Accurate diagnostic biomarker testing is crucial to treatment decisions in breast cancer. Biomarker testing is performed on core needle biopsies (CNB) and is often repeated in the surgical specimen (SS) after resection. As differences between CNB and SS testing may alter treatment decisions, we evaluated concordance between CNB and SS as well as associated changes in treatment and clinical outcomes.We performed a retrospective analysis of breast cancer patients at our institution between January 2010 and May 2020. Concordance between CNB and SS was assessed for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) by immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). Survival in patients, including recurrence, metastatic recurrence, and death, were assessed using chi‐squared likelihood ratio.p < 0.001) and HER2 FISH (50.0%) led to more management changes than HER2 IHC  and PR . Patients with ER major discordance had increased risk of death .In total, 961 patients met eligibility criteria. Concordance, minor discordance, total concordance (concordance plus minor discordance), and major discordance between CNB and SS were reported for ER , PR , and HER2 IHC , respectively. HER2 FISH concordance and major discordance were 58.5% and 1.2%, respectively. Of major discordance, ER (48.2%, Overall, retesting ER and HER2 was more clinically beneficial than retesting PR. To aid decision‐making and minimize healthcare costs, we propose patient‐centered guidelines on retesting biomarker profiles. Retesting estrogen receptor and HER2 status provides more clinical benefit than retesting progesterone receptor status. We propose guidelines for retesting receptor profiles to aid patient care management decisions, prioritize clinical benefits, and minimize healthcare costs. This study was conducted in accordance with the Rush University Medical Center Institutional Review Board (IRB) and the Declaration of Helsinki. Patients ≥18 who underwent primary surgical resection or had neoadjuvant chemotherapy with residual disease on surgical excision were included in the study. Patients were included if pathology with receptor expression testing  was available on both CNB and SS. All testing was performed at Rush University Medical Center. ER and PR were lab developed tests , which is a CAP accredited, internally validated test. Biomarker tests are automated. Time to fixation and time in formalin was routinely included after the updated 2013 ASCO‐CAP Guidelines. HER2 IHC was evaluated by HER‐2/neu (HercepTest) and FISH by PathVysion assay kit by Abbott Inc.Exclusion criteria included patients with CNB or SS obtained at outside institutions, pathologic complete response on SS, and patients with distant metastatic disease. Patients with distant metastatic disease were excluded from the analysis given biomarker differences between the primary tumor and metastatic disease sites has different management implications than in the neoadjuvant or adjuvant setting. Medical records were individually reviewed to ensure data accuracy.Concordance rates between CNB and SS were evaluated for ER, PR, and HER2 IHC and FISH. ER and PR status were defined per NCCN guidelines as “positive,” “low‐positive (ER),” or “negative” based on IHC. The major discrepancy was defined as a change in receptor status. The minor discrepancy was defined as >10% change in expression with no change in receptor status. Total concordance included both concordance and minor discordance. For HER2, major discordance was defined as a change in receptor status  based on IHC or FISH. The minor discrepancy was defined as a change in HER2 IHC (0–3) or FISH amplification without a change in receptor status.p‐values were assessed by Fisher’s exact test.The frequency of treatment changes in patients with discordant biomarker expression was assessed. Patients with major discordance were reviewed by an investigator to determine whether the treatment course was changed based on the SS receptor profile . A second independent reviewer was available to resolve discrepancies in the data. Statistical analysis was performed with chi‐squared likelihood ratio using SPSS (IBM Corporation) software. P values were performed by Pearson's chi‐squared test or Fisher's exact test. Recurrence, metastatic recurrence, and death from any cause were evaluated for correlation of concordance, minor, or major discordance. We evaluated the impact of retesting on nationwide healthcare expenditure. The number of concordance tests that could have been safely omitted was analyzed for projected cost savings in the United States in 2020.Finally, we performed a literature search from July 2020 to September 2020 to identify previously conducted studies of concordance between CNB and SS. Eligible studies were identified using a MEDLINE search using the keywords including “Breast Cancer,” “Estrogen Receptor (ER),” “Progesterone Receptor (PR),” “HER2 or HER2/neu,” “Concordance,” “Discordance,” “Core Needle Biopsy,” “Surgical Specimen,” “Excisional Biopsy,” and “Immunohistochemistry.” We excluded meta‐analyses, studies examining receptor status on non‐breast metastatic sites or non‐invasive breast cancer, and studies that did not report specific CNB and SS concordance rates for ER, PR, or HER2.3Of 5581 breast cancer patients who underwent treatment at Rush University Medical Center between January 2010 and May 2020, 961 patients met eligibility criteria, and 86 of these patients received neoadjuvant therapy. Baseline characteristics were assessed for the total cohort Table . Concordp < 0.001) and HER2 FISH (50.0%) led to more changes in management than HER2 IHC  and PR  (Table n = 86), discordance leading to treatment changes represented a small group of patients and did not show statistical significance , ER  Table . Retestice Table .n = 6, 22.2%, p = 0.004) compared to concordance  or minor discordance  (Table p = 0.38), respectively. Metastatic recurrence was noted in 22.6%, 31.6%, and 50.0% of patients (p = 0.19) with ER concordance, minor discordance, and major discordance, respectively  compared to specimens with concordance  and major discordance   Table . Recurrely Table . In HER2p = 0.30), metastatic disease at recurrence , and death from any cause  compared to patients with no treatment changes. In patients with HER2 IHC discordance‐driven treatment changes, there was a trend towards increased risk of recurrence  but not towards increased risk of metastatic disease  or death  compared to patients with no treatment changes. In summary, we did not find a statistically significant increase in the risk of recurrence, metastatic recurrence, or death due to treatment changes arising from ER or HER2 IHC discrepancies between CNB and SS in our cohort  demonstrated complete concordance between CNB and SS for ER, PR, and HER2 IHC. For 2020, the American Cancer Society estimated that 276,480 new cases of invasive breast cancer would be diagnosed in women in the United States.4(Table ).As breast cancer is the most common malignancy in women, retesting SS for breast cancer patients has important implications for individuals and the healthcare system in the United States.Table .There are various explanations for discordance between CNB and SS biomarker profiles in breast cancer, including tumor heterogeneity and pre‐analytic variation.Retesting HER2 on SS did not lead to a change in management if HER2 was positive on initial CNB; however, we must also consider cases in which HER2 was equivocal on initial CNB Table . Gupta e4.1Recurrence, metastatic disease at recurrence, and death from any cause were assessed for ER and HER2 IHC based on concordance, minor discordance, and major discordance. Patients with major discordance or those with treatment changes tended to have worse outcomes; however, this was only statistically significant for ER major discordance and death from any cause. These findings suggest that ER discordance, but not HER2 IHC discordance, correlates to an increased risk of mortality in patients. Instead, HER2 IHC demonstrated a statistically significant increase in mortality in patients with concordance (8.5%) and minor discordance (28.2%) compared to major discordance (4.0%). This may be due to the lower number of treatment changes associated with HER2 IHC/FISH compared to ER. HER2‐positive patients also tended to be treated with HER2 directed therapy, which may differentially influence survival. The poor survival or recurrence in patients with ER discordance may have several explanations. Low‐positive ER tumors may behave more similarly to triple negative disease, which tends to have worse outcomes compared to patients with strongly positive ER expression. In addition, tumors with high heterogeneity may be at risk of discordant results and respond less robustly to therapy compared to tumors with high ER expression. Clinicians should be aware that discordance may be a poor prognostic risk factor for patients with breast cancer.4.2In total, 27 reports evaluating biomarker receptor concordance were included in our literature review Table .2, 94.3Our institution adopted best practice guidelines for retesting receptor expression on SS Table . In pati4.4Similar to the study by VandenBussche et al., our institution's estimated cost of retesting ER, PR, and HER2 (IHC) projected an annual cost upwards of $43 million in the United States.4.5We performed a large, retrospective analysis of receptor concordance between primary surgical and neoadjuvant breast cancer specimens comparable to others reported in the literature. Our study focused on clinically relevant end points based on discordance, including treatment changes and recurrence, metastatic recurrence, and death from any cause. Moreover, our data was collected from an academic and tertiary referral hospital in Chicago, a city with a diverse patient population. It is thought that receptor expression rates can be influenced by population‐dependent variables . Previous studies have looked at discordance rates primarily in Asian, European, and Middle Eastern populations Table . The divOur study also has inherent limitations given its retrospective design. All data were extracted from medical records , and incomplete or missing werea was excluded. Our study spans a 10‐year period, and the recent advent of tumor profiling and genomic sequencing has enabled clinicians to make and alter therapy decisions based on predicted response to certain therapies, adding another layer of complexity to the treatment decision process. In addition, we did not have the resources to contact each patient in the data set to confirm recurrence and outcome status. There are potential confounding factors to the survival analysis, such as the time from initial diagnosis to recurrence, metastatic disease, or death. In addition, biological factors could also influence survival given Ki67 was not assessed and both ER‐positive, low positive, and negative cases were included in the concordant and discordant cohorts. Therefore, the interpretation of our survival data may not reflect true outcomes. Finally, death from any cause does not imply causation, as multiple factors play a role in mortality of breast cancer patients.5Although discordance was more common in PR and HER2 IHC than in ER or HER2 FISH biomarker profiles, major discordance leading to treatment changes was more common in ER and HER2 FISH. Our findings suggest that retesting ER and HER2 is more clinically beneficial than retesting PR. When discordance was present between the CNB and SS, clinical outcomes tended to be poor but did not reach statistical significance. We did find a statistically significant association between death from any cause and cases of ER major discordance. Our study suggests that retesting ER and HER2 can be clinically beneficial. Clinicians should limit retesting to cases in which discordance would change clinical management. Our proposed best practice guidelines promote a patient‐centered approach to breast cancer care that minimizes patient and healthcare costs.All authors have reviewed, discussed, and agreed to their individual contributions. Jessica Slostad: Conceptualization, data curation, formal analysis, investigation, methodology, project administration, supervision, validation, visualization, writing – original draft, and writing – review and editing. Nicole Yun: Data curation, methodology, formal analysis, investigation, visualization, writing – original draft , and writing – review and editing. Aimee Schad: Data curation, investigation, visualization, writing – original draft, and writing – review and editing. Surbhi Warrior: Data curation, investigation, visualization, writing – original draft, and writing – review and editing. Louis Fogg: Formal analysis, methodology, validation, and writing – review and editing. Ruta Rao: Conceptualization, formal analysis, supervision, validation, visualization, and writing – review and editing.No outside or third‐party funding was used. Internal funding through the Rush Research Mentoring Program was used for manuscript editing services.The authors do not have any disclosures or conflicts of interest related to this manuscript to report.This study was conducted in accordance with the Rush University Medical Center Institutional Review Board (IRB) and the Declaration of Helsinki.Table S1Table S2:Table S3:Table S4:Table S5:Click here for additional data file.


