Phaser crystallographic software.

Phaser is a program for phasing macromolecular crystal structures by both molecular replacement and experimental phasing methods. The novel phasing algorithms implemented in Phaser have been developed using maximum likelihood and multivariate statistics. For molecular replacement, the new algorithms have proved to be significantly better than traditional methods in discriminating correct solutions from noise, and for single-wavelength anomalous dispersion experimental phasing, the new algorithms, which account for correlations between F(+) and F(-), give better phases (lower mean phase error with respect to the phases given by the refined structure) than those that use mean F and anomalous differences DeltaF. One of the design concepts of Phaser was that it be capable of a high degree of automation. To this end, Phaser (written in C++) can be called directly from Python, although it can also be called using traditional CCP4 keyword-style input. Phaser is a platform for future development of improved phasing methods and their release, including source code, to the crystallographic community

Development and simultaneous application of multiple care protocols in critical care: amulticenter feasibility study

Objective: To test the feasibility of and interactions among three software-driven critical care protocols. Design: Prospective cohort study. Setting: Intensive care units in six European and American university hospitals. Patients: 174 cardiac surgery and 41 septic patients. Interventions: Application of software-driven protocols for cardiovascular management, sedation, and weaning during the first 7days of intensive care. Measurements and results: All protocols were used simultaneously in 85% of the cardiac surgery and 44% of the septic patients, and any one of the protocols was used for 73 and 44% of study duration, respectively. Protocol use was discontinued in 12% of patients by the treating clinician and in 6% for technical/administrative reasons. The number of protocol steps per unit of time was similar in the two diagnostic groups (n.s. for all protocols). Initial hemodynamic stability (a protocol target) was achieved in 26 ± 18 min (mean ± SD) in cardiac surgery and in 24 ± 18 min in septic patients. Sedation targets were reached in 2.4 ± 0.2 h in cardiac surgery and in 3.6 ± 0.2 h in septic patients. Weaning protocol was started in 164 (94%; 154 extubated) cardiac surgery and in 25 (60%; 9 extubated) septic patients. The median (interquartile range) time from starting weaning to extubation (a protocol target) was 89 min (range 44-154 min) for the cardiac surgery patients and 96 min (range 56-205 min) for the septic patients. Conclusions: Multiple software-driven treatment protocols can be simultaneously applied with high acceptance and rapid achievement of primary treatment goals. Time to reach these primary goals may provide aperformance indicato

Long-term NOx measurements in the remote marine tropical troposphere

Atmospheric nitrogen oxides (NO + NO2 = NOx) have been measured at the Cape Verde Atmospheric Observatory (CVAO) in the tropical Atlantic (16∘51′ N, 24∘52′ W) since October 2006. These measurements represent a unique time series of NOx in the background remote troposphere. Nitrogen dioxide (NO2) is measured via photolytic conversion to nitric oxide (NO) by ultraviolet light-emitting diode arrays followed by chemiluminescence detection. Since the measurements began, a blue light converter (BLC) has been used for NO2 photolysis, with a maximum spectral output of 395 nm from 2006 to 2015 and of 385 nm from 2015 onwards. The original BLC used was constructed with a Teflon-like material and appeared to cause an overestimation of NO2 when illuminated. To avoid such interferences, a new additional photolytic converter (PLC) with a quartz photolysis cell (maximum spectral output also 385 nm) was implemented in March 2017. Once corrections are made for the NO2 artefact from the original BLC, the two NO2 converters are shown to give comparable NO2 mixing ratios (BLC = 0.99 × PLC + 0.7 ppt, linear least-squares regression), giving confidence in the quantitative measurement of NOx at very low levels. Data analysis methods for the NOx measurements made at CVAO have been developed and applied to the entire time series to produce an internally consistent and high-quality long-term data set. NO has a clear diurnal pattern with a maximum mixing ratio of 2–10 ppt during the day depending on the season and ∼ 0 ppt during the night. NO2 shows a fairly flat diurnal signal, although a small increase in daytime NOx is evident in some months. Monthly average mixing ratios of NO2 vary between 5 and 30 ppt depending on the season. Clear seasonal trends in NO and NO2 levels can be observed with a maximum in autumn and winter and a minimum in spring and summer.</p

Development and simultaneous application of multiple care protocols in critical care: a multicenter feasibility study

