were independent predictors in terms of clinical variables, with statistical significance in the MRI model Table .Table 3LP < 0.05) in the MRI model in the research cohort   or cancer had disseminated beyond the prostate and outside the surgical field at surgery  19. Several studies reported that MRI-derived parameters in a risk model increased the accuracy of BCR prediction. For example, a multivariable model including MRI PIRADS, along with clinical and pathological variables, outperformed European Association of Urology classification and CAPRA scores for predicting BCR  20. Moreover, in another study 8, a pre-surgical model incorporating PI-RADS, fusion-targeted biopsy grade, and extraprostatic extension on MRI showed better accuracy in predicting BCR (AUC = 0.68–0.71) when compared with the D’Amico classification (AUC = 0.66–0.71). However, these findings used BR as the endpoint, and persistent PSA levels (> 0.2 ng/ml) after RP also required preoperative intervention. In Soga et al., three sub-groups were defined in terms of the D’Amico classification risk  and the GP score (Gleason score multiplied by PSA). No significant difference was observed in the non-BF rate between low risk and low GP score subgroups or intermediate risk and intermediate GP score subgroups. But the non-BCF rate of the high GP score subgroup was significantly lower when compared with the high-risk subgroup . Based on multivariate analyses, a high GP score : 3.78; 95% CI: 1.95–7.35) was a significant independent risk factor for BCF after prostatectomy. However, these prediction models were limited to clinical parameters 21. In previous studies, Teloken et al., reported that transition zone location indicated a better BR-free survival after adjusting for poor clinicopathological features 22. Shin et al., showed the zonal location of lesions by MRI, and in addition to the PI-RADS category, this was putatively helpful estimating postoperative BF risks 9. These studies confirmed the role of MRI in predicting BF, but they did not develop prediction models. When MRI parameters were included in our prediction model, we identified better model fitting and a higher diagnostic accuracy, avoided more BFs, and maintained a similar level of sensitivity to BFs in contrast with the baseline model.Several commonly used multivariate risk tools based on pre-diagnosed PSA, T stage by DRE, and biopsy grading group categories have been used to predict postoperative PSA results We used DCA in both risk prediction models to compare the NBs of “treat none” with “treat all”. “Treat none” refers to RP for localized PCa, while “treat all” refers to neoadjuvant androgen deprivation, extended radical operation, and lymph node dissection. In clinical settings, the risk threshold of “treat all” may be determined after physicians and patients weigh and judge the relative hazards of aggressive treatment regimen and the benefits of determining postoperative BFs. So, there was no one risk threshold in deciding who demanded RP, but a series of risk thresholds. Because of higher adverse-effect profiles and the disputed curative effects of “treat all”, we selected high risk thresholds for our DCA. Our novel MRI model also demonstrated better calibration characteristics and higher NBs when compared with the baseline model. Our DCA data indicated that when index lesion locations on bpMRI were included in the prediction model, it showed better model fitting and a higher predictive accuracy, thereby decreasing unnecessary treatments while increasing BF sensitivity when compared with the baseline model.23.Our model data were similar to previous data. However, our study had several limitations; it was a retrospective, single center data study, and was internally validated. In addition, this study was based on bpMRI, which may have some bias compared with multi-parameter MRI. These factors may have caused some verification bias and the data may not be universally applied Using preoperative clinical and MRI-related variables, we developed and verified a MRI-based prediction model which predicted BF incidence in patients after RP. This model could be helpful in clinical settings.


Dynesys stabilization (DS) is utilized to preserve mobility at the instrumental segments and prevent adjacent segment pathology in clinical practice. However, the advantages of DS method in medium and long-term follow-up remain controversial.To compare the radiographic and clinical outcomes between DS and instrumented fusion in the treatment of degenerative lumbar spine disease with or without grade I spondylolisthesis with a minimum follow-up period of 2 years.We conducted a comprehensive search of PubMed, EMBASE, Cochrane, and Web of Science databases, Chinese National Knowledge Databases, and Wanfang Database for potentially eligible articles. Clinical outcomes were assessed in terms of VAS and ODI scores, screw loosening and breakage, and surgical revision. Radiographic outcomes were assessed in terms of postoperative range of movement (ROM) and disc heigh. Moreover, adjacent segment degeneration (ASDeg) and adjacent segment disease (ASDis) were evaluated.Seventeen studies with 1296 patients were included in the meta-analysis. The DS group was associated with significantly lower postoperative VAS scores for low-back and leg pain, and lower rate of surgical revision than the fusion group. Moreover, the Dynesys group showed significantly less ASDeg than the fusion group but showed no significant advantage over the fusion group in terms of preventing ASDis. Additionally, the ROM at the stabilized segments of the fusion group decreased significantly and that at the adjacent segments increased significantly compared with those of the DS group.DS showed comparable clinical outcomes and provided benefits in preserving the motion at the stabilized segments, thus limiting the hypermobility at the adjacent segments and preventing ASDeg compared with the fusion method in degenerative disease with or without grade I spondylolisthesis.The online version contains supplementary material available at 10.1186/s12893-023-01943-6. Lumbar fusion has been considered as the gold standard for the treatment of lumbar degenerative pathologies over the last decades , 2. HoweIn recent years, non-fusion systems have been applied clinically to prevent the incidence of adjacent segment pathology  after lumbar surgeries –11. The However, inconsistent results have been obtained in the advantages of DS over fusion method in terms of clinical outcomes, including the relief in post-operative pain status (VAS scores) and functional status restoration (ODI scores) –7, 20–23This meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines . A systeThe inclusion and exclusion of studies for the meta-analysis were based on the following criteria. (1) For participants, the study population consisted of patients who satisfied the following criteria: aged 18 years or older; mean follow-up period ≥ 2 years; suffering from lumbar degenerative diseases, including disc herniation, lumbar spinal stenosis, and grade I degenerative spondylolisthesis; and having 1–4 fixed segments in the lumbar. Studies on patients with grade II or higher spondylolisthesis, ankylosis spondylitis, spinal tumor, and severe spinal deformity were excluded. (2) The intervention in the experimental group was dynamic DS. Studies on hybrid dynamic stabilization and other kinds of dynamic stabilization, including Coflex, Wallis, and X-stop systems were excluded. (3) For comparison, the intervention in the control group was instrumented fusion methods, including posterior lumbar interbody fusion, transforaminal lumbar interbody fusion (TLIF), and posterolateral fusion. (4) In terms of outcomes, studies were eligible if they satisfied at least one of the following outcomes: clinical outcomes at final follow-up , ASP (ASDeg and ASDis), and radiographical outcomes (postoperative ROM and disc heigh). ASDeg (radiographic ASD) represents radiographic etiologies adjacent to the surgically treated spinal level that involves loss of disc height, disc degeneration, stenosis, instability, or hypertrophic facet arthritis, regardless of the presence of symptoms. [Cochrane risk-of-bias criteria  and NewcTwo reviewers independently extracted relevant data from the qualified studies. Any disagreement was settled by a third reviewer. Leading author, publication year, study design, country of origin, study period, age, gender distribution, number of treated segments, fusion type, and follow-up period were extracted from the included studies.2 and chi-squared tests at a significance level of P < 0.05 for assessment of statistical heterogeneity. A fixed-effects model was utilized if no evidence of heterogeneity (I2 < 50%) was observed among the studies. Otherwise, a random-effects model was used. The sensitivity analyses were performed to investigate the source of heterogeneity. In addition, publication bias was evaluated by Egger tests when the number of included studies was 9 or more. Except for publication bias assessed by STATA version 15.1, statistical analysis was performed with Review Manager version 5.3. All tests were two-tailed, and P < 0.05 was considered statistically significant.Odds ratio (OR) and its 95% confidence interval (CI) were calculated for dichotomous data. Mean difference (MD) and its 95% CI were calculated for continuous data. We used IThe process for literature search is summarized in Fig. Table The risk of bias for the included studies are shown in Additional file P < 0.001, I2 = 0%; Fig. P < 0.001, I2 = 0%; Fig. Four prospective studies , 17, 30 P = 0.36, I2 = 0%; Fig. Four prospective studies , 16, 30 P = 0.73; I2 = 0%; Fig. P = 0.62; I2 = 15%; Fig. P = 0.756).Eleven studies –33, 35 aP = 0.03; I2 = 0%; Fig. Seven studies , 32, 33 P < 0.001; I2 = 0%; Fig. Eight studies , 32–35 pP = 0.15; I2 = 0%; Fig. Four studies , 33, 35 P < 0.001, I2 = 98%; Fig. 2 = 98%). The results showed the same conclusion  as before.Five studies , 31, 35 P < 0.001, I2 = 95%; Fig. 2 = 95%). The