Activated astroglia is involved in the pathophysiology of neurodegenerative diseases and has also been described in animal models of spinal muscular atrophy (SMA). Given the urgent need of biomarkers for treatment monitoring of new RNA‐modifying and gene replacement therapies in SMA, we examined glial fibrillary acidic protein concentrations in cerebrospinal fluid (cGFAP) as a marker of astrogliosis in SMA.58 adult patients and 21 children with genetically confirmed 5q‐associated SMA from four German motor neuron disease specialist care centers and 30 age‐ and sex‐matched controls were prospectively included in this study. cGFAP was measured and correlated to motor performance and disease severity. Additionally, we compared cGFAP with neurofilament light chain concentrations in cerebrospinal fluid (cNfL).cGFAP concentrations did not differ from controls but showed higher levels in more severely affected patients after adjustment for patients' age. Normalized cNfL values were associated with disease severity. Within 14 months of nusinersen treatment, cGFAP concentrations did not change, while cNfL decreased significantly.cGFAP is not an outstanding biomarker in SMA, but might support the hypothesis that glial activation is involved in SMA pathology. Unlike previously suggested, cNfL may be a promising biomarker also in adult patients with SMA, which should be subject to further investigations. Survival of motor neuron 1 gene (SMN1).5q‐associated spinal muscular atrophy (SMA) is a lower motor neuron disease based on a lack of survival of motor neuron (SMN) protein caused by a loss‐of‐function mutation of the The aim of this study was to evaluate GFAP concentration in CSF (cGFAP) as a biomarker for disease severity and treatment monitoring in patients with SMA and to further investigate the non‐neuronal involvement in the pathophysiology of SMA. Furthermore, we aimed to compare cGFAP with neurofilament light chain (cNfL) as a marker of neurodegeneration and with chitotriosidase 1 (cCHIT1) as a marker of neuroinflammation in CSF. cCHIT1 has recently been shown to be elevated in treatment‐naïve patients with SMA.58 adult patients and 21 children with genetically confirmed 5q‐associated SMA from 4 German motor neuron disease specialist care centers  and 30 age‐ and sex‐matched controls were prospectively included in this study between 2017 and 2020. The local ethics committees of all participating sites approved the study and all patients signed written informed consent.SMN2 copies if available and ambulatory status.The demographic and clinical data of patients were collected including age, sex, disease onset, baseline weight and height, clinical subtype, number of Patients received nusinersen treatment according to the prescribing information for up to 14 months (Visit 7 = V7). CSF was obtained by lumbar puncture (LP), which was performed for intrathecal administration of nusinersen.g; RT). In total, 214 CSF samples were analyzed for GFAP concentration at three time points  using ELISA kits  at 1:3 dilution according to the instructions of the manufacturer. For quality control, a CSF pool was measured in triplicates per plate additionally to duplicates of the control samples included in the GFAP ELISA kits. The mean intra‐assay and inter‐assay coefficients of variation were <15% for both the kit controls and the CSF pool. One patient was excluded from the analysis since the CSF sample of that patient was insufficient for GFAP determination at baseline. cNfL levels were determined by the ELLA microfluidic system  and measurements were performed according to the manufactures instructions. In more detail, CSF samples were diluted 1:4 and analyzed in technical triplicates with an acceptance threshold of 10% coefficients of variation. In addition, chitotriosidase 1 concentrations in CSF (cCHIT1) were measured in the same cohort and at the same time as cGFAP .To monitor motor and functional outcome, established motor scores . We therefore applied rank‐based, non‐parametric tests for the baseline analysis. To estimate the comparability of study group and control group, we used Pearson's Chi‐squared test for equal distribution regarding sex and Mann–Whitney U test concerning conformity of age. To investigate the association between cGFAP values and disease severity, we correlated cGFAP baseline values with demographic features and clinical assessments using Spearman's rank correlation coefficient (ρ). Due to the significant association with age, we considered it a confounding factor and controlled for baseline age by partial correlation regarding both cGFAP and cNfL. A correlation coefficient of ρ < 0.3 was considered as a weak, ρ = 0.3–0.59 as a moderate, and ρ > 0.6 as a strong correlation  with post‐hoc Bonferroni adjustment for comparison of cGFAP or cNfL (dependent variables) between different patient subgroups considering age as covariate. To meet the assumptions of ANCOVA, we subjected the cGFAP data to a square root transformation and the cNfL data to an inverse and log transformation. For longitudinal analysis under nusinersen treatment, we performed Wilcoxon signed‐rank test to include all available data (N = 58) for the comparison between baseline (V1) and 14‐month follow‐up . Data sets with missing values were excluded pairwise for cross‐sectional and longitudinal analysis. Statistical significance threshold was set to <0.05.Statistical analysis and data visualization were performed using SPSS Statistics 27 , USA) and GraphPad Prism 5 , USA). Unless otherwise stated, cGFAP and cNfL data and the assessed scores are presented as median ± interquartile range (IQR). cGFAP and cNfL data were not normally distributed as tested by Shapiro–Wilk test (N = 7), type 2 (N = 33) or type 3 (N = 39) were included in the analysis. Median age was 31 years (IQR 17–43), 52% were female. The control group was age‐ and sex‐matched and comprised 23 adults and 7 children without neurodegenerative or neuroinflammatory disease . In the control group, median age was 30 years (IQR 17–44), 60% were female. The distribution of sex or age did not differ significantly between the groups. Details of study group characteristics and study profile are presented in Table 58 adult patients and 21 children with SMA type 1  = 0.024, p = 0.877; Fig. ρ = 0.405, p < 0.001, N = 79; Fig. ρ = 0.544, p = 0.002, N = 30; Fig. SMN2 copy number  = 3.673, p < 0.05, partial η2 = 0.090) after adjustment for patients' age, but did not differ between SMA type 1 versus 2 or type 1 versus 3 or compared to controls or regarding SMN2 copy number  = 0.333, p = 0.855). Moreover, patients who were able to walk had lower cGFAP concentrations than patients who were not  = 4.813, p < 0.05, partial η2 = 0.060).cGFAP concentrations of treatment‐naïve patients with SMA did not differ from the control group . cGFAP and cNfL did not correlate at baseline after adjustment for patients' age .Data for cNfL concentration at baseline was available for 74 patients, because the amount of CSF of five patients was not sufficient for NfL determination. One adolescent patient with SMA type 1 showed a cNfL level of 18272 pg/mL, which was outside of 1.5 fold IQR from the median within the subgroup of SMA type 1 (>5193.75 pg/mL) and has been therefore excluded from the analysis. Finally, the baseline data set represented 73 treatment‐naïve patients with SMA, of whom 20 were younger than 20 years. cNfL levels (for baseline data see Table N = 24) and 3 (N = 34), determination of serum creatinine concentration (sCrn) was done as part of the clinical routine. Patients lacking baseline cGFAP, cNfL, and sCrn were excluded listwise from this subanalysis. In this subset, there was a slight difference between SMA type 2 and 3 for cGFAP  = 4.991, p < 0.05, partial η2 = 0.083) and no difference regarding cNfL  = 36.837, p < 0.0001, partial η2 = 0.401) and higher sCrn‐normalized cNFL  = 27.311, p < 0.0001, partial η2 = 0.332) values were found in SMA type 2 compared to SMA type 3 . Similar to Olsson et al., cGFAP concentrations declined during nusinersen treatment. In fact, cGFAP concentrations decreased by 70% in these two patients with SMA type 1 with recent onset and notably, cNfL concentration decreased and CHOP INTEND scores improved coincidently  and more severely affected patients. Median change was −71 pg/mL  while cNfL/sCrn ratio did overall  and in SMA type 2 . The change within SMA type 3 slightly missed significance .In our study cohort, cGFAP concentrations in patients with SMA did not differ significantly from age‐ and sex‐matched controls before the start of treatment. In contrast, Olsson et al. reported higher cGFAP concentrations in children with SMA type 1 and 2 copies of Higher cGFAP concentration was associated with more impaired motor function and patients with SMA type 2 and non‐ambulatory patients had a higher cGFAP concentration than patients with SMA type 3 and patients who were still able to walk, respectively. This still supports the hypothesis of astrocyte involvement in SMA pathogenesis. However, despite the correlation of cGFAP concentration with disease severity, its limited applicability to distinguish SMA samples from control samples does not advocate for a diagnostic or prognostic use, at least in adult patients with SMA. For comparison of cGFAP with surrogate markers of neurodegeneration, we also determined cNfL concentrations, since these are known to reflect the extent of neurodegenerative processes in other motor neuron diseases, for example in amyotrophic lateral sclerosis. When investigating neurofilaments, one has to take into account their different subunits (e.g. phosphorylated neurofilament heavy chain (pNfH) versus NfL), the possibility of determination in different compartments (CSF versus blood) and their various detection methods (ELISA versus more sensitive methods as SIMOA and ELLA). As we reported before, pNfH in CSF was under lower limit of detection in most adult patients with SMA. In contrast, only few patients showed cNfL concentrations under the lower limit of detection measured with ELISA.Furthermore, regarding SMA type 1, Olsson et al. reported decreasing cGFAP concentrations during nusinersen treatment in severely affected children with SMA and short treatment delay.Our study has some limitations. Statistical analysis could be compromised by the small proportion of patients with SMA type 1 compared to type 2 and 3 within our study cohort. Also, GFAP was measured in the CSF compartment, which might not allow a conclusion about the origin of GFAP .GFAP concentration in CSF is not an outstanding biomarker in patients with long‐standing SMA, but might support the hypothesis that glial activation is involved in SMA pathology and may be modulated by nusinersen treatment. In contrast, NfL in CSF measured with high sensitive methods may be a promising biomarker in patients with SMA when normalized to preserved motor neuron mass, which should be subject to further studies along with a comprehensive investigation of the different neurofilament subunits in SMA.MF reports non‐financial support from Biogen outside the submitted work.PS reports no disclosures. CDW has received honoraria from Biogen as an advisory board member and for lectures and as a consultant and advisory board member from Hoffmann‐La Roche. She also received travel expenses from Biogen. OSK has received honoraria as a speaker/consultant and/or funding for travel expenses from the German Neuromuscular Society “Deutsche Gesellschaft fuer Muskelkranke” (DGM e.V.), Novartis, Biogen GmbH, Biermann Verlag GmbH, MK + S ‐ Medizin, Kommunikation & Service GmbH, and the Jain Foundation, outside the submitted work; and research support from the DGM e.V., outside the submitted work. AO has received honoraria from Biogen for lectures. SP has received grants from the German Neuromuscular Society, the Federal Ministry of Education and Research, the German Israeli Foundation for Scientific Research and Development, and the EU Joint Programme for Neurodegenerative Disease Research; and other support from Cytokinetics, Desitin Pharma, Biogen, Novartis, and Teva outside of the submitted work. JCK has received payment for consultation and advisory board participation from Biogen, Hoffmann‐La Roche and AveXis. KR has no conflicts of interest to declare that are relevant to the content of this article. AHu has no conflicts of interest to declare that are relevant to the content of this article. HT funding for research projects, lectures, and travel from Alexion, Bayer, Biogen, Celgene/Bristol‐Myers‐Squibb, GlaxoSmithKline, Janssen, Merck Serono, Novartis, Roche, Sanofi/Genzyme, Siemens and Teva, and received research support from Chemische Fabrik Karl Bucher GmbH, German Multiple Sclerosis Society (DMSG), and the German Ministry for Education and Research (BMBF). BW declares honoraria for lectures, travel support for meetings, and advisory board participation for