Understanding the natural history of thoracic aortic aneurysms (TAAs) is essential to patient care and surgical decision making. In this evidence summary we discuss some of the most clinically relevant features of the disease. The true incidence of TAAs is likely to be higher than currently reported because of the inherently silent nature of TAAs. However, TAAs can become rapidly lethal once dissection or rupture occurs, highlighting the need for more robust screening. The impressive discovery of familial patterns and novel genetic loci for TAAs challenges the idea that most TAAs are simply sporadic. Although the aorta grows in an indolent manner, its rate of growth and its current diameter both have important clinical implications. Biomechanical studies have supported clinical findings of 6.0 cm as a dangerous threshold. Surgical extirpation of TAAs is currently the mainstay of effective treatment. Although endovascular TAA repair is becoming increasingly common, long-term safety remains unproven. We still need more data to support the concept that any medical therapy is effective.

Recent studies have confirmed a close association between various medical conditions (intracranial aneurysm, abdominal aortic aneurysm, temporal arteritis, autoimmune disorder, renal cysts), certain aortic anatomic variants (bovine aortic arch, direct origin of left vertebral artery from aortic arch, bicuspid aortic valve), and family history of aneurysm disease with thoracic aortic aneurysm and dissection. This paper reviews these associations. We propose to capitalise on these associations as powerful and expanding opportunities to diagnose the virulent but silent disease of thoracic aortic aneurysm. This can be accomplished by recognition of this ‘guilt by association’ with the other conditions. Thus, patients with associated diseases and anatomic variants should be investigated for silent aortic aneurysms. Such a paradigm holds substantial potential for reducing death from the silent killer represented by thoracic aortic aneurysm disease.

Abbreviations: 4EBP, 4E-binding protein; DMSO, dimethyl sulfoxide; EBV, Epstein-Barr virus; ERK, extracellular signal-regulated kinase; IC 50 , half maximal Inhibitory concentration; LI, Loewe index; LMP1, latent membrane protein 1; MAPK, mitogen-activated protein kinase; mTORC, mammalian target of rapamycin complex; mTOR, mammalian target of rapamycin; NOD-SCID, Non-obese diabetic/severe combined immunodeficiency; PI3K, Phospho-inositide 3-kinase; PTLD, posttransplant lymphoproliferative disorder; RI, reduction of immunosuppression; SEM, standard error of the mean; STAT, signal transducer and activator of transcription. Posttransplant lymphoproliferative disorder (PTLD) is a serious complication of organ transplantation that often manifests as Epstein-Barr virus (EBV)-associated B cell lymphomas. Current treatments for PTLD have limited efficacy and can be associated with graft rejection or systemic toxicities. The mTOR inhibitor, rapamycin, suppresses tumor growth of EBV+ B cell lymphoma cells in vitro and in vivo; however, the efficacy is limited and clinical benefits of mTOR inhibitors for PTLD are variable. Here, we show constitutive activation of multiple nodes within the PI3K/Akt/mTOR pathway in EBV+ PTLD-derived cell lines. Inhibition of either PI3K or Akt, with specific inhibitors CAL-101 and MK-2206, respectively, diminished growth of EBV+ B cell lines from PTLD patients in a dose-dependent manner. Importantly, rapamycin combined with CAL-101 or MK-2206 had a synergistic effect in suppressing cell growth as determined by IC 50 isobolographic analysis and Loewe indices. Moreover, these combinations were significantly more effective than rapamycin alone in inhibiting tumor xenograft growth in NOD-SCID mice. Finally, both CAL-101 and MK-2206 also prolonged survival of heterotopic cardiac allografts in C57BL/6 mice. Thus, combination therapy with rapamycin and a PI3K inhibitor, or an Akt inhibitor, can be an efficacious treatment for EBV-associated PTLD, while simultaneously promoting allograft survival. K E Y W O R D S basic (laboratory) research/science, immunosuppressant-mechanistic target of rapamycin (mTOR), immunosuppression/immune modulation, infection and infectious agents-viral: Epstein-Barr Virus (EBV), infectious disease, posttransplant lymphoproliferative disorder (PTLD)

BACKGROUND: Bedside rounding involving both nurses and physicians has numerous benefits for patients and staff. However, precise quantitative data on the current extent of physician–nurse (MD–RN) overlap at the patient bedside are lacking. OBJECTIVE: This study aimed to examine the frequency of nurse and physician overlap at the patient beside and what factors affect this frequency. DESIGN: This is a prospective, observational study of time-motion data generated from wearable radio frequency identification (RFID)-based locator technology. SETTING: Single-institution academic hospital. MEASUREMENTS: The length of physician rounds, frequency of rounds that include nurses simultaneously at the bedside, and length of MD–RN overlap were measured and analyzed by ward, day of week, and distance between patient room and nursing station. RESULTS: A total of 739 MD rounding events were captured over 90 consecutive days. Of these events, 267 took place in single-bed patient rooms. The frequency of MD–RN overlap was 30.0%, and there was no statistical difference between the three wards studied. Overall, the average length of all MD rounds was 7.31 ± 0.58 minutes, but rounding involving a bedside nurse lasted longer than rounds with MDs alone (9.56 vs 5.68 minutes, P < .05). There was no difference in either the length of rounds or the frequency of MD–RN overlap between weekdays and weekends. Finally, patient rooms located farther away from the nursing station had a lower likelihood of MD–RN overlap (Pearson’s r = –0.67, P < .05). CONCLUSION: RFID-based technology provides precise, automated, and high-throughput time-motion data to capture nurse and physician activity. At our institution, 30.0% of rounds involve a bedside nurse, highlighting a potential barrier to bedside interdisciplinary rounding.

Alloimmune responses in acute rejection are complex, involving multiple interacting cell types and pathways. Deep profiling of these cell types has been limited by technology that lacks the capacity to resolve this high dimensionality. Single-cell mass cytometry is used to characterize the alloimmune response in early acute rejection, measuring 37 parameters simultaneously, across multiple time points in two models: a murine cardiac and vascularized composite allotransplant (VCA). Semi-supervised hierarchical clustering is used to group related cell types defined by combinatorial expression of surface and intracellular proteins, along with markers of effector function and activation. This expression profile is mapped to visualize changes in antigen composition across cell types, revealing phenotypic signatures in alloimmune T cells, natural killer (NK) cells, and myeloid subsets that are conserved and that firmly distinguish rejecting from non-rejecting grafts. These data provide a comprehensive, high-dimensional profile of cellular rejection after allograft transplantation.