Although cholesterol has been hypothesized to promote cancer development through several potential pathways, its role in the risk of developing hormonally driven cancer is controversial. This literature review summarizes evidence from the highest quality studies to examine the consistency and strength of the relationship between serum cholesterol parameters and incidence of hormonally driven cancer. Articles were identified using EMBASE. Longitudinal observational studies published between January 2000 and December 2020 were considered for inclusion. The endpoint of interest was incident prostate, ovary, breast, endometrium, and uterine cancers. In total, 2732 reports were identified and screened; 41 studies were included in the review. No associations were found for ovarian cancer. Most endometrial cancer studies were null. The majority (76.9%) of studies reported no association between cholesterol and prostate cancer. Data on breast cancer were conflicting, associations limited, and effect sizes modest. Our results do not provide evidence for a clear association between cholesterol and different types of incident, hormonally driven reproductive cancers. Future studies should investigate the impact of lipid‐lowering therapy. A literature review summarizing evidence from studies examining the consistency and strength of the relationship between serum cholesterol parameters and incidence of hormonally driven cancer was conducted. The endpoint of interest was incident prostate, ovary, breast, endometrium, and uterine cancers. In total, 2372 reports were identified and screened; 41 studies were included in the review. Overall, our results do not provide evidence for a clear association between cholesterol and different types of incident, hormonally driven cancers. Further studies are needed to assess the role of cholesterol in the development of other cancer types.2We conducted a literature review to find studies that assessed the association between serum cholesterol levels and the development of hormonally driven reproductive cancers in humans.2.1Studies reporting on adults (≥18 years of age) in the general population who were at risk of developing hormonally driven cancers (and without the cancer of interest at baseline) were included. Studies enrolling both those <18 years old and adults (≥18 years old) were included if >80% of the population were adults, or if separate data were presented for adults. Studies enrolling patients who already had cancer at the start of the study were excluded. The exposure of interest was high serum cholesterol levels versus low serum cholesterol levels. High versus low cholesterol could be assessed incrementally (tertiles and quartiles) or using a single cutoff point. Cholesterol measurements of interest included total cholesterol, high‐density lipoprotein cholesterol (HDL‐C), and low‐density lipoprotein cholesterol (LDL‐C). Outcomes of interest were the incidences of breast, endometrial, or ovarian cancer (for women) and the incidence of prostate cancer (for men). Studies reporting on the risk of testicular cancer in men or cervical cancer in women were excluded, since hormone levels have not been previously associated with the incidence of these cancers. Observational studies designed to assess the temporal association between cholesterol and cancer development were considered, including cohort, case‐cohort, nested case–control, and Mendelian randomization studies. Both prospective and retrospective study designs were considered. Published systematic literature reviews and/or meta‐analyses of studies with relevant designs, as noted above, were also included. The following study designs were excluded: case control studies, case series, and case reports. Interventional studies  were excluded, due to additional effects that may be independent from lipid lowering. All articles and abstracts reviewed were required to be in English. Non‐English papers (even if the abstract was in English) were excluded.2.2We searched the EMBASE electronic bibliographic database from January 1, 2000, through to December 14, 2020. In addition, we searched congress abstracts listed in EMBASE over a 2‐year period . A full‐text screen was performed on the references identified from the title and abstract screening. Systematic reviews and meta‐analyses were identified during the first pass, and manual bibliographic searching was conducted to identify any additional relevant studies. The search criteria are provided in Table 2.3p values.The identified reports, based on the above eligibility criteria, were screened in a two‐step process:  title/ab33.1A flow diagram of the screening results is shown in Figure 3.2n = 2118; 43 cases) reported a positive association between higher total cholesterol and an increased risk of prostate cancer .In total, 17 longitudinal studies reporting on the incidence of prostate cancer met the inclusion criteria, including cohorts from Korea, Scandinavia, Western Europe, the USA, and the UK Table . A summaOnly three studies assessed the association between LDL‐C and incidence of prostate cancer.Lastly, the association between low HDL‐C levels and prostate cancer was reported in seven studies3.3Three Mendelian randomization studies assessing the association between circulating lipids and prostate cancer were identified Table .48, 43.4The literature review identified 17 records reporting on the association between serum cholesterol levels and risk of breast cancer, including cohorts from Austria, Denmark, France, Korea, Italy, Norway, Sweden, and the USA Table . A summaptrend 0.96) after model adjustment for age and treatment  or per 1 SD increase (HR [95% CI]: 0.96 [0.89–1.03]) and breast cancer risk.n = 9738; 326 cases) reported that the relative risk of breast cancer had no significant trends over quartiles of total cholesterol levels in perimenopausal/postmenopausal women ; furthermore, total cholesterol did not affect breast cancer risk in premenopausal women .The effect of total serum cholesterol levels on incident breast cancer risk varied among the studies identified. An analysis of the Women's Health Study cohort, including 15,602 women aged ≥45 years and without cardiovascular disease, use of hormone replacement therapy, or use of lipid‐lowering therapies at baseline, demonstrated no association between quartiles of total cholesterol  of the National Institute of Health‐American Association of Retired Persons (NIH‐AARP) Diet and Health Study reported a consistent positive association between elevated cholesterol (self‐reported) and overall risk of breast cancer (HR [95% CI]: 1.13 [1.04–1.23]), which was maintained in a normal BMI subgroup.n = 38,823; 708 cases), an inverse association between total serum cholesterol was reported for those with cholesterol in the highest quartile (>6.82 mmol/L) compared with the lowest quartile (<5.24 mmol/L) and postmenopausal breast cancer . However, it should be noted that no association was reported among overweight and obese women.ptrend 0.04).In comparison, a positive association between serum total cholesterol levels and risk of breast cancer was reported in three studies.ptrend 0.1); interestingly, the same study reported that total cholesterol and HDL‐C were associated with breast cancer risk .p = 0.84); the results were not modified when assessed by menopausal status.ptrend 0.02); no significant association was observed in the premenopausal cohort.ptrend 0.05; postmenopausal: per one unit increment in HDL‐C, HR [95% CI]: 0.53 [0.28–1.01], ptrend 0.05).ptrend 0.03), which strengthened when excluding users of hormone therapy .In total, 12 studies reported on the association between HDL‐C levels and breast cancer. A prospective study evaluating the association of breast cancer with lipid biomarkers in participants from the Women's Health Study reported no association between HDL‐C levels and breast cancer risk .Four Mendelian randomization studies were identified that evaluated the association between circulating lipids and breast cancer Table .49, 6p = 0.02 and 1.09 (1.02–1.18); p = 0.020, respectively. The other two studies found no association between genetically predicted LDL‐C and breast cancer.p = 0.004) but not for ER‐ breast cancer (p = 0.577).PCSK9 genetic variants known to result in elevated LDL‐C levels were associated with increased breast cancer risk overall .Four studies reported the association between genetically predicted increase in LDL‐C and breast cancer.p = 4.93 × 10−4 and 1.12 [1.08–1.16]; p = 1.7 × 10−9), respectively.p = 0.037).Similar to the LDL‐C findings, half of the studies examining the relationship between HDL‐C and breast cancer observed a significant association.3.6The risk of endometrial cancer has risen substantially over the years, mainly due to increases in BMI.ptrend 0.731). However, when the association was analyzed according to the National Cholesterol and Education Program thresholds for high cholesterol, <6.50 versus ≥6.50 mmol/L, instead of quartiles, the association no longer remained.For the lipoproteins of interest, four of the five studies reported associations between the risk of endometrial cancer by total cholesterol, LDL‐C, and HDL‐C,ptrend 0.0003); however, after further adjustment for sex steroid hormones and other obesity‐related hormones, the observed association between HDL‐C and endometrial cancer was no longer significant (ptrend 0.09).Of the four studies that assessed the relationship between HDL‐C levels and incidence of endometrial cancer, only one reported an association.3.7n = 188,578p = 0.036); however, this finding was not significant after adjusting for multiple comparisons.One record reporting on a bidirectional, two‐sample Mendelian randomization analysis to investigate the relationship between circulating lipids  and endometrial cancer risk was identified.3.8n = 24,208; 115 cases) reported no association between quartiles of total cholesterol, LDL‐C, and HDL‐C with ovarian cancer risk.n = 27,394; 808 cases) showed no association between circulating levels of total cholesterol, LDL‐C, and HDL‐C with risk of ovarian cancer (assessed by quartiles).Only two studies evaluated the relationship between circulating cholesterol levels and ovarian cancer.There were no Mendelian randomization studies for ovarian cancer located in the literature.4The aim of our study was to summarize the association between serum cholesterol levels and incidence of hormonally driven cancers, with a focus on epidemiological studies with designs supporting the highest level of causal evidence. We identified 41 longitudinal or Mendelian randomization studies reporting on the association between circulating cholesterol levels and risk of prostate, breast, endometrial, or ovarian cancers. These results provide evidence for a complex association between cholesterol and different types of incident hormonally driven reproductive cancers. Even among the same types of cancer and serum cholesterol measures, often studies reported conflicting results and overall failed to convey evidence of an effect of plasma lipids.p‐value was non‐significant after adjusting for multiple comparisons.Thus far, the evidence reviewed does not support an association between serum cholesterol variables  and incident ovarian cancer. Additionally, there were no observed associations between endometrial cancer and serum cholesterol variables among the longitudinal studies. However, the single Mendelian randomization study examining this relationship found that higher genetically predicted levels of HDL‐C and lower genetically predicted levels of LDL‐C were associated with incident endometrial cancer. The association with HDL‐C is likely spurious as the confidence interval for the comparison with HDL included 1 [estimate 1.07 (1.00–1.14)] and the Similarly, the evidence reviewed does not support an association between cholesterol and prostate cancer. Most of the longitudinal studies and all the Mendelian randomization studies assessing the relationship between cholesterol and prostate cancer found no association. In the few studies reporting an association, the direction is inconsistent. Two publications reported an association between higher levels of total cholesterol and an increased risk of prostate cancerFinally, the association between cholesterol levels and breast cancer requires further research. Interestingly, our summary of longitudinal studies indicates a potential effect of lower HDL levels and increased breast cancer risk in some subgroups . To examine these relationships often requires a large sample size and statistical evaluation of the interaction. These variables were not handled consistently across these studies. For example, menopausal status is often treated as a confounding variableThe limitations of this study include the inability to account for potential differences in risk factors related to cholesterol across geographic and ethnic populations. The data were not pooled for meta‐analysis due to the wide variety of populations, study designs, and serum cholesterol parameters included in the studies. Studies in this review were not formally assessed with a quality tool, but common weaknesses across included studies are insufficient sampling, short follow‐up time, and potential misclassification, such as pre‐clinical bias. In cases of pre‐clinical bias, undiagnosed cancer may already be affecting serum cholesterol as the cancer may utilize cholesterol for cell replication and therefore result in decreased serum levels. This could result in a mistaken association between low serum cholesterol and cancer diagnosis. The strengths of this analysis include the robustness of the review of studies and selection of those with the strongest epidemiologic study designs.In summary, these results show no clear signal between serum cholesterol  and incident, hormonally driven cancer. The apparent lack of a role for cholesterol in the risk of developing the hormonally driven cancers in the studies included in this review may be related to confounders, modifiers, or the design of such studies (limitations discussed above) that prevent clear patterns of association from emerging. While serum cholesterol levels do not necessarily reflect the status of intracellular cholesterol trafficking, these cells are reliant on circulating cholesterol for cancer development and growth. This need may be particularly elevated for malignant and fast‐growing tumors and for steroid hormone‐dependent cancers.Thus, additional research into the role of cellular cholesterol is warranted. In addition, we would suggest conducting a rigorous life course epidemiologic study examining both the genetic and longitudinal association between serum lipids  and cancer risk. Such a study would help to elucidate biological and behavioral processes that operate in combination across an individual's life that influence cancer risk, accounting for multiple confounders such as diet, exercise, and use of lipid‐lowering therapy.Dana J. Murdock: Conceptualization ; formal analysis ; methodology ; writing – original draft ; writing – review and editing . Robert Sanchez: Conceptualization ; formal analysis ; methodology ; writing – original draft ; writing – review and editing . Kusha A Mohammadi: Conceptualization ; formal analysis ; methodology ; writing – review and editing . Sergio Fazio: Conceptualization ; formal analysis ; methodology ; writing – review and editing . Gregory P. Geba: Conceptualization ; formal analysis ; methodology ; writing – review and editing .This analysis was funded by Regeneron Pharmaceuticals, Inc.All authors are employees of and stockholders in Regeneron Pharmaceuticals, Inc.Appendix S1Click here for additional data file.


