Patients with acute severe asthma (ASA) may in rare cases require invasive mechanical ventilation (IMV). However, recent data on this issue are lacking.In this retrospective and bicentric study conducted on a 10 year period, we investigate the in-hospital mortality in patients with ASA requiring IMV. We compare this mortality to that of patients with other types of respiratory distress using a standardized mortality ratio (SMR) model.3 on day of admission. In-hospital mortality was 15% (n = 12). Compared to a reference population of 2,670 patients, the SMR relative to the SAPS II was very low at 0.48 . The only factor independently associated with in-hospital mortality was cardiac arrest on day of admission. In-hospital mortality was 69% in patients with cardiac arrest on day of admission and 4% in others (p < 0.01). Salvage therapies were given to 7 patients, sometimes in combination with each other: ECMO (n = 6), halogenated gas (n = 1) and anti-IL5 antibody (n = 1). Death occurred in only 2 of these 7 patients, both of whom had cardiac arrest on day of admission.Eighty-one episodes of ASA requiring IMV were evaluated. Factors significantly associated with in-hospital mortality were cardiac arrest on day of admission, cardiac arrest as the reason for intubation, absence of decompensation risk factors, need for renal replacement therapy on day of admission, and intubation in pre-hospital setting. Non-survivors had higher SAPS II, SOFA, creatinine and lactate levels as well as lower blood pressure, pH, and HCONowadays, the mortality of patients with ASA requiring IMV is low. Death is due to multi-organ failure, with cardiac arrest on day of admission being the most important risk factor. In patients who did not have cardiac arrest on day of admission the mortality is even lower (4%) which allows an aggressive management. Asthma is a chronic inflammatory disease of the respiratory tract that affects 235 to 300 million people worldwide and that is responsible for approximately 180,000 deaths annually . The worAcute severe asthma (ASA) is an asthma attack that does not respond to usual treatment and that can potentially lead to respiratory distress and death. However, there is no clear and consensual clinical definition of ASA at present –9. AccorPatients with ASA may in rare cases (approximately 1% to 4%) require invasive mechanical ventilation (IMV) –13. IndiIn view of these elements concerning patients with ASA requiring IMV in the era of modern resuscitation techniques, this retrospective and bicentric study has been implemented. The main objectives were to determine the in-hospital mortality and to investigate the factors associated with this in-hospital mortality. The secondary objective was to compare the mortality of these patients to that of patients with other types of respiratory distress encountered in the ICU. Finally, this study aimed to describe: (I) the main characteristics of these patients; (II) the therapeutic management at admission; (III) the use of salvage therapies such as ECMO; (IV) and the complications encountered in ICU.This study retrospectively analyzed patients hospitalized for ASA in 1 of the 2 ICUs of the French overseas territory of Reunion Island over a 10-year period (from January 2008 to December 2017). All hospitalized adult patients (≥ 18-year-old) who received a primary diagnosis of ASA requiring IMV were included. The 2 ICUs involved in this study, the University Teaching Hospital of Saint-Denis and the University Teaching Hospital of Saint-Pierre, are the only healthcare facilities of Reunion Island  where patients can receive prolonged IMV. Patients were admitted to ICU either directly from home by the pre-hospital medical team or from 1 of the 4 emergency departments of the island.The electronic database of the 2 ICUs was reviewed to identify eligible patients. Medical records were then analyzed to confirm that patients had been well diagnosed with ASA. For instance, all records of patients requiring mechanical ventilation for exacerbation of chronic obstructive pulmonary disease or congestive heart failure were specifically excluded. Medical records were analyzed by 2 investigators  to ensure that patients satisfied these inclusion criteria. Disagreements between the 2 principal investigators were resolved after discussion with a third investigator (RP).The following patient characteristics were recorded: age, gender, height, weight, smoking, alcohol and/or drug abuse, chronic diseases, duration of asthma, presence of atopy, asthma treatment, previous hospitalization(s) for ASA requiring IMV or not, and compliance to treatment. Decompensation risk factor(s), intubation management (location and indications), vital signs on admission  were also recorded. Laboratory results (including blood gas results) were recorded on admission to ICU. Severity and comorbidity scores (Simplified Acute Physiology Score II (SAPS II) and Sequential Organ Failure Assessment (SOFA)) on the day of admission were calculated. Occurrence of cardiac arrest on the day of admission was investigated carefully based on medical records.Data on the medical management of patients on the day of admission were collected. These data included: medications used for sedation, hemodynamic support, specific asthma treatment , mechanical ventilator settings, fluid administration, and use of renal replacement therapy. Data on the use of various types of salvage therapies , including indications for treatment, were also gathered. Indications for ECMO support were decided on a case-by-case basis. Indeed, because ASA is a very rare indication for ECMO, there is no specific protocol for the administration of ECMO in patients with ASA, unlike what is the case for patients with refractory ARDS. It should be noted that a mobile ECMO team is available in Reunion Island. Finally, we recorded the complications encountered during ICU stay, namely: ICU-acquired weakness, barotrauma, ventilator-associated pneumonia or other ICU-acquired infections, shock related to ASA (cardiac tamponade due to gas trapping), severe atelectasis, myocardial ischemia, and severe cardiac arrhythmia. The rate of tracheotomy was also recorded.According to French law, no informed consent is necessary for the extraction of anonymous data or for the anonymous analysis of patients’ medical records. This study was approved by the Ethics Committee of the “Société de Réanimation de Langue Française” (# CE SRLF 18–10). This study was approved by the French National Commission on Informatics and Liberty (# 2184166v0). This study follows the STROBE statement recommendations .Patients’ characteristics were expressed as frequencies and proportions for categorical variables and as medians and interquartile ranges for quantitative variables. Bivariate comparisons were performed using Pearson’s Chi-Square test or Fisher’s exact test for qualitative data and Student’s t-test or the Mann-Whitney test for quantitative data, as appropriate. Backward logistic regression was conducted to determine the factors associated with in-hospital mortality. All factors associated with a p-value < 0.20 in bivariate analysis were entered in the model and then removed if they did not reach the significance level of p < 0.05. Adjusted Odds Ratios and their 95% Confidence Intervals were estimated. All tests were performed with a 2-tailed type I error of 5%. All analyses were made using SAS 9.4 .A reference population was created to compare the mortality of ASA to that of other types of respiratory distress. The respiratory distress group was composed of patients with a primary diagnosis of hypoxemic respiratory distress, hypercapnic respiratory distress, acute respiratory distress syndrome, or ASA. Medical records were selected based on the International Classification of Diseases, 10th Edition, coding. Inclusion was limited to patients requiring IMV who were hospitalized during the same period (from January 2008 to December 2017) and in the same 2 Reunion Island ICUs as patients hospitalized for ASA. Finally, the observed mortality of ASA was compared to the expected mortality according to the reference population using a standardized mortality ratio (SMR). The SMR was calculated from SAPS II quartile of the reference population with any type of respiratory distress.A total of 81 patients with ASA requiring IMV were admitted to 1 of the 2 Reunion Island ICUs between January 2008 and December 2017 . The estIn almost half of the cases, no decompensation risk factors were found. Identified decompensation risk factors were: bacterial or viral pneumonia (15%), acute bronchitis (14%), cessation of asthma treatment 12%), exposure to allergens (10%), and non-respiratory sepsis (4%). The location of intubation was mainly the emergency department (54%), followed by the pre-hospital setting (24%) and the ICU (22%). Intubation was performed in 74 patients (91%) on day 1, in 6 patients (7%) on day 2, and in 1 patient (1%) on day 3. The main intubation criteria were: signs of respiratory exhaustion, hypercapnia, hypoxemia, altered state of consciousness, and cardiac arrest. The SAPS II was 40 [30–54] and the SOFA score was 5  %. These results are summarized in The majority of the patients were treated with a short-acting beta-agonist (96%), often in association with a short-acting muscarinic antagonist (87%). Short-acting agonists were always administered with a nebulizer. Intravenous short-acting beta-agonists were given to only 8% of the patients. Systemic corticosteroids were administered to 83% of the patients. The majority of patients (65%) received continuous neuromuscular blockade on the day of admission. Nearly half of the patients (45%) had hemodynamic failure that required infusion of catecholamines (sometime in combination with each other) on the day of admission: norepinephrine was given to 39% of the patients, epinephrine to 23% of the patients, and dobutamine to none of the patients. To note, adrenalin was used when both Beta1 and Beta2 effects were needed (inotropic effect and bronchodilator effect). Only 5% of the patients needed renal replacement therapy on the day of admission. Patients received 1,000  mL of fluids on the day of admission. Mechanical ventilator settings on the day of admission were as follows: a tidal volume of 405 [375–455] mL, a respiratory rate of 15 –16 breatSalvage therapies were given to 7 patients, sometimes in combination with each other: ECMO was given to 6 patients, halogenated gas to 1 patient, and anti-IL5 antibody (mepolizumab) to 1 patient. The characteristics and outcome of these 7 patients are shown in Nearly half of the patients experienced complications: 25% of the patients had ventilator-associated pneumonia, 15% had other ICU-acquired infections, 7% had severe atelectasis requiring specific management, 6% had ICU-acquired weakness, 6% had severe cardiac arrhythmia, 6% had myocardial ischemia, 6% had shock related to ASA, and 5% had barotrauma . The rate of tracheostomy was 7%. Hospital and ICU length of stay was 13 –17 and 7In-ICU mortality was 14% (n = 11) and in-hospital mortality was 15% (n = 12). One death occurred in the medical ward after ICU discharge due to hypoxic cardiac arrest caused by a tracheostomy mucus plug. The characteristics and in-hospital evolution of the 12 non-surviving patients are presented in A total of 2,670 patients with any type of respiratory distress requiring IMV were identified to create the reference population. 