Biogen, Novartis and Roche. BF has no conflicts of interest to declare that are relevant to the content of this article. ACL has received personal fees from AB Science, Biogen, Cytokinetics, GlaxoSmithKline, Orion Pharma, Novartis, Tau Rx Therapeutics, Teva, Mitsubishi, and Hoffmann‐La Roche outside of the submitted work. MO has no conflicts of interest to declare that are relevant to the content of this article. AH received royalties from BIOGEN and DESITIN as an advisory board member. RG has received honoraria from Biogen as an advisory board member and for lectures and as a consultant and advisory board member from Hofmann‐La Roche. He also received travel expenses and research support from Biogen.All authors contributed to the acquisition of data and revised the manuscript for intellectual content. MF, PS, and RG analyzed and interpreted the data and prepared the original draft. AH and RG concepted and designed the study. RG did supervision and project administration.Not applicable.The local ethics committees of all participating sites approved the study and all patients and controls signed written informed consent.Figure S1. Correlation between cGFAP and cCHIT1 concentration before treatment initiation. Correlation  calculated by partial rank correlation controlling for patients' age and height. Shading distinguishes SMA type: light gray, SMA type 1; mid gray, SMA type 2; dark gray, SMA type 3. cGFAP, glial fibrillary acidic protein concentration in cerebrospinal fluid; cCHIT1, chitotriosidase 1 concentration in cerebrospinal fluid.Figure S2. Individual dynamics of c GFAP concentrations during nusinersen treatment.N = 79Individual longitudinal cGFAP raw data plotted against patients' age. Connected symbols represent the change of cGFAP concentration for an individual patient during 14 months of nusinersen treatment. cGFAP, glial fibrillary acidic protein concentration in cerebrospinal fluidFigure S3. Relationship between decreasing cGFAP and cNfL concentration and motor improvement. Individual data regarding cGFAP and cNfL concentration and motoric outcome of two selected patients  who met the inclusion criteria by Olsson et al. . Each upward tick on the x‐axis indicates the time of nusinersen administration. cGFAP (light green symbols) and cNfL (lilac symbols) measurement and CHOP INTEND assessment (black symbols) were done before treatment initiation (V1), after 6 months (V5) and after 14 months (V7) of nusinersen treatment. cGFAP, glial fibrillary acidic protein concentration in cerebrospinal fluid; cNfL, neurofilament light chain concentration in cerebrospinal fluid; SMN2, Survival of motor neuron 2 gene; CHOP INTEND, Children's Hospital of Philadelphia Infant Test of Neuromuscular Disorders (higher score indicates better motor function).Figure S4. Subgroup analysis of cGFAP and cNfL values normalized to sCrn. (A–C) Comparison of different variables between patients with SMA type 2 and 3 using Mann–Whitney U test (B) or one‐way analysis of covariance (ANCOVA) considering age as covariate (A and C). Boxes show interquartile range (IQR), whiskers indicate values within 1.5‐fold IQR, single icons show individual values outside the whisker range, bold horizontal line represents median, + indicates mean; color shading distinguishes SMA subtype. (D) Change of ratios during 14 months of nusinersen treatment. Colored circles represent median value of respected biomarker and subgroup; each tick on the x‐axis indicates a nusinersen administration. cGFAP, glial fibrillary acidic protein concentration in cerebrospinal fluid; cNfL, neurofilament light chain concentration in cerebrospinal fluid; sCrn, serum creatinine concentration; V1, baseline visit; V7, follow‐up visit after 14 months; *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.Table S1. cNfL levels in treatment‐naïve patients with SMA (N = 73). cNfL, Concentration of neurofilament light chain in cerebrospinal fluid; IQR, interquartile range.Table S2. Dynamics in cNfL concentration during 14 months of nusinersen treatmentp value calculated by Wilcoxon signed‐rank test, significant values are marked in bold.cNfL, Concentration of neurofilament light chain in cerebrospinal fluid; IQR, interquartile range; Δ, difference vs baseline; Click here for additional data file.


Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV2)is a highly contagious virus that has infected 260 million individuals since December 2019. The severity of coronavirus disease 2019 (COVID‐19) depends upon the complex interplay between viral factors and the host's inflammatory response, which can trigger a cascadeeventually leading to multiorgan failure. There is contradictory evidence that angiotensin‐converting enzyme (ACEi) or angiotensin receptor blockers (ARBs) may affect mortality in patients with severe COVID‐19, theoretically due to interaction with the bradykinin pathway. Therefore, we aim to explore the association between ACEi and ARB use and mortality in severe SARS‐CoV2 infection.Severe acute respiratory yndrome with coronavirus (SARS‐CoV2) is a highly contagious virus that has infected 260 million individuals since December 2019. The severity of COVID‐19 depends upon the complex interplay between viral factors and the host's inflammatory response, which can trigger a cascadeeventually leading to multiorgan failure. There is contradictory evidence that angiotensin‐converting enzyme (ACEi) or angiotensin receptor blockers (ARBs) may affect mortality in patients with severe COVID‐19, theoretically due to interaction with the bradykinin pathway. Therefore, we aim to explore the association between ACEi and ARB use and mortality in severe SARS‐CoV2 infection.χ2 and t test was done. Finally, we did a backward selection Cox multivariate regression analysis using mortality as a dependent variable.This multicenter retrospective observational study enrolled 2935 COVID‐19 patients admitted at six hospitals in Southern California, USA, between March 2020 and August 2021. Our primary outcome was the association of pre‐hospital use of ACEi and ARB on in‐hospital mortality in COVID‐19 patients. First, relevant deidentified patient data were extracted using an SQL program from the electronic medical record. Then, a bivariate analysis of the relationship between ACEi and ARB use and different study variables using Of the 2935 patients in the study, hypertension was present in 40.6%, and congestive heart failure in 13.8%. ACEi and ARB were used by 17.5% and 11.3% of patients, respectively, with 28.8% of patients on either medication. After adjusting for confounding variables in the multivariate analysis, the use of ACEi  or ARB  was not independently associated with increased mortality.Our results are consistent with the clinical guidelines and position statements per the International Society of Hypertension, that there is no indication to stop the use of ACEi/ARB in COVID‐19 patients. It is known to primarily affect the respiratory system, creating flu‐like symptoms which can eventually lead to severe hypoxia and acute respiratory distress syndrome (ARDS).According to Yang et al.,ACE2 is a glycoprotein that is expressed in the kidney, intestine, endothelium, lungs, and heart.We aim to explore the association between pre‐hospital use of ACEi and ARBs and mortality in patients with COVID‐19. Most of the randomized trials to date have underpowered clinical endpoints and therefore cannot comment on the safety of ACEi and ARBs on adults with COVID‐19. Our study is the largest multicenter retrospective study to date with a sample size of greater than 2900 patients commenting on prior ACEi or ARB usage on mortality in COVID‐19.2This multicenter retrospective observational study was conducted at six hospitals in Southern California, USA. The study enrolled 2935 COVID‐19 patients admitted to six hospitals between March 2020 and August 2021. All patients were confirmed to have COVID‐19 infection through a positive PCR nasopharyngeal swab. Relevant de‐identified patient data were extracted using a structured query language (SQL) program from the electronic medical record, which included: age, gender, race, comorbidities, laboratory results on admission, date of hospital admission, date of discharge, medications they received while on admission, heart rate, and disposition at discharge. Our primary outcome was in‐hospital mortality of COVID‐19 patients who were taking ACEi or ARBs before hospitalization versus those who were not.χ2 and t test, with a p value of 0.05 considered significant. Finally, a backward selection Cox multivariate regression analysis was performed using mortality as a dependent variable. Biologically plausible or statistically significant variables from the bivariate analysis, such as age, sex, body mass index (BMI), comorbidities, use of ACEi or ARB, intensive care unit (ICU) admission, and mechanical ventilation, were used as independent variables in the multivariate model. The effect was expressed in terms of hazards ratio, and hypothesis testing was done using a two‐sided test, and an α value of 0.05 indicated statistical significance. Statistical analysis was completed using IBM SPSS version 27. The study was approved by the WIRB‐Copernicus Group (WCG) institutional review board (IRB).A univariate analysis of the independent variables was performed which included: patients' age, gender, ethnicity, marital status, comorbidities, the medication patients received while in the hospital, and laboratory results using means and percentages. Furthermore, a bivariate analysis was performed of the relationship between ACEi and ARB use and different study variables using 33.1Tables 3.2t test bivariate analysis of continuous variables, age, platelet count, and potassium were significantly associated with ACEi/ARB use. The mean age for patients on ACEi/ARB was 68.3 years compared to 58.7 for those not on ACEi/ARB (p < .001). The mean platelet count was 319,000/ml in those on ACEi/ARB compared to 334,000/ml in those not on ACEi/ARB (p = .01). Additionally, the mean potassium level was 4.8 meq/L in those on ACEi/ARB compared to 4.6 meq/L in those not on ACEi/ARB (p < .001) , diabetes (p < .001), HTN (p < .001), acute kidney injury (AKI) (p < .001), chronic kidney disease (CKD) (p = .002), congestive heart failure (CHF) (p < .001), chronic obstructive pulmonary disease (COPD) (p < .001), and coronary artery disease (CAD) (p < .001) were significantly associated with pre‐hospital ACEi/ARB use. Patients with diabetes (17.7% vs. 15.7%), HTN (63.5% vs. 31.4%), AKI (12.2% vs. 7.4%), CKD (23.4% vs. 18.3%), CHF (22% vs. 10.5%), COPD (7.1% vs. 4.1%), and CAD (88.9% vs. 57.7%) were more likely to be on ACEi or ARBs compared to those who were not. In addition, mortality was higher for patients on ACEi or ARB compared to those who were not (27% vs. 20.3%) (p < .001) . However, there was no statistically significant difference in mortality between patients who received ARBs and those who did not (p = .171)  Figure .3.3Backward selection Cox‐regression multivariate analysis was performed to determine whether ACEi/ARB use was independently associated with mortality Table . In the 3.4Multivariate subgroup analysis was performed to investigate other patient demographic factors or comorbidities which may be independently related to mortality in patients who received ACEi/ARB. Similar to our primary analysis, our multivariate subgroup analysis showed that ACEi/ARB use was not associated with mortality in the subset of patients with CHF and those without CHF. Similarly, ACEi/ARB use was not associated with mortality in patients with CKD versus those without CKD, and those aged 65 and above versus those below 65.4During the COVID‐19 pandemic, most of the patients who required hospitalization already had pre‐existing comorbidities such as CAD and HTN. Per Suleyman et al.'sp value of 0.005 in the bivariate analysis  and monoclonal antibody lanadelumab. Van deVeerdonk et al.Future studies should focus on the effects of ACEi/ARBs with concomitant use of Icatibant and Lanadelumab. It would be ideal to separate those taking ACEi  from those taking ARBs to accurately determine the effect of each drug independently. Previous use of ACEi/ARBs could potentially downregulate ACE2, therefore, minimizing the effects of Icatibant and Lanadelumab. However, without a larger sample size to cross‐reference pre‐exisiting use of ACEi/ARBs, it is difficult to truly quantify the benefits of these drugs.4.1Our results are consistent with the clinical guidelines and position statements; that there is no indication to stop ACEi/ARB in COVID‐19 patients. This is consistent with the International Society of Hypertension's 14 RCT meta‐analysis by Gnanethiran et al. which showed no difference in all‐cause mortality between subjects receiving ACEI/ARB and those receiving the placebo.The authors declare no conflicts of interest.Supporting information.Click here for additional data file.


