Pulmonary infections are frequent in immunocompromised hosts (ICH), and microbial detection is difficult. As a new method, next‐generation sequencing (NGS) may offer a solution.This study aimed to assess the impact of NGS‐assisted pathogenic detection on the diagnosis, treatment, and outcomes of ICH complicated by pulmonary infection and radiographic evidence of bilateral diffuse lesions.This study enrolled 356 patients with ICH complicated by pulmonary infection that were admitted to Zhongshan Hospital, Fudan University, from November 17, 2017, to November 23, 2018, including 102 and 254 in the NGS and non‐NGS groups, respectively. Clinical characteristics, detection time, rough positive rate, effective positive rate, impact on anti‐infective treatment plan, 30‐day/60‐day mortality, and in‐hospital mortality were compared.P < 0.001), increased positive rate, rate of mixed infection detected, effective positive rate, and proportion of antibiotic treatment modification . The NGS group had a significantly lower 60‐day mortality rate . The difference in the Kaplan–Meier survival curve was significant (P = 0.029). After multivariate logistic regression, NGS‐assisted pathogenic detection remained a significant predictor of survival .NGS‐assisted pathogenic detection reduced detection time (28.2 h [interquartile range (IQR) 25.9–29.83 h] vs. 50.50 h [IQR 47.90–90.91 h], NGS‐assisted pathogenic detection may improve detection efficiency and is associated with better clinical outcomes in these patients. In this study, we discovered that next‐generation sequencing (NGS)‐assisted pathogenic detection may improve detection efficiency and is associated with better clinical outcomes in immunocompromised pulmonary‐infected patients with radiographic evidence of bilateral diffuse lesions. For these patients, pulmonary infection is one of the most frequent and fatal complications.Molecular diagnostic methods, such as polymerase chain reaction (PCR) and next‐generation sequencing (NGS), may provide a solution to this problem. Pathogen sequences can be sorted using deep sequencing and data mining without using a specific primer.22.1This study was conducted at Zhongshan Hospital, Fudan University, a tertiary medical center in Shanghai. Clinical Research Ethics Committee of Zhongshan Hospital, Fudan University  approved this study . This study enrolled consecutive immunocompromised patients between November 17, 2017, and November 23, 2018. Inclusion criteria involved patients: (1) aged ≥16 years old, (2) with pulmonary infection, (3) who required routine standard microbial detection (either blood samples or respiratory tract specimens), and (4) whose pulmonary imaging revealed bilateral diffuse lesions. Immunocompromise was defined in accordance with the hospital‐acquired pneumonia or ventilator‐associated pneumonia (HAP/VAP) guidelines of the Japanese respiratory society 2009.Anti‐infection treatment usually takes 24–48 h to take effect, and it is difficult to determine whether the treatment was effective if patients died before the microbial results or less than 48 h after the microbial results. Therefore, we excluded those who died before the microbial results were reported after 48 h. When comparing the sequence of microbial results and patient death, mycobacteria or negative Aspergillus culture results were not considered. In our hospital, at least 168 h is necessary for a negative Aspergillus culture result, and mycobacteria culture may take approximately 6 weeks. In this study, ICH was required for the timely adjustment of anti‐infection treatment. Some patients may die before these two types of results are obtained, and these results had little effect. Only one HIV‐positive patient was transferred to the Shanghai Public Health Clinical Center after the test, and we could not follow‐up on the outcome. Thus, this patient was excluded.2.2Mycoplasma pneumoniae and Legionella pneumophila, detection of nine main pathogens in the respiratory tract, CMV‐IgG, CMV‐IgM, CMV‐DNA, influenza A/B, and T‐SPOT. Empiric antibiotics were adjusted based on the results of the microbiological tests. For the NGS group, samples were sent to the BGISEQ‐500/100 NGS and conventional pathogenic detection platforms simultaneously, and empiric antibiotics were adjusted later. The follow‐up period was limited to 60 days. Data This was a retrospective study. During the research period, physicians screened patients who met the criteria and asked the research assistants to assess the patients as a group. After obtaining informed consent, patients received free NGS detection . If the patient survived for at least 48 h after the microbial result, the patient was included in the NGS group. For the non‐NGS group, we screened medical records during the research period and selected all patients who met the study's criteria but did not receive NGS detection. Patient baseline data, including age, sex, acute physiology and chronic health evaluation II (APACHE II) score, type of immunosuppression, experimental examination, treatment, length of hospital stay, and survival data, were collected from medical records and electronic databases. In both groups, sputum, BALF, blood, lung tissue, throat swabs, and pleural effusion samples were collected before antibiotic use. In the non‐NGS group, only conventional microbiological methods, including smears and cultures of normal bacteria and fungi, were used. Subsequently, positive cultures were subjected to drug‐sensitivity tests. Samples from suspected cases of mycobacteria were also sent for acid‐fast bacillus testing and mycobacterial culture. Based on clinical features, serological tests and PCR were used in some cases. These tests included 1,3‐β‐D‐glucan, Cryptococcus capsular antigen, G‐lipopolysaccharide, antibodies against 2.3The detection time is the time duration from sample collection to result (Mycobacteria culture and negative Aspergillus culture not included). If there were more than one sample, we recorded the time of the first positive sample or the first sample  for the non‐NGS group, and for the NGS group, we recorded the average time of all the samples sent for NGS detection.An NGS report was considered positive if at least one pathogen was detected that met the following three criteriaEffective positive result is a result required overall consideration of NGS results, traditional microbial results, previous literature, other experiments or imagological examinations, and clinical characteristics by physicians. In this study, we considered an uncertain clinical microbial diagnosis as negative for ease of analysis.Modification of antibiotic treatment (MAT): Antibiotic treatment was adjusted based on the results of microbial detection.2.4t‐test or the Wilcoxon rank‐sum test. Non‐parametrically distributed variables were assessed using chi‐square (χ2) test or Fisher's exact test. The R and C χ2 test and Bonferroni method were used to compare the proportions of different ICH types between the two groups. Univariate and multivariate analyses were performed using logistic regression. The Kaplan–Meier survival analysis was used to compare survival rate between different groups. Statistical significance was set at P < 0.05.Data were analyzed using SPSS 24.0 . For continuous variables, we used a two‐tailed independent Student's 33.1P < 0.001). After further comparison using the Bonferroni method, we discovered the cause of this difference. The proportion of hematological neoplasms was lower in the non‐NGS group , and the proportion of chemotherapy or radiotherapy for solid tumors was higher  , and 356 patients were included in the final analysis . The positive rate, effective positive rate, rate of mixed infection detected, and proportion of modified antibiotic treatment were significantly higher in the NGS group  (Data P < 0.001). In total, 31 types of bacteria (only those with reported evidence of pathogenicity in the lungs), 9 types of fungi, 9 types of viruses, and 2 types of mycobacteria were identified in the NGS group. Pathogens that are frequently detected include Pneumocystis jeroveci (PJ) and cytomegalovirus (CMV). In the non‐NGS group, culture‐positive Candida albicans was the most common pathogen, which was clinically insignificant  Data . In tota3.3C. albicans, and after removing this interference, the proportion declined to 2.15% . The negative predictive value was 81.82% ± 40.45%. Subsequently, we compared NGS and culture results for these double‐positive cases. Match, partly matched, and mismatched cases accounted for 21.51%, 7.53%, and 9.67% of all cases, respectively. Mismatch cases were mostly caused by culture‐positive 15% Data  and S5.3.4P < 0.05). This difference was also significant in Kaplan–Meier curve , invasive ventilation , and APACHE II scores  were risk factors for 60‐day mortality, and NGS detection was a predictor of survival . Subsequently, subgroup analysis was used to identify the appropriate population that benefitted from this detection method in terms of survival , APACHE II score >10 , severe pneumonia , radiotherapy or chemotherapy for malignant tumors , and multidrug resistant infection .There was a significant difference in 30‐/60‐day and in‐hospital mortality between the NGS and traditional detection groups  may benefit more. However, this study had several limitations. First, it was a non‐randomized clinical trial single‐center study, population size was not very large and patients were not enrolled prospectively. Second, not all patients in the NGS group underwent NGS detection for blood samples. Third, NGS detection in this study only covered DNA, thus eliminating potential viruses. This study provides strong evidence to justify further studies, including randomized trials, to determine whether NGS can improve clinical decision‐making and subsequent outcomes in ICH with pulmonary infection.The authors have no conflict of interest to declare.This study was approved by the Clinical Research Ethics Committee of Zhongshan Hospital, Fudan University   and informed consent was obtained from every participant. Informed consent was obtained from individual or guardian participants.DH Z, SJ C, JJ J, and YL S designed the study and the idea of this article; SJ C, DN H, DH Z, and JJ J enrolled patients; CC C, LL W, XJ T, XY C, L T, and YY Z collected data; DH Z, SJ C, and Y W conducted statistics and analysis of results; DH Z and Y W also conducted manuscript writing and editing; SJ C, JJ J, and YL S revised and corrected the manuscript.Data S1. Supporting InformationClick here for additional data file.Data S2. Supporting InformationClick here for additional data file.Data S3. Supporting InformationClick here for additional data file.Data S4. Supporting InformationClick here for additional data file.Data S5. Supporting InformationClick here for additional data file.


Smoking is highly prevalent among patients with anxiety disorders. Previous studies suggest that smokers show altered fear learning as compared to non-smokers. To test the effect of acute smoking on fear learning and generalization, we conducted a fear learning experiment online. 202 healthy subjects learned to differentiate a danger and a safe cue on day 1 and were tested for generalization of threat responses 24 h later. To see if the timing of smoking impacts fear learning, we formed three smoker groups with manipulations of acute smoking and withdrawal at different time-points (each group: n = 46) and one non-smoker control group (n = 64). Smoking manipulations contained a 6 h withdrawal after fear learning, smoking directly before or after fear learning. We found no group differences between smoker manipulation groups for fear learning or generalization. However, we found differences in fear generalization between smokers and non-smokers. Smokers showed increased fear ratings towards the stimulus that has been learned as safe and higher US expectancy to stimuli similar to the safe stimulus, when compared to non-smokers. Smoking might constitute a risk factor for impaired discrimination between danger and safety and smoking restrictions could be an effective way to reduce the risks of development or maintenance of anxiety disorders. Patients suffering from AD, similar to other patients with psychiatric disorders, are more likely to smoke compared to healthy individuals 3. Furthermore, symptom severity in patients with posttraumatic stress disorder (PTSD) was positively correlated with the extent of nicotine dependence5. But not only patients with AD are affected by the influence of smoking on maladaptive responses to threats. Isensee et al. conducted a prospective longitudinal study that found a higher risk for the onsets of panic attacks in healthy individuals that smoked when compared to non-smoking individuals6.Anxiety disorders (AD) are among the most frequent mental disordersWhile being a smoker seems to increase the risks of maladaptive aversive learning, it is an open question how acute smoking affects associative aversive learning mechanisms and might drive maladaptive responses to threats.7. Associative learning of threat responses in the laboratory is commonly examined using classical fear conditioning protocols. When employing differential fear conditioning, a conditioned stimulus (CS+) is predictive for an aversive unconditioned stimulus (US), whereas another conditioned stimulus (CS−) is not. Subjects learn the differential prediction of the two CSs for the US and express conditioned threat responses to the CS+ in comparison to the CS−. The CS− is learned as a safety stimulus and it is therefore adaptive to inhibit conditioned threat responses to the CS−9.It is assumed that one central mechanisms for the development of AD is  aversive associative learning, when confronted with threatsTransfer of learned threat responses to novel objects can be very useful for coping with changing environments. Such transfer can be observed as generalization and therefore includes expression of threat responses to stimuli that resemble the CS+ and inhibition of responses to stimuli that are similar to the CS−. Such generalization can be examined across a gradient of stimuli between the CS+ and the CS−. A shallow generalization gradient indicates a stronger generalization between stimuli, whereas a steeper generalization gradient indicates a stronger discrimination between stimuli.10) have been reported in patients diagnosed with Generalized anxiety disorder (GAD)11.Disproportionate threat responses to stimuli that resemble the CS+  on conditioned threat responses in mice. In particular, acute nicotine administration increased responses to conditioned cues and contexts, relative to saline injections14. Another study showed that smokers, as compared to non-smokers, had an impaired differentiation between danger and safety context when retrieving of conditioned threat memories15. While these studies underline that smokers show a deficit in safety learning, they cannot, however, delineate how acute smoking before or after learning might drive later deficits in retrieving safety information.There is further translational evidence that animal studies of chronic nicotine administration might resemble effects of smoking on threat learning in human individuals. Kutlu et al. found that mice show a reduced discrimination between CS+ and CS− during threat learning (nicotine in a chronic schedule), which was mirrored by lower CS discrimination in humans that were smokers17. With this study, we want to provide a deeper understanding of the effects of acute smoking, when comparing fear acquisition between smokers and non-smokers. Further, a generalization task should clarify if a disruption of safety learning transfers to novel stimuli. We expected that acute smoking before or after fear acquisition would lead to an impaired safety learning in fear acquisition and generalization, when compared to individuals restricted from smoking. Furthermore, we expected a deficit of safety learning in smokers, when compared to non-smokers.To this end, we employed an online experiment entailing a differential threat conditioning protocol and a generalization task (24 h later)In order to establish that subjects learn to discriminate between CS+ and CS− during acquisition training, we examined US expectancy and fear ratings towards the CS+ , when compared to the CS−. We expected this pattern to be disrupted in regard to safety learning in groups that were acutely smoking before acquisition training and in general, when comparing smokers to non-smokers.p < 0.001) with higher US expectancy for the CS+ as compared to the CS−   with an overall increasing US expectancy from block 1 to block 2  and a stimulus by block interaction  = 76.523, p < 0.001). The interaction consisted of higher differentiation between the CS+ and the CS− in block 2 when compared to block 1 (t(1989) = 5.86, pcorr < 0.001) as well as in block 3 when compared to block 2 (t(1990) = 4.543, pcorr < 0.001). Additionally, we found a block by group interaction  = 2.394, p < 0.026), but follow-up post-hoc tests revealed no group differences.Participants learned to predict the US by the presence of the CS+ , indicated by a main effect of stimulus  = 46.857, ,4376.7 =p = 0.064), but follow-up post-hoc tests revealed no differences. We found a main effect of stimulus  = 46.657, p < 0.001) with higher US expectancy for the CS+  as compared to the CS−  with an increasing US expectancy from block 1 to block 2  and a stimulus by block interaction  = 76.194, p < 0.001). The interaction consisted of higher differentiation between the CS+ and the CS− in block 2 when compared to block 1 (t(1992) = 15.919, pcorr < 0.001) as well as in block 3 when compared to block 2 (t(1995) = 4.992, pcorr < 0.001).When we compared smokers against non-smoking individuals, we found a trend towards a stimulus by block by group interaction  = 2.75, imulus  and CS+ as compared to the CS− (t(804) = 9.005, pcorr < 0.001)  with an overall increase in fear ratings from pre ACQ to post ACQ (pre-post: t(804) = − 7.253, pcorr < 0.001) and a stimulus by time interaction  = 132.4, p < 0.001). The interaction consisted of higher differentiation between the CS+ and the CS− post ACQ when compared to pre ACQ (t(402) = 10.168, pcorr < 0.001). Additionally we found a main effect of group  = 2.701, p = 0.047), but follow-up post-hoc tests revealed no differences.Participants rated higher fear for the CS+ as compared to the CS−  = 75.554, ,197 = 75p < 0.006) that indicated increased fear ratings in the smoker group, when compared to the non-smoker group (t(804) = 2.79, pcorr = 0.005; see Fig. p < 0.001) with higher fear ratings for the CS+ as compared to the CS− (t(804) = 9.005, pcorr < 0.001). Furthermore, we found a main effect of time  = 78.511, p < 0.001) with an increase in fear ratings from pre ACQ to post ACQ (pre–post: t(804) = − 7.253, pcorr < 0.001) and a stimulus by time interaction  = 134.803, p < 0.001) .When comparing smokers to non-smokers, we found a main effect of group  = 7.754, ,199 = 7.We found that smokers show a generally increased fear rating during fear acquisition, when compared to non-smokers. Against our hypotheses, we did not find any group differences between smoking manipulation groups.To test for transfer of threat responses to the novel generalized stimuli, we employed a generalization in which we presented a gradient of new stimuli between the CS+ and the CS−. Now no stimulus was predictive for a US. We expected that retrieval of learned safety information  is altered in groups that were acutely smoking before and after acquisition training and in general, when compared to non-smokers.p < 0.001). Furthermore, participants rated lower US expectancy for the CS- as compared to each generalization-stimuli from GS7 to CS+  with a decrease of US expectancy from block 1 to block 2 , which is likely an effect of no US presentation during this phase (resembling extinction training).Participants rated higher US expectancy for the CS+ as compared to each generalization-stimuli from GS3 to the CS−  = 20.601, p < 0.001) with higher US expectancy to the CS + like in comparison to novel stimuli  and higher US expectancy when comparing novel stimuli to CS− like stimuli . We found a main effect of block  = 21.18, p < 0.001) with a decreasing US expectancy from block 1 to block 2 , as in the previous model. Additionally we found a stimulus group by block interaction  = 3.4, p = 0.03) that was characterized by a decrease of US expectancy for each stimulus group decreasing from block 1 to block 2 .During the generalization test, we found that participants generalized their US expectancy to stimuli that resembled the CS+ and the CS-. Hence, we could identify two generalization groups of stimuli: Stimuli that were “CS+ like” ) and “CS− like” ). Additionally, we identified a third group of stimuli that was different from both, the CS+ and the CS− and hence ambiguous stimuli (GS4–GS7). For grouping these stimuli we used solely non-smoker US expectancy ratings (for details see supplementary methods). Thereby, we defined how stimuli would be grouped in a “control” population. When using these generalization groups of stimuli in the mixed-model, we found a main effect of stimulus  = 77.01, p < 0.001) with higher US expectancy for the CS+ as compared to each generalization stimulus that ranged from GS3 to CS− (estimates > 0.517) and lower US expectancy for the CS− as compared to each generalization stimulus that ranged from CS+ to GS7  with a decrease of US expectancy from block 1 to block 2 . When grouping the stimuli as CS+ like, CS− like and novel, we found an interaction for stimulus by group  = 3.37, p = 0.035). The following post-hoc test revealed a trend towards an increased US expectancy rating in the smoker group when compared to the non-smokers for the CS− like stimulus group .We found a stimulus main effect  20.703, 614.6 20.p < 0.001) with higher fear ratings for the CS+ as compared to the CS− (t(806) = 10.901, pcorr < 0.001)  with a decrease in fear ratings from pre generalization test to post generalization test (pre–post: t(806) = 3.35, pcorr < 0.001). Additionally, we found a stimulus by time interaction  = 11.791, p < 0.001). The interaction consisted of higher differentiation between the CS+ and the CS− pre generalization test when compared to post generalization test (t(402) = 2.6, pcorr = 0.01).We found a stimulus main effect  = 75.745, 01) Fig. c. Furthep < 0.001) with higher fear ratings for the CS+ as compared to the CS− (t(806) = 10.901, pcorr < 0.001). Furthermore, we found a main effect of time  = 23.920, p < 0.001) with a decrease in fear ratings from pre generalization test to post generalization test (pre–post: t(806) = 3.35, pcorr < 0.001). We found a stimulus by time interaction  = 10.109, p = 0.002). The interaction consisted of higher differentiation between the CS+ and the CS− pre generalization test when compared to post generalization test (t(402) = 2.6, pcorr = 0.01) . An independent samples t-test revealed that the non-smoker group rated lower fear compared to the smoker group after the experiment towards the CS− (t(200) = − 2.857, pcorr = 0.02).We found a stimulus main effect  = 75.013, 00 = 75.0We found that smokers show an increased fear rating towards the safety cue (CS−) after fear generalization, when compared to non-smokers. Furthermore, we found a trend towards an increased US expectancy in CS- like stimuli in smokers, when compared to non-smokers. Again, we found no difference between groups that were acutely smoking before acquisition training or not.14. The experiments in rodents further suggest that nicotine