MJMA 7.4) and the 2011 off Ibaraki earthquake (MJMA 7.6). We found that the coseismic ruptures of these earthquakes did not overlap with the active areas of slow earthquakes, while their foreshocks and aftershocks occurred in slow-earthquake-prone areas. Moreover, the 2011 off Iwate earthquake and the previous M7-class events shared common fault rupture characteristics: coseismic rupture occurred in a common asperity area, and afterslip with many aftershocks was triggered in the active area of slow earthquakes. Off the Ibaraki coast, tremor activity on a subducting seamount located updip of the coseismic rupture of the 2011 off Ibaraki earthquake implies that the seamount acted as a soft barrier to the coseismic rupture of the 2011 off Ibaraki earthquake. This study demonstrates that large earthquakes off the Iwate and Ibaraki coasts feature similar rupture behaviors, spatially complementary distributions of coseismic ruptures with slow-earthquake activity and foreshock and aftershock activities within and around slow-earthquake-prone areas. This information is useful in considering future large earthquakes along the Japan Trench.To improve our understanding of the interactions between regular and slow earthquakes along the Japan Trench, we investigated the spatial relationship of slow-earthquake activity with the preseismic, coseismic, and postseismic fault ruptures of interplate earthquakes off the Iwate and Ibaraki coasts, Japan, including two large interplate aftershocks of the 2011 Tohoku earthquake: the 2011 off Iwate earthquake ( These studies have shown that slow earthquakes frequently occur in regions neighboring megathrust seismogenic zone and sometimes trigger large interplate earthquakes. Therefore, the investigation of slow-earthquake activity can provide insight into the earthquake-rupture mechanism in subduction zones. To improve our understanding of the interactions between regular and slow earthquakes in subduction zones, it is important to investigate the relationship between the fault ruptures of large interplate earthquakes and the slow-earthquake activity. Nishikawa et al.5 revealed the comprehensive spatial distribution of slow earthquakes along the Japan Trench and compared the resulting distribution with the coseismic rupture extents of the 2011 Tohoku earthquake and large interplate earthquakes that occurred before the 2011 Tohoku earthquake. The authors concluded that slow-earthquake activity spatially complements the coseismic ruptures of large interplate earthquakes and discussed the variation in fault slip behavior along the Japan Trench based on the regional characteristics of slow-earthquake activity.Over the past few decades, a considerable number of studies have been carried out on “slow earthquakes”, such as tectonic tremors, very-low-frequency earthquakes (VLFs), and slow slip events (SSEs)5 focused mainly on coseismic fault ruptures, this study compiles various types of information on foreshock activity, mainshock coseismic rupture, aftershock activity, and slow-earthquake activity to understand the whole context of interplate slip behavior. We focus on two large interplate earthquakes that occurred after the 2011 Tohoku earthquake, namely, the 2011 off Iwate earthquake (MJMA 7.4) and the 2011 off Ibaraki earthquake (MJMA 7.6), which were not featured in Nishikawa et al.5. We investigate the spatial relationship of the slow-earthquake activity off the Iwate and Ibaraki coasts with the coseismic rupture extents of M7-class interplate earthquakes including the two large earthquakes in 2011. We further examine the spatial relationship of slow-earthquake activity with the foreshock and aftershock activities. The slow-earthquake observations employed herein include tremors, VLFs, and SSEs as well as earthquake swarms containing repeating earthquakes (referred to hereafter as “repeaters”), which can be used as potential indicators of SSEs7. We also discuss the role of a subducting seamount off the Ibaraki coast on the coseismic fault rupture of the 2011 off Ibaraki earthquake. Finally, we discuss the similarity between the rupture behaviors of large earthquakes off the Iwate and Ibaraki coasts.To expand our understanding of the variation in fault slip behavior along the Japan Trench, we probe the relationship between the preseismic, coseismic, and postseismic fault ruptures of interplate earthquakes and the slow-earthquake activity off the Iwate and Ibaraki coasts, Japan. Although Nishikawa et al.MJMA) of 7.4 occurred at 15:08 on March 11, 2011 [JST], approximately 20 min after the 2011 Tohoku earthquake. The moment magnitude (Mw) estimated from the moment tensor inversion by F-net of National Research Institute for Earth Science and Disaster Resilience (NIED) was 7.4. This event was the second-largest interplate aftershock of the 2011 Tohoku earthquake. Nishikawa et al.5 divided the slow-earthquake activity along the Japan Trench into three along-strike segments: the northern segment (39° N to 40.7°N), the central segment (37.3°N to 39°N), and the southern segment (south of 37.3°N). This earthquake occurred in the northern segment.Off the coast of Iwate Prefecture, Tohoku region, Northeast Japan Fig. , a thrusIn this study, we estimated the source process of this earthquake by using a joint source inversion with near-source waveforms and geodetic data see “” sectionSlow earthquakes actively occurred in the area surrounding the source region of the 2011 off Iwate earthquake see “” section8, three earthquakes occurred in the period between the 2011 Tohoku earthquake and the 2011 off Iwate earthquake  and the 1989 off Sanriku earthquake , occurred off the Iwate coast. The source inversion analysis12 using near-source waveforms indicated that the major slip area of the 1989 event was the same as that of the 1960 event; their slip distributions are shown in Fig. Several e MJMA 7. and the 12. Furthermore, the common aftershock area corresponds to the active aftershock area of the 2011 event, indicating that the three events have common fault rupture characteristics: coseismic rupture occurred in the common asperity and many aftershocks were triggered on the updip side of the asperity. However, the time interval between the 1989 and 2011 events is approximately two-thirds of that between the 1960 and 1989 events. The shortening of the recurrence interval may have been caused by the triggering effect of the 2011 Tohoku earthquake.The spatial distributions of the aftershocks corresponding to the 1960 and 1989 events are shown in Fig. 14 and the 2011 Tohoku earthquake14. Considering that the accelerated recurrence of repeaters reflects rapid aseismic slip on the plate interface7, these results suggest that afterslip occurred just after the 1989 and 2011 events and that these afterslip triggered numerous aftershocks on the updip side of the coseismic ruptures. The similarity between the aftershock activity of the 1960 event and that of the other two events implies that an aseismic slip transient also occurred immediately after the 1960 event in the same area.The common aftershock area corresponds to the active area of earthquake swarms containing repeaters  and its spatial extent was approximately 60 km × 30 km. Figure 5. Tremors actively occurred updip of the area of large slip for the 2011 off Ibaraki earthquake  and the 2008 off Ibaraki earthquake , exhibit a recurrence interval of approximately 20 years20. The slip distributions of the two most recent events in 198220 and 200821 are shown in Fig. 7 suggested the recurrence of aseismic slip transients in this area and pointed out that the aseismic slip transients that preceded the 1982 and 2008 M7-class events had larger seismic moments than the other transients. Moreover, the aftershocks of the 1982 and 2008 events occurred mainly in area Y and the foreshocks and aftershocks of the 1982, 2008, and 2011 events occurred in this common area (area Y), but the coseismic rupture extent of the 2011 event does not overlap with those of the other events.The characteristic 20. Based on the fact that the fault rupture of this earthquake did not reach the seamount zone, Kubo et al.17 suggested that the seamount likely stopped the rupture propagation of this event by acting as a barrier to fault rupture. However, the behavior of a seamount or ridge in resisting the coseismic rupture of an interplate earthquake is still controversial25. Here, we shall focus on the barrier mechanism of a seamount in response to fault rupture. One reasonable hypothesis is a “hard” barrier to fault rupture that has a strong frictional resistance. Scholz and Small22 suggested that the subduction of a large seamount increases the normal stress across the subduction interface and locally strengthens the seismic coupling . Accordingly, if the seamount area is not ready for coseismic rupture, a seamount with a strong frictional resistance will act as an indenter against the subducting plate and impedes earthquake rupture propagation. In Central America, the Cocos Ridge is expected to act as an indenter against the Caribbean Plate24. However, the hard-barrier interpretation in our case is inconsistent with the fact that the seamount zone overlaps the active area of tremors (area X) because the occurrence of tremors indicates a frequent release of interplate strain. Another plausible idea is a “soft” barrier to fault rupture that has little potential for coseismic fault ruptures. Mochizuki et al.20 suggested that the interplate coupling in the seamount zone is very weak, probably due to the fluid-rich sediment entrained in the subducting seamount. This indicates that the seamount has little potential for coseismic fault rupture and thus arrests coseismic rupture propagation. The occurrence of tremors supports the soft-barrier idea because abundant fluids are one of the possible causes of slow earthquakes26. Based on these observations, we propose that the fault rupture of the 2011 off Ibaraki earthquake was stopped by a soft-barrier seamount. Another example of the soft-barrier model is the Nazca Ridge, which is subducting beneath offshore central and southern Peru. Perfettini et al.25 revealed that the subducting Nazca Ridge with low interseismic coupling stopped the seismic rupture propagation of the 2007 Pisco earthquake (Mw 8.0) and featured prominent afterslip after the 2007 event.In the updip side of the source area of the 2011 off Ibaraki earthquake, a subducting seamount  of the megathrust seismogenic zones off the Iwate and Ibaraki coasts frequently release their strain energy via slow earthquakes and do not rupture coseismically Figs. , 3, cons7. Here, we speculate that some large interplate earthquakes off the Iwate and Ibaraki coasts  were preceded by SSEs located updip of their coseismic rupture areas. However, a large observable SSE that triggers intensive foreshock activity is not a prerequisite for the occurrence of large interplate earthquakes off the Iwate and Ibaraki coasts because the 1960 off Sanriku earthquake was preceded by only a few foreshocks  and from 15:11:00 to 15:14:00 (JST), respectively. Then, the coseismic static displacements for the event were obtained by differencing the preseismic and postseismic positions. This study used two horizontal displacement components (east–west and north–south) at 83 GEONET stations . We obtained station positions every 30 s using Kinematic Precise Point Positioning as implemented in RTKLIBs Figure .30. The fault model was divided into 81 subfaults, each with dimensions of approximately 10 km × 10 km. The strike and dip angles of each subfault were calculated by Shiono’s31 method from grid data for the plate boundary of the JIVSM. The horizontal location of the rupture starting point was fixed at , which is the epicenter location in the JMA unified seismic catalog. The depth of the rupture starting point was set to 28.6 km, which corresponds to the depth of the plate boundary in the JIVSM at the JMA epicenter.A curved fault model with a size of 90 km along strike and 90 km along dip Figure  was assu32. Because we estimated the weights of the slips with 45° and 135° rake angles for each time window at each subfault, together with a nonnegative constraint, the rake angle of the slip vector for each subfault was allowed to vary within 90° ± 45°. The slip history at each subfault was represented by a series of nine smoothed-ramp functions with a width of 4.0 s, each with a 2.0-s lag. The triggering velocity of the first time window of 3.6 km/s was selected to minimize the data-fit residual. Although the amplitudes of the strong-motion waveforms in the source inversion were normalized by the maximum amplitude at each station, this normalization was not applied to the geodetic data to avoid the instability caused by the low signal-to-noise ratio data with small absolute values33. The relative weight between the datasets was determined to ensure that the data fit for each dataset was satisfactory.The spatiotemporal rupture history was estimated by using the fully Bayesian multiple-time-window source inversion34 and the reflection/transmission matrix method35, with a one-dimensional (1-D) layered velocity structure model. The 1-D velocity structure models were obtained for each station from the three-dimensional velocity structure model37. Logging data were also referenced for the KiK-net stations. For the geodetic Green’s functions, we calculated the theoretical static displacements caused by a unit slip on each subfault, assuming a homogeneous elastic half-space38.The strong-motion Green’s functions were calculated using the discrete wave number method20 N m (Mw 7.4) and 1.0 m, respectively. Large slips (> 0.5 m) are distributed at depths of 20–35 km including the epicenter with a maximum slip of 1.0 m, and the spatial extent of large slips is approximately 50 km × 60 km. During the first 5 s, the rupture slowly grew around the hypocenter with small slips. Subsequently, the rupture developed in the area of large slip with a large moment release between 5 and 20 s. The total rupture duration was approximately 30 s. The synthetic strong-motion waveforms and static displacements matched well the observations .We used the catalogs of tectonic tremors, VLFs, and earthquake swarms containing repeaters provided by Nishikawa et al.Supplementary information.