obtained result  was consistent with the above outcomes after removing the studies of Yang et al. [Seven studies , 32, 33 g et al.  and WangP = 0.040, I2 = 99%; Fig. P < 0.001, I2 = 0%) confirmed the above outcome.Three studies , 31, 35 P = 0.170, I2 = 83%; Additional file P = 0.300, I2 = 0%; Additional file Five studies , 24, 33 Spine fusion is a primary therapy for spinal degenerative diseases, but this method is associated with several complications, especially the acceleration of ASP , 5, 13. Many studies have confirmed the safety and clinical equivalence of DS to fusion method. , 24, 36 DS is mainly used to minimize ASP. , 37 HashAnother early radiographic manifestation of ASP in clinical practice is the narrowness and loss of the intervertebral space, and its height is commonly considered as an indicator to evaluate the degree of ASP , 15. In Whether DS can delay the occurrence of ASP has not been confirmed. In the study of Bredin et al. , a mean The prevention of ASDis is crucial because of the potential risk of revision surgery and adverse effect on health care outcomes and cost. Our meta-analysis demonstrated that the Dynesys group showed less ASDis than the fusion group, whereas the difference was not significant. The result revealed that DS can prevent ASDeg instead of ASDis compared with the fusion method. The occurrence of ASDis is relatively lower than that of ASDeg, because ASDeg does not always cause clinical symptoms. Furthermore, the lack of remarkable difference in disabilities (ODI) post-operatively between the two methods indicate the similar incidence of ASDis after surgery.Screw loosening is a common complication of DS. The current study also showed that the Dynesys group did not differ from the fusion group in terms of screw loosening and screw breakage. Ko et al.  includedThe disadvantages of DS should be highlighted. DS is designed to preserve lumbar vertebral mobility and reduce the load on the intervertebral disc; if these two points cannot be achieved, the use of this technique has no advantage . The DynThis meta-analysis has several limitations. First, only one RCT along with 16 comparative cohort studies was included, resulting in less powerful results compared with that obtained purely from RCTs. Second, the definitions of ASDed and ASDis in previous studies are inconsistent and ambiguous. No consensus criterion has been established to define ASDed and ASDis, leading to imprecise outcome measures. Third, the number of the included studies was limited in terms of the ROM of LL, disc heigh at proximal adjacent segments, and ASDis. Furthermore, the fusion method is likely to encounter screw loosening initially, while the dynamic stabilization is likely to fail in the latter part. This flaw is expected in studies that evaluate early outcomes. Thus, future work should employ more RCTs of high quality and patients with follow-up more than 10 years from different cultural contexts.DS showed equivalent outcomes in terms of ODI, screw loosing, screw breakage, and ASDis compared with fusion method. Moreover, DS had better clinical measurements in terms of VAS scores for back and leg pain than fusion instrument. DS showed comparable clinical outcomes and provided benefits in preserving the motion at the stabilized segments, thus limiting the hypermobility at the adjacent segments and preventing ASDeg compared with the fusion method in degenerative disease with or without grade I spondylolisthesis.Additional file 1.Table S1. Search strategy for each database.Additional file 2.Table S2. Risk of bias assessment of the RCT study.Additional file 3.Table S3. Risk of bias assessment of the cohort studies.Additional file 4.Fig. S1. Forest plots of Dynesys stabilization versus instrumented fusion: (A) disc height at the intervertebral segment; (B) disc height at the proximal adjacent segment.


The treatment of choice for patients presenting with obstructive cholestasis due to periampullary carcinoma is oncologic resection without preoperative biliary drainage (PBD). However, resection without PBD becomes virtually impossible in patients with obstructive cholangitis or severely impaired liver cell function. The appropriate duration of drainage by PBD has not yet been defined for these patients.A retrospective analysis was conducted on 170 patients scheduled for pancreatic resection following biliary drainage between January 2012 and June 2018 at the University Hospital Dresden in Germany. All patients were deemed eligible for inclusion, regardless of the underlying disease entity. The primary endpoint analysis was defined as the overall morbidity (according to the Clavien-Dindo classification). Secondary endpoints were the in-hospital mortality and malignancy adjusted overall and recurrence-free survival rates.A total of 170 patients were included, of which 45 (26.5%) and 125 (73.5%) were assigned to the short-term (< 4 weeks) and long-term (≥ 4 weeks) preoperative drainage groups, respectively.p = 0.02). We found that long-term preoperative drainage  and periampullary carcinoma  were independent risk factors for postoperative morbidity, based on the results of a multivariate regression model. The adjusted overall and recurrence-free survival did not differ between the groups (p = 0.12).Surgical complications (Clavien-Dindo classification > 2) occurred in 80 (47.1%) patients, with significantly fewer complications observed in the short-term drainage group (31.1% vs. 52%; PBD in patients scheduled for pancreatic surgery is associated with substantial perioperative morbidity. Our results indicate that patients who have undergone PBD should be operated on within 4 weeks after drainage. Preoperative biliary drainage (PBD) in patients presenting with painless jaundice due to periampullary carcinoma has been an issue of debate for many years. According to van der Gaag et al. , surgicaInterestingly, the existing data for the subcohort of patients with PBD are weak and somewhat inconsistent with respect to the accurate preoperative drainage time. Son et al.  found thThus, it remains inconclusive whether patients develop more postoperative complications following a short or long biliary drainage duration prior to pancreaticoduodenectomy. In addition, there is still a lack of sufficient data to determine the clinical benefit of prophylactic stenting in patients with tumor-related cholestasis who are scheduled for neoadjuvant chemotherapy.Therefore, the primary aim of this study was to evaluate the optimal period for PBD prior to pancreatic resection. We aimed to provide data on perioperative morbidity and mortality rates, along with overall and recurrence-free survival rates.This article was written in accordance with the STROBE statement . The expNo exclusion criteria were defined regarding the time between drainage and surgery, the entity of the underlying disease, or the type of operation performed.Basic patient characteristics included median age, sex, body mass index (BMI), and physical status according to the American Society of Anesthesiologists (ASA) . The patPBD is usually avoided unless there is no alternative due to patient-related or therapy-associated factors. Indications for PBD include excessive jaundice > 250 µmol/L) with severe symptoms , neoadjuvant treatment, acute obstructive cholangitis, or impaired liver cell function [0 µmol/L The preoperative period between stent placement and surgery was classified as one of two categories: < 4 weeks (PBD I) and > 4 weeks (PBD II). The groups were defined according to the most recent literature .The primary endpoint for this study was the overall morbidities defined according to the Clavien–Dindo classification (CDC)  that areMorbidity analysis was performed separately for the different PBD periods.Data on the length of hospital stay (LOS) and duration of intensive care unit stay were extracted from the patient files. The rehospitalization rate was defined as any hospital readmission within 30 days of discharge after the index operation due to PD-related complications. Overall survival (OS) and recurrence-free survival (RFS) rates were adjusted for in-hospital mortality and underlying malignancy. The adjusted OS for patients with an underlying malignancy was calculated as the date of death or the time of last contact (censored) and RFS, by the date of diagnosis of recurrence.Intraoperative bile duct swabs were analyzed with respect to the frequency of positive bacterial detection. In addition, the resistance situation of the bacterial cultures found in the bile duct swabs was analyzed according to the publication by Magiorakos et al. .The classification of the results was made according to the observed results of the bile duct cultures: negative bile duct cultures, multidrug-sensitive (MDS), multidrug-resistant (MDR), and extensivedrug-resistant (XDR).Data were analyzed using SPSS version 21 software . The normality of continuous data was assessed using the Kolmogorov–Smirnov test and by inspecting the frequency distributions. Variance homogeneity was tested using Levene’s test.t-test, or the Mann–Whitney U test was performed on continuous variables where appropriate, and the results were represented as median and interquartile range (IQR).Competitive analysis was performed to compare baseline characteristics between the groups of patients categorized according to PBD duration using the chi-square test or Fisher’s exact test for categorical variables. Unifactorial analysis of variance, Student’s Logistic regression analysis was performed to determine the relationship between the different groups regarding PBD duration and CDC > 2 complications. Other factors included in the multivariate regression analysis were comorbidities, preoperative cholestasis, and preoperative chemotherapy. All clinically relevant variables and those with a p-value of < 0.3 in univariate regression analysis were included in a multivariate stepwise regression model.The Kaplan–Meier method was used to calculate OS and RFS curves, and the log-rank test was used to identify the differences