administration throughout fear acquisition and extinction delayed safety learning and inhibition of conditioned threat responses during extinction training18. Additionally, the translation of this finding to humans revealed reduced CS-discrimination in smokers when compared to non-smokers, along with reduced CS-discrimination in mice14. Our finding that smokers show an impairment in retrieving safety information is further in line with a previous study that indicated impaired contextual inhibition in a safe context in smokers when compared to non-smokers15. Hence, our results pinpoint the influence of smoking to increased fear ratings and US expectancy ratings towards stimuli that have been learned as safe.Our results indicate a difference in fear learning and fear generalization between smokers and non-smokers that is not affected by acute smoking before or after acquisition training. Smokers show increased fear ratings towards the CS− after the generalization test when compared to non-smokers. Additionally, we found a trend to an increased US expectancy towards stimuli that were generalized as the CS− (CS− like stimuli) in smokers, when compared to non-smokers. Our results thereby suggest that safety learning processes in smokers might be impaired and that this impairment is even transferred to novel stimuli. Interestingly, we found these differences between smokers and non-smokers in a situation that required retrieval of safety information , but not during learning . Our results are in line with findings from chronic nicotine administration in mice, which indicated increased freezing responses towards the CS−Against our hypothesis, we did not find an effect of any of our interventions on acute smoking  and even withdrawal  on fear learning or generalization. We furthermore could not find differences in aversive learning or the generalization test with respect to withdrawal symptoms or nicotine dependency between smokers (for details see supplement).19; see for no difference of trait anxiety between smokers and non-smokers:20).As a main effect, smokers showed generally increased fear ratings when compared to non-smokers, but we found no main group differences in the US expectancy or anxious temperament (STAI-trait anxiety). This indicates that there is no support for increased trait anxiety in smokers in our sample when compared to non-smokers (for details see supplement). Previous studies have found inconsistent results on whether smoking influences trait anxiety in humans  to a stimulus that was learned safe (CS−) when compared to non-smokers. This effect in smokers could be linked to maladaptive threat responses that are observed in individuals that suffer from pathological anxiety. Previous meta-analyses found that patients with anxiety-related disorders show an increased fear response during fear acquisition towards the CS− when compared to healthy controls22. Hence, individuals that might be diagnosed with AD or exhibit other symptomatology that involves impaired safety learning might also benefit from smoking cessation programs.One interesting aspect from our results might be relevant for the prevention and treatment of pathological anxiety: We would advocate to promote smoking cessation programs in order to reduce the risk of maladaptive threat responses in the long run. Our results support no effect of smoking restriction and withdrawal symptoms on threat responses. Hence, the process of quitting should not lead to exaggerated threat responses, per se. In fact, clinical studies that employed a smoking cessation treatment in parallel to mental health care for PTSD patients reported high rates of smoking abstinence and successful reduction of PTSD symptomsOur results have several limitations. As this is an online study, there is an inherently reduced control of the participants with respect to their adherence to the study protocol (i.e. smoking manipulations). We informed the participants that there are no consequences if they for example could not fulfil the 6 h smoke break, but we encouraged them to honestly report if they managed to restrict smoking for 6 h, or not. Several participants reported that they have not followed instruction and were regrouped. This might seem like a big disadvantage of an online study, but it also provides a chance to investigate participants at home in their usual smoking environment. Most participants also followed the timeframe instructions of 24 h between day 1 and day 2 very precisely, which indicates a general adherence to instructions.In sum, we found that smoking leads to increased fear responses towards the safety stimulus during and after the generalization test. No group differences were found during fear acquisition. Manipulations acute smoking and withdrawal at different time-points seem to make no difference in aversive learning, however the crucial point is if a person is a smoker or not. Smoking therefore might be considered a risk factor for impaired safety learning and ultimately enhances the individual development or maintenance of pathological anxiety. However, further investigations are needed to specify the causal effect of smoking and its active ingredient nicotine on fear learning in humans. Nevertheless, one clear recommendation for the reduction of the risk to develop maladaptive threat responses is to quit smoking.For this online study 273 participants were recruited online. Healthy individuals between 18 and 65 years with no self-reported diagnoses of neuropsychiatric disorders, who consume less than 15 units alcohol per week and no illegal drugs could participate. The final sample for analysis consisted of 202 subjects  served as conditioned Stimuli (CS). CS1 and CS2 were counterbalanced as CS+ or CS−. For the Generalization test, additional eight generalized stimuli (GS2-–GS9) with an increasing 15% ring size between CS1 and CS2 were presented23 that were rated as unpleasant  were chosen as unconditioned Stimuli (US) that followed upon the CS+ . Three different pictures that were rated neutral  were chosen as neutral US (nUS) that followed upon the CS−.Three pictures from the International affective picture system (IAPS) databasewww.soscisurvey.de25. Directly after completing the questionnaires, participants started the behavioural experiment.The study took place on 2 consecutive days with a temporal difference of 24 h (± 6 h). On the first day participants filled out a questionnaire containing a Fagerström test for nicotine dependence (FTND) and the State-Trait Anxiety Inventory (STAI-S/STAI-T) and gave information on age, sex, alcohol and coffee consumption and smoking habit. Questionnaires were completed on The experiment on day 1 contained a habituation phase in which the CS+ and CS− were presented once without being followed by the US/nUS. Day 1 further entailed an acquisition phase with three blocks, each consisting of four CS+ and four CS− presentations. Blocks were presented randomized. The CS+ presentation was followed by a US picture in nine out of twelve trials (75% reinforcement rate). Similarly, a nUS picture followed in 75% of the CS− trials. In 25% of the trials, the CSs faded out without US/nUS presentation. Each trial started with a 7 s CS presentation that was followed by a 3 s US/nUS presentation and ended with an ITI presentation (jittered between four to six seconds) Fig. a.26. On the second day participants started again with a questionnaire containing STAI-S and a report on their overnight sleep. If the participant was sorted into the second group, they additionally answered if they managed to take a smoking break of 6 h after the acquisition and if not, when they started smoking again. Those participants were also asked if they noticed any withdrawal symptoms between day 1 and day 2.Behavioural experiments were completed with PsychoPy3Similar to the day before, participants started the behavioural experiment after finishing the questionnaires. The experiment on day 2 contained the generalization test with two blocks including one CS+ and one CS− presentation, as well as one GS2 to GS9 each. That concludes to ten trials per block, which were presented in random order. No CS or GS was followed by a US/nUS picture Fig. b. The exParticipants rated their fear when confronted with CS+ and CS− on a continuous scale between 1 (no fear/stress) and 10 (very much fear/stress) before and after the acquisition phase on day 1, as well as before and after the generalization test on day 2.On both days, participants rated their US expectancy on each trial (two to six seconds after CS onset) on a continuous scale from 1 (I don’t expect an unpleasant picture) to 10 (I definitely expect an unpleasant picture).After generalization test and fear rating participants were asked about how unpleasant they perceived the US/nUS photos on a continuous scale from 1 (not unpleasant) to 10 (very unpleasant) , blocks (one to three) and groups  (lmer (RatingResults ~ (1|participants) + stimuli*block*group)).Then an F-test with a Kenward-Roger approximation for degrees of freedom was performed in the form of an ANOVA type 3 calculation28. To further test the results estimated marginal means (EMMs) were computed using the emmeans package as post-hoc tests and p-values were corrected for multiple comparisons using Bonferroni-Holms method. Results with z-ratio are asymptotic results.For analysis of the US expectancy we calculated linear mixed effect models in R using lme4 packageFear ratings were analysed in Jasp using a repeated-measures ANOVA type 3 with repeated measures factors CS-type and time-point, as well as the between subject factor group. Follow-up tests were calculated by independent sample t-tests and were Bonferroni-Holm corrected.Supplementary Information.


Liver cancer is one of the most deadly and prevalent cancers. A routine follow‐up plan for liver cancer is crucial but limited. In the present study, we aimed to disclose possible risk factors and critical survival time windows for primary liver cancer.We enrolled 692 liver cancer patients from Sun Yat‐sen University Cancer Center (SYSUCC). Univariate and multivariate logistic regression analyses of cirrhosis and recurrence were conducted. A meta‐analysis was utilized to validate an indication of creatinine (CRE) in recurrence. Conditional survival analysis was performed using the Kaplan–Meier method. The results were further verified by the SYSUCC validation cohort and Surveillance, Epidemiology, and End Results (SEER) validation cohort.Our results indicated that A/G, history of hepatitis, history of alcohol consumption and platelet (PLT) might be potential prognostic factors for cirrhosis in liver cancer patients. CRE was significantly correlated with recurrence due to various therapies, especially after transarterial embolization. Moreover, 1.5 years to 2 years may be a critical time window for deterioration in survival rate based on the conditional survival analysis.A/G, history of hepatitis, alcohol consumption and PLT may be potential prognostic factors for cirrhosis in liver cancer patients. More attention should be focused on the renal function when treating the patients due to the significant role of CRE. 1.5 years to 2 years is a critical time window for deterioration in survival rate for liver cancer patients that contributes to determining the optimal follow‐up plan in the future. A/G, history of hepatitis, history of alcohol consumption and PLT may be potential prognostic factors for cirrhosis in liver cancer patients. CRE is a significant factor in recurrence due to various therapies, especially transarterial embolization, which suggests more attention in renal function. 1.5 years to 2 years is a critical time window for deterioration in survival rate for liver cancer patients, which may contribute to the determination of the optimal follow‐up plan in the future.  