3 on the day of admission.Factors associated with in-hospital mortality in bivariate analysis are presented in Tables In multivariate analysis, the only factor independently associated with in-hospital mortality was cardiac arrest on the day of admission. In-hospital mortality was 69% (n = 9) in the 13 patients who presented with cardiac arrest on the day of admission and 4% (n = 3) in the other 68 patients (p < 0.01) Tables  and S4.Our results suggest that patients with ASA requiring IMV have low mortality. Indeed, the in-hospital mortality of patients recruited in our study was low at 15%, and was even lower (4%) for the sub-group of patients who did not present a cardiac arrest on the day of admission.These results are in line with older studies, which reported mortality rates ranging from 0% to 38% for patients with ASA requiring IMV , 22. LikHowever, our in-hospital mortality results must be qualified. The in-hospital mortality rate of 15% was much lower than the in-hospital mortality rate of 25% predicted by the SAPS II score on admission . Moreover, compared to patients with any kind of respiratory distress requiring IMV, the SMR of patients with ASA relative to the SAPS II was very low at 0.48, and was even lower in the lower SAPS II quartile . These fIndeed, in our study, death was mainly due to multiple organ failure complicating cardiac arrest. As in other studies of ASA , cardiacInsofar as the complications that we have reported are concerned, an interesting point of our study is the higher than usually reported incidence of ventilator associated pneumonia . Indeed,Our study also explored the efficacy of salvage therapies . It has The main strength of our study is the comprehensiveness of the data. The latter applied to all of Reunion Island, since the only 2 ICUs of this French overseas territory were involved in the study. In other words, all Reunionese patients with ASA requiring IMV during the study period were analyzed.However, our study also has limitations that must be acknowledged. The first limitation is the retrospective nature of the study. Consequently, data collection is unfortunately sometimes not exhaustive: lack of anthropometric data, lack of respiratory mechanics values , etc. In addition, the selection of patients may have resulted in bias. Second, one might argue that our results cannot be transposed to other regions. Indeed, it has been suggested that the prevalence of asthma is higher in Reunion Island than in mainland France . HoweverOur study shows that nowadays, the mortality of patients with ASA requiring IMV is lower than that of patients with any other type of respiratory distress encountered in the ICU. Death was only due to multi-organ failure, with cardiac arrest on the day of admission being the most important risk factor. In patients who did not present with cardiac arrest on the day of admission, mortality was even lower. In view of these findings, patients with ASA who do not present a cardiac arrest on the day of admission should be given aggressive treatment, including salvage therapies like ECMO. However, other studies are needed to specify the precise indications and the selection of patients for such exceptional treatments.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file. 18 Aug 2020PONE-D-20-20581Acute severe asthma requiring invasive mechanical ventilation in the era of modern resuscitation techniques: a 10-year bicentric retrospective studyPLOS ONEDear Dr. PERSICHINI,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.plosone@plos.org. 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Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: Yes**********5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: This paper summarises the retrospective experience of ventilated asthma from an electronic database over 10 years. As such it contributes to a small number of patients reported in the literature.1. The strengths of this paper is the report of ECMO outcomes and greater detail of the international experience of ECMO in asthma should be reported in the discussion.2. There was a high incidence of ventilator associated pneumonia which seems at variance with other papers - could this be expanded upon and how that diagnosis was made3. A number pf patients received immunotherapy - could the rationale for this be expanded upon as it is unlikely to benefit in acute therapy4. The use of other respiratory failure seems an arbitrary basis by which to report a SMR in the asthma patients - the details of the matching needs to be described as SAPS II would seem not to be a good way to do this for asthma especially in that asthma patients have few comorbidities and perhaps would be better done with a charlson score as well or perhaps APACHE in include the chronic health points in SAPS II are very limited and severe in nature and there is a need to ensure that the respiratory failure is not compared in surgical or trauma patients- so much greater detail is needed on this area and whether this approach is a validated way to do it.5. There are more recent reviews of asthma managed in the ICU which the present data could be compared to6. In how many were as the IV adrenaline given for blood pressure support or for asthma? Was the Magnesium given as an infusion? Were bronchodilators given by MDI or nebuliser? At which point were the ventilator settings to report selected?7. Was there any information available on the degree of asthma control prior to admission and what follow-up was organised for these patients?**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  16 Sep 2020Response to ReviewersWe thank the reviewer for his comments, all of which have been considered as follows. 1. The strengths of this paper is the report of ECMO outcomes and greater detail of the international experience of ECMO in asthma should be reported in the discussion.We thank the reviewer for this suggestion. More details on the experience of ECMO in asthma have been added in the discussion: other interesting results on the 2 studies of Mikkelsen and Schmidt have been added, and in addition, we now mention the recent study of Yeo et al.  [page 18 – lines 336 to 355].2. There was a high incidence of ventilator associated pneumonia which seems at variance with other papers - could this be expanded upon and how that diagnosis was made.We agree with the reviewer on this point. In our study, the crude incidence rate is not especially higher than what we find in the most recent literature , but as the average length of stay is short in our study (7 [4-12] days), the incidence rate per 1000 days is actually higher at 24 episodes per 1000 ventilator-days . This point is now discussed in the revised manuscript in a specific paragraph on complications [page 16 – lines 302 to 312].According to international and French recommendations, diagnosis was made using a combination of clinical respiratory deterioration, a modification of the Chest x-ray and by the presence of a positive bacterial culture (quantitative or semi-quantitative) on a respiratory sample.3. A number of patients received immunotherapy - could the rationale for this be expanded upon as it is unlikely to benefit in acute therapy.We fully agree with the reviewer that this kind of treatment is not common in ICU. This type of medication is typically indicated in chronic hypereosinophilic asthma. Only one patient received immunotherapy (mepolizumab) in our study.Doubts and questions concerning the use of this type of treatment in acute therapy have been emphasized in the revised manuscript [page 17 – lines 325 to 333].4. The use of other respiratory failure seems an arbitrary basis by which to report a SMR in the asthma patients - the details of the matching needs to be described as SAPS II would seem not to be a good way to do this for asthma especially in that asthma patients have few comorbidities and perhaps would be better done with a Charlson score as well or perhaps APACHE in include the chronic health points in SAPS II are very limited and severe in nature and there is a need to ensure that the respiratory failure is not compared in surgical or trauma patients- so much greater detail is needed on this area and whether this approach is a validated way to do it.We agree with the reviewer on this point and we thank him for this valuable remark. SAPS II indeed does not take account of the history of chronic pathologies, unlike Charlson scores and APACHE II. Unfortunately, only SAPS II is collected prospectively on the medical records in our units, which is why it was chosen to construct the Standardized Mortality Ratio of our patients. If we had tried to find the APACHE and Charlson scores retrospectively by searching the medical records of the patients, this would have resulted in significant biases due to too many missing data.However, taking into account this important limitation, it should be noted that this method has already been used in 3 other published studies by our team on ARDS and/or septic shock:-Mortality of critically ill patients with severe influenza starting four years after the 2009 pandemic, David Vandroux et al., Infect Dis (Lond) 2019.-Acute respiratory distress syndrome in leptospirosis, David Vandroux et al., J Crit Care 2019.