Residual lung lesions after completion of chemotherapy for gestational trophoblastic neoplasia: should we operate?

The significance of residual lung metastasis from malignant gestational trophoblastic neoplasm (GTN) after the completion of chemotherapy is unknown. We currently do not advocate resection of these masses. Here, we investigate the outcome of these patients. Patients with residual lung abnormalities after the completion of treatment for GTN were compared to those who had a complete radiological resolution of the disease. None of the residual masses post-treatment were surgically removed. In all, 76 patients were identified. Overall 53 (70%) patients had no radiological abnormality on CXR or CT after completion of treatment. Eight (11%) patients had residual disease on CXR alone 15 patients had residual disease on CT (19%). During follow-up, two patients (2.6%) relapsed. One of these had had a complete radiological response post-treatment whereas the other had residual disease on CT. Patients with residual lung lesions after completing treatment for GTN do not appear to have an increased chance of relapse compared to those with no residual abnormality. We continue to recommend that these patients do not require pulmonary surgery for these lesions

Statistical Characterization of the Charge State and Residue Dependence of Low-Energy CID Peptide Dissociation Patterns

Data mining was performed on 28 330 unique peptide tandem mass spectra for which sequences were assigned with high confidence. By dividing the spectra into different sets based on structural features and charge states of the corresponding peptides, chemical interactions involved in promoting specific cleavage patterns in gas-phase peptides were characterized. Pairwise fragmentation maps describing cleavages at all Xxx-Zzz residue combinations for b and y ions reveal that the difference in basicity between Arg and Lys results in different dissociation patterns for singly charged Arg-and Lys-ending tryptic peptides. While one dominant protonation form (proton localized) exists for Arg-ending peptides, a heterogeneous population of different protonated forms or more facile interconversion of protonated forms (proton partially mobile) exists for Lys-ending peptides. Cleavage C-terminal to acidic residues dominates spectra from singly charged peptides that have a localized proton and cleavage N-terminal to Pro dominates those that have a mobile or partially mobile proton. When Pro is absent from peptides that have a mobile or partially mobile proton, cleavage at each peptide bond becomes much more prominent. Whether the above patterns can be found in b ions, y ions, or both depends on the location of the proton holder(s) in multiply protonated peptides. Enhanced cleavages C-terminal to branched aliphatic residues (Ile, Val, Leu) are observed in both b and y ions from peptides that have a mobile proton, as well as in y ions from peptides that have a partially mobile proton; enhanced cleavages Nterminal to these residues are observed in b ions from peptides that have a partially mobile proton. Statistical tools have been designed to visualize the fragmentation maps and measure the similarity between them. The pairwise cleavage patterns observed expand our knowledge of peptide gas-phase fragmentation behaviors and may be useful in algorithm development that employs improved models to predict fragment ion intensities. Low-energy collision-induced dissociation (CID) in mass spectrometry has been used extensively in peptide sequencing for protein identification and analysis of protein modifications. 1,2 Computer algorithms are employed to automate the spectral analysis and assign peptide sequences to the fragmentation spectra. 2-4 Numerous peptide fragmentation spectra are obtained everyday, but only a low percentage (e.g., 10-35%) of them are successfully identified by readily available algorithms. [5][6][7][8] One explanation for the high failure rate of current algorithms is the very simple fragmentation model on which they are based, which assumes that cleavage will occur mainly, if not exclusively, at the amide bonds between consecutive amino acid residues to produce ions of identical abundance (or intensity), regardless of the identity or the chemical property of the residues. 4,9 Although intensity patterns of the fragment ions from the same peptide under the same experimental settings are highly reproducible, current readily available algorithms only use the mass-to-charge (m/z) information from a tandem mass (MS/MS) spectrum and ignore the other information availablesthe relative intensity information. While this approach is sufficient to identify many peptides, many others yield fragmentation patterns that significantly deviate from a uniform fragmentation model. 8 A more detailed and chemically meaningful fragmentation model might improve algorithm performance and might include using different models for different candidate sequences. In addition, the gas-phase unimolecula

Vitamin C selectively kills KRAS and BRAF mutant colorectal cancer cells by targeting GAPDH

