Expectation of forward-backward rapidity correlations in p+pp+p collisions at the LHC energies

Forward-backward correlation strength ($b$) as a function of pesudorapidity intervals for experimental data from $p+\bar{p}$ non-singly diffractive collisions are compared to PYTHIA and PHOJET model calculations. The correlations are discussed as a function of rapidity window ($\Delta \eta$) symmetric about the central rapidity as well as rapidity window separated by a gap ($\eta_{gap}$) between forward and backward regions. While the correlations are observed to be independent of $\Delta \eta$, it is found to decrease with increase in $\eta_{gap}$. This reflects the role of short range correlations and justifies the use of $\eta_{gap}$ to obtain the accurate information about the physics of interest, the long range correlations. The experimental $b$ value shows a linear dependence on $\ln \sqrt{s}$ with the maximum value of unity being reached at $\sqrt{s}$ = 16 TeV, beyond the top LHC energy. However calculations from the PYTHIA and PHOJET models indicate a deviation from linear dependence on $\ln \sqrt{s}$ and saturation in the $b$ values being reached beyond $\sqrt{s}$ = 1.8 TeV. Such a saturation in correlation values could have interesting physical interpretations related to clan structures in particle production. Strong forward-backward correlations are associated with cluster production in the collisions. The average number of charged particles to which the clusters fragments, called the cluster size, are found to also increase linearly with $\ln \sqrt{s}$ for both data and the models studied. The rate of increase in cluster size vs. $\ln \sqrt{s}$ from models studied are larger compared to those from the data and higher for PHOJET compared to PYTHIA. Our study indicates that the forward-backward measurements will provide a clear distinguishing observable for the models studied at LHC energies.Comment: 15 pages, 14 Figures, accepted for publication in International Journal of Modern Physics

Prognostic implications of negative dobutamine stress echocardiography in African Americans compared to Caucasians

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Gabapentin for chronic pelvic pain in women (GaPP2):a multicentre, randomised, double-blind, placebo-controlled trial

BackgroundChronic pelvic pain affects 2–24% of women worldwide and evidence for medical treatments is scarce. Gabapentin is effective in treating some chronic pain conditions. We aimed to measure the efficacy and safety of gabapentin in women with chronic pelvic pain and no obvious pelvic pathology.MethodsWe performed a multicentre, randomised, double-blind, placebo-controlled randomised trial in 39 UK hospital centres. Eligible participants were women with chronic pelvic pain (with or without dysmenorrhoea or dyspareunia) of at least 3 months duration. Inclusion criteria were 18–50 years of age, use or willingness to use contraception to avoid pregnancy, and no obvious pelvic pathology at laparoscopy, which must have taken place at least 2 weeks before consent but less than 36 months previously. Participants were randomly assigned in a 1:1 ratio to receive gabapentin (titrated to a maximum dose of 2700 mg daily) or matching placebo for 16 weeks. The online randomisation system minimised allocations by presence or absence of dysmenorrhoea, psychological distress, current use of hormonal contraceptives, and hospital centre. The appearance, route, and administration of the assigned intervention were identical in both groups. Patients, clinicians, and research staff were unaware of the trial group assignments throughout the trial. Participants were unmasked once they had provided all outcome data at week 16–17, or sooner if a serious adverse event requiring knowledge of the study drug occurred. The dual primary outcome measures were worst and average pain scores assessed separately on a numerical rating scale in weeks 13–16 after randomisation, in the intention-to-treat population. Self-reported adverse events were assessed according to intention-to-treat principles. This trial is registered with the ISRCTN registry, ISCRTN77451762.FindingsParticipants were screened between Nov 30, 2015, and March 6, 2019, and 306 were randomly assigned (153 to gabapentin and 153 to placebo). There were no significant between-group differences in both worst and average numerical rating scale (NRS) pain scores at 13–16 weeks after randomisation. The mean worst NRS pain score was 7·1 (standard deviation [SD] 2·6) in the gabapentin group and 7·4 (SD 2·2) in the placebo group. Mean change from baseline was −1·4 (SD 2·3) in the gabapentin group and −1·2 (SD 2·1) in the placebo group (adjusted mean difference −0·20 [97·5% CI −0·81 to 0·42]; p=0·47). The mean average NRS pain score was 4·3 (SD 2·3) in the gabapentin group and 4·5 (SD 2·2) in the placebo group. Mean change from baseline was −1·1 (SD 2·0) in the gabapentin group and −0·9 (SD 1·8) in the placebo group (adjusted mean difference −0·18 [97·5% CI −0·71 to 0·35]; p=0·45). More women had a serious adverse event in the gabapentin group than in the placebo group (10 [7%] of 153 in the gabapentin group compared with 3 [2%] of 153 in the placebo group; p=0·04). Dizziness, drowsiness, and visual disturbances were more common in the gabapentin group.InterpretationThis study was adequately powered, but treatment with gabapentin did not result in significantly lower pain scores in women with chronic pelvic pain, and was associated with higher rates of side-effects than placebo. Given the increasing reports of abuse and evidence of potential harms associated with gabapentin use, it is important that clinicians consider alternative treatment options to off-label gabapentin for the management of chronic pelvic pain and no obvious pelvic pathology.FundingNational Institute for Health Research

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly