Using Bacteria to Determine Protein Kinase Specificity and Predict Target Substrates

The identification of protein kinase targets remains a significant bottleneck for our understanding of signal transduction in normal and diseased cellular states. Kinases recognize their substrates in part through sequence motifs on substrate proteins, which, to date, have most effectively been elucidated using combinatorial peptide library approaches. Here, we present and demonstrate the ProPeL method for easy and accurate discovery of kinase specificity motifs through the use of native bacterial proteomes that serve as in vivo libraries for thousands of simultaneous phosphorylation reactions. Using recombinant kinases expressed in E. coli followed by mass spectrometry, the approach accurately recapitulated the well-established motif preferences of human basophilic (Protein Kinase A) and acidophilic (Casein Kinase II) kinases. These motifs, derived for PKA and CK II using only bacterial sequence data, were then further validated by utilizing them in conjunction with the scan-x software program to computationally predict known human phosphorylation sites with high confidence

Multi-Institutional experience with FOLFIRINOX in pancreatic adenocarcinoma

Combination chemotherapy with FOLFIRINOX (oxaliplatin, irinotecan, fluorouracil, and leucovorin) was shown to be effective in a large phase III trial. The purpose of this study was to examine the tolerance and effectiveness of FOLFIRINOX as practiced outside of the confines of a clinical trial and to document any dose modifications used by practicing oncologists. Data on patients with all stages of pancreatic adenocarcinoma treated with FOLFIRINOX at three institutions was analyzed for efficacy, tolerance, and use of any dose modifications. Total of 61 patients was included in this review. Median age was 58 years (range: 37 to 72 years), 33 were male (54.1%) and majority had ECOG performance of 0 or 1 (86.9%, 53 patients). Thirty-eight (62.3%) had metastatic disease, while 23 (37.7%) were treated for locally advanced or borderline resectable disease. Patients were treated with a median number of four cycles of FOLFIRINOX, with dose modifications in 58.3% (176/302) of all cycles. Ten patients had stable disease (16.4%), four had a partial response (6.6%) while eight had progressive disease (13.1%) on best imaging following therapy. Median progression-free survival and overall survival were 7.5 months and 13.5 months, respectively. The most common grade 3-4 adverse event was neutropenia at 19.7% (12 cases), with 4.9% (3 cases) rate of febrile neutropenia. Twenty-one patients (34.4%) were hospitalized as a result of therapy but there were no therapy-related deaths. Twenty-three (37.7%) had therapy eventually discontinued as a result of adverse events. Despite substantial rates of adverse events and use of dose modifications, FOLFIRINOX was found to be clinically effective in both metastatic and non-metastatic patients. Regimen toxicity did not detract from overall response and survival

A unique cause of hemoperitoneum: spontaneous rupture of a splenic hemangiopericytoma

Non-traumatic hemoperitoneum may be catastrophic if it is not promptly diagnosed and treated. It is critical to identify this clinical picture and treat any active bleeding. We report the first case in the literature (to our knowledge) of spontaneous hemoperitoneum caused by a cystic splenic hemangiopericytoma. Hemangiopericytomas represent a small subset of soft tissue sarcomas. They rarely originate in the spleen as a primary tumor, with only ten cases having been previously described. The difficulty of predicting the prognosis and clinical behavior of these lesions has been repeatedly stressed. The literature concerning this rare and unusual neoplasm is reviewed

The Catalytic Mechanism of Electron-Bifurcating Electron Transfer Flavoproteins (ETFs) Involves an Intermediary Complex with NAD\u3csup\u3e+\u3c/sup\u3e

