The lack of organ donors has become a limiting factor for the development of organ transplantation programs. Many countries are currently facing a severe shortage of organs for transplantation. Medical students, as future doctors can engage in the role of promoting organ donation by creating awareness and motivating the community to donate their organs besides their voluntary organ donation. The aim of this study is to assess the knowledge, attitude and willingness of undergraduate medical students’ towards organ donation at Jimma University.A cross-sectional study was conducted among 320 medical students from year I to internship using questionnaire in order to assess their knowledge, attitude and willingness regarding organ donation. Data collected was entered using epidata and analyzed using Statistical Package for Social Sciences (SPSS) software version 20.P = 0.014, Wilk’s Λ = .033. Variables which were related to a positive attitude towards organ donation were: being of the male sex (Odds Ratio = 1.156); having awareness about organ donation (Odds Ratio = 2.602); not having a belief on the importance of burying intact body (Odds Ratio = 5.434); willingness to donate blood (Odds Ratio = 4.813); and willingness to donate organ (Odds Ratio = 19.424).Mean (±SD = standard deviation) age of participants was 23.48 ± 17.025 years. 57.8% of the study subjects were male. There was a statistically significant interaction effect between gender and year of study on the combined knowledge questions (dependent variables) F = 1.755,High level of knowledge but low level of positive attitude and willingness was noticed among the study participants toward organ donation. The need for organ donation has increased globally in the past years due to an increase in organ failure . Every dThere are no sufficient facilities which provide maintenance and transplantation therapy for failed organs in Ethiopia. Currently there are only cornea and living related kidney transplant programs established in the nation’s capital Addis Ababa . FacilitOrgan transplantation is one of the great advances in modern medicine and is the best option for failed organ. Transplantation is defined as the transfer of human cells, tissues or organs from a donor to recipient with an aim of restoring normal physiology in the body . In EthiSome studies found out that the issue of organ donation is multifactorial. In developed countries relational ties, religious beliefs, cultural influences, family influences, body integrity, and previous interactions with the health-care system were reported as the potential factors for organ donation . HoweverAmong 100,000 of people died each year are believed to be potential donors; however, only less than 200 actually become donors . This inIn Ethiopia there are no data on public perception of organ donation and transplantation Therefore, the present study was designed to assess the knowledge, attitude and willingness of organ donation among medical students. Medical students, as future doctors can take up the role of promoting organ donation by educating and motivating the public to initiate them donate their organs besides their voluntary organ donation. Therefore, assessing medical student’s knowledge, attitude and willingness to donate organ is very important to decrease the shortage of organ in the future.A cross sectional study was carried out for 3 months from May to July 2019among under graduate medical students in Jimma University after obtaining Institutional Ethical Clearance from institutional review board (IRB) of Jimma University. The University is located in Jimma town which is 352 km from Addis Ababa, the capital city of Ethiopia. Jimma University is one of the most distinguished centers of excellence in medical education in the country.All medical students (from first to internship) registered in the year 2018/2019 were the source population. Based on their training background, medical students in Jimma University were divided into two groups: PRE-CLINICAL and CLINICAL. PRECLINICAL is subdivided in to two groups: Year I (PC-I) and Year II (PC-II) and CLINICAL in to three subgroups Year III(C-I), Year IV(C-II) and internship. The sample size was calculated by using simple proportion formula assuming a prevalence of 50% for knowledge, attitudes and willingness of organ donation, a 95% confidence interval and a sample error of 5%. This was adjusted for 10% non-response rate; bringing the total sample size to 320.There were about 1200 students studying in Jimma University medical school.The questionnaire was distributed to undergraduate medical students during lecture hours in the classroom and in ward during attachment. They were instructed not to discuss the questions among themselves. The importance of the study was explained and confidentiality regarding the participant response for the questions was ensured.A 20-item self-administered questionnaire was developed. The first part of the questionnaire gathered the demographic details from the students, which included age, gender, year of study and religion. The second, third and fourth sections assessed the levels of knowledge (Q1–7), attitude (Q8–16) and willingness (Q17–20) to donate organ, respectively.The students were grouped as those who do have adequate and inadequate knowledge based on their score.Adequate knowledge is when 4–6 questions were answered correctly and inadequate when less than 4 questions answered correctly out of 6 knowledge questions.Attitude was assessed by using 9 attitude statements and respondents were categorized as those who do have positive attitude and negative if they agree to 6–9 and less than 6 attitude statements respectively.Data was entered to EPI data and exported to SPSS version 20 for analysis. Descriptive statistics like percentage and mean and standard deviation were used to present socio-demography, knowledge, attitude and willingness response of the participants. Multivariate analysis was used in order to relate those factors that gave a significant result: One way Multivariate analysis of variance (MANOVA) was used to see a significant relationship between one independent variable and dependent variables and two ways MANOVA was considered to know if there was an interaction between two independent variables on the dependent variables. One way Analysis of Variance (ANOVA) was used for comparing means of variables to know among which groups were the differences. Finally, Odds ratio analysis was used to find out variables which were related to a positive attitude towards organ donation.Out of 320 participants 57.8% were male. Mean (±SD = standard deviation) age of participants was 23.48 ± 17.025 years. Majority of the participants were orthodox (49%.7) and the least percentage being others constituting wakeefeta, apostolic, humanity, atheist and Seventh Day Adventist (SDA) (2.8%) (Table 96.9% of the students had awareness about organ donation. Only 25% had knowledge that there was no age limit for organ donation (Table p = 0.001). Based on the post hoc test the significant difference was between PC-I and C-II(p = 0.001), PC-I and intern(p = 0.001), PC-II and C-I(P = 0.022) and PC-II and intern(p = 0.010). The mean for PC-I, PC-II, C-I, C-II and intern is 1.37, 1.27, 1.20, 1.08 and 1.05 respectively. Therefore, PC=I had significantly higher level of knowledge when compared to the rest year of study  =7.6, 15 =7.6, 74.1% of the participants agreed to support family members if they wish to become an organ donor. Majority of the study subjects (91.9%) felt that awareness about organ donation should be made a part of school education  times likely to have positive attitude towards to organ donation as compared to female. Students who had an awareness about organ donation were 2.602 (Odds Ratio = 2.602) times likely to have positive attitude towards to organ donation as compared to those who were unaware. The other variables which were related to a positive attitude towards organ donation were: not having a belief on the importance of burying intact body (Odds Ratio = 5.434); knowing definition of brain death (Odds Ratio = 1.257); not having a belief that there is a danger of misuse, abuse or misappropriation of donated organ (Odds Ratio = 2.777); willingness to donate blood (Odds Ratio = 4.813); and willingness to donate organ (Odds Ratio = 19.424).58.1% of the study participants were willing to donate their organs and allow organ donation after the death of a family member. Majority of the study subjects (88.4%) did not like to take money for organ donation. 90.3% of the study subjects were willing to donate blood and 58.1% were willing to donate their organ (Table There were an association between willingness and attitude. Willingness to donate organ was significantly higher among those who do have positive attitude (88.2%) as compared to those with negative attitude (11.8%) Table .Table 6p = .004). Based on the post hoc test the significant difference was between Protestant and Muslim (p = .007). The mean for protestant is 1.83 and Muslim 1.56.Therefore, Protestant had significantly higher belief on the importance of burying intact body when compared to Muslim  =4.5, m p = .00. The meaΛ = .96, F  = 2.247, P = 0.039, multivariate ƞ2 = 0.041 and attitude statements consider jointly Wilk’s Λ = .94, F  = 2.301, P = 0.016, multivariate ƞ2 = 0.063.There was a statistically significant difference between males and females when knowledge questions considered jointly Wilk’s Λ = .75, F  = 3.966, P < 0.001, multivariate ƞ2 = .071, attitude statements considered jointly Wilk’s Λ = .77, F  = .766, P < 0.001, multivariate ƞ2 = .065 and willingness questions considered jointly Wilk’s Λ = .93, F  = 2.072, P = 0.017, multivariate ƞ2 = .026.When year of study is considered, there was a statistically significant difference among year of studies when knowledge questions considered jointly Wilk’s P = 0.014, Wilk’s Λ = .033.Two way MANOVA was considered to know if there was an interaction between two independent variables on the dependent variables. There was a statistically significant interaction effect between gender and year of study on the combined knowledge questions (dependent variables) F  = 1.755, Organ failure and shortage of donated organs are global problem. Among 100,000 of people died each year are believed to be potential donors; however, only less than 200 actually become donors . The widIn our study 96.9% of the participants heard about organ donation which is similar to study done by Annadurai et al and Jothula et al. , 16 bothIn the present study the main sources of information about organ donation was found to be internet (61%) and television (50%).This was similar to study conducted in USA and Australia , 20. How206(64.4%) of our study participants had identified all the organs that can be donated. This finding was higher than the study done by Annadurai et al.  and Kari201(62.8%) of our study subjects have a positive attitude towards organ donation which is lower than the study in Spain and India which found 80 and 71.3% respectively , 24. 91.77(24.1%) of our study subjects belief that person’s body should be intact when buried A study in USA reported that 8% of participants strongly agree and 11.7% agree to this statement which is almost similar to our finding . In our In this study 186(58.1%) of the study participants were willing to donate their organ which is similar to a study done in USA  and loweThough most of the students had adequate knowledge, still gaps exist in their attitude and willingness. This implies the need for an intensified and sustained education to raise attitude and willingness of the students towards organ donation.Most of the students (91.9%) felt that awareness about organ donation should be made a part of school education; until it included in school curriculum, we recommend the students to acquire an adequate knowledge by themselves; In our study the most common source of information about organ donation was internet; so, they can browse more to acquire additional knowledge and make informed decision.