Due to COVD-19, many health/wellness programs transitioned from in-person to virtual. This mixed methods study aims to explore older adults with Parkinson’s disease (PD) perceptions of in-person versus virtual Parkinson’s-specific exercise classes. Attitudes, perceptions, and experiences were determined through focus groups  among older adults with PD and an online survey . Eighteen respondents attended both in-person and virtually . Four respondents only attended in-person, citing reasons such as difficulty with computer access to virtual classes, limited internet, easier accessibility to in-person classes, and physical injury preventing attendance to any classes. Respondents who participated in both delivery methods preferred virtual classes. Time, convenience, comfort at home, and not having to navigate transportation barriers supported participants’ preference for virtual classes. The majority of respondents indicated their fatigue and mental health were either unchanged or improved. Eighty-nine percent reported improved mobility since attending either class; specifically, in balance (n=8), flexibility (n=7), and coordination (n=3). Older adults with PD who attended both classes had minimal difficulty with computer usage and accessing the virtual program with only one participant reporting difficulty transitioning from in-person to virtual classes. Seventy percent stated they would enjoy a combination of on-site and virtual programming. Eighty-nine percent and seventy-seven perfect felt the virtual-based program was safe and beneficial, respectively. Participants who transitioned from an in-person to a virtual exercise program for people with Parkinson’s disease felt the program was safe, effective, and improved or prevented declines in their mobility.


Leveraging the collective experience of program leaders at Queen’s University, where CBME simultaneously launched across 29 specialty programs in 2017, this paper leverages change management theory to provide a short summary of how program leaders can navigate the successful preparation, launch, and initial implementation of CBME within their residency programs.Competency-based medical education (CBME) curricula are becoming increasingly common in graduate medical education. Put simply, CBME is focused on educational outcomes, is independent of methods and time, and is composed of achievable competencies. Oversights and difficult conditions will surely be encountered if the processes driving change are rigid, non-iterative, and top-down, or neglect important support structures and personnel essential to the overall functioning of a program. Proceeding prematurely and/or unprepared puts a program at risk during the implementation process. Luckily, this need not be the case.Worldwide, competency-based medical education (CBME) curricular models are now increasingly common.6,7 Through their lived experiences, this cohesive group of postgraduate medical education leaders negotiated a shared understanding of CBME theory and worked collaboratively to navigate the institution-wide transition during the first years of implementation. This collective experience from our university context is shared in a series of tips, adapted from Kotter’s 8 step change model,8 about how to be successful when implementing CBME at the program level.In 2017, 29 specialty programs at Queen’s University in Kingston, Canada launched CBME curricula simultaneously, uniquely positioning its program leaders to offer insights to inform others’ efforts in their implementation of Competency by Design (CBD) across Canada.8 In 2015, a 3-day program leader workshop was held at Queen’s University by the central CBME team, more than two years prior to the institutional 2017 launch date, to communicate the plans of the transformative change process and ignite early developments at the program level. This was immediately followed by messaging across all departments, divisions, and programs so that all stakeholders were aware that a new curricular model would be launched across all specialty programs within postgraduate medical education. Numerous stakeholder meetings and townhalls were held across the institution and division and department chairs met with program education leaders to begin steps to raise immediate awareness of CBME at the program level.Creating a sense of urgency by raising awareness about an existing problem and helping people see a possible solution is the first step in a change management process.Early on, education leaders leveraged multiple opportunities within their programs at grand rounds, departmental meetings, education rounds, and using blogs and online resources to communicate that a large-scale transformative change was underway. It was explicitly communicated that this change would affect everyone – leaders, frontline faculty, trainees, program administrators, hospital partners, and patients.8 Ultimately, this coalition helps spread the change message, delegates tasks and ensures there is support for the coming change. After all, introducing CBME should be conceptualized as departmental change, not merely curricular renewal. As an early strategic priority, education leaders must become effective coalition builders—establishing strong partnerships with those who influence resource allocation decisions. Fostering mutually supportive relationships with department (and division) leaders, departmental resource committees, dean’s office personnel, and hospital leadership are essential early steps in the process. At a minimum, this means setting up regular meetings with departmental leaders to continually message the importance of investing in the change. This is not simply about financial support; these individuals and groups can facilitate necessary access to faculty time, administrative support, and avenues of communication.Since clinical education happens in a complex, resource-demanding context blending patient care, education, and research, it is important to think broadly about the composition of this coalition. According to Kotter’s model, identifying a team of influential people with a range of skills and experience to help champion change must be a priority.8 Determining the values that are central to CBME curricular reform and designing a plan for change are fundamental components of creating this unifying vision. Operationalizing CBME is disruptive and initially threatens the status quo of all involved. Adopting the right change management strategy helps address challenges related to stakeholder engagement, information sharing, and ultimately dealing with resistance.9 Early preparation involves not only information sharing about the benefits of CBME curricular reform, but also invites co-production with stakeholders about how best to operationalize features of these new curricula.Once the change coalition is in place, a concise, comprehensive, but accessible message must be developed that will inspire action.10 This initial resistance is mitigated by exploring the rationale for change, how CBME can assist in this pursuit, and underlining the iterative process of curricular reform. Early and ongoing stakeholder engagement supports individuals to adopt the required transformational shift. Nurturing ongoing conversations, debate, and discussions across all stakeholder groups  builds momentum of the CBME project and stimulates the emergence of collaborative solutions.It is common to encounter conscientious objectors, masked as resistors, who perhaps don’t fully understand what is happening, need to be convinced of a need for change, or fear change in general.what to do’ and have a clear understanding of the why and how of CBME program design.Implementing CBME significantly expands the responsibility and complexity of the program administrator (PA) role. PAs will manage a larger flow of assessment data and reports, coordinate the sequence of meetings and reporting demanded in CBME, manage and direct faculty and residents engaged in the assessment program (academic advisors and competence committee members), implement an expanded, reliable, and closed loop communication strategy, and serve as a super-user of the electronic assessment platform. Success demands that PAs go beyond the ‘Promoting regular collaboration across program administrators to form community networks also fosters the sharing of early lessons learned and resources developed to address shared needs. Such activities can reduce feelings of isolation and serve to distribute the burden of resource development when common needs are identified. Although many resources will be program-specific , ideas gleaned from one program can be customized to the context-specificity of others. For example, adapting context-specific training materials for frontline faculty – including regional faculty  and learners  can be very effective.8 Piloting components of a new CBME program is a low-risk, effective way to field-test with minimal consequences. These types of activities engage faculty and learners in the change process and promote acceptance of change.11 For example, piloting assessment tools provides faculty the opportunity to experience their ease of use and promotes learners’ acceptance, ultimately lessening the enormity of change, and needed assessment tool modifications such as length of assessment, format, entrustment scales and electronic delivery methods prior to the official CBME launch date and initial implementation period. Such opportunities can also identify challenges, inform refinements, and promote feelings of ownership, but also offer everyone the chance to gain familiarity with the electronic platform before full implementation. This provides short-term wins that help motivate all involved.Change theory cautions about the challenge of maintaining momentum over the long-term and advocates for the setting of short-term goals to help offset this risk.There are many other examples of short-term wins to maintain momentum that should be celebrated within programs, such as new education champions recruited to the program, trainees interested in helping with CBME implementation, successful funding grants, academic projects and scholarship that stems from the CBME change, and positive developments in IT platform functionality.12 This is ideally tailored to address ongoing stakeholder needs. For example, program leaders benefit from learning about strategies for leading and optimizing change efforts, especially in relation to shifting program culture.13 Providing opportunities for this group to share their challenges and useful strategies in a supportive environment fosters cross-pollination and provides emotional support and practical suggestions about navigating the inevitable implementation dip.Acknowledging the significant investment required to launch CBME, development initiatives must be maintained for program leaders, frontline faculty, and residents post-launch.14 While frontline faculty need orientation to entrustable professional activities (EPAs) and new assessment tools, residents also need to understand what is expected of them. As assessment paradigms shift, residents will need to move from simply becoming comfortable asking for EPA assessments on a daily basis to actively seeking out appropriate learning opportunities in order to fulfill their clinical and non-clinical experience requirements. Building on the cultural change necessitated by residents becoming the primary drivers of their assessment experiences, trainees can be encouraged to take progressively greater responsibility for identifying and addressing their learning needs.The long- term success also requires resident trainees to take an active role in their learning in CBME.Lastly, CBME is associated with a marked increase in