Liver cancer is one of the most deadly and prevalent cancers, with approximately 906,000 new cases and 830,000 deaths in 2020, ranking fifth in global incidence.A routine follow‐up plan is vital in liver cancer. It has been suggested that regular follow‐up improves patient prognosis.Currently, survival estimates are typically stratified through interrelated risk factors, such as tumor size, lymph nodes, and family history. As in many other malignancies, liver cancer patients have shown higher hazard rates for death in the first few years followed by decreases over time.Aiming to describe the short‐term and long‐term survival characteristics, we conducted a retrospective study concerning pathologically diagnosed primary liver cancer patients. Primary liver cancer patients from Sun Yat‐sen University Cancer Center (SYSUCC) were enrolled in our study. Univariate and multivariate logistic regression analyses of cirrhosis and recurrence were conducted. To further validate an indication of creatinine (CRE) in recurrence, we utilized a related meta‐analysis. Conditional survival analysis was performed using the Kaplan–Meier method. The results were verified by the SYSUCC validation cohort and Surveillance, Epidemiology, and End Results (SEER) validation cohort Figure .22.1www.seer.cancer.gov) as another validation cohort. In addition, we conducted a meta‐study for the logistic regression analysis, including 1964 patients derived from the PubMed database (https://pubmed.ncbi.nlm.nih.gov/) and Embase database (https://www.embase.com/).This study was approved by the SYSUCC. We retrospectively identified 1895 liver cancer patients from SYSUCC. Patients were excluded if they had missing data for the clinical and pathological characteristics, including age, sex, family cancer history, TNM stage, survival status, AFP, carcinoembryonic antigen (CEA), or other critical information. A total of 692 patients pathologically diagnosed with liver cancer were included in our population. According to the comparability of the samples, we divided the patients into a validation set and a training set. For further verification, 29,521 liver cancer patients with complete survival status and survival time were selected from the SEER database (2.2http://www.r‐project.org/). We analyzed the association between CS and other outcomes, such as cirrhosis, relapse and other clinicopathological characteristics, to identify predictors adjusted for age, first age (age at diagnosis), sex, family cancer history, cirrhosis, treatments, tumor size, lymph node ratio and laboratory test results, including CEA, AFP, platelet (PLT), CRE, albumin–globulin ratio (A/G), glutamyl transpeptidase, glucose, triglyceride (TG), aspartate transaminase (AST), alanine transaminase (ALT), and AST/ALT. Univariate and multivariate logistic analyses were conducted to explore cirrhosis in liver cancer patients. Based on different periods of patients at 3 months, 6 months, 9 months, 1 year, 3 years, 5 years, and 7 years, conditional univariate and multivariate logistic analyses were utilized to assess potential risk factors for recurrence.All statistical analyses were conducted in R software (version 4.0.5) , and “creatinine” . The references were also checked for articles that may correlate with our study.2.3.2The inclusion criteria for the meta‐analysis were as follows: (1) patients with pathologically confirmed primary liver cancer; (2) CRE measured in serum‐based methods; and (3) research demonstrated the correlation between CRE and recurrence as reported by disease‐free survival (DFS) or relapse‐free survival (RFS). The exclusion criteria for the meta‐analysis were as follows: (1) abstracts, letters, reviews, case reports, animal studies, or other nonclinical studies; (2) articles not written in English; (3) studies lacking sufficient information, such as the hazard ratio (HR) and 95% confidence interval (CI); and (4) duplicate data or repeat analysis.2.4All articles first included were assessed and extracted by two independent authors (W.L. and W.H.). The HR and CI of CRE in RFS or DFS were extracted from the abstracts or full‐text reviews. Disagreement on article selection was discussed until a third author reached a consensus (H.Q.). The following items were recorded for each study: first author, year of publication, country, the total number of cases, gender, follow‐ups, and HRs with 95% CIs. The Newcastle–Ottawa Scale (NOS) was then applied to evaluate the quality of the selected studies.2.5α|β) = S(α + β)/S(β). CS predicts the probability of additional α‐year survivorship for those who have already survived β years after the time of observation. In our study, CS was conducted using the survival and survminer R packages in the training and validation cohorts, including the samples from the SEER database. To further investigate the time point at which the CS probability dramatically changed, 6 months, 1 year, 2 years, 3 years, and 4 years were selected as additional observational ending times. The crude death rate (CDR) was also calculated to compare deaths over time.Originating from the concept of conditional likelihood in biostatistics by Henson and Ries,To evaluate the role of clinical characteristics in conditional survival, we classified different subgroups by potentially significant factors. Patients were divided into subgroups according to A/G, AFP, age, ALT, AST, AST/ALT, CEA, CRE, first age, sex, hepatitis, metastasis, PLT, TG, or treatments. Kaplan–Meier analyses were then performed based on the identified subgroups.33.1Among the 692 patients included, the median age was 60 in the 3‐month group, 6‐month group, 9‐month group, and 1‐year group, while the median age was 61 in the 3‐year group, 63.5 in the 5‐year group, and 66 in the 7‐year group, respectively (Table 3.2p ≤ 0.1) were exposed to multivariate logistic regression analysis. All the regression analysis results of cirrhosis were adapted to construct the nomogram , history of hepatitis (p < 0.001 for univariate logistic regression and multivariate logistic regression), history of alcohol consumption (p = 0.040 for univariate logistic regression and p = 0.020 for multivariate logistic regression), and PLT (p < 0.001 for univariate logistic regression and multivariate logistic regression) were found to be potentially associated with the outcome of liver cirrhosis. Further subgroup analysis suggested that a history of alcohol consumption was more closely associated with cirrhosis in older patients (age ≥45), while it was not significant in younger patients . Moreover, A/G, history of hepatitis, and PLT were indicated as possible prognostic factors for cirrhosis after the age of 45. Hence, these findings suggested that there are different potential indicators of prognosis at different ages.From the nomogram, A/G (p = 0.032 at 0–3 months and 3–6 months), which was also accompanied by metastasis , we did not continue to analyze the recurrence using a standard method.3.4We assessed the CS statuses at 0–1 year, 1–3 years, 3–5 years, and 5–7 years. A total of 692 patients were divided into a training cohort and a validation cohort. A significant decline was observed in the survival curve at 1–3 years, and this trend was partially rescued at 3–7 years, indicating that liver cancer patient survival may deteriorate within 1–3 years Figure . The CDRTo identify a more accurate time window for potential deterioration of liver cancer, we subdivided the different survival times of all patients  and then conducted a CS analysis at different time points. The results indicated that the survival probability significantly decreased between 1.5 and 2 years after treatment according to the survival curve Figure  as the CTo elucidate potential factors involved in the 1.5–2 years deterioration time window, we conducted subgroup survival analysis with different clinical characteristics Table . Accordip < 0.001), 1–2 years (p = 0.002), and 2–3 years (p = 0.002). A/G demonstrated an opposite trend at 0–1 year (p = 0.019), 1–2 years (p < 0.001), and 2–3 years (p = 0.008). However, there was no noticeable difference for single ALT in each stage (data not shown), while single AST was predominantly upregulated at 0–1 year (p = 0.002). Nevertheless, the DeRitis ratio, which is defined as the ratio of AST to ALT, was significantly upregulated in the 0–1 year (p = 0.028) and 1–2 year stages (p = 0.011)  have cirrhosis at the same time as liver cancer. PLT and other liver function factors should be further evaluated to guide treatment options for younger patients.We also illustrated the potential relationship between CRE and liver cancer recurrence. Numerous studies have explored the underlying mechanism but failed to reach a consistent conclusion. Faillaci et al. demonstrated that CRE does not correlate with relapse in hepatocellular cancer patients after direct‐acting antiviral treatment.Because conventional actuarial OS estimates rely exclusively on static factors determined around the time of surgery, CS analysis sheds new light on a better assessment of survival time at each follow‐up. CS analysis has been widely applied in the analysis of renal cell carcinoma,According to more than 10 years of experience at the University of Bologna,The present study had several limitations. First, the present study was susceptible to biases because all the analyses were conducted based on retrospective data. Moreover, only a small number of pathologically diagnosed samples were included in the present study, and metastasis was not investigated due to the limited number of patients. In addition, other potential factors, such as comorbidities, were not included. The relationship between endogenous CRE clearance and recurrence of liver cancer was not evaluated due to the lack of information. In addition, we did not further investigate the patients regarding treatment modalities, which will be explored in the future.Despite these limitations, our results indicated that A/G level, history of hepatitis, alcohol consumption, and PLT are potentially associated with liver cirrhosis when considering age. Moreover, CRE may be significantly correlated with the outcome of recurrence in primary liver cancer in the first 6 months after treatment, especially after transarterial embolization. Our results also suggested a potentially critical time window for deterioration in survival rate based on the CS analysis, which may contribute to the determination of the optimal follow‐up plan in the future.None of the authors has personal or financial conflict of interest to declare in relation to this publication.Jingdun Xie and Weiqiang Zhong conceived and designed most of the project. Zhonglian He, Zhongguo Zhou, and Weian Zeng collected clinic samples, Weicheng Lu, Weifeng Hong, and Haibo Qiu conducted experiments and analyzed the data. Weicheng Lu and Weifeng Hong organized the figures and tables. All authors wrote the manuscript together and approved the final manuscript.This study was approved by the ethics committee of Sun Yat‐sen University Cancer Center (RDDA2021594509).Figure S1Click here for additional data file.Figure S2Click here for additional data file.Figure S3Click here for additional data file.Table S1Click here for additional data file.


Euglena gracilis is widely used in the food, cosmetics and feed industries  and myristyl alcohol (C14:0)  was generated using Fe‐ion beam irradiation. However, M3−ZFeL grew slower and produced less lipids than the wild type (WT), suggesting that the mutagenesis caused undesirable side mutations  genes in E. gracilis to generate non‐motile strains. We identified the genes encoding proteins homologous to Caenorhabditis elegans BBS‐7  or BBS‐8 . These BBSome components are associated with the intraflagellar transport of particles and mediate the trafficking of cilium/flagellum membrane proteins in eukaryotic cells ‐based genome‐editing technique , which are useful for inducing the stable non‐motility phenotype in E. gracilis . To establish clonal bbs strains, we isolated two cell lines each for bbs7 and bbs8  at 7 days after culture initiation (Figure bbs mutants and WT in terms of biomass harvested at 7 days after culture initiation or for the lipid content of cells under aerobic or hypoxic conditions (Figure bbs mutants than in the WT (Figure EgBBS genes that facilitate sedimentation do not negatively affect the production of biomass or high‐value products.We also examined the growth, biomass, paramylon content and lipid content of WT and the s Method . Using tn Figure . We did s Figure . InteresT Figure , which mbbs mutants to be 32–38% higher than that of the WT (Figure EgBBS genes in E. gracilis could improve harvesting efficiency without negatively affecting productivity.During the mass cultivation of microalgae, harvesting accounts for 20–30% of total production costs; therefore, improving harvesting procedures will enhance the economic viability of microalgal biomass production (Brennan and Owende, T Figure , while aT Figure , aerobicThis study was partially supported by a matching fund‐based research programme between RIKEN and euglena Co., Ltd.MI, TN and ST contributed equally to this work. MI, TN, KY and ST conceived the study and designed the experiments. MI, TN, ST, KO, TS, TK and KH performed experiments and analysed the data. KM and KS supervised the project. KM and MI wrote the manuscript. All authors read and approved the final manuscript.LC644194, LC644196–LC644198, LC644202 Method .Method S1Euglena gracilis genome editing.Method S2 Genotyping of bbs mutants.Method S3 Microscopy observations.Method S4 Quantitative motion analysis.Method S5 Sedimentation analysis.Method S6 Growth, biomass, paramylon content, and lipid contents.Table S1 Oligos used in this study.Click here for additional data file.