Wind has a significant yet complex effect on bird migration speed. With prevailing south wind, overall migration is generally faster in spring than in autumn. However, studies on the difference in airspeed between seasons have shown contrasting results so far, in part due to their limited geographical or temporal coverage. Using the first full‐year weather radar data set of nocturnal bird migration across western Europe together with wind speed from reanalysis data, we investigate variation of airspeed across season. We additionally expand our analysis of ground speed, airspeed, wind speed, and wind profit variation across time  and space . Our result confirms that wind plays a major role in explaining both temporal and spatial variabilities in ground speed. The resulting airspeed remains relatively constant at all scales . We found that spring airspeed is overall 5% faster in Spring than autumn, but we argue that this number is not significant compared to the biases and limitation of weather radar data. The results of the analysis can be used to further investigate birds' migratory strategies across space and time, as well as their energy use. Using the first full year of weather radar data in western Europe, we investigate the difference of airspeed accros time  and space . Our result show that wind plays a major role in explaining the variation of groundspeed, while airspeed remains constant through space and time. Indeed, the stronger supporting winds in spring over autumn contribute to faster migration speed in spring  on the birds' airspeed. To further compare the seasonal difference in ground speed and airspeed, we investigate intraseasonal, geographical, and altitudinal differences.22.12.1.1ρ [bird/km3], ground speed along the east–west u and south–north v components [m/s], and radial velocity standard deviation  extracted from 37 weather radars in western Europe using vol2bird  at each datapoint of the weather radar data.The east–west 2.2We compare ground speed, airspeed, experienced wind speed, available wind speed, and wind profit in spring and autumn (taking 15 July as cut‐off day) at four different scales: (1) seasonal, (2) daily , (3) geographical, and (4) altitudinal.Vg) and airspeed (Va) can be computed respectively withUsing the triangle of velocities  average for the available wind speed.Finally, wind profit is computed as the vector projection of the wind speed on the assumed bird migration direction of 225°  and a smaller increase in autumn of 0.57 m/s per month (95% CI: 0.19– 0.94 m/s). In comparison, airspeed had a similar rate of −0.53 m/s per month in spring (95% CI: −0.34 to −0.73 m/s) and −0.58 m/s per month in autumn (95% CI: −0.44 to −0.72 m/s). This indicates that after accounting for wind conditions, the change in airspeed was much stronger within a season than between seasons.3.3Wind speed was stronger in south‐west Europe than in north‐east Europe Figure , particu3.4The vertical profile of ground speed resembled the profile of wind speed in both spring and autumn Figure . As a reThe slight decrease in the standard deviation radial velocity with altitude indicates a more directional flow of birds at higher altitude . In autumn, the higher standard deviation radial velocity in the first 100 m above ground suggests a high scatter of flight directions, which in turn explains the drop in airspeed .4We quantified wind assistance for nocturnal mass movements of migratory birds using a large data set covering western Europe with 37 weather radars over a full year. Airspeed is nearly constant across seasons, geography, and altitudes, but wind profit varied between seasons, geography, and altitudes, and consequently, birds migrate faster in spring than in autumn, in France compared to Germany, and at higher altitudes compared to lower altitudes. As flight costs are proportional to airspeed , while the airspeed was only about 24% higher . Harnessing the wind, bird ground speed was on average 25% higher than their airspeed . For an average bird migrating a distance of 3000 km in 80 h (assuming a ground speed of 10.5 m/s), wind profit saves 15 h of flight time (or 2–3 nights). As wind profit lowers the energy required to cover a certain distance, it reduces the number of stopovers and/or refueling time and ultimately migration duration.4.2Based on flight optimization theory, birds should reduce their airspeed with tailwinds and increase airspeed with head‐ or crosswinds in order to minimize flight costs per distance flown , mainly explained by wind conditions in both seasons: wind profit was on average 4.6 m/s in spring and only 1.1 m/s in autumn ; data curation (lead); formal analysis (lead); visualization (lead); writing – original draft (lead). Baptiste Schmid: Conceptualization ; data curation (supporting); formal analysis (supporting); writing – review and editing . Silke Bauer: Conceptualization ; writing – review and editing . Felix Liechti: Conceptualization ; data curation (supporting); formal analysis ; writing – review and editing .This research was funded by the Swiss National Science Foundation (grant no. 191138). This project is part of GloBAM funded through the 2017–2018 Belmont Forum and BiodivERsA joint call for research proposals, under the BiodivScen ERA‐Net COFUND programme, and with the funding organizations Swiss National Science Foundation (SNF 31BD30_184120), Belgian Federal Science Policy Office (BelSPO BR/185/A1/GloBAM‐BE), Netherlands Organization for Scientific Research (NWO E10008), Academy of Finland (aka 326315) and National Science Foundation .The authors have no conflicts of interest to declare that are relevant to the content of this article.Appendix S1Click here for additional data file.


Patients with substance use disorders (SUD) under methadone maintenance therapy (MMT) are susceptible to a number of complications . Evidence studies have shown the roles of the glutamatergic system in addiction. N‐Acetylcysteine (NAC) enhances extracellular glutamate, and is effective in the treatment of neuropsychiatric disorders. We assessed oral NAC as an add‐on to MMT medication for the treatment of SUD.n = 30) or placebo (n = 30) for 12 weeks. Psychological status and metabolic biomarkers were assessed at baseline and the end of the trial.In the current randomized, double‐blind, placebo‐controlled clinical trial, outpatients with SUD under MMT who were 18–60 years old received 2400 mg/day NAC (p = .005), and anxiety score . Furthermore, NAC treatment resulted in a significant elevation in total antioxidant capacity levels , total glutathione (GSH) levels , and a significant reduction in high‐sensitivity C‐reactive protein levels , and homeostasis model of assessment‐insulin resistance , compared with the placebo group.Compared with the placebo group, NAC treatment resulted in a significant improvement in depression score (β −2.36; 95% CI, −3.97, −0.76; In the current study, improvement in depression and anxiety symptoms as well as some metabolic profiles with NAC treatment for 12 weeks in outpatients with SUD under MMT was detected.  NAC is a sulfur‐containing agent that is widely studied for its anti‐inflammatory and anti‐oxidant impact , and the study was registered at the Iranian Registry of Clinical Trials . Before obtaining written informed consent, it was explained to the patients that withdrawing from the clinical trial would not affect their relationship with their healthcare provider.This was a 12‐week, randomized, double‐blind, placebo‐controlled, parallel‐group clinical trial of NAC in participants with SUD under MMT who were referred to a university‐affiliated outpatient SUD clinic (Soltan Mirahmad) in Kashan, Iran. The Soltan Mirahmad clinic is a center that is certified for the treatment and diagnosis of SUD. The personnel include a Ph.D. addiction expert, a general physician, an experienced psychiatrist, well‐trained nurses, and a clinical psychologist. The World Medical Association Code of Ethics (Declaration of Helsinki) was considered by the Research Ethics Committee of Kashan University of Medical Sciences for study approval 2.2Inclusion criteria: (1) SUD as diagnosed by DSM‐IV‐TR scales, (2) patients who received MMT, and (3) patients who were between 18 and 60 years.Exclusion criteria: (1) taking of anti‐oxidant and anti‐inflammatory supplements during the last 3 months, (2) hypertension, (3) hypothyroidism and hyperthyroidism, (4) positive urine test for methamphetamine (MA) and cannabis, and (5) unwillingness to cooperate.2.3n = 30) or placebo (n = 30) for 12 weeks in patients with SUD under MMT. Participants were randomized to receive either 12 weeks of oral NAC (2400 mg/day) or matched placebo, delivered as a take‐home medication. Due to lack of information about the appropriate dosage of NAC for patients with SUD under MMT, we used the treatment duration and dose of NAC based on a previous study in individuals with cannabis use and tobacco use disorder  by trained staff at the Soltan Mirahmad Clinic . Allocation concealment was done using sequentially numbered, sealed, opaque packages. Both randomization and allocation were carried out by independent persons who were not involved elsewhere in the clinical trial. Physicians, patients, nurses responsible for referring the patients, the statistician, also the investigators who rated the patients and administered the drugs, were all blinded to the allocation. Placebo tablets were identical to NAC tablets in color, shape, size, and odor. They were all kept in identical containers and were administered by an investigational drug pharmacist.2.6Psychological status is an important indicator of the health status in patients with SUD under MMT. So, psychological status was considered as the primary outcome and metabolic biomarkers as the secondary outcome.2.7Beck's Depression Inventories (BDI) was used to assess the levels of depression. BDI was determined using a self‐compiled questionnaire of 21 items in multiple‐choice format  in the early morning after an overnight fast. Blood was collected in two separate tubes: (1) one without EDTA to separate the serum to determine serum insulin, fasting plasma glucose (FPG), lipid profiles, and high sensitivity C‐reactive protein (hs‐CRP) concentration and (2) another one containing EDTA to examine plasma nitric oxide (NO), total antioxidant capacity (TAC), total glutathione (GSH), and malondialdehyde (MDA). Blood samples were immediately centrifuged  at 3500 rpm for 10 min to separate plasma and serum. Then, the samples were stored at −80°C before analysis at the Kashan laboratory. Serum insulin status was measured using an ELISA kit  with inter‐ and intra‐assay coefficient variances (CVs) of 4.5% and 2.6%, respectively. Quantitative insulin sensitivity checks index (QUICKI) and homeostasis model of assessment‐insulin resistance (HOMA‐IR) were calculated using the established formulas . Descriptive statistics were calculated for demographic variables. To detect the differences in anthropometric scales among two intervention groups, we used the independent‐samples Chi‐square and t‐test analyses. Multiple linear regression models were used to determine treatment effects on trial outcomes  after adjusting for confounding variables. The effect sizes were presented as the mean differences with 95% confidence intervals.2.10α) and type two errors (β) were defined as .05 and .20 (power = 80%), respectively. Based on a previous study  were analyzed. The CONSORT flow diagram on the enrollment of individuals in the present study is demonstrated in Figure Out of 82 screened outpatients with SUD under MMT program, 60 individuals were enrolled in the clinical trial and randomly assigned to both treatment and control groups to receive NAC or placebo, respectively . In the control group, seven people discontinued the clinical trial due to personal reasons, and positive cannabis urine tests. In the intervention group, nine people revoked their consent. Hence, 44 individuals  and the score of anxiety level , respectively. In addition, no significant differences were shown among the two groups in PSQI score , compared with the placebo group. In addition, NAC resulted in a significant reduction in hs‐CRP , and a significant increase in GSH levels , and TAC levels . There was no significant effect of NAC on FPG, insulin, QUICKI, total cholesterol, triglycerides, very‐low‐density lipoprotein (VLDL), LDL, and high‐density lipoprotein (HDL) cholesterol, NO, and MDA levels  NAC can inhibit NF‐κB, which plays a central role in the expression of genes involved in inflammation and oxidative stress; (2) NAC stimulates the synthesis of glutathione, which acts as a nucleophilic scavenger and as an anti‐oxidant in the event of oxidative tissue injury; (3) NAC might change the balance of T helper‐1 to T helper‐2 cells through its ability in changing the thiol intracellular solubility  are required to more precisely shed light. Also, we did not evaluate the cognitive function, relapses, craving, pain, and gene expression involved in metabolic profiles especially markers related to NF‐ĸB signaling pathways in outpatients with SUD under MMT. Unfortunately, because of limited funding, we did not examine the effects of NAC supplementation on these measures and it is suggested for a future study.5Overall, NAC consumption for 12 weeks had promising effects on mental health symptoms (depression and anxiety), insulin resistance, body anti‐oxidative defense system (TAC and GSH), and hs‐CRP levels in outpatients with SUD under MMT.Fateme Padoei, Peyman Mamsharifi, Pooya Hazegh, Homa Boroumand, Fatemeh Ostadmohammady, Samira Abbaszadeh‐Mashkani, Hamid Reza Banafshe, Amir Hassan Matini, Somayeh Ghadami Dehkohneh, and Amir Ghaderi contributed to the conception, design, statistical analysis, and drafting of the manuscript. All authors approved the final version for submission. Amir Ghaderi and Somayeh Ghadami Dehkohneh supervised the study.The authors declare that they have no conflict of interest.https://publons.com/publon/10.1002/brb3.2823.The peer review history for this article is available at


Epilepsia partialis continua is a rare epileptic syndrome presenting with simple, partial, repetitive motor seizures. It can be a result of structural central nervous system lesion or due to metabolic causes. We report a case of a 65‐year‐old male patient diagnosed with EPC secondary to diabetic ketoacidosis. Although epilepsia partialis continua is a rare presentation and its occurrence secondary to diabetic ketoacidosis is even a rarer presentation, the diagnosis should be considered in patients with diabetic ketoacidosis who have no other metabolic abnormalities and a normal central nervous scan. Regarding cognitive impairment, DM was reported to be associated with Alzheimer's disease.2A 65‐year‐old male patient presented to the emergency department due to involuntary and repetitive episodes of the left upper limb movement for 2 days. These episodes consisted of continuous clonic movement of the left elbow, left wrist, and fingers of the left hand. Seizures had been occurring every 2–5 h, continuing for one to 3 min in each episode. To add, consciousness and sphincter control were preserved throughout the episodes. The patient denied a history of similar symptoms or epilepsy.The patient looked unwell, temperature was 37.2°C, pulse rate was 98 beats per minute, respiratory rate was 28 cycles per minute, and blood pressure was 100/70 mmHg. In addition, the patient was thirsty with dry lips and mouth. The neurological examination of the patient was normal.Based on the presentation, central nervous system lesions and electrolyte abnormalities were considered as a differential diagnosis. Based on that, laboratory investigations, magnetic resonance imaging (MRI), cerebrospinal fluid (CSF) study, and an electroencephalogram (EEG) were ordered.2: 22.1 mmHg, HCO3: 16 mEq\L) . This established a new diagnosis of DM and diabetic ketoacidosis. Furthermore, serum sodium was 125 mEq/L , calcium was 8.7 mg/dL , blood albumin was 3.1 g/dL , and serum osmolarity was 292 mOsm/L .Laboratory investigations revealed a glucose level of 330 mg/dL  and ketone bodies in the urine (three crosses). An arterial blood gas (ABG) test was consistent with metabolic acidosis  levels, an inhibitory neurotransmitter, lowering the seizure threshold, and thus, explaining the occurrence of EPC.In our case, DKA was the first presentation of the DM. In addition, the MRI and CSF were normal. This is consistent with Van et al case report of EPC in a patient with DKA.4This report highlighted the association between EPC and diabetic ketoacidosis. Investigating metabolic disorders is an important part of assessing seizures, as EPC is resistant to anti‐epileptic as a sole treatment, detecting and treating the underlying cause is a cornerstone aspect of management.Ahmed Sayedahmed: Conceptualization; data curation; investigation; resources; software; writing – original draft; writing – review and editing. Abdelrahman Mohammed Alkhair: Data curation; investigation; writing – original draft; writing – review and editing. Abdalla Mohamedali: Software; writing – original draft; writing – review and editing. Mahmoud Mahgoub: Writing – original draft; writing – review and editing.The authors declare no conflict of interest. This case report did not receive any form of funding.Patient confidentiality was maintained in this report, and all ethical considerations were done in accordance with the Declaration of Helsinki.A written informed consent was obtained from the patient prior to the writing and submission of this case report.