Short‐range functional connectivity in the limbic network is increased in patients with temporal lobe epilepsy (TLE), and recent studies have shown that cortical myelin content correlates with fMRI connectivity. We thus hypothesized that myelin may increase progressively in the epileptic network. We compared T1w/T2w gray matter myelin maps between TLE patients and age‐matched controls and assessed relationships between myelin and aging. While both TLE patients and healthy controls exhibited increased T1w/T2w intensity with age, we found no evidence for significant group‐level aberrations in overall myelin content or myelin changes through time in TLE. The dynamic relationship between brain structure and function is a critical problem to unravel in epilepsy, where structural and functional aberrations can have clinical consequences. Specifically in temporal lobe epilepsy (TLE) patients, the epileptic network has been linked to increases in short‐range functional connectivity.Most investigations to date using noninvasive myelin mapping techniques have focused on cortical myelin.Epilepsy may be a progressive disease,In this study, we analyze T1w/T2w structural MR images to investigate potential changes in myelination in TLE patients. We predict that epileptic activity will result in new myelin formation in the seizure focus and in more distant recruited areas. We also investigate how age relates to myelin changes and compare this relationship in TLE patients and healthy controls, hypothesizing increases in myelin content over time in affected regions.The study sample included 88 participants  from the Epilepsy Connectome Project (ECP). Due to a significant discrepancy in mean age between these groups, we also included 13 controls from the Alzheimer's Disease Connectome Project (ADCP), for a total of 101 subjects. The ECP and ADCP are both collaborations between the Medical College of Wisconsin (MCW) and University of Wisconsin‐Madison (UW). Each study was approved by the respective institutional review boards, and all subjects provided written informed consent. Participant demographics can be found in Table Selection criteria included an estimated IQ of at least 70, fluency in English, and age from 18 to 60 years (ECP) or 55 to 90 years (ADCP). Patients participating in the ECP all had a diagnosis of TLE based on clinical, radiographic, and EEG criteria as described in previous papers.T1w and T2w structural images were obtained using 3T GE  750 MRI scanners at UW and MCW. T1w scans used a magnetization prepared gradient echo (MPRAGE) sequence , and T2w scans used a 3D fast spin‐echo (CUBE) sequence .T1‐ and T2‐weighted images were preprocessed using standard Human Connectome Project (HCP) pipelines and Statistical Parametric Mapping 12 (SPM).We restricted our analyses to cortical and subcortical gray matter using a gray matter mask generated by segmenting each subject's T1w/T2w map into images containing only gray matter. The average of all subjects' gray matter T1w/T2w maps was then subjected to a threshold of 0.2 to form a mask which was applied to all statistical images. This arbitrary threshold resulted in the removal of most white matter and cerebrospinal fluid from T1w/T2w images, but also prevented variations in cortical folding and uncertain gray/white matter boundaries from eliminating voxels which represented gray matter in most, but not all, subjects.t‐tests. We also used one‐sample t‐tests to examine the significance of each group's relationship between T1w/T2w intensity and age.We performed statistical analyses in SPM with a general linear model (GLM) design that included both group membership and age/group interaction as factors. Comparisons of T1w/T2w intensity between patient and control groups used two‐sample (Welch's) unequal variance p < 0.001, after which we applied a significance threshold of FWER‐corrected p < 0.05. After determining clusters of statistical significance in any test, MNI coordinates of maximally significant results in each cluster were converted into Talairach coordinates using the mni2tal MATLAB function,All reported statistics are corrected for multiple comparisons at the cluster level using the family‐wise error rate (FWER). Reported cluster statistics use a primary cluster‐forming threshold of Mean myelin maps in both TLE patient and control groups were broadly in line with findings from Ganzetti et al.,p = 0.002) and the left and right putamen (both p < 0.001). In controls, a large significant cluster covered the right orbitofrontal cortex, left putamen, and right parahippocampal gyrus, with each of these local maxima significant at the voxel‐level (p ≤ 0.001). However, we found no significant difference in the rate of this age effect between groups. Furthermore, there was no significant relationship between seizure burden and T1w/T2w intensity.Both patients and controls show a significant positive relationship between T1w/T2w intensity and age, with effects present primarily in bilateral basal ganglia (Fig. F‐test at voxels of maximal significance for the age relationship in patients. These tests revealed no significant group differences in variance, and box plots of the adjusted data at these voxels did not demonstrate any propensity for outliers in either group (Fig. To address concerns that a different cluster extent in the group relationships between age and T1w/T2w may be caused by a greater propensity for outliers in the epilepsy group, we performed a post hoc variance The controls and patients in this study both show increased T1w/T2w intensity with age, consistent with literature that suggests new myelin formation continues well into adulthood.Recent literature supports a hypothesis of increased functional connectivity in the epileptic network.As no noninvasive myelin imaging technique correlates perfectly with myelin content as determined by histology,Furthermore, the volumetric image registration methods used in this study may provide suboptimal alignment of cortical tissues.Additionally, our hypothesis targets the epileptic network, which manifests in different locations even among patients whose epilepsy is confined to the temporal lobe. While a group‐level analysis between TLE patients and healthy controls allows for greater statistical power to uncover myelin aberrations common to most patients, such an analysis may not offer the sensitivity required to capture aberrations unique to each individual. Thus, highly localized changes to myelination patterns in the epileptic network remain a possibility. Further, in Bernhardt et al.,This work finds no evidence for significant aberrations in myelin formation in TLE patients. These findings do not rule out the possibility of structural correlates to functional connectivity changes in TLE; however, they do suggest that gray matter T1w/T2w intensity values may not efficiently capture any such structural changes if they exist. Future studies using quantitative T1 myelin mapping may be useful to further examine network‐level changes in myelin content.CD, VAN, JM, AN, RMB, LC, CH, EG, MR, EAD, JRB, BH, VP, MEM, MB, AFS contributed to the conception and design of this project. CD, KD, VAN, JM, DNA, AL, AN, LC, CH, MR, EAD, JRB, BH, VP, BBB, MB, AFS contributed to acquisition, analysis, and interpretation of data. CD, LC, JRB, BH, VP, MP, AFS contributed to drafting and revising it critically for important intellectual content. All authors gave their final approval of the version to be published and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.


