Crystallographic investigation into the self-assembly, guest binding, and flexibility of urea functionalised metal-organic frameworks

Introduction of hydrogen bond functionality into metal-organic frameworks can enhance guest binding and activation, but a combination of linker flexibility and interligand hydrogen bonding often results in the generation of unwanted structures where the functionality is masked. Herein, we describe the self-assembly of three materials, where Cd2+, Ca2+, and Zn2+ are linked by N,Nʹ-bis(4-carboxyphenyl)urea, and examine the effect of the urea units on structure formation, the generation of unusual secondary building units, structural flexibility, and guest binding. The flexibility of the Zn MOF is probed through single-crystal to single-crystal transformations upon exchange of DMF guests for CS2, showing that the lability of the [Zn4O(RCO2)6] cluster towards solvation enables the urea linkers to adopt distorted conformations as the MOF breathes, even facilitating rotation from the trans/trans to the trans/cis conformation without compromising the overall topology. The results have significant implications in the mechanistic understanding of the hydrolytic stability of MOFs, and in preparing heterogeneous organocatalysts

Estimation of Multivariate Discrete Hawkes Processes: An Application to Incident Monitoring

Hawkes processes are a class of self-exciting point processes that are used to model complex phenomena. While most applications of Hawkes processes assume that event data occurs in continuous-time, the less-studied discrete-time version of the process is more appropriate in some situations. In this work, we develop methodology for the efficient implementation of discrete Hawkes processes. We achieve this by developing efficient algorithms to evaluate the log-likelihood function and its gradient, whose computational complexity is linear in the number of events. We extend these methods to a particular form of a multivariate marked discrete Hawkes process which we use to model the occurrences of violent events within a forensic psychiatric hospital. A prominent feature of our problem, captured by a mark in our process, is the presence of an alarm system which can be heard throughout the hospital. An alarm is sounded when an event is particularly violent in nature and warrants a call for assistance from other members of staff. We conduct a detailed analysis showing that such a variant of the Hawkes process manages to outperform alternative models in terms of predictive power. Finally, we interpret our findings and describe their implications

Identifying immunological biomarkers of sepsis using cytometry bioinformatics and machine learning

Sepsis is a leading cause of mortality and significantly strains healthcare systems worldwide. Improving sepsis care and outcomes depends on appropriate risk stratification and timely identification of the causative pathogen to guide patient management and treatment. Enormous efforts have been made to identify diagnostic and prognostic biomarkers to aid decision making, but to date, they have failed to identify candidates with acceptable accuracy and precision to have an impact in the clinic. Past studies have often focused on individual biomarkers without considering the potential benefit of multi-marker panels incorporating deep immunological phenotyping. This work addressed this issue with a cross-disciplinary approach that integrated sepsis biomarker discovery, cytometry bioinformatics, and supervised machine learning. Firstly, a novel framework for cytometry data analysis was developed, along with a new ensemble clustering algorithm that reduced the risk of biasing exploratory analyses with the application of a single clustering technique. Secondly, the analysis framework was applied to a study cohort of severe sepsis patients, and their early immunological profile consisting of cellular and humoral parameters (within 36 hours of diagnosis) was determined. The captured immunological parameters were then combined with routine clinical data and lipid plasma concentrations to generate interpretable machine learning models for predicting mortality and the underlying cause of infection. The generated models discriminated between survivors and non-survivors, and between Gram-negative and Gram-positive infections, and identified potential combinations of biomarkers with predictive value

Using multi-echo simultaneous multi-slice (SMS) EPI to improve functional MRI of the subcortical nuclei of the basal ganglia at ultra-high field (7T)

The nuclei of the basal ganglia pose a special problem for functional MRI, especially at ultra-high field, because T2* variations between different regions result in suboptimal BOLD sensitivity when using gradient-echo echo-planar imaging (EPI). Specifically, the iron-rich lentiform nucleus of the basal ganglia, including the putamen and globus pallidus, suffers from substantial signal loss when imaging is performed using conventional single-echo EPI with echo times optimized for the cortex. Multi-echo EPI acquires several echoes at different echo times for every imaging slice, allowing images to be reconstructed with a weighting of echo times that is optimized individually for each voxel according to the underlying tissue or T2* properties. Here we show that multi-echo simultaneous multi-slice (SMS) EPI can improve functional activation of iron-rich subcortical regions while maintaining sensitivity within cortical areas. Functional imaging during a motor task known to elicit strong activations in the cortex and the subcortex (basal ganglia) was performed to compare the performance of multi-echo SMS EPI to single-echo SMS EPI. Notably within both the caudate nucleus and putamen of the basal ganglia, multi-echo SMS EPI yielded higher tSNR (an average 84% increase) and CNR (an average 58% increase), an approximate 3-fold increase in supra-threshold voxels, and higher t-values (an average 39% increase). The degree of improvement in the group level t-statistics was negatively correlated to the underlying T2* of the voxels, such that the shorter the T2*, as in the iron-rich nuclei of the basal ganglia, the higher the improvement of t-values in the activated region