The risk of graft‐induced dyskinesias (GIDs) presents a major challenge in progressing cell transplantation as a therapy for Parkinson's disease. Current theories implicate the presence of grafted serotonin neurons, hotspots of dopamine release, neuroinflammation and established levodopa‐induced dyskinesia.To elucidate the mechanisms of GIDs.Neonatally desensitized, dopamine denervated rats received intrastriatal grafts of human embryonic stem cells (hESCs) differentiated into either ventral midbrain dopaminergic progenitor (vmDA) (n = 15) or ventral forebrain cells (n = 14).2‐like receptor antagonists and not affected by 5‐HT1A/1B/5‐HT6 agonists/antagonists. Grafts in GID rats showed more microglial activation and lacked serotonin neurons.Of the eight rats with surviving grafts, two vmDA rats developed chronic spontaneous GIDs, which were observed at 30 weeks post‐transplantation. GIDs were inhibited by DMovement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder SocietyThese findings argue against current thinking that rats do not develop spontaneous GID and that serotonin neurons are causative, rather indicating that GID can be induced in rats by hESC‐derived dopamine grafts and, critically, can occur independently of both previous levodopa exposure and grafted serotonin neurons. © 2021 The Authors.  Intrastriatal grafts of hESC‐derived vmDA cells have been widely reported to survive, integrate, release DA, and alleviate functional impairments in rodent models of PDIn the process of studying the long‐term functional efficacy of hESC‐derived vmDA grafts in 6‐hydroxydopamine (6‐OHDA) lesioned rats, we unexpectedly observed spontaneous, continuous abnormal AIMs in a subset of rats. The rats had been checked weekly for health and welfare purposes, but detailed behavioral analysis commencing at 30 weeks led to the identification of chronic GIDs. We characterized the GIDs pharmacologically, targeting DAergic and 5‐HTergic systems. Subsequent immunohistochemical analysis of the brain tissue compared vmDA grafts from GID rats with vmDA grafts from non‐GID rats and with control hESC‐derived non‐DA, forebrain‐patterned (vFB) cells.Experiments were conducted in compliance with the United Kingdom (UK) Animals (Scientific Procedures) Act 1986 under Home Office License No. 30/2498, with the approval of the local Cardiff University Ethics Review Committee.Sprague–Dawley rat pups  were neonatally desensitized at 2 days post‐birth with mixed hESC‐derived neural progenitors and mature neurons Fig. , as descRotational behaviors were measured for 90 minutes  after 2.5 mg/kg methamphetamine , for 60 minutes after 0.05 mg/kg apomorphine  and after administration of other pharmacological agents Fig. . Observa+, CD8+, and 5‐HT+ cells were counted manually within and at the border of the graft. TH+, HuNu+, Ox42+/CD11b+, and GFAP+ cells were estimated using unbiased stereology. Two‐dimensional stereology was performed . Ox42 was also measured by optical density .At 52 weeks post‐graft, rats were terminally anaesthetized and transcardially perfused . Brains were processed for peroxidase‐based immunohistochemistry as previously described.Pharmacological challenges and rotation data were analyzed using Kruskal‐Wallis non‐parametric test with Group (non‐GID vs. GID) as the factor. Histological data were analyzed by one‐way ANOVA with Group  as the factor. Histological and behavioral data were correlated using Spearman's ρ. All statistical analyses were conducted using IBM SPSS Statistics 25 software.l‐dopa‐induced rotations and reduced amphetamine‐induced rotations , fenfluramine (5‐HT reuptake inhibitor), 8‐OH‐DPAT+CP94253 (5‐HT1A/1B agonists) and SB399885 (5‐HT6 antagonist) did not alter expression of the AIMs behaviors. High dose 1 mg/kg buspirone2/D3 antagonist) largely eliminated GID expression without reducing normal motor activity.To elucidate the neurobiological basis of the GIDs, pharmacological challenges were undertaken using receptor agonists and antagonists. AIMs were observed in both the home cage and rotometers , and (4) GIDs occur in association with functional improvements . Although in the present study, grafts contained ~14,000 TH+ cells ,These long‐term (1 year post‐graft) pilot data are important insofar as they suggest that GID emergence is possible in clinical trials of hESC‐derived vmDA grafts. This is despite the evidence that hESC‐derived cell preparations for clinical use will contain no/limited 5‐HT neurons and patient selection will prioritize patients without severe LIDs. Important parallels can be drawn with recently published details on five patients who developed persistent GIDs in a double‐blind United States (US) fetal cell transplant study.There has remained an unanswered question about the temporal pattern of GID emergence clinically. One supposition is that it relates to the withdrawal of immunosuppression, potentially triggering inflammatory driversThe use of neonatal desensitization makes this the first behavioral study of extended (12 months) human vmDA graft survival times in immunologically intact animals (in the absence of immunosuppression). Graft survival was low in this study (n = 4 grafts/group), but variability within this model has been reported previously.The severity of spontaneous GIDs in these rats were mild‐to‐moderate in magnitude when compared to LID established in standard protocols in rodentsImportantly for future clinical trials, although stem‐cell based therapies can be designed to be completely devoid of 5‐HT neurons and, therefore, may be considered safer from a GID perspective,l‐dopa exposure and 5‐HT neurons in the graft. Instead, the data presented here suggest involvement of D2‐like family receptors and suggest that GIDs may be associated with graft inflammation.This is the first study to demonstrate that stem cell‐based therapies can induce spontaneous GIDs in a rodent model of PD, simultaneous with functional recovery. The data demonstrate that GID onset can occur independently of (1) Research project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript: A. Writing of the First Draft, B. Review and CritiqueE.L.L.: Research project: Conception, Organization, Execution; Manuscript: Writing of the First Draft, Review and Critique.D.J. H.: Research project: Conception, Organization, Execution; Manuscript: Review and Critique.E.R.V.: Research project: Execution; Statistical Analysis: Execution; Manuscript: Review and Critique.R.L.H.: Research project: Execution; Manuscript: Writing of the First Draft and Review and Critique.S.T.: Research project: Organization, Execution; Manuscript: Review and Critique.M.J.L.: Research project: Conception, Organization, Execution; Statistical Analysis: Design, Execution, Review and Critique; Manuscript: Writing of the First Draft, Review and Critique.MJL was supported by a Parkinson's UK Senior Research Fellowship (F1502); ELL was support by MRC grant MR/R00630X/1.Video S1 Two rats are shown in this video, neither of whom have received any drug treatment at the point of videoing. These are spontaneous behaviors. Both rats have 6‐OHDA lesions in the right medial forebrain bundle. Grafted non‐GID rat: behaviors displayed by this rat typify those of 6‐OHDA lesioned rats, with ipsilateral tendencies (locomoting in a clockwise direction) with limited deviation of the head to tail line from the neutral straight with exploratory behaviors of sniffing and occasional rearing. Grafted GID rat: behaviors displayed by this rat reveal persistent driven contralateral locomotion (counterclockwise) with slow axial twisting involving repeated deviation of the head to tail line to a 45°–90° angle. The mild GIDs also consisted of repeated fast tapping of the contralateral forelimb, head bobbing, and orolingual movements, including tongue protrusions.Click here for additional data file.


Patients with endocrine therapy resistance and chemotherapy insensitivity have poor prognosis. Androgen receptor (AR) is widely expressed in breast cancer, but there is no clear conclusion about its function and correlation with prognosis in luminal B breast cancer. Further research is needed to reveal the role of AR in luminal B (HER–2 negative) breast cancer. (2) Methods: Retrospectively analyzed patients with early–stage luminal B breast cancer. The correlation between AR and its associated indexes with long–term survival was determined. (3) Results: A total of 985 patients were included with 143 treated by neoadjuvant therapy. Of these, 83.5% of the patients had AR expression ≥65%. High AR expression was associated with good disease–free survival (DFS) and overall survival (OS). In the neoadjuvant population, AR/estrogen receptor (ER) > 1.06 and residual tumor Ki67 > 23% had significantly worse DFS. (4) Conclusion: Low AR (<65%) expression is associated with poor prognosis in luminal B (HER–2 negative) breast cancer patients. High AR/ER and residual tumor Ki67 were associated with poor DFS in neoadjuvant group with a cutoff value of AR/ER > 1.06 and residual tumor Ki67 > 23%. Hormone receptor (HR)–positive breast cancers account for about 75% of all breast cancers ,2,3. TheThe systemic treatment of breast cancer can be classified as neoadjuvant or adjuvant therapy, depending on its timing. Neoadjuvant therapy plays a vital role in the treatment of breast cancer, not only to reduce the extent of surgery, and obtain information on treatment responsiveness and prognosis, but also to adjust subsequent treatments based on the treatment response to improve the survival of patients in non–pathological complete response (non–pCR) patients. In HER–2–overexpressing breast cancer and triple–negative breast cancer (TNBC) patients, the rate of pCR can reach 40–50% with neoadjuvant treatment, and the long–term survival of patients achieving pCR is significantly better. Luminal B (HER–2 negative) breast cancer lacks HER–2 targets, and the current standard neoadjuvant treatment regimen is chemotherapy; neoadjuvant endocrine therapy is still