OBJECTIVE: To test the feasibility of and interactions among three software-driven critical care protocols. DESIGN: Prospective cohort study. SETTING: Intensive care units in six European and American university hospitals. PATIENTS: 174 cardiac surgery and 41 septic patients. INTERVENTIONS: Application of software-driven protocols for cardiovascular management, sedation, and weaning during the first 7 days of intensive care. MEASUREMENTS AND RESULTS: All protocols were used simultaneously in 85% of the cardiac surgery and 44% of the septic patients, and any one of the protocols was used for 73 and 44% of study duration, respectively. Protocol use was discontinued in 12% of patients by the treating clinician and in 6% for technical/administrative reasons. The number of protocol steps per unit of time was similar in the two diagnostic groups (n.s. for all protocols). Initial hemodynamic stability (a protocol target) was achieved in 26+/-18 min (mean+/-SD) in cardiac surgery and in 24+/-18 min in septic patients. Sedation targets were reached in 2.4+/-0.2h in cardiac surgery and in 3.6 +/-0.2h in septic patients. Weaning protocol was started in 164 (94%; 154 extubated) cardiac surgery and in 25 (60%; 9 extubated) septic patients. The median (interquartile range) time from starting weaning to extubation (a protocol target) was 89 min (range 44-154 min) for the cardiac surgery patients and 96 min (range 56-205 min) for the septic patients. CONCLUSIONS: Multiple software-driven treatment protocols can be simultaneously applied with high acceptance and rapid achievement of primary treatment goals. Time to reach these primary goals may provide a performance indicator

Overview of the CCP4 suite and current developments.

The CCP4 (Collaborative Computational Project, Number 4) software suite is a collection of programs and associated data and software libraries which can be used for macromolecular structure determination by X-ray crystallography. The suite is designed to be flexible, allowing users a number of methods of achieving their aims. The programs are from a wide variety of sources but are connected by a common infrastructure provided by standard file formats, data objects and graphical interfaces. Structure solution by macromolecular crystallography is becoming increasingly automated and the CCP4 suite includes several automation pipelines. After giving a brief description of the evolution of CCP4 over the last 30 years, an overview of the current suite is given. While detailed descriptions are given in the accompanying articles, here it is shown how the individual programs contribute to a complete software package

How to Minimize the Attack Rate during Multiple Influenza Outbreaks in a Heterogeneous Population

<div><h3>Background</h3><p>If repeated interventions against multiple outbreaks are not feasible, there is an optimal level of control during the first outbreak. Any control measures above that optimal level will lead to an outcome that may be as sub-optimal as that achieved by an intervention that is too weak. We studied this scenario in more detail.</p> <h3>Method</h3><p>An age-stratified ordinary-differential-equation model was constructed to study infectious disease outbreaks and control in a population made up of two groups, adults and children. The model was parameterized using influenza as an example. This model was used to simulate two consecutive outbreaks of the same infectious disease, with an intervention applied only during the first outbreak, and to study how cumulative attack rates were influenced by population composition, strength of inter-group transmission, and different ways of triggering and implementing the interventions. We assumed that recovered individuals are fully immune and the intervention does not confer immunity.</p> <h3>Results/Conclusion</h3><p>The optimal intervention depended on coupling between the two population sub-groups, the length, strength and timing of the intervention, and the population composition. Population heterogeneity affected intervention strategies only for very low cross-transmission between groups. At more realistic values, coupling between the groups led to synchronization of outbreaks and therefore intervention strategies that were optimal in reducing the attack rates for each subgroup and the population overall coincided. For a sustained intervention of low efficacy, early intervention was found to be best, while at high efficacies, a delayed start was better. For short interventions, a delayed start was always advantageous, independent of the intervention efficacy. For most scenarios, starting the intervention after a certain cumulative proportion of children were infected seemed more robust in achieving close to optimal outcomes compared to a strategy that used a specified duration after an outbreak’s beginning as the trigger.</p> </div