Stress) and recovery (PostStress) in 65 participants. Higher IVP‐induced cortisol responses were associated with lower pulse rate increases during stress recovery  and lower increases in negative affect after the task . While the cortisol response to IVP was not associated with subsequent specific stress‐induced neural activation patterns, the similarity of brain responses Pre‐ and PostStress was higher IVP‐cortisol responders  indicating faster recovery. In conclusion, preparatory stress induced by IVP reduced reactivity in a subsequent stress task by modulating the latency of stress recovery. Thus, an individually stronger preceding release of cortisol may attenuate a second physiological response and perceived stress suggesting that relative changes, not absolute levels are crucial for stress attribution. Our study highlights that considering the entire trajectory of stress induction during an experiment is important to develop reliable individual biomarkers.Acute and chronic stress are important factors in the development of mental disorders. Reliable measurement of stress reactivity is therefore pivotal. Critically, experimental induction of stress often involves multiple “hits” and it is an open question whether individual differences in responses to an earlier stressor lead to habituation, sensitization, or simple additive effects on following events. Here, we investigated the effect of the individual cortisol response to intravenous catheter placement (IVP) on subsequent neural, psychological, endocrine, and autonomous stress reactivity. We used an established psychosocial stress paradigm to measure the acute stress response ( Stress often involves multiple “hits” and it is an open question whether individual differences in responses to an earlier stressor lead to habituation, sensitization, or additive effects. Here, we show that a cortisol response to the placement of an intravenous catheter attenuated reactivity to a subsequent psychosocial stress task on the neural, endocrine, autonomous, and subjective level. All participants underwent a comprehensive, computer‐based, standardized diagnostic interview (CIDI) in which diagnoses are derived by an automatically evaluated, standardized, DSM‐IV‐based algorithm. We did not exclude participants that received a diagnosis and thus capture a sample of participants self‐identifying as healthy yet showing symptoms that would be considered subclinical or lead to a diagnosis in multiple cases. Briefly, 48% (n = 32) did not have any current or lifetime diagnosis, while 40% (n = 27) received at least one (lifetime) diagnosis belonging to the anxiety disorders spectrum including specific phobias, 19% (n = 13) a substance use‐related diagnosis and 7% (n = 5) a mood disorder  study at the Max Planck Institute of Psychiatry, registered on n = 2) samples from all analyses, and serum samples (n = 12) from analyses regarding serum cortisol responses to the stress task . Moreover, we excluded 12 participants from analyses regarding pulse rate as their signal quality was too low for reliable peak detection.To maximize the sample size, we excluded participants with missing or low‐quality data for each analysis separately. More specifically, we excluded participants because of missing cortisol saliva  kit . The standard range was 20–800 ng/ml. The %CV in serum samples was between 2.6 and 3.5% for intra‐assay variability and between 2.1 und 5% for inter‐assay variability.2.4.2n = 12). Subsequent analysis of the pulse rate was based on the derived RR‐intervals and conducted with the RHRV package , electrocardiography, and skin conductance. The PPG data was acquired with an MR compatible pulse oximeter  attached to the pulp of the left ring finger. PPG data, sampled at 5 kHz, was amplified using a MR compatible multi‐channel BrainVision ExG AUX Box coupled with a BrainVision ExG MR Amplifier  and recorded with BrainVision Recorder software 1.0. After down‐sampling to 100 Hz, RR‐intervals were detected using the Physionet Cardiovascular Signal toolbox  white matter and cerebrospinal fluid segments, performed PCA, and used the first five components of each segment as physiological noise covariates.MRI data were acquired on a GE 3Tesla scanner . The functional data were T2*‐weighted echo‐planar images (EPIs) consisting of 755 volumes for the stress task (details in the 2.52.5.1IVP = CortT2 − CortT1). Further, we classified participants into responders and non‐responders to the IVP based on a conservative cut‐off of ∆CortIVP > 2.5 nmol/L  values starting at the beginning of the stress task and ~60 min after IVP, a time‐interval frequently recommended to aid recovery of the cortisol system. Thus, we included serum cortisol measures from the time point T3 until T8, 30 min after the end of the task. Cortisol responses may be partly offset by declining cortisol concentrations over the day starting shortly after the morning cortisol peak. Therefore, we additionally calculated cortisol concentrations corrected for a linear circadian trend between T3 and T8 and used those values to subsequently derive a circadian corrected AUC (AUCStress = HRStress − HRPreStress). In the same way, the lasting effects of stress during the acute recovery (PostStress) phase were calculated as ∆HRPostStress = HRPostStress − HRPreStress.Autonomous stress effects elicited by the stress task were estimated as change in average pulse rate  during the arithmetic blocks in the Stress condition compared to the arithmetic blocks in the PreStress condition (∆HRSubjective stress effects elicited by the stress task were estimated as the change in positive and negative affect after the task (∆Pos/∆Neg = Positive/Negative affect (T6) − Positive/Negative affect (T3)). As in previous work  as predictor and sex, age, and presence of any lifetime psychiatric diagnosis (coded yes/no) as covariates.The effects of cortisol induced by IVP on autonomous, subjective or serum HPA responses to the subsequent stress task were assessed with multiple linear regression models including either the responder status to IVP or the cortisol increase  were built using individual onsets and durations of all task‐blocks extracted from the log files for each participant. The task was modeled with three regressors, each modeling the five arithmetic blocks (60 s) of the conditions PreStress, Stress and PostStress, respectively. In addition, we included two regressors modeling individual motor responses and verbal feedback during the Stress phase. Nuisance regressors were the six movement parameters derived from realignment, their derivatives, and five physiological noise components extracted from white matter and cerebrospinal fluid each. Data were high pass filtered with a cut‐off of 256 s. The contrasts of interest, IVP or responder status were included as predictor and sex, age, and lifetime psychiatric diagnosis (no/yes) as covariates. In addition to this cluster‐based approach, we again used aggregated betas within networks to compare neural stress responses in IVP‐responders and non‐responders. We depict t values  in Figure 3 to ease their comparison.To test the effects of IVP‐induced cortisol responses on the subsequent neural stress response to the psychosocial stressor, we performed whole‐brain voxel‐wise multiple regression analyses using the contrast images derived in the first‐level statistics. Either ∆CortHowever, this approach may mask individual variation in the direction or localization of stress effects. To capture individual neural stress effects independent of their directionality and localization, we calculated within‐participant similarity of the neural activity during PreStress compared to Stress and PostStress, respectively. To this end, we extracted mean beta estimates of the conditions  from 268 regions of interest (ROIs) spanning the whole brain using an established brain parcellation . Clusters were considered as significant with an FWE cluster‐corrected p value threshold of pcluster.FWE < .05.Statistical analyses were performed in R v3.5.1.  and PostStress  phase. Still, it recovered significantly  after stress  = −3.30, p = .0002) and negative affect increased (mean ∆Neg(T6) = 6.16, t(66) = 6.48, p < .0001) directly after the task  = −2.16, p = .034) 30 min later while negative affect had recovered to levels slightly below baseline (mean ∆Neg(T8) = −0.82, t(66) = −1.26, p = .21, Figure rs between 0.63 and 0.77, all ps < .0001) indicating that interindividual differences of the autonomous and subjective stress response also persist during the recovery period. The task elicited a significant serum cortisol response  when taking into account the approximated circadian cortisol decline for each individual. Eighteen participants would be classified as responders with a peak cortisol response higher than 55 nmol/L .First, we assessed if stress induction by the imaging stress task was successful. As expected, stress induction increased the pulse rate in the Stress , precuneus and lateral parietal (angular gyrus) and temporal cortex, dorsomedial prefrontal cortex, thalamus, and insula Figure . Consist3.2IVP = 0.93 ng/ml, SD ∆CortIVP = 2.29 ng/ml, t[64] = 3.27, p = .001, pboot < .001, Figure n = 23) of the participants reacted to IVP with a cortisol response larger than 2.5 nmol/L  = −0.18, p = .85; saliva: t(63) = −0.03, p = .98). Serum and salivary cortisol at baseline were highly correlated . Of note, cortisol responses to IVP were higher in participants for whom more than one attempt was needed until success . Responders to IVP did not differ from non‐responders with respect to various other demographic and psychopathological variables  was lower in IVP responders compared to non‐responders  lower in IVP responders  in IVP responders compared with non‐responders. In contrast, positive affect and pulse rate increases during stress were not significantly different in responders compared to non‐responders . In contrast, there were no differences in the affective state  directly before the task (T3). Comparable results were obtained when using the quantitative salivary cortisol response to IVP as a predictor , during stress (Stress–PreStress) or recovery (PostStress–PreStress) was not different in IVP responders compared to non‐responders, as whole‐brain voxel‐wise analysis revealed no significantly different clusters even without further correction for multiple comparisons. Moreover, additional network‐level analysis showed that there were no low‐intensity shifts in activity in any of the main functional networks . Nonetheless, the effects of any adaptations to the procedure that could induce a pre‐task cortisol response, should be assessed by repeated cortisol measurements even before the start of the task. Second, we only assessed the cortisol response to IVP and did not concurrently measure pulse rate or the subjective experience of blood taking. However, this information may help to understand how the appraisal of the different physiological responses influences subsequent stress reactivity (Gaab et al., In summary, the IVP led to a significant cortisol response in 35% of the participants. Critically, in these IVP responders, reactivity to the psychosocial stress task was significantly reduced including lower endocrine, subjective, autonomous, and neural responses. These effects were found despite a delay of about 60 min between IVP and the start of the stress task, a time frame that has often been considered as sufficient to avoid carry‐over effects. Collectively, our results suggest that an unrelated cortisol response that is induced before a psychological stressor may have beneficial, stress‐reducing effects in a consecutive stressful situation. Interestingly, this is not only the case for “positive” stressors such as exercise (Zschucke et al., The authors declare no potential conflict of interest.Elisabeth B. Binder and Philipp G. Sämann: were responsible for the study concept and design. Immanuel G. Elbau, Michael Czisch and Philipp G. Sämann: validated the paradigm and procedure. Anne Kühnel: performed the data analysis and Nils B. Kroemer: contributed to analyses. Anne Kühnel: wrote the manuscript. All authors contributed to the interpretation of findings, provided critical revision of the manuscript for important intellectual content and approved the final version for publication.AppendixS1. Supporting Information.Click here for additional data file.


