Muscle protein synthesis is increased after exercise, but evidence is now accruing that during muscular activity it is suppressed. In life, muscles are subjected to shortening forces due to contraction, but may also be subject to stretching forces during lengthening. It would be biologically inefficient if contraction and stretch have different effects on muscle protein turnover, but little is known about the metabolic effects of stretch. To investigate this, we assessed myofibrillar and sarcoplasmic protein synthesis (MPS, SPS, respectively) by incorporation of [1-13 C]proline (using gas chromatography-mass spectrometry) and anabolic signalling (by phospho-immunoblotting and kinase assays) in cultured L6 skeletal muscle cells during 30 min of cyclic stretch and over 30 min intervals for up to 120 min afterwards. SPS was unaffected, whereas MPS was suppressed by 40 ± 0.03% during stretch, before returning to basal rates by 90-20 min afterwards. Paradoxically, stretch stimulated anabolic signalling with peak values after 2-30 min: e.g. focal adhesion kinase (FAK Tyr576/577; +28 ± 6%), protein kinase B activity (Akt; +113 ± 31%), p70S6K1 (ribosomal S6 kinase Thr389; 25 ± 5%), 4E binding protein 1 (4EBP1 Thr37/46; 14 ± 3%), eukaryotic elongation factor 2 (eEF2 Thr56; −47 ± 4%), extracellular regulated protein kinase 1/2 (ERK1/2 Tyr202/204; +65% ± 9%), eukaryotic initiation factor 2α (eIF2α Ser51; −20 ± 5%, P < 0.05) and eukaryotic initiation factor 4E (eIF4E Ser209; +33 ± 10%, P < 0.05). After stretch, except for Akt activity, stimulatory phosphorylations were sustained: e.g. FAK (+26 ± 11%) for ≥30 min, eEF2 for ≥60 min (peak −45 ± 4%), 4EBP1 for ≥90 min (+33 ± 5%), and p70S6K1 remained elevated throughout (peak +64 ± 7%). Adenosine monophosphate-activated protein kinase (AMPK) phosphorylation was unchanged throughout. We report for the first time that acute cyclic stretch specifically suppresses MPS, despite increases in activity/phosphorylation of elements thought to increase anabolism.

Objectives:To examine the effects of early formula feeding or breast-feeding on hypoglycemia in infants born to 303 A1-A2 and 88 Class B-RF diabetics.Methods:Infants with hypoglycemia (blood glucose < 40 mg/dL) were breast-fed or formula-fed, and those with recurrences were given intravenous dextrose.Results:Of 293 infants admitted to the well-baby nursery, 87 (30%) had hypoglycemia, corrected by early feeding in 75 (86%), while 12 (14%) required intravenous dextrose. In all, 98 infants were admitted to the newborn intensive care unit for respiratory distress (40%), prematurity (33%) or prevention of hypoglycemia (27%). Although all newborn intensive care unit patients received intravenous dextrose, 22 (22%) had hypoglycemia. Of 109 hypoglycemia episodes, 89 (82%) were single low occurrences. At discharge, 56% of well-baby nursery and 43% of newborn intensive care unit infants initiated breast-feeding.Conclusions:Hypoglycemia among infants of diabetic mothers can be corrected by early breast-feeding or formula feeding.

BackgroundOsteoarthritis (OA) is an inflammatory disease of synovial joints involving the loss and degeneration of articular cartilage. The gold standard for evaluating cartilage loss in OA is the measurement of joint space width on standard radiographs. However, in most cases the diagnosis is made well after the onset of the disease, when the symptoms are well established. Identification of early biomarkers of OA can facilitate earlier diagnosis, improve disease monitoring and predict responses to therapeutic interventions.MethodsThis study describes the bioinformatic analysis of data generated from high throughput proteomics for identification of potential biomarkers of OA. The mass spectrometry data was generated using a canine explant model of articular cartilage treated with the pro-inflammatory cytokine interleukin 1 β (IL-1β). The bioinformatics analysis involved the application of machine learning and network analysis to the proteomic mass spectrometry data. A rule based machine learning technique, BioHEL, was used to create a model that classified the samples into their relevant treatment groups by identifying those proteins that separated samples into their respective groups. The proteins identified were considered to be potential biomarkers. Protein networks were also generated; from these networks, proteins pivotal to the classification were identified.ResultsBioHEL correctly classified eighteen out of twenty-three samples, giving a classification accuracy of 78.3% for the dataset. The dataset included the four classes of control, IL-1β, carprofen, and IL-1β and carprofen together. This exceeded the other machine learners that were used for a comparison, on the same dataset, with the exception of another rule-based method, JRip, which performed equally well. The proteins that were most frequently used in rules generated by BioHEL were found to include a number of relevant proteins including matrix metalloproteinase 3, interleukin 8 and matrix gla protein.ConclusionsUsing this protocol, combining an in vitro model of OA with bioinformatics analysis, a number of relevant extracellular matrix proteins were identified, thereby supporting the application of these bioinformatics tools for analysis of proteomic data from in vitro models of cartilage degradation.

Background: Venous thromboembolism is a significant cause of postoperative death and morbidity. While prophylactic and treatment regimens exist, they usually come with some risk of clinically relevant bleeding and, thus, must be considered carefully for each individual patient. Methods: This special topic article represents a review of current evidence regarding venous thromboembolism risk, biology, and prevention in plastic surgery patients. The specific types and duration of available prophylaxis are also reviewed. The balance of venous thromboembolism risk must be weighed against the risk of hemorrhage. Results: Though alternatives exist, the most validated risk assessment tool is the 2005 modification of the Caprini Risk Assessment Model. Controversies remain regarding recommendations for outpatient and low risk cosmetic patients. The authors additionally make recommendations for high-risk patients regarding the use of tranexamic acid, estrogen therapy, anesthesia, and prophylaxis regimens. Conclusion: Our profession has made great strides in understanding the science behind venous thromboembolism, risk stratification for patients, and prophylactic regimens; yet, continued studies and definitive data are needed. (Plast.