between the curves.p-value of < 0.05 was considered the threshold of statistical significance for all analyses. During the analyses, missing data were treated as missing completely at random. Thus, a complete case analysis was performed, and some patients were excluded from the analysis.A Between January 2012 and June 2018, a total of 702 patients scheduled for pancreatic resection due to an underlying malignancy, borderline tumor , or chronic pancreatitis were identified using data from a prospectively created database.n = 532). Our study cohort included a total of 170 (24.2%) patients with PBD with a median age of 68.2 years. Of these 170 patients, 149 (87.6%) underwent surgery for an underlying malignancy. Pancreatic ductal adenocarcinoma (PDAC), neuroendocrine tumor (NET), and distal bile duct malignancies were histologically confirmed in 71 (41.8%), 4 (2.4%), and 74 (43.5%) cases, respectively. The operations performed were PPPD, cPD, DPPHR, and TP in 112 (65.9%), 29 (17.1%), 8 (4.7%), and 18 (10.6%) cases, respectively.Patients without PBD were excluded from further analysis  and 125 into the long-term group . Both groups were comparable in terms of sex distribution, median age, BMI, preoperative tumor marker, ASA score, and insulin/non-insulin-dependent diabetes (Table The incidence of preoperative cholestasis differed significantly between groups. The percentage of patients in the short- and long-term groups who presented with hyperbilirubinemia at the time of surgery was 71.1% and 36% (p < 0.001), respectively.The median time between preoperative stent placement and surgery was 40.5 days IQR 27–90.3), with the majority of stents being plastic stents (95.3%). Stent replacement was performed in 43 (25.3%) cases and at least twice in 25 (14.7%) cases. Patients in the long-term group underwent significantly (p < 0.001) more stent replacements. In the short-term group, only six patients (13.3%) required a stent replacement. Additional stent-related information is presented in Table 7–90.3, wp < 0.001) longer time interval between stent placement and surgery  compared to patients with PDAC , NET , and distal bile duct carcinoma .Patients who underwent surgery for pancreatitis experienced a significantly  fewer positive bile duct cultures (46.7%) compared to the long-term stenting group (91.8%).The results of the bile duct culture were available in 127 (74.7%) of the cases, of which 103 (81.1%) showed a positive smear test. The short-term stenting group had significantly (The same observation could be seen with regard to the resistancy pattern: Significantly more MDR and XDR bacteria were found in the PBDII group Table .Table 3Ip = 0.02) between the PBD groups. Patients assigned to the short-term PBD group experienced significantly fewer complications (31.1%) than those in the long-term PBD group . The results are presented in Table Overall, major complications occurred in 80 patients 47.1%), and the complication rate differed significantly  for major postoperative complications (CDC > 2). The p-value threshold of 0.3 in univariate regression analysis was reached in patients with an ASA score II , ASA-score III , ductal adeno-carcinoma , neuroendocrine tumor , periampullary carcinoma , and preoperative anemia   2.399; 95% confidence interval (CI), 1.165–4.939; p < 0.01) and 5.519 for periampullary carcinoma   as well as periampullary cancer in our cohort. The odds ratio for PBD II was 3.386 . The 30-day rehospitalization rate was 13.5%. By performing a log-rank test for the probability of discharge following PD, we found that patients in the PBD I group were significantly more likely to be discharged from the hospital earlier (p < 0.01) , and a significant difference is observable between the groups  recommend that patients should only be considered for PBD if the preoperative bilirubin level exceeds 250 µmol/L, cholangitis is present, or if the patient is undergoing preoperative chemotherapy , 20, 24.In our cohort, 80 patients (47.1%) experienced a major complication (CDC > 2) during the postoperative follow-up. These data correspond to the complication rates reported in previous studies that have investigated the influence of PBD on postoperative morbidity , 25. HowIn addition, the median hospital stay duration of the short-term PBD group (19 days) was significantly shorter than that of the long-term PBD group (22 days). Using the log-rank test, we found a significantly greater probability of postoperative early hospital discharge for patients in the short-term PBD group. Moreover, after adjusting for the indication for adjuvant chemotherapy, more patients in the short-term group (51.2%) received adjuvant chemotherapy than those in the long-term group (35.3%).The complexity of determining the appropriate PBD time is evident from these contradictory data. While our data suggest that a shorter PBD time might be beneficial in terms of postoperative morbidity, Sandini et al. concluded that pancreatic resection should be postponed for 4–6 weeks after stent placement to reduce postoperative complications. These conclusions are supported by experimental data showing that impaired liver cell function due to cholestasis is restored 4–6 weeks after biliary drainage at the earliest –28. In cThe strength of the presented dataset is that it originates from a single high-volume center with uniform standards concerning the decision for PBD , along wNotably, while our study provides some new evidence, we acknowledge its limitations. In line with the results reported by Son et al. and Sandini et al. , we presFurthermore, the retrospective design of the study has inherent limitations, such as recall and selection biases. Moreover, the severity of the underlying disease might also influence the PBD-time which is not possible to assess in this retrospective design.Another limitation we need to acknowledge is the distribution of the different types of histo-pathology between the groups: Even though the allocation of malignant and benign disease was comparable between the groups, still the different pathologies are not distributed completely equal between the PBD groups. This still can cause a bias in the survival analysis.Nevertheless, discussion on the appropriate duration of preoperative drainage is still ongoing. Given the inconsistent evidence, the question of whether postponing PD in cases of PBD increases postoperative morbidity has not yet been answered. However, one must be mindful of the psychological burden of these patients and pancreatic resection should be performed at the earliest possible stage, unless stronger contrary evidence arises.PBD in patients scheduled for pancreatic surgery is associated with substantial postoperative morbidity and a high mortality rate. In contrast to recently published results by Sandini et al.,  we showeAdmittedly, the complexity of determining the appropriate preoperative drainage time in light of the increasing number of patients being treated in a neoadjuvant setting cannot be determined with small, inconsistent retrospective trials. In view of these contradictory results, we advocate performing a prospective multicenter trial to determine the optimal interval between PBD and time-to-surgery.


Pennisetum giganteum (P. giganteum) on growth performance, oxidative stress, immunity and gastrointestinal microflora of Boer goats under thermal stress.This study was conducted to evaluate the effects of fermented feed of n = 10; normal P. giganteum) and FPG , and the ratio of concentrates to roughage was 3:2. Both groups of animals were kept in sheds and exposed to summer thermal stress from 10:00 h to 18:00 h . At the end of the study, the animals were slaughtered and assessed for various characteristics.The study was conducted during 45 days using twenty 2 months Boer goats. The goats were randomly allocated into two groups: NPG (p < 0.05) average daily gain  and carcass weight (4.38 kg), while decreased (p < 0.01) average daily feed intake  and the feed:gain  ratio. The CAT, GSH-Px activities and GSH in serum, liver and spleen, and the levels of IgA, IgG, IgM, IL-2, IL-4 and IL-1β in serum of FPG-fed goats were significantly higher (p < 0.05) than those of NPG-feeding goats. Further, we found that FPG feed is rich in nutrients with Lactobacillus (65.83%) and Weissella (17.80%). Results for gastrointestinal microbiota composition showed that FPG-feeding significantly enhanced the abundance of Lactobacillus and unidentified Clostridiales, and reduced Anaerovibrio and Methanobrevibacter. Meanwhile, Spearman’s correlation analysis showed that these microbiotas were closely related to the improvement of oxidative stress and immune indexes of goats.The findings from the study revealed that FPG-feeding significantly increased (These results demonstrated that FPG-feeding not only reduces oxidative stress and improves ROS clearance to enhance antioxidant defense system, but also improves gastrointestinal microbiota to enhance immune function by overcoming the adverse effects of heat stress, and further improve growth performance of goats. P. giganteum (FPG) under thermal stress in summer.It is first time to study the feeding of Boer goats with the fermented feed of P. giganteum (FPG) in Boer goats’ diets improved growth performance, alleviated oxidative stress, enhanced immune defense function, and gastrointestinal microflora.Fermented feed of The growth performance and health of small ruminants are closely related to the stability of gastrointestinal microflora.Small ruminants, especially goat kids, play a significant part in the livestock industry . Goat kiThe gastrointestinal tract of ruminants is a very complex ecosystem, in which the development and microflora composition have a close effect on the establishment of digestion and absorption function, growth performance and health statue of the body . BickharPennisetum giganteum (P. giganteum), a perennial erect tufted plant of tall Gramineae, has thick and large leaves and rich in sugar, lignin, crude protein and crude fiber, so it has the