being investigated. Luminal B (HER–2 negative) breast cancer has poor sensitivity to neoadjuvant therapy, with a pCR rate of 5–10%, and the predictive value of pCR for long–term prognosis is not as high as that for HER–2 positive breast cancer and TNBC. Therefore, there is a need to find novel indicators to predict the efficacy of neoadjuvant therapy and outcomes for luminal B (HER–2 negative) breast cancers. The literature suggests that Ki–67 can be used to evaluate the efficacy of neoadjuvant endocrine therapy in patients with luminal B (HER–2 negative) breast cancer. However, the cutoff values and predictive sensitivities in different reports vary widely, and its predictive ability lacks validation in neoadjuvant chemotherapy.The androgen receptor (AR) is widespread across various breast cancer subtypes, and over 70% of HR–positive breast cancers express AR. Most retrospective studies have found that positive AR expression is associated with a better long–term prognosis of breast cancer ,5. HowevIn this single–center study, cases of luminal B (HER–2 negative) breast cancer at the Peking University First Hospital were retrospectively analyzed to investigate the correlation between AR and survival and neoadjuvant treatment outcomes in luminal B (HER–2 negative) breast cancer, and to determine AR cutoff values with clinical value.Patients with early–stage luminal B (HER–2 negative) breast cancer admitted to the Peking University First Hospital Breast Center between January 2013 and December 2019 were retrospectively analyzed. The inclusion criteria were patients with luminal B (HER–2 negative) breast cancer diagnosed using core needle biopsy (CNB) and treated by surgery at our hospital. The exclusion criteria were patients who had the following: (1) first diagnosis of stage IV breast cancer; (2) AR expression level missing from pathology report and inability to retest; and (3) underwent excisional biopsy or ultrasound–guided vacuum–assisted breast biopsy (VABB) prior to admission . The hosPreparation of CNB and surgically resected specimens was as described in the 2007 American Society of Clinical Oncology and the College of American Pathologists (ASCO/CAP) guidelines . SpecimeIHC for ER, PR, HER–2, AR, and Ki67 was performed for all included cases. In this study, ER , PR , AR , and Ki67  staining was performed using a fully automated IHC stainer (Dako Autostainer Link 48), and HER–2  staining was performed using a fully automated IHC stainer . In this study, ER, PR, and HER–2 were tested in accordance with the 2010 ASCO/CAP Guideline Recommendations for Immunohistochemical Testing of Estrogen and Progesterone Receptors (ER/PgR) in Breast Cancer  and the 2 intravenous infusion once every 3 weeks or albumin–bound paclitaxel 200–260 mg/m2 intravenous infusion once every 3 weeks; ② A: pirarubicin 50 mg/m2 intravenous infusion once every 3 weeks. Response evaluation was performed every two cycles in accordance with the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and patients underwent surgical treatment after completing neoadjuvant therapy. The pathological response was evaluated using the Miller–Payne system. According to the recommendations of the Collaborative Trials in Neoadjuvant Breast Cancer (CTNeoBC) international working group, pCR was defined as the absence of invasive cancer in the breast and axillary nodes irrespective of ductal carcinoma in situ (ypT0/is ypN0) [Among the included patients undergoing neoadjuvant therapy, neoadjuvant chemotherapy and neoadjuvant endocrine therapy were allowed. The first choice for the neoadjuvant chemotherapy regimen was 6–8 cycles of taxanes + anthracycline (TA), with the specific drugs being ① T: docetaxel 75 mg/mis ypN0) . The dect–test for independent samples was used for continuous variables, Pearson’s χ2 test or Fisher’s exact probability test was used for categorical variables, and the Mann–Whitney U test was used for ranked variables. The odds ratio (OR) for a pathological response was calculated using a binary logistic regression model. The hazard ratio (HR) for long–term survival was calculated using Cox analysis. In both binary logistic regression and Cox analysis, continuous variables were analyzed by groups according to clinical practice and experience. DFS was defined as the time from the surgery date to recurrence and metastasis, death, or last follow–up. Overall survival (OS) was defined as the time from the surgery date to death or last follow–up. DFS/OS was analyzed using the Kaplan–Meier method, and differences between subgroups were tested using the log–rank test. Diagnostic tests were analyzed using ROC curve analysis. The selection of the best threshold is based on the boundary point when the Youden index is the maximum value. Differences with p < 0.05 were considered statistically significant. All tests were two–sided. All statistical analyses were performed using the IBM SPSS Statistics .For comparisons of clinicopathological characteristics between groups, the A total of 985 patients, including 978 women and 7 men with a median age of 56 years, were included in the study. Patients were divided into neoadjuvant and non–neoadjuvant therapy groups based on the treatment modality, with 143 patients  in the neoadjuvant therapy group and 842 patients  in the non–neoadjuvant therapy group. Most patients in the neoadjuvant therapy group (88.1%) underwent neoadjuvant chemotherapy containing anthracycline and taxanes, and nine (6.3%) underwent neoadjuvant endocrine therapy. Seven patients achieved pCR for a pCR rate of 4.9%. The median follow–up time was 42 months (range: 4–101 months), with 37 DFS events and 10 OS events in the neoadjuvant therapy group and 46 DFS events and 19 OS events in the non–neoadjuvant therapy group during follow–up. The baseline characteristics of the overall population were shown in Table 1Compared to patients in the non–neoadjuvant therapy group, patients in the neoadjuvant therapy group were mostly young and non–menopausal, in late clinical stage, and had a high histological grade, low ER, PR, and AR expression levels, and high Ki67 expression levels; the differences between the two groups were statistically significant. There were no statistically significant differences in body mass index (BMI) or HER–2 expression levels between the two groups.p = 0.032).Eleven patients (7.7%) in the neoadjuvant therapy group were AR–negative before treatment, 39 (27.3%) had AR expression levels of 1–64%, 21 (14.7%) had AR expression levels of 65–89%, and 72 (50.3%) had AR expression levels above 90%. Eleven patients (1.3%) in the non–neoadjuvant therapy group were AR–negative before treatment, 101 (12.0%) had AR expression levels of 1–64%, 196 (23.3%) had AR expression levels of 65–89%, and 534 (63.4%) had AR expression levels above 90%; the differences between the two groups were statistically significant .AR/ER and AR/PR were calculated as AR expression level/ER expression level and AR expression level/PR expression level, respectively. In cases of PR negativity, the AR expression level was used as AR/PR. Overall, 14.7% of patients had AR/ER > 1.00 and 55.1% had AR/PR > 1.00; the difference between the two groups was not statistically significant (AR/ER p = 0.003).Ki67 expression before treatment was higher than 30% in 95 patients (66.4%) in the neoadjuvant therapy group and 207 patients (24.6%) in the non–neoadjuvant therapy group; the difference between the two groups was statistically significant  had a residual tumor Ki67 over 20%. The ΔKi67 was calculated as ΔKi67 = residual tumor Ki67 − CNB Ki67, with “substantial decrease” defined as a decrease of at least 40%, “moderate decrease” defined as a decrease of 20–39%, “small decrease/no change” defined as a decrease of 0–19%, and “elevation” defined as a higher residual tumor Ki67 than CNB Ki67. A total of 31 patients (21.7%) exhibited a substantial decrease, and 15 patients (10.5%) exhibited elevation of Ki67 levels compared to preoperative levels. Details of the neoadjuvant therapy group are summarized in A multifactorial survival analysis was performed on the overall luminal B (HER–2 negative) breast cancer population using backward regression. Age, baseline T–stage, baseline N–stage, histological grade, baseline ER, PR, HER–2, Ki67, AR, AR/ER, AR/PR levels, and whether neoadjuvant therapy was administered as the factors initially included. A total of seven steps were performed, with age, baseline T–stage, baseline N–stage, histological grade, baseline AR, and whether neoadjuvant therapy was administered as the factors included in the end. The results of steps 1 and 7 are presented in OS multifactorial survival analysis was also performed using the same backward regression with the same included factors as for DFS and a total of 8 steps. The factors included in the end were baseline T stage, baseline N stage, histological grade, CNB HER–2, and CNB AR. The results of steps 1 and 8 are presented in p < 0.001; OS p < 0.001), with a poor DFS and OS in patients with AR < 65%. In order to further determine whether AR is a prognostic factor independent of ER, we compared the ER expression levels between groups of AR < 65% and ≥65%. The results showed that there was a significant difference in the expression of ER between the two groups. The expression of ER was relatively lower in the subgroup with low AR expression . This conclusion is consistent with the finding that expression of ER and AR was related in the overall population.In this study, the AR cutoff value was selected as 90% based on clinical experience. Multifactorial survival analysis suggested that AR ≥ 90% was a protective factor for patient prognosis. To further investigate the optimal AR cutoff value associated with long–term prognosis, the ROC curve of AR for predicting recurrent metastatic events was plotted a, and thAmong the neoadjuvant therapy patients, seven achieved pCR, with one DFS event and no OS events during the follow–up period. A total of 136 patients did not achieve