Pseudomonas putida donor and recipient strains with plasmid pKJK5::gfpmut3b and mathematical modeling, we here demonstrate that the presence of MWCNTs leads to increased plasmid transfer rates in a concentration-dependent manner. The percentage of transconjugants per recipient significantly increased from 0.21 ± 0.04% in absence to 0.41 ± 0.09% at 10 mg L−1 MWCNTs. Similar trends were observed when using an Escherichia coli donor hosting plasmid pB10. The identified mechanism underlying the observed dynamics was the agglomeration of MWCNTs. A significantly increased number of particles with >6 μm diameter was detected in the presence of MWCNTs, which can in turn provide novel surfaces for bacterial interactions between donor and recipient cells after colonization. Fluorescence microscopy confirmed that MWCNT agglomerates were indeed covered in biofilms that contained donor bacteria as well as elevated numbers of green fluorescent transconjugant cells containing the plasmid. Consequently, MWCNTs provide bacteria with novel surfaces for intense cell-to-cell interactions in biofilms and can promote bacterial plasmid transfer, hence potentially elevating the spread of antimicrobial resistance.Multiwalled carbon nanotubes (MWCNTs) regularly enter aquatic environments due to their ubiquity in consumer products and engineering applications. However, the effects of MWCNT pollution on the environmental microbiome are poorly understood. Here, we evaluated whether these carbon nanoparticles can elevate the spread of antimicrobial resistance by promoting bacterial plasmid transfer, which has previously been observed for copper nanomaterials with antimicrobial properties as well as for microplastics. Through a combination of experimental liquid mating assays between IMPORTANCE In recent decades, the use of carbon nanoparticles, especially multiwalled carbon nanotubes (MWCNTs), in a variety of products and engineering applications has been growing exponentially. As a result, MWCNT pollution into environmental compartments has been increasing. We here demonstrate that the exposure to MWCNTs can affect bacterial plasmid transfer rates in aquatic environments, an important process connected to the spread of antimicrobial resistance genes in microbial communities. This is mechanistically explained by the ability of MWCNTs to form bigger agglomerates, hence providing novel surfaces for bacterial interactions. Consequently, increasing pollution with MWCNTs has the potential to elevate the ongoing spread of antimicrobial resistance, a major threat to human health in the 21st century. They ar2–−1 , 7. Stil−1 . This isChlorella vulgaris cell walls resulted in shading effects and the inhibition of photosynthetic activity due to lower light availability  in activated sludge sequencing batch bioreactors , with thThis hypothesis is based on previous reports that the exposure to certain nano- and microparticles can indeed affect bacterial plasmid transfer. For example, copper nanoparticles were able to promote horizontal plasmid transfer at environmentally relevant concentrations mainly due to causing an overproduction in ROS in the exposed bacteria . This lePseudomonas putida KT2440 served as the bacterial plasmid donor and recipient strain and was exposed to different concentrations of MWCNTs. We further tested if either of the proposed mechanisms, overproduction of ROS or providing novel surfaces, could play a role in the effects of MWCNTs on bacterial plasmid transfer.To test our hypothesis that MWCNTs affect bacterial plasmid transfer, we here combined experimental plasmid transfer assays with mathematical modeling of plasmid transfer dynamics. 6 cells/mL to 3.09 ± 1.10 × 108 mL−1 (P. putida donor of pKJK5) and 5.61 ± 1.02 × 108 mL−1 (P. putida recipient), respectively .Within the 24 h of incubation, bacterial densities increased in the control without MWCNT from initially ∼10ectively . The preEscherichia coli donor or the P. putida recipient   . Consequrs = 0.66603, P < 0.001 of Spearman’s rho being zero; 6 mL−1 in the absence of MWCNTs to 2.28 ± 0.64 × 106 mL−1 at 10 mg L−1 MWCNTs. The concentration-response behavior held true when normalizing the absolute number of transconjugants to the number of recipient cells  and the growth rate constant (μ = 1 h−1), fitting of the ordinary differential equation (ODE) model of mating experiments  to the observed data at T24h yielded estimates for all parameters of a” represents the basal plasmid transfer efficiency in the absence of MWCNT while “b” and “c” describe a possible exposure effect in the form of a power law. This includes the basal transfer efficiency (a = 12.6) and the coefficients reflecting the effect of MWCNT exposure . The value of b > 0 confirms a positive relationship between MWCNT exposure and plasmid transfer within the range of conditions tested. The value of c < 1 clearly suggests a non-linear dependency where an ever-increasing exposure to MWCNTs does not stimulate plasmid transfer further. Comparing predictions of the fitted model to observations reveals notable mismatches for individual experimental runs , we employed modeling of the plasmid transfer dynamics of plasmid pKJK5 between the tal runs . HoweverP. putida, we repeated the plasmid transfer experiment for the control and highest MWCNT concentration in the presence of 100 μmol thiourea, a well-known ROS scavenger. At the selected concentration, thiourea did not affect growth of the donor and recipient bacteria. Again, significant increases in plasmid transfer (transconjugants per recipient) were observed in the presence of MWCNTs. In the absence of thiourea, plasmid transfer increased from 0.21 ± 0.03% (0 mg L−1 MWCNT) to 0.38 ± 0.05% (10 mg L−1 MWCNT) in a significant manner . However, both in the absence  and in the presence of 10 mg L−1 MWCNTs , no significant effect of ROS scavenging thiourea on plasmid transfer was observed. Experiments were repeated with a 100-fold increased concentration of thiourea (10 mM), with observed results being identical (data not shown). Consequently, the overproduction of ROS in response to the exposure to MWCNTs plays a negligible role, if any, in promoting plasmid transfer.To gain mechanistic insights into whether a potential overproduction of ROS in response to exposure to MWCNTs could explain the observed increase in plasmid transfer in 50p = 0.038, R50 = 0.603; 75p = 0.027, R75 = 0.633; 90p = 0.048, R90 = 0.581; Pearson correlation, n = 12)  , bottom.Here, we demonstrate that the presence of MWCNTs can have a significant effect on bacterial plasmid transfer in liquid-phase environments, leading to a more than 2-fold increase of observed transconjugants per recipient. This effect was demonstrated for two different plasmid:donor combinations. An MWCNT concentration dependence of the observed increase in plasmid transfer was detected through statistical analysis as well as modeling of plasmid transfer dynamics. The main identified mechanism underlying the observed dynamics was the agglomeration of MWCNTs, leading to a significantly increased number of particles with an >6 μm diameter which can in turn be colonized by bacterial biofilms. This ability to form MWCNT-bacterial agglomerates has been described previously . In biof−1 being above previously reported inhibitory concentrations for CNTs  cells and are hence biotechnologically exploitable as a novel gene transfer vector system (–−1) of specifically extracted plasmid DNA were necessary to observe effects. On the contrary, in our experimental design, as well as in most environmental settings, concentrations of naked plasmid DNA, if present due to bacterial lysis in the culture, would be expected to be several orders of magnitude lower. Furthermore, the association of this free DNA with the here-used, non-functionalized MWCNTs is highly unlikely. Consequently, this mechanism, while biotechnologically exploitable, will most likely not have contributed to the observed results.Further, special functionalized MWCNTs loaded with plasmid DNA could enhance plasmid introduction through transformation into various bacterial hosts as well as r system –32. Thes system –. However−1 of MWCNTs at which a constant and significant effect on plasmid transfer was observed. However, there are only very limited measured environmental concentrations for CNTs, as they consist of pure carbon and can hardly be distinguished from other carbon in the environment. Still, the few known aquatic environmental concentrations remain significantly below the here-determined effect concentration and are usually reported in the ng L−1 range  and the extrapolated effect concentrations , is assessed. If this quotient is larger than 1, a risk can be assumed . The eff−1 range , 7. A fu−1 range . Further−1 range , 35. Dep−1 range  or heavy−1 range . This ha−1 range , have fo−1 range . HoweverWe here demonstrate that MWCNTs are indeed able to promote bacterial plasmid transfer by providing novel surfaces for bacterial interactions through agglomeration. While a pronounced effect was observed under laboratory conditions, the identified effect concentrations as well as the effect mode suggest that MWCNT pollution provides only a minor risk to significantly enhance the proliferation of AMR in the environment. Our results provide concise and important insights into the effects of MWCNTs on microorganisms that should be regarded when considering the use of MWCNTs for medical application.3.The applied pristine MWCNTs  were purchased from Bayer Material Science AG 2007 and visualized via transmission electron microscopy (TEM). Properties of the used MWCNTs  are as follows: number of walls: 3 to 15; outer diameter distribution: 5 to 20 nm; inner diameter distribution: 2 to 6 nm; length: 1 to 10 μm; bulk density: 140 to 160 kg/m−1 pristine MWCNTs was freshly prepared. For this, 50 mg of sterile MWCNT agglomerates were transferred into a glass beaker with 500 mL sterile deionized H2O. Afterwards, dispersion by an ultrasonic probe  was applied for 45 min to ensure single MWCNT strands. After dispersion, 0, 0.025 mL, 0.25 mL, and 2.5 mL from the MWCNT stock solution were withdrawn, filled up to a final volume of 2.5 mL with sterile deionized H2O, and added to the microcosms, resulting in final MWCNT concentrations of 0, 0.1, 1, and 10 mg L−1.A detailed description and characterization of MWCNTs can be found in Politowski et al. , 41 and Pseudomonas putida KT2440 was used as a plasmid donor and a plasmid recipient strain in liquid mating assays. For the recipient strain, a spontaneous rifampicin-resistant mutant of the nonfluorescent Pseudomonas putida KT2440 wild-type strain  agar plates containing 200 μg mL−1 rifampicin. After cultivation at 37°C overnight, a rifampicin-resistant mutant colony was picked and grown in LB liquid medium containing 200 μg mL−1 rifampicin and served subsequently as the recipient strain.e strain  was creaPseudomonas putida KT2440::q-pLpp-mCherry-KmRlacI . The donor strain was chromosomally tagged with a gene cassette encoding kanamycin resistance as well as constitutive red fluorescence, expressed by the mCherry gene, and constitutive qlacI production, repressing the plasmid’s qlacI promoter. As a result, gfp expression is repressed in the donor strain but expressed in recipients upon successful receipt of the plasmid, resulting in green fluorescent transconjugant cells. Hence, plasmid transfer can be confirmed by fluorescence microscopy (−1) or rifampicin (100 μg mL−1), respectively, harvested by centrifugation, washed in 0.9% sterile NaCl solution, adjusted in cell density (OD600 = 1), and used in liquid mating assays.erry-KmR  carryinggfpmut3b . The plagfpmut3b  genetic croscopy . Donor a−1) at 3 to 12 replicates per concentration. Vials were inoculated with 500 μL of optical density (OD)-adjusted donor and recipient strain solution resulting in initial concentrations of approximately 106 cells mL−1 each of the donor and recipient strains. The mating mixture was incubated at 30°C under continuous shaking at 180 rpm.To quantify plasmid transfer across a gradient of MWCNT concentrations, liquid mating assays between the donor and the recipient strain were carried out in microcosms. Mating experiments were performed in glass vials containing 25 mL sterile, liquid LB medium supplemented with appropriate concentrations of MWCNTs , 100 μg mL−1 rifampicin (recipient), or 50 μg mL−1 rifampicin and 5 μg mL−1 tetracycline (transconjugants), and subsequently incubated . Thereafter, colonies were counted. Similarly, the initial donor and recipient cell densities were quantified immediately after inoculation of the microcosms. Note that the selective concentrations for the combination of rifampicin and tetracycline had to be lowered, as those two antibiotics have a synergistic effect in inhibiting growth of P. putida. Further, when quantifying recipients and transconjugants on rifampicin-containing plates, colonies were checked under a fluorescence microscope for red fluorescence to detect any potentially occurring spontaneous rifampicin mutants of the donor strain and for green fluorescence to confirm the successful receipt of plasmid pKJK5::gfpmut3b.After 24 h, samples were taken from each replicate microcosm, serially diluted, plated on LB selective plates with 50 μg mLEscherichia coli MG1655::q-pLpp-mCherry-KmRlacI , donor (D), and transconjugant (T) populations in liquid cultures due to the simultaneous effects of growth and conjugation  and that a single intrinsic growth rate constant (μ) is representative of all three bacterial strains .To quantify the impact of MWCNT on the efficiency of plasmid transfer in a mechanistic framework, we employed a model of ordinary differential equations (ODE). The latter equation captures the dynamics of recipient  meeting a plasmid-carrying partner  multiplied with a small positive rate constant (f) carrying the unit (cells mL−1)−1 h−1. Here, the rate constant is dependent on the MWCNT concentration (X) according to a” represents the basal plasmid transfer efficiency in the absence of MWCNT while “b” and “c” describe a possible exposure effect in the form of a power law. Modeling was performed in R version 4.1 using the packages rodeo  production induced by MWCNTs affects plasmid transfer rates, liquid matings at MWCNT concentrations of 0 and 10 mg Lthiourea  at a finParticle size distribution in the cultures was measured with a Coulter Counter Multisizer3  after 24 h of incubation. ISOTON II was used as the electrolyte. The aperture diameter was 100 μm with an aperture current of 1,600 μA. Measurements were carried out in 3 replicates of 500 μL across 300 size bins ranging from 2 μm to 60 μm. The total particle size distributions across those bins were recorded. To identify colonizable agglomerates, the numbers of particles with a diameter of at least 6 μm were further assessed.To visualize bacteria-MWCNT agglomerates, associated biofilm bacteria, and successful plasmid transfer, a 10-μL drop of bacterial-MWCNTs culture was placed on a microscope cover slide. Images were taken using an epifluorescence inverted microscope (Nikon Eclipse Ti), with a 100× oil-immersion objective, equipped with a GFP and TRITC/CY3 filter cubes, and a DS-Fi1c digital camera (Nikon instruments). The sample was observed by first focusing on the MWCNT agglomerate in bright field mode. The agglomerates were then examined for mCherry (donor)- and GFP (transconjugant)-positive cells. Images in all three channels were captured from identical locations using the NSI-elements AR 5.11.01 software. For optimized visualization using the ImageJ software (version 1.53f51), the images were separately adjusted in brightness and contrast with additionally performed background subtraction. Furthermore, the images of all three channels were merged into one overall image using the operation Image Calculator so that both the agglomerate and the red and green fluorescent bacteria could be visualized.


