Orexigenic Gene Expression in Late Gestation Ovine Foetal Hypothalamus is Sensitive to Maternal Undernutrition and Realimentation

Acknowledgements Research was funded by the Scottish Government's Rural and Environment Science and Analytical Services Division (RESAS), including the Strategic Partnership for Animal Science Excellence (SPASE). The authors have no conflicts of interest to declare.

Perioperative fluid therapy: a statement from the international Fluid Optimization Group.

BACKGROUND: Perioperative fluid therapy remains a highly debated topic. Its purpose is to maintain or restore effective circulating blood volume during the immediate perioperative period. Maintaining effective circulating blood volume and pressure are key components of assuring adequate organ perfusion while avoiding the risks associated with either organ hypo- or hyperperfusion. Relative to perioperative fluid therapy, three inescapable conclusions exist: overhydration is bad, underhydration is bad, and what we assume about the fluid status of our patients may be incorrect. There is wide variability of practice, both between individuals and institutions. The aims of this paper are to clearly define the risks and benefits of fluid choices within the perioperative space, to describe current evidence-based methodologies for their administration, and ultimately to reduce the variability with which perioperative fluids are administered. METHODS: Based on the abovementioned acknowledgements, a group of 72 researchers, well known within the field of fluid resuscitation, were invited, via email, to attend a meeting that was held in Chicago in 2011 to discuss perioperative fluid therapy. From the 72 invitees, 14 researchers representing 7 countries attended, and thus, the international Fluid Optimization Group (FOG) came into existence. These researches, working collaboratively, have reviewed the data from 162 different fluid resuscitation papers including both operative and intensive care unit populations. This manuscript is the result of 3 years of evidence-based, discussions, analysis, and synthesis of the currently known risks and benefits of individual fluids and the best methods for administering them. RESULTS: The results of this review paper provide an overview of the components of an effective perioperative fluid administration plan and address both the physiologic principles and outcomes of fluid administration. CONCLUSIONS: We recommend that both perioperative fluid choice and therapy be individualized. Patients should receive fluid therapy guided by predefined physiologic targets. Specifically, fluids should be administered when patients require augmentation of their perfusion and are also volume responsive. This paper provides a general approach to fluid therapy and practical recommendations.

Cytotoxicity Evaluation of Si-Diatom Frustules in a Mouse Model

Silica additives in bone substitute materials are topical, clinically interesting and have significant support in the Orthopaedic field. Biosilica, e.g isolated from diatoms, has many advantages over its synthetic counterparts, e.g. it is amorphous, thus will be absorbed by the body, however, issues such as purity, presence of endotoxins and cytotoxicity need to be addressed before it can be further exploited. Biosilica isolated from Cyclotella Meneghiniana was then tested in a mouse model, to test the immunological response, organ toxicity (kidney, spleen, liver) and route of metabolism/excretion of silica. Five-week-old Balb-c mice were injected subcutaneously with a single high dose (50mg/ml) of Si-frustules, Si-frustules + organic linker and vehicle only control. Animals were sacrificed at 1d and 28d. The animal studies were conducted under an ethically approved protocol at Queen’s University, Belfast. The animals showed no adverse stress during the experiment and remained healthy until sacrifice. Blood results using ICP-OES analysis suggest the frustules were metabolized between comparator groups at different rates, and clearly showed elevated levels of silicon in groups injected with frustules relative to control. The histology of organs showed no variation in morphology of mice injected frustules relative compared to the control group.
Acknowledgements: The authors would like to thank Marie Curie International Outgoing Fellowships from the EU and Beaufort Marine Biodiscovery Award as part of the Marine Biotechnology Ireland Programme for providing financial support to this project.