reputation of good palatability and high nutrition .The study was carried out from August to October at the Breeding Farm which is located in Baizhong Town, Minqing County, Fujian Province . Ambient temperature and relative humidity (RH) inside and outside the sheds were recorded daily (daytime and nighttime) throughout the entire period of experiment. The temperature and humidity index (THI) values were calculated according to P. giganteum  were obtained from the plantation base of the National Engineering Research Center of JUNCAO Technology. Fermented film was purchased from Shanghai Bright Holstan Co., Ltd. The fermentation process of fermented feed of P. giganteum is as follows. Briefly, the smashed P. giganteum (2–3 cm), while was mixed with corn flour and wheat bran , was sprayed with 2.64% culture-fermented  for 45 days, which were kept in a well-ventilated shed (3 m × 4 m) under proper sanitary conditions. All animals were fed forage mix containing concentrate (60%) and roughage (40%) ad libitum, which coarse ratio was based on P. giganteum as normal group, base material of P. giganteum was composed of P. giganteum and corn flour and wheat bran (8:1:1); (2) FPG group: goats were fed with fermented feed of P. giganteum. Feed was offered at 09:00 and 18:00 every day, water and salt-mineral lick were offered for ad libitum access to animals during the experiment. Feed amount was 4 ~ 5% of the body weight of goat and adjusted according to the feed intake of the previous day to ensure that there was unfinished feed in the feeding tank.Twenty Boer goats  of 2 months of age were used for this experiment. Animals were vaccinated and dewormed for external parasites before the start of this experiment. After 2 weeks of adaptation, the goats were randomly divided into the following two groups (P. giganteum (PG), base material of P. giganteum (NPG) and fermented feed of P. giganteum (FPG) were collected, frozen with liquid nitrogen and stored at −80°C.At the beginning of the experiment, samples of fresh During the experiment, the feed and residual feed amount of the two groups were accurately recorded every day. The animals were weighed on an empty stomach at 8:00 am on the 2nd day of the experiment every 15 days, the aim was to monitor their initial and final body weight (IBW and FBW) to calculate net weight (NW), average daily gain (ADG), average daily feed intake (ADFI) and feed to gain ratio (F/G).At the end of the experimental period, the Boer goats were fasted for 12 h. Blood samples were collected into 1.5 ml sterilized tubes by jugular puncture using 10 ml disposable needle tube and placed at room temperature for 2 h. The serum was separated from the blood by centrifugation at 3000 rpm for 10 min and stored at −80°C.The carcass was obtained from each goat after postmortem, which was killed by bloodletting through jugular vein. Then, the carcass weight, the eye muscle area and backfat thickness of the carcass were evaluated. In addition, all parts of gastrointestinal tract , viscera and kidney fat were separated and weighed successively. The cecal contents and rumen fluid samples filtered by four layers of gauze were collected in 5 and 15 ml sterile tubes, respectively, rapidly frozen in liquid nitrogen and stored at −80°C. At the same time, part of the rumen and intestine  were taken and fixed with 10% formalin. Finally, parts of liver tissue and spleen tissue from the same group were removed, cleaned with phosphate buffered saline (PBS), rapidly frozen with liquid nitrogen and stored at −80°C.Rumen and intestinal samples were clipped, dehydrated, paraffin-embedded, sectioned, stained with hematoxylin and eosin, sealed and observed under a positive white light microscope  at 20 × or 40 × magnification.w/v) to prepare homogenates using Ultra-turrax in an ice bath. The supernatant was collected after centrifugation at 1000 × g for 15 min at 4°C. Then, biochemical assays of the serum or liver and spleen samples were immediately measured by the kit  according to the manufacturer’s instructions, including hydrogen peroxide (H2O2), malondialdehyde (MDA), lipid peroxidation (LPO), catalase (CAT), total antioxidant capacity (T-AOC), total superoxide dismutase (T-SOD), glutathione reductase (GR), glutathione peroxidase (GSH-PX), reduced glutathione (GSH).The liver or spleen was mixed with normal saline at a ratio of 1:9 , and were qualified by Qubit quantification. And then the sequencing was conducted by the Illumina NovaSeq platform. The raw tags were processed by QIIME (V1.9.1) and UCHIME algorithm  and 806R (5′-GGA CTA CHV GGG TWT CTA AT-3′) of feed samples, 341F (5′-CCT AYG GGR BGC ASC AG −3′) and 806R of rumen fluid and cecal contents samples . All thelgorithm . The efflgorithm  with 97%lgorithm .t-test using SPSS 13.0 and GraphPad Prism 8 software. All the results are presented as the mean. The reliability of experimental data was expressed by Standard Error of Mean (SEM). The significance level of the test results was set at p < 0.05 and p < 0.01, which were considered as statistically significant and extremely significant, respectively.Statistical analysis of all data was applied to investigate correlation by unpaired two-tailed Students’ p = 0.44). After the experiment, compared with NPG group, FBW of FPG group was increased by 11.44% (p = 0.05), NW and ADG of FPG group were extremely significantly increased by 73.6 and 82.7% (p < 0.01), respectively. ADFI and F/G ratio were extremely significantly decreased (p < 0.01).Both groups of Boer goats showed normal behavior throughout the 45-day experiment. As can be seen from p < 0.05), which were increased by 20.5, 25.86, and 94.94%, respectively. Carcass weight ratio, back fat thickness and viscera weight of FPG group were higher than those of NPG group, but there was no significant difference between the two groups (p > 0.05). Performance indexes of gastrointestinal tract were shown in p < 0.01), and omasum weight, abomasum weight and large intestine weight of FPG group were significantly higher than that of NPG group (p < 0.05). There were no significant differences between the two groups in other indexes of gastrointestinal tract detection, such as rumen wall thickness, papilla height, rumen weight and reticulum weight (p > 0.05).The slaughter performance  was showp < 0.01), only rumen tissue score has no significant difference (p > 0.05).The histological morphology of rumen sections is referred to in 2O2, MDA and LPO in serum of FPG group were decreased by 45.74% (p < 0.05), 4.28% (p > 0.05) and 14.81% (p < 0.05) as compared to the control group (NPG). The above three indicators in liver of FPG group were significantly decreased by 54.97, 58.97, and 59.09% (p < 0.05), respectively. In spleen, the content of H2O2 in FPG group was significantly decreased (p < 0.05), while MDA and LPO contents had no significant differences. As shown in p < 0.05) and GSH, GSH-Px (p < 0.01) in serum of FPG group were significantly increased, while there was no significant difference in T-SOD. In liver and spleen, the activities of CAT, GSH and GSH-Px in FPG group were significantly increased (p < 0.05), while there was no significant difference in T-SOD. Interestingly, there was no significant difference between liver GR and spleen T-AOC activities, while spleen GR and liver T-AOC activities increased significantly (p < 0.05).The oxidant indices in p < 0.05). Furthermore, the levels of IL-6 increased and decreased without any significant difference.At the end of 45 days of feeding, different immune indexes were observed in Lactobacillus (65.83%) and Weissella (17.80%) in FPG feed was significantly higher (p < 0.01) than that in PG feed and NPG feed (Lactobacillus in FPG group (3.94%) were significantly higher (p < 0.05), while Anaerovibrio and Methanobrevibacter was significantly lower (p < 0.05) than that in NPG group. Lastly, the intestinal microbiota of NPG and FPG group were composed mainly by the phyla Firmicutes , Bacteroidetes  and Proteobacteria , respectively  were higher than those in NPG group .Relative percentages of dominant taxa at phylum and genus levels were assessed by feed, rumen and intestinal microbiota . The abuNPG feed . AdditioNPG feed . Interesectively . Other pectively , the relMethanobrevibacter was positively correlated with spleen MDA, but negatively correlated with spleen GSH-Px and liver GSH-Px, T-AOC  and spleen indexes , but positively correlated with liver . More interestingly, the Lactobacillus was positively associated with serum GSH, GR, IgA, IgG, IgM, liver GSH, spleen CAT, GSH, T-SOD, T-AOC, but negatively related to serum H2O2, LPO, and liver H2O2. In addition, serum IL-2 had a positive correlation with Succiniclasticum, Alistipes, Romboutsia and unidentified Enterobacteriaceae. Results , while crude protein, crude fat content and abundant microorganisms such as Lactobacillus and Weissella were significantly increased (p < 0.01). Reports indicate that the roughage with high protein and low crude fiber had better palatability, which was beneficial to animal digestion and absorption, thus improving the carcass quality (Lactobacillus and Weissella can increase the abundance of short-chain fatty acids (SCFAs), and stimulate the development of the gastrointestinal tract by adjusting gastrointestinal flora structure, thereby improve inflammation  were significantly decreased  as well as the production of volatile fatty acids . Furthermore, FPG significantly attenuated oxidative stress of liver and spleen and improved its antioxidant capacity. Finally, FPG ameliorated cytokines of serum to enhance immune function. However, we have only been able to demonstrate that FPG diets improve immune function through regulating the gastrointestinal microbiota, and further research is needed on how the gastrointestinal microbiota works.The above experiments indicated that the decrease of various biochemical indexes in goats under thermal stress conditions resulted in the immunosuppression of goats. FPG diet can improved the immunity of goats, as evidenced by remission