The amygdala is a key region in current neurocircuitry models of reactive aggression as it is crucially involved in detecting social threat and provocation. An increased amygdala reactivity to angry faces has been reported in aggression-prone individuals and the neuropeptide oxytocin (OT) could dampen anger-related amygdala reactivity in a number of mental disorders. One example is the antisocial personality disorder (ASPD) which has so far only been studied in limited numbers. To address the question whether OT can normalize amygdala hyperreactivity to emotional faces, we conducted a functional magnetic resonance imaging experiment with 20 men and 18 women with ASPD and 20 male and 20 female healthy control (HC) participants in a double-blind, randomized, placebo (PLC)-controlled within-subject design. Participants were exposed to an emotion classification task  after receiving an intranasal dose (24 IU) of synthetic OT or PLC. We found OT to attenuate right amygdala hyperactivity to angry faces in participants with ASPD to such an extent that the intensity of amygdala activity in the ASPD group in the OT condition decreased to the level of amygdala activity in the PLC condition in the HC group. There was also a trend that OT effects were generally larger in women than in men. These findings suggest that OT differentially modulates the amygdala following social threatening or provoking cues in dependence of psychopathology (ASPD vs. HC) and sex . Particularly female ASPD patients could benefit from OT in the treatment of reactive aggression. Reactive aggression is often defined as response to perceived social threat, provocation, frustration, or rejection . Unlike One neuromodulator of the amygdala is oxytocin (OT)  which reWhile reactive aggression can be present in a number of mental disorders, it is central to the antisocial personality disorder (ASPD) . CurrentThe present study examined the effect of a single dose of intranasal OT on amygdala reactivity to emotional facial expressions in men and women with ASPD in comparison to healthy men and women in a double-blind, randomized, placebo-controlled within-subject design. We used blood oxygenation level-dependent (BOLD) fMRI coupled with an emotional face classification task which has been established in the investigation of amygdala activation  and its Participants were 20 men and 18 women with ASPD and 20 male and 20 female healthy control (HC) participants aged 18–30 years . ASPD participants had to fulfil the DSM-IV, respectively DSM-5, criteria for ASPD ) and were recruited at the Department of General Psychiatry at the University Hospital of Heidelberg, through local probation services, and through institutions offering anti-aggression trainings. HC participants were age- and IQ-matched and recruited through advertisement .Exclusion criteria for all participants were an intelligence quotient (IQ) lower than 80, insufficient German language skills, pregnancy, breast feeding, claustrophobia, any current medication , past cranio-cerebral injuries, and somatic, endocrine, or neurological diseases. Additional exclusion criteria for ASPD participants were autism spectrum disorder, lifetime diagnoses of schizophrenia or bipolar disorder, and current alcohol or drug dependence. Additional exclusion criteria for HC participants were any lifetime or current mental disorder or personality disorder and any psychological/psychiatric treatment assessed by the Structured Clinical Interview for DSM-IV (SCID-I) and antisocial behavior assessed by the International Personality Disorder Examination (IPDE). Four subtests of the Wechsler Adult Intelligence Scale were used to estimate intelligence . Other cThe study was approved by the local ethics committee of the Faculty of Medicine, Heidelberg University, and conducted in accordance with the Declaration of Helsinki. All participants gave written informed consent and were financially remunerated for their participation.The study was conducted with a randomized, double-blind, placebo-controlled within-subject design. After an extensive telephone screening, participants took part at an initial diagnostic assessment . They were then invited to two experimental assessments, scheduled four weeks apart, at which they underwent functional magnetic resonance imaging (fMRI). The order of the drug administration was randomized by an independent pharmacist providing a computerized simple randomization list. Participants were instructed to abstain from nicotine, food, and drinks except water for 2 h before the experiment. Upon arrival, urine drug tests had to be negative except from tetrahydrocannabinol (THC) due to its dissemination in the general population and particularly in participants with ASPD   sequence for blood-oxygen-level-dependent (BOLD) functional images using an amygdala-sensitive sequence . Images were preprocessed and analyzed using SPM8 . Final analysis used a region-of-interest (ROI) approach. Anatomically-defined masks for the amygdala were created using the Talaraich atlas in the WFU PickAtlas tool . Parametp < 0.05. Relationships between amygdala activation and behavioural/psychological/hormonal variables were then assessed using correlation analyses.Statistical analysis was performed using SPSS 25.0. The effects of OT on task performance and amygdala activation were assessed using repeated measured analyses of covariance (ANCOVAs) with the between-subject factors group  and sex , and within-subject factors condition , emotion , initial fixation , and hemisphere . We used Huynh-Feldt correction in case of violations of the assumption of sphericity. For significant results, post-hoc tests were performed by Dunn’s multiple comparison procedure including Bonferroni correction for multiple testing. All statistical analyses were performed two-tailed with a level of significance of To examine whether individuals with ASPD and healthy controls differ in proportion of correct responses, response latencies, and amygdala activation in response to facial emotion expressions, we run group by emotion by initial fixation ANOVAs for the placebo (PLC) condition . To answer our first research question, we will report effects including the factor group. To keep the results clear, we do not report non-significant effects of the other factors.F = 3.75, p = 0.057, η² = 0.051). Descriptively, individuals with ASPD were worse than healthy controls at classifying happy and fearful faces, while performances between groups did not differ for angry faces  = 2.36, p = 0.098, η² = 0.033). Furthermore, there was a significant group by fixation interaction  = 4.03, p = 0.049, η² = 0.028). Post-hoc tests showed that the ASPD group was better at classifying emotions when the eye region was initially fixated (p < 0.050). In comparison, there was no difference in the proportion of correct responses in dependence of the initial fixation of facial region in the HC group (p > 0.050). HC were more precise than individuals with ASPD when the initial fixation was on the mouth (p < 0.010) and the eye region (p < 0.050). The group by emotion by fixation interaction was not significant  = 1.09, p = 0.339, η² = 0.015).Individuals with APSD tended to make more errors than healthy controls in the emotion classification task  = 0.23, p = 0.631, η² = 0.003). There was a significant group by emotion interaction  = 5.58, p = 0.005, η² = 0.005) . More interestingly, individuals with ASPD responded faster to angry faces than HC (p < 0.010). Neither the effect of group by fixation  = 1.69, p = 0.198, η² = 0.024) nor the group by emotion by fixation interactions  = 1.99, p = 0.144, η² = 0.028) were statistically significant.Overall, there was no significant group effect on response latencies (05) Fig. . Post-hoF = 3.46, p = 0.034, η² = 0.045). Post-hoc tests revealed significant differences in the right amygdala when the mouth region was initially fixated: Individuals with ASPD showed stronger right amygdala activations for angry vs. fearful faces (p < 0.010), but no significant differences between angry and happy or fearful and happy faces . In the HC group, happy faces resulted in stronger right amygdala activation than fearful and angry faces , while there was no difference between fearful and angry faces (p > 0.050). When the mouth region was initially fixated, group comparisons showed stronger right amygdala activation for individuals with ASPD vs. HC for angry faces (p < 0.010), but no significant differences for fearful or happy faces . Neither the main effect of group  = 0.21, p = 0.648, η² = 0.003) nor the interactions of group by emotion  = 0.79, p = 0.455, η² = 0.011), group by fixation  = 0.73, p = 0.787, η² = 0.021), and group by emotion by fixation  = 0.44, p = 0.644, η² = 0.006) were statistically significant. Furthermore, we found a statistically not significant trend for the group by fixation by hemisphere interaction  = 3.61, p = 0.062, η² = 0.047). Descriptively, the right amygdala activation for emotional faces was higher in the HC group than in the ASPD group when the eyes region was initially fixated.We found a significant group by emotion by fixation by hemisphere interaction . To answer our second research question, we will report whether the factor condition interacted with the significant and trend-level findings in the placebo (PLC) condition.F = 1.13, p = 0.292, η² = 0.016) nor the group by condition by emotion interaction  = 1.23, p = 0.295, η² = 0.017) nor the interaction effect of group by condition by fixation  = 0.48, p = 0.490, η² = 0.007) reached statistical significance. Since the proportion of correct responses was generally high , we cannot dismiss a ceiling effect.Neither the group by condition  = 0.51, p = 0.578, η² = 0.007)  Fig. .F = 1.69, p = 0.189, η² = 0.023). However, we found the threefold interaction effect of group by condition by emotion by hemisphere to be significant  = 4.27, p = 0.016, η² = 0.055) . Under OT, the ASPD group had a lower activation than the HC group at presentation of fearful, angry, and happy faces . This group differences could be accounted by a lower right amygdala activation for angry and happy faces in the ASPD group under OT compared to PLC and a higher right amygdala activation for fearful faces in the HC group under OT compared to PLC . Essentially, the group difference in right amygdala activation for angry faces could be reversed under OT: The ASPD group under OT showed a similarly low right amygdala activation like the HC group under PLC (p > 0.050) and the HC group under OT showed a similarly high right amygdala activation like the ASPD group under PLC (p > 0.050). Further, the post-hoc tests showed no group differences in the left amygdala activation under PLC. Under OT, the ASPD group had a lower left amygdala activation in response to fearful and happy faces than the HC group . This effect was driven by the ASPD group with lower left amygdala activation in response to happy faces under OT compared to PLC (p < 0.010) and the HC group with higher left amygdala activation in response to any facial emotion under OT compared to PLC . There were no group differences under OT when angry faces were shown (p > 0.050).The interaction effect of group by condition by hemisphere by emotion by fixation was not significant (55) Fig. . In postIn order to explore the sex-specific effect of OT on group differences, we calculated the additional sex-, group-, and condition-related interaction effects. We will only report significant and trend-level significant results.We did not find significant or trend-level interaction effects of sex.F = 2.48, p = 0.087, η² = 0.033)  and happy  faces were lower under OT than under PLC in the female ASPD group and activation for fearful  and angry  faces were higher under OT than under PLC in the female HC group.We found a statistically not significant trend for the interaction effect of group by sex by condition by emotion by hemisphere (33) Fig.  and 1.2Br = −0.506, p < 0.050) and right  amygdala activation in women with ASPD in the PLC but not in OT condition    has been proposed to be beneficial to several psychiatric disorders characterized by social dysfunction by modulating the amygdala during facial emotion recognition . As we hConsistent with our earlier findings obtained with an overlapping sample , we obseUnder PLC, we found a stronger right amygdala activation in ASPD vs. HC participants for angry faces when the mouth region was initially presented. This is in line with the executive emotion model, in which increased amygdala responsiveness to threat cues  might lead to reactive aggression . Here, tAfter OT administration, we found a decreased right amygdala activity for angry and happy faces in the ASPD group and an increased right amygdala activity for fearful faces in the HC group. Most interesting was the effect of OT on amygdala activation to angry faces: The activation pattern of ASPD and HC were opposite in the OT condition compared to the PLC condition. This group difference in OT effect is in line with the social salience hypothesis  which stThere is evidence of hormonal cycle-related OT effects on emotion recognition accuracy in healthy young females . FurtherAlthough ASPD is prevalent in males and females, most studies have exclusively focused on males . Little One strength of this study is the largest ASPD sample in the fMRI literature . We inclEven though the sample size is comparably large, it is limited since we explored up to six-way interactions. Still, we found group effects on amygdala activation which speaks for a validity of our results. Furthermore, we did not have a clinical control group. A significant proportion of the ASPD sample met criteria for psychopathy. However, we decided to be cautious with correlation analyses due to the small sample  and the fact that the SRP score has not been a target variable. Yet, the differences between ASPD and psychopathy in emotion classification tasks are not well understood, calling for further studies with larger sample sizes. Second, due to lack of compliance of individuals with ASPD, we resigned from controlling the phase of the menstrual cycle though research indicates that amygdala function in females differs between different phases of their menstrual cycle . We manaIn conclusion, data from this study showed that OT has a specific effect on anger-related amygdala activity in ASPD. OT was found to dampen amygdala activity in response to angry faces that are highly salient for individuals with ASPD and high trait anger especially in ASPD women compared to ASPD men. These findings suggest that attenuating the salience of cues perceived as threatening or provoking, is promising in the treatment of reactive aggression in ASPD patients, particularly when they are females.Supplemental Material 1Supplemental Material 2