pCR, with 36 DFS events and 10 OS events during the follow–up period. The differences in DFS and OS between the pCR and non–pCR groups were not statistically significant .p = 0.105). In the ER high expression group, DFS of the population with AR/ER > 1.00 showed a trend of benefit, but there was also no statistical difference (p = 0.213). OS multifactorial survival analysis was not performed due to the small number of OS events.To further investigate the prognosis–related factors in the neoadjuvant therapy population, DFS multifactorial survival analysis was performed on the non–pCR population of luminal B (HER–2 negative) breast cancer who underwent neoadjuvant therapy. Patients were screened using a backward regression, with age, baseline T–stage, baseline N–stage, histological grade, CNB ER, PR, HER–2, Ki67, AR, AR/ER, AR/PR levels, residual tumor TN stage, residual tumor ER, PR, HER, Ki67, and ΔKi67 as the factors initially included . Late bap = 0.003) with no significant difference in OS (p = 0.222), and patients with residual tumor Ki67 > 23% had significantly worse DFS than patients with residual tumor Ki67 ≤ 23% (p = 0.003) with no significant difference in OS (p = 0.148).In this part of the study, an AR cutoff value of 65% was selected, AR/ER and AR/PR cutoff values of 1.00 were selected, and a residual tumor Ki67 cutoff value of 20% was selected. Multifactorial survival analysis suggested that AR/ER > 1.00 and residual tumor Ki67 > 20% were risk factors for DFS events. To further investigate the prognosis–related optimal AR/ER cutoff value, the ROC curve of AR/ER for predicting DFS events was plotted a, and thThe 2011 St. Gallen International Expert Consensus proposed classifying breast cancers based on molecular expression markers. Those with positive ER expression and low PR expression or high Ki67 expression were defined as luminal B breast cancer, which accounted for approximately 50–60% of all breast cancers. The systemic treatment of luminal B (HER–2 negative) breast cancer primarily involves endocrine therapy and chemotherapy. The 8–year DFS of patients with luminal B (HER–2 negative) breast cancer is 78.9% . Some paAR is a widespread molecular marker across various breast cancer subtypes, and approximately 70–90% of luminal–type breast cancers express AR ,20. In EA total of 985 patients with luminal B (HER–2 negative) breast cancer were enrolled in this study, with a median follow–up of 42 months. There were a total of 83 DFS events and 29 OS events, and the 3–year DFS was 97.3%, 3–year OS was 98.7%, 5–year DFS was 93.5%, and 5–year OS was 97.4%. In the SOFT trial, the 5–year DFS of patients ranged 84.7–86.6% , and in In this study, over 60% of patients had AR expression levels above 90%, and only 2.2% did not express AR. In the literature, the definition of negative and positive AR expression is not consistent, with 1%, 10%, or more, or the Allred score all being used. It is generally accepted that 70–90% of patients with luminal–type breast cancer are positive for AR expression. The high percentage reported in this study may be associated with the difference between Chinese and Western populations and using an AR cutoff value of 1%. The inconsistency of AR cutoff values in the literature affects the comparability of the study results. It informs the need for finding AR prognosis–related cutoff values. The literature reports that male breast cancer patients represent approximately 1% of the patient population, and almost all are ER+ AR+ . A totaln = 219) and a validation cohort (n = 418) to determine AR expression cutoff values. Their findings revealed that although most studies selected 1% or 10% as cutoff values, these were not the best cutoff values to differentiate between patients with different outcomes, and they suggested that a positivity cutoff value of 78% had better sensitivity (57.1%) and specificity (75.0%). Patients with AR > 78% had better survival, and those with positive ERα and AR > 78% had the best outcomes. Yang et al. [Multifactorial analysis of survival in the overall population suggested that age above 40 years was a protective factor for DFS events. Late T stage, axillary lymph node metastasis, and high histological grade were risk factors for DFS events. In this study, over 60% of patients had at least 90% AR expression levels, and the median AR level of the overall population was 90%. Therefore, a preliminary analysis was performed using an AR expression level of 90% as a cutoff value, and it was observed that the AR expression level correlated with DFS and OS. Further analysis showed that when patients were grouped using an AR of 65% as a cutoff value, there were significant differences in DFS and OS between the two groups, and patients with AR ≤ 65% had significantly worse survival. Recciardelli et al.  reviewedg et al.  studied In the population of patients who underwent neoadjuvant therapy, 37 DFS events occurred, with a relapse rate of 25.9%. pCR was achieved in only seven individuals in this study, for a pCR rate of 4.9%. Prognostic analysis grouped by pCR or non–pCR suggested that pCR did not correlate with long–term survival. Therefore, further investigation of prognostic correlates in the neoadjuvant therapy population is needed. Currently, there have been few studies on AR in neoadjuvant therapy for breast cancer, and some studies have suggested that AR positivity may be associated with poor neoadjuvant outcomes in TNBC. Witzel et al.  reviewedp = 0.023). Further investigation of the cutoff value showed that the optimal AR/ER cutoff value was 1.06, and patients with AR/ER >1.06 accounted for 15.4% of the population who underwent neoadjuvant therapy. Kaplan–Meier analysis suggested that patients with high AR/ER had significantly worse DFS and no significant difference in OS when classified using an AR/ER cutoff value of 1.06. However, the follow–up period of this study was short, and the OS results were incomplete.The present study investigated the prognostic, predictive value of AR/ER and AR/PR. Most patients had high AR and ER expression, with a median and mode AR/ER of 1.00. Overall, 14.7% of patients had AR/ER > 1.00, and 31 patients had AR/ER ≥ 2.0, accounting for 3.1% of the study population. There were no statistically significant differences in AR/ER and AR/PR between the neoadjuvant and non–neoadjuvant therapy populations. In the neoadjuvant therapy population, the risk of recurrence was 5.381 times higher in patients with high AR/ER than in those with low AR/ER  and disease–specific survival . In a study by Rangel et al. [The literature shows that AR/ER and AR/PR correlate with endocrine resistance and survival. The study by Cochrane et al.  includedl et al. , 402 patl et al.  performel et al.  reviewedl et al.  reviewedIn luminal–type breast cancers, high AR expression is associated with a good prognosis, and low ER expression is associated with a poor prognosis. Therefore, further investigation is required to determine whether AR/ER is an indirect manifestation of low ER expression. The role of AR in HR–positive breast cancer is controversial, particularly with regard to the relationship between AR and resistance to endocrine therapy. Cochrane et al.  found thKi67 expression levels are predictive of breast cancer prognosis, with higher Ki67 expression levels indicating worse survival. In hormone receptor–positive breast cancer, Ki67 is an important molecular marker to distinguish between luminal A and B breast cancers.A multifactorial survival analysis of non–pCR patients who underwent neoadjuvant therapy revealed that high residual tumor Ki67 expression was a risk factor for recurrence and metastasis, whereas changes in residual tumor ER, PR, and Ki67 before and after neoadjuvant therapy were not correlated with prognosis. Using the ROC curve, we found that the optimal residual tumor Ki67 cutoff value for distinguishing prognosis was 23%. Non–pCR patients with residual tumor Ki67 < 23% had significantly better survival . Among nThe advantage of the present study is that it is an early and large population–based, single–center study of the relationship between AR and related indicators and survival among the luminal B breast cancer population in China, and the number of included cases is larger than most foreign studies. This is the first study of the correlation between AR/ER and AR/PR with survival in China. The number of cases far exceeds that of foreign studies related to AR/ER. Moreover, this is the first study of neoadjuvant therapy and AR, AR/ER, and AR/PR in China, and it is also a less studied and novel research topic internationally. The limitations of the study are that it is a single–center, retrospective study that lacks further testing of gene transcription levels; therefore, its results should be validated in a large–sample, prospective study, and gene–level and translational studies are needed to investigate the mechanism.Luminal B breast cancer has a relatively good overall prognosis. However, a few patients still exhibit endocrine resistance, early recurrence, and low neoadjuvant chemotherapy pCR rates. Novel prognostic and response–related biomarkers can help screen patients with poor prognoses and may serve as a therapeutic target. In this study, we found that AR influenced the long–term survival of patients with luminal B (HER–2 negative) breast cancer, with an optimal cutoff value of 65%. Patients had significantly worse DFS and OS when AR < 65%. In patients with luminal B (HER–2 negative) breast cancer who underwent neoadjuvant therapy, AR expression level alone was not an influencing factor for prognosis, whereas AR/ER > 1.06 and residual tumor Ki67 > 23% were risk factors for DFS. The study contributes to the early screening of patients with a poor prognosis of luminal B (HER–2 negative) breast cancer and provides a basis for studies on AR–targeted therapies. More extensive and in–depth studies are further needed to address the relationship between luminal B breast cancer and AR.