The development and progression of hepatitis B virus‐related decompensated cirrhosis (DeCi) is associated with inflammatory responses. The monocyte‐to‐lymphocyte ratio (MLR), neutrophil‐to‐lymphocyte ratio (NLR), and red cell distribution width (RDW) are well‐known inflammation markers. We aimed to assess the utility of these parameters for predicating the prognosis of patients with HBV‐DeCi.We retrospectively recruited 174 patients diagnosed with HBV‐DeCi. Univariate and multivariate regression models were used to determine risk factors for mortality. Areas under the receiver operating characteristic curves were calculated to estimate and compare the predictive values of the three parameters. Hepatic function was evaluated using the Model for End‐Stage Liver Disease (MELD) score.The NLR, RDW, and MLR were found to be significantly higher in patients who did not survive compared with surviving patients. Moreover, these variables were all able to predict early poor outcomes in patients with HBV‐DeCi, with NLR exhibiting the highest accuracy. Furthermore, a combination of the NLR and MELD score was a more accurate prognostic marker for predicting mortality than either marker alone in such patients.Hematological parameters can provide prognostic information for patients with HBV‐DeCi. Routine assessment of these parameters at admission may provide valuable data to complement other conventional measures for assessing disease condition in patients with HBV‐DeCi. Receiver operating characteristic curve analysis by neutrophil‐to‐lymphocyte ratio, red cell distribution width, monocyte‐to‐lymphocyte ratio, Model for End‐Stage Liver Disease score, and neutrophil‐to‐lymphocyte ratio combined with Model for End‐Stage Liver Disease score for predicting mortality in patients with hepatitis B virus‐related decompensated cirrhosis. ALTAlanine aminotransferase;ASTAspartate aminotransferase;AUCsAreas under the curve;BUNBlood urea nitrogen;CIConfidence interval;DeCiDecompensated cirrhosis;HBVHepatitis B virus;HEHepatic encephalopathy;HRSHepatorenal syndrome;INRInternational normalized ratio;LCLiver cirrhosis;MELD scoreModel for End‐stage liver disease score;MLRMonocyte‐to‐lymphocyte ratio;NLRNeutrophil‐to‐lymphocyte ratio;RDWRed cell distribution width;ROCReceiver operating characteristic;SIRSSystemic inflammatory response syndrome;WBCWhite blood cell1Hepatitis B virus (HBV) infection is a major cause of liver cirrhosis (LC); 3% of cases of HBV‐compensated LC progress to decompensated cirrhosis (DeCi) each year in China.22.1This study was performed according to the ethical guidelines of the Declaration of Helsinki and was approved by the Ethics Committee of the First Affiliated Hospital, School of Medicine, Zhejiang University.We recruited all consecutive patients with HBV‐DeCi who were treated at our hospital from July 2017 to December 2019 for this retrospective study. Cirrhosis was diagnosed by histopathological examination or clinical laboratory tests and imaging studies. Liver decompensation was determined by the presence of various complications including ascites, hepatorenal syndrome (HRS), hepatic encephalopathy (HE), and/or variceal hemorrhage. In the present study, there were no exclusions for age/sex. The following exclusion criteria were applied: (a) presence of HAV, HCV, HIV, or other viral infection; (b) presence of chronic liver disease ; (c) malignancy; (d) presence of any other blood system diseases; (e) cardiovascular diseases; and (f) received interferon, corticosteroid, or immunosuppressive therapy 6 months before admission were excluded. All participants received antiviral therapy from the start date.2.2For each patient, demographic and baseline clinical data  were obtained from medical records and were recorded in a specific liver disease pro forma. Laboratory variables that were evaluated included levels of total protein, serum albumin, alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin, creatinine, and blood urea nitrogen (BUN) as well as the international normalized ratio (INR). All biochemical values were measured using a Hitachi 7600 clinical analyzer (Hitachi) and a Sysmex CA1500 fully automatic analyzer (Sysmex Corp.). Hematological parameters including white blood cell (WBC) count and the relevant subpopulations , RDW, platelet counts, and hemoglobin levels were analyzed using an automated analyzer (Sysmex XN‐9000). The MLR and NLR were calculated by dividing the number of monocytes by lymphocytes and by dividing the neutrophil count by lymphocyte count, respectively. Additionally, hepatic function was evaluated using the Model for End‐Stage Liver Disease (MELD) score, which was calculated as previously described.2.3t test, the Mann‐Whitney U test, or the chi‐square test, as appropriate. Associations between variables were explored using Spearman's correlation analysis. To assess diagnostic value, logistic regression and receiver operating curve analyses (ROC) were performed. Statistical analyses were performed using Statistical Package for the Social Sciences (SPSS) 11.0 software  and MedCalc 12.0 software . We considered P < .05 to indicate statistical significance.All continuous variables are presented as mean ± standard deviation (mean ± SD) or median with interquartile ranges (IQR). Categorical data are presented as percentages. Comparisons between the non‐surviving and surviving groups were carried out using the Student's 33.1r = .218, P = .004) and RDW  .Of the 213 patients that were recruited for the present study, 39 were excluded: five due to hepatocellular carcinoma, two due to liver transplantation, four due to autoimmune liver disease, three due to HIV infection, 14 due to concurrent infection with hepatitis C/D/E/G, four due to alcoholic liver disease, two due to blood system diseases (iron deficiency anemia or chronic lymphocytic leukemia), and five due to undergoing immunomodulatory therapy (steroids or interferon therapy). Finally, 174 patients  with HBV‐DeCi were enrolled, with a mean age of 53.6 ± 11.4 years. The most common complications were ascites in 114 patients (65.5%), followed by gastrointestinal bleeding in 50 patients (28.7%), HRS in 31 patients (17.8%), and HE in 4 patients (2.3%). Sixty‐one patients (35.1%) had more than one feature of decompensation at the time of first presentation. The median values of NLR, RDW, and MLR at enrollment were 2.39 , 16.1 , and 0.36 , respectively. Positive correlations were found between the MELD scores and the NLR (P < .001).Of the total study population, 150 patients survived and 24 died, giving a 28‐day mortality rate of 13.8%. The cause of death was hepatic failure in five patients, upper gastrointestinal bleeding in seven, HE in four, and HRS in eight. Demographic, clinical, and laboratory parameters of non‐survivors and survivors are shown in Table 3.2P < .05) and MELD score —and the specificity (87.5%) the sensitivity (82.0%) improved.Analysis of the associations between mortality and three parameters and MELD score by univariate logistic regression revealed that a higher MELD score, RDW, NLR, and MLR are associated with 28‐day mortality in patients with DeCi. Multivariate analysis revealed that only MELD and NLR remained independently associated with 28‐day mortality Table . When NL4The role of the NLR, RDW, and MLR in patients with HBV‐DeCi has been extensively studied, but the present study is the first to compare prognostic capabilities of these parameters within a single study. Our results demonstrate that the NLR, RDW, and MLR were significantly higher among non‐surviving than surviving patients. More importantly, we also found that the NLR, RDW, and MLR were all able to predict early unfavorable outcomes in these patients, among which NLR was the most accurate for predicting mortality. Furthermore, the combination of NLR and MELD was found to be a more accurate prognostic index for the prediction of mortality than either marker alone in patients with HBV‐DeCi.Systemic inflammation is known to play an important role in the disease progression of HBV‐DeCi. The NLR has been identified as a potent inflammatory marker, associated with diagnostic and prognostic properties in various clinical problems.Similar to NLR, MLR is also known to be an inflammatory marker.The RDW is an automated measure of the size variation of circulating red blood cells and therefore reflects the heterogeneity of these cells.The MELD score has been widely used as for organ allocation in liver transplantation and is the current standard prognostic tool for predicting the 3‐ to 6‐month survival of patients with liver failure.The present study has some limitations which warrant consideration. First, the retrospective study design may have led to selection bias. Second, we were unable to evaluate some inflammatory markers, such as C‐reactive protein or IL‐6, which may be helpful in establishing the mechanism underlying the findings presented here. Further verification in a multi‐center, prospective study is warranted.In conclusion, we assessed the role of the NLR, RDW, and MLR in predicating poor prognosis of patients with HBV‐DeCi. We show that these parameters are useful for predicating the 28‐day mortality in such patients and that using a combination of the NLR and MELD score is the most accurate approach. According to our data, routine assessment of these parameters at the time of admission may provide valuable supplementary information to other conventional approaches for assessing disease condition in these patients. Further prospective clinical trials are required to confirm the current findings.