These results provide novel clues as to how DMN may contribute to executive task performance. Specifically, the improved task performance, unique activity, and increased miFC associated with increased sequential predictability suggest that the DMN may coordinate more strongly with the MDC to generate a temporal schema of upcoming task events, which may attenuate switching costs.Switching is a difficult cognitive process characterised by costs in task performance; specifically, slowed responses and reduced accuracy. It is associated with the recruitment of a large coalition of task‐positive regions including those referred to as the multiple demand cortex (MDC). The neural correlates of switching not only include the MDC, but occasionally the default mode network (DMN), a characteristically task‐negative network. To unpick the role of the DMN during switching we collected fMRI data from 24 participants playing a switching paradigm that perturbed predictability  across three switch dimensions—sequential, perceptual, and spatial predictability. We computed the activity maps unique to switch vs. stay trials and all switch dimensions, then evaluated functional connectivity under these switch conditions by computing the pairwise mutual information functional connectivity (miFC) between regional timeseries. Switch trials exhibited an expected cost in reaction time while sequential predictability produced a significant benefit to task accuracy. Our results showed that switch trials recruited a broader activity map than stay trials, including regions of the DMN, the MDC, and task‐positive networks such as visual, somatomotor, dorsal, salience/ventral attention networks. More sequentially predictable trials recruited increased activity in the somatomotor and salience/ventral attention networks. Notably, changes in sequential and perceptual predictability, but not spatial predictability, had significant effects on miFC. Increases in perceptual predictability related to decreased miFC between control, visual, somatomotor, and DMN regions, whereas increases in sequential predictability  Increasing sequential predictability switching contributes to improved task performance, increased brain activity, and elevates functional connectivity between multiple demand cortex (MDC) and default mode network (DMN) regions. DMN and MDC coordination may reflect a working memory strategy whereby a temporal schema of upcoming switches is generated to attenuate switch costs. For example, switches may be driven exogenously or organised endogenously, or a person may switch between stimulus and response rules, current goals within the same overarching task, or between different tasks altogether . The effects of switching on task performance are among the most established cognitive phenomena, being characterised by post‐switch costs in both reaction time (RT) and accuracy Monsell, . While tCompared to MDC, the role of the default mode network (DMN) is less well understood. The DMN has historically been associated with processes that primarily occur during resting state, such as autobiographical recall and episodic memory  sequential predictability, when within the sequence of event the switches occur, (2) spatial predictability, where the focus of attention will switch to next, and (3) perceptual predictability, what visual category the focus of attention will switch to next. We modulated the predictability of each dimension in a fully factorial design to evaluate whether predictability level influenced behavioural performance, network activity, and connectivity. By varying predictability, we manipulated cognitive load by enabling or disabling the construction of a mental schema of the task structure . More sequentially, spatially, and perceptually predictable trials allow participants to construct a representation of when upcoming task switches will occur, where the new task will be located, and the visual characteristics of the next trial, respectively. This would enable participants to anticipate aspects of a task switch, prepare cognitive resources accordingly, and reduce switch costs . Participants reported no history of neurological or psychiatric conditions and had normal or corrected vision. The Hammersmith and Queen Charlotte's Research Ethics committee approved the studies, which conform with the Declaration of Helsinki. All participants gave their written consent after being informed about the nature of the study.2.2The switching task was programmed in MATLAB using Psychophysics Toolbox extension  preceded the appearance of a new target image.2.3The parameters of the cognitive paradigm were modified within the predictability along three dimensions: sequential, spatial, and perceptual predictability of switch events. These dimensions were limited to a number (three) that allowed the experiment space to be sampled in a single session, and the three dimensions were selected based on previous work showing modulations in sequential , spatially the relevant stimuli could switch one position upwards or downwards (maintaining the frequency of direction a maximum of two switches) and perceptually the category of the stimuli was randomly chosen (ensuring it did not follow the predictable sequence and it was distinct from the preceding rule).The size of the experiment space allowed for a full‐factorial experiment to be conducted, where every possible combination of dimensions was sampled Figure . For exa2.4The participants performed three back‐to‐back fMRI runs. Within each run, the participants performed eight blocks of 30 trials of the switching task, with 16 s of rest in between. Each block corresponded to one of the previously defined combinations of sequential, perceptual, and spatial predictability, thus, over the entire session the fully factorial design ensured each participant performed 90 trials of every combination of the three switch dimensions. The order of block presentation was randomised across runs and participants. Participants were trained in the task by performing one practice block outside the scanner. In the scanner, the task was projected onto a screen that the participants could see through mirrors placed on the head coil and the responses were recorded using a pair of MRI compatible response grips . Participants used the index finger on their right or left hand to select whether the target image was more similar to the right or left flanker of interest, respectively.2.53, repetition time (TR) of 2300 ms, echo time (TE) of 2.98 ms, inversion time of 900 ms, flip angle (FA) of 90°, field of view of 256 × 256 mm, 256 × 256 mm matrix, 160 slices and GRAPPA acceleration factor of 2. For the fMRI images, a T2*‐weighted echo‐planar imaging (EPI) sequence was acquired using an isotropic voxel of 3 mm3, TR of 2 s, a TE of 30 ms, FA of 80°, field of view of 192 × 192 × 105 mm, 64 × 64 matrix, 35 slices, and GRAPPA acceleration factor of 2.MRI data were acquired in a 3 T Siemens Verio  at the Imperial College London Central Imaging Facility using a 32‐channel head coil. Standard T1‐weighted structural images were acquired using an MP‐RAGE sequence, isotropic voxel of 1 mm2.6The fMRI Expert Analysis Tool  from the FMRIB's Software Library (FSL)  were constructed with regressors corresponding to task blocks  and switch trials  for each of the conditions tested (the eight combinations of dimensions). Thus, 16 regressors of interest were fitted into each subject‐level GLM. The task regressors were modelled by convolving a double‐gamma haemodynamic response function (HRF) with a boxcar kernel.Movement‐related noise was accounted for by adding 24 motion regressors  to the design matrix. Additional regressors of no interest were added to the GLM as nuisance regressors and used for censoring of motion outliers (as estimated through the fsl_motion_outliers tool using DVARS with a threshold of 50%).z > 3.1 and cluster‐correction significance threshold of p < .05) was applied to threshold the final Z statistical images.The following contrasts of interest were generated: all task blocks (“Task > Rest”) and all switch events (“Switch > Rest”). A second‐level analysis using a fixed effects model was performed to estimate each subject's mean response across the three runs. This was done by forcing the random effects variance to zero in FMRIB's Local Analysis of Mixed Effects (FLAME) .A second‐level analysis using a fixed effects model was performed to estimate each subject's mean response across the three runs. This was done by forcing the random effects variance to zero in FLAME  using a three‐dimensional watershed algorithm from the Function and Structural Integration of Neuroimages (Fusion‐WS) toolbox  in another variable  is canonically defined asp(x), p(y), and p are probabilistic density functions  as p^x in the following manner:Mutual information for continuous variables δ. is a Gaussian kernel density window function, xi is the ith sample, and h is the window width, which scales with x. It is necessary that h scales with x, as one of the conditions for generating a density estimation is that the probability of the occurrence of x out of the total population equals 1—thus, as the size of x increases, so too must h . When d = 2, as is our case, δ. Equation , p, which is also the joint density of x and y. After computing the joint probability distribution using Equation (x and y in Equation (A Gaussian kernel density means that 2.7.5n = 22). The reliability of all regions across participants per run was moderate   to evaluate the reliability in miFC per region within and across participants. In line with Koo and Li , we comp2.7.6We evaluated the effect of switch dimensions on miFC by first computing the average miFC among all ROIs in the 100‐parcel, 17‐network Schaefer atlas  to assess whether there was an effect of switch dimensions on miFC. Results were FDR‐corrected for the number of comparisons in miFC. Directions of effects were computed using Wilcoxon sign‐rank tests of miFC between the two difficulty levels per dimension.We then investigated how the significant changes in pairwise miFC were distributed across functional networks. We grouped regions according to the functional network in which they reside and defined each network as a node. Nodes were connected by edges if the miFC between the nodes had a significant change in miFC due to sequential or perceptual predictability. For example, the precuneus and inferior parietal lobule are both a part of the DMN network/node, and a significant change in miFC between the inferior parietal lobule and the precuneus or motor cortex would count as a within‐ or between‐network change in connectivity, or edge. Edges were not counted twice, for example, a significant change in miFC between the inferior parietal lobule and precuneus would only be counted once. We also computed the total number of edges that emanated from each node, referred to as the node's degree. Edges were weighted by the number of regions within each network showing increases in miFC. For example, if two regions from the control network have significantly increased miFC to two regions within the DMN, the edge weight between the control network and DMN would be 2.2.8p < .05  = 151, p = 3.4e‐22) where switch trials showed longer RT than stay trials  = 0.85, p = .55) or an interactive effect of block and trial  = 0.41, p = .90) on RT. There was no significant effect of sequential  = 1.3, p = .25), perceptual  = 0.15, p = .69), or spatial  = 0.32, p = .57) predictability on RT, nor were there any interactive effects of sequential  = 0.52, p = .47), spatial  = 0.35, p = .55), or perceptual predictability  = 0.18, p = .67), and trial type on RT.There was a significant, main effect of trial type on RT  = 32, p = 5.7e‐223, D = 0.34). There was not a significant main effect of block  = 1.8, p = .07) or trial type  = 0.89, p = .34) or an interactive effect between block and trial type  = 0.78, p = .61) on accuracy  = 4.6, p = .03) on accuracy, with higher accuracy during more sequentially predictable trials. There were no significant effects of spatial  = 0.49, p = .48) or perceptual predictability  = 0.49, p = .48), and no interactive effects of sequential  = 1.8, p = .18), spatial  = 2.2, p = .14), or perceptual predictability  = 0.10, p = .78) and trial type on accuracy.Participants performed the task well, and accuracy was significantly above chance  Figure  Supplem. The somIn addition, there was a generalised increase in cross‐network degree Figure .Shifting focus from a network‐level perspective towards a regional focus, we note that the majority (63%) of sequential predictability‐related changes in miFC in DMN regions are within the parahippocampal cortex (PHC). The PHC showed increased miFC to MDC regions including the anterior insula, iPS, and dlPFC. Another DMN region, the ventral PFC, also showed increased miFC to a region within the MDC, the pre‐SMA. Thus, miFC between regions within the MDC and DMN showed a positive relationship with sequential predictability.Between‐network changes in miFC due to perceptual predictability were less pronounced, but involved decreases in miFC between the MDC and DMN when perceptual predictability increased Figure  Supplem. The larIn summary, sequential and perceptual predictability differentially influenced connectivity, where increases in sequential predictability recruited connectivity between somatomotor, control, DMN, and other networks, whereas increases in perceptual predictability reduced connections among the same networks.4Here, we report results of a novel fMRI switching task where imaging results showed concurrent activation of the DMN and MDC during switch trials as compared to stay trials. This concomitant activation inverts the stereotypical association of task difficulty with MDC and DMN network activity . Because some networks are composed of a greater number of regions, it is possible that this may skew the likelihood of the involvement of this network. However, we show that the two networks with greatest changes in degree , are not the two largest networks . This indicates that the functional role of networks (and the regions that compose them), rather than the number of times they are represented, drives their involvement during sequentially predictable switches.A final limitation of our study could be the simple experimental design that makes inferences to real‐world situations challenging. However, the simple design allowed disentangling the effects of different task dimensions, and it is a necessary first step to better understand the role of the networks during switching. A straightforward next step is to test whether our results hold in a naturalistic switching task  where real‐world relevance could be more directly inferred . It would also be informative to extend the current paradigm to one where there is a deeper structure to the task schema that is learnt progressively, in order to study the shifting role of MDC and DMN regions across the learning curve. Such a task was employed by Daws et al. , which cIn summary, our results further extend the known roles of the MDC and DMN, and collectively indicate a more active role for regions included in the DMN during task performance than was commonly believed.D.L.K. received funding from the University of Surrey. R.L. received funding from the EPSRC (P70597) and the Wellcome Trust (209139/Z/17/Z). I.R.V. received funding from the BBSRC (Ref: BB/S008314/1). A.H. is supported by the Dementia Research Institute and the Imperial NIHR Biomedical Research Centre. The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.DATA S1 Supporting Information.Click here for additional data file.


Mean platelet volume (MPV), as a marker of platelet activity, has been shown to be an efficient prognostic biomarker in several types of cancer. Using MPV, this study aimed to create and validate a prognostic nomogram to the overall survival in esophageal squamous cell carcinoma (ESCC) patients.The nomogram was constructed and tested using data from a retrospective study of 1893 patients who were randomly assigned to the training and testing cohorts with a 7:3 randomization. In order to screen out the optimal predictors for overall survival (OS), we conducted the LASSO‐cox regression, univariate, and multivariate cox regression analyses. Subsequently, the predictive accuracy of the nomogram was validated in both the training and the testing cohorts. Finally, decision curve analysis (DCA) was used to confirm clinical validity.Age, MPV, nerve invasion, T stage, and N stage were found as independent prognostic variables for OS and were further developed into a nomogram. The nomogram's prediction accuracy for 1‐, 3‐, and 5‐year OS was 0.736, 0.749, 0.774, and 0.724, 0.719, 0.704 in the training and testing cohorts, respectively. Furthermore, DCA results indicated that nomograms outperformed the AJCC 8th and conventional T, N staging systems in both the training and testing cohorts.The nomogram, in conjunction with MPV and standard clinicopathological markers, could improve the accuracy of prediction of OS in ESCC patients. High epithelial CTC level (n ≥ 2) at the end of neoadjuvant chemoradiation therapy significantly associated with non‐pathological complete response (p = 0.032), shorter PFS (p = 3.0 × 10–6), and OS (p = 0.019) for locally advanced ESCC.The 5‐year survival rate for esophageal cancer was only 15.3% in the 2000s.Platelets are widely established to have a crucial role in cancer progression, metastasis, and angiogenesis in a variety of ways.Furthermore, platelets educate tumor cells, which then efficiently transfer lipids, proteins, and RNA.In the context of this research, we hoped to create and test a novel prognostic nomogram that incorporates MPV analysis and clinical parameters to predict prognosis and support doctors in providing appropriate treatment for ESCC patients.22.1This study included patients from Sichuan Cancer Hospital from January 2012 to December 2016. The patients were examined and chosen retrospectively using the following eligibility criteria: (1) They had pathologically proven ESCC with the resected material; (2) they did not receive any preoperative radiotherapy, chemotherapy, chemoradiotherapy, or other treatment; (3) they had presurgery hematologic detection data and clinical information. Meanwhile, we established the exclusion criteria: (1) patients had a history of cancer or any other major chronic disease; (2) the tumor penetrated the neck. With the 7:3 randomization, patients included in the trial were randomly divided into training and testing cohorts. Furthermore, we use multi‐factor stratification to increase the generalization property of both the training and testing cohorts. All of these patients were pathologically staged using the 8th edition TNM classification system of the American Joint Committee on Cancer (AJCC). This study was approved by the ethics committee of Sichuan Cancer Hospital.2.29/L), MPV (FL), PDW (%), PCT (%), PT (s), INR, APTT (s), FIB (g/L), TT (s), DD (μg/mL), and FDPs (μg/mL)) were included. The clinical laboratory department of Sichuan Cancer Hospital was used to obtain the reference values for laboratory parameters.Clinical data for the included patients were obtained from the electronic medical record system of Sichuan cancer hospital. Demographic information (age and gender), clinical data , and preoperative laboratory results (PLT (102.3All patients had surgery. Patients who have one or more of the following indications for postoperative adjuvant therapy: (1) Patients with R1 or R2 resections who did not receive prior radiation. (2) Adenocarcinoma patients without preoperative radiation who had positive R0 resected lymph nodes or negative pT2‐4a lymph nodes. (3) Postoperative adjuvant can be recommended for patients with squamous carcinoma who have positive R0 resected lymph nodes or negative pT2‐4a lymph nodes and have not undergone preoperative irradiation. Radiotherapy was provided using the intensity‐modulated radiation therapy technique. Telephone calls, clinical visits, outpatient records, or messages were used to acquire regular follow‐up data. The key outcomes were 1‐, 3‐, and 5‐year overall survival (OS). OS was measured from the date of surgery to the date of death or the final follow‐up.2.4p < 0.05 in multivariable cox regression. To get access to clinical use, the time receiver operating characteristic (ROC) curve, calibration curve, and decision curve analyses (DCA) were used.To begin, the least absolute shrinkage and selection operator (LASSO) regression was utilized to discover the OS predictive variables, and 15 predictors conforming to the minimum lambda. Second, a univariate and multivariable cox regression analysis with 15 predictors was done to estimate the hazard ratio (HR) and 95% confidence interval of OS. Finally, the nomogram was constructed with five predictors  with 2.5t‐test was used to compare two groups of continuous variables with normal distribution. The Mann–Whitney test was performed to compare variables that did not have a normal distribution. The Bonferroni method was used to correct multiple tests. The Kaplan–Meier method was used to calculate OS probabilities. To evaluate the relationship between clinical variables and OS, cox proportional hazard models were utilized, with extra adjustments for possible confounders. In the univariate analysis, variables with a p < 0.05 were used to do multivariable cox regression. The optimal cut‐point for MPV was determined by using “maxstat” package. C index and Brier test values were calculated in training and test cohorts. All statistical analyses were carried out with R software 4.1.3, and a p‐value (two‐sided) of <0.05 was considered to indicate statistical significance.For categorical variables, the features were expressed as number (%) and for continuous variables, median (interquartile range [IQR]). The Chi‐squared test was used to compare categorical variables. The 33.1p > 0.05). Average follow‐up was 31.487 months.The characteristics of 1327 ESCC patients in the training cohort and 566 patients in the testing cohort are described in Table 3.2LASSO‐logistic regression was used to pick out the best predictors of OS from the 24 parameters provided in Table p < 0.05, Table p < 0.05, Table As shown in Figure 3.3Calibration curves were applied to validate the nomogram's ability to predict 1‐, 3‐, and 5‐year OS. For survival rates, calibration curves showed higher agreement between nomogram prediction and actual observations. The training cohort Figure  and testIn addition, the predicted accuracy was evaluated with time‐dependent receiver operating characteristic (time‐ROC). Figure 3.4Finally, DCA was used to validate the nomogram's clinical validity. The nomogram's prediction power was compared to the AJCC 8th stage, T, N stage scheme. The advantage of the MPV nomogram outperformed the AJCC 8th, T, and N stages in both the training and testing cohorts Figure .4As is widely documented, the initial tumor site, treatment, smoking status, histology, older age, TNM stage, and vascular invasion all have a significant impact on the OS of ECSS patients.p = 0.035).p < 0.05).In clinical practice, MPV is commonly referred to the mean size of platelets. Many studies on new perspectives for MPV in inflammation and carcinoma have been conducted over the last few decades. MPV has been identified as a useful prognostic biomarker in cancer and cardiovascular disorders.α contribute to platelet increase in ESCC.The underlying mechanisms and signaling have not been thoroughly studied. In a previous study, Shen et al.MPV, which had never been studied in ESCC patient nomograms, was combined with age, nerve invasion, T and N stage in our study to create an effective survival prognosis nomogram. The accuracy and efficacy of OS prediction for ESCC were evaluated with ROC. The AUC of the nomograms was more than 0.7 in both the training and the testing cohorts. Furthermore, when compared to the T, N staging system, the nomogram proposed in the study was found to be more accurate and superior. Despite the benefits, there are some drawbacks that should not be overlooked. First, because this was a retrospective study, the nomogram was only tested in one study center. As a result, a multicenter confirmation is required to confirm its efficacy. Second, because our study's endpoint was OS, the prediction value for progression‐free survival or disease‐free survival was not included. In addition to tumors, platelets are influenced by infection, medication, and other variables. These shortcomings serve as an invitation for future research in this area.5This is the first time to construct and evaluate an ESCC prognostic nomogram in conjunction with MPV and standard clinicopathological markers. The finding of this study indicated the proposed nomogram accurately predicted the OS for ESCC.Qiao He: Writing – original draft . zhenglian luo: Writing – original draft . Haiming Zou: Conceptualization ; data curation . bo ye: Data curation ; investigation . lichun wu: Investigation ; methodology . Yao Deng: Investigation ; methodology . Mu Yang: Conceptualization ; project administration . Dongsheng Wang: Conceptualization ; funding acquisition ; supervision . qifeng wang: Conceptualization . kaijiong Zhang: Conceptualization ; methodology ; project administration ; validation .The authors state that there are no conflicts of financial interest or otherwise regarding the publication of this article.The study was approved by the ethics committee of the Institutional Ethics Committee of Sichuan Cancer Hospital (SCCHEC‐02‐2020‐015) and carried out in accordance with relevant guidelines and regulations. All patients included in this study signed informed consent statements.Figure S1.Click here for additional data file.