PROGNOSTIC FACTORS PREDICTING FUNCTIONAL OUTCOME AT FOUR MONTHS FOLLOWING ACUTE ANKLE SPRAIN

PROGNOSTIC FACTORS PREDICTING FUNCTIONAL OUTCOME AT FOUR MONTHS FOLLOWING ACUTE ANKLE SPRAINBleakley C.M.1, O'Connor S.R.1, Tully M.A.2, Rocke L.G.3, MacAuley D.C.1, Bradbury I.4, Keegan S.4, McDonough S.M.11University of Ulster, Health & Rehabilitation Sciences Research Institute, Newtownabbey, United Kingdom, 2Queen's University, UKCRC Centre of Excellence for Public Health (NI), Belfast, United Kingdom, 3Royal Victoria Hospital, Department of Emergency Medicine, Belfast, United Kingdom, 4Frontier Science (Scotland), Kincraig, Inverness-shire, United KingdomPurpose: To identify clinically relevant factors assessed following acute ankle sprain that predict functional recovery at four months post-injury.Relevance: Ankle sprains are one of the most common musculoskeletal injuries with an estimated 5000 new cases occurring each day in the United Kingdom. In the acute phase, ankle sprains may be associated with pain and loss of function. In the longer-term there is a risk of residual problems including chronic pain or reinjury. Few studies have sought to examine factors associated with a poor long-term prognosis.Participants: 101 patients (Age: Mean (SD) 25.9 (7.9) years; Body Mass Index (BMI): 25.3 (3.5) kg/m2) with an acute grade 1 or 2 ankle sprain attending an accident and emergency department or sports injury clinic. Exclusion criteria included complete (grade 3) rupture of the ankle ligament complex, bony ankle injury or multiple injuries.Methods: Participants were allocated as part of a randomised controlled trial to an accelerated intervention incorporating intermittent ice and early therapeutic exercise or a standard protection, rest, ice, compression, and elevation intervention for one week. Treatment was then standardised in both groups and consisted of ankle rehabilitation exercises focusing on muscle strengthening, neuromuscular training, and sports specific functional exercises for a period of approximately four to six weeks. On initial assessment age, gender, mechanism of injury, presence of an audible pop or snap and the presence of contact during the injury were recorded. The following factors were also recorded at baseline and at one and four weeks post-injury: weight-bearing dorsi-flexion test, lateral hop test, presence of medial pain on palpation and a positive impingement sign. Functional status was assessed using the Karlsson score at baseline, at week four and at four months. Reinjury rates were recorded throughout the intervention phase and at four months.Analysis: A mixed between-within subjects analysis of variance (ANOVA) was used to determine the effect of each factor on functional status at week four and at four months. Significance was set at a Bonferroni adjusted level of 0.0125 (0.05/4).Results: Eighty-five participants (84%) were available at final follow-up assessment. Pain on weight-bearing dorsi-flexion and lateral hop tests at week four were both associated with a lower functional score at four months post-injury (P = 0.011 and P = 0.001). No other significant interactions were observed at any other timepoint (baseline or week one). There were only two reinjuries within the four month follow-up period with a further two reported at approximately six months post-injury. We were therefore unable to determine whether any factors were associated with an increased risk of reinjury.Conclusions: Potential prognostic factors on initial or early examination after acute ankle sprain did not help predict functional recovery at four months post-injury. However, pain on weight-bearing dorsi-flexion and lateral hop tests observed at four weeks were associated with a slower rate of recovery.Implications: Some clinical tests may help identify patients at risk of poor functional recovery after acute ankle sprain. However, further work is required to examine factors which may be predictive on initial assessment.Key-words: 1. Prognostic factors 2. Recovery 3. Ankle sprainFunding acknowledgements: Physiotherapy Research Foundation, Chartered Society of Physiotherapy, Strategic Priority Fund; Department of Employment and Learning, Northern Ireland.Ethics approval: Office for Research Ethics Committee (UK).