of disease phenotype, the restoration of intestinal microecology, and improvement of growth performance. In terms of the correlation between gastrointestinal microbiota and immunity, FPG feed rich in beneficial bacteria, such as In conclusion, this experiment highlighted the effects of thermal stress on immunocompromised Boer goat models under temperate environment. The results indicate that FPG-feeding improves the growth performance and biochemical indices of Boer goats. Besides, FPG-feeding effectively enhanced antioxidant defense system and immune function through reducing hepatolienal oxidative stress and increasing the scavenging ability of ROS, as well as ameliorating cytokines of serum and the homeostasis of gastrointestinal microbiotas. FPG will have a good application prospect in replacing antibiotics acted as a functional feed. These investigations provide new experimental evidence for the future application of FPG diets in goats.The datasets presented in this study can be found in online repositories. The data of 16s sequence data presented in the study are deposited in the NCBI repository, accession number PRJNA922864. The original contributions of nutritional measurements presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.The animal study was reviewed and approved by Animal Ethics Committee of the National Engineering Research Center of JUNCAO Technology. Written informed consent was obtained from the owners for the participation of their animals in this study.YQ: investigation, resources, formal analysis, writing: original draft preparation. HZ: investigation, visualization, and supervision. XH and FuZ: data curation. FeZ: validation. BL and QL: conceptualization, methodology, funding acquisition, supervision, and writing: review and editing. All authors contributed to the article and approved the submitted version.This work was financially supported by grants from Fujian Agriculture and Forestry University International Cooperation and Exchange Project (No. KXG15001A), Science and Technology Innovation Fund Project of Fujian Agriculture and Forestry University (KFA18055A and KFA18056A), Fungus and Grass Science and Industry Development Project (XKJC-712021030), Central Leading Local Science and Technology Development Fund of Fujian Province (2022L3085).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Alexander disease (AxD) is classified into AxD type I (infantile) and AxD type II (juvenile and adult form). We aimed to determine the potential genetic cause(s) contributing to the AxD type II manifestations in a 9-year-old male who presented area postrema-like syndrome and his vomiting and weight loss improved after taking prednisolone.de novo heterozygous mutation, NM_001242376.1:c.262 C > T;R88C in exon 1 of the GFAP  was verified. Because of persistent vomiting and weight loss of 6.0 kg, prednisolone was prescribed which brought about ceasing vomiting and led to weight gaining of 3.0 kg over the next 3 months after treatment. Occasional attempts to discontinue prednisolone had been resulting in the reappearance of vomiting.A normal cognitive 9-year-old boy with persistent nausea, vomiting, and a significant weight loss at the age of 6 years was noticed. He also experienced an episode of status epilepticus with generalized atonic seizures. He showed non-febrile infrequent multifocal motor seizures at the age of 40 days which were treated with phenobarbital. He exhibited normal physical growth and neurologic developmental milestones by the age of six. Occasionally vomiting unrelated to feeding was reported. Upon examination at 9 years, a weak gag reflex, prominent drooling, exaggerated knee-deep tendon reflexes (3+), and nasal tone speech was detected. All gastroenterological, biochemical, and metabolic assessments were normal. Brain magnetic resonance imaging (MRI) revealed bifrontal confluent deep and periventricular white matter signal changes, fine symmetric frontal white matter and bilateral caudate nucleus involvements with garland changes, and a hyperintense tumefactive-like lesion in the brain stem around the floor of the fourth ventricle and area postrema with contrast uptake in post-contrast T1-W images. Latter MRI at the age of 8 years showed enlarged area postrema lesion and bilateral middle cerebellar peduncles and dentate nuclei involvements. Due to clinical and genetic heterogeneities, whole-exome sequencing was performed and the candidate variant was confirmed by Sanger sequencing. A This study broadens the spectrum of symptomatic treatment in leukodystrophies and also shows that R88C mutation may lead to a broad range of phenotypes in AxD type II patients. Alexander disease  is a rare, progressive autosomal dominant neurological disorder. According to a classification system proposed by Prust et al. AxD is categorized into two major groups: AxD type I (infantile subgroup) and AxD type II (juvenile and adult type) . This syThe area postrema syndrome consists of uncontrollable vomiting, brain stem lesions, and weight loss symptoms and has been reported in association with inherited white matter disorders such as AxD . MitochoDARS mutation) has been reported [Steroid therapy may be important and occasionally life-saving in adrenal insufficiency with X-adrenoleukodystrophy (X-ALD). In addition, symptomatic treatment of spasticity in HBSL , phenobarbital was prescribed and led him being seizure-free. The drug was discontinued at 16 months of age and the patient had normal physical growth and neurologic developmental milestones by the age of six. He had been showing occasional vomiting, i.e., once or twice a month, unrelated to feeding without any remarkable etiology. To control this condition, proton pump inhibitors were prescribed and it gave rise to a relative improvement.He was born at 38 weeks of gestational age through an uneventful normal cesarean section in a nonconsanguineous family. His birth weight and head circumference (HC) were recorded 3,050 g (z score = 0) and 37.0 cm (z score = 2), respectively. Over the first 2 weeks of his life, he was admitted due to prolonged physiologic jaundice with indirect bilirubin of 14 mg/dL which was resolved with phototherapy. While HC of his father and uncle was above the 2 standard deviations (SD) of their age, they had no clinical symptoms.At the age of 6 years, the patient showed an episode of status epilepticus with generalized atonic seizures followed by severe occasional projectile vomiting and recurrent daily nausea in the early morning and sometimes at midnight. His seizures were controlled by taking sodium valproate and levetiracetam. He also showed significant weight loss of 6.0 kg  over the following 2 months. At the first visit at this age, the patient had normal developmental milestones including speech, motor, and cognition. Upon examination, his weight and HC were 13.0 kg (z score = − 1) and 52.5 cm (z score = 2).Ophthalmic examinations revealed a normal gaze in all directions and normal pupils’ reaction to light. Palatal myoclonus was not detected, however, nasal tone speech was obvious. He had a weak gag reflex and prominent drooling. Examination of other cranial nerves was normal. Knee deep tendon reflexes (DTRs) were exaggerated (3+), but others were normal (2+). Plantar reflexes were bilaterally downward. His gross motor function was valued as 1 out of 5 (1/5) based on the Gross Motor Function Classification System (GMFCS) scale.All basic biochemical and metabolic tests such as thyroid and liver function tests, serum ammonia and lactate, urine organic acids profile, metabolic screen test (MS/MS), acylcarnitine profile, and serum amino acids chromatography (HPLC) were normal. The wrist X-Ray was consistent with the patient’s real age.The first MRI at the age of 6 years revealed faint bifrontal confluent deep and periventricular white matter signal changes, bilateral caudate nucleus involvement, significantly high in T2-W and low in T1-W images with garland and cystic changes around the tip of the frontal horns of the lateral ventricles, especially the left side  and 19.0 kg (z score= − 2), respectively. The repeated brain MRI at age of 8 years showed enlargement of the lesion in the area postrema  which was previously indicated to be pathogenic in infantile-onset AxD [de novo, i.e., neither of the parents carry the mutation.Genomic DNA was extracted from the patient’s blood sample and subjected to whole-exome sequencing (WES) that was performed using the Illumina Hiseq4000 platform  to obtain an average coverage depth of ~ 100×. Data analysis, base calling, annotation of variants, and filtering were undertaken according to previous studies [nset AxD , 12. Sande novo missense mutation,  in the GFAP.As identified by Van der Knaap et al. five typical MRI findings are often associated with type I AxD including (i) extensive cerebral white matter changes with frontal predominance, (ii) a periventricular rim with high signal on T1-W and low signal on T2-W images, (iii) abnormalities of basal ganglia and thalami, (iv) brain stem abnormalities, and (v) contrast enhancement of particular gray and white matter structures . At leasGFAP mutations that are present in about 95% of AxD patients. Most AxD cases are genetically imputed to de novo mutations, although familial cases have also been expected [GFAP mutations have been identified in association with AxD mainly including missense and short in-frame indels [GFAP mutations [AxD is caused only by expected . GFAP isexpected , 14, 15.e indels . R88C anutations , 17. TheMacrocephaly is noticed in most patients with infantile AxD and some cases of late-onset disease . The patDifferent pathomechanisms may contribute to AxD pathology, e.g., immune system activation, cellular proteasome and autophagic response dysfunctions, and impaired excitatory neurotransmitters transport . The parThere is still a lack of knowledge about the symptomatic treatment of leukodystrophies. Here, we introduced a case with novel manifestations who responded to symptomatic treatment using steroids.