The main purpose of this experimental study was to determine the in vitro effects of two calcium phosphate‐containing agents (Remin Pro® and GC Tooth mousse™) on the enamel resistance of permanent molars to demineralization.Fifty extracted human third molars were randomly divided into four groups; that is the control group and three case groups treated with Remin Pro®, GC Tooth mousse™, and sodium fluoride gel. The three case groups were treated with 0.25 ml of the paste associated with each experimental group for 5 min, kept in fluoride‐free artificial saliva, and incubated at 37°C for 28 days. After the treatment regimen, 10 samples of each case group were subjected to demineralization using an acetic acid‐containing solution, and remineralization using a remineralizing solution. The morphology of enamel was observed via scanning electron microscopy and their enamel calcium/phosphorus (Ca/P) ratios were measured before/after the demineralization cycle with energy‐dispersive X‐ray analysis. Data were statistically analyzed using one‐way analysis of variance and post hoc Tukey tests.p < .0001). However, the ratios were not significantly different between the case study groups after the treatment regimen and demineralization cycle (p > .05).The enamel Ca/P ratios in the case study groups were significantly higher than that of the control group before/after the demineralization regimen (The outcomes of the current study indicated that all three agents seemed to increase the enamel resistance of permanent molar teeth to demineralization. REC.1396.597).”n = 5, untreated specimens) and three case groups treated with Remin Pro® (n = 15) , GC Tooth mousse™ (n = 15) , and sodium fluoride gel (n= 15) .Fifty hopeless sound third molar teeth were extracted and polished with fluoride‐free pumice paste and distilled water using a low‐speed handpiece and rubber cup for 10 s, followed by copious irrigation with deionized water for 30 s. Then, the teeth were cut with a diamond disc bur, at the level of the cementoenamel junction. Next, tooth crown pieces were sectioned to buccal or lingual portions with dimensions of 2 × 4 mm, and 50 sound enamel specimens were randomly selected. Then, the inner side  of specimens was completely flattened using a fissure bur. Afterward, the specimens were divided into four groups; that is, the control group  equipped with an EDXA analyzer  Figure . The buc2, 0.13 gr NaH2PO4, 5 ml NaN3, 1.5 ml Acid acetic) for a week. The specimens were immersed in the demineralizing solution with pH=4.4 for 6 h and then, in remineralizing solution  with pH = 6.5 for 18 h (pH Cycling). Ten samples from each group were dried, examined under SEM for their morphology, and assessed by an EDXA analyzer for their mineral content.Ten remaining specimens in each case group were subjected to a demineralization regimen  was set at .05 in the present study.Data were analyzed using the statistical package for social sciences (SPSS) software, version 21. Differences in mineral content of the three groups of specimens were evaluated using one‐way analysis of variance (ANOVA) before and after exposure to remineralizing agents. The control group was compared with the case groups before and after exposure to demineralizing/remineralizing solutions using one‐way ANOVA test. The probability value . However, there were insignificant differences between the case group specimens after the treatment regimen. Moreover, the specimens that underwent pH cycling showed insignificant differences before and after the cycle within their group and with the other groups (p > .05).Table p < .05)  and lowest in GC tooth mousse™ (mean = 1.77) before the pH cycling and the highest in Fluoride Gel Masterdent (mean = 1.86) and the lowest in Remin Pro® (mean = 1.80) after the cycling, although the differences between groups were not significant.4The present study investigated two recently introduced calcium phosphate‐containing agents and fluoride gel as well as their effects on the resistance of permanent teeth enamel to the demineralization process, indicating an increase in Ca/P ratio in the examined specimens. Besides, the agents showed promising results on the remineralization pattern and positive effects on the enamel resistance to demineralization.In the current study, SEM/EDXA were used to examine the surface/layer morphology and analysis of the mineral content of the affected enamel surfaces as a noninvasive measurement approach. The comparison between the lower number of porosities in the groups experimented with and that of the control group, revealed by SEM, indicated a higher possibility for an increase in enamel resistance and thus, a potential decrease in the formation of carious lesions in the groups tested. In addition, the porosities read by SEM in the groups experimented with after pH cycling showed insignificant differences with porosities before the corresponding cycling, which, in turn, exhibited the resistance of the specimens against demineralization. Moreover, SEM/EDXA showed a statistically significant increase in Ca/P ratio, indicating an appropriate matrix for possible remineralization , leading to better remineralization of the enamel. In addition, the gel could result in enhanced enamel resistance due to the production of fluorapatite  were not considered.51.The current investigation showed that Remin Pro®, GC Tooth mousse™, and sodium fluoride gel were able to increase the Ca/P ratio in the enamel samples.2.The application of Remin Pro®, GC Tooth mousse™, and sodium fluoride gel could enhance the enamel resistance to demineralization.3.The application of Remin Pro®, GC Tooth mousse™, and sodium fluoride gel should help clinicians promote enamel resistance and thus, lower the possibility of carious lesions.Within the natural limitations of an experimental study:Fatemeh Molaasadolah: Conceptualization; data/formal analysis; investigation; methodology; project administration; supervision; validation; visualization; writing—original draft; and writing—review/editing. Zohre Sadat Hosseinipour: Conceptualization; investigation; methodology; validation; visualization; and writing—original draft. Fatemeh Afzali: Conceptualization; data/formal analysis; investigation; methodology; project administration; and visualization. Ardavan Parhizkar: Conceptualization; investigation; methodology; validation; visualization; writing—original draft; and writing—review/editing. Kiana Poorzandpoush: Conceptualization; data/formal analysis; investigation; methodology; project administration; supervision; validation; visualization; writing—original draft; and writing—review/editing.The authors declare no conflict of interest.