SYSTEMATIC REVIEW AND META-ANALYSIS: EFFECTS OF WALKING EXERCISE IN CHRONIC MUSCULOSKELETAL PAIN

SYSTEMATIC REVIEW AND META-ANALYSIS: EFFECTS OF WALKING EXERCISE IN CHRONIC MUSCULOSKELETAL PAIN O'Connor S.R.1, Tully M.A.2, Ryan B.3, Baxter D.G.3, Bradley J.M.1, McDonough S.M.11University of Ulster, Health & Rehabilitation Sciences Research Institute, Newtownabbey, United Kingdom, 2Queen's University, UKCRC Centre of Excellence for Public Health (NI), Belfast, United Kingdom, 3University of Otago, Centre for Physiotherapy Research, Dunedin, New ZealandPurpose: To examine the effects of walking exercise on pain and self-reported function in adults with chronic musculoskeletal pain.Relevance: Chronic musculoskeletal pain is a major cause of morbidity, exerting a substantial influence on long-term health status and overall quality of life. Current treatment recommendations advocate various aerobic exercise interventions for such conditions. Walking may represent an ideal form of exercise due to its relatively low impact. However, there is currently limited evidence for its effectiveness.Participants: Not applicable.Methods: A comprehensive search strategy was undertaken by two independent reviewers according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) and the recommendations of the Cochrane Musculoskeletal Review Group. Six electronic databases (Medline, CINAHL, PsychINFO, PEDro, Sport DISCUS and the Cochrane Central Register of Controlled Trials) were searched for relevant papers published up to January 2010 using MeSH terms. All randomised or non-randomised studies published in full were considered for inclusion. Studies were required to include adults aged 18 years or over with a diagnosis of chronic low back pain, osteoarthritis or fibromyalgia. Studies were excluded if they involved peri-operative or post-operative interventions or did not include a comparative, non exercise or non-walking exercise control group. The U.S. Preventative Services Task Force system was used to assess methodological quality. Data for pain and self-reported function were extracted and converted to a score out of 100.Analysis: Data were pooled and analyzed using RevMan (v.5.0.24). Statistical heterogeneity was assessed using the X2 and I2 test statistics. A random effects model was used to calculate the mean differences and 95% CIs. Data were analyzed by length of final follow-up which was categorized as short (≤8 weeks post randomisation), mid (2-12 months) or long-term (>12 months).Results: A total of 4324 articles were identified and twenty studies (1852 participants) meeting the inclusion criteria were included in the review. Overall, studies were judged to be of at least fair methodological quality. The most common sources of likely bias were identified as lack of concealed allocation and failure to adequately address incomplete data. Data from 12 studies were suitable for meta-analysis. Walking led to reductions in pain at short (<8 weeks post randomisation) (-8.44 [-14.54, -2.33]) and mid-term (>8 weeks - 12 month) follow-up (-9.28 [-16.34, -2.22]). No effect was observed for long-term (>12 month) data (-2.49 [-7.62, 2.65]). For function, between group differences were observed for short (-11.57 [-16.06, -7.08]) and mid-term data (-13.26 [-16.91, -9.62]). A smaller effect was also observed at long-term follow-up (-5.60 [-7.70, -3.50]).Conclusions: Walking interventions were associated with statistically significant improvements in pain and function at short and mid-term follow-up. Long-term data were limited but indicated that these effects do not appear to be maintained beyond twelve months.Implications: Walking may be an effective form of exercise for individuals with chronic musculoskeletal pain. However, further research is required which examines longer term follow-up and dose-response issues in this population.Key-words: 1. Walking exercise 2. Musculoskeletal pain 3. Systematic reviewFunding acknowledgements: Department of Employment and Learning, Northern Ireland.Ethics approval: Not applicable.

'Bayesian Optimisation for Nurse Scheduling'

A Bayesian optimisation algorithm for a nurse scheduling problem is presented, which involves choosing a suitable scheduling rule from a set for each nurse's assignment. When a human scheduler works, he normally builds a schedule systematically following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not yet completed, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this paper, we design a more human-like scheduling algorithm, by using a Bayesian optimisation algorithm to implement explicit learning from past solutions. A nurse scheduling problem from a UK hospital is used for testing. Unlike our previous work that used Genetic Algorithms to implement implicit learning [1], the learning in the proposed algorithm is explicit, i.e. we identify and mix building blocks directly. The Bayesian optimisation algorithm is applied to implement such explicit learning by building a Bayesian network of the joint distribution of solutions. The conditional probability of each variable in the network is computed according to an initial set of promising solutions. Subsequently, each new instance for each variable is generated by using the corresponding conditional probabilities, until all variables have been generated, i.e. in our case, new rule strings have been obtained. Sets of rule strings are generated in this way, some of which will replace previous strings based on fitness. If stopping conditions are not met, the conditional probabilities for all nodes in the Bayesian network are updated again using the current set of promising rule strings. For clarity, consider the following toy example of scheduling five nurses with two rules (1: random allocation, 2: allocate nurse to low-cost shifts). In the beginning of the search, the probabilities of choosing rule 1 or 2 for each nurse is equal, i.e. 50%. After a few iterations, due to the selection pressure and reinforcement learning, we experience two solution pathways: Because pure low-cost or random allocation produces low quality solutions, either rule 1 is used for the first 2-3 nurses and rule 2 on remainder or vice versa. In essence, Bayesian network learns 'use rule 2 after 2-3x using rule 1' or vice versa. It should be noted that for our and most other scheduling problems, the structure of the network model is known and all variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus, learning can amount to 'counting' in the case of multinomial distributions. For our problem, we use our rules: Random, Cheapest Cost, Best Cover and Balance of Cost and Cover. In more detail, the steps of our Bayesian optimisation algorithm for nurse scheduling are: 1. Set t = 0, and generate an initial population P(0) at random; 2. Use roulette-wheel selection to choose a set of promising rule strings S(t) from P(t); 3. Compute conditional probabilities of each node according to this set of promising solutions; 4. Assign each nurse using roulette-wheel selection based on the rules' conditional probabilities. A set of new rule strings O(t) will be generated in this way; 5. Create a new population P(t+1) by replacing some rule strings from P(t) with O(t), and set t = t+1; 6. If the termination conditions are not met (we use 2000 generations), go to step 2. Computational results from 52 real data instances demonstrate the success of this approach. They also suggest that the learning mechanism in the proposed approach might be suitable for other scheduling problems. Another direction for further research is to see if there is a good constructing sequence for individual data instances, given a fixed nurse scheduling order. If so, the good patterns could be recognized and then extracted as new domain knowledge. Thus, by using this extracted knowledge, we can assign specific rules to the corresponding nurses beforehand, and only schedule the remaining nurses with all available rules, making it possible to reduce the solution space. Acknowledgements The work was funded by the UK Government's major funding agency, Engineering and Physical Sciences Research Council (EPSRC), under grand GR/R92899/01. References [1] Aickelin U, "An Indirect Genetic Algorithm for Set Covering Problems", Journal of the Operational Research Society, 53(10): 1118-1126,