The CCP4 suite: integrative software for macromolecular crystallography

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.Jon Agirre is a Royal Society University Research Fellow (UF160039 and URF\R\221006). Mihaela Atanasova is funded by the UK Engineering and Physical Sciences Research Council (EPSRC; EP/R513386/1). Haroldas Bagdonas is funded by The Royal Society (RGF/R1/181006). Jose´ Javier Burgos-Ma´rmol and Daniel J. Rigden are supported by the BBSRC (BB/S007105/1). Robbie P. Joosten is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 871037 (iNEXTDiscovery) and by CCP4. This work was supported by the Medical Research Council as part of United Kingdom Research and Innovation, also known as UK Research and Innovation: MRC file reference No. MC_UP_A025_1012 to Garib N. Murshudov, which also funded Keitaro Yamashita, Paul Emsley and Fei Long. Robert A. Nicholls is funded by the BBSRC (BB/S007083/1). Soon Wen Hoh is funded by the BBSRC (BB/T012935/1). Kevin D. Cowtan and Paul S. Bond are funded in part by the BBSRC (BB/S005099/1). John Berrisford and Sameer Velankar thank the European Molecular Biology Laboratory–European Bioinformatics Institute, who supported this work. Andrea Thorn was supported in the development of AUSPEX by the German Federal Ministry of Education and Research (05K19WWA and 05K22GU5) and by Deutsche Forschungsgemeinschaft (TH2135/2-1). Petr Kolenko and Martin Maly´ are funded by the MEYS CR (CZ.02.1.01/0.0/0.0/16_019/0000778). Martin Maly´ is funded by the Czech Academy of Sciences (86652036) and CCP4/STFC (521862101). Anastassis Perrakis acknowledges funding from iNEXT (grant No. 653706), iNEXT-Discovery (grant No. 871037), West-Life (grant No. 675858) and EOSC-Life (grant No. 824087) funded by the Horizon 2020 program of the European Commission. Robbie P. Joosten has been the recipient of a Veni grant (722.011.011) and a Vidi grant (723.013.003) from the Netherlands Organization for Scientific Research (NWO). Maarten L. Hekkelman, Robbie P. Joosten and Anastassis Perrakis thank the Research High Performance Computing facility of the Netherlands Cancer Institute for providing and maintaining computation resources and acknowledge the institutional grant from the Dutch Cancer Society and the Dutch Ministry of Health, Welfare and Sport. Tarik R. Drevon is funded by the BBSRC (BB/S007040/1). Randy J. Read is supported by a Principal Research Fellowship from the Wellcome Trust (grant 209407/Z/17/Z). Atlanta G. Cook is supported by a Wellcome Trust SRF (200898) and a Wellcome Centre for Cell Biology core grant (203149). Isabel Uso´n acknowledges support from STFC-UK/CCP4: ‘Agreement for the integration of methods into the CCP4 software distribution, ARCIMBOLDO_LOW’ and Spanish MICINN/AEI/FEDER/UE (PID2021-128751NB-I00). Pavol Skubak and Navraj Pannu were funded by the NWO Applied Sciences and Engineering Domain and CCP4 (grant Nos. 13337 and 16219). Bernhard Lohkamp was supported by the Ro¨ntgen A˚ ngstro¨m Cluster (grant 349-2013-597). Nicholas Pearce is currently funded by the SciLifeLab and Wallenberg Data Driven Life Science Program (grant KAW 2020.0239) and has previously been funded by a Veni Fellowship (VI.Veni.192.143) from the Dutch Research Council (NWO), a Long-term EMBO fellowship (ALTF 609-2017) and EPSRC grant EP/G037280/1. David M. Lawson received funding from BBSRC Institute Strategic Programme Grants (BB/P012523/1 and BB/P012574/1). Lucrezia Catapano is the recipient of an STFC/CCP4-funded PhD studentship (Agreement No: 7920 S2 2020 007).Peer reviewe

Measurement of inclusive π0\pi^{0} production in hadronic Z0Z^{0} decays

An analysis is presented of inclusive \pi^0 production in Z^0 decays measured with the DELPHI detector. At low energies, \pi^0 decays are reconstructed by \linebreak using pairs of converted photons and combinations of converted photons and photons reconstructed in the barrel electromagnetic calorimeter (HPC). At high energies (up to x_p = 2 \cdot p_{\pi}/\sqrt{s} = 0.75) the excellent granularity of the HPC is exploited to search for two-photon substructures in single showers. The inclusive differential cross section is measured as a function of energy for {q\overline q} and {b \bar b} events. The number of \pi^0's per hadronic Z^0 event is N(\pi^0)/ Z_{had}^0 = 9.2 \pm 0.2 \mbox{(stat)} \pm 1.0 \mbox{(syst)} and for {b \bar b}~events the number of \pi^0's is {\mathrm N(\pi^0)/ b \overline b} = 10.1 \pm 0.4 \mbox{(stat)} \pm 1.1 \mbox{(syst)} . The ratio of the number of \pi^0's in b \overline b events to hadronic Z^0 events is less affected by the systematic errors and is found to be 1.09 \pm 0.05 \pm 0.01. The measured \pi^0 cross sections are compared with the predictions of different parton shower models. For hadronic events, the peak position in the \mathrm \xi_p = \ln(1/x_p) distribution is \xi_p^{\star} = 3.90^{+0.24}_{-0.14}. The average number of \pi^0's from the decay of primary \mathrm B hadrons is found to be {\mathrm N} (B \rightarrow \pi^0 \, X)/\mbox{B hadron} = 2.78 \pm 0.15 \mbox{(stat)} \pm 0.60 \mbox{(syst)}