Anlotinib as a third‐line or beyond therapy for extensive‐stage small‐cell lung cancer (ES‐SCLC) was studied. This single‐arm phase II trial was to investigate the value of anlotinib plus platinum‐etoposide as first‐line treatment in ES SCLC.The primary endpoint was progression‐free survival (PFS) and objective response rate (ORR). The secondary endpoints included overall survival (OS), disease control rate (DCR), time to progression (TTP), duration of remission (DoR), and safety. The subgroups of preset liver metastasis and brain metastasis were analyzed.In 35 ES‐SCLC patients, the median PFS, ORR, DCR, and OS were 8.02 months [95% confidence interval (CI): 6.90–9.66], 85.71% (95% CI: 69.74–95.19), 94.29% (95% CI: 80.84–99.30), and 15.87 months (95% CI: 10.38–18.89), respectively. The median PFS in the liver metastasis and brain metastasis subgroups was 7.33 months (95% CI: 4.76–9.69) and 7.34 months (95% CI: 5.68–9.20), respectively. The most common AEs with grade 3–4 were hand–foot syndrome (17%), granulocytosis (17%), stomatitis (14%), hypertriglyceridemia (11%), hypercholesterolemia (11%), as well as nausea and vomiting (11%), and no grade 5 AEs were recorded.Anlotinib combined with platinum‐etoposide provided an effective and safe therapy for patients with ES‐SCLC. Abstract graphic for the table of contents. However, patients with both high tumor mutational burden (TMB) and a programmed death‐ligand 1 (PD‐L1) expression ≥50% tumor cells had a higher response rate (75%).Although the results of immunotherapy are promising, the CASPIAN trial assessed the durvalumab plus platinum‐etoposide regimen and showed that OS was significantly longer than that in the platinum‐etoposide group (13.0 vs. 10.3 months).Administration of anti‐vascular‐targeted therapies combined with chemotherapy has been reported in the first‐line treatment of SCLC patients. The pooled survival data from the previous first‐line trials revealed a median PFS time of 6–7 months and a median OS time of ~11 months for combined treatment of bevacizumab and chemotherapy, which were similar to those results reported in other trials concentrated on chemotherapy only.Anlotinib is an oral tyrosine kinase inhibitor targeting c‐kit, platelet‐derived growth factor receptors, fibroblast growth factor receptor, and vascular endothelial growth factor receptor.This clinical trial aimed to investigate the efficacy and safety of anlotinib plus platinum‐etoposide, as the first‐line treatment, for patients with ES‐SCLC.22.1This single‐arm phase II trial enrolled patients with ES‐SCLC, without prior systematic chemotherapy or ICI therapy, who were admitted to Xiangya Hospital Affiliated to the Central South University, from August 23, 2018, to January 16, 2020. The study was conducted in accordance with the International Conference on Harmonization Good Clinical Practice Guideline, the Declaration of Helsinki, and applicable local regulations with approval from an independent ethics committee or institutional review boards. The protocol and all modifications were approved by the Medical Ethics Committee of Xiangya Hospital, Central South University . All patients provided written informed consent for participation.The inclusion criteria were as follows: (1) patients who aged 18–70 years old; (2) patients who were histologically confirmed with ES‐SCLC according to the diagnostic criteria presented by the Veterans Administration Lung Study Group and the Response Evaluation Criteria in Solid Tumors ; (3) patients with an Eastern Cooperative Oncology Group (ECOG) performance‐status (PS) score of 0 or 1, and 4) patients who had not received previous systemic treatment for EC‐SCLC and had an expected survival time ≥3 months. Patients with asymptomatic central nervous system (CNS) metastases who underwent therapy were also eligible under some circumstances  or carboplatin , and anlotinib treatment of 12‐mg qd from day 1 to day 14 of a 21‐day cycle. Eligible patients received anlotinib plus platinum‐etoposide for 4–6 cycles, followed by maintenance therapy with anlotinib.The platinum‐etoposide regimen consisted of administration of etoposide 100 mg/m,Discontinuity/Withdrawal: All patients who signed the informed consent had the right to withdraw from the study at any time. Any patient who withdrew from the study for any reason at any time and without completing all observations of the clinical study was deemed as a case of loss. The reasons for loss and withdrawal of patients included the following: (1) adverse events (AEs); (2) serious breach of protocol; (3) loss of follow‐up; (4) voluntary withdrawal of informed consent by patients; (5) situations in which, researchers believed, the patient should withdraw from the study; and (6) others .Efficacy evaluation was conducted every 6 weeks during the post‐enrolment enhancement period (anlotinib +EP/EC) after enrolment and every 9 weeks (anlotinib maintenance) following in the maintenance period. The tumor evaluation schedule was calculated on a calendar basis from random days, regardless of whether the treatment was delayed or not. For other parts (including the brain and bone) known or suspected to have lesions, patients underwent imaging examination when clinical indications were present. The evaluation was also performed when the disease was suspected to have progressed  or when the patient discontinues the treatment . For patients suspected to have disease progression before the next scheduled tumor evaluation, an extra tumor evaluation was performed. AEs were graded according to the National Cancer Institute Common Terminology Criteria (version 4.02).2.3The primary endpoint was the PFS and ORR [complete response (CR) + partial response (PR)], and the secondary endpoints were OS, the disease control rate , including the time to progression (TTP), duration of remission (DoR), and safety of the whole therapeutic process of anlotinib plus EP as a first‐line therapy for patients with EC‐SCLC. In the liver metastasis and brain metastasis subgroups, the OS, PFS, ORR, and DCR were analyzed. PFS, ORR, and DoR were assessed using the RECIST (ver. 1.1), and the ORR was confirmed twice according to the RECIST (ver. 1.1).2.4Efficacy‐based data were analyzed on an intention‐to‐treat basis, regardless of whether patients have received treatment or not. All patients who received at least one dose of the therapy were included in the safety analysis. Periodic safety monitoring and interim efficacy assessment were conducted by an independent data monitoring committee.ORR and PFS do not share the α value but historical controls were given from the previously study.P‐value <0.05 was considered statistically significant.Statistical analysis was performed using the SAS 9.4 software . Continuous variables were expressed as mean ± standard deviation (SD), and categorical variables were presented as percentage. PFS and ORR were analyzed using the log‐rank test with hazard ratios (HRs) and 95% confidence intervals (95% CIs), which were estimated using the Cox proportional hazards model. The Kaplan–Meier method was also used to estimate OS, TTP, and DoR. A two‐tailed 33.1Of the 35 patients with extensive‐stage SCLC enrolled between August 23, 2018, and January 16, 2020, 36 patients were enrolled and 35 patients were available for efficacy analysis  and the median OS was 15.87 months  in the whole patient cohort , and the median PFS in the brain metastasis subgroup was 7.34 months   was 97% in the whole cohort. In all patients, 40% had 3–4 grade AEs and 11% had serious AEs (SAEs). The most common AEs with grade 3–4 were hand–foot syndrome (17%), granulocytosis (17%), stomatitis (14%), hypertriglyceridemia (11%), hypercholesterolemia (11%), as well as nausea and vomiting (11%) , 15.87 months , and 85.71% (95% CI: 69.74%95.19%), respectively. These results were more significant compared to chemotherapy alone , and bevacizumab + chemotherapyIn addition, according to the 2021 NCCN guidelines for SCLC, patients with relapse time >6 months after undergoing the first‐line therapy for ES‐SCLC could individually select the original therapeutic regimen.In the real world, limited patients have access to second‐line treatment, and low PS scores after first‐line treatment become a reason to stop receiving post‐line treatment.The follow‐up period of this study was every two cycles (42 days) over 12 cycles (8 months) and every three cycles (63 days) starting from cycle 13. This ensures timely detection of disease progression and increases the accuracy of determining PFS.Brain metastasis is associated with a poor SCLC prognosis. Approximately 10%–25.8% of patients with SCLC at diagnosis had symptomatic or asymptomatic brain metastases. First‐line immunotherapy studies that enrolled ES‐SCLC patients with asymptomatic or stable brain metastases for treatment included the IMpower133,n = 21) versus placebo (n = 9) had a PFS of 3.8 m versus 0.8 m (HR = 0.15) and a DCR of 71.4% versus 11.1% (P = 0.004).The multicenter, randomized, double‐blind, phase II ALTER1202 trial assessed anlotinib in patients with limited‐stage SCLC or ES‐SCLC who had developed progression after two lines of chemotherapy. In a subgroup of third‐line and post‐line extensive‐stage SCLC combined with stable brain metastases, anlotinib alone (n = 12). In contrast, OS in IMpower133 was 9.3 m. However, as determined by imaging data of liver lesions in patients with liver metastases from this regimen alone in the present study, the subgroup with liver metastases had a PFS of 7.33 m , OS of 10.38 m , ORR of 76.92% , and DCR of 84.62% . In conclusion, anlotinib + EP can have a trend of benefit in the population with liver metastasis ES‐SCLC.The CASPIAN, IMPOWER‐133, KEYNOTE‐604, Reck‐2016, and ECOG‐ACRIN‐5161 studies included a subset of people with combined liver metastases and explored the benefit of ICI + EP in patients with liver metastases from ES‐SCLC: the HR of OS was 0.84.The reason for the aforementioned results might be that anti‐vascular‐targeted drugs combined with platinum‐etoposide improved the survival of patients with ES‐SCLC, and the safety was controllable. It also had a good performance in liver and brain metastasis. This encouraging result might be due to the favorable transmembrane effect of anlotinib hydrochloride and its synergistic effect with chemotherapy.Grade 3 to 4 AEs commonly observed in this study were hand–foot syndrome (17%) and hypertriglyceridemia (11%), which are also the common adverse responses of anlotinib monotherapy, similar with other study.The present study was a greater safety compared to Atezolizumab + EP, and Durvalumab + EP ± Tremelimumab.In this study, among the 35 subjects, a total number of three grade 3 AEs that led to discontinuation , none of the above grade 3 AEs were severe and difficult to salvage . The shorter duration of chemotherapy with our regimen (compared to other first‐line treatments) has the potential to improve patient quality of life and adherence. Overall, anlotinib showed clinical benefits and a tolerable safety in a considerable number of patients with ES‐SCLC.This study had some limitations. This was a single‐arm study with small sample size. And the PFS and ORR were not achieved to the preset 9 months and 80%. However, PFS in this study was 8.02 months with the lower 95%CI limit was 6.09 months, which was higher than the historical control of 5.2 months. While ORR was 85.71% with the lower 95%CI limit was 69.74%, which also higher than the historical control of 55%. Therefore, this study met the primary endpoint. Studies with a large sample size are further needed to validate these findings. Meanwhile, the comparison with chemotherapy alone was missing in this single‐arm study. However, the trial was designed based on historical data from clinical trials of chemotherapy alone, and statistical calculations also had been performed in combination with expected survival goals, including the sample size was estimated and compared with historical data. In addition, the biomarker with predictive value was hard to explore in the present study because of the small sample size. Although the ORR was very high, and the DCR was very close to 100%, it is still expected to be verified in a larger sample study. Actually, a multicenter randomized controlled trial is undergoing, which will provide more evidence on the efficacy and safety of chemotherapy alone and chemotherapy + anlotinib in ES‐SCLC patients.In summary, this single‐arm phase II trial in the first‐line treatment of ES‐SCLC showed that the addition of anlotinib to platinum‐etoposide was associated with significantly improved PFS and ORR, accompanying with a safety profile.The anlotinib + etoposide + platinum therapy showed promising prognosis  and favorable tolerability profile in the first‐line treatment of ES‐SCLC, which needs to be demonstrated in studies of larger sample size.This study received funding from Chia Tai Tianqing Pharmaceutical Group Co., Ltd. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication. All authors declare no other competing interests.CPH, HPY, and PBD contributed to the conception of the study; PBD, HPY, LMC, QHG, JA, LQ, ML, and BMH performed the experiment; PBD, CC, and JJ contributed significantly to data analysis and wrote the manuscript.The study was conducted in accordance with the International Conference on Harmonization Good Clinical Practice Guideline, the Declaration of Helsinki, and applicable local regulations with approval from an independent ethics committee or institutional review boards.All patients provided written informed consent for participation.https://clinicaltrials.gov/.Clinical Trials. Gov number, NCT04675697. Appendix S1Click here for additional data file.


