The bortezomib/proteasome inhibitor PS-341 and triterpenoid CDDO-Im induce synergistic anti-multiple myeloma (MM) activity and overcome bortezomib resistance

The synthetic triterpenoid 2-cyano-3, 12-dioxooleana-1, 9-dien-28-oic acid (CDDO) induces apoptosis in leukemic cells. Here we show that CDDO and its new derivative CDDO-imidazolide (CDDO-Im) trigger apoptosis in multiple myeloma (MM) cells resistant to conventional therapies including melphalan (LR-5), doxorubicin (Dox-40), and dexamethasone (MM.1R, U266, RPMI 8226) without affecting the viability of normal cells. CDDO-IM also triggers apoptosis in bone marrow stromal cells (BMSCs) and decreases interleukin-6 (IL-6) secretion induced by MM cell adhesion to BMSCs. Moreover, CDDO-Im-induced apoptosis in MM cells is not blocked by IL-6 or insulin growth factor-1 (IGF-1). Importantly, CDDO-Im and bortezomib/proteasome inhibitor PS-341 trigger synergistic apoptosis in MM cells associated with loss of mitochondrial membrane potential, superoxide generation, release of mitochondrial proteins cytochrome c/second mitochondria-derived activator of caspases (cytochrome c/Smac), and activation of caspase-8, -9, and -3. Conversely, the pancaspase inhibitor Z-VAD-fmk abrogates the CDDO-Im + bortezomib-induced apoptosis. Low doses of CDDO-Im and bortezomib overcome the cytoprotective effects of antiapoptotic proteins Bcl2 and heat shock protein-27 (Hsp27) as well as nuclear factor-kappa B (NF-kappaB)-mediated growth/survival and drug resistance. Finally, combining CDDO-Im and bortezomib induces apoptosis even in bortezomib-resistant MM patient cells. Together, these findings provide the framework for clinical evaluation of CDDO-Im, either alone or in combination with bortezomib, to overcome drug resistance and improve patient outcome in MM.     

Artificial intelligence in perioperative management of major gastrointestinal surgeries

Artificial intelligence (AI) demonstrated by machines is based on reinforcement learning and revolves around the usage of algorithms. The purpose of this review was to summarize concepts, the scope, applications, and limitations in major gastrointestinal surgery. This is a narrative review of the available literature on the key capabilities of AI to help anesthesiologists, surgeons, and other physicians to understand and critically evaluate ongoing and new AI applications in perioperative management. AI uses available databases called “big data” to formulate an algorithm. Analysis of other data based on these algorithms can help in early diagnosis, accurate risk assessment, intraoperative management, automated drug delivery, predicting anesthesia and surgical complications and postoperative outcomes and can thus lead to effective perioperative management as well as to reduce the cost of treatment. Perioperative physicians, anesthesiologists, and surgeons are well-positioned to help integrate AI into modern surgical practice. We all need to partner and collaborate with data scientists to collect and analyze data across all phases of perioperative care to provide clinical scenarios and context. Careful implementation and use of AI along with real-time human interpretation will revolutionize perioperative care, and is the way forward in future perioperative management of major surgery.     

预防青光眼性失明——优先使用现有检查进行更好的筛查

诊断和治疗原发性开角型青光眼是卫生保健工作的重点。原发性开角型青光眼是全球第二大致盲性眼病，全球共有6680万人受累，其中有670万人因此而双目失明。在英国，人口的老龄化意味着在今后的20年内，原发性开角型青光眼患者的数目可能要增长30％。     

Reducing Unnecessary and Duplicate Ordering for Ovum and Parasite Examinations and Clostridium difficile PCR in Immunocompromised Patients by Using an Alert at the Time of Request in the Order Management System

We implemented hospital information system (HIS) alerts to deter unnecessary test orders for ovum and parasite (O&P) exams and Clostridium difficile PCR. The HIS alerts decreased noncompliant O&P orders (orders after >72 h of hospitalization) from 49.8% to 30.9%, an overall decrease of 19%, and reduced noncompliant C. difficile PCR orders (orders <7 days after a previous positive result) from 30.6% to 19.2%, an overall decrease of 31.9%.