Olea europaea extracts and evaluated their anticancer potential. The biosynthesized AgNPs were characterized using various methods, showing stable AgNPs with a desirable morphology and high yield, improving the properties of AgNPs for various medicinal applications. The biosynthesized AgNPs were predominantly spherical, with small sizes ranging from 13 to 21 nm and highly stable at −23 and −24 mV. The findings of this study suggest that green-synthesized AgNPs using Olea europaea and sunlight possess significant anticancer activity against cancer cells in vitro. Further investigation of green synthesis would help to form high-quality AgNPs that have promising potential in treating disease and fighting undesirable pathogens.Green synthesis has attracted significant attention as an eco-friendly, low-cost, energy-efficient, and non-toxic method for preparing silver nanoparticles (AgNPs) for cancer therapy. This study optimized the green synthesis of AgNPs using  Nanotechnology is a scientific field that involves the creation and application of nanosized particles. Nanoparticles are well-known as particles that range between 1 nm and 100 nm in diameter. The physical, chemical, and biological properties of these particles can be easily modified and used in various applications . ConsequNanoparticles can be classified into several types based on their morphology and physical and chemical properties. Metal nanoparticles such as gold, silver, zinc, and iron can be made of pure metals or compounds. Among the metal nanoparticle types, silver nanoparticles (AgNPs) are the most important. AgNPs have numerous applications in different fields because of their unique properties –7.Top-down and bottom-up methods are the two major approaches for synthesizing nanoparticles . The top+ into Ag0. Furthermore, they serve as capping agents for the coating of nanoparticles, providing greater stability in the size and shape of nanoparticles [Green synthesis is an easy way to obtain nanoparticles with more advantages than disadvantages. Green synthesis provides a fast, economical, nontoxic, eco-friendly, and biocompatible alternative to physical and chemical techniques . The synarticles .Reaction conditions, such as extract concentration, temperature, pH, and light intensity, can influence the production, characterization, and application of AgNPs . OptimizOlea europaea extracts for improved biological applications. The fundamental aim of the study was to provide an alternative to physical and chemical techniques for producing high-quality AgNPs that would improve their biological efficacy without introducing hazardous chemicals. The aim included examining the antitumor activities of the biosynthesized AgNPs against breast cancer cells, achieving remarkable results.The present study optimized the green synthesis of AgNPs using O. europaea extracts along with phytochemical screening, optimization, characterization, and anticancer activity evaluation is illustrated in the schematic diagram . The morphology, size, and shape of biosynthesized AgNPs are considered essential characteristics of nanoparticle systems because they determine their biological activity and toxicity [The biosynthesized AgNPs were characterized using ultraviolet-visible spectroscopy (UV-Vis), Fourier-transform infrared (FTIR) spectroscopy, dynamic light scattering (DLS), zeta potential analysis, and field-emission scanning electron microscopy (FE-SEM). For illustration, the green synthesis of AgNPs was monitored using a Cary® 50 ultraviolet-visible spectrophotometer in the 300–600 nm wavelength range. The association of biomolecules involved in the formation and stabilization of AgNPs were detected using an FTIR spectrometer (Fisher Nicolet iS10) in the 600–4000 cmtoxicity . Thus, t2 incubator at 37°C and passaged three times per week.The human hormone-dependent breast cancer cell lines, MCF7 and T47D, were obtained from the King Fahd Medical Research Centre. The cells were maintained in a high-glucose Dulbecco's Modified Eagle Medium (DMEM), supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin . Cancer cells were grown in a humidified 5% COO. europaea leaf extract (OLE) and AgNPs dissolved in leaf extract (AgNPs-OLE) samples were evaluated using the MTT assay. An MTT assay was performed according to the method described in a previous study [4 cells per well in 96 well plates supplied with DMEM. The plates were incubated for 24 h at 37°C and maintained in a 5% CO2 atmosphere to allow the cells to adhere overnight. Thereafter, the cells were treated with different concentrations  of treatments in triplicate and incubated for 24 h, and the control cell cultures were left untreated. After incubation, the old media was discarded, and 100 μL of MTT solution was added to each well. The 96 well plates were then incubated for approximately 3–4 h until formazan crystals formed. The medium was then replaced with a 100 μL of DMSO solution and the OD was measured using an ELISA reader at 570 nm. The cytotoxic effects of the three treatments on breast cancer cells were expressed as the % cell viability using the following formula:Blank refers to the background, which means the medium, MTT solution, and DMSO.Control cells refer to untreated cells.The cytotoxicity of green-synthesized AgNPs dissolved in 0.3 dimethyl sulfoxide DMSO (AgNPs), us study . Cells wP < 0.05.Statistical analyses were performed using SPSS software. All data were analysed using one-way analysis of variance (ANOVA) followed by Tukey's post hoc test for multiple comparisons, and significance was considered O. europaea extracts, as listed in + to Ag0 and the stabilization of biosynthesized AgNPs.Phytochemical screening analysis confirmed the presence of flavonoids, phenols, triterpenes, and saponins in the 3 solution. Thus, reaction mixtures with the ratios of 1 : 9, 2 : 9, and 3 : 9 plant extract to 1 mM AgNO3 silver nitrate were prepared, following the process described in an earlier study [To examine the effect of the extract concentration, three different volumes of 1, 2, and 3 mL of each extract were added separately to 9 mL of 1 mM AgNOer study . Increaser study . BiomoleThe biosynthesized AgNPs were prepared at different reaction temperatures , following the method of a previous study . The resThe effect of pH on the synthesis process was investigated at three different pH values: acidic (pH = 4), neutral (pH = 7), and basic (pH = 9). The pH of the green synthesis mixture was adjusted to the desired value using 0.1 N sodium hydroxide and 0.5 N acetic acid. Light can considerably influence the green synthesis of AgNPs . A spect3, pH value of 9, temperature of 80°C, and room light produced a lower amount of AgNPs compared with 1 : 9 plant extract to AgNO3, pH value of 7, and sunlight, as shown in 3, a pH value of 7, and sunlight, as shown in After studying these parameters, two sets of working conditions were selected as the optimum reaction conditions to produce high-quality AgNPs. By examining the two sets, the set of 3 : 9 plant extract to AgNOO. europaea leaf extracts and biosynthesized AgNPs. The results showed a broad and robust peak at 3340.2 cm−1, representing the hydroxyl (O-H) functional group and indicating the presence of a phenolic group. Additionally, the absorption peaks that emerged at 2962.2 and 1639.2 cm−1 correspond to the functional groups (C-H) and (C = C), respectively. In addition, the spectrum observed at 1064.5 cm−1 points to (C-O). O. europaea fruit extract and biosynthesized AgNPs. A broad peak, responsible for (O-H) stretching was seen at 3361.4 cm−1. Characteristic peaks were also observed at 2954.5 (C-H), 1629.6 (C = C), and 1056.8 (C-O) cm−1. The FTIR spectrum results confirmed that the bioactive compounds present in the plant extracts were adsorbed on the surface of the biosynthesis of AgNPs, which is in agreement with that reported in an earlier study [O. europaea parts, phenolics, and flavonoids played an essential role in reducing, capping, and stabilizing the green-synthesized AgNPs, thus enhancing their properties [An FTIR analysis helped identify the various biomolecules of the plant extracts responsible for capping and efficiently stabilizing the AgNPs. er study . The biooperties , 52.O. europaea leaf extract was found to be 182 nm with a single peak and a polydispersity index (PDI) of 0.2. In addition, the zeta potential was −24 mV with a sharp peak. However, the average hydrodynamic size, PDI, and zeta potential for synthesized AgNPs using O. europaea fruit extract were 66 nm, 0.2, and −23 mV, respectively. These numerical values for PDI are generally acceptable because the smaller the PDI, the more homogeneous nanoparticles are produced [From the DLS analysis , the aveproduced . Zeta poproduced –55.FE-SEM images helped visualize the morphology, shape, and size of the biosynthesized AgNPs. O. europaea leaf rather than fruit because of their better stability, smaller size, and good shape.After characterization of biosynthesized AgNPs, a better anticancer application would be obtained for AgNPs biosynthesized using in vitro against T47D and MCF7 breast cancer cell lines, and their IC50 values were determined from a graph of cell viability measured over a range of concentrations between 25 and 200 μg/mL. The results showed that AgNPs, OLE, and AgNPs-OLE effectively inhibited the proliferation of T47D and MCF7 cancer cells in a dose-dependent manner after 24 h of treatment , (C-H), (C = C), and (C-O) and confirmed that the bio-compounds, phenolics, and flavonoids present in the plant extracts were adsorbed on the surface of the AgNPs, thus enhancing their properties and future applications. The different biosynthesized AgNPs were spherical and ranged in size between 13–21 nm for O. europaea leaf and between 14.9–23 nm for O. europaea fruit. Furthermore, the cytotoxicity results of green-synthesized AgNPs using O. europaea leaf extract, OLE, and AgNPs-OLE suggest that they possess significant anticancer activity against human breast cancer (T47D and MCF7) cell lines. These results prove that green synthesis of AgNPs via O. europaea extracts is an excellent way to create nanoparticles with well-defined sizes and morphologies, which could have various novel therapeutic applications.Green synthesis of AgNPs using This study focused on the green synthesis of AgNPs via medicinal plants as a fast, simple, economic, nontoxic, eco-friendly, and biocompatible technique. In addition, future optimization of the green synthesis conditions will help produce particles with well-defined sizes and morphologies, thereby improving the properties of the nanoparticles. This would enhance the widespread therapeutic application of AgNPs and would bring forward the investigation into toxicity and clinical research, offering good opportunities to fight several diseases and undesirable pathogens using nanotechnology with natural compounds, leading to new insights and new types of medicine.