The role of adjuvant chemotherapy (ACT) for patients with stage IB–IIA non‐small cell lung cancer (NSCLC) according to the eighth edition of the AJCC TNM staging system remains controversial.Data were collected from patients with NSCLC stage IB–IIA according to the eighth edition of the AJCC TNM staging system who underwent surgical resection from 2008 to 2015. The relationship between ACT and overall survival (OS) or disease‐free survival (DFS) was analyzed using the Kaplan–Meier method and Cox proportional hazards model.P = 0.13) in ACT and non‐ACT settings, respectively. Subgroup analyses demonstrated that ACT treatment was correlated with an improved five‐year OS in patients with visceral pleural invasion (VPI) in the 3 < tumor ≤ 4 cm subgroup .The study included 648 patients with completely resected NSCLC stage IB–IIA; 312 underwent ACT after surgical resection and 336 were placed under observation. After propensity score matching, 247 pairs of patients were matched and the five‐year OS was 88.08% and 83.12%  subgroup might benefit more from ACT. Further studies are required to validate the findings and better systemic strategies need to be developed in these patients.For patients with stage IB–IIA NSCLC according to the eighth edition of the AJCC TNM staging system, the effect of ACT remains unclear.ACT was not significantly associated with improved five‐year OS in stage IB–IIA NSCLC patients. However, it was correlated with better DFS before or after PSM.Patients with VPI in the 3 < tumor ≤ 4 cm subgroup may benefit from ACT.ACT was not significantly associated with improved five‐year OS in stage IB–IIA NSCLC patients. However, it was correlated with better DFS before or after PSM.Patients with VPI in the 3 < tumor ≤ 4 cm subgroup may benefit from ACT. Whether adjuvant chemotherapy can improve the survival of patients with stage IB–IIA NSCLC, according to the eighth edition of the AJCC TNM staging system, remains unclear. We reviewed our database and found that patients with VPI in the 3 < tumor ≤ 4 cm subgroup may benefit from ACT. Lung cancer is one of the most commonly diagnosed cancers  and the leading cause of cancer death  predicted in 2018.Randomized controlled trials and meta‐analyses of adjuvant chemotherapy (ACT) versus observation in patients with resected NSCLC have previously demonstrated a statistically significant benefit of the addition of systemic therapy.However, the efficacy of ACT on patients with stage IB NSCLC remains controversial. In the Cancer and Leukemia Group B (CALBG) 9633 trial, patients with stage IB NSCLC  failed to show an overall survival (OS) benefit with ACT, except in patients with tumor > 4 cm.In the current study, we investigated 648 cases of stage IB–IIA NSCLC who underwent surgical resection in the Cancer Hospital Chinese Academy of Medical Sciences from 2008 to 2015. Relative clinical and pathological characteristics that may influence survival results were collected, including sex, age, smoking history, histopathological diagnosis, tumor size, differentiation, lympovascular invasion (LVI), visceral pleural involvement (VPI), and number of examined lymph nodes (ELNs). The aim of this study was to investigate whether ACT can improve the OS for patients with stage IB–IIA NSCLC according to the eighth edition of the TNM classification.A total of 648 pathological stage IB–IIA NSCLC patients who underwent surgical resection at the National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences/Peking Union Medical College between 1 January 2008, and 30 April 2015, were included in this study. Pathological staging was done according to the eighth edition of the TNM classification. In the eighth edition of the TNM classification, T2 is considered to be a tumor >3 cm but ≤5 cm, or having any of the following features: (i) Involving the main bronchus, regardless of distance to the carina, but without involvement of the carina; (ii) invading the visceral pleura (PL1 or PL2); and (iii) is associated with atelectasis or obstructive pneumonitis that extends to the hilar region, involving part or all of the lung. Therefore, we included the cases with these features in the 0 < tumor ≤ 3 cm group . Moreover, T2aN0M0 was defined as 3 < tumor ≤ 4 cm (stage IB) and T2bN0M0 was 4 < tumor ≤ 5 cm (stage IIA). We excluded data from patients with neoadjuvant chemotherapy, radiotherapy, wedge excision, positive surgical margins, recurrence within six months, or death within one month.Patients were included if they had received ACT within 1–3 months after surgical resection. The decision as to whether a patient received or did not receive ACT was based on the physical and pathological condition of each patient. ACT consisted mostly of platinum‐based agents. Most regimens included cisplatin or carboplatin combined with vinorelbine, gemcitabine, pemetrexed, paclitaxel, or docetaxel. Due to physical conditions or personal wishes, some patients received only single‐agent chemotherapy without platinum agents. Four cycles of ACT were routinely administered.Routine surveillance after completion of definitive therapy, including history and physical examination, blood tests, and chest CT scan, were done every 3–6 months for the first three years, at six‐month intervals for the next two years, and annually thereafter. Once symptoms or signs of recurrence appeared, patients underwent systemic examinations. The duration of OS was defined as the interval between the date of surgical resection and death. The duration of DFS was defined as the interval between the date of surgical resection and locoregional or distant recurrence.t‐test and Pearson's Chi‐square test were used to compare clinical and pathological characteristics between ACT and observation groups. To reduce selection bias, propensity score matching (PSM) was used to achieve balance in baseline characteristics between the ACT and observation groups. Patients were matched regard to sex, age, smoking history, histopathological diagnosis, tumor size, tumor differentiation, LVI, VPI, and ELNs.The Student's P‐values <0.05.The Kaplan–Meier method with log‐rank test was used to estimate OS and DFS rates in all patients and in such subgroups. Univariate and multivariate regression models were constructed to estimate the simultaneous effects of potential independent predictors of survival. Multivariate regression models incorporated factors identified in univariate analyses with http://www.R-project.org) and EmpowerStats software .All data were double‐entered and then exported to tab‐delimited text files. All analyses were performed with R (P < 0.05). After PSM, 247 pairs of patients were individually matched between the two groups, and all baseline characteristics were well‐balanced. Table This study included 648 patients, comprising 566 with pathological stage IB disease and 82 with stage IIA (4 < tumor ≤5 cm) disease according to the eighth edition of the staging system. Patients with stage IB disease were divided into two subgroups based on tumor size . Among these patients, 312 (48.15%) underwent ACT after surgical resection and 336 (51.85%) were placed under observation. ACT was more common in the subgroup patients with young age, smoking history, larger tumor size, poor differentiation or LVI (P < 0.01) was an independent adverse predictor of OS (Table ). Post‐PSM data further corroborated this conclusion . Irrespective of whether this was before or after PSM analyses, large tumor size was found to be associated with poor DFS  (Table ). Despite the insufficient number of cases, patients with larger tumor sizes (4 < tumor ≤ 5 cm) had significantly worse OS than those with smaller tumors . The five‐year OS and DFS rates of patients with larger tumors were 71.02% and 44.68%, respectively, which was significantly lower than those of patients with small tumors . Subgroup analysis stratified by tumor size was also performed in the matched population (SI1). Furthermore, having fewer ELNs (<10) was associated with a higher recurrence rate . Unfortunately, we did not detect a relationship between fewer ELNs and shorter DFS after PSM (Table ).After univariate regression analyses and multivariate risk adjustment for potential confounding factors, we found that larger tumor size (4 < tumor ≤ 5 cm)  . After PSM was performed, the five‐year survival rates in patients with ACT and those placed under observation were statistically similar at 88.08% and 83.12%, respectively (P = 0.13) . Although ACT did not demonstrate a benefit in OS, it was correlated with better DFS before or after PSM  , the five‐year OS rate was 84.54% for all study participants as determined using Kaplan–Meier survival models and log‐rank tests. However, subgroup analysis showed that ACT was not associated with higher survival rate in patients with stage IB–IIA NSCLC. The five‐year OS rates were 87.66% and 81.65% for patients in the ACT and observation groups, respectively (.06) Fig . After .13) Fig . Althou.04) Fig .P = 0.01; HR, 0.70; 95% CI: 0.53–0.95; P = 0.02, respectively). However, there was no ACT influence on OS in such patients  and benefit from ACT was not confounded in this study. Moreover, patients in the 3 < tumor ≤ 5 cm group did not benefit from ACT, neither in the 3 < tumor ≤ 4 cm subgroup nor in the 4 < tumor ≤ 5 cm subgroup. The association between tumor size and benefit from ACT was not confounded regardless of PSM (Table P = 0.02)     Fig . MeanwhiPSM) Fig .P < 0.01)  . In addition, the five‐year DFS rates were 74.01% and 39.65% in these two subgroups, respectively (P < 0.01)   Fig . In addPSM) Fig . HoweverAlthough increasing evidence suggests that cisplatin‐based doublet ACT may improve OS for patients with surgical resection, whether stage IB–IIA NSCLC patients can benefit from ACT remains controversial.In multiple studies, tumor size has been shown to predict outcome in NSCLC patients following surgical resection.P < 0.001).It has been reported that VPI and tumor size have a synergistic effect on survival in node‐negative NSCLC. The prognostic value of VPI in stage IB NSCLC has been re‐evaluated using the prospective multicenter ACOSOG Z0030 trial data set.et al. reported that a greater number of ELNs is associated with more‐accurate node staging and better long‐term survival of patients with stage I–IIIA resected NSCLC.Lymph node sampling or dissection plays an important role in precise nodal staging by identifying lymph node involvement and determining the extent of disease and the therapeutic effect on lymph node metastatic lesion clearance.We evaluated the influence of ACT on survival in stage IB–IIA NSCLC patients according to the eighth edition of the AJCC/UICC, which is the major strength of this study. Through further in‐depth analysis, we identified that only larger tumor size and advanced age were the potential independent prognostic factors. Having fewer ELNs was associated with a higher rate of recurrence. More importantly, patients with VPI in the 3 < tumor ≤ 5 cm subgroup might benefit from ACT, particularly so the patients in the 3 < tumor ≤ 4 cm subgroup.This study also has certain limitations. First, it was a retrospective and single‐center study. Second, an insufficient number of cases and deaths were observed during the median follow‐up of 63.72 months in our cohort to fully investigate the interaction between ACT, and OS and DFS benefits in stage IB–IIA NSCLC patients following resection. A longer follow‐up period and multicenter approach may overcome this limitation.In conclusion, ACT may improve DFS, but not OS, in patients with stage IB–IIA based on the eighth edition of the AJCC TNM classification. Although larger tumor size (4 < tumor ≤ 5 cm) was an independent prognostic factor, we did not conclude that patients in the 4 < tumor ≤ 5 cm subgroup could benefit from platinum‐based ACT. Fortunately, subgroup analysis confirmed that patients with VPI in the 3 < tumor ≤ 4 cm subgroup may benefit more from ACT. Further prospective randomized clinical trials are needed to further identify the role of ACT and better systemic strategies need to been developed in resected stage IB–IIA NSCLC.The authors declare that there are no conflicts of interest.


Osteoarthritis (OA) affects over 301 million adults worldwide. Inflammation is a recognized component of the OA process; two potent pro‐inflammatory cytokines involved in OA are interleukin‐1β and tumor necrosis factor‐α. Placental‐derived tissues and fluids are known to contain anti‐inflammatory and immunomodulatory cytokines and growth factors. The objective of this study was to evaluate the anti‐inflammatory effects of amniotic suspension allograft (ASA) in an in vivo model of OA; we evaluated pain, function, and cytokine levels following ASA treatment in the rat monosodium iodoacetate (MIA) OA pain model. Rats were injected with 2 mg of MIA, which causes pain, cartilage degeneration, and inflammation, followed by treatment with saline, triamcinolone (positive control), or ASA 7 days following disease induction with MIA. Behavioral assays, including gait analysis, mechanical pain threshold, incapacitance, and swelling were evaluated, along with histology and serum and synovial fluid biomarkers. Treatment with ASA resulted in significant improvements in pain threshold, while weight bearing aversion and swelling were significantly decreased. There were no differences between groups in total joint score after histological grading. Serum biomarkers did not show differences, indicating a lack of systemic response; however, synovial fluid levels of IL‐10 were significantly increased in animals treated with ASA. ASA treatment significantly reduced pain, weight‐bearing aversion and swelling. This study provides mechanistic data regarding potential therapeutic effects of ASA in OA and preliminary evidence of the anti‐inflammatory nature of ASA. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 38:1141‐1149, 2020 Osteoarthritis (OA) is a degenerative disease involving the soft tissues, cartilage, and subchondral bone of joints, afflicting 301 million adults worldwide.OA is a multi‐faceted disease, with both biological and mechanical factors at play.One potential treatment approach for OA is the use of amniotic tissue; these tissues are known to be inherently anti‐inflammatory. Amniotic tissue is derived from the human placenta, which is composed of two layers (i) the chorion: the thick, outermost layer in contact with the mother and (ii) the amnion: the thin, innermost layer in contact with the fetus.n = 10 for all groups): saline (vehicle control), 25 μl ASA  + 25 μl saline), 50 μl ASA (no dilution), or 0.06 mg triamcinolone acetonide injectable suspension . The volume for dosing was established from a previously reported study with recommendations based on the body weight of rats.All animal procedures were completed at Bolder BioPATH  and protocols were approved by the Bolder BioPATH Institutional Animal Care and Use Committee (IACUC) (Protocol #BBP‐020). Forty‐five male Sprague–Dawley rats  were obtained and acclimated for 8 days prior to the start of any experiments; animal weights were between 175 and 225 g at the beginning of the study. Animals were housed, 4–5 animals per cage on a 12 h/12 h light/dark cycle; Harlan Teklad diet #8640 was fed ad libitum and unrestricted access to tap water was available throughout the study. On day 0, the right knees of forty rats were injected with 2 mg of MIA to induce OA in the knee  for 48 h. Following fixation, knees were cut in half in the frontal plane and embedded in the same paraffin block for histological assessment. Sections were stained using standard techniques with toluidine blue for histopathological grading. Whole‐joint graded components are displayed in Table At sacrifice, serum and synovial fluid was collected from each rat. Serum was spun down, aliquoted, and placed at −80°C until use. Analysis of cytokines in the serum samples, including IL‐1β, IL‐6, IL‐10, MCP‐1, TIMP‐1, and TNF‐α, were measured using rat enzyme‐linked immunosorbent assay (ELISA) kits . All kits were run according to the manufacturer's instructions. Synovial fluid was collected via lavage with 50 μl heparinized saline from the right knee; samples were spun down, aliquoted, and placed at −80°C until use. Analysis of synovial fluid cytokine levels was completed using the Rat Inflammatory Panel Q1 multiplexed sandwich ELISA . This panel included IFN‐γ, IL‐1α, IL‐1β, IL‐2, IL‐4, IL‐6, IL‐10, IL‐13, MCP‐1, and TNF‐α, and was run according to the manufacturer's instructions.All statistical analysis was done using GraphPad Prism 6 . For animal behavioral and histological data, a one‐way analysis of variance (ANOVA) was run for each time point, with a Dunn's post hoc test to assess statistical significance between groups. For animal serum and synovial fluid data, a one‐way ANOVA was run with a Tukey's post hoc test to assess statistical significance between groups.p = 0.0207, Fig. The MIA model was chosen to evaluate inflammation and pain in vivo due to its previous validation as a model to evaluate nociception changes.p = 0.018 and p = 0.0049, respectively; Fig. p = 0.0006 and p = 0.0021, respectively; Fig. In addition to sensitivity using dynamic gait, pain was measured by determining pain thresholds via Von Frey assessment. In this study, rats treated with 50 μl of ASA showed a significant improvement in pain threshold levels at day 14 that was sustained until study completion 21 days) compared with vehicle controls . In addition, triamcinolone had significantly reduced osteophyte measurements and scores compared with the vehicle control . Treatment with 50 μl of ASA resulted in a significant increase in synovitis and fibrosis scores compared with the vehicle control .Individual components of the total joint score, along with the synovitis and fibrosis scores, are shown in Table p < 0.05, Fig. p < 0.05, Fig. Following sacrifice, serum and synovial fluid were collected from rats and analyzed using ELISAs. In serum analyses, there were no significant differences between any of the groups, indicating treatment was localized to the joint and there were no measured systemic effects of ASA Table . SynoviaIn the MIA rat OA model, treatment with ASA resulted in significant improvement in pain threshold levels and a significant reduction in weight‐bearing difference and swelling. Histological analysis indicated no significant changes in total joint scores between groups; however, the 50 μl ASA and triamcinolone groups resulted in some differences in sub‐scores compared with the vehicle control. Analysis of serum levels showed no systemic effects of ASA treatment, while synovial fluid analysis revealed a significant increase in IL‐10 levels following 25 μl ASA treatment.Currently, there are limited treatment options that slow or prevent the progression of OA. Common treatments for early‐stage OA range from exercise and physical therapyMechanistic data in the MIA model of OA presented here, coupled with early clinical data,Another interesting finding in this study was increased subchondral bone sclerosis observed with triamcinolone treatment; this finding has been observed in previous in vivo and clinical studies.The current study is, to our knowledge, the only study to evaluate pain and function resulting from use of a placental tissue product. Ferreira‐Gomes et al.The study presented here focused on pain and inflammation in a MIA model of arthritis and evaluated behavioral effects mechanistically. Our study demonstrated changes to the cytokine levels within the joint, improved pain thresholds, and reductions in swelling and weight‐bearing differences. One limitation to this study is that only male rats were used; this decision was made to increase reproducibility within the study between animals and improve chances of seeing differences in treatment due to the known effects of sex and reproductive status on disease severity in OA animal models.Other areas of interest for future work include ASA effects on cartilage degeneration in vivo and the influence of macrophages in vitro and in vivo. Finally, clinical studies validating these effects are necessary; as such, a 200‐patient multicenter study evaluating ASA as a treatment for knee OA has completed enrollment at the time of this evaluation (NCT02318511).K.A.K. designed the study, executed experiments, analyzed and interpreted the data, and wrote the manuscript. K.C.M. designed the study, interpreted the data, and wrote and edited the manuscript. A.H.G. and J.F. interpreted the data and wrote and edited the manuscript. All authors have read and approved the final manuscript.


Trichomonas vaginalis, the causative agent of a prevalent urogenital infection in humans, is an evolutionarily divergent protozoan. Protein-coding genes in T. vaginalis are largely controlled by two core promoter elements, producing mRNAs with short 5′ UTRs. The specific mechanisms adopted by T. vaginalis to fine-tune the translation efficiency (TE) of mRNAs remain largely unknown.T. vaginalis: codon usage and mRNA secondary structure. Statistical dependence between TE and codon adaptation index (CAI) highlighted the impact of codon usage on mRNA translation in T. vaginalis. A genome-wide interrogation revealed that low structural complexity at the 5′ end of mRNA followed closely by a highly structured downstream region correlates with TE variation in this organism. To validate these findings, a synthetic library of 15 synonymous iLOV genes was created, representing five mRNA folding profiles and three codon usage profiles. Fluorescence signals produced by the expression of these synonymous iLOV genes in T. vaginalis were consistent with and validated our in silico predictions.Using both computational and experimental approaches, this study investigated two key factors influencing TE in T. vaginalis mRNAs, contributing to a better understanding of the factors that influence, and possibly regulate, gene expression in this human pathogen.This study demonstrates the role of codon usage bias and mRNA secondary structure in TE of  Trichomonas vaginalis is a flagellated protozoan that infects the human urogenital tract causing trichomoniasis, the most common non-viral sexually transmitted infection worldwide , wa, waT. va_CO Fig. , althougp < 0.05, grey shaded cells in Table S1). Importantly, when synonymous genes of the same folding profile were compared, the fluorescence intensity decreased from high through low CAI, without exception  implies that the mRNA itself contains information that directly affects the protein synthesis rate during translation. To investigate factors that potentially modulate TE in a particular organism, previous studies have relied on in silico analyses of expression abundances of endogenous genes –20 and/oT. vaginalis genes with solid transcriptomic (nEST ≥5) and proteomic (nMS ≥ 2) expression evidence  [T. vaginalis mRNAs.To validate our computational characterisation experimentally, we designed a collection of synonymous iLOV genes that were expressed in iLOV_CO) , represeT. vaginalis mRNAs , to the 100th nt of the ORF  or the lowest (Bottom 200) TE were isolated and subjected to the same sliding window scheme and MFE calculation Figure , as per https://github.com/Huaqiedward.Python programming language was widely used in this study to process gene sequences, make calculations, perform statistical analysis and plot data on graphs. All Python scripts in this study have been uploaded to Nru I endonuclease, without altering the amino acids specified  gene in T. vaginalis (7 nt in length) was linked to the 5′ end and the joined sequence was sliced by the same sliding window scheme as described above. Window 8, 51 and 66, containing ambiguous DNA codes, were expanded into all possible unambiguous sequences. MFE values of these unambiguous sequences were calculated and the distribution of MFE values was analysed for each window position separately. Five representative unambiguous sequences were chosen for each window position, representing five discrete MFE levels  [The 15 synonymous iLOV genes were chemically synthesised by Integrated DNA Technologies (IDT) and inserted to pMN  for expriLOV_CO) , and pMNT. vaginalis G3 strain cells. All 17 plasmids were examined in three independent transfection assays. Briefly, wild type G3 strain T. vaginalis cells were cultured in complete Diamond’s medium at 37 °C, until reaching a concentration of 1–2 × 106 cells/ml. Cells were harvested by centrifugation at 3000 g for 20 min at 4 °C and resuspended in cold fresh Diamond’s medium to a concentration of 8.33 × 108 cells/ml. Aliquots of 300 μl cell suspension were transferred into 0.4 cm electrocuvettes (Bio-Rad), mixed with 60 μg plasmid and electroporated at 350 V with 975 μF capacitance using a Bio-Rad Gene Pulser II. Electroporated cells were transferred to 50 ml pre-warmed Diamond’s medium, incubated at 37 °C. At 8 h post-electroporation, cells were sampled from the supernatant, pelleted by centrifugation, resuspended in phosphate-buffered saline (PBS) and taken for analysis of transient expression. After sampling of cells for transient expression analysis, G418 was immediately added to cell culture at a concentration of 200 μg/ml to perform drug selection. After 18–24 h, the pellets containing dead cells and debris in each tube were removed. Cells in the supernatant were then recovered by centrifugation and resuspended in fresh complete media containing G418. Once cells grew to a concentration of 0.5–1 × 106 cells/ml in the presence of G418 , they were passaged daily always in the presence of G418. After being passaged for 1 week, cells were harvested by centrifugation, resuspended in PBS and taken for analysis of stable expression.A standard electroporation protocol  was usedBoth transient and stable expression analyses of the iLOV genes were carried out with an Accuri C6 Flow Cytometer, BD Biosciences. Green fluorescence intensity was detected by FL1, and dead cells excluded by FL3 after being stained by 0.2% propidium iodine (PI). A protocol was set up to count a total of approximately 30,000 live cells per sample. At the transient expression stage, the presence of live and FP-positive cells was confirmed by dots  located in quadrant Q3. The strength of fluorescent signals released from each sample during transient expression was quantified by multiplying the percentage of dots located in quadrant Q3 and the median FL1 value of all dots in Q3. At the stable expression stage, the fluorescence intensity of every single cell was measured by FL1 and the median fluorescence intensity value of the entire cell community in each transfected sample was calculated. For both transient and stable expression data, One-way analysis of variance (ANOVA) and Post hoc analysis (Tukey method) were performed (see Additional file 1: Figure S1. Workflow for the investigation of codon usage bias as a TE determinant in T. vaginalis.Figure S2. Workflow for the investigation of mRNA secondary structure as a TE determinant in T. vaginalis.Figure S3. Structural pattern and variation of GC content across the length of T. vaginalis mRNAs from Dataset 4. Figure S4. Spearman’s correlation analyses did not reveal a direct association between TE and MFE at 5′ end or surrounding the AUG start codon of T. vaginalis mRNAs from Dataset 1. Figure S5. Transient expression of the synonymous iLOV genes from three independent transfections. Table S1. Pairwise comparisons across transient expression illustrated on Fig. S5. Table S2. Pairwise comparisons acrosss stable expression illustrated on Fig.