Electron bifurcation plays a key role in anaerobic energy metabolism, but it is a relatively new discovery, and only limited mechanistic information is available on the diverse enzymes that employ it. Herein, we focused on the bifurcating electron transfer flavoprotein (ETF) from the hyperthermophilic archaeon Pyrobaculum aerophilum. The EtfABCX enzyme complex couples NADH oxidation to the endergonic reduction of ferredoxin and exergonic reduction of menaquinone. We developed a model for the enzyme structure by using nondenaturing MS, cross-linking, and homology modeling in which EtfA, -B, and -C each contained FAD, whereas EtfX contained two [4Fe-4S] clusters. On the basis of analyses using transient absorption, EPR, and optical titrations with NADH or inorganic reductants with and without NAD+, we propose a catalytic cycle involving formation of an intermediary NAD+-bound complex. A charge transfer signal revealed an intriguing interplay of flavin semiquinones and a protein conformational change that gated electron transfer between the low- and high-potential pathways. We found that despite a common bifurcating flavin site, the proposed EtfABCX catalytic cycle is distinct from that of the genetically unrelated bifurcating NADH-dependent ferredoxin NADP+ oxidoreductase (NfnI). The two enzymes particularly differed in the role of NAD+, the resting and bifurcating-ready states of the enzymes, how electron flow is gated, and the two two-electron cycles constituting the overall four-electron reaction. We conclude that P. aerophilum EtfABCX provides a model catalytic mechanism that builds on and extends previous studies of related bifurcating ETFs and can be applied to the large bifurcating ETF family

Long-Term Outcomes in Percutaneous Radiofrequency Ablation for Histologically Proven Colorectal Lung Metastasis

Introduction To evaluate the long-term outcome of image-guided radiofrequency ablation (RFA) when treating histologically confirmed colorectal lung metastasis in terms of overall survival (OS), progression-free survival (PFS) and local tumour control (LTC). Materials and Methods Retrospective single-centre study. Consecutive RFA treatments of histologically proven lung colorectal metastases between 01/01/2008 and 31/12/14. The primary outcome was patient survival (OS and PFS). Secondary outcomes were local tumour progression (LTP) and complications. Prognostic factors associated with OS/ PFS were determined by univariate and multivariate analyses. Results Sixty patients (39 males: 21 females; median age 69 years) and 125 colorectal lung metastases were treated. Eighty percent (n = 48) also underwent lung surgery for lung metastases. Mean metastasis size (cm) was 1.4 ± 0.6 (range 0.3–4.0). Median number of RFA sessions was 1 (1–4). During follow-up (median 45.5 months), 45 patients died (75%). The estimated OS and PFS survival rates at 1, 3, 5, 7, 9 years were 96.7%, 74.7%, 44.1%, 27.5%, 16.3% (median OS, 52 months) and 66.7%, 31.2%, 25.9%, 21.2% and 5.9% (median PFS, 19 months). The LTC rate was 90% with 6 patients developing LTP with 1-, 2-, 3- and 4-year LTP rates of 3.3%, 8.3%, 10.0% and 10.0%. Progression-free interval < 1 year (P = 0.002, HR = 0.375) and total number of pulmonary metastases (≥ 3) treated (P = 0.037, HR = 0.480) were independent negative prognostic factors. Thirty-day mortality rate was 0% with no intra-procedural deaths. Conclusion The long-term OS and PFS following RFA for the treatment of histologically confirmed colorectal lung metastases demonstrate comparable oncological durability to surgery

Interpretable Forward and Inverse Design of Particle Spectral Emissivity Using Common Machine-Learning Models

Radiative particles are ubiquitous in nature and in various technologies. Calculating radiative properties from known geometry and designs can be computationally expensive, and trying to invert the problem to come up with designs specific to desired radiative properties is even more challenging. Here, we report a machine-learning (ML)-based method for both the forward and inverse problem for dielectric and metallic particles. Our decision-tree-based model is able to provide explicit design rules for inverse problems. Furthermore, we can use the same trained model for both the forward and the inverse problem, which greatly simplifies the computation. Our methodology shows the promise of augmenting optical design optimizations by providing interpretable and actionable design rules for rapidly finding approximate solutions for the inverse design problem. Inverse design is usually done by expensive, slow, iterative optimization. Elzouka et al. show how a simple machine-learning model (decision trees) can efficiently perform inverse design in one shot, while recovering design rules understandable by humans. Inverse design of the spectral emissivity of particles is used as an example