-Leptospirosis in ICU: A Retrospective Study of 134 Consecutive Admissions, Benjamin Delmas et al., Crit Care Med 2018).This important point is now discussed as a limitation of the study in the discussion section of the revised manuscript [pages 19/20 – lines 380 to 386].5. There are more recent reviews of asthma managed in the ICU which the present data could be compared to.This is a very pertinent comment indeed. As proposed by the reviewer, we reviewed again the most recent literature. We found four other interesting reviews and studies that we have added to the bibliography.The main results of these studies have been added to the discussion and provides more perspective and context:-A comparison of characteristics and outcomes of patients admitted to the ICU with asthma in Australia and New Zealand and United states, Abdelkarim et al., J Asthma 2020 [citation 19 and discussion page 16 – lines 296 to 298].-Noninvasive Ventilation Use in Critically Ill Patients with Acute Asthma Exacerbations, Althoff et al., Am J Respir Care Med 2020 [citation 20 and discussion page 15 – lines 275 to 279].-Clinical management practices of life-threatening asthma: an audit of practices in intensive care, Secombe et al., Crit Care Resusc 2019 [citation 24 and discussion pages 16/17 – lines 305 to 315].-Utilization of Mechanical Ventilation for Asthma Exacerbations: Analysis of a National Database, Nanchal et al., Respir Care 2014 [citation 13].6. In how many were as the IV adrenaline given for blood pressure support or for asthma? Was the Magnesium given as an infusion? Were bronchodilators given by MDI or nebuliser? At which point were the ventilator settings to report selected?Indeed, those are important matters on which we need to be more specific:-IV adrenaline: as the data were collected retrospectively, we cannot be absolutely sure of the indication the practitioner in charge had in mind. However, in our clinical practice, drugs indications are fairly standardized:° we use IV salbutamol when we are looking for a bronchodilator effect only.° when we are looking for a pressor effect only, we use norepinephrine. ° when we are looking for an inotropic effect only, we use dobutamine.° therefore, adrenalin is used most often for its double Beta1 and Beta2 effects, i.e. as an inotropic drug for cardiogenic shock associated with acute severe asthma but also for its bronchodilator effect.-Magnesium: always given as an infusion.-Bronchodilators: given by nebulizer only (no MDI devices are used in our ICU).-Ventilator settings: the reported ventilator settings were reported by the practitioner in charge on the first prescription sheet at day one, just after patient admission and clinical evaluation at the bedside.The sentences concerning these treatments and the ventilator settings have been modified; we hope that it is now clearer [page 11 – lines 200 to 214].7. Was there any information available on the degree of asthma control prior to admission and what follow-up was organized for these patients?Unfortunately, we do not have accurate information about asthma control of our patients prior to admission.It must be recognized that the degree of asthma control  is unfortunately often poorly researched with relatives when patients are admitted to intensive care. This notion may appear, wrongly, to be secondary to the immediate seriousness of the patient.The only information we have collected that could approach this notion is the history of previous ICU admissions (Table 1). In the majority of cases, the patients were transferred from ICU to the pneumology ward where follow up took place before hospital discharge. Unfortunately, we do not have access to this specific data.We hope that we provided a satisfactory answer to all the reviewer’s criticisms and requests and that the manuscript is significantly improved.Respectfully yours,Romain PERSICHINI on behalf of all the co-authors.Attachment_Response to Reviewers (16.09.2020).docxSubmitted filename: Click here for additional data file. 18 Sep 2020Acute severe asthma requiring invasive mechanical ventilation in the era of modern resuscitation techniques: a 10-year bicentric retrospective studyPONE-D-20-20581R1Dear Dr. PERSICHINI,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. 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For more information, please contact Kind regards,Corstiaan den UilAcademic EditorPLOS ONEAdditional Editor Comments :Reviewers' comments: 23 Sep 2020PONE-D-20-20581R1 Acute severe asthma requiring invasive mechanical ventilation in the era of modern resuscitation techniques: a 10-year bicentric retrospective study Dear Dr. Persichini:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact plosone@plos.org. 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Aggressive pituitary tumors (APTs) are associated with significant morbidity and mortality, and effective treatment options are limited. Immune checkpoint inhibitors (ICIs) have revolutionized clinical cancer care; however, there is little experience with these agents in the management of APTs. Vascular endothelial growth factor (VEGF) targeted therapy has reported success in a small number of APT case reports. Here we describe a case of pituitary carcinoma responding to ICI therapy and subsequently VEGF inhibition. We discuss the possible mechanisms and experience with ICI therapy and VEGF inhibitors in the management of APTs, biomarkers that may predict response, and the potential role of combination therapies including ICIs and temozolomide. Aggressive pituitary tumors (APTs) including pituitary carcinomas (PCs) are a subset of pituitary tumors with a more aggressive course defined clinically by significant invasion, rapid tumor growth rate, and resistance to optimal standard therapies . MorbidiImmune checkpoint inhibitors (ICIs) have revolutionized clinical cancer care and are now approved for use in many malignancies including melanoma, lung cancer, renal cell carcinoma, squamous cell, head and neck cancer, lymphoma, urothelial carcinoma and gastro-esophageal carcinoma . ICIs arThirteen cases of APTs treated with VEGF inhibition therapy have been reported, with the majority responding to treatment , 7–12. P2. This responded to high dose glucocorticoid therapy with recovery over 10 days. Ipilimumab was discontinued and maintenance nivolumab 3 mg/kg IV twice weekly was continued for 17 cycles over 8 months. There was a marked clinical and radiological response of the primary pituitary carcinoma and all metastatic lesions that was sustained for eight months  and was significantly greater in those receiving CTLA-4 inhibitors (3.2%) compared with PD-1 inhibitors (0.4%)  . The mecClinical experience with ICIs to treat APTs is limited with just two other cases reported in the literature to date. Lin et al. described the case of a 35 year old female with an aggressive ACTH secreting pituitary tumor that initially responded to combination TMZ and capecitabine prior to metastasizing to the liver. She subsequently received dual ICI therapy with ipilimumab and nivolumab resulting in a 92% reduction in volume of the liver metastasis, 59% reduction in intracranial tumor volume, and normalization of ACTH levels. The liver metastasis had low (<1%) PD-L1 expression by immunohistochemistry . InteresIt is possible that the excellent response to therapy observed in our case and that of Lin et al. was due to the use of combination CTLA4 and PD-L1 inhibition, compared with the use of pembrolizumab monotherapy as reported by Caccese et al. Pre-clinical studies suggest improved response to ICI combination therapy when compared to monotherapy by acting synergistically, increasing the number of tumor infiltrating lymphocytes, reducing T regulatory (T reg) lymphocytes, and retarding tumor growth , 26. ImpSeveral potential biomarkers for response to ICI therapy have been proposed in the management of other cancers which can be considered in the context of the cases described. High PD-L1 expression on tumor cells has been associated with improved response rate and survival in a number of cancers treated with PD-L1/PD1 inhibition including melanoma, non-small cell lung cancer, urothelial cancer, and renal cell carcinoma –38. HoweElevated tumor mutational burden (TMB) has emerged as a predictor of improved survival and response to ICI in tumors such as melanoma and non-small cell lung cancer. It is thought that tumors with a high mutation burden express higher numbers of neoantigens that can be recognized by the immune system in response to immune checkpoint inhibitor therapy –48. A grMLH1, PMS2, MSH2, and MSH6) that encode the MMR complex  which is defined by defects in one of four key genes  which can occur in up to 60% of patients treated with anti-CTLA4 antibodies and up to 20% of patients treated with anti-PD-1 and anti-PD-L1 antibodies . Fatal iAdverse effects of VEGFi occur as a result of endothelial dysfunction and include hypertension in up to 32% of patients and proteinuria in 23% of patients, as well as venous and arterial thromboembolic events, cardiotoxicity, impaired wound healing, gastrointestinal perforation, and increased risk of hemorrhagic events , 87.There is emerging experience using the combination of ICI and VEGFi therapy. Seminal phase III trials of atezolizumab plus bevacizumab in non-small cell lung cancer and hepatocellular carcinoma did not reveal any new safety signals , 88. ReaWhen considering the use of ICIs or VEGFi in the management of APTs, judicious risk assessment is paramount, taking into account the limited clinical experience thus far in APTs, the potential but unproven efficacy of these drugs, and the risk of adverse effects.The case we have reported demonstrates excellent initial response of a pituitary carcinoma to combination anti-CTLA4 and anti-PD-1 ICI therapy despite exhibiting an absence of biomarkers considered predictive of response. In this case, ICI therapy undoubtedly prolonged survival and reduced morbidity in this patient. Our experience and that of the previously published pituitary cases suggest that the combination of CTLA4 and PD-1 blockade but not PD-1 blockade alone may be more effective in the treatment of APT and PC and a rationale for this has been described. In addition, the case raises the possibility of sequential or combination ICI and VEGFi therapy as novel therapy for APTs. These new approaches to treatment of APTs represent promising new avenues for research.All datasets presented in this study are included in the article/supplementary material.Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.LL is supported by a University Postgraduate Award from the University of New South Wales.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