More than half of human colorectal cancers (CRCs) carry either KRAS or BRAF mutations, and are often refractory to approved targeted therapies. We report that cultured CRC cells harboring KRAS or BRAF mutations are selectively killed when exposed to high levels of vitamin C. This effect is due to increased uptake of the oxidized form of vitamin C, dehydroascorbate (DHA), via the GLUT1 glucose transporter. Increased DHA uptake causes oxidative stress as intracellular DHA is reduced to vitamin C, depleting glutathione. Thus, ROS accumulates and inactivates glyceraldehyde 3-phosphate dehydrogenase (GAPDH). Inhibiting GAPDH in highly glycolytic KRAS or BRAF mutant cells leads to an energetic crisis and cell death not seen in KRAS and BRAF wild-type cells. High-dose vitamin C impaired tumor growth in Apc/KrasG12D mutant mice. These results provide a mechanistic rationale for exploring the therapeutic use of vitamin C for CRCs with KRAS or BRAF mutations

Endurance, resistance and resilience in the South African health care system: case studies to demonstrate mechanisms of coping within a constrained system

BACKGROUND: South Africa is at present undertaking a series of reforms to transform public health services to make them more effective and responsive to patient and provider needs. A key focus of these reforms is primary care and its overburdened, somewhat dysfunctional and hierarchical nature. This comparative case study examines how patients and providers respond in this system and cope with its systemic demands through mechanisms of endurance, resistance and resilience, using coping and agency literatures as the theoretical lenses. METHODS: As part of a larger research project carried out between 2009 and 2010, this study conducted semi-structured interviews and observations at health facilities in three South African provinces. This study explored patient experiences of access to health care, in particular, ways of coping and how health care providers cope with the health care system’s realities. From this interpretive base, four cases (two patients, two providers) were selected as they best informed on endurance, resistance and resilience. Some commentary from other respondents is added to underline the more ubiquitous nature of these coping mechanisms. RESULTS: The cases of four individuals highlight the complexity of different forms of endurance and passivity, emotion- and problem-based coping with health care interactions in an overburdened, under-resourced and, in some instances, poorly managed system. Patients’ narratives show the micro-practices they use to cope with their treatment, by not recognizing victimhood and sometimes practising unhealthy behaviours. Providers indicate how they cope in their work situations by using peer support and becoming knowledgeable in providing good service. CONCLUSIONS: Resistance and resilience narratives show the adaptive power of individuals in dealing with difficult illness, circumstances or treatment settings. They permit individuals to do more than endure (itself a coping mechanism) their circumstances, though resistance and resilience may be limited. These are individual responses to systemic forces. To transform health care, mutually supportive interactions are required among and between both patients and providers but their nature, as micro-practices, may show a way forward for system change

A Modular BAM Complex in the Outer Membrane of the α-Proteobacterium Caulobacter crescentus

Mitochondria are organelles derived from an intracellular α-proteobacterium. The biogenesis of mitochondria relies on the assembly of β-barrel proteins into the mitochondrial outer membrane, a process inherited from the bacterial ancestor. Caulobacter crescentus is an α-proteobacterium, and the BAM (β-barrel assembly machinery) complex was purified and characterized from this model organism. Like the mitochondrial sorting and assembly machinery complex, we find the BAM complex to be modular in nature. A ∼150 kDa core BAM complex containing BamA, BamB, BamD, and BamE associates with additional modules in the outer membrane. One of these modules, Pal, is a lipoprotein that provides a means for anchorage to the peptidoglycan layer of the cell wall. We suggest the modular design of the BAM complex facilitates access to substrates from the protein translocase in the inner membrane

Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics

Timm W, Scherbart A, Boecker S, Kohlbacher O, Nattkemper TW. Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics. BMC Bioinformatics. 2008;9(1):443.Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides and proteins, however, is the fact that absolute quantification is severely hampered by the unclear relationship between the observed peak intensity and the peptide concentration in the sample. While there are numerous approaches to circumvent this problem experimentally (e. g. labeling techniques), reliable prediction of the peak intensities from peptide sequences could provide a peptide-specific correction factor. Thus, it would be a valuable tool towards label-free absolute quantification. Results: In this work we present machine learning techniques for peak intensity prediction for MALDI mass spectra. Features encoding the peptides' physico-chemical properties as well as string-based features were extracted. A feature subset was obtained from multiple forward feature selections on the extracted features. Based on these features, two advanced machine learning methods (support vector regression and local linear maps) are shown to yield good results for this problem (Pearson correlation of 0.68 in a ten-fold cross validation). Conclusion: The techniques presented here are a useful first step going beyond the binary prediction of proteotypic peptides towards a more quantitative prediction of peak intensities. These predictions in turn will turn out to be beneficial for mass spectrometry-based quantitative proteomics