Strength and conditioning in dance: a systematic review and meta-analysis

This is an author's accepted manuscript of an article due to be published by Wiley in European Journal of Sport Science. The accepted manuscript may differ from the final published version.To assess the evidence for the effect of strength and conditioning on physical qualities and aesthetic competence in dance populations, three electronic databases (PubMed, Scopus, SPORTDiscus) were searched (until September 2022) for studies that met the following criteria: (i) dancers aged >16 years; (ii) structured strength and conditioning intervention; and (iii) with physical qualities and aesthetic competence as outcome measures. Methodological quality and risk of bias of the included studies were assessed through the systematic review tool “QualSyst”. Meta-analyses of effect sizes (Hedges’ g) with forest plots explored the effects of the strength and conditioning interventions. Thirty-six studies met the inclusion criteria and were included in this review. Meta-analysis indicated strength and conditioning significantly (p < 0.05) improved lower body power (g = 0.90, 95%CI: 0.53 to 1.27), upper body strength (g = 0.98, 95%CI: 0.39 to 1.57), lower body strength (g = 1.59, 95%CI: 0.97 to 2.22), and flexibility (g = 0.86, 95%CI: 0.05 to 1.66). Strength and conditioning interventions were found to be effective at improving physical qualities in dancers, recommending their participation in additional sessions to enhance overall fitness and ultimately dance performance. It is recommended that future strength and conditioning intervention research should include sample size calculations, with participants recruited from a specific dance genre and skill level in order to evaluate how strength and conditioning influences dance performance

T-odd Gluon-Top-Quark Effective Couplings at the CERN Large Hadron Collider

The T-odd top-quark chromoelectric dipole moment (tCEDM) is probed through top-quark-pair production via gluon fusion at the CERN Large Hadron Collider (LHC) by considering the possibility of having polarized protons. The complete analytic expressions for the tree-level helicity amplitudes of gg-> ttbar is also presented. For the derived analytic results we determine the 1-sigma statistical sensitivities to the tCEDM form factor for (i) typical CP-odd observables composed of lepton and anti-lepton momenta from t and tbar semileptonic decays for unpolarized protons, and (ii) a CP-odd event asymmetry for polarized protons by using the so-called Berger-Qiu (BQ) parametrization of polarized gluon distribution functions. We find that at the CERN LHC, the CP-odd energy and angular correlations can put a limit of 10^{-18} to 10^{-17} g_scm on the real and imaginary parts of the tCEDM, while the simple CP-odd event asymmetry with polarized protons could put a very strong limit of 10^{-20} g_scm on the imaginary part of the tCEDM.Comment: 14 pages(LaTeX), 1 Postscript figure(use epsfig.sty

Genomic characterisation of Eμ-Myc mouse lymphomas identifies Bcor as a Myc co-operative tumour-suppressor gene

The Eμ-Myc mouse is an extensively used model of MYC driven malignancy; however to date there has only been partial characterization of MYC co-operative mutations leading to spontaneous lymphomagenesis. Here we sequence spontaneously arising Eμ-Myc lymphomas to define transgene architecture, somatic mutations, and structural alterations. We identify frequent disruptive mutations in the PRC1-like component and BCL6-corepressor gene Bcor. Moreover, we find unexpected concomitant multigenic lesions involving Cdkn2a loss and other cancer genes including Nras, Kras and Bcor. These findings challenge the assumed two-hit model of Eμ-Myc lymphoma and demonstrate a functional in vivo role for Bcor in suppressing tumorigenesis.We acknowledge the following funding agencies: Leukaemia Foundation of Australia, Arrow Bone Marrow Transplant Foundation, National Health and Medical Research Council Australia, Cancer Council Victoria, Victorian Cancer Agency, Australian Cancer Research Foundation, Peter MacCallum Cancer Centre Foundation, National Institutes of Health