'Bayesian Optimisation for Nurse Scheduling'

A Bayesian optimisation algorithm for a nurse scheduling problem is presented, which involves choosing a suitable scheduling rule from a set for each nurse's assignment. When a human scheduler works, he normally builds a schedule systematically following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not yet completed, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this paper, we design a more human-like scheduling algorithm, by using a Bayesian optimisation algorithm to implement explicit learning from past solutions. A nurse scheduling problem from a UK hospital is used for testing. Unlike our previous work that used Genetic Algorithms to implement implicit learning [1], the learning in the proposed algorithm is explicit, i.e. we identify and mix building blocks directly. The Bayesian optimisation algorithm is applied to implement such explicit learning by building a Bayesian network of the joint distribution of solutions. The conditional probability of each variable in the network is computed according to an initial set of promising solutions. Subsequently, each new instance for each variable is generated by using the corresponding conditional probabilities, until all variables have been generated, i.e. in our case, new rule strings have been obtained. Sets of rule strings are generated in this way, some of which will replace previous strings based on fitness. If stopping conditions are not met, the conditional probabilities for all nodes in the Bayesian network are updated again using the current set of promising rule strings. For clarity, consider the following toy example of scheduling five nurses with two rules (1: random allocation, 2: allocate nurse to low-cost shifts). In the beginning of the search, the probabilities of choosing rule 1 or 2 for each nurse is equal, i.e. 50%. After a few iterations, due to the selection pressure and reinforcement learning, we experience two solution pathways: Because pure low-cost or random allocation produces low quality solutions, either rule 1 is used for the first 2-3 nurses and rule 2 on remainder or vice versa. In essence, Bayesian network learns 'use rule 2 after 2-3x using rule 1' or vice versa. It should be noted that for our and most other scheduling problems, the structure of the network model is known and all variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus, learning can amount to 'counting' in the case of multinomial distributions. For our problem, we use our rules: Random, Cheapest Cost, Best Cover and Balance of Cost and Cover. In more detail, the steps of our Bayesian optimisation algorithm for nurse scheduling are: 1. Set t = 0, and generate an initial population P(0) at random; 2. Use roulette-wheel selection to choose a set of promising rule strings S(t) from P(t); 3. Compute conditional probabilities of each node according to this set of promising solutions; 4. Assign each nurse using roulette-wheel selection based on the rules' conditional probabilities. A set of new rule strings O(t) will be generated in this way; 5. Create a new population P(t+1) by replacing some rule strings from P(t) with O(t), and set t = t+1; 6. If the termination conditions are not met (we use 2000 generations), go to step 2. Computational results from 52 real data instances demonstrate the success of this approach. They also suggest that the learning mechanism in the proposed approach might be suitable for other scheduling problems. Another direction for further research is to see if there is a good constructing sequence for individual data instances, given a fixed nurse scheduling order. If so, the good patterns could be recognized and then extracted as new domain knowledge. Thus, by using this extracted knowledge, we can assign specific rules to the corresponding nurses beforehand, and only schedule the remaining nurses with all available rules, making it possible to reduce the solution space. Acknowledgements The work was funded by the UK Government's major funding agency, Engineering and Physical Sciences Research Council (EPSRC), under grand GR/R92899/01. References [1] Aickelin U, "An Indirect Genetic Algorithm for Set Covering Problems", Journal of the Operational Research Society, 53(10): 1118-1126,