Despite some uncertainty surrounding the estimated numbers, these findings argue for systematically including biological variation rather than eliminating it in animal studies and call for future research on effective improvement strategies.The credibility of scientific research has been seriously questioned by the widely claimed “reproducibility crisis”. In light of this crisis, there is a growing awareness that the rigorous standardisation of experimental conditions may contribute to poor reproducibility of animal studies. Instead, systematic heterogenisation has been proposed as a tool to enhance reproducibility, but a real-life test across multiple independent laboratories is still pending. The aim of this study was therefore to test whether heterogenisation of experimental conditions by using multiple experimenters improves the reproducibility of research findings compared to standardised conditions with only one experimenter. To this end, we replicated the same animal experiment in 3 independent laboratories, each employing both a heterogenised and a standardised design. Whereas in the standardised design, all animals were tested by a single experimenter; in the heterogenised design, 3 different experimenters were involved in testing the animals. In contrast to our expectation, the inclusion of multiple experimenters in the heterogenised design did not improve the reproducibility of the results across the 3 laboratories. Interestingly, however, a variance component analysis indicated that the variation introduced by the different experimenters was not as high as the variation introduced by the laboratories, probably explaining why this heterogenisation strategy did not bring the anticipated success. Even more interestingly, for the majority of outcome measures, the remaining residual variation was identified as an important source of variance accounting for 41% (CI An experimenter heterogenisation was not sufficient to prevent idiosyncratic results in a multi-laboratory setting. Astonishingly, neither the experimenter nor the laboratory accounted for the main portion of the observed variation, but a high amount of residual variation in fact remained unexplained despite strict standardisation regimes. One core principle of science is the reproducibility of results, i.e., obtaining consistent results when replicating a study by collecting new data. However, over the past decade, the credibility of scientific results has been challenged by the fact that many replication studies failed to reproduce published results –4. BasedFailures to reproduce results of previous studies have been attributed to deficiencies in reporting standards, as well as to flaws in experimental design and statistical analysis –10. To iPhenotypic plasticity leads to variation in results, even if all animals are genetically identical ,18. PlasThe common approach to dealing with such factors is the rigorous standardisation of the experimental conditions. Thus, in most studies, all animals have the same age, are housed under the same conditions, and are tested by the same experimenter. This way, the variation within a study is expected to be minimised, and thus, the power to detect potential treatment effects is enhanced. However, this concept relies on the assumption of a fixed treatment effect, which can be detected by eliminating all sources of variation within a study. It ignores the fact that biological variation is an inherent characteristic of animal research and treatment effects may vary depending on the exact conditions to which a study is standardised ,28. AlthThis fallacy of enhancing reproducibility through standardisation becomes most apparent with respect to the experimenter effect: It is not only impossible to standardise experimenters across laboratories, but fundamentally misleading as the experimenter identity usually is of no biological interest for the study question. Instead of minimising variation by rigorous standardisation, embracing biological variability might be a better strategy to address replication failure. With regard to the experimenter, this would mean that instead of trying to eliminate this uncontrollable influencing factor in science, it could be used in a controlled way to systematically introduce variation in a study .A growing body of evidence suggests that introducing heterogeneity in a controlled way to the study design (referred to as “systematic heterogenisation”) increases the inference space of the results, leading to better reproducibility under varying background conditions ,30–35. FAgainst this background, the overall aim of the present multilaboratory study was to empirically test the potential of the experimenter as a heterogenisation factor. We expected improved reproducibility of research findings in comparison to a conventionally standardised design. In line with this assumption, we also aimed at estimating the amount of variance explained by multiple experimenters, assuming that the factor “experimenter” represents the major source of variation. To this end, the same animal experiment was replicated independently in 3 different laboratories, using both a heterogenised design with 3 experimenters being involved in testing the study sample and a standardised design with one experimenter testing the study sample. To assess reproducibility, a typical animal experiment in the field of biomedical research was mimicked. More precisely, many studies examine the role of specific genes in the modulation of the phenotype and therefore rely on the phenotypic characterisation of animals of different genotypes. To reflect such an experiment with a typical “treatment under investigation”, 2 inbred mouse strains  were tested in a range of physiological and behavioural outcome variables commonly used in such phenotyping studies (cf. ).In this study, 96 naïve female mice of 2 inbred mouse strains  were used in each of the 3 laboratories. To ensure consistent housing conditions across the 3 laboratories, female mice were chosen because, in contrast to male mice, they can be easily housed in stable groups without taking the risk of having to separate some mice over the course of the experimental phase . AllAll procedures complied with the regulations covering animal experimentation within Germany , Switzerland  and the EU (European Communities Council DIRECTIVE 2010/63/EU) and were approved by the local  and federal authorities .The present project was designed as a multilaboratory study, involving 3 independent laboratories in Germany and Switzerland . The overall aim was to compare a conventionally standardised design and a systematically heterogenised design in a real-life situation (cf. ). Therefn = 12 mice per strain, see “Data analysis” for details on sample size estimation) were tested by one experimenter, while in the heterogenised design, 3 different experimenters were involved in conducting the experiment  reproducibility of the strain effect across laboratories; (2) exploration of impact of experimenter allocation; and (3) components of variance analysis.In the first analysis, we compared the reproducibility of the results between both designs in terms of the consistency across the 3 laboratories and the performance of the experimental designs to predict the overall effect size. This analysis was completed on the basis of the prior determined experimenter allocation. In the second analysis, we evaluated if the results of the first analysis may have been due to the specific experimenters allocated to each design rather than due to the characteristics of the designs itself. Here, the first analysis was repeated on the basis of 10 alternative experimenter allocations .In a third analysis, we used the data generated to disentangle the different components of variance and estimate their contribution to the total variance in this study .In each of the 3 participating laboratories, 4 experimenters conducted the same animal experiment (C57BL/6J versus DBA/2N mice) following the same standardised test protocols . In the laboratory in Bern, all experimenters were females, whereas in Münster and Osnabrück, male and female experimenters were involved in the study. Experimenters with different levels of experience in both, handling mice and conducting the test procedures, were involved in all laboratories , except for the laboratory in Osnabrück. Here, due to technical reasons, the sample size of 2 experimenters (Exp A and B) was reduced to n = 11 for the “C57BL/6J” group and n = 9 and n = 8, respectively, for the “DBA/2N” group. Due to the consecutive testing of the 4 experimenters, experiments in the heterogenised design comprised not only animals tested by different experimenters, but also tested at different time points, while in the standardised design, all animals from one laboratory were delivered and tested at one specific point in time by one experimenter  to guarantee that all experimenters were blind to the experimental design. As a consequence, 4 “full” independent experiments were performed by 4 experimenters consecutively in each laboratory , all mice were subjected to the same testing procedures. Thereby, behavioural paradigms were chosen in accordance with established protocols for the phenotypic characterisation of mice in experimental animal research .Experimental procedures started on postnatal day (PND) 70 ± 2 and lasted for 8 days. Over the course of this period, the following tests were conducted during the active phase in the same order for all animals: Elevated Plus Maze (EPM) on PND 70 ± 2, Dark Light (DL) test on PND 71 ± 2, Open Field (OF) test on PND 72 ± 2, Novel Cage (NC) test on PND 76 ± 2, and Nest (NT) test starting on PND 77 ± 2 see . AdditioFour days before the start of the experimental phase, habituation of the animals to the designated experimenter took place. Each experimenter handled the mice at least 3 times before the start of the first test procedure (EPM). Animals tested by one experimenter were exclusively handled by this person during the whole experimental phase.The order of mice tested on the same day was pseudo-randomised, following 2 rules. First, mice of neighbouring cages (C57BL/6J and DBA/2) were tested consecutively. Second, in the EPM, DL, OF, and NC tests, a break of at least 1 h between the testing of 2 cage mates was ensured to minimise influences caused by any disturbances in the cage.While the experimenters were blind with respect to the allocation of the mice to the experimental design , blinding to the mouse strain was not possible due to different fur colours of the 2 strains . However, the main outcome  was unlikely to be influenced by the lack of blinding at this stage of the study. Importantly, all experimenters were unaware of the results from other experimenters in their own laboratory and in the other participating laboratories.In this study, 20 outcome measures were recorded, which derived from 7 experimental test procedures. To minimise dependencies between these outcome measures, all 20 outcome measures were checked for correlations among each other. We selected 10 outcome measures see , which hn = 12 mice per strain and laboratory, we could ensure to detect biologically relevant variations of the strain effect across the 3 laboratories with a power of 80%.To estimate the sample size in our study, an a priori power analysis was conducted using previously published data by Bodden and colleagues . AccordiThe main analysis to evaluate the reproducibility of the treatment effect across the 3 laboratories and compare it between both experimental designs was adapted from von Kortzfleisch and colleagues  and comp(I.) Consistency of the strain effect across laboratories. The consistency of the strain effect across laboratories is statistically reflected in the variation captured by the interaction between the factors “strain” and “laboratory” . To assess this “strain-by-laboratory” interaction term as a measurement for reproducibility, a linear mixed model (LMM) was applied to both designs (standardised and heterogenised). Details on this analysis and the model equation are presented in (II.) Estimation of how often and how accurately the overall effect is predicted in the laboratories. How good each experimental design predicted the overall effect size was assessed by the following 2 measurements that were adapted from the analysis by Voelkl and colleagues  to 27%, CI95 ), indicating a rather small to moderate influence on outcome measures . Instead, they were attributed to interindividual differences of unknown sources . Whether this observation only holds true for the here examined physiological and behavioural differences between inbred mouse strains or can be applied to other settings in animal research  needs to be further examined. Yet, our findings are in line with Kafkafi and colleagues [Concerning sources of variation, the results of our study point to a further, so far widely overlooked aspect. Although the data were collected across different laboratories and experimenters, in 6 out of 10 outcome measures, our analysis suggests that a great proportion of variation Click here for additional data file.S2 Text(DOCX)Click here for additional data file.S3 Text(DOCX)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 TableListed are the randomly chosen combination for the main analysis (Combination 0) and 10 alternative combinations. In each lab, the allocation process consisted of the following steps. First, all mice tested by one randomly chosen experimenter (Exp A—Exp D) were assigned to be part of the standardised design. Second, the remaining 3 experimenters in each lab were assigned to be part of the heterogenised design and one block of mice (B1 –B3) from each experimenter was pseudo-randomly selected for the heterogenised experiment in each lab. This was done in a way that in each heterogenised experiment, all 3 blocks were represented. Please note, due to the loss of animals, the datasets generated by Exp A and B in Lab C were only used for the heterogenised design in a restricted way. In detail, block B3 from Exp A and B2 from Exp B were excluded from the selection process.