To describe the presence of practice effects in persons with Alzheimer disease (AD) or mild cognitive impairment (MCI) and to evaluate how practice effects affect cognitive progression and the outcome of clinical trials.11 as the primary outcome, we defined practice effects based on the improvement in the first two ADAS-Cog11 scores and then estimated the presence of practice effects and compared the cognitive progression between participants with and without practice effects. The robustness of practice effects was investigated using CDR SB, an outcome independent the definition itself. Furthermore, we evaluated how practice effects can affect sample size estimation.Using data from a meta-database consisting of 18 studies including participants from the Alzheimer disease Cooperative Study (ADCS) and the Alzheimer Disease Neuroimaging Initiative (ADNI) with ADAS-CogThe overall percent of practice effects for AD participants was 39.0% and 53.3% for MCI participants. For AD studies, the mean change from baseline to 2 years was 12.8 points for the non-practice effects group vs 7.4 for the practice effects group; whereas for MCI studies, it was 4.1 for non-practice effects group vs 0.2 for the practice effects group. AD participants without practice effects progressed 0.9 points faster than those with practice effects over a period of 2 years in CDR-SB; whereas for MCI participants, the difference is 0.7 points. The sample sizes can be different by over 35% when estimated based on participants with/without practice effects.Practice effects were prevalent and robust in persons with AD or MCI and affected the cognitive progression and sample size estimation. Planning of future AD or MCI clinical trials should account for practice effects to avoid underpower or considers target trials or stratification analysis based on practice effects. Thus either the treatment is ineffective or this is consistent with the conclusion that designing targeted trial or sub-group selection based on genotype APOE ε4 may not work unless there was a sufficiently large differential treatment effect between the APOE ε4 groups ); whereas for 1 year increase in age, the odds of demonstrating practice effect decreased by 4% (odds ratio: 0.960 [95% CI: 0.944–0.977]).Participants with practice effects were observed in all 10 studies (ADNI AD and ADNI MCI were considered as 1 study) ranging from 26.9% to 57.7% . The ove1 study) . For AD 11 score for patients with practice effects was generally higher at baseline than for those without practice effects at baseline, but lower in post baseline visits in all but one study regardless of the similarity in the mean baseline ADAS-Cog11  (With the same practice effects groups defined by ADAS-Cognd time) . Similarnd time) .11 [14 [When planning AD clinical trials, the sample size can be estimated in two ways. One is to estimate the mean (SD) of the change from baseline to the end of study for the primary endpoint using pilot studies or previously published studies; then a minimum clinical meaningful difference  is chosen to calculate the sample size. For example, in the EXPEDITION and EXPEDITION2 trials, the minimum clinical meaningful difference was chosen to be 1.8 points at 18 months on the ADAS-Cog11 [14 , and in 11), we re-ran all the analysis and obtained similar results in terms of the progression in CDR-SB, the change over time in ADAS-Cog11, and the variance of each group. Because some practice effects subjects under the first definition now belonged to the non-practice effects group under the second definition, the difference between the two groups for the second definition became smaller  for the practice effects group and an effect size of 0.2 (= 4*40%/8) for the non-practice effects group. Given the same sample size, such differences in the change from baseline and in the resulting effect sizes may be crucial in determining the success of AD trials. On the other hand, if the same minimum clinical meaningful difference is used for each group (meaning different percentage reductions are assumed for each group), then the practice effects group requires a much smaller sample size than the non-practice effects group. However, it is unclear which group of participants is more likely to respond to an experimental drug. For example, if the non-practice effects participants are associated with more rapidly progressive disease that is treatment-resistant, while the practice effects participants are more slowly progressive but treatment-responsive, then a larger trial with practice effects participants would be required to detect treatment effects. Moreover, absolute cutoff scores in ADAS-Cog11 change have been recommended to interpret treatment effects. For example, 1.5- to 4-point differences in ADAS-Cog11 (11 items or 14 items) over 6 to 18 months have been considered by some to be minimally clinically relevant [11 from baseline between the practice effects and non-practice effects participants suggest that these cutoff scores may miss a number of practice effects participants showing a significant change that is less than these thresholds.Varying the mixture of participants with practice effects and those without in AD trials, therefore, may have significant impact on the outcome of such trials due to the large differences in sample sizes. For example, assuming that the percentage reduction is the same, the change in ADAS-Cogrelevant , 27–29. 11 which itself will vary by illness stage, using practice effects provides a direct way for designing targeted trials or sub-group analyses based on the ADAS-Cog11 sample distribution for clinical trials. It also offers an alternative standard to measure disease severity based on the trial participants’ learning ability. Participants who learn or improve their ADAS-Cog11 scores are more likely to be less cognitively impaired than the non-practice effects participants, even within a narrowly defined study sample. The difference in practice effects can subsequently be taken into account in the statistical analysis or used for stratification of subjects to enhance an efficacy signal [Instead of relying on presumed relationships between genotypes or biomarkers and the ADAS-Cogy signal . Furthery signal , using py signal .11 and MMSE and the similarity in their primary cognitive functions [11 implicate the potential inaccuracy of categorizing disease stages by a single measurements. In future studies, it may be helpful to use the average of the first two measurements for categorizing disease stages.There is a prevalent opinion in AD research community that participants should be treated in clinical trials during the earlier stages of the illness in order to maximize the treatment benefits. Consequently, sub-group analyses based on the stages of illness have been conducted (e.g. mild AD vs moderate AD) . The MMSunctions , the obs11. This tells us that the information that is classifying individuals as having practice effects may be due to regression toward the mean [11, we re-classified practice effects groups using a minimum clinical meaningful threshold of 2 points. Results based on this classification are very similar and reinforce the robustness of practice effects.In our analyses, we observed that the strongest predictor of the practice effects group was the severity of cognitive impairment on the ADAS-Cogthe mean . Althoug11 and need to be tested with different cognitive outcomes. Additionally, using ADAS-Cog11 may underestimate the practice effect due to its lack of sensitivity to detect changes in preclinical AD stage. The use of measurements with greater sensitivity to change would be expected to lead to even greater power to detect changes in cognition and function over time. Third, from a pragmatic perspective of conducting a clinical trial, we employed the most straightforward method to define the practice effects by using the first two assessments. Although other methods such as the complex standardized regression-based method can be used [Potential limitations to this study include that the practice effects were defined based on two assessments collected over a variety of time intervals ranging from 28 weeks to 6 months. Although it would be ideal if all the intervals were the same, the consistent findings from each individual study and from the pooled studies alleviated the effects of unequal intervals. In a planned clinical trial, these two assessments can be collected at the screening and at the baseline; or consecutively at the baseline with a few hours/days apart before the administration of experimental drugs. How the results from this study may apply to these scenarios warrant further validation. Second, our findings are based on ADAS-Cog be used , these mAlthough, these findings might be confirmed in other pooled databases of cohort studies or clinical trials, it appears that practice effects can independently reflect participants’ true cognitive status and lead to significant difference in cognitive decline between participants with and without practice effects. Trial planning without considering practice effects may result in inefficient trials with insufficient power. It may be worthwhile to utilize practice effects in clinical trials by beginning with planning sub-group analysis in future studies or even targeted trials.S1 FigThe practice effects group progressed more slowly than the non-practice effects group in all but one study.(DOCX)Click here for additional data file.S2 FigThe practice effects group progressed more slowly than the non-practice effects group.(DOCX)Click here for additional data file.S3 FigThe practice effects group progressed more slowly than the non-practice effects group in all studies.(DOCX)Click here for additional data file.S4 FigThe practice effects group progressed more slowly than the non-practice effects group.(DOCX)Click here for additional data file.S5 Fig11 change over time.Similar results to those individual studies were observed for the mean ADAS-Cog(DOCX)Click here for additional data file.S6 FigFor both AD and MCI studies, the non-practice effects group declined faster.(DOCX)Click here for additional data file.S7 Fig(DOCX)Click here for additional data file.


