String Method for the Study of Rare Events

We present a new and efficient method for computing the transition pathways, free energy barriers, and transition rates in complex systems with relatively smooth energy landscapes. The method proceeds by evolving strings, i.e. smooth curves with intrinsic parametrization whose dynamics takes them to the most probable transition path between two metastable regions in the configuration space. Free energy barriers and transition rates can then be determined by standard umbrella sampling technique around the string. Applications to Lennard-Jones cluster rearrangement and thermally induced switching of a magnetic film are presented.Comment: 4 pages, 4 figure

Dynamic of a non homogeneously coarse grained system

To study materials phenomena simultaneously at various length scales, descriptions in which matter can be coarse grained to arbitrary levels, are necessary. Attempts to do this in the static regime (i.e. zero temperature) have already been developed. In this letter, we present an approach that leads to a dynamics for such coarse-grained models. This allows us to obtain temperature-dependent and transport properties. Renormalization group theory is used to create new local potentials model between nodes, within the approximation of local thermodynamical equilibrium. Assuming that these potentials give an averaged description of node dynamics, we calculate thermal and mechanical properties. If this method can be sufficiently generalized it may form the basis of a Molecular Dynamics method with time and spatial coarse-graining.Comment: 4 pages, 4 figure

Action-derived molecular dynamics in the study of rare events

We present a practical method to generate classical trajectories with fixed initial and final boundary conditions. Our method is based on the minimization of a suitably defined discretized action. The method finds its most natural application in the study of rare events. Its capabilities are illustrated by non-trivial examples. The algorithm lends itself to straightforward parallelization, and when combined with molecular dynamics (MD) it promises to offer a powerful tool for the study of chemical reactions.Comment: 7 Pages, 4 Figures (3 in color), submitted to Phys. Rev. Let

Efficient Dynamic Importance Sampling of Rare Events in One Dimension

Exploiting stochastic path integral theory, we obtain \emph{by simulation} substantial gains in efficiency for the computation of reaction rates in one-dimensional, bistable, overdamped stochastic systems. Using a well-defined measure of efficiency, we compare implementations of ``Dynamic Importance Sampling'' (DIMS) methods to unbiased simulation. The best DIMS algorithms are shown to increase efficiency by factors of approximately 20 for a $5 k_B T$ barrier height and 300 for $9 k_B T$, compared to unbiased simulation. The gains result from close emulation of natural (unbiased), instanton-like crossing events with artificially decreased waiting times between events that are corrected for in rate calculations. The artificial crossing events are generated using the closed-form solution to the most probable crossing event described by the Onsager-Machlup action. While the best biasing methods require the second derivative of the potential (resulting from the ``Jacobian'' term in the action, which is discussed at length), algorithms employing solely the first derivative do nearly as well. We discuss the importance of one-dimensional models to larger systems, and suggest extensions to higher-dimensional systems.Comment: version to be published in Phys. Rev.

Improving rates of advanced care planning discussion and documentation in the primary care setting : a DNP quality improvement study

Background: Advance Care Planning (ACP) documents enable patients to receive medical care that aligns with treatment preferences and goals. Discussions regarding ACP in primary care are often inadequate due to patient and provider barriers. The lack of completed ACP documents leads to patient care goals not being addressed and ACP metrics not being met. Major themes in the literature demonstrated that multidisciplinary teams, workflow redesign, staff education, and the use of the Electronic Health Record (EHR) can aid in improving ACP discussion and documentation rates. Purpose: The purpose of this QI project was to improve the existing ACP processes for patients 50 years and older within our designated family medicine clinic by increasing discussion and documentation rates. Methods: The project was implemented in a family medicine clinic in an urban area over a 3 month time period. An ACP focused workflow was implemented defining specific roles and responsibilities for the team members. Pre and post intervention data was collected through the EHR dashboard for patients 50 years and older with and without existing ACP documents. Implementation: During staff meetings, clinic staff and providers were educated about new roles and responsibilities. The Making Choices Michigan Advance Directive form was made available to patients and providers. Staff addressed if a patient had an existing ACP and providers then discussed ACP with the patient. Both were documented in the EHR. The ACP form was given to interested patients to be filled out at home or in the office at a separate appointment with staff. Results: Project outcome goal of 30% increase in ACP discussion and documentation was not met. There was a slight increase in the percentage of 5.62%. No statistical change (p=0.16) was noticed when comparing pre-intervention rates of ACP CPT II code use, 1123F (80) and 1124F (41), with post-intervention CPT II code use, 1123F (66) and 1124F (26) after chi square test.Thesis (D.N.P.)--Michigan State University. Family Nurse Practitioner, 2023Includes bibliographical references (pages 31-35

Drug Burden Index is a Modifiable Predictor of 30-Day-Hospitalization in Community-Dwelling Older Adults with Complex Care Needs:Machine Learning Analysis of InterRAI Data

BACKGROUND: Older adults (≥ 65 years) account for a disproportionately high proportion of hospitalization and in-hospital mortality, some of which may be avoidable. Although machine learning (ML) models have already been built and validated for predicting hospitalization and mortality, there remains a significant need to optimise ML models further. Accurately predicting hospitalization may tremendously impact the clinical care of older adults as preventative measures can be implemented to improve clinical outcomes for the patient.METHODS: In this retrospective cohort study, a dataset of 14,198 community-dwelling older adults (≥ 65 years) with complex care needs from the Inter-Resident Assessment Instrument database was used to develop and optimise three ML models to predict 30-day-hospitalization. The models developed and optimized were Random Forest (RF), XGBoost (XGB), and Logistic Regression (LR). Variable importance plots were generated for all three models to