(XLSX)Click here for additional data file.S4 Tablen = arcsine (sqrt (y/100)).Transformations: log = log10 (y-1), sqrt = square root, asi(XLSX)Click here for additional data file.S5 Table2- and p-values for the main effect of strain, laboratory, and the strain-by-laboratory interaction for all 10 selected outcome measures. Bold p-values indicate significant effects. Transformations (Transf): log = log10 (y-1), sqrt = square root. LMM, linear mixed model.Presented are χ(XLSX)Click here for additional data file.S6 Tablep-values for the pairwise comparison of the strain-by-laboratory interaction, the Pc, and the Pa between both designs . Bold p-values indicate significant differences between both designs. Shown is the output of the Wilcoxon signed-rank test for the main analysis (Comb 0) and for 10 alternative allocations of the experimenters to the designs (Comb 1 –Comb 10). Pa, proportion of accurate results; Pc, coverage probability.Presented are V- and (XLSX)Click here for additional data file.S7 Table95) of the point estimates are presented in square brackets. Please note: confidence intervals were limited to the maximum possible range . LMM, linear mixed model.Presented are point estimates of the component of variance analysis on the full data set for all 10 selected outcome measures. For the random factors in the LMM also confidence intervals (CI(XLSX)Click here for additional data file.S8 Tablep-values for the main effect of strain, experimenter, and the strain-by-experimenter interaction for all 10 selected outcome measures. Bold p-values indicate significant effects. Transformations (Transf): log = log10 (y-1), sqrt = square root. LMM, linear mixed model.Presented are F- and (XLSX)Click here for additional data file.S1 Figp-values of the “strain-by-laboratory” interaction term across all 10 outcome measures for 10 alternative allocations of the experimenters to the designs (Combination 1–10). Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Black dots represent single p-values for each outcome measure in both designs. Statistics: Wilcoxon signed-rank test , *p ≤ 0.05. The raw and processed data underlying this figure are available in the Figshare repositories https://figshare.com/s/f327175aa8b541ef01bd and https://figshare.com/s/2245cee43a544ee1ffff.Shown are (JPG)Click here for additional data file.S2 Fign = 10). The raw and processed data underlying this figure are available in the Figshare repositories https://figshare.com/s/f327175aa8b541ef01bd and https://figshare.com/s/2245cee43a544ee1ffff. Pc, coverage probability.Shown are Pc ratios of 10 outcome measures for 10 alternative allocations of the experimenters to the designs (Combination 1–10). Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Black dots represent single values for each outcome measure in both designs. Statistics: Wilcoxon signed-rank test Click here for additional data file.S3 Fign = 10). The raw and processed data underlying this figure are available in the Figshare repositories https://figshare.com/s/f327175aa8b541ef01bd and https://figshare.com/s/2245cee43a544ee1ffff. Pa, proportion of accurate results.Shown are Pa ratios of 10 outcome measures for 10 alternative allocations of the experimenters to the designs (Combination 1–10). Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Black dots represent single values for each outcome measure in both designs. Statistics: Wilcoxon signed-rank test Click here for additional data file.S4 Fighttps://figshare.com/s/f327175aa8b541ef01bd.The raw data underlying this figure are available in the Figshare repository (JPG)Click here for additional data file.S5 Fign = 12) in each laboratory. Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Statistics: LMMs followed by Tukey’s test for post hoc pairwise comparisons of the means. The analyses were conducted separately for the data of each laboratory, * p < 0.05. Abbreviations are indicating a significant strain effect (Strain*), experimenter effect (Exp*), or strain-by-experimenter interaction (Strain × Exp*). The raw data underlying this figure are available in the Figshare repository https://figshare.com/s/f327175aa8b541ef01bd. EPM, Elevated Plus Maze; LMM, linear mixed model.Results are displayed separately for each experimenter (Exp A–Exp D) conducting a full experiment ((JPG)Click here for additional data file.S6 Fign = 12) in each laboratory. Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Statistics: LMMs followed by Tukey’s test for post hoc pairwise comparisons of the means. The analyses were conducted separately for the data of each laboratory, * p < 0.05. Abbreviations are indicating a significant strain effect (Strain*), experimenter effect (Exp*), or strain-by-experimenter interaction (Strain × Exp*). The raw data underlying this figure are available in the Figshare repository https://figshare.com/s/f327175aa8b541ef01bd. EPM, Elevated Plus Maze; LMM, linear mixed model.Results are displayed separately for each experimenter (Exp A–Exp D) conducting a full experiment ((JPG)Click here for additional data file.S7 Fign = 12) in each laboratory. Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Statistics: LMMs followed by Tukey’s test for post hoc pairwise comparisons of the means. The analyses were conducted separately for the data of each laboratory, * p < 0.05. Abbreviations are indicating a significant strain effect (Strain*), experimenter effect (Exp*), or strain-by-experimenter interaction (Strain × Exp*). The raw data underlying this figure are available in the Figshare repository https://figshare.com/s/f327175aa8b541ef01bd. EPM, Elevated Plus Maze; LMM, linear mixed model.Results are displayed separately for each experimenter (Exp A–Exp D) conducting a full experiment ((JPG)Click here for additional data file.S8 Fign = 12) in each laboratory. Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Statistics: LMMs followed by Tukey’s test for post hoc pairwise comparisons of the means. The analyses were conducted separately for the data of each laboratory, * p < 0.05. Abbreviations are indicating a significant strain effect (Strain*), experimenter effect (Exp*), or strain-by-experimenter interaction (Strain × Exp*). The raw data underlying this figure are available in the Figshare repository https://figshare.com/s/f327175aa8b541ef01bd. DL, Dark Light; LMM, linear mixed model.Results are displayed separately for each experimenter (Exp A–Exp D) conducting a full experiment ((JPG)Click here for additional data file.S9 Fign = 12) in each laboratory. Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Statistics: LMMs followed by Tukey’s test for post hoc pairwise comparisons of the means. The analyses were conducted separately for the data of each laboratory, * p < 0.05. Abbreviations are indicating a significant strain effect (Strain*), experimenter effect (Exp*), or strain-by-experimenter interaction (Strain × Exp*). The raw data underlying this figure are available in the Figshare repository https://figshare.com/s/f327175aa8b541ef01bd. LMM, linear mixed model; OF, Open Field.Results are displayed separately for each experimenter (Exp A–Exp D) conducting a full experiment ((JPG)Click here for additional data file.S10 Fign = 12) in each laboratory. Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Statistics: LMMs followed by Tukey’s test for post hoc pairwise comparisons of the means. The analyses were conducted separately for the data of each laboratory, * p < 0.05. Abbreviations are indicating a significant strain effect (Strain*), experimenter effect (Exp*), or strain-by-experimenter interaction (Strain × Exp*). The raw data underlying this figure are available in the Figshare repository https://figshare.com/s/f327175aa8b541ef01bd. FCMs, faecal corticosterone metabolites; LMM, linear mixed model.Results are displayed separately for each experimenter (Exp A–Exp D) conducting a full experiment ((JPG)Click here for additional data file.S11 Fign = 12) in each laboratory. Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Statistics: LMMs followed by Tukey’s test for post hoc pairwise comparisons of the means. The analyses were conducted separately for the data of each laboratory, * p < 0.05. Abbreviations are indicating a significant strain effect (Strain*), experimenter effect (Exp*), or strain-by-experimenter interaction (Strain × Exp*). The raw data underlying this figure are available in the Figshare repository https://figshare.com/s/f327175aa8b541ef01bd. LMM, linear mixed model; NC, Novel Cage.Results are displayed separately for each experimenter (Exp A–Exp D) conducting a full experiment ((JPG)Click here for additional data file.S12 Fign = 12) in each laboratory. Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Statistics: LMMs followed by Tukey’s test for post hoc pairwise comparisons of the means. The analyses were conducted separately for the data of each laboratory, * p < 0.05. Abbreviations are indicating a significant strain effect (Strain*), experimenter effect (Exp*), or strain-by-experimenter interaction (Strain × Exp*). The raw data underlying this figure are available in the Figshare repository https://figshare.com/s/f327175aa8b541ef01bd. LMM, linear mixed model.Results are displayed separately for each experimenter (Exp A–Exp D) conducting a full experiment ((JPG)Click here for additional data file.S13 Fign = 12) in each laboratory. Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Statistics: LMMs followed by Tukey’s test for post hoc pairwise comparisons of the means. The analyses were conducted separately for the data of each laboratory, * p < 0.05. Abbreviations are indicating a significant strain effect (Strain*), experimenter effect (Exp*), or strain-by-experimenter interaction (Strain × Exp*). The raw data underlying this figure are available in the Figshare repository https://figshare.com/s/f327175aa8b541ef01bd. LMM, linear mixed model; NT, Nest.Results are displayed separately for each experimenter (Exp A–Exp D) conducting a full experiment ((JPG)Click here for additional data file.S14 Fign = 12) in each laboratory. Data are presented as boxplots showing medians, 25% and 75% percentiles, and 5% and 95% percentiles. Statistics: LMMs followed by Tukey’s test for post hoc pairwise comparisons of the means. The analyses were conducted separately for the data of each laboratory, * p < 0.05. Abbreviations are indicating a significant strain effect (Strain*), experimenter effect (Exp*), or strain-by-experimenter interaction (Strain × Exp*). The raw data underlying this figure are available in the Figshare repository https://figshare.com/s/f327175aa8b541ef01bd. LMM, linear mixed model; NT, Nest.Results are displayed separately for each experimenter (Exp A–Exp D) conducting a full experiment ((JPG)Click here for additional data file.