There is low diagnostic accuracy of the proxy restrictive spirometric pattern (RSP) to identify true pulmonary restriction. This knowledge is based on patients referred for spirometry and total lung volume determination by plethysmograpy, single breath nitrogen washout technique or gas dilution and selected controls. There is, however, a lack of data from general populations analyzing whether RSP is a valid proxy for true pulmonary restriction. We have validated RSP in relation to true pulmonary restriction in a general population where we have access to measurements of total lung capacity (TLC) and spirometry.1) and forced vital capacity (FVC) were obtained before and after bronchodilation. TLC and residual volume (RV) was recorded using a body plethysmograph. All lung function values are generally expressed as percent predicted (% predicted) or in relation to lower limits of normal (LLN). True pulmonary restriction was defined as TLC < LLN5 defined as a Z score < − 1.645, i e the fifth percentile. RSP was defined as FEV1/FVC ≥ LLN and FVC < LLN after bronchodilation. Specificity, sensitivity, positive and negative likelihood ratios were calculated, and 95% confidence intervals (CIs) were calculated.The data was from the Swedish CArdioPulmonary bioImage Study (SCAPIS Pilot), a general population-based study, comprising 983 adults aged 50–64. All subjects answered a respiratory questionnaire. Forced expiratory volume in 1 s , the corresponding specificity was 0.98 (0.97–0.99), and the positive likelihood ratio was 21.1 (11.3–39.4) and the negative likelihood ratio was 0.67 (0.55–0.81).RSP has low accuracy for identifying true pulmonary restriction. The results support previous observations that RSP is useful for ruling out true pulmonary restriction. True pulmonary restriction is synonymous with reduced total lung capacity (TLC) and is associated with a number of pathological conditions that either take up space in the thoracic cavity or restricts movements of the thoracic cage or diaphragm – for example interstitial lung diseases, pleurisy, lung edema, kyphosis, neuromuscular weakness and severe obesity. Measurements of TLC require relatively sophisticated equipment such as a body plethysmograph, or helium or nitrogen gas analyzers , 2. Thes1)/forced vital capacity (FVC) ≥ 0.7 and FVC < 80% predicted [1/FVC ≥ LLN and FVC < LLN [Conversely, dynamic spirometry can be done at low cost. The procedure is simple and widely used, but does not measure TLC. Consequently, there is a need for a spirometric algorithm that identifies reduced TLC with high diagnostic accuracy. It has been suggested that low vital capacity in the absence of airflow limitation could be used as a proxy for true pulmonary restriction. The proxy restrictive spirometry pattern (RSP) has been defined as forced expiratory volume in 1 s , and dynamic spirometry before and after bronchodilation. Hence, we will have the possibility to validate RSP for indicating true pulmonary restriction.Our data was from the pilot part of the Swedish CArdioPulmonary bioImage Study (SCAPIS Pilot), a Swedish general population-based study. For this initial pilot study, a randomly selected population sample of 2243 adults aged 50–64 years were invited to take part and 1111 agreed to participate . All per1, FVC and slow vital capacity (SVC) was performed before and 15 min after inhalation of 400 μg of salbutamol using a nose clamp with the subject in a sitting position. All accepted exhalations had a duration of > 6 s and a plateau on the curve the last second of the exhalation. Static lung volumes, TLC and RV, were determined by body plethysmography based on two measurements recorded after bronchodilation. There were daily calibrations of pressure, volume and flow. All procedures were performed according to American Thoracic Society (ATS)/European Respiratory Society (ERS) standards [1, FVC and SVC were based on recently published local reference equations [Dynamic spirometry, including FEVtandards . There wquations , 18. Prequations . For anaquations , 18.z score < − 1.645 (i. e. a z score below the fifth percentile), using both the published equations of Quanjer et al., TLC < LLNQUANJER, and the local equation TLC < LLNGOTHENBURG, see “True pulmonary restriction was defined as TLC < LLN described as a LLN = FEV1/FVC ≥ LLN and FVC < LLN after bronchodilationRSP0.7 = FEV1/FVC ≥ 0.7 and FVC < 80% predicted after bronchodilation [RSPdilation , 18.PREDIL = FEV1/FVC ≥ LLN and FVC < LLN before bronchodilation [RSPdilation , 18.LLNSVC = FEV1/SVC ≥ LLN and SVC < LLN after bronchodilation [RSPdilation , 18.0.7SVC = FEV1/SVC ≥ 0.7 and SVC < 80% predicted after bronchodilation [RSPdilation , 18.Restrictive spirometric pattern (RSP) was in five different ways;Asthma was defined as an affirmative answer to an item about physician-diagnosed asthma . DyspneaSmoking was categorized into current smokers, former smokers, and never-smokers. Former smokers were defined as those who had smoked for at least 1 year but who had not smoked during the past 12 months. In this analysis current smokers and former smokers were categorized as ever-smokers.All calculations were performed using SAS version 9.4 . The local reference equation for TLC was computed by a linear regression model with height as a covariate, stratified by gender. The resulting equation for women was TLC = height (cm)*0.085–8.71, with residual standard deviation (RSD) = 0.56. For men the equation was TLC = height (cm)*0.102–10.93), with RSD = 0.83.LLN using increasing percentiles of FVC were plotted. Factors associated with disconcordance between true pulmonary restriction and RSPLLN and RSPLLNSVC were analyzed as odds ratios (OR), using multiple logistic regression. The variables age, body mass index, gender, smoking habits and RV were a priori selected as potentially associated with disconcordance.Specificity, sensitivity, positive and negative predictive values , positive and negative likelihood ratios (LR+ and LR-) were calculated, and 95% confidence intervals (CIs) were calculated using exact methods. Post-test probabilities of disease after positive and negative tests were assessed . We calcQUANJER, was 4.7% (n = 46), and when using our local equation, the prevalence of TLC < LLNGOTHENBURG was 5.4% (n = 53). The prevalence of RSPLLN, RSP0.7, and RSPPREDIL was, 3.4% (n = 33), 3.2% (n = 31), and 3.4% (n = 23), respectively. When applying SVC, the prevalence of RSPLLNSVC and RSP0.7SVC was 2.1% (n = 21) and 1.8% (n = 18), respectively  of true pulmonary restriction of 5.4%, a LR+ around 21 indicates a 50% post-test probability of true pulmonary restriction if presence of RSP. The negative likelihood ratios ranged from 0.67 to 0.71. A negative likelihood ratio around 0.70 means that there is a 4% post-test probability of true pulmonary restriction if there is no RSP. When applying the Gothenburg TLC equations to calculate predicted values the results were quite similar as compared to the Quanjer equation  and residual volume was negatively associated  , as in this case, the NPV rather accurately reflects that a negative test indicates no abnormality . This coEven if the specificity was 0.98, this level of specificity of a test will generate a substantial number of false positives when applied in a general population study when the true condition, true pulmonary restriction, has a low prevalence. This will lead to falsely decreased risk estimates because of misclassification of the disease . The conLLNSVC instead of RSPLLN. In clinical practice that means that overweight men may be at risk for disconcordant results. The material was too small to differentiate whether the disconcordance was dependent on true pulmonary restriction or on RSP.We found that high BMI and low residual volume were associated with this disconcordance. There was also an association with disconcordance and male gender, although with borderline significance. The results were more obvious when using RSPThe RSP phenotype has been linked to diabetes, metabolic syndrome and increased mortality . The preWe used a published reference equation to estimate the predicted values of TLC . In accoThe main weakness of the present study is the small study sample. We have outlined 95% confidence interval around our estimates to be able to judge the reliability of our results. Another limitation is the narrow age interval 50–64 years, making the conclusions valid for this age group only. Selection bias may be a problem, as the participation rate was around 50%. In the current population chronic obstructive pulmonary disease and cardiovascular disease seem to have increased the participation, but we believe this has only marginally affected the validity of the estimates .RSP has low validity for identifying true pulmonary restriction. We do not recommend using RSP in general population studies as a proxy for true pulmonary restriction. Our results support previous observations that RSP is useful for ruling out true pulmonary restriction.Additional file 1: Table S1. Age, gender, smoking habits, symptoms and lung function values in 983 subjects according to different definitions of restrictive spirometry pattern (RSP) based on slow vital capacity.