assessment data collection, interpretation, and reporting. To support learning, coaching, progress and promotion decision-making, and appeals policies, programs must standardize these processes. Developing templates for learning plans, academic advisor reporting, and competence committee reporting are key steps towards success and consistency in these areas.8 Documenting the shift to CBME via program evaluation is critical for understanding impact, understanding losses, and refining implementation efforts. With each program-level implementation, evaluation processes must be utilized to gather timely, formative feedback about whether the CBME program is being implemented as intended, uncover unintended outcomes, and identify iterative adaptations that need to occur. Multiple information sources inform such efforts, including for example, interviews, focus groups, stakeholder surveys, and data mining . With this knowledge in-hand, CBME implementation is improved in response to stakeholder experience informing iterative change, which also helps to inform others in their implementation efforts through dissemination of the evaluation results.6Finally, Kotter ‘s change model highlights the need to integrate the change into the organizational culture by making it visible, continuing to support it, and publicly valuing key contributors.8 and implementing it within our specific context promotes a better understanding of implementing CBME at the program level. The lessons shared by the program leaders at Queen’s University, through their lived experience, will hopefully assist you to get a grip on your CBME change journey.There are many challenges associated with implementing CBME at the program level. Bridging theory to practice brings with it many potential wrong turns and slips and requires explicit strategic planning to ensure success. Leveraging change management theory such as Kotter’s 8-Step Change Model


ARID1A in genomes of human cancer, including pancreatic cancer, its role in tumorigenesis is not clear. We aim to understand the role of Arid1a in pancreatic cancer development and maintenance by investigating its role in both early pancreatic precursor cells and established pancreatic cancer cells. Besides novel understanding of context-dependent role of Arid1a in pancreatic cancer, this study will also enable development of therapeutic strategies for pancreatic cancers patients with ARID1A mutations, which is currently a critical unmet need in clinic.Genes with deleterious mutations in tumors are widely accepted as tumor suppressors, since, loss of their normal expression often promotes tumor development. However, most tumors develop over a long period, with gradual accumulation of tumor-promoting events. Thus, to comprehend the role of individual genes in this evolving process of tumorigenesis, it is critical to investigate their role in both early precursors and established tumor cells. Despite recurrent mutations in Background & Aims: ARID1A is postulated to be a tumor suppressor gene owing to loss-of-function mutations in human pancreatic ductal adenocarcinomas (PDAC). However, its role in pancreatic pathogenesis is not clear despite recent studies using genetically engineered mouse (GEM) models. We aimed at further understanding of its direct functional role in PDAC, using a combination of GEM model and PDAC cell lines. Methods: Pancreas-specific mutant Arid1a-driven GEM model  was generated by crossing Ptf1a-Cre; G12DKras (“KC”) mice with Arid1af/f mice and characterized histologically with timed necropsies. Arid1a was also deleted using CRISPR-Cas9 system in established human and murine PDAC cell lines to study the immediate effects of Arid1a loss in isogenic models. Cell lines with or without Arid1a expression were developed from respective autochthonous PDAC GEM models, compared functionally using various culture assays, and subjected to RNA-sequencing for comparative gene expression analysis. DNA damage repair was analyzed in cultured cells using immunofluorescence and COMET assay. Results: Retention of Arid1a is critical for early progression of mutant Kras-driven pre-malignant lesions into PDAC, as evident by lower Ki-67 and higher apoptosis staining in “KAC” as compared to “KC” mice. Enforced deletion of Arid1a in established PDAC cell lines caused suppression of cellular growth and migration, accompanied by compromised DNA damage repair. Despite early development of relatively indolent cystic precursor lesions called intraductal papillary mucinous neoplasms (IPMNs), a subset of “KAC” mice developed aggressive PDAC in later ages. PDAC cells obtained from older autochthonous “KAC” mice revealed various compensatory (“escaper”) mechanisms to overcome the growth suppressive effects of Arid1a loss. Conclusions: Arid1a is an essential survival gene whose loss impairs cellular growth, and thus, its expression is critical during early stages of pancreatic tumorigenesis in mouse models. In tumors that arise in the setting of ARID1A loss, a multitude of “escaper” mechanisms drive progression. ARID1A gene), is believed to be involved in transcriptional regulation, DNA replication and DNA damage repair [ARID1A mutations in ~6% of cases [KRAS, TP53, SMAD4 and CDKN2A. These predicted loss-of-function alterations has led to the prevailing assumption that ARID1A behaves as a classic tumor suppressor gene (TSG), likely demonstrating genetic cooperation with mutant KRAS in pancreatic tumorigenesis. Based on this premise, recent genetically engineered mouse (GEM) models have been developed, with pancreas-specific Arid1a loss and mutant Kras expression [bona fide precursor lesion of PDAC, with only one study reporting progression to PDAC on the backdrop of IPMNs in 20% of these mice [ARID1A mutation or loss of expression in human IPMN samples is substantially higher than in human PDAC samples [ARID1A loss in multistep pancreatic carcinogenesis using GEM model and its direct cellular functions in cancer cells. Our functional data establishes that loss of ARID1A within pancreatic precursors restrains progression, unless circumvented by one of several escape mechanisms. Our findings reconcile the observed discrepancy in rates of Arid1a loss between human IPMNs and PDAC, and identify several potential targetable opportunities in tumors with ARID1A mutations.The mammalian SWI/SNF chromatin remodeler subunit, AT-rich interactive domain 1  mice by crossing fl/flArid1a; Ptf1a-Cre (“AC”) mice with G12DLox-stop-lox Kras mice [G12DLSL-Kras; Ptf1a-Cre) were necropsied either at first sign of distress or at periodic age intervals to perform histological assessment of pancreatic pathology. Numerous groups have described the natural history of disease in “KC” mice, which show histological pancreatic lesions, similar to human acinar-to-ductal metaplasia (ADM) and LG-PanINs around 16 weeks of age. These lesions progress to high-grade PanINs (HG-PanINs) with age and infrequently (<10% of cases) to frank PDAC after 1 year. In stark contrast with “KC”, necropsy of “KAC” mice revealed large fluid-filled cysts in “KAC” mice at 8 weeks, which increased in size and distribution with age . This suggested that Arid1a is critical for growth of pancreatic premalignant lesions during early stages of disease development.With progressing age (20–32 weeks), the average area comprising of normal parenchyma gradually decreased in “KAC” pancreas , mostly replaced by LG-IPMNs, LG-PanINs and ADM lesions B. Lack oDespite restrained growth of precursor lesions, we witnessed a sudden shift in mortality of “KAC” mice with subsequent age F. With pDue to dominance of LG-IPMNs of gastric subtype in Arid1a-null “KAC” mice, we assessed for loss of expression of ARID1A by IHC in a collection of 53 human IPMN sections representing various histological subtypes and dysplasia grades. Notably, loss of ARID1A expression was restricted only to low grade IPMNs of gastric subtype  in 10/53G12D/+LSL-Kras; R172H/+LSL-Trp53; Pdx-1-Cre) mice. Genomic PCR sequencing and immunoblot analysis confirmed Arid1a deletion in puromycin-selected clones of CRISPR-ARID1A “KC” and “KPC” cells  and the matched liver metastasis (““KAC”-L”) from a 12-month old “KAC” mouse with invasive cancer. For subsequent experiments, we also used the aforementioned parental “KC” and “KPC” lines as orthogonal controls for “conventional” PDAC. When comparing monolayer growth characteristics, we found “KC” and “KPC” cells grew in clustered colonies with tight cell–cell adhesion, autochthonous “KAC” lines showed elongated, spindle-shaped morphologies, characteristic of mesenchymal cells A. While Similarly, in contrast with isogenic cell lines, there was no difference in growth of the autochthonous “KAC” cells with “KC” or “KPC” cells, in either monolayer or 3D cultures in soft-agar B,C, cellArid1a-null “KAC” cells to circumvent the growth constraining effects of Arid1a loss, and progress to PDAC, we subjected the RNA from “KAC-P” and “KC” cells to global RNA sequencing (RNA-Seq). Among all differentially expressed transcripts , Claudin 18 (Cldn18) was one of the most highly-expressed in “KAC” cells  of differentially expressed transcripts for known tumor-promoting networks that might serve as putative “escaper” mechanism(s) in “KAC-P” cells. GSEA identified enrichment of signatures positively associated with EMT  is a well-known chemotherapeutic agent known to induce DSBs and early activation of ATM leading to pH2AX and p53 activation [TRP53 using isogenic “KC” cells, we did not find this decrease in the levels of either pH2AX or 53BP1 foci upon ARID1A deletion  via ATM/ATR . Surpristivation . Thus, ptivation , along wtivation . When medeletion . For furdeletion C–F. In cdeletion C–F. Thisdeletion , reflectC” lines .Recently, ARID1A was suggested to be important for DNA mismatch repair (MMR) due to its interaction with the MMR protein, MSH2 in ovarian and colon cancer cell lines . Thus, wArid1a mutation was reported as a biomarker for sensitivity of platinum-resistant urothelial carcinoma cells to Panobinostat-mediated HDAC targeting [Arid1a-null PDAC tumors.The concept of synthetic lethality has been widely exploited for cancer therapy since most cancers have loss-of-function mutations that are not readily targetable . ARID1B,argeting . InteresHOMER analysis of our ATAC-Seq data showed enrichment in binding sites for PU.1 transcription factor in open chromatin regions of “KAC” compared to “KC” cells , suggestIn summary, we identified a novel context-dependent role of Arid1a in PDAC where immediate loss of Arid1a function in cells is growth restrictive, at least partially due to impaired DNA repair, but potentially creates opportunities for various compensatory oncogenic mechanisms to drive the disease progression. We also identified therapeutic vulnerabilities of Arid1a-mutant PDAC cells that can be readily tested in clinical studies in imminent future.ARID1A reported across tumor types, led to the prevailing assumption that it behaves as a prototypal tumor suppressor. However, DepMap analysis  of ARID1A using both CRISPR and RNAi screens in various cancer and pancreatic cancer cell lines showed dependency scores (CERES) < 0, which indicates it is an essential gene for survival, comparable to the median of all pan-essential genes. Nonetheless, emerging evidence from both functional and correlative data challenges the role of Arid1a as a relatively straightforward TSG. For example, Zhu and colleagues demonstrated in murine models of hepatocellular carcinomas (HCCs) that sustained Arid1a expression was pro-tumorigenic, while loss of Arid1a was deleterious, during primary tumor formation [min mice significantly inhibited intestinal neoplasia [ARID1A in human colorectal cancer cells with KRAS mutations