Serum neurofilament light (sNfL) is a promising marker of outcome after cardiac arrest, but its kinetics are unclear. We prospectively measured sNfL concentrations in 62 patients at 0, 1, 3, 5, 7 and 10 days after cardiac arrest. Survivors and non‐survivors had similar sNfL at admission (14.2 [8.6–21.9] vs. 22.5 [14.2–46.9] pg/mL) but largely different at 24 h . The AUC for sNfL concentrations predicting death was above 0.95 from Day 1 to 10 (highest on Day 3). Late sNfL measurements may exert prognostic value, especially when early samples are unavailable or prognosis remains unclear. Prognosis of post‐anoxic encephalopathy after cardiac arrest (CA) currently integrates clinical findings, somatosensory evoked potentials, electroencephalogram (EEG), neuroimaging and serum neuron‐specific enolase (NSE) concentration.We prospectively recruited all consecutive patients with post‐anoxic encephalopathy due to CA admitted to Cardiocentro Ticino Institute  between September 2020 and August 2022. Inclusion criteria were (1) age above 18 years; (2) evidence of CA by ventricular tachycardia, ventricular fibrillation, pulseless electrical activity or asystole; (3) informed consents from patients or legal representatives. Exclusion criteria were (1) known underlying neurodegenerative disease, (2) pregnancy, (3) CA due to trauma and (4) concomitant acute stroke.normal/good cerebral performance; 2 = disabled but independent; 3 = conscious but disabled and dependent; 4 = unconscious, coma or vegetative state; 5 = death) at hospital discharge and at 6 months after CA. Information on outcomes at 6 months were retrieved by phone interviews.Serum samples were collected at time of admission and at 1, 3, 5, 7 and 10 days after CA. sNfL concentrations were measured in duplicate with the NF‐light assay  as previously described.Variables were described by median and interquartile range (IQR) or counts and percentage, as appropriate. Multivariable mixed‐effect models with individuals as random effect were used to simultaneously test variables for association with log‐transformed sNfL concentrations measured at all time points. Regression coefficients were back‐transformed to the original scale to allow easier interpretation of coefficients. Predicting power and sNfL cut‐offs for mortality and survival were investigated using receiver operating characteristic (ROC). ROC analyses were performed first using all available samples collected in the study, and then using only those samples collected from patients who had not regained full consciousness . Thirty‐three patients (53.2%) were alive at 6 months (24 with CPC 1 and 9 with CPC 2). Twenty‐eight (45.2%) patients died before hospital discharge, and one 4 months after discharge because of an additional cardiovascular event. Life‐sustaining therapies were withdrawn in 18 individuals . Fifty‐one (82.2%) had ≥2, 45 (72.6%) had ≥3, 41 (66.1%) had ≥4, 34 (54.8%) had ≥5 and 19 (30.6%) had 6 samples collected . Main demographic and clinical characteristics are shown in Table A total of 62 CA patients  were included in the study. Acute coronary syndromes (ACS) were the most frequent cause of CA , while significant at 24 h , day of sampling since CA  and CPC at hospital discharge , those with highly malignant patterns β = 8.22, 95% CI = 3.48–18.72, P < 0.001, Fig. Using mixed effect models, sNfL concentrations were positively associated with age  for sNfL was above 0.95 from Day 1 to 10, and the highest on Day 3  at 6 months after CA with 100% sensitivity. As all individuals who were alive at 6 months after CA had CPC 1–2, sNfL cut‐offs with 100% sensitivity for CPC 1–2 mirrored those with 100% specificity for mortality at 6 months Table .We describe longitudinal sNfL variation in post‐anoxic encephalopathy up to 10 days after CA. Higher sNfL levels were associated with age, suggesting that age‐related brain susceptibility to the anoxic insult can contribute to neuronal death. Although EEG were only performed in a minority of patients, we confirmed that malignant EEG patterns reflect the extent of brain injury as measured by sNfL.While sNfL levels were comparable in survivors and non‐survivors at admission, non‐survivors showed up to 1000‐fold sNfL increase at 24 h, reaching higher concentrations than those observed in other conditions affecting the central nervous system (including most neurodegenerative diseases).Accordingly, the predictive power of sNfL was greater within 24–72 h, but later measurements also showed AUC above 0.90. We provide approximate time‐specific sNfL cut‐offs with 100% specificity for mortality and survival. As an example, in this cohort, sNfL concentrations approximately above 400 pg/mL on Day 3 after CA were specific predictors of death . Our cut‐offs were relatively lower compared to those provided by Moseby‐Knappe et al.,As sNfL concentrations are positively associated with age, it has been suggested to use age‐corrected thresholds (e.g. percentiles or Z scores) to define normal and pathological sNfL values.Strengths of the study are represented by the standardized and prospective collection of samples at specific time points from consecutively admitted CA patients, including very early (admission) and late (10 days) samples, that are not available in most of the studies performed to date. The main limitation is the relatively small sample size of the cohort, which suggests caution in the application of prognostic sNfL cut‐offs. In particular, when the analysis was restricted to patients who had not regained full consciousness and were still in the ICU, the sample size became too small to make our cut‐offs clinically applicable. The relatively high proportion of patients with shockable rhythms may also limit generalizability of findings. Prognostication assessments  were performed when deemed indicated based on the clinical situation , without strictly following Nolan et al guidelines.To conclude, we provide new information regarding longitudinal kinetics of sNfL in post‐anoxic encephalopathy patients up to 10 days after the anoxic insult, that can be used as a guide when planning future studies. Based on these data, we suggest that sNfL measurements performed >72 h after CA could also be of value, especially when early samples/NSE are unavailable or prognosis remains unclear. We provide approximate time‐specific cut‐offs with 100% specificity for death and survival, to be integrated and replicated in future studies of larger sample size.Giulio Disanto reports no conflicts of interest. Michele Villa reports no conflicts of interest. Aleksandra Maleska Maceski reports no conflicts of interest. Chiara Prosperetti reports no conflicts of interest. Claudio Gobbi reports that the employer , Lugano, Switzerland) receives financial support from Teva, Merck Serono, Biogen Idec, Bayer Schering, Genzyme, Roche and Novartis. The submitted work is not related to these agreements. Jens Kuhle served on scientific advisory boards for Novartis Pharmaceuticals, Merck, Biogen, Sanofi Genzyme, Roche and Bayer; has received funding for travel and/or speaker honoraria from Biogen, Sanofi Genzyme, Novartis, Merck Serono, Roche, Teva and the Swiss MS Society; and research support from Bayer, Biogen, Merck, Sanofi Genzyma, Novartis, Roche, ECTRIMS Research Fellowship Programme, University of Basel, Swiss MS Society, Swiss National Research Foundation (320030_160221). Tiziano Cassina reports no conflicts of interest. Pamela Agazzi reports no conflicts of interest.Giulio Disanto: conception and design of the study; acquisition and analysis of data; drafting a significant portion of the manuscript. Michele Villa: acquisition and analysis of data. Aleksandra Maleska Maceski: acquisition and analysis of data. Chiara Prosperetti; conception and design of the study; drafting a significant portion of the manuscript. Claudio Gobbi: conception and design of the study. Jens Kuhle: acquisition and analysis of data; drafting a significant portion of the manuscript. Tiziano Cassina: conception and design of the study; acquisition and analysis of data; drafting a significant portion of the manuscript. Pamela Agazzi: conception and design of the study; acquisition and analysis of data; drafting a significant portion of the manuscript.Figure S1. Increasing sNfL concentrations from admission to up to 10 days after cardiac arrest, stratified by cerebral performance category (CPC) at 6 months after cardiac arrest.Table S1. Multivariable mixed‐effects regression testing the association between variables of interest with log‐transformed sNfL (predicted variable). Regression coefficients are back‐transformed to the original scale . ROSC, return of spontaneous circulation; SOFA, Sequential Organ Failure Assessment.Table S2. Multivariable mixed‐effect regression testing the association between EEG pattern  and longitudinal sNfL (predicted variable). Regression coefficients are back‐transformed to the original scale.Figure S2. Increasing sNfL concentrations from admission to up to 10 days after cardiac arrest stratified by survival at hospital discharge, using only samples collected from patients who were not fully conscious and still in the ICU at time of sampling. By doing this, we excluded from the analysis 5 individuals since admission, 6 since day 1, 12 since day 3, 2 since day 5, 3 since day 7 and 3 since day 10.Table S3. Time specific area under the curve (AUC) with 95% confidence intervals (CI) for sNfL predicting outcome at 6 months after cardiac arrest, with sNfL cutoffs with 100% specificity for death and survival (and corresponding sensitivities). The upper part of the table shows results using all available collected samples. The lower part of the table shows results using only samples collected from patients who were not fully conscious and still in the ICU.Table S4. Time specific area under the curve (AUC) with 95% confidence intervals (CI) for sNfL predicting CPC 1–2 at 6 months after cardiac arrest, with sNfL cutoffs with 100% sensitivity and corresponding specificities.Click here for additional data file.