Domain-specific expertise changes the way people perceive, process, and remember information from that domain. This is often observed in visual domains involving skilled searches, such as athletics referees, or professional visual searchers . Although existing research has compared expert to novice performance in visual search, little work has directly documented how accumulating experiences change behavior. A longitudinal approach to studying visual search performance may permit a finer-grained understanding of experience-dependent changes in visual scanning, and the extent to which various cognitive processes are affected by experience. In this study, participants acquired experience by taking part in many experimental sessions over the course of an academic semester. Searchers looked for 20 categories of targets simultaneously ,in displays with 0–3 targets present, while having their eye movements recorded. With experience, accuracy increased and response times decreased. Fixation probabilities and durations decreased with increasing experience, but saccade amplitudes and visual span increased. These findings suggest that the behavioral benefits endowed by expertise emerge from oculomotor behaviors that reflect enhanced reliance on memory to guide attention and the ability to process more of the visual field within individual fixations. We examined the development of expertise in a longitudinal visual search study, measuring how experience changes individual performance and gaze behaviors. Across 14 sessions throughout an academic semester, observers gained experience searching for items from 20 memorized categories among displays of 32 objects. Some displays contained no targets, and others contained up to three. With experience, observers became faster and more accurate. More importantly, their eye movements revealed that, relative to their average performance, experience allowed observers to rely more heavily on memory to identify objects efficiently and to process more of the visual field within each fixation. Although experts and novices may differ in many factors , our results confirm that the oculomotor behaviors associated with expert scanning are learned, rather than innate. These results carry implications for training and assessment in professional search domains and represent one of the only longitudinal studies to track how skill development influences gaze behaviors over time.Across many domains and sensory modalities, expertise confers perceptual and cognitive benefits. Within visual domains, these benefits can include the abilities to efficiently extract relevant information from the environment, quickly process/perceive that information, and/or act on that information. For example, expert referees must direct attention to certain “contact zones” while monitoring for penalties .An expanded FVF would be of limited utility without the ability to efficiently perceive the attended objects and avoid revisiting previously perceived scene regions. The role of memory, therefore, seems important to expert search performance. Across domains, researchers often find that experts exhibit superior ability to remember domain-specific material . Decision speed and accuracy often separate experts from novices, as experts have been found to be faster and/or more accurate than novices in sports , experts are more likely to locate the target with their first fixation , one cannot control for innate or coincidental differences in visual skill that may encourage some people to self-select into professions that capitalize on that skill. In the present study, we used a relatively longitudinal approach to investigate expertise, such that each participant served as both a novice and, later, a skilled searcher with expert-level performance. Using this approach allowed us track changes to behavioral, cognitive, and oculomotor skills as expertise develops, rather than using between-group comparisons, which may be susceptible to individual-difference variations.In the present investigation, we monitored untrained searchers’ performance and oculomotor behaviors as they became adept at a laboratory visual search task designed to mimic some of the challenges faced by professional visual searchers, including the use of poorly specified and numerous potential targets, and targets which appeared with varying frequencies. Although many laboratory search tasks are guided by picture cues of targets, real-world search is often guided by categorical  cues, which impair, but do not preclude, attentional guidance . Despite their importance, such rare targets often go undetected, a phenomenon known as the low-prevalence effect , cognitive (decision time), and oculomotor  measures that change as expertise develops.n = 10). Only the first 14 sessions of these participants were included in analyses.Thirteen unpaid research assistants from the laboratories directed by the first two authors volunteered to participate during their regularly scheduled laboratory hours (in lieu of data collection responsibilities). All participants were naïve to the purpose and design of the study, reported normal or corrected-to-normal vision (including color vision), and provided written informed consent. Participants completed a variable number of sessions , ranging from 6 to 23. In total, there were 192 experimental sessions recorded . To standardize (and maximize) the number of sessions in our analyses, we limited the sample to participants who completed at least 14 experimental sessions  and category frequency, with categories appearing with variable frequency across all trials in an experimental session: least frequently (4 times), infrequently (8 times), frequently (16 times), and most frequently (32 times).All stimuli came from the “Massive Memory” database  and conducted in two separate laboratories simultaneously. In one laboratory, the stimuli were presented on a 17″ CRT monitor with refresh rate of 75 Hz and screen resolution of 1920 × 1200, and in the other, the monitor was 24″ with a refresh rate of 60 Hz. Both laboratories used monocular eye tracking at 500 Hz using S-R Systems Eyelink 1000 or 1000 + trackers. Each participant only took part in the experiment at a single laboratory.interest areas were defined as the smallest rectangular area that encompassed any given image. An eye movement was classified as a saccade when its distance exceeded 0.5° and its velocity reached 35°/s (or acceleration reached 9500°/s2). Viewing was binocular, but only the right eye was recorded.Participants took part in the study individually. Participants used a chin rest during all trials and were calibrated (using a nine-point system) prior to each session. The chin rest was adjusted so each participant’s gaze landed centrally on the computer screen when the participant looked straight ahead. Calibration was accepted if the mean error was less than 0.5° of visual angle, with no error exceeding 1.0° of visual angle. Periodic recalibrations ensured accurate recording of gaze position throughout the experiment; recalibrations occurred at the beginning of each block and within blocks when necessary.  For analysis purposes, During the first session, participants memorized the names of all target categories before performing any visual search trials; they performed two rounds of memorization and test. During memorization, participants viewed the full list of 20 target categories in a single alphabetized display, with a black box drawing their attention to each category name for 3 s before moving to the next category. After all categories were highlighted, participants completed a 40-trial old/new memory test , using the keyboard to indicate whether the tested item was one that they were instructed to memorize. Accuracy was assessed after the second round of memorization and test. Participants could only continue to the visual search phase if they completed the memory test with 80% accuracy or better, else the memorization and test phase would be repeated. All participants performed the above criterion on the first try.Following memorization, participants completed a practice block of 53 visual search trials . In the practice block, each target category appeared with equal frequency , so that frequency effects could only arise in experimental blocks.In each session, participants completed five 40-trial experimental blocks of visual search, with equal use of the four trial types . At the start of each block , participants were reminded of the 20 target categories  for which they would be searching. When they were ready to begin, they pressed any key on the keyboard. To initiate each trial, participants clicked the mouse, after which a centrally presented, gaze-contingent fixation cross was shown. After participants fixated the cross for 500 ms, it disappeared and was replaced by the 32-object visual search array. Search arrays were constructed by dividing the entire screen into an invisible 6 × 6 grid, from which 32 (of 36 possible) locations were randomly chosen, with the provision that one cell within each screen quadrant remains empty. Precise target locations within each cell were jittered to ensure that a minimum of 1.5° visual angle separated items from each other and the edge of the display.Within a single trial, targets could appear from across 20 categories, and multiple  exemplars from a single category could also appear . Participants indicated target selections by clicking on the pictures using the mouse. When pictures were selected, a black box was drawn around them to indicate that the computer detected the selection, but no indication was provided regarding whether the selected item was a target or distractor. Participants’ search was self-paced, and they terminated each trial by clicking on a “STOP” sign presented in the center of the display . Thus, analyses presented in text were conducted on “change percentages” for each individual session relative to that participant’s own grand average across all sessions. Because of this scaling, only the main effect of session and interactions with it are interpretable. For other main effects, please see the supplemental analyses on raw data values in “F = 2.95, p = 0.04; ηp2 = 0.25. As shown in Fig. Because the overarching hypotheses predict that expertise changes oculomotor measures, we treated analyses on behavioral measures as manipulation checks: Did accuracy and RT improve with accumulated experience? We examined search accuracy via hit rates F3.49, 3.41 = 2.9In our paradigm, expertise development can influence different aspects of the overall trial-level response time, including the latency to first target detection, the latency to click on all targets, and the overall time required for participants to terminate the trial. In the interest of brevity, we only report analyses on first target detection and search termination RTs in text, as these provide insight into expertise effects on search efficiency and quitting thresholds, respectively  8 for a three-target trial. We examined search efficiency in a 3 (effective set size) × 14 (session) RM ANOVA, which revealed a main effect of session, F = 39.10, p < 0.011, ηp2 = 0.81, but no interaction, p = 0.53.Although we did not manipulate set size, the analysis examining the latency to first target detection offers a way to explore the effect of F = 11.10, p < 0.001, ηp2 = 0.55. As shown in the right panel of Fig. p < 0.05). By session 3, quitting times became stable and did not reliably differ. Analyses on target-present quitting RTs revealed a reliable interaction, F = 3.52, p = 0.01, ηp2 = 0.28. As shown in the left panel of Fig. RTs may capture different phases of search, such as target identification or quitting decisions, each of which can be made more efficient by expertise development. Our paradigm also allowed us to isolate an additional cognitive process, search termination decisions. Because observers never knew how many targets would appear in any given trial, the latency between their final target detection and when they clicked “stop” in the 1- and 2-target trials can reveal insights into their quitting decisions . Moreover, the latency to click the stop sign in target-absent trials may reflect a more global estimate of quitting thresholds . This calculation included zeroes, for rare instances in which a displayed object was not examined. Importantly, visits are consistent with, but not identical to, the number of fixations a given interest area received. For instance, if the eyes enter an interest area and commit two fixations before leaving the area, that would count as two fixations but only one visit. In this way, visits can be interpreted as the number of times each item was examined, irrespective of small corrective fixations that may have been committed within the interest area.F = 9.17, p < 0.01, ηp2 = 0.51, which revealed that the probability of fixating items decreased with increasing experience across sessions. This main effect, however, was qualified by a reliable interaction, F = 4.31, p < 0.01, ηp2 = 0.32. As shown by the bar graphs in Fig. FS1 = 10.38, p = 0.01; FS2 = 6.46, p = 0.03) but that targets received relatively more fixations than distractors in session 14 . Although targets are obviously more likely to be viewed than distractors in the raw data  = 7.90, p < 0.01, ηp2 = 0.47: Relative to their grand average dwell times, participants’ dwell times decreased across sessions  = 4.12, p < 0.01, ηp2 = 0.31. Simple effect tests confirm that the interaction was in the predicted direction: In early sessions, distractors were looked at longer than average, relative to targets , but by session 14, this relationship flipped , which may reflect a change in quitting threshold.For each item visited, we calculated the average amount of time participants spent on each visit as a measure of object identification. Because experts are better able to rely on memory processes during search  = 22.18, p < 0.001; ηp2 = 0.71, and a reliable interaction between session and number of targets, F = 5.6, p = 0.001; ηp2 = 0.38. Observers’ ability to process multiple objects from a single fixation increased with experience, which was reflected in a percentage increase in FVF size across sessions. As shown in Fig. To determine whether experience and the number of targets in the display influence observers’ initial FVF sizes, we examined FVF in a 3 (number of targets) × 14 (session) RM ANOVA. This analysis confirmed a reliable effect of session, F4.4, 40.18 =ps > 0.3.Although the FVF changed with accumulated experience, the measure has not been without criticism  = 0.67, p = 0.79; ηp2 = 0.07. Both searching and targeting saccade amplitudes reliably changed across sessions, FS = 22.00, p < 0.001; ηp2 = 0.71; FT = 8.10, p < 0.001; ηp2 = 0.47. As shown in Fig. Although the distributions of the saccade amplitudes in each panel of Fig. F13, 7 = 0.67,The present study examined behavioral and oculomotor measures of expertise development in a multiple-target hybrid search task conducted longitudinally over the course of a single semester. With practice, observers became faster and more accurate at searching for categorically defined targets, as would be expected in many real-life domains .Changes in gaze behavior underlie the perceptual-cognitive benefits enjoyed by experts over novices , and whether these changes mitigate the LPE. Moreover, experience-based increases in visual span have important implications for theories of visual search, which may need to incorporate future model adjustments to address this modifiable parameter.


Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research.Concerns about bone health in transgender people using gender‐affirming hormonal treatment (HT) exist, but the fracture risk is not known. In this nationwide cohort study, we aimed to compare the fracture incidence in transgender people using long‐term HT with an age‐matched reference population. All adult transgender people who started HT before 2016 at our gender‐identity clinic were included and were linked to a random population‐based sample of 5 age‐matched reference men and 5 age‐matched reference women per person. Fracture incidence was determined using diagnoses from visits to hospital emergency rooms nationwide between 2013 and 2015. A total of 1089 trans women aged <50 years (mean 38 ± 9 years) and 934 trans women aged ≥50 years (mean 60 ± 8 years) using HT for median 8 (interquartile range [IQR] 3–16) and 19 (IQR 11–29) years, respectively, were included. A total of 2.4% of the trans women aged <50 years had a fracture, whereas 3.0% of the age‐matched reference men  and 1.6% of the age‐matched reference women  experienced a fracture. In trans women aged ≥50 years, 4.4% experienced a fracture compared with 2.4% of the age‐matched reference men  and 4.2% of the age‐matched reference women . A total of 1036 trans men (40 ± 14 years) using HT for median 9 (IQR 2–22) years were included. Fractures occurred in 1.7% of the trans men, 3.0% of the age‐matched reference men , and 2.2% of the age‐matched reference women . In conclusion, fracture risk was higher in older trans women compared with age‐matched reference men. In young trans women, fracture risk tended to be increased compared with age‐matched reference women. Fracture risk was not increased in young trans men. © 2019 The Authors.  Transgender people can receive gender‐affirming hormonal treatment (HT) to change the physical characteristics belonging to their experienced gender. Trans women  receive estrogens to induce feminization, resulting, for example, in breast growthSex steroids also play important roles in the acquisition and homeostasis of bone. In cis (non‐transgender) men, testosterone stimulates periosteal apposition, leading to a wider cortical bone size than in women,Besides changes in physical characteristics in transgender people, HT also influences BMD. Earlier studies found either a maintenancen < 50) or were using questionnaires to define fractures.In clinical practice, there are concerns about bone health in transgender people, particularly regarding the low initial BMD in trans women and the lack of fracture data. A few studies described no increased fracture risk before the start of HT in trans womenTherefore, the aim of this study is to investigate the fracture incidence in a large cohort of adult trans women and trans men after long‐term HT, based on diagnoses from visits to the hospital emergency rooms nationwide, and to compare this incidence with an age‐matched male and female reference population. In addition, we aimed to study whether the types of fractures differed between the transgender population and their age‐matched reference groups and whether BMD or other characteristics were different in the transgender population with fractures compared with those without fractures.This study is part of the Amsterdam Cohort of Gender Dysphoria study,After the diagnostic process, people could start with HT when the diagnosis gender dysphoria was confirmed.The total population of transgender people and their 10 age‐matched references were linked to a database from Statistics Netherlands, which stores all diagnoses made by medical doctors from visits to the hospital emergency rooms nationwide based on Diagnosis‐Treatment‐Combination trajectories (DTCs) for specialized medical care. These DTCs are used to calculate the insurance claim, which is sent to the individual's medical insurance company. Health insurance is obligatory for every inhabitant of the Netherlands. The diagnoses were available for the years 2013, 2014, and 2015.2) of the lumbar spine (LS) were obtained and T‐scores were calculated, based on the birth‐assigned sex reference values of the National Health and Nutrition Examination Survey (NHANES). BMD measurements were available for 77% of the trans women and 84% of the trans men.BMD was regularly measured during patient care at baseline and thereafter every 5 years, independently of the occurrence of fractures. A DXA Hologic Delphi was used, which was updated in July 2004 and replaced in February 2011 by a Hologic Discovery A . For both machines, the coefficient of variation (CV) was <1%. Phantom calibration allowed for comparison of the absolute BMD values. Absolute BMD values  with an interassay CV of 10% and a lower limit of quantitation (LOQ) of 18 pmol/L. Between January 2010 and July 2014, a competitive immunoassay  was used . For conversion, the formula Delfia = 1.267*Diasorin–28.87 was used. Since July 2014, LC–MS/MS  was used  and the formula LC–MS/MS = 1.60*Delfia–29 was used for conversion. Testosterone was measured using a radioimmunoassay  until January 2013 , hereafter a competitive immunoassay  was used . Two formulas were used for conversion: Architect = 1.1*RIA+0.2 for testosterone concentrations <8 nmol/L; Architect = 1.34*RIA–1.65 for testosterone concentrations >8 nmol/L. Luteinizing hormone (LH) was measured using an immunometric assay (Delfia) until June 2011 . After June 2011, an immunometric assay  was used , using the formula Architect = 0.91*Delfia–0.01 for conversion. Mean estradiol, testosterone, and LH concentrations per person were calculated by averaging the results from the measurements performed during HT. Laboratory measurements were available for 66% of the trans women and 72% of the trans men.T‐score of the LS, estradiol concentrations, testosterone concentrations, and LH concentrations were associated with fracture risk, multivariable logistic regression analyses were performed in the transgender population. To protect the anonymity of the population, data are only shown if more than 10 individuals were present in each group. Subgroup analyses were therefore not performed if less than 20 individuals were present in one group. Analyses were performed using STATA Statistical Software , version 14.2.Characteristics of the transgender population are presented as mean with standard deviation (SD), median with interquartile range (IQR), or percentages. First, the fracture incidence was calculated in trans women, trans men, and the age‐matched reference men and women. Thereafter, logistic regression analyses were performed to calculate odds ratios (OR) with 95% confidence intervals (CI), as an approximation of the relative risk for fractures. As age affects the risk of fractures, the trans women group was divided into two groups (<50 years and ≥ 50 years), and the analyses were repeated for both age groups separately. Fractures were divided into two groups: hip, spine, forearm, and humerus fractures , and other fractures.Of the 6793 people who are included in the total cohort, 2726 people were excluded from this study because they did not start with any treatment (yet), 442 started with treatment during adolescence, 15 received alternating testosterone and estradiol treatment, 319 could not be linked to the Statistics Netherlands database , and 232 people were deceased. This led to a total study population of 3059 people, consisting of 2023 trans women and 1036 trans men. The characteristics are shown in Table n = 67) in the 3‐year time period, whereas 2.7% of the age‐matched reference men (n = 275) and 2.8% of the age‐matched reference women (n = 283) had a fracture. The overall fracture incidence was not increased in trans women compared with age‐matched reference men  nor with age‐matched reference women . A total of 41.8% of all fractures in trans women was a hip, spine, forearm, or humerus fracture, compared with 26.6% in age‐matched reference men (p = 0.014) and 36.0% in age‐matched reference women (p = 0.381).Fractures occurred in 3.3% of the trans women (n = 934) had an increased fracture risk  compared with age‐matched reference men aged ≥50 years , but a similar fracture risk compared with age‐matched reference women aged ≥50 years   did not have an increased fracture risk  compared with age‐matched reference men aged <50 years  but tended to have a higher fracture risk compared with age‐matched reference women aged <50 years   were associated with fracture risk. Smoking tended to be associated with a higher fracture risk , whereas mean BMI  and age at start of HT  were not associated with an increased fracture risk. Laboratory measurements were not included in this multivariable analysis because of the smaller number of individuals with laboratory measurements available. However, in univariable analyses, no associations were found between estradiol , testosterone , and LH  concentrations and fracture risk.In Table n = 155) and 2.2% of the age‐matched reference women (n = 114) had a fracture . Because of the smaller number of individuals with laboratory measurements, these were not included in the multivariable analyses. However, in the univariable analyses, it was found that estradiol concentrations were associated with fracture risk , but testosterone  and LH  concentrations were not.Eighteen trans men experienced a fracture 1.7%) in the 3‐year time period, whereas 3.0% of the age‐matched reference men . This is in line with the finding of an earlier study, describing that BMD does not change during long‐term HT.In trans women, lower Trans men had a similar fracture risk compared with age‐matched reference women but a lower risk than age‐matched reference men. Earlier studies found no increased fracture risk,2 in cis women and 25.8 kg/m2 in cis men.This study is the first to investigate the fracture risk in a large population of adult trans women and trans men using long‐term HT. This population was linked to a random sample of 10 age‐matched reference men and women per person, which makes the control population more accurate. The occurrence of fractures was retrieved from the database from Statistics Netherlands, which stores all diagnoses of the visits to the emergency rooms nationwide. As in the Netherlands, everybody with a (suspicion of a) fracture visits the emergency room, so this is a reliable source for fracture data. However, there are also some limitations. First, the time frame for fracture occurrence was only 3 years. Although it is long enough for a point prevalence of fractures, most ideally transgender people would be followed from the moment they start with HT. Second, we did not have any clinical data of the age‐matched reference population besides fracture data. Therefore, no other factors with effect on fracture risk, for example BMD, smoking habits, BMI, and physical activity, could be analyzed in the control groups. However, in a large population‐based study in the Netherlands, it was found that 48% of the cis women and 56% of the cis men are (former) smokers. The mean BMI is 25.6 kg/mIn conclusion, fracture risk was higher in older trans women using long‐term HT compared with age‐matched reference men but similar to age‐matched reference women. In young trans women, fracture risk tended to be increased compared with age‐matched reference women but not compared with age‐matched reference men. Fracture risk was not increased in young trans men using long‐term HT. However, because type of fractures differed in trans women and the transgender population was still young, bone health remains an important health topic, particularly in trans women, and longer follow‐up studies are needed.The authors have no relevant disclosures to declare.