significantly reduced proliferation, accompanied by attenuation of MEK/ERK dependent transcriptional signaling [ARID1A mutations also correlated with better survival in uterine corpus endometrial carcinoma [ARID1A mutations, all in the low-grade gastric type IPMNs [ARID1A alterations in PDAC reported in TCGA analysis [TRP53 and CDKN2A, which demonstrate a progressive increase in rate of alterations from low-grade to high-grade precursors to invasive adenocarcinoma [ARID1A during multistep neoplastic progression ascribed in recently published GEM models [Deleterious mutations of ormation . In factormation  have shoeoplasia . In addiignaling . ARID1A arcinoma . Similarpe IPMNs , in contanalysis . This suanalysis , carry aarcinoma . These lM models ,5,6.Arid1a loss with co-expression of mutant KrasG12D allele (“KAC”), developed LG-IPMNs and LG-PanINs ubiquitously, with the former resembling gastric type IPMNs in patients, as has been previously reported [Arid1a loss in pancreatic precursor lesions [Arid1a-null cancers [Indeed, our genetically-engineered mice of conditional reported ,6. In co lesions , albeit  lesions . The app cancers . Low ARI cancers . Interes cancers ,41, MYC  cancers ,43.Arid1a deletion-induced growth constraint in vivo, likely under the selection pressure of oncogenic Ras and other secondary events within the pancreatic epithelium. Further, the compendium of tumor-promoting pathways in the autochthonous PDAC models (such as Myc upregulation and perturbation of p53 function) identified by us, and others [Trp53 background . Similarly, our recently published CRISPR-based mouse model of PDAC [Arid1a loss concurrent with oncogenic Kras mutation in adult acinar tissue only caused LG-PanINs, while emergence of well-differentiated PDAC in the same period required deletion of TRP53, irrespective of Arid1a loss. The distinction between the two scenarios—whether Arid1a loss cooperates with oncogenic Ras to induce PDAC formation , or-cancers .Arid1a-deleted precursor lesions to robustly proliferate in vivo? GSEA data on the “KAC” PDAC lines identified DNA repair as one of the highly ranked pathways, which was paradoxical, since numerous prior studies in preclinical models have suggested ARID1A protein to be integral to repair of DNA DSBs [ARID1A mutations showed increased sensitivity to cisplatin, radiation and PARP inhibitors [Arid1a wild type PDAC lines. This led us to postulate that acquisition of DNA repair capacity might be a crucial “escape” mechanism co-opted by “KAC” cells, and vice versa, impaired DNA repair a feature of Arid1a ablated precursors. Indeed, in response to doxorubicin-induced DNA damage, isogenic derivatives of “KC” and “KPC” cells showed compromised DNA repair on the Comet assay, compared to the respective parental controls. Extrapolating from these findings, we suggest that early PDAC precursors (LG-IPMNs and LG-PanINs) with Arid1a loss are vulnerable to genetic stress within the pancreatic epithelium created by mutant Ras generated reactive oxygen species [Arid1a-null precursor lesions that are unable to adapt, either “stall” or undergo apoptosis, while clones that can re-functionalize their repair machinery through secondary adaptations  survive and subsequently progress to PDAC.What mechanism underlies the inability of DNA DSBs ,18,46,47 species ,49. DuriARID1A mutations. In light of our observations, it is imperative that putative targets be distinguished into those that persist in the established PDAC, versus those present in precursor lesions, but circumvented in established PDAC. For example, we posit that “escape” mechanisms are the basis for our observation that synthetic lethal effects described in other ARID1A mutant solid cancer models, such as susceptibility to PARP inhibition and cisplatin [Arid1a mutant PDAC cells is the requirement of sustained ARID1B expression for survival. Increased expression of Arid1b in Arid1a-null cells irrespective of an “escape” setting , points towards a compensatory effect directly related to Arid1a deletion. GeneHancer analysis [Arid1b showed multiple binding sites for transcription factors such as MYC (11 sites), RUNX3 (25 sites), SOX6 (14 sites), FOXA1 (nine sites), and ZNF213 (seven sites). Interestingly, expression of these transcription factors was also upregulated (ARID1B and CLDN18 replete with binding sites for the Pu.1 (SPI1) transcription factor . Pu.1 could be one of the pivotal transcription factors driving the compendium of transcriptional alterations directly related to ARID1A loss in the pancreatic epithelium. Indeed, our proof of concept data with a first-in-class Pu.1 small molecule inhibitor demonstrates robust growth inhibition in “KAC” cells, and pending future validation studies, this might represent a facile pharmacological strategy for targeting ARID1A mutant PDAC. Additionally, Panobinostat has been shown to cause growth arrest and apoptosis in cells from many cancer types including leukemia, by decreasing MYC expression and increasing expression of TRP53, CDKN1A (p21) and DNA repair genes [Finally, an area of considerable translational potential is the opportunity to develop targeted therapies against PDAC harboring isplatin ,46,47, aisplatin  identifianalysis  of promoegulated , RNA-Seqegulated . We alsoir genes . In ovarir genes . Thus, iARID1A loss induces a paradoxical growth constraint within low-grade cystic precursor lesions harboring mutant Ras; a finding we believe underlies the prolonged, indolent natural history of most gastric type human IPMNs. Eventually, through loss of p53, or upregulation of oncogenic networks like Myc and pluripotency factors, a subset of Arid1a-depleted precursor cells progress to frank adenocarcinomas. Our data reassesses the utility of therapeutic vulnerabilities previously described in other ARID1A mutant cancer, in the setting of PDAC [In conclusion, using a repertoire of GEM models, autochthonous and isogenic cell line models, we provide compelling evidence that  of PDAC ,46,47, wAdditional methods are described in the G12D/+LSL-Kras; R172H/+LSL-Trp53; Pdx-1-Cre (“KPC”) mouse; “KC” and “KAC” cell lines were isolated from spontaneous tumors arising in G12D/+LSL-Kras; Pdx-1-Cre and G12D/+LSL-Kras; fl/flARID1a; Ptf1a-Cre mice, respectively and their epithelial origin confirmed by genomic PCR for Cre-mediated Kras recombination [2 incubator and cultured in DMEM  supplemented with 2 mM L-glutamine , 10% FBS , and 100 µg/mL Pen-Strep . All cell lines were tested routinely for mycoplasma contamination.Murine “KPC” cell line was derived from a spontaneous tumor arising in a female bination ,5,6. Pathttp://crispr.mit.edu). The sequence of various sgRNAs were Mouse-Ex.2a sgRNA (GGTCCCTGTTGTTGCGAGTA), Mouse-Ex3a sgRNA (GCCCTGCTGGCCATACGCAC), Human-Ex1a sgRNA (GATCCCCGCTGTCTC GTCCG), Human-Ex1b sgRNA (TTGTTGGGCCCCTCCCGAGG). The sgRNAs were cloned into the pX459 (pSpCas9 (BB)-2A-Puro) plasmid vector . Mouse or human cell lines were transfected with the abovementioned plasmids using Lipofectamine 3000, and positive cells selected in the presence of 1.5 µg/mL puromycin.sgRNA cassette was generated using the CRISPR design tool  and images analysed with the IncuCyte HD software. Proliferation was measured through quantitative kinetic processing metrics derived from time-lapse image acquisition and presented as percentage of culture confluence over time. For experiments where cells underwent change in morphology due to effect of a drug, cells stably expressing the inert RFP in the nuclei  were used to perform quantitative kinetic metrics and evaluate proliferation, expressed as count/well.Anchorage-independent growth assay in soft-agar was performed as described before . BrieflyIn 96-well Image Lock plates  of confluent cell culture, a central scratch-wound per well was made using the 96-pin WoundMaker . Cells were grown for a further 24 h and the recovery of the scratch-wound was analysed by taking images at 1 h intervals with the Incucyte Live-Cell Imaging System (Essence BioScience). The images were analysed with the IncuCyte HD software and the results presented in the form of relative wound densities and standard deviations for each time point. The relative wound density (%) represents the cell density in the wound area expressed relative to that outside the wound area as a function of time.Twenty-four hours after seeding cells on IBIDI µ-Slides Collagen IV coated , they were treated with 0.1 µM of Doxorubicin (Doxo)  for 30 min. After media change, cells were grown for 0, 2, 4, 8 and 24 h and then washed with DPBS  and fixed with 4% formalin  for 10 min at RT. After washes, cells were Permeabilized with DPBS containing 0.5% Triton-X100  for 10 min at RT. Blocking was then performed with DBPS containing 3% BSA  and 1% Chicken serum  for 1 h at RT and P-H2AX (1:800) and 53BP1 (1:1000) primary antibodies were incubated over night at 4C and secondary antibodies for 1 h at room temperature. After DAPI staining, slides were mounted with mounting media  and pictures taken using an Andor Revolution XDi WD Spinning Disk Confocal Microscope  equipped with an iXon Ultra 888 EMCCD Camera. Objective: 40×/1.3 UPlanFl N Oil, WD: 0.20 mm, ∞/0.17/FN26.5, UIS2. Laser lines used: 488 nm (50 mW) diode, 561 nm (50 mW) diode, 405 nm (100 mw) diode. Fluorescent filter cubes (excitation/emission) on a microscope : DAPI (350 nm/460 nm), FITC/GFP (480 nm/535 nm), TRITC/RFP/Cy3 (540 nm/605 nm). Five different fields of pictures were taken for each well with same intensities and laser power for all cell lines. Images were then processed and analysed for quantification of foci/cell with iMaris 9.2 Image Analysis Software.Comet Assay was performed using a CometAssay Kit , according to manufacturer’s instructions. Briefly, cells were seeded into 6-well plates and treated next day with 0.1 µM of doxorubicin for 30 min. After media change, cells were cultured for 2 or 24 h and then combined with molten LMAgarose  at a ratio of 1:10 and immediately spread onto both wells of a CometSlide . Upon lysis with Lysis Solution  and immersion in Alkaline Unwinding Solution , slides were then placed into the electrophoresis slide tray of the CometAssay ES Unit  covered with Alkaline Electrophoresis Solution . After electrophoresis, slides were washed, dried, stained with SYBR Gold  and scanned using 10× objective with the Cytation 3 Cell Imaging Multi-Mode Reader . Each well was scanned using a 10 × 10 grid , images processed and analysed using CometScore 2.0 to calculate % of DNA in tail and Tail length (µm).t test with Welch’s correction and two-way ANOVA with Sidak’s post hoc test, as appropriate. For all experiments with error bars, S.D. was calculated to indicate the variation within each experiment and data, and values represent mean ± S.D.Statistical analyses were performed  using the unpaired Student’s Arid1a is an essential survival gene whose loss impairs cellular growth, and can induce cell death. Thus, when lost during early stages of pancreatic tumorigenesis in mutant Ras-driven mouse models, it leads to cellular growth constraint, resulting in indolent low-grade cystic precursor lesions, such as IPMNs. However, with occurrence of an ‘escaper’ event(s), such as loss of p53, or upregulation of oncogenic networks like Myc and pluripotency factors, a subset of Arid1a-depleted precursor cells progress to adenocarcinomas. This provides novel opportunities to target such tumor cells in the clinic.In present study, we show that