Sleep apnea is a respiratory disorder characterized by an intermittent reduction (hypopnea) or cessation (apnea) of breathing during sleep. Depending on the presence of a breathing effort, sleep apnea is divided into obstructive sleep apnea (OSA) and central sleep apnea (CSA) based on the different pathologies involved. If the majority of apneas in a person are obstructive, they will be diagnosed as OSA or otherwise as CSA. In addition, as it is challenging and highly controversial to divide hypopneas into central or obstructive, the decision about sleep apnea type (OSA vs CSA) is made based on apneas only. Choosing the appropriate treatment relies on distinguishing between obstructive apnea (OA) and central apnea (CA).The objective of this study was to develop a noncontact method to distinguish between OAs and CAs.Five different computer vision-based algorithms were used to process infrared (IR) video data to track and analyze body movements to differentiate different types of apnea (OA vs CA). In the first two methods, supervised classifiers were trained to process optical flow information. In the remaining three methods, a convolutional neural network (CNN) was designed to extract distinctive features from optical flow and to distinguish OA from CA.2; 27 men and 15 women; mean number of OA 16, SD 30; mean number of CA 3, SD 7; mean apnea-hypopnea index 27, SD 31 events/hour; mean sleep duration 5 hours, SD 1 hour) were collected for this study. The test and train data were recorded in two separate laboratory rooms. The best-performing model (3D-CNN) obtained 95% accuracy and an F1 score of 89% in differentiating OA vs CA.Overnight sleeping data of 42 participants . The developed algorithm tracks and analyses chest and abdominal movements captured via an IR video camera. Unlike previously developed approaches, this method does not require any attachment to a user that could potentially alter the sleeping condition. Sleep apnea is a chronic respiratory disorder, caused by intermittent reduction (hypopnea) or cessation (apnea) of respiratory airflow during sleep. About 10% of the population have this disorder -5. The sDepending on the presence of breathing effort, sleep apneas can be divided into obstructive sleep apnea (OSA) or central sleep apnea (CSA) by measuring the thoracoabdominal movement and its contributions to the total respiratory volume . The majDuring normal breathing, the chest and abdomen move in phase due to interaction between the diaphragm and parasternal intercostals during inhalation . During The treatment of sleep apnea decreases patients’ health-related costs by 25% . A highlThe gold standard for differentiating OA from CA is the evaluation of swings in esophageal pressure measured via an esophageal catheter . Measurenight vision) video frames and were processed via computer vision algorithms.A promising approach to distinguish different types of sleep apnea is using computer vision systems. The goal of computer vision is to extract information from images or videos. In this study, a noncontact approach was proposed to identify the types of apneas (OA vs CA) using computer vision techniques. In this approach, the upper body respiratory movements were captured in infrared . Participants signed a written consent form before taking part in the study.Full overnight PSG was recorded for clinical diagnosis of sleep apnea in two separate rooms. Additionally, an IR camera  was mounted about 1.4 m above the bed. The rooms were illuminated by IR light (Raytec RM25-F-50). Simultaneous and synchronized with PSG, IR videos were recorded from an overhead view with the aforementioned camera at a resolution of 640×480 at 30 frames per second. The 680×480 resolution captured the upper body part  with sufficient detail.OA and CA were annotated by 3 trained individuals based on the RIP signal of the chest, the abdomen, the sum of the movement of the chest and the abdomen, nasal pressure, and oxygen saturation, following the American Academy of Sleep Medicine guideline ,26. The Recorded IR videos were down-sampled from 30 Hz to 2 Hz to decrease the computational cost. The breathing rate during sleep is between 12 and 25 breaths per minute, that is, below 0.5 Hz. Therefore, the reduced sampling frequency of 2 Hz still satisfied the Nyquist rate for the respiratory signal by a wide margin. As each apnea lasts a minimum of 10 seconds, the sampling rate of 2 frames per second translates to a minimum of 20 image frames per event.x (side to side) and the y (up and down) movement vector of each pixel from one video frame to the next. A 3D-CNN model was trained to analyze the sequence of optical flow images during each apnea to distinguish between OAs and CAs. This 3D-CNN model processed the optical flow of the entire image without explicit knowledge of where the person was at every frame of the video. For comparison, another CNN architecture was used to analyze the optical flow sequences in only the chest and abdomen regions. This model was trained to distinguish OAs from CAs via a late fusion of two 3D-CNN branches processing chest and abdominal movements. Performance was evaluated when either manually marked or automatically detected chest and abdomen regions were used. The performance of these CNN architectures was compared with three baseline models, including autocorrelation, movement histograms, and 2-dimensional fast Fourier transform (2DFFT)-CNN, which were chosen as commonly used approaches for motion analysis. These models were not applied previously for distinguishing OAs from CAs. The first two baseline models (autocorrelation and movement histograms) operate on the time-series data of optical flow movements, whereas the third baseline model (2DFFT-CNN) first transforms the signal into the frequency domain and then applies a CNN model to the resulting 2DFFT images.Frame-to-frame movements were tracked using dense optical flow. FlowNet 2.0 , a convox (side to side) and y (up and down) directions. Details of the 3D-CNN model are shown in Sleep apneas last a minimum of 10 seconds . A 3D-CNOAs are more frequent than CAs; therefore, to achieve a more balanced training set, different stride was using for the sliding window in OAs and CAs (stride of 1 second for CA and stride of 5 seconds for OA). In test time, a stride of 1 second was used, and voting  determined the estimated label (OA vs CA) for that event.To investigate if knowledge about the location of the chest and abdomen at each image frame improves performance, the frames were manually marked as follows: for each person, at the first video frame of their sleep. After each position shift, a human annotator manually marked the locations of the chest and abdomen via two rectangles on the image. If the participant was covered by a blanket, the annotator used his/her best judgment to mark these locations . Position shifts were automatically detected based on the total amount of movement in the scene, with a low threshold, so even small position shifts were not missed.As the annotation of the chest and abdomen regions is subjective and time-consuming, we have also developed an algorithm to automatically find the chest and abdomen regions. To develop this model, as the chest and abdomen were often covered by a blanket sheet, it was challenging to train an object-detection CNN to detect them directly. Instead, a CNN model (YOLO v3)  was usedTwo 100×100 images were cropped around the estimated center of the chest and abdomen. Dense optical flow was computed in cropped regions of both the chest and abdomen. A 3D-CNN branch processed the sequence of chest movements, and another branch processed the sequence of abdominal movements. Outputs from both branches were concatenated into a fully connected network. The network was trained end to end. The architecture of the entire network is shown in d=√(x2+y2)) was calculated from the original 2-channel optical flow image (640×480×2) to form a single-channel movement magnitude image (640×480). Pixels with a large movement magnitude (>0.5 pixel per second), likely caused by large position shifts, were capped, that is, set to 0.5. The average of the movement image was then calculated for each event, leading to a 1-dimensional movement signal m(t). A Butterworth band-pass filter with a lower cutoff frequency of 0.05 Hz and an upper cutoff frequency of 0.5 Hz was applied to the one-dimensional movement signal. Autocorrelation was computed for the filtered signals, and its first 10 peaks  were used to train three different binary classifiers to distinguish between OA and CA. Classifiers compared were linear support-vector machines, logistic regression, and random forest. Sample autocorrelation signals with their detected peaks are illustrated in This method uses autocorrelation to separate OAs from CAs based on their periodicity. The magnitude of the movement vector  was set equal to the event duration. The summations are over all the values of t.This method separates OAs from CAs based on their range of motion. Histogram of the movement magnitude was constructed for movements in the range of 0 to 0.5 pixels/second with a constant number of 1000 bins. Sample histogram signals for OA and CA are shown in This method separates OAs from CAs based on the frequency-domain representation of movement histograms. The movement histograms of each event were concatenated together over time to form an image and then transformed to the frequency domain via 2DFFT with a constant size of 128×128. A sample of 2DFFT signal is shown in The data were divided into training and validation and test sets by the room in which the study was conducted to ensure the setup camera placement did not affect the algorithm performance. The recorded data of 21 participants (recorded in laboratory room number 1) were used in the training and validation sets. This set included 40 CAs and 313 OAs. The remaining 21 (recorded in laboratory room number 2) comprised the test set, which included 75 CAs and 299 OAs.For the autocorrelation and movement histogram methods, classifier hyperparameters were tuned via 3-fold cross-validation on the training set. For the 3D-CNN (whole body) and 3D-CNN (chest and abdomen) methods, early stopping was based on performance on the validation set.Performance of the head, chest, and abdomen bounding box detection was evaluated based on accuracy at the intersection over union values higher than 0.5 between predicted and manually annotated regions.P value of .04.Data from 42 participants (27 men and 15 women) were collected for this study. Participants’ demographic information is shown in F1 score of 88.7%.Results of distinguishing OAs from CAs are shown in The proposed 3D-CNN model outperformed all three baseline methods. We hypothesized that localizing the chest and abdomen in the video will increase the signal-to-noise ratio to improve performance. However, as shown in The methods developed and evaluated in this study are the first to use computer vision to differentiate between OAs and CAs. Although the models were externally validated on data collected in a different room, a limitation of this study was that the same camera model and camera setup was used to collect data in both rooms. Remedying this limitation will involve external validation on a dataset that will be recorded under different conditions, for example, use of another camera model, different viewing angle, or a different camera distance from the bed. This will evaluate how the models trained here generalize to potential variations that might occur in real-life scenarios, for example, in the home. Another limitation of the current system is that it relies on the assumption that apneas were already segmented, for example, using previously developed vision-based methods . RemedyiTo address the challenges associated with PSG, there have been several investigations to develop convenient sleep apnea screening devices that can also distinguish CA from OA ,28,31,32In one attempt, Nandakumar et al  tracked This research project is the first vision-based noncontact method that differentiates sleep apneas by tracking body movements using IR videos. The developed algorithm was validated on 42 participants with various levels of sleep apnea severity. The algorithm performed well in distinguishing the OAs from the CAs. In this study, it was assumed that apneas were given. Future work can apply existing techniques  or novel