Gastric cancer (GC) ranks fourth among the causes of death from malignant tumors in the world. Studies have implicated the dysregulation of circRNAs with GC. However, the relationship between hsa‐circ‐0052001 and GC is unclear.In our current study, we assessed the expression levels of hsa‐circ‐0052001 in GC cells and tissues using quantitative real‐time PCR (qPCR). The role of hsa‐circ‐0052001 expression on the proliferation and invasion of GC cells was assessed using in vitro experiments. The role of hsa‐circ‐0052001 on the proliferation of GC cells was also analyzed using in vivo models. The pathways downstream of hsa‐circ‐0052001 were identified using bioinformatics analyses, western blot (WB) assays, and qRT‐PCR.We found that compared with normal gastric mucosa epithelial cells and adjacent paracancer tissues, hsa‐circ‐0052001 was overexpressed in GC cells and tissues. Also, the hsa‐circ‐0052001 level was linked to patient clinicopathological characteristics of GC. Cell proliferation and metastatic ability were inhibited in gastric cancer cells when hsa‐circ‐0052001 was knocked down in vitro and cancer growth in vivo. Mechanistically, hsa‐circ‐0052001 promoted the carcinogenesis of GC cells via the MAPK signal pathway.Hsa‐circ‐0052001 functions as a tumor gene in promoting the progression of GC through MAPK pathway, which has provided a promising target for patients with GC. This study provides important insights into the expression of hsa‐circ‐0052001 in patients with gastric cancer and its influence on the prognosis of patients. The data showed that hsa‐circ‐0052001 expression was increased in patients with gastric cancer and suggested a poor prognosis. East Asia has the highest GC incidence, particularly in men in Japan and women in Mongolia, with Northern America and Northern Europe reporting some of the lowest GC incidences.CircRNAs perform numerous functions, including sponging with miRNA, protein binding (RBPs), and regulating protein translation.In our research, we demonstrated that hsa‐circ‐0052001 promoted the tumorigenesis of GC. The expression of hsa‐circ‐0052001 is overexpressed in GC tissues. Mechanistically, hsa‐circ‐0052001 promotes the proliferation and metastasis of GC cells via the MAPK pathway. Thus, hsa‐circ‐0052001 and the MAPK pathway are a potential target for the diagnosis and treatment of GC patients.22.1Surgical excision of GC patients without preoperative chemoradiotherapy at The First Affiliated Hospital of Soochow University acquired 102 GC tissues and adjacent noncancerous specimens between 2015 and 2017. Following surgical resection, all samples were collected and placed into liquid nitrogen until RNA extraction. Two pathologists independently verified all clinicopathological diagnoses. The First Affiliated Hospital of Soochow University Ethics Committee authorized the trial, and each patient gave written informed permission before the operation (IRB number: 2021112).2.2https://www.ncbi.nlm.nih.gov/geo/), comprising data for 6 GC and 6 paracancer tissues. Differently expressed genes (DEGs) between GC and paracancer tissues were identified from an online database (https://www.ncbi.nlm.nih.gov/geo/geo2r/) based on |logFC| > 1 and adj. p‐value < 0.05. The Benjamini and Hochberg false discovery rate (FDR) approach was utilized to explain the emergence of FDR via the modified P‐values. MiRNAs that might directly bind to circRNAs were predicted using data in the CircBank database (https://www.circbank.cn). The gene targets for the predicted miRNAs were identified in the TargetScan database. The cumulative weight context++ score < −0.6 were set as the cutoff. The function of the circRNAs and downstream target genes was investigated further using Gene Ontology (GO)CircRNAs expression profile (GSE83521) was downloaded from the NCBI GEO database  and normal gastric mucosal epithelial cell line (GES‐1) were provided by the Culture Collection of the Chinese Academy of Sciences . At 37°C under 5% CO2, AGS, MKN‐45, and SGC7901 cells were cultivated in RPMI 1640 medium (Hyclone), whereas GES‐1 cell was cultivated in DMEM medium (Hyclone) added containing 10% FBS  and a mixture of 1% penicillin/kyowamycin .2.4−ΔΔCT method was utilized. The primers utilized herein are presented in Additional file 1: Table Following the manufacturer's instructions, RNA was extracted from GC cells and tissues via TRIZOL reagent . Substantial, Nano Drop 2000  was used to identify the concentration and purity of the RNA. For circular RNA and mRNA, reverse transcription was conducted with random hexamers using HiScriptIIQ Select RT Super Mix for qPCR (+gDNA wiper) . For miRNA, cDNA was synthesized from the miRNA 1st Strand  using the Stem‐loop primer. TB Green Premix Ex Taq II  was used to amplify cDNA using an ABI Prism 7500 . Internal controls for circRNA and mRNA were GAPDH, and all samples were run three times in total. The expression of genes was calculated using the 22.5TM 2000  was utilized to realize the transfection of the oligonucleotides and plasmids into cells following the manufacturer's protocol. The oligonucleotide sequences are shown in Table GC cells were planted and cultured until 80% confluence in 6‐well plates before transfection. GenePharma  developed and manufactured si‐circ‐0052001, miR‐608 inhibitor, and their representative negative control oligonucleotides. Lipofectamine2.6We seeded the transfected AGS and MKN45 cells in a 96‐well dish at 3000 cells per well. After 24, 48, 72, and 96 h of incubation, 10 μl of CCK‐8 liquor  were added to the wells. The absorbance of the wells at 450 nm was measured with a full‐wavelength marker after 2 h of incubation at 37°C.2.7The treated GC cells were seeded in 6‐well dishes and cultured under 37°C for 2 weeks with 500 cells in each well. We fixed the cells in 4% PFA and stained the cells in gentian violet  for 30 min, followed by two washes in PBS. After that, a count and evaluation of colonies were conducted.2.8We planted the transfected GC cells in a 6‐well plate. A scratch was made from the top to the center at the bottom of the well. Cells were washed twice in PBS and cultivated in the RPMI 1640 medium without serum under 37°C for 24 h. After that, at 0 h and 24 h, image collection and migration distance measurement were performed.The Transwell chamber was put in a 24‐well plate for transwell analysis. The treated MKN45 and AGS cells in the medium without serum were seeded into the upper layer, and 700 μl of complete medium were supplemented into the lower layer. Posterior to the 24h cultivation, cells passing through the film were fixed in 4% PFA and stained in gentian violet for 15 min. Count the number of invasive GC cells, then repeat the experiment three times.2.9In order to identify the concentration of proteins in GC cells expressing si‐circ‐0052001, RIPA buffer  was prepared and the protein content was identified using the BCA method . Protein extracted from GC cells was separated on SDS‐PAGE and transferred onto PVDF membranes. Non‐specific binding sites were blocked from PVDF membranes using 5% skimmed milk under ambient temperature for 1.5 h. The cultivation with the first antibody was completed overnight under 4°C. Subsequently, cultivation with the second antibody was completed at room temperature for 1 h. The protein band images were captured using Odyssey and analyzed using the ImageJ software. Additional file 1: Table 2.106 of si‐circ cells, whereas than in the control group received an injection of si‐NC MKN45 cells into the left or right dorsal flanks.The Animal Ethics Committee at Soochow University approved animal care and experiments . Male SPF BALB/c nude mice for tumor heterograft assays were obtained from Shanghai SLRC Lab Animal Company. The mice were about 4–5 weeks old and weighed 15–16 g. The experiment started after 3 days of acclimatization. On the day of the experiment, the mice were randomly divided into the hsa‐circ‐0052001 knockdown or control groups, each containing six mice. Mice in the treatment group received 5 × 102.11t test. The connection among hsa‐circ‐0052001 expressing level and clinicopathologic characteristics were investigated via the Chi‐square test. In contrast among the other two groups of data, an independently completed sample t test was used. p < 0.05 was considered statistically significant.SPSS 23.0 software , GraphPad Prism 7, and R programs were employed to analyze the data. Continuous normally distributed data were expressed as mean and SD. The expressing level of hsa‐circ‐0052001 in GC and adjacent noncancerous specimens were contrasted via a paired 33.1The GSE83521 dataset in the GEO database contains data for circRNAs in GC tissues. We found 40 circRNAs highly expressed in GC tissues and 12 underexpressed circRNAs Figure . Hsa‐cir3.2To further confirm the overexpression of hsa‐circ‐0052001 in GC tissues, we assessed the expression of this circRNA in 102 GC specimens. The results confirmed that hsa‐circ‐0052001 expression was considerably high in GC tissues than in normal adjacent noncancerous tissues, consistent with bioinformatic analysis findings Figure . Further3.3Our preliminary study demonstrated that hsa‐circ‐0052001 is overexpressed in GC tissues than in normal gastric epithelium tissues. Further in vitro studies were performed in AGS and MKN45 cells Figure . The rol3.4We found when hsa‐circ‐0052001 was knocked down, miR‐608 expressing level was relatively upregulated in GC cells Figure . As a re3.5Previous research have demonstrated that miR‐608 can activate the MAPK pathway in ameloblastoma.3.6The mouse GC model was established to further assess the impact of hsa‐circ‐0052001 on the GC growth in vivo. MKN45 cells, which were transfected with si‐NC or si‐circ‐0052001, were injected subcutaneously into each mice. Compared with mice in the NC group, inhibiting hsa‐circ‐0052001 expression had no significant effects on the bodyweight of the mice Figure , but rem4The most common malignant tumor of the digestive tract is Gastric Cancer. Due to difficulty in early GC diagnosis, the prognosis of gastric cancer patients is usually poor. The molecular mechanism underlying the development and progression of gastric cancer is still unclear. To improve the OS of GC patients, there is a need to develop accurate markers for early‐stage GC diagnosis. CircRNAs have emerged as hot spots for cancer research, thanks to the recent advances