Depression is one of the most common disorders in psychiatric and primary care settings, and is associated with disability, loss in quality of life, and economic costs. Internet-based psychological interventions have been shown to be effective in depression treatment but present problems with a low degree of adherence. The main aim of this study is to analyze the adherence predictors in three low-intensity interventions programs applied by Information and Communication Technologies (ICTs) for depression. A multi-center, randomized, controlled clinical trial was conducted with 164 participants with depression, who were allocated to: Healthy Lifestyle Program, Positive Affect Promotion Program or Mindfulness Program. Sociodemographic characteristics, Patient Health Questionnaire-9, Visual Analog Scale, Short Form Health Survey, Positive and Negative Affect Schedule, Five Facets Mindfulness Questionnaire, Pemberton Happiness Index and Treatment Expectancy Questionnaire were used to study adherence. Results showed that positive affect resulted in a predictor variable for Healthy Lifestyle Program and Positive Affect Promotion Program. Perceived health was also a negative adherence predictor for the Positive Affect Promotion Program. Our findings demonstrate that there are differences in clinical variables between treatment completers and non-completers and we provide adherence predictors in two intervention groups. Although new additional predictors have been examined, further research is essential in order to improve tailored interventions and increase adherence treatment. About 30 million Europeans are estimated to suffer from depression . In SpaiA large body of research has reported that Internet-based intervention programs have been shown as an efficacious therapeutic option for the treatment of many mental health problems including depression ,17,18,19A large body of research has focused on the study of adherence predictors in the past years ,29,30,31In reference to clinical predictors, baseline depression severity is one of the most commonly explored characteristics. Many studies have reported that lower levels of baseline depression predicted adherence ,25,28 whOther psychological characteristics were also studied, such as pre-treatment expectations, perceived credibility of the treatment, and/or attitudes toward Internet-interventions. Nevertheless, results showed that these variables were not related with treatment completion ,34. It iFor all these reasons, it is crucial to examine new additional characteristics such as factors of mindfulness, positive and negative affect, and well-being, in order to have new knowledge of which variables are associated and predict treatment adherence.The aim of the present study is to examine the differences in sociodemographic and clinical characteristics between treatment completers and non-completers and to analyze the adherence predictors in three low-intensity intervention programs applied by ICTs: Healthy Lifestyle Program; Positive Affect Promotion Program and Mindfulness Program, for depression treatment in Spanish Primary Care.The current study is a secondary analysis of a multi-center, controlled, randomized clinical trial conducted with patients with depression recruited in the primary care. They were randomized to receive one of four intervention groups: (a) improved primary care usual treatment (iTAU), (b) Healthy Lifestyle Program + iTAU, (c) Positive Affect Promotion Program + iTAU or (d) Mindfulness Program + iTAU.Trial Number Registration from the original study is ISRCTN82388279. The aim of the original study was to assess the effectiveness of three low-intensity intervention programs applied by ICTs  compared with a control condition. The research protocol and main results have been reported elsewhere ,36.In the original study, a total of 221 patients with depression were recruited in primary care settings, between March 2015 and March 2016 in the Spanish regions of Aragon, Andalucía and Baleares. Inclusion criteria were: older than 18 years old; DSM-5 diagnose of Major Depression or Dysthymia, with mild or moderate severity depression assessed as score lower than 14 according to the Patient Health Questionnaire (PHQ-9) , with syn = 164) led to a lack of statistical power, resulting in our major limitation.For the present study, a total of 164 participants were selected and included, those who were allocated to one of the intervention groups . Those allocated to iTAU were excluded from the analysis because they were control group, with no access to online treatment. Our small sample size .The Healthy Lifestyle Program provides information to understand the relationship between physical and mental health and physical activity, diet and sleep control. Modules are: (1) Beginning of a lifestyle change, focused on the importance of healthy lifestyle to improve emotional health and general well-being; (2) physical activity—learning to move, to give information about exercises to improve mood, to increase motivation, to start being more active, and to maintain this physical activity; (3) diet—learning to eat, focused on the importance of diet to achieve a good physical and mental health, and the role of the Mediterranean diet in the prevention and treatment of depression; and (4) sleep—the importance of good sleep, to understand the relationship between sleep, and general health.The Positive Affect Promotion Program aims to decrease depressive symptomatology and to prevent relapses using the promotion of well-being and positive affect. The modules are: (1) Learning to live, focused on the importance of establishing and maintaining an adequate activity level and the relevance of choosing activities that are significant for the individual; (2) learning to enjoy, to give education about the effect of positive emotions and to train the patient in learning procedures to increase the likelihood of experiencing positive emotions; (3) accepting to life, focused on the training to the patient in concentrating on positive emotions related with the past or the future; and (4) living and learning, to train the patient in understanding life as a continuous process of learning and personal growth, emphasizing the training in strategies to promote psychological strengths, resilience, and meaningful goals linked to important values.The Mindfulness Program has the objective to decrease depressive symptomatology using mindfulness, emphasizing the benefits of its therapy. The modules are: (1) Getting to know mindfulness, to explain what mindfulness is, prejudices about it, the inattention problem, and some of its main benefits and recommendations to practice it; (2) establishing formal and informal practices, focused on the importance of the establishment of formal and informal practice; (3) through management, body scan practice and values, to help people to see the importance of values to keep a regular mindfulness practice; and (4) Self-compassion. Integrating mindfulness in everyday life, to establish a regular practice of mindfulness to be indefinitely kept.Full details of the interventions are described in Castro et al.  and GiliIn the context of this analysis, adherence refers to the extent to which individuals complete the whole intervention in the post-test evaluation. Therefore, a participant was considered to be part of the adherence group (completer participant) if they completed the whole intervention (1 face-to-face session plus 4 self-guided online therapeutic modules) at the post-test assessment. A participant who did not complete the whole intervention at the post-test was considered non-completer participant.Case report form (CRF). The patient’s sociodemographic and clinical characteristics were gathered using a CRF: gender, date of birth and age, place of residence, family status, if they live alone or accompanied, level of education, work status and income level. Psychopharmacologic medication (yes vs. no) and the number of physician visits in the last 12 months were also collected.The Mini International Neuropsychiatric Interview 5.0 (M.I.N.I. 5.0) . This diPatient Health Questionnaire-9 (PHQ-9) . This inThe Visual Analog Scale of the EuroQol (VAS); . This scThe Short Form Health survey (SF-12v1) . This scPositive and Negative Affect Schedule (PANAS) . This scFive Facets Mindfulness Questionnaire (FFMQ) . This quThe Pemberton Happiness Index (PHI) . This inTreatment Expectancy Questionnaire . This quhttps://psicologiaytecnologia.labpsitec.es/). Included participants were randomized to 1 of the 4 groups by an independent researcher using a computer-generated random number. The Ethical Review Board of the regional health authority approved the study (Ref: IB 2144/13 PI). More details about the study design, recruitment, randomization and data collection procedure are described elsewhere [Patients were recruited in Spanish Primary Care settings. When the general practitioner (GP) identified a potential participant during a visit, he or she explained to the participant the characteristics of the study. If the participant was interested on it, he or she signed an informed consent form and the GP filled a referral form describing the sociodemographic characteristics of the patient and a checklist for inclusion and exclusion criteria. GP also gave him or her the patient’s information sheet and a handout describing the study. Then, the GP sent these documents to the local researcher. Participants were interviewed after a few days by the researcher, which administered psychological assessment instruments related with inclusion and exclusion criteria by phone. All participants fulfilled their assessments through a web . Descriptive analysis examined the differences between groups of adherence (treatment completer vs. non-completer) for each intervention group and was computed in terms of mean and standard deviation for continuous variables, and frequency with percentage for ordinal and nominal variables. Discrete variables were compared using the chi-square test and Student t tests were used for continuous variables comparisons. A post-hoc analysis was conducted in order to explore the intervention group differences regarding adherence considering adherence as a dichotomous variable (completers vs. non-completers) through chi-square homogeneity test, and as a continuous variable (number of modules completed) by ANOVA test. Logistic regression models using adherence as a dependent variable were constructed using independent predictor variables. Subsequent binary logistic regression analyses for each intervention group were conducted to build parsimonious models. Significance associated probability for analyzed contrasts were fit to 0.05, while significance analyses for b coefficients in logistic regressions and for Odd Ratios were calculated based on 95% CI. The effects of b coefficients of final logistic regressions were bootstrapped with 1000 replications. The analyses were performed using IBM SPSS v22 .Final analyses were undertaken on 164 subjects, those who were allocated in one of the three intervention groups, with 32.9% receiving Healthy Lifestyle Program, 32.9% receiving Mindfulness Program, and 34.1% receiving Positive Affect Promotion Program. The sample was predominantly female (79.9%) and the mean age was 45.03 (SD = 11.16) years. Most were married (58%), lived accompanied (83.4%), had primary/secondary educational level (68%) and had no paid employment (51.6%), and had an income level predominantly more than 2 NMW (35.6%). With respect to clinical variables, the PHQ-9 mean of the total sample was 12.62 (SD = 2.34) and 70.9% used psychopharmacologic treatment.p = 0.000), baseline scores from “Describing” FFMQ Subscale  and baseline global average PHI . In the Positive Affect Promotion Program, statistically significant differences between treatment completers and non-completers were found in baseline perceived health, self-measured by the VAS  and baseline scores from “Not reacting to inner experience” FFMQ Subscale . In the Mindfulness