Previously, we showed that activation of CaMKII triggers the exchange of subunits between holoenzymes, potentially increasing the spread of the active state . Using mass spectrometry, we show now that unphosphorylated and phosphorylated peptides derived from the CaMKII-α regulatory segment bind to the CaMKII-α hub and break it into smaller oligomers. Molecular dynamics simulations show that the regulatory segments dock spontaneously at the interface between hub subunits, trapping large fluctuations in hub structure. Single-molecule fluorescence intensity analysis of CaMKII-α expressed in mammalian cells shows that activation of CaMKII-α results in the destabilization of the holoenzyme. Our results suggest that release of the regulatory segment by activation and phosphorylation allows it to destabilize the hub, producing smaller assemblies that might reassemble to form new holoenzymes.Ca Mutatio2+/CaM . Consist2+/CaM . Recent 2+/CaM . A prominent feature of the hub assembly is the presence of grooves located at the inter-subunit interfaces. These grooves are lined by negatively-charged residues, and we proposed that positively-charged residues in the calmodulin-binding element might recognize these negatively-charged residues . Each inIn this paper, we present the results of investigations into interactions between the regulatory segment and the hub, and the effect of activation on the stability of the holoenzyme. We used electrospray ionization mass spectrometry to show that peptides derived from the regulatory segment can bind to and destabilize the dodecameric or tetradecameric CaMKII-α hub assembly, releasing smaller oligomers of the hub domain. We generated a 13 μs molecular dynamics trajectory of the dodecameric hub of CaMKII-α, which shows that two regulatory segments bind spontaneously to the hub at two inter-subunit interfaces. This docking is facilitated by large distortions in the structure of the hub, which reflect an intrinsic feature of hub dynamics, as shown by a normal mode calculation. Finally, we use single-molecule TIRF microscopy to show that activation of CaMKII-α expressed in mammalian cells is accompanied by apparent destabilization of the holoenzyme.2+/CaM-independent activity, or ‘autonomy’ when phosphorylated . In these experiments, CaMKII-α hub at a final subunit concentration of 120 µM was incubated with Peptide Aphos for 5 min at room temperature prior to injection into the mass spectrometer under similar ionization conditions as before. Under these conditions, the mass spectra obtained comprised predominantly of smaller oligomeric species and aggregates, suggesting that the breakage of the hub is accelerated in the presence of the phosphorylated peptide compared to the unphosphorylated peptide. We dispensed with the incubation step, and the sample was injected directly into the mass spectrometer as soon as the hub, at a final subunit concentration of 120 µM, was mixed with Peptide Aphos at final concentrations of 1 µM, 10 µM and 100 µM  and ATP (10 mM), captured the activated CaMKII-α on a coverslip functionalized with streptavidin, and measured the distribution of fluorescence intensity of the imaged spots. These conditions have been shown previously to result in robust phosphorylation of CaMKII-α on Thr 286, with a lower amount of phosphorylation on Thr 305/Thr 306  leads to destabilization of the hub, with the release of dimers from the isolated hub . We used2+/CaM for kinase activity. Once phosphorylated at Thr 286, CaMKII subunits acquire calmodulin-independent activity (autonomy). Thr 286 phosphorylation must necessarily occur in trans, with one kinase subunit phosphorylating another. Efficient Thr 286 phosphorylation occurs only within a holoenzyme  followed by a linker (GASGASGASGAS) at the N-terminus of mEGFP. Full-length human CaMKII-α (Uniprot_ID: Q9UQM7) was cloned into this vector backbone (Clontech), at the C-terminus of mEGFP, with a linker sequence (PreScission protease site: LEVLFQGP) separating the mEGFP tag from the coding sequence of CaMKII-α, before being overexpressed in mammalian cells . BirA was cloned into the pSNAPf vector (New England Biolabs) after modifying the vector to remove the SNAP-tag. All constructs with insertions and deletions were made using standard protocols for Gibson assembly (New England Biolabs). All point mutants used were generated using standard Quikchange protocols (Agilent Technologies).For the mass spectrometry analyses, the human CaMKII-α hub domain  was cloned into a pET-28 vector (Novagen) that was modified to contain a PreScission Protease (Pharmacia) site between the N-terminal 6-histidine tag and the coding sequence, before being expressed in an cells . This coα hub domain was expressed in E. coli and purified as previously described  and lysed using a cell homogenizer. The cell lysate was filtered through a 1.1 micron glass fiber prefilter (ThermoFisher). The filtered lysate was loaded onto a 5 mL Ni-NTA column and eluted with Buffer B . The eluate was desalted using a HiPrep 26/10 desalting column into Buffer A with 10 mM imidazole, and cleaved with PreScission protease (overnight at 4°C). The cleaved samples were loaded onto a Ni-NTA column, the flow through was collected, concentrated and purified further using a Superose six gel filtration column equilibrated in gel filtration buffer phosphine [TCEP] and 10% glycerol). Fractions with pure protein were pooled, concentrated and stored at −80°C. All purification steps were carried out at 4°C, and all columns were purchased from GE Healthcare .Human CaMKII-escribed . Briefly2O. All peptides used in this study were purchased from Elim Biopharm, Hayward, CA. The hub and peptide were mixed such that final concentrations in the reaction mix contained 120 µM CaMKII-α hub (subunit concentration) and 1 µM to 1 mM of the peptide, with a constant ionic strength of ~400 mM of ammonium acetate. This reaction mix was incubated for 5 min at room temperature before analysis by electrospray ionization mass spectrometry. In experiments of the hub incubated with phosphorylated peptides, the mass spectra obtained comprised predominantly of smaller oligomeric species and aggregates. Therefore, the last incubation step was eliminated, and the sample was introduced into the mass spectrometer as soon as the hub was mixed with the phosphorylated peptide. As a control experiment, 120 µM of CaMKII-α hub in 400 mM ammonium acetate was also incubated for five minutes at room temperature and analyzed using electrospray ionization mass spectrometry.Stock solutions of CAMKII-α hub were buffer-exchanged into 1 M ammonium acetate using a Bio-Spin column . 10 mM stock solutions of different regulatory segment-derived unphosphorylated and phosphorylated peptides were prepared by dissolving the lyophilized powder in ddHMass spectra were acquired on a Waters SYNAPT G2-Si mass spectrometer . Ions were formed from borosilicate emitters with a tip diameter of ~500 nm that were pulled from capillaries  using a Flaming/Brown micropipette puller . The submicron emitters were chosen to help reduce salt adducts on the protein ions and to reduce the chemical noise . Nanoelem/z (mass-to-charge ratio). For all experiments, the mass spectral results were continuously recorded as long as protein signals were observed. Mass spectra of the hub incubated with peptides were generated by averaging the scans for specific time segments after the initiation of electrospray ionization. These times correspond to the start of the mass spectrometry data acquisition and do not include the initial incubation time.To minimize collisional activation of the ions, a relatively low-sample cone voltage (50 V) and low-source temperature (80°C) were used. The voltages of collisional induced dissociation cells (both Trap and Transfer cells) were set at 2 V, a value at which no gas-phase dissociation of the protein complex was observed. Mass spectral data were smoothed using the Savitsky-Golay smoothing algorithm, available via the Waters MassLynx software, with a smoothing window of 100 2O. The hub and peptide were mixed in 1M ammonium acetate to achieve final concentrations of 120 µM CaMKII-α hub (subunit concentration) and 500 µM of the peptide. This reaction mix was incubated for 15 min at room temperature before loading onto the gel filtration column. Samples  were loaded onto a Superose 6 10/300 column  equilibrated with 1M ammonium acetate at pH 7, at a flow rate of 0.5 ml/min .For analytical gel filtration chromatography, stock solution of CAMKII-α hub was diluted to 120 µM (subunit concentration) in 1 M ammonium acetate to maintain the same conditions with mass spectrometry. 10 mM stock solution of Peptide A was prepared by dissolving the lyophilized powder in ddHFor the long-timescale simulations, we built a dodecameric hub assembly by first building a model of a vertical dimer of hub domains connected to the regulatory segments by unstructured linkers. We ran short simulations of this structure while holding the hub domains fixed and allowing the linkers and regulatory segments to sample various conformations. We used instantaneous structures from these short simulations to build the dodecameric hub assembly with linkers and regulatory segments, to ensure that the simulation started with the regulatory segments in a variety of conformations at varying distances from the hub assembly.For the short simulations of a vertical dimer, one vertical dimer of hub domains (residues 345–472) was taken from the crystal structure of the human CaMKII-α dodecamer (PDB ID - 5IG3) . ResidueThe protein was solvated, and ions were added such that the ionic strength was 0.15 M, using VMD . The eneInstantaneous structures from these simulations, with the linker and regulatory segment in arbitrary conformations, were then used to build a dodecameric assembly comprising of the hub, linker and regulatory segments, by aligning a pair of vertical hub domain dimers onto the vertical hub domain dimers of the human dodecameric hub assembly (PDB ID – 5IG3) . This syA second system comprising of the dodecamer hub assembly only, without the linker and regulatory segments was built from the system described above, by removing residues 281–335 from each subunit. This system was solvated with TIP3P water and ions were added so that the final ionic strength was 0.15 M using VMD . The finThe energies of both systems were minimized first while holding the protein fixed, then while allowing all the atoms to move. The two systems were then equilibrated at constant pressure (1 atm) and temperature (300 K) for 5 ns. The NAMD package was used to run the minimization and equilibration simulations  with theProduction runs for both systems were carried out on Anton2 . The resThe angle between the αA helices (residues 341–363) of adjacent subunits were calculated using the CHARMM package . The r. elNémo server was used for the analysis with a minimum and maximum perturbation of 400, a step-size of 16 and a residue-block size of 8 (Suhre and Y.