Ultrafast transient absorption spectroscopy: principles and applications

The study of photophysical and photochemical processes crosses the interest of many fields of research in physics, chemistry and biology. In particular, the photophysical and photochemical reactions, after light absorption by a photosynthetic pigment-protein complex, are among the fastest events in biology, taking place on timescales ranging from tens of femtoseconds to a few nanoseconds. Among the experimental approaches developed for this purpose, the advent of ultrafast transient absorption spectroscopy has become a powerful and widely used technique.[1,2] Focusing on the process of photosynthesis, it relies upon the efficient absorption and conversion of the radiant energy from the Sun. Chlorophylls and carotenoids are the main players in the process. Photosynthetic pigments are typically arranged in a highly organized fashion to constitute antennas and reaction centers, supramolecular devices where light harvesting and charge separation take place. The very early steps in the photosynthetic process take place after the absorption of a photon by an antenna system, which harvests light and eventually delivers it to the reaction center. In order to compete with internal conversion, intersystem crossing, and fluorescence, which inevitably lead to energy loss, the energy and electron transfer processes that fix the excited-state energy in photosynthesis must be extremely fast. In order to investigate these events, ultrafast techniques down to a sub-100 fs resolution must be used. In this way, energy migration within the system as well as the formation of new chemical species such as charge-separated states can be tracked in real time. This can be achieved by making use of ultrafast transient absorption spectroscopy. The basic principles of this notable technique, instrumentation, and some recent applications to photosynthetic systems[3] will be described. Acknowledgements M. Moreno Oliva thanks the MINECO for a “Juan de la Cierva-Incorporación” research contract. References [1] U. Megerle, I. Pugliesi, C. Schriever, C.F. Sailer and E. Riedle, Appl. Phys. B, 96, 215 – 231 (2009). [2] R. Berera, R. van Grondelle and J.T.M. Kennis, Photosynth. Res., 101, 105 – 118 (2009). [3] T. Nikkonen, M. Moreno Oliva, A. Kahnt, M. Muuronen, J. Helaja and D.M. Guldi, Chem. Eur. J., 21, 590 – 600 (2015).

PDF Pre-Preface

On the 15th of April, 1897, a 19 year-old European resident of Baghdad, named Alexander Richard Svoboda, set out on a long journey to Europe by caravan, boat and train. From a large and influential family of merchants, artists, and explorers settled in Ottoman Iraq since the end of the 18th century, Alexander traveled in the company of his parents and a departing British diplomat accompanied by his retinue. They followed a circuitous route through the Middle East to Cairo and thence to Europe on a three and a half month journey which Alexander described day-by-day in a journal written in the Iraqi Arabic of his time.

DOC X Pre-Preface

On the 15th of April, 1897, a 19 year-old European resident of Baghdad, named Alexander Richard Svoboda, set out on a long journey to Europe by caravan, boat and train. From a large and influential family of merchants, artists, and explorers settled in Ottoman Iraq since the end of the 18th century, Alexander traveled in the company of his parents and a departing British diplomat accompanied by his retinue. They followed a circuitous route through the Middle East to Cairo and thence to Europe on a three and a half month journey which Alexander described day-by-day in a journal written in the Iraqi Arabic of his time.

Antioxidant activity of jacaranda decurrens Cham.

Many diseases and related degenerative processes including heart, câncer and Parkinson diseases are associated with rcactive oxygen species (ROS). In an effort Io preveni diseases, search for com-pounds with antioxidant activity hás been a major interestof dif-ferent research groups in natural products research. The objective of this research was to investigatethe antioxidant activity of EtOH leaf extract ofjacarando decurrrens and its fractions using the 2,2-diphenyl-2-picrylhydrazyl hydrate (DPPH) assay [lJ, that uses s pé ciro me t ric method to determine radical scavenging activity, Rutinattheconcçntrationof l.Omg-L was used as the standard. Our results ha vê shown lhat crude extract and fractions had anti-oxidant activities mainly if tested at concentrations of 5.0 to 10.0mg-L. such activities, however. were lesser or equal to the standard (Table 1). The triterpenes, ursolic and oleanohc acids, were detected in the crude extract, Jd-1 and Jd-2, Possibly, these triterpenes are the active constituents responsible for the antioxi-dant activity |2j. At lower concentrations (0,6mg-L than the standard. Jd-3 fraction was the most active. The presenceof flavo-noids and glycosilated compounds were detected in jcl-3 fraction (2], This is the first attempt to demonstrate antioxidant activities found i n Já cara n (ia decurrens leaf extracts. Acknowledgements. Re-search funded by FAPESP. The State of São Paulo Research Founda-tion. Brazil, Referentes: 11) Koleva I. et ai. (2002). Phytochem Anal. 13: 8-17, (2! Oh CJ, et ai. (2007)- Free Radie Rés. 41(6): 638-44.