Program, statistically significant differences between treatment completers and non-completers were not found in sociodemographic and clinical variables.Regarding differences in sociodemographic and clinical characteristics between treatment completers and non-completers in each intervention groups, analysis found that the Healthy Lifestyle Program group had statistically significant differences in Positive Affect baseline scores, self-measured by the Positive Affect dimension from PANAS Schedule (PA-PANAS)  = 4.417; p = 0.110), nor in terms of modules completed .Results of the post-hoc analysis found neither statistically significant differences in the proportions of completers and non-completers between intervention groups (χp < 0.10). After a literature review, models were also adjusted by the following variables: age, sex, educational level, depression symptomatology (PHQ-9), perceived health (VAS), and treatment expectations.A logistic regression was carried out to test if there were interactions between the predictors variables. Because of an effect of interaction between some predictor variables and intervention variable, models were analyzed separately. After that, a bivariate analysis was performed between independent baseline demographic and clinical variables and adherence (completers vs. non-completers) as a dependent variable in order to identify the potential predictors. No reactivity to inner experience FFMQ subscale and positive affect (PA-PANAS) variables were significantly associated (p = 0.005) for Healthy Lifestyle Program and perceived health (self-measured by the VAS) for Positive Affect Promotion Program (p = 0.012). Models were significant fit of data for Healthy Lifestyle Program (X2(8) = 23, p = 0.003) and for Positive Affect Promotion Program (X2(8) = 21.628, p = 0.006) but not for Mindfulness Program (X2(8) = 2.479, p = 0.963).Odds ratio (OR) and 95% confidence intervals for each adherence predictor in each intervention group are shown in 2(1) = 16.11, p < 0.001, for Healthy Lifestyle Program; χ2(2) = 16.358, p < 0.001 for the Positive Affect Promotion Program  = 3.422, p = 0.181).For Mindfulness Program, the most parsimonious model was found, although it was not significant fit of data  for depression in primary care.Our completion treatment rates were relatively low in the whole sample (41.5%) and in each intervention groups with no differences between them . Our results were comparable to previous research that showed that only about half of the participants of unguided interventions complete all modules . HoweverContrary to prior findings, sociodemographic characteristics were not associated to adherence condition in our sample. This is inconsistent with the findings of earlier researches on this subject which found that participant’s characteristics, such as age, gender, or educational level are associated with adherence ,29. In tWhen logistic regression analyses were performed, some of our findings were attenuated. According to adherence predictors, a consistent finding was found: for patients in Healthy Lifestyle Program and Positive Affect Promotion Program, positive affect, self-measured by the PA-PANAS, predicted adherence. Hence, those participants that presented high positive affect scores at baseline tend to adhere more than those with low positive affect levels. A possible explanation of this finding could be that positive affect assesses personal traits such as interest, excitement, enthusiasm, among others. These traits could be related to the motivation to start and use a non-conventional psychotherapy such as an intervention program applied by ICTs, as the Healthy Lifestyle Program or the Positive Affect Promotion Program are. Also, it is important to note that Positive Affect Promotion Program is mainly designed to decrease depressive symptomatology through the promotion of positive affect and subjective-well-being, and this could maybe explain why people with higher basal levels of positive affect persist in this program. Nevertheless, our finding cannot be compared with the previous literature. To the best of our knowledge, this predictor has not been explored before. Therefore, more research is required to determine the impact of this predictor on adherence in other intervention programs applied by ICTs for depression.Perceived health, self-measured with the EuroQoL VAS, also predicted adherence but just in Positive Affect Promotion Program. Therefore, those participants that perceived their health to be worse at baseline assessment are more likely to adhere to the treatment. As we reported before, Positive Affect Promotion Program is also designed to promote well-being, and well-being could be related with perceived health. Participants with worse perceived health could feel the treatment useful for their health and maybe they are more like to keep on this program.The result that perceived health is related to adherence is partially in line with the findings of an earlier study on this subject, where Castro et al.  found thIn fact, a growing body of research found that low depression severity at baseline predicted higher adherence ,25,26,28No adherence predictors were found for Mindfulness program. Possible explanations of this fact could be that the percentage of treatment completers and non-completers are almost equal. Another potential explanation could be that this study examined a specific number of predictors of adherence, and perhaps other possible variables that could predict adherence treatment have not been included in this study.There are several limitations associated with this research. First, our sample size is smaller than the previous studies ,27 and cAlthough the adherence rates found in this research are low in the three intervention groups, it is surprising that only about 30% of the participants completed the Positive Affect Promotion Program. More specific research is needed to understand and improve the adherence in this type of intervention in particular, and Internet interventions in general. It is well-known that adherence is an important measure of acceptability, appropriateness, and effect of psychological treatment . The ideOur research found that there are some clinical variables associated with adherence in two low-intensity intervention programs applied by ICTs. In particular, treatment completers present higher basal levels of positive affect, higher basal scores in the FFMQ Subscale Describing and higher basal levels of well-being compared to treatment non-completers in Healthy Lifestyle Program. In Positive Affect Promotion Program, treatment completers present lower basal levels of perceived health and higher basal scores in the FFMQ Subscale Not reacting to inner experience. With regard to adherence predictors, for patients in Healthy Lifestyle Program and Positive Affect Promotion Program, positive affect predicts adherence. That is, those participants that present high positive affect scores at baseline tend to adhere more than those with low positive affect level. Finally, perceived health, is a negative predictor of adherence but just in Positive Affect Promotion Program; those participants that perceived their health to be worse at baseline assessment are more likely to adhere to the treatment. Significant differences in sociodemographic and clinical characteristics between treatment completers and non-completers were not found nor adherence predictors in Mindfulness Program.


N. Instead of inducting over individual loops, our technique inducts over the entire program (possibly containing multiple loops) directly via the program parameter N. Significantly, this does not require generation or use of loop-specific invariants. We have developed a prototype tool Vajra to assess the efficacy of our technique. We demonstrate the performance of Vajra vis-a-vis several state-of-the-art tools on a set of array manipulating benchmarks.We present a full-program induction technique for proving (a sub-class of) quantified as well as quantifier-free properties of programs manipulating arrays of parametric size


ARID1A has been described as a tumor suppressor gene, participating in chromatin re-modeling, epithelial-mesenchymal-transition and many other cellular and molecular processes. It has been cited as a contribute in tumorigenesis. The role of ARID1A in CRC is not yet defined.ARID1A methylation and CNV in its expression in CRC cell lines and to examine the relationship between ARID1A status with survival and clinicopathologic characteristics in patients with CRC.To investigate the role of ARID1A. IHC was used to assess ARID1A protein expression. We also evaluated MSI and EMAST status in 18 paired CRC and adjacent normal tissues. 5AzadC was used to assess effect of DNA demethylation on ARID1A expression. Statistical analysis was performed to establish correlations between ARID1A expression and other parameters.We used RT-PCR to determine both CNV and expression of ARID1A from six CRC cell lines. We used MSP to evaluate methylation of ARID1A promoter methylation was observed in 4/6 (66%) cell lines and correlated with ARID1A mRNA expression level ranging from very low in SW48, to more pronounced in HCT116 and HT-29/219. Treatment with the methyltransferase inhibitor 5-Azacytidine (5-aza) resulted in a 25.4-fold and 6.1-fold increase in ARID1A mRNA expression in SW48 and SW742 cells, respectively, while there was no change in SW480 and LS180 cells. No ARID1A CNV was observed in the CRC cell lines.Among the 18 CRC tumors studied, 7 (38.8%) and 5 tumors (27.7%) showed no or low ARID1A expression, respectively. We observed no significant difference in ARID1A expression for overall patient survival, and no difference between clinicopathological parameters including MSI and EMAST. However, lymphatic invasion was more pronounced in the low/no ARID1A expression group when compared to moderate and high expression group (33% VS. 16.6% respectively. ARID1A expression is downregulated in CRC tissues which correlates with it being a tumor suppressor protein. This finding confirms ARID1A loss of expression in CRC development. Our in-vitro results suggest high methylation status associates with reduced ARID1A expression and contributes to CRC tumorigenesis. However, there was no significant association between ARID1A loss of expression and clinicopathological characteristics. Future in-vivo analysis is warranted to further establish ARID1A role in colorectal neoplastic transformation. Colorectal cancer (CRC) is rapidly increasing in prevalence among several regions of the world, such as Asia , 2. CRC ARID1A encodes the AT-rich interactive domain-containing protein 1A, a representative of the DNA-binding protein family and principal subunit of the SWI–SNF complex (switch/sucrose non-fermentable). ARID1A is frequently deleted in multiple human tumors. It is located on chromosome 1p36.11, a region that is commonly deleted in various cancer types and suspected to contain tumor suppressor genes [ARID1A, was observed in more than half pancreatic carcinomas [ARID1A knock-out cells do not enter cell cycle arrest [ARID1A is detected repeatedly and frequently in various cancer types [ARID1A knockdown in renal cells led to epithelial-mesenchymal-transition, highlighting its role in cell differentiation and tissue homeostasis [or genes . For exarcinomas . SWI–SNFrcinomas , 14. Thercinomas . ARID1A rcinomas , 17. Alsrcinomas . The intrcinomas . ARID1A e arrest . The ARIer types , 21. A reostasis .ARID1A mutation or loss of ARID1A protein expression strongly correlates with microsatellite instability, and is inversely correlated with alterations in TP53 [Although ARID1A expression loss has been described chiefly in gynecological cancers, it is reported among