The experimental design was arranged in a 2 × 2 × 3 factorial format together with two temperatures , two forage/concentrate ratios , and two CAP concentrations in the incubation fluid at 20 and 200 mg/L with a control group. Regarding the fermentation characteristics, high temperature reduced short-chain fatty acids (SCFA) production except for molar percentages of butyrate while increasing acetate-to-propionate ratio and ammonia concentration. The diets increased total SCFA, propionate, and ammonia concentrations while decreasing acetate percentage and acetate-to-propionate ratio. CAP reduced acetate percentage and acetate-to-propionate ratio. Under hyperthermal condition, CAP could reduce acetate percentage and increase acetate-to-propionate ratio, lessening the negative effect of high heat on SCFA. Hyperthermal condition and diet altered the relative abundance of microbial abundance in cellulose-degrading bacteria. CAP showed little effect on the microbial abundance which only increased Butyrivibrio fibrisolvens. Thus, CAP could improve rumen fermentation under different conditions, with plasticity in response to the ramp of different temperature and dietary conditions, although hardly affecting rumen microbial abundance.This study aimed to determine the effect of capsicum oleoresin (CAP) on rumen fermentation and microbial abundance under different temperature and dietary conditions  In the ruminants, the rumen functioning is susceptible to climatic and dietary changes. It was reported that temperature and feed characteristics (forage: concentration) are significant parameters that affect rumen function . RuminalCapsicum oleoresin (CAP) is extracted from capsicum and the active ingredient is capsaicin. As a dietary additive, CAP has a variety of functions, such as anti-inflammatory , antioxiThe experiment conditions were arranged in a 2 × 2 × 3 factor design, including two temperatures , two diet ratios , and two CAP concentrations in the incubation fluid at 20 (LC) and 200 mg/L (HC) with a control group (CON). Physiological temperature and high temperature were selected based on physiological rumen temperature  and the 2 flushing. Fermentation substrate (0.5 g) and incubation fluid (50 mL) were added to each fermentation flask, injected with CO2, and sealed with a butyl rubber plug and aluminum cap. Finally, the flask was placed in two constant temperature shock incubators set at 39°C and 42°C, respectively.Rumen fluid was collected from four cows immediately after slaughtering at a commercial slaughterhouse . All cows were fed a total mixed diet mainly consisting of silage, excluding disease factors, and rumen fluid was collected individually through four layers of cheesecloth within 15 min after slaughter and reached the laboratory within 30 min. Rumen fluid was maintained in a preheated bottle without top air at 39°C after collecting until it reached the laboratory. Next, fresh buffer solutions were mixed according to At the end of fermentation, the pH of the incubation fluid was measured with a pH meter . The collected culture medium was divided into 2 mL sterile tubes. Isometric samples were collected and stored at −20°C immediately for ammonium and SCFA analysis. The remaining samples were stored at −80°C with one isometric sample for further microbial abundance analysis and the remaining samples were retained.g for 10 min at 4°C to obtain the supernatant. Using a gas chromatograph , capillary column , and a pyrophoric detector. The oven temperature was initially maintained at 80°C for 5 min, increased to 190°C, 12.5°C/min, and held at 190°C for 3 min. The injector and detector temperatures were 250°C and 280°C, respectively. Determination of ammonia nitrogen was performed by colorimetry according to For SCFA analysis, incubation fluid (1 mL) was added to 200 μL of 25% metaphosphoric acid and centrifuged at 12,000 4 yield was calculated according to previously reported formula  = 0.45 × Acetate (mmol/L) – 0.275 × Propionate (mmol/L) + 0.40 × Butyrate (mmol/L).CHMicrobial DNA was extracted from rumen fluid using a Tiangen commercial kit according to the instructions  as reported in a previous study , and DNARuminococcus albus, Ruminococcus flavefaciens, Butyrivibrio fibrisolvens, Fibrobacter succinogenes, Prevotella ruminicola, and Ruminobacter amylophilus were expressed as the proportion of 16S rDNA of total rumen bacteria at 24 h. Relative abundance was expressed as a proportion of the specific gene fragments number to the total rumen bacterial 16S rDNA number, calculated according to the following equation: relative quantification = 2− , where Ct represents threshold cycle based on the report of The relative population sizes of total bacteria, total anaerobic fungi, total protozoa, total methanogens, p < 0.05) was used for the mean comparison and the trend was set at 0.05 < p ≤ 0.10.All statistical analyses were performed using the PROC MIXED procedure of SAS 9.4 (SAS Institute Inc.). Data were analyzed according to factorial permutations in a randomized compartmentalized design. The main effects of amylases include temperature, diet, and CAP levels, their 2-way, 3-way interactions, and the random effects. For daily measurements, the data were analyzed as repeated measurements. The composite symmetry was a variance–covariance structure. All values were presented as least squares mean ± standard error of the mean (SEM), stated otherwise. Comparisons between LS means were performed according to the PDIFF function. All experiments and analyses were made in triplicate. The analysis of variance followed by a Duncan test (p < 0.05), while there was no effect on CAP addition. Hyperthermal condition increased the molar percentages of butyrate, isobutyrate, and acetate-to-propionate ratio while decreasing propionate and caproate percentage (p < 0.05). The addition of CAP decreased acetate percentage and acetate-to-propionate ratio (p < 0.05) and tended to increase propionate percentage (p = 0.09). Hyperthermal condition and high concentration diet increased ammonia concentrations (p < 0.05), and there was an interaction between temperature and diet (p < 0.05). Temperature tended to increase pH in the hyperthermal group compared to the normal group (p = 0.09). Temperature, diet, and CAP addition did not affect methane.The fermentation characteristics influenced by culture conditions and CAP addition are indicated in p < 0.05) compared with the CON and HC (p < 0.05) while tending to increase propionate percentage (p ≤ 0.10). At the same time, hyperthermal condition reduced propionate percentage and increased acetate to propionate ratio in the CON and LC compared with physiological temperature (p < 0.05), while there was no difference in the HC group.Under hyperthermal condition, the CAP group reduced the SCFA in LC (N and HC . The HC p < 0.05), and tended to decrease valerate percentage (p = 0.08). Under dietary factors, LF tended to decrease acetate concentrations in the LC . Under dietary factors, LF tended to decrease acetate concenF (p < 0.05), and the ammonia concentration in the LF was significantly higher in the HC than in the LF (p < 0.05).As shown in B. fibrisolvens, while it decreased total protozoa, F. succinogenes, and P. amylophilus (p < 0.05). There is no difference in R. albus, R. flavefaciens, and R. ruminicola by the effect of hyperthermal condition. The diets significantly decreased total anaerobic fungi, B. fibrisolvens, F. succinogenes, and P. amylophilus (p < 0.05) while tended to increase total protozoa and lower Ruminococcus flavefaciens (p < 0.10). The CAP significantly increased the relative abundance of B. fibrisolvens in the LC relative to the CON (p < 0.05).The results of the relative abundance of microbial populations are presented in in vivo  reportebutyrate . CAP didin vitro, by reducing acetate percentage and acetate-to-propionate ratio. Microbial abundance was mainly influenced by temperature and diet, while the effect of CAP was minimal.Hyperthermal condition and dietary factors could alter SCFA concentrations, acetate percentage, propionate percentage, acetate-to-propionate ratio, and ammonia concentrations. The CAP could influence ruminal fermentation The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.ZA and GL wrote the manuscript. MA, UR, and LY revised the manuscript. SG investigated for this research. ZY, TY, and HL provided the methodology for this research. JZ and CC did the formal analysis. All authors have read and agreed to the published version of the manuscript.This work was supported by the earmarked fund for CARS36.CC was employed by Bright Farming Co. Ltd.The remaining 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.