-H. The hub assembly (residues 340:470) from the structure of the dodecameric autoinhibited CaMKII-α (PDB ID – 3SOA) was used for normal mode analysis. The 2. CaMKII-α variants were transiently transfected using the standard calcium phosphate protocol. Briefly, calcium phosphate/DNA coprecipitate was prepared by combining CaMKII-α plasmids with 5 μg of empty pcDNA3.1 vector and 1 μg of BirA plasmid. The mixture was then diluted with 10X ddH2O, and CaCl2 was added such that the final CaCl2 concentration is 250 mM. This mixture was incubated for 15 min. One volume of this 2X calcium phosphate/DNA solution was added to an equal volume of 2X HEPES-buffered saline (HBS)  and the solution was mixed thoroughly by reverse pipetting. This mixture was then added to HEK 293 T cells and the cells were allowed to express the protein for 18–20 hr, before the protein was harvested.HEK 293 T cells (UC Berkeley cell culture facility) were grown in DMEM  supplemented with 10% fetal bovine serum (FBS), 1X antibiotic–antimycotic reagent (ThermoFisher) and 20 mM HEPES buffer and maintained at 37°C under 5% COAll single-molecule experiments were performed in flow chambers  that were assembled with functionalized glass substrates. The glass substrates  were first cleaned using 2% Hellmanex III solution  for 30 min, followed by a 30 min sonication in 1:1 mixture (vol/vol) of isopropanol:water. The glass substrates were then dried with nitrogen and cleaned for another 5 min in a plasma cleaner (Harrick Plasma PDC-32 G). These cleaned glass substrates were used to assemble the flow chambers immediately after plasma cleaning. After assembly, the glass substrates were treated with a mixture of Poly-L-lysine PEG and PEG-Biotin  for 30 min (SuSoS). The glass substrates were then washed with 2 mL of phosphate-buffered saline (PBS). Streptavidin was added to these glass substrates at a final concentration of 0.1 mg/mL and incubated for 30 min. Following incubation, excess streptavidin was washed away using 2 mL of PBS and these assembled flow chambers were used for all our single-molecule experiments.E. coli biotin ligase, BirA, with the CaMKII-α variants bearing an N-terminal Avitag, results in the biotinylation of the Avitag in HEK 293 T cells. After harvesting, the cells were lysed in a lysis buffer ), 0.5% phosphatase inhibitor cocktails 2  and 3 , 50 mM NaF, 15 μg/ml benzamidine, 0.1 mM phenylmethanesulfonyl fluoride and 1% NP-40 (ThermoFisher).The co-expression of the 2, 10 mM ATP and 20 mM MgCl2  for 60 min at room temperature. For the unactivated sample, the 60-min incubation was carried out in gel filtration buffer without the addition of any components of the activation buffer. For both the activated and unactivated samples, 100 μL of the diluted cell lysate was added to a well in the flow chamber. After incubation for 1 min, the diluted cell lysate was washed out with 1 mL of PBS. During this incubation, the biotinylated mEGFP-CaMKII-α variants were immobilized on the surface of the functionalized glass substrates, via the streptavidin-biotin interaction.The cell lysate was diluted in the gel filtration buffer . mEGFP-CaMKII-α in the diluted cell lysate was activated by incubating the lysate with an activation buffer containing 5 μM CaM, 100 μM CaClSingle-particle total internal reflection fluorescence (TIRF) images were acquired on a Nikon Eclipse Ti-inverted microscope equipped with a Nikon 100 × 1.49 numerical aperture oil-immersion TIRF objective, a TIRF illuminator, a Perfect Focus system, and a motorized stage. Images were recorded using an Andor iXon electron-multiplying CCD camera. The sample was illuminated using the LU-N4 laser unit (Nikon) with solid-state lasers for the channels emitting at wavelengths of 488 nm, 561 nm and 640 nm. Lasers were controlled using a built-in acousto-optic tunable filter. A 405/488/561/638 nm Quad TIRF filter set (Chroma Technology Corp.) was used along with supplementary emission filters of 525/50 m, 600/50 m, 700/75 m for the 488 nm, 561 nm and 640 nm channels, respectively. Image acquisition was performed with the automated change of illumination and filter sets, at 75 different positions from an initial reference frame, so as to capture multiple non-overlapping images, using the Nikon NIS-Elements software. mEGFP- CaMKII-α was imaged by illuminating the 488 nm laser set to 5.2 mW. Images for all the mEGFP-CaMKII-α variants were acquired using an exposure time of 80 ms, while keeping the laser power unchanged over all conditions.To correct for the baseline clamp and dark current, a series of dark images were collected under the same exposure time of 80 ms as the experimental sample. Uneven illumination and fringe interference effects in the intensity distribution  were corFor photobleaching experiments, the GFP-fluorescence signal was recorded in a stream acquisition mode, with an exposure time of 80 ms, under the same conditions as described above. As a control, the intensities and photobleaching traces of mEGFP-Hck, a monomeric protein kinase, were also collected under the same conditions.2 were included in the calculation. The intensity distributions for single particles of mEGFP-CaMKII-α (488 nm) were determined using custom in-house software written in Python. The total intensity values acquired from TrackMate for the 488-channel were adjusted by subtracting the local median background intensity for each spot  to produce an intensity histogram for all the mEGFP-CaMKII-α spots.Individual single particles of mEGFP-CaMKII-α were detected and localized using the single particle tracking plugin TrackMate in ImageJ . The parFor the analysis of the GFP step-photobleaching data, the photobleaching traces for each spot were built by plotting the maximum intensities of mEGFP-CaMKII-α as a function of time with MATLAB. The number of single photobleaching events were counted manually by inspecting the photobleaching trace for every spot. Single-step and two-step bleaching traces were clearly identified, but multistep photobleaching traces exhibited relatively unclear, distinct bleaching events. We therefore categorized the bleaching traces into single-step, two-step, and multi-step photobleaching. A similar analysis was used for mEGFP-Hck, which exhibited only single step traces.The intensity distribution of monomeric GFP species is lognormal when detected on an EMCCD camera, and is given by N times . An oligSubsequent convolutions of this modified probability mass function carry the effect of the dark GFP. The probability mass function was then reconverted back to a density function.We estimated the dark fraction (ν) by auto-convolving the monomeric distribution 12 times and determining value of ν that yields the best alignment of the predicted dodecameric distribution with the high-intensity peak in the experimental data. These gave values of ν ~0.3 . While tThe following procedure was used to create the final mixture model in  In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:The calcium/calmodulin-dependent kinase II (CamKII) plays key roles in the brain and heart. This paper uses an elegant combination of mass spectrometry, computational analysis, and cellular experiments to extend our understanding of the dynamics of the oligomeric structure of CamKII. Using synthetic peptides derived from the CaMKII regulatory segment, the authors show that the highly organized Hub structure of this kinase can be destabilized providing a molecular mechanism of controlling its cellular function.Decision letter after peer review:eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by Leslie Griffith as Reviewing Editor and Philip Cole as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Richard Bayliss (University of Leeds) (Reviewer #2); Dorothee Kern (Reviewer #3).Thank you for submitting your article "Breakage of the Oligomeric CaMKII Hub by the Regulatory Segment of the Kinase" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.eLife". Please let us know if you would like to pursue this option. As the editors have judged that your manuscript is of interest, but as described below request an additional experiment before it is published, we would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). First, because many researchers have temporarily lost access to the labs, we will give authors as much time as they need to submit revised manuscripts. We are also offering, if you choose, to post the manuscript to bioRxiv  along with this decision letter and a formal designation that the manuscript is "in revision at Summary:eLife that have suggested that CaMKII, which exists as a 12-mer or 14-mer complex, can exchange subunits upon activation by Ca/CaM. Here they show short peptides derived from the CaMKII regulatory segment can bind and destabilize the 12-mer using native ESI mass spec. Molecular dynamics simulations were also performed to model a mechanism for dissociation. Lastly, the authors show data from a single molecule assay that suggest that activation can cause dissociation.This paper builds on studies from the Kuriyan lab published in Essential revisions:eLife paper(s). They do feel, however, that the manuscript could be improved by additional data  and by additional prose/analysis/figures to flesh out a couple other areas  below.The reviewers found that this was both an interesting and potentially important follow-up to the lab's previous 1) The authors' previous studies indicated that phosphorylation of Thr305 and/or Thr306 in the regulatory domain potentiates subunit exchange. Indeed, the authors conclude that phosphorylation at T286 and T305/6 disrupt the linker's interactions with kinase domain and Ca/CaM, respectively, so that it can then bind to hub. However, none of the peptides  used in the current work were phosphorylated. Their prior paper indicated that peptide phosphorylation does not directly affect binding to the hub, but it should be very informative to compare the effects of Thr305- and/or Thr306-phosphorylation of peptide A to the current data set for subunit disassembly using the peptide/MS method.2) There is not enough detail in the figures to make a clear comparison of the distortions in the hub observed in the presence and absence of peptide. The reviewers were therefore not completely convinced about the relevance of these distortions to the mechanism of peptide-induced dissociation of the hub. The analysis of subunit-subunit changes is presented simply as angular changes, whereas the docking interface is shown in atomic detail. Would it not make sense to also show the interface interactions, and to present an analysis of the molecular contacts at these interfaces?3) In the second part of the manuscript, binding of peptide to the hub is investigated via docking/long MD simulations on ANTON. Two peptides are found to bind in two interfaces between subunits leading to distortions of the hub rom its normal circular shape to an oval shape. However, the hub does not actually separate at any of the interfaces. The authors suggest that the docking of additional