Atrial fibrillation (AF) is an uncommon arrhythmia in young adults without structural heart disease, and cryoballoon pulmonary vein isolation (CB‐PVI) is an important therapeutic strategy for rhythm control in patients with drug‐refractory AF. The aim of this analysis was to evaluate efficacy and safety of CB‐PVI in a large cohort of young patients in comparison with middle‐aged adults in a real‐world setting.n = 368) and a MIDDLE‐AGED group .From 2012 to 2020, a total of 3033 patients with AF underwent CB‐PVI and were followed prospectively in the framework of the 1STOP Clinical Service project, involving 34 Italian centers. Out of 3033 total 1STOP project subjects, a subgroup of 1318 patients were defined which included a YOUNG group . There was no difference in procedural characteristics, and periprocedural complication rates were similar among the two cohort . The 12‐month freedom from AF recurrence was 88.9%  in the YOUNG cohort and 85.6% (95% CI: 82.9–88.0) in the MIDDLE‐AGED group. At 36‐month follow‐up, freedom from AF recurrence was 72.4% (65.5%–78.2%) and 71.8% (67.7%–75.6%), respectively with no significant difference among groups (p = 0.550).The acute success rate of PVI did not differ between the two cohorts  for atrial fibrillation between young and middle‐aged patients.Our analysis demonstrated the same rate of acute success, freedom from recurrent atrial fibrillation between young and middle‐aged patients, despite (as expected) older patients having more comorbidities.Safety outcomes of the procedure did not differ between young and middle‐aged patients, with a very low complication rate overall in both cohorts.The rate of repeat ablations following the index procedure was higher in young as compared to middle‐aged Compared with older patients, young patients have lower comorbidities, a more symptomatic clinical course, and an aversion toward life‐long medication intake.22.1n = 368) and between 60 and 65 years (MIDDLE‐AGED n = 950). The age range 60–65 years was chosen for middle‐aged patients as this age group is the most represented in the 1STOP project population.From April 2012 to August 2020, 3033 patients with paroxysmal or persistent AF who had undergone CB‐PVI  in 34 Italian institutions were prospectively followed, according to each center's clinical practice, by means of in‐hospital visits through the framework of the of One Shot to PVI (1STOP) project. Patients with previous AF ablations and lost to follow‐up data were excluded. In this sub‐group analysis, 1318 patients were studied and divided, into two groups according to their age, including: ≤45 years  access was immediately followed by a heparin bolus delivery. The subsequent heparin delivery was titrated to maintain an activated clotting time of above 300 s. A dedicated delivery sheath  was used to handle the balloon catheter and/or guidewire assembly during the ablation procedure. Ablations were performed with a 23‐ and/or 28‐mm CB, which was advanced by an over‐a‐wire method into the LA. The number and length of freeze applications, as well as postablation testing methods varied according to each center's practice. During freezing of the right‐sided PVs, phrenic nerve function was monitored with continuous pacing maneuvers to record diaphragmatic performance. Acute PVI was consistently defined as electrical conduction isolation confirmed by bidirectional block and assessed using the dedicated diagnostic mapping catheter  and/or a standard circular diagnostic mapping catheter. Acute procedural success was defined as the ratio between the number of effectively isolated PVs and the number of target PVs.2.32DS2‐VASc), and echocardiographic parameters. During the index CB ablation procedure, further data were recorded within the procedural hospitalization, including data on anticoagulation strategy, ablation and procedural durations, and fluoroscopic radiation exposure. Routine follow‐up assessments were made in accordance with the standard clinical practices at each center through in‐hospital visits or telephone interviews. Typically, follow‐up visits were scheduled for every 3 months after the index ablation during the first 12 months, and for every 6 months thereafter. Each follow‐up examination included an AF‐related symptoms' review, ECG for arrhythmic event assessment, and 24‐h ECG Holter monitoring. Patients were routinely discharged with previously ineffective antiarrhythmic agents that were typically discontinued after 12 weeks if the patient had paroxysmal AF and at 6 months if they had persistent AF. The management of antiarrhythmic agents was left to the discretion of the clinical practice of each center. The first 90‐days after AF ablation were considered a landmark blanking period during which any arrhythmia occurrence would not be counted against the long‐term efficacy, to allow time for cardiac healing following cryoablation.At the baseline visit, clinical patient characteristics were collected, including: age, gender, body mass index, AF‐related symptoms, EHRA score, cardiovascular risk factors, previous history of cardiovascular and thromboembolic events, thromboembolic risk index  lasting ≥30 s in duration after the 90‐day blanking period. Secondary endpoints were repeat ablation(s) after the index procedure. All reported procedural and peri‐procedural complications were recorded, and adverse event classifications of minor or major events were made in accordance with the previously published worldwide survey on AF ablation.2.5The 1STOP project is a retrospective examination of CB ablations conducted in 34 Italian cardiology centers. This project is part of a larger Italian medical care research project  that is a clinical data repository for an integrated network consortium of Italian cardiac hospitals with the shared goal of evaluating and improving the usage of medical therapies in clinical practice through the mutual collection, examination, and analysis of pooled data. The project and data collection activities conform to the principles outlined in the Declaration of Helsinki, and each patient included in the One Hospital Clinical Service project provided informed written consent. Detailed methods for follow‐up, data collection, reporting, and data repository have been previous described in detail for the 1STOP project.2.6χ2‐test or Fisher's exact test for extreme proportions, as appropriate. The analyses of time‐to‐first event were described using Kaplan–Meier curves and compared between the groups with the log‐rank test. The annual rates of complications were reported, together with the 95% confidence intervals [CI]. To identify predictors of AF recurrence, a cox regression model was imputed for both univariate and multivariate analyses. Parameters that were identified as significant in univariate analyses (p < 0.10) were also analyzed in a multivariate model. Statistical tests were based on a two‐sided significance level of 0.05. The SAS software, version 9.4, (SAS Institute Inc.) was used to perform statistical analyses.Descriptive statistics were used to summarize patient characteristics, including: mean, standard deviation, minimum, maximum, and median with the interquartile range (IQR) for continuous variables, and counts and percentages for categorical variables. Comparisons between groups have been performed using Wilcoxon's Test for continuous variables, while comparisons of categorical variables have been performed using 33.1Demographic, clinical, and echocardiographic characteristics of the 1318 patients are summarized in Table 3.2p = 0.415), respectively. There was no difference in overall procedure duration , fluoroscopy duration  and ablation time  between the two groups, respectively. At the end of procedure sinus rhythm was obtained in 1275 (96.8%) patients, with no difference between YOUNG and MIDDLE‐AGED groups , respectively.Data detailing acute results are summarized in Table 3.3p = 0.646), as reported in Table In total, 29/1318 (2.2%) patients had at least one procedural complication, equally distributed between the groups . The time‐to‐first AF recurrence is shown in Figure p = 0.550). Limited to paroxysmal AF, at 36‐months follow‐up freedom from AF recurrence was 74.6% (95% CI: 67.1%–80.6%) in the YOUNG and 72.6% (67.7%–76.8%) in the MIDDLE‐AGED with no significant difference (p = 0.34). In persistent AF, at 36‐months follow‐up freedom from AF recurrence was 57.5% (95% CI: 37.3%–73.3%) and 69.6% (95% CI: 61.2%–76.6%) in YOUNG and MIDDLE‐AGED patients respectively, with no significant difference (p = 0.14). However, the rate of repeat ablations following the index procedure  differs between YOUNG and MIDDLE‐AGED patients . Several conditions possibly associated with AF recurrence were investigated by means of univariate and multivariate analyses in the YOUNG (Table p = 0.025) resulted as independent predictor of AF recurrence. Echocardiographic parameters were not included in the multivariate model, due to correlation coefficient >0.25 or due to low number of patients with information recorded.The mean length of follow‐up was 23.6 ± 20.2 months. During follow‐up, 254/1318 (19%) patients had AF recurrence: 69/368 (18.7%) in the YOUNG and 185/950 (19.5%) in the MIDDLE‐AGED. The incidence rate for 100 patient‐years was 9.29 (95% CI: 7.72–11.18) in the YOUNG and 9.99 (95% CI: 8.93–11.19) in the MIDDLE‐AGED. The atrial arrhythmia recurrence rate was not statistically different between the two groups  in the acute success rate of CB‐PVI; (2) in the rate of AF relapse after index procedure. However, the rate of repeat ablations following the index procedure was higher in young as compared to middle‐age. Persistent AF was the only predictor of AF recurrence in the cohort of patients aged <45.4.1To date, this is the first multicenter analysis to evaluate the differences in efficacy and safety of a single ablation technique (CB‐PVI) between young and middle‐aged patients. In our experience, CB‐PVI was not more effective in young patients than in middle‐aged patients. The analysis demonstrated the same rate of acute success, freedom from recurrent arrhythmia, in both groups, despite (as expected) older patients having more comorbidities , larger LA diameter and volume, and more persistent form of AF. The long‐term efficacy of CB‐PVI observed in our analysis (freedom from AF recurrence is 88.9% at the 12‐month follow‐up and 72.4% at the 36‐month follow‐up) overlaps that of Moran et al., who reported a freedom from AF relapse of 88% after a median follow‐up of 18 ± 10 months in a young cohort of patients <40 years.The same homogeneity of results was not maintained when efficacy of PVI is compared between young and older patients. Both Chun et al. and Tijskens et al. reported a significant lower recurrence rate after a single procedure in a population ≤45 years in comparison to a cohort of patients >45 years.4.2Safety outcomes of the procedure did not differ between young and middle‐aged patients, with a very low complication rate overall in both cohorts. Transient phrenic nerve paralysis (1.2%) was lower than that reported in recent large studies with the second‐generation CB ,4.3In our analysis, persistent AF was independently associated with AF recurrence after CB‐PVI in young patients. Persistent AF was the most frequently observed independent predictor of AF recurrence both in the young and older cohort, and the other predictors observed were structural heart disease,4.4Management of AF in young patients is challenging. Understanding the longer‐term effects of AF in young patients is vital as they will live with the disease ramifications for many decades. Current guidelines identify young symptomatic patients with paroxysmal AF and no structural heart disease as ideal candidates for catheter ablation.5This analysis was based on a group of patients who underwent an AF catheter ablation with a specific technology and strategy (CB‐PVI), without predefined inclusion criteria. Due to the observational nature of the study, potential selection bias cannot be excluded. Although cryoablation technology is highly standardized, many procedural aspects are left to the discretion of the various centers, and thus, these factors may have influenced parameters of efficacy and safety. Moreover, the large number of patients and centers may have mitigated possible bias while demonstrating a real‐world clinical experience. We did not perform an electrophysiologic study in young patients before PVI, and this choice could have allowed us to identify a supraventricular tachycardia as the substrate of AF in around a quarter of young adult patients.6In this large observational cohort, CB‐PVI for AF in young patients was not more effective than in older patients. The younger age did affect acute procedural results nor longer‐term AF recurrence after a single procedure. Importantly, procedures were safe in the young and older patients. Further studies are required to investigate very long‐term outcomes in young patients treated with CB‐PVI.