other tumor types, such as from gastrointestinal tract tumors –25. In g in TP53 , 26. Rec in TP53 .ARID1A copy number loss is the major cause of low ARID1A expression in pancreatic cancer (47%) [ARID1A mutation (with 50% mutation rate) as the major cause of loss of expression. Moreover, among breast cancers, promoter hypermethylation and histone modification are the main reasons for loss of ARID1A expression [Molecular mechanisms related to low ARID1A expression seem to be distinct amongst different cancerous tumors. For instance, er (47%) . Prior ser (47%) . Mutatiopression .ARID1A was reported in the colorectal cancer (10–40%) [ARID1A methylation, expression and CNV in clinical samples and CRC cell lines. We also determine if treatment of these cell lines with 5-aza affect the expression of ARID1A. In addition, we examined possible correlations between ARID1A expression loss and various clinicopathological parameters in CRC tissues.Studies on ARID1A expression in CRC is limited. A relatively high mutation rate of (10–40%) , 29–31, Eighteen paraffin-embedded patient-derived paired CRC and adjacent nontumorous tissue samples were collected from the archives of the department of pathology of Faghihi Hospital of Shiraz University of Medical Sciences. All patients underwent primary tumors resection between 2016 and 2017. None of the patients had preoperative radiotherapy or preoperative chemotherapy. Tumor staging was determined according to AJCC TNM system. All tumors were histologically classified based on World Health Organization criteria. Clinical, pathologic and follow-up information of patients were obtained from hospital medical records. Overall survival (OS) was defined as the time interval (in months) from surgery to the time of death from any cause or to end of follow-up if the patient was alive (censored). Twelve separate cancer-matched normal pairs were from Howard University Hospital and used for exome sequencing . The IRBImmunohistochemistry was performed on 4-μm thick paraffin-embedded tissue sections from patients with colorectal cancer using a rabbit anti-human ARID1A antibody  at a dilution of 1:200. Briefly, sections were deparaffinized using xylene and rehydrated in a descending series of alcohol dilutions. Activity of endogenous peroxidase was inhibited with 3% hydrogen peroxide in methanol for 5 min. After, the sections were heated for 15 min at 120 °C in 10 mM citrate buffer for antigen retrieval. Sections were then blocked with goat serum 1:100 in PBS for 20 min and subsequently incubated with primary antibodies for 30 min at room temperature. After washing, immunohistochemical staining was performed using Master Polymer Plus Detection System kit (Incl. DAB Chromogen) according to the manufacturer’s instructions. Sections were then counterstained with hematoxylin, dehydrated by ethanol and mounted.Immunostained sections were reviewed and scored by an expert pathologist who was blinded to patient’s clinicopathological and molecular information, according to the percentage of the stained cells and the intensity of staining. The percentage of positively stained cells was scored as: ≤ 10% = 0, 11–25% = 1, 26–50% = 2, 51–75% = 3, and > 75% = 4. Staining results were considered positive for tumor tissues with nuclear staining. Staining intensity was scored as negative = 0, weak = 1, moderate = 2, and strong = 3. The final score of each section equals the percentage score × intensity score. Based on the overall score, the immunostained sections were further divided into two groups: The group of ARID1A-negative  and the group of ARID1A-positive . The group of ARID1A-positive was further divided into three subgroups: low ARID1A expression group , moderate ARID1A expression group  and high ARID1A expression group .MSI and EMAST analysis using DNA extracted from 18 paraffin-embedded patient-derived paired CRC and adjacent nontumorous tissue samples were performed as described previously , 34. BriIn this study, six human CRC cell lines  were purchased from the National Cell Bank of Iran . cells were cultured in RPMI 1640  or DMEM (LS180), containing 10% fetal bovine serum, 1% penicillin, 2 mM glutamine, and 1% streptomycin, in a humidified CO2 (5%) incubator at 37 °C.Cells were cultured in T-25 flasks, after 24 h, cells were covered for 72 h with 2.5 μM 5-Azacytidine (5-aza) (Sigma), a methyltransferase inhibitor. The culture media were replaced every 24 h with fresh media, containing 5-aza. Stock solutions of 5-aza were prepared fresh every day, sterilized by filtration, and kept at 0 °C, until further use. For drug treatment, 5-aza was dissolved in acetic acid: water (1:1 v/v). Then, the stock solution (100 mM) was diluted, up to a final concentration of 3 μM in PBS and the cells treated with 5-aza for 3 day.ARID1A promoter region was analyzed, using MS-PCR as previously described [Genomic DNA was extracted from cells as follows: Cells were collected and initially lysed in 1.0 ml DNA lysis buffer , supplemented with 100 μl 1% SDS and 200 μg/mL proteinase K (Sigma-Aldrich). Following the addition of RNAse A (100 μg/mL), samples were incubated at 65 °C for 1 h. Subsequently, an equal volume of phenol:chloroform: isoamyl alcohol (25:24:1 v/v), was added to the cell lysate, shaken vigorously, and then spun at 12000 rpm for 10 min. Afterward, the supernatant was collected, and the isolated DNA was precipitated by adding 2 volumes of 100% ethanol and sodium acetate, at a concentration of 300 μM, and kept at − 20 °C for 24 h. The DNA was next dissolved in 50 μl of DNAse-free water and quantified with a NanoDrop ND-1000 spectrophotometer . The methylation status of CpG islands in the escribed . BrieflyARID1A promoter region included: methylated, forward: 5′-GGCGTAGGTTTTAGAGATGC-3′, and reverse: 5′- AAACGAACTCGCTCCCTT-3′; unmethylated, forward: 5′-GGTGTAGGTTTTAGAGATGT-3′; and reverse: 5′ - AAACAAACTCACTCCCTT- 3′. The MS-PCR primers were designed using a methylation specific software (www.mspprimers.org). PCR reactions were performed in triplicates, using the following conditions: 95 °C for 10 min, and 35 cycles of 95 °C for 40 s, 59 °C (unmethylated DNA) or 53 °C (methylated DNA) for 40 s, and 72 °C for 30 s, followed by an extension at 72 °C for 10 min. A band size of 163 bp was observed in the ARID1A methylation set  and visualized, using the UV illumination system. Genomic DNA extracted from peripheral blood leukocytes, served as an unmethylated control sample. Human methylated DNA from Zymo Research , was used as methylated positive control. Distilled water was used as a blank control for the PCR reaction.The primer sequences used for the detection of Total RNA was extracted from sub-confluent cell cultures, using the Tripure RNA isolation kit , based on the manufacturer’s guidelines. The isolated RNA was quantified by a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies). Furthermore, RNA integrity was examined by the presence of the 28S, 18S rRNA bands on 1.5% agarose gel. The cDNA was synthesized, with DNase-treated RNA, 2 μg of RNase-free, random primers or random hexamers, using the RevertAid First Strand cDNA Synthesis Kit (Fermentas), in 20 μl volumes reaction, based on the manufacturer’s instructions.ARID1A mRNA analysis: forward, 5′-CAGTACCTGCCTCGCACATA-3′; reverse, 5′ GCCAGGAGACCAGACTTGAG- 3′. Additionally, GAPDH was used as the internal housekeeping gene with the following primers: forward, 5′- CGACCACTTTGTCAAGCTCA- 3′, reverse, 5′- AGGGGTCTACATGGCAACTG-3′. The PCR reaction mixture contained 1 μl cDNA of each sample, 1 μl of forward and reverse primers  and 12.5 μl SYBR Green master mix  in a total final volume of 25 μl. PCR was carried out using the following conditions: a pre-cycling thermal activation at 95 °C for 15 min, and 40 cycles of denaturation at 95 °C for 15 s, annealing at 60 °C for 30 s, extension at 72 °C for 30 s, and a final extension of 72 °C for 10 min, followed by a melt curve (58–95 °C) analysis. Experiments were performed in duplicate. Furthermore, products specificity was confirmed by electrophoresis on 2% agarose gel. The relative expression was calculated, using the 2-ΔΔCT method and normalized to the GAPDH expression.Real-time quantitative PCR (qPCR) was carried out, using ABI 7500 Sequence Detection System  and the following primers for the ARID1A copy numbers among six CRC cell lines and a normal colon tissue sample. Ten nanograms of genomic DNA from each cell line and normal colon tissue was used as template to carry out the real time PCR reaction, using specific primer for ARID1A, and RNase P (two copies in a diploid genome) as a reference gene. Primers used for the RNase P are as follows: Forward 5′-AGATTTGGACCTGCGAGCG-3′ and reverse 5′- GAGCGGCTGTCTCCACAAGT-3′, giving an amplicon size of 65 bp. Primers used for ARID1A are forward, 5′- GGATGGCACTTTGAGAAC − 3′ and reverse 5′- GAAAGATGAACAGGAGGA − 3′, giving a fragment length of 166 bp. Amplification of the product was carried out with the following conditions: a pre-cycling thermal activation at 95 °C for 15 min, accompanied by 40 cycles of 95 °C for 15 s, 60 °C for 30 s, 72 °C for 30 s, and a final extension of 72 °C for 10 min. Experiments were performed in triplicates.Real time quantitative PCR (qPCR) was carried out to reveal the relative changes in -ΔΔCT method, which were normalized to a calibrator sample  to have normal diploid genomes) and a reference gene (RNase P). In comparison to the normal sample, a two-fold decrease or increase in the copy number of ARID1A in the CRC cell lines was referred to as a deletion or amplification, respectively.For all experiments, cycle threshold (Ct) values are extracted, with 7500 software (Applied Biosystems). Relative CNVs were computed, using the 2P value ≤0.05 were statistically significant.Data analysis was performed, using SPSS software (Version 23). Data are presented as mean ± SD. The association between ARID1A expression and the clinicopathological characteristics were evaluated by Pearson χ2 test and Fisher’s exact test based on the type of data. The Kaplan-Meier method was used for survival rates estimation. Other experiments were analyzed, using the one-way ANOVA, accompanied by Tukey’s multiple comparison tests. Differences with a ARID1A mRNA expression was examined in six colorectal cancer cell lines, SW48, SW742, HT29/219, HCT116, LS180, and SW480 , showed that SW48 cells expressed at the lowest levels. As shown in Figs. ARID1A mRNA expression was not observed in SW48 cells and therefore were used as baseline/reference for ARID1A expression levels (set at 1.0). The average expression level of the ARID1A mRNA in HCT116 cells was significantly higher  in comparison with the other cell lines. Quantitation of the ARID1A mRNA revealed that HT29/219, LS180, SW480 and SW742 cells, expressed approximately, 136.8, 24.3, 15.5 and 8.6- fold more than the SW48 cells, respectively. We observed a spectrum of high-level expression (in HCT116) to virtually no expression (in SW48) for ARID1A mRNA . MSP showed that SW48 cells were fully methylated  after 5-aza treatment  tumor tissues when compared with adjacent non-malignant counterparts. Five (27.7%) tumors had low expression of ARID1A, 4 (22.2%) tumors had moderate expression of ARID1A, and 2 (11.1%) tumors had high expression of ARID1A. Thus, a total of 12 of 18 (66.6%) CRCs demonstrated negative or low ARID1A expression when compared with normal tissues. Collectively, these results demonstrate that ARID1A is frequently down regulated in CRC tumors. Typical immunostaining of high, moderate, low and negative expression of ARID1A are shown in Fig. ARID1A expression and clinicopathological features was analyzed in patients with colorectal cancer. Table p = 0.457). These trends failed to reach statistical