in RNA sequencing technology and bioinformatics analysis.In our research, bioinformatics analysis first revealed that hsa‐circ‐0052001 is overexpressed in GC cells and tissues. Further analyses revealed that hsa‐circ‐0052001 was linked to tumor size, T grade, lymphonodus invasion, TNM phase, vascular invasion, and GC prognosis. Studies show that hsa‐circ‐0052001 promotes the proliferative and invasion of GC cells in vitro by binding to hsa‐miR‐608 and could activate the MAPK pathway. Accordingly, hsa‐circ‐0052001 is a potential target for GC diagnosis, treatment, and prognosis prediction.CircRNAs regulate cancer progression by acting as ceRNAs.In the present study, bioinformatics analysis revealed that hsa‐circ‐0052001 may be related to gastric cancer and the MAPK pathway. Western blot was used to analyze key proteins related to tumor proliferation and invasion in the MAPK signaling pathway. The results showed the suppression of hsa‐circ‐0052001 downregulated p‐ERK, p‐P38, and p‐JNK, while there was no significant change in ERK, P38, and JNK, further confirming that hsa‐circ‐0052001 could promote the proliferative and invasion of GC cells via the MAPK pathway. MAPK pathway is a key signaling pathway involved in diverse cancers and other human diseases.As far as we know, this is the first report on the expression, role, relationship with clinical features, and the mechanism underlying the effect of hsa‐circ‐0052001 on GC cells. Generally, we found that hsa‐circ‐0052001 is highly expressed in gastric cancer tissues, and its expression is related to the prognosis of gastric cancer patients. This indicates that hsa‐circ‐0052001 is a potential marker for the treatment, diagnosis, and prognosis prediction of GC. Regarding limitations, our preliminary study first shows that hsa‐circ‐0052001 expression is upregulated in GC cells and tissues. However, whether it is also overexpressed in the blood is unknown. Second, our research demonstrated that hsa‐circ‐0052001 could activate the MAPK pathway, but the specific mechanism is still unclear, and needs further investigation. Third, in addition to binding to miR‐608, other hsa‐circ‐0052001 target miRNAs which may impact the progression and developmental process of GC are unknown. Therefore, other aspects of hsa‐circ‐0052001 in relation to GC need further investigation.5Summarily, this study revealed that hsa‐circ‐0052001 is highly expressed in gastric cancer tissues and is closely related to the prognosis of gastric cancer. Hsa‐circ‐0052001 promotes GC development and progression by binding to the miR‐608. Moreover, our data revealed that hsa‐circ‐0052001 could promote the MAPK pathway and promote the growth of GC cells in vivo. Thus, hsa‐circ‐0052001 is not only a prognostic marker for gastric cancer patients but also a diagnostic and prognosis prediction for GC.Qixuan Xu: Data curation ; methodology ; software ; writing – original draft . Yizhou Yao: Methodology ; software . Haishun Ni: Methodology . Jinrong Gu: Project administration ; resources . Xuchao Wang: Formal analysis . Linhua Jiang: Resources ; validation . Bin Wang: Software ; visualization . Xinguo Zhu: Conceptualization ; supervision ; writing – review and editing .There are no conflicts of interest according to the authors.The First Affiliated Hospital of Soochow University's Ethics Review Committee authorized the study . The animal study followed the First Affiliated Hospital of Soochow University's Guidelines for Animal Care and Use.Table S1.Table S2.Table S3.Click here for additional data file.Figure S1.Click here for additional data file.


Enterococcus faecalis compared to calcium hydroxide in primary root canals.Successful endodontic therapy is based on the reduction of infecting bacteria by cleaning, shaping, and disinfecting of the root canal system, thus the use of intracanal dressing is necessary for optimal success of root canal treatment. This study was designed to evaluate the effect of chitosan and propolis as intracanal medicaments against E. faecalis. Then, tested materials were applied for all groups in accordance to the groups each tooth belonged to. Following this, the bacterial colonies were counted after 24 h, 72 h, and 1 week of applying dressing materials and incubation. Finally, one–way analysis of variance and Fisher's least significant difference tests were used for statistical comparisons between the groups at a significance level of .05.Ninety‐six extracted primary second molars were collected. Teeth preparation was completed to size 30 K‐file. They were randomly divided into four groups; (A): chitosan, (B): propolis, (C): calcium hydroxide, and (D): control group . The tooth specimens were inoculated with p ≥ .05). Yet, a statistical difference between groups A, B, C, and D after 72 h and 1 week were seen (p ≤ .05).No statistically significant difference was found between groups A, B, and C for both 24 h and a week (E. faecalis in primary root canal treatment and might be considered as an alternative dressing material between treatment sessions.Chitosan and propolis medicaments were as effective as calcium hydroxide against  Afterward, the solution was filtered with (Whatman paper)  .E. faecalis was cultured on Petri dishes with a nutrient medium (Mueller–Hinton agar) at 37°C for 24 h in a 5% CO2 incubator. Then, a bacterial suspension was formed and adjusted to (4.5 × 108) colony‐forming units per mL (No. 1.5 McFarland Standard) using a BD PhoenixSpec™ nephelometer (BD Company). In the following stage, 50 μl of bacterial suspension (4.5 × 108 [CFU/mL]) was applied into the prepared root canals using a sterile micropipette .Then, samples were divided randomly into four groups to apply one of the tested materials. Randomization was performed using an online service (n = 24): 2% chitosan was applied using a sterile syringe with disposable plastic needles to inject the dressing into the root canal, then lentulo spirals at low speed had been used.Group (A) CH (n = 24): 10% ethanol propolis extract dressing was applied using a sterile syringe with disposable plastic needles and lentulo spirals at low speed to inject the dressing into the canal.Group (B) EEP (2 (n = 24): calcium hydroxide (Produits Dentaires SA) dressing was applied after mixing with sterile saline solution in a volume ratio (1:1) using lentulo spirals at low speed.Group (C) Ca (OH)n = 24): without applying any dressing in root canals.Group (D) negative control group . Finally, specimens were incubated at 37°C/CO2.51.N = 32): 24 h (2.N = 32): 72 h (3.N = 32): 7 Days  (IBM). A After using Kolmogorove–Smirnov test to determine if the data were molded by a normal distribution, the test showed that data after 24 h and 72 h are distributed normally. Therefore, to study the differences between experimental groups one way analysis of variance test was utilized at 0.05 significant level. While the data after 7 days are not distributed normally. Therefore, Kruskal–Wallis test was used to determine if there was a statistically significant difference between groups.Subsequently, Fisher's least significant difference test was carried out to emphasize the differences between binary groups.Wilcoxon test was carried out to study the significant bilateral differences in the mean bacterial colony units between the two stages before and after  of applying the dressing.3The descriptive statistics of the mean, standard deviation, and percentages of the decimal logarithm (log 10) of bacterial counts after disinfection procedures is shown in Figures p > .05) . Chitosan, propolis, and calcium hydroxide exhibited similar antibacterial effect after 24 h  and 1 week  respectively, without any statistically significant differences between them (p > .05). On the contrary, the antibacterial effect of propolis was higher than Chitosan (2.777 ± 0.86 log10 CFU/ml) with a statistically significant difference (p < .05). While, there is no statistically significant difference (p > .05) between the efficacy of chitosan, propolis, and calcium hydroxide after 1 week of application  and calcium hydroxide (2.543 ± 0.31 log10 CFU/ml) demonstrated similar antibacterial effects with no statistically significant difference (p < .05) in comparison to the bacterial counts before applying the dressing in all studied periods  for each studied dressing is shown in Figure 4E. faecalis are the most prevalent bacteria  and during the three time periods studied.The results of this study showed reduction of bacterial count after applying the dressings compared to the bacterial count before with a statistically significant difference, in studied groups The antibacterial ability of chitosan was higher than propolis and calcium hydroxide after 24 h of applying the dressing with no statistically significant difference; yet, with statistically significant difference compared to the negative control group.The mechanism of antibacterial action of chitosan is attributed to the interaction between positively charged chitosan molecules and negatively charged bacteria cell membranes; in addition to that, leakage of intracellular components , which leads to bacterial growth inhibition , and phenol components. These active components of propolis will prevent cell division that will in turn inhibit the growth of bacteria Lotfy, . In addiE. faecalis strains after 72 h, 1 week, and 1 month of applying. These results are in accordance with those obtained in this study, although the concentration of propolis used by Ahangari et al. (8 CFU/ml) was lower than the one determined in this study.Ahangari et al.  showed ti et al.  was 30%,E. faecalis  that are lower than that used in this study.In an in vitro study carried out by Sabarathinam and Muralidharan  showed tlidharan  study waAntibacterial ability of calcium hydroxide was higher than chitosan and propolis after 1 week of applying the dressings with no statistically significant difference.Long‐term application of calcium hydroxide has bactericidal properties, as it can lead to damaging bacterial cytoplasmic membranes that in turn lead to cell death , yet the results of both studies were similar, which can lead to conclude that the effect of calcium hydroxide is higher in comparison to chitosan, even when the concentration of the last one was increased here  was obtained for conducting the study by the ethical review board of the faculty of dentistry and Damascus University, Syria.