segments to the hub are needed for hub disassembly. Would not the binding of just these two peptides as shown in Figure 5 with full disruption of the hub interactions in these two interfaces result in hexamers that are seen in the MS data? Why would docking of additional segment be needed? Looking at the rough time-scale of disassembly from the MS data (in the minute regime), could the more likely explanation for the lack of disassembly be that the process is too slow relative to the simulation times? A discussion of the timecourse of the dissociation, as observed by ESI-MS, and how this relates to the timescale of the simulation should also be included.4) The data purportedly demonstrating that activation of mammalian cell-expressed CaMKII holoenzymes are not completely convincing: there is no statistical analysis of the replicates and the changes in the area of the peaks appear rather minor in two of the three replicates. The effects, if any, on WT holoenzymes 60 min after activation appear to be very modest compared to the essentially complete disruption of the hubs that was observed within a few minutes of peptide addition. This would seem to be important to ascertain whether this apparent "holoenzyme dissociation" results from the specific mechanism defined in the prior studies, or from a more general instability of CaMKII over this extended incubation. Indeed, the surprisingly significant levels of monomer/dimer in the inactivated samples may result from an alternative more general instability, complicating interpretation. The authors need to acknowledge and comment on these issues and provide adequate data treatment. Essential revisions:The reviewers found that this was both an interesting and potentially important follow-up to the lab's previous eLife paper(s). They do feel, however, that the manuscript could be improved by additional data  and by additional prose/analysis/figures to flesh out a couple other areas  below.1) The authors' previous studies indicated that phosphorylation of Thr305 and/or Thr306 in the regulatory domain potentiates subunit exchange. Indeed, the authors conclude that phosphorylation at T286 and T305/6 disrupt the linker's interactions with kinase domain and Ca/CaM, respectively, so that it can then bind to hub. However, none of the peptides  used in the current work were phosphorylated. Their prior paper indicated that peptide phosphorylation does not directly affect binding to the hub, but it should be very informative to compare the effects of Thr305- and/or Thr306-phosphorylation of peptide A to the current data set for subunit disassembly using the peptide/MS method.phos) at different concentrations, when compared to unphosphorylated Peptide A. A similar effect was observed when phosphorylated Peptide B (Peptide Bphos) was mixed with the hub. In order to capture by mass spectrometry the more rapid destabilization upon the addition of Peptide Aphos or Peptide Bphos, we had to eliminate the 5-minute incubation prior to introducing the sample into the mass spectrometer that was done in the original experiments with Peptide A and Peptide B. That is, mass spectral acquisition was started as soon as the hub was mixed with the peptide. As the reviewer points out, our earlier publication had noted that there is no apparent difference in affinity between phosphorylated and unphosphorylated peptides. Those earlier experiments did not consider the effects of the peptide on hub stability. That the phosphorylated peptides are more effective at breaking the hub was therefore not anticipated. A more thorough analysis of this effect awaits future study.We thank the reviewers for this suggestion. We now include results from experiments that explore the effects of phosphorylated Peptide A and Peptide B on hub stability, as measured by electrospray mass spectrometry . We observed a more rapid decrease in hub stability upon addition of the phosphorylated Peptide A (Peptide A2) There is not enough detail in the figures to make a clear comparison of the distortions in the hub observed in the presence and absence of peptide. The reviewers were therefore not completely convinced about the relevance of these distortions to the mechanism of peptide-induced dissociation of the hub. The analysis of subunit-subunit changes is presented simply as angular changes, whereas the docking interface is shown in atomic detail. Would it not make sense to also show the interface interactions, and to present an analysis of the molecular contacts at these interfaces?We thank the reviewers for raising this point and have included figures of the distortions of the hub at an interface that “opens” and at which docking occurs, as well as one of the interfaces that “closes” . We have also included a figure , where the regulatory segment that docked at one of the open interfaces was modeled onto a closed interface, showing how steric clashes would prevent this docking unless the interface undergoes further distortion, which might lead to destabilization and disassembly of the hub. Hydrogen bonds across interfaces are preserved in the simulation, irrespective of whether the interface opens or closes, and we have included a discussion and figures showing this . While it is likely, based on analyses in Bhattacharyya et al., 2016, that these interactions will break when the hub undergoes disassembly, this has not occurred on the timescale of this simulation.3) In the second part of the manuscript, binding of peptide to the hub is investigated via docking/long MD simulations on ANTON. Two peptides are found to bind in two interfaces between subunits leading to distortions of the hub rom its normal circular shape to an oval shape. However, the hub does not actually separate at any of the interfaces. The authors suggest that the docking of additional segments to the hub are needed for hub disassembly. Would not the binding of just these two peptides as shown in Figure 5 with full disruption of the hub interactions in these two interfaces result in hexamers that are seen in the MS data? Why would docking of additional segment be needed? Looking at the rough time-scale of disassembly from the MS data (in the minute regime), could the more likely explanation for the lack of disassembly be that the process is too slow relative to the simulation times? A discussion of the timecourse of the dissociation, as observed by ESI-MS, and how this relates to the timescale of the simulation should also be included.We agree with the reviewers that the simulation is not long enough to capture the complete course of disassembly. Binding by two regulatory segments might be sufficient to induce disassembly and we have included this in the Discussion. We have also included a figure of one of the “closed” interfaces with a regulatory segment modeled into the docked position to show the steric clashes that might prevent further docking  without further distortion and destabilization of the hub.4) The data purportedly demonstrating that activation of mammalian cell-expressed CaMKII holoenzymes are not completely convincing: there is no statistical analysis of the replicates and the changes in the area of the peaks appear rather minor in two of the three replicates. The effects, if any, on WT holoenzymes 60 min after activation appear to be very modest compared to the essentially complete disruption of the hubs that was observed within a few minutes of peptide addition. This would seem to be important to ascertain whether this apparent "holoenzyme dissociation" results from the specific mechanism defined in the prior studies, or from a more general instability of CaMKII over this extended incubation. Indeed, the surprisingly significant levels of monomer/dimer in the inactivated samples may result from an alternative more general instability, complicating interpretation. The authors need to acknowledge and comment on these issues and provide adequate data treatment.Due to the nature of these experiments with cell lysates, conventional statistical measures, such as the average and standard error, are really not applicable. Variations from run to run are dominated by systematic error sources  that affect the degree to which the reaction progresses. To address these variations, we present data from multiple independent replicates (3 replicates) for each experiment. The consistent theme is that activation always increases the proportion of monomers, dimers and lower order oligomers. Figures 8 and 9 have been reformatted to emphasize this dominant feature of the data.The effect of activation on CaMKII holoenzyme destabilization is actually not that small. If we look strictly at the increase of dimers, we see that it increases ~1.3-2 fold in each replicate, which is significant. This can come from a relatively small fraction of dodecamer dissociation, and the original figures did not readily convey this fact. We have now updated the Figures 8 and 9 to more clearly indicate the fold-changes in dimer fraction.trans. In contrast, intact CaMKII holoenzyme is studied in the single-molecule experiments, where the CBE peptide segment is presented in cis. Also, the cell lysate experiments are done in the presence of saturating Ca2+/calmodulin, which binds to the regulatory segment . In addition, the holoenzyme activation may also lead to some subunit exchange, where the released smaller oligomeric species may re-equilibrate with the holoenzyme.The extent of peptide-induced destabilization is different between mass spectrometry and single-molecule TIRF as these are measuring two different samples and under very different experimental conditions. In mass spectrometry, we are studying the hub (without the rest of the protein) after addition of the calmodulin-binding element (CBE) peptide in 2+/calmodulin, which would normally subside to low levels after a calcium pulse. In these experiments, therefore, Ca2+/calmodulin protects the regulatory segment from phosphorylation on Thr 305/Thr 306, and also from interaction with the hub. In the mass spectrometry experiments it is surprising that we see so much breakage, given that the peptide is added in trans. Indeed, the incubation of the isolated hub with the CBE peptides at different concentrations does not lead to the detection of smaller oligomeric species by classical analytical gel filtration. In the gel filtration experiment, the peptide is separated from the hub as soon as the sample enters the column. It is important to note that classical biochemical experiments, such as gel filtration, may not detect destabilization, as it may be a subtle effect under those experimental conditions. In contrast, in the mass spectrometry experiment, the local concentration of peptides and hub may be very high in the electrospray droplets, and they may also be subjected to local heating. Note that such heating, if it occurs, does not lead to any detectable destabilization of the hub in the absence of the peptide. We have included this discussion in the revised manuscript and presented the gel filtration data as a supplementary figure . We believe this will inform future experiments trying to characterize subtle destabilization effects in CaMKII or other systems.The reviewer’s comments led us to appreciate the fact that the different experiments we have carried out represent different approximations of the physiologically relevant conditions, which are themselves not well understood. As noted above, the cell-based experiments are done in the presence of saturating Ca