significance. Overall, there was no significant association between the loss of ARID1A expression and any clinicopathological parameters examined.Relationships between In addition, we further evaluated the relationship between ARID1A expression and overall survival in colorectal cancer patients. The mean duration of follow up was 29.18 months, ranging 12–44 months, during which 2 patients died of the disease. Kaplan-Meier survival analysis showed that overall survival was worse for patients with positive ARID1A expression than the ones with negative ARID1A expression, although it was not statistically significant Fig. . The KapARID1A. The patient was KRAS wild type and displayed mutations in MSH6 and PKHD1 genes  CRC cell lines. This study showed that the SW48 cell line, displaying the ARID1A methylated allele only, did not express detectable ARID1A. In contrast, HCT116 and HT-29/219 displayed an unmethylated allele and a methylated allele, which was not detectable. We have also shown that treatment with the 5-aza dramatically restored ARIA1A expression in low ARID1A expressing cell lines, SW48 and SW742.In order to characterize molecular mechanisms affecting ARID1A expression, we evaluated the possible role of promoter methylation in the downregulation of the ARID1A expression in various types of colorectal cell lines. A study showed that t cancer . HoweverARID1A silencing or downregulation in the CRC cell lines. However, other processes such as histone modification cannot be excluded. Indeed, ARID1A expression was not restored after 5-aza treatment in SW480 and LS180 cell lines. Zhang et al. carried out chromatin immunoprecipitation assays to evaluate ARID1A promoter histone modification levels in breast cancer samples and reported methylation of histone H3 at lysine 27 was linked to ARID1A silencing [To sum up, the present study identified that promoter DNA hypermethylation strongly contributes to ilencing . These fARID1A promoter could be considered as an inactivating mechanism of ARID1A expression, and the co-occurrence of loss of ARID1A expression and MLH1 promoter hypermethylation might be the consequently a reflection of global genomic hypermethylation [ARID1A gene in the CRC cell lines. On a different note, lymphatic penetration was more pronounced in no/low ARID1A expression cases when compared to moderate/high expressing cases (33% vs. 16.66%). This finding suggests that lack of ARID1A expression renders the tumors more aggressive and invasive to neighboring tissues. Indeed, Kishida et al. have reported that negative ARID1A expression was correlated with early onset, lymphatic invasion, and lymph nodes metastasis and was also associated with specific mutational profile in PKHD1, RNF213, and MSH6 genes whereas KRAS mutations were more common in ARID1A-positive tumors [As previously mentioned, a significant association between loss of ARID1A expression and MSI because of hypermethylation of the MLH1 gene promoter was reported in various cancers, including CRC , 40, 43.hylation , 43. Thie tumors .ARID1A was the major mechanism for loss of expression in pancreatic cancer [ARID1A copy number in the CRC cell lines and normal sample revealed that CRC cell lines had no significant difference in ARID1A copy number and values were similar to the control sample (Fig. Previous studies showed that copy number loss in c cancer . In addic cancer . These lple Fig. . These dARID1A promoter hypermethylation in CRC requires further elucidation including complete CpG island promoter analysis that will be our goal for future studies using previous protocols [This study has several limitations. The possible significance of rotocols . In addiIn the case of our finding that loss of ARID1A expression was not correlated to survival and clinicopathological parameters, the limited number of patients might have limited our analysis. Further investigations with a larger number of patients are warranted to establish clinical and pathological impact of ARID1A expression loss in CRC.ARID1A gene as an important regulator of ARID1A expression in CRC cell lines and clinical specimens. The clinical significance of loss of ARID1A in CRC remains a goal for future studies.We found a high incidence of ARID1A expression loss in CRC that suggests ARID1A as a tumor suppressor. There was no significant association between the loss of ARID1A expression and any of the clinicopathological parameters examined. Here we identified aberrant methylation of Additional file 1.


Symbiotic  8 for Test-Comp  2021 brings radical changes in the test generation for coverage-branches property. Similarly as in Symbiotic  7, we generate tests by running our fork of symbolic executor Klee on the analyzed program. Symbiotic  8, however, runs several instances of Klee in parallel. We run one instance of Klee on the original program and, simultaneously, we create one  program slice for every program-terminating instruction in the program and run Klee on these slices. Apart from this principal change, we also improved other components of the tool, mainly the program slicer. Further, our fork of Klee now supports symbolic pointer arithmetics and comparison of symbolic addresses.The setup of


Recombinant production of IgM antibodies poses a special challenge due to the complex structure of the proteins and their not yet fully elucidated interactions with the immune effector proteins, especially the complement system. In this study, we present transient expression of IgM antibodies  in HEK cells and compared it to the well-established stable expression system in CHO cells. The presented workflow investigates quality attributes including productivity, polymer distribution, glycosylation, antibody structure and activation of the classical complement pathway. The HEK293E transient expression system is able to generate comparable amounts and polymer distribution as IgM stably produced in CHO. Although the glycan profile generated by HEK293E cells contained a lower degree of sialylation and a higher portion of oligomannose structures, the potency to activate the complement cascade was maintained. Electron microscopy also confirmed the structural integrity of IgM pentamers produced in HEK293E cells, since the conventional star-shaped structure is observed. From our studies, we conclude that the transient expression system provides an attractive alternative for rapid, efficient and high-throughput production of complex IgM antibodies with slightly altered post-translational modifications, but comparable structure and function. Immunoglobulins of subclass M (IgM) are considered as the main actors in the protection against humoral microbial infection and in the mediation of cell debris clearance by activating and controlling the complement classical pathway and inflammation. This crucial role theoretically makes them relevant for therapeutic applications. Although clinical trials of metastatic melanoma patients with a human anti-GD2 IgM (MORAb-028) were already started, the study was terminated due to a lack of product availability . Production of IgMs is a cost-intensive and tedious process no matter if isolated from serum or recombinantly expressed in stable cell lines . AnotherIn the herein presented study, we evaluated if transient expression systems produce acceptable quantity, high quality and functional IgMs and thereby provide rapid, efficient and high-throughput alternatives to the established expression systems. The production of the three model antibodies IgM012, IgM012_GL and IgM617 was investigated in the human HEK293E cell line and compared to the well-established IgM producing CHO DG44 cell lines –13. CHO et al., 2015 [The stable IgM producing CHO DG44 cell lines were generated as described in Chromikova EBNA1 gene for episomal plasmid amplification and the CMV promoter upstream the gene of interest  was used for affinity chromatography. The IgMs were eluted with 1 M Arginine, 2 M MgCl2, pH 3.5. As a second purification step, the eluted IgM samples were applied on a SuperoseTM 6 column . IgM was separated from nucleic acid contaminants with running buffer  at a flow rate of 0.5 mL/min.IgM antibodies were purified according to Hennicke l., 2017 . BrieflySeparation and identification of purified IgMs by SDS-PAGE and Western blot was performed as described in . Silver 60–80 ng of IgM was applied to a Mica Sheet covered with evaporated carbon film. The film was floated off in ~100 μL 2% sodium silicotungstate  and fished onto a 400 mesh Cu TEM grid (Delta Microscopies). Images were taken with a Tecnai F20 TEM microscope at 200 keV.The site-specific glycan pattern was analyzed as described in . Brieflyet al., 2019 [The activation of the classical complement pathway was monitored by an ELISA-assay based on detection of C4b deposition according to Bally l., 2019 . NHS wase.g., approx. 8.4 × 106 cells/mL in CHO DG44 and 8.1 × 106 cells/mL in HEK293E expressing 36 μg/mL and 30 μg/mL IgM012_GL, respectively)  , althougl., 2015 .IgMs bear five potential N-glycosylation sites (GS) which can be divided into the mainly complex glycosylated GS1-3 and the primarily oligomannose type GS4 and GS5 . EspeciaProduction in HEK293E cells led to a higher mobility on the SDS gel of all protein fractions compared to production in CHO DG44 . This efOligomannose type was the predominant glycan structure found at GS4 and GS5 of IgM produced by both expression hosts . The numAll in all, glycosylation analysis revealed that transient expression in HEK293E cells leads to a less processed glycan pattern compared to stable expression in CHO DG44 cells.et al., 2016 [The structures of IgMs produced by HEK293E were analyzed with negative stain TEM in order to evaluate their structural integrity. The pentameric IgMs produced by HEK293E exhibited a central circular core with projecting Fab units in a star-shaped manner  as it isl., 2016 ,26. HencDuring recombinant production, it is of particular importance that the product exhibits its natural properties. In the case of antibodies, the interaction with the antigen is a key function. IgM617 and IgM012_GL were chosen as a representative to study the impact of the host cell line and expression system. The binding affinity of IgM617 to its natural antigens, glycosphingolipids, was evaluated by a ganglioside ELISA. Products of both expression hosts showed comparable binding to the gangliosides GM1, GD3 and GM3 . Moreoveet al., 2019 [The capacity of the different recombinant IgM preparations and polyclonal IgM isolated from human serum (pIgM) to trigger complement activation was analyzed and compared by ELISA as described in Bally in vitro complement activation level  pIRES plasmids for stable transfection into CHO DG44 host cell line. Image was reprinted from Chromikova et al. . (B) pCE(PDF)Click here for additional data file.S2 Figμ and anti-κ chain.Silver staining and western blots under reducing conditions were done for anti-(PDF)Click here for additional data file.S3 FigRepresentative field of particles with a 200 nm scale bar. Circled particles represent side views of pentameric IgM012. The smaller particles pointed out by the yellow arrows indicate molecules that could be dimers.(PDF)Click here for additional data file.S4 Figet al., 2005 [Potency was tested with anti-hu IgM (μ-chain specific) alkaline phosphatase according to Zeng l., 2005 .(PDF)Click here for additional data file.S5 FigμL/well of IgM sample. Binding of the IgM to UG37 was detected with anti-kappa-HRP conjugate and TMB. All samples were analyzed in duplicates, except for the negative control, which was the IgM617 (black lines).A microtiter plate was coated with UG37, washed and incubated with 50 (PDF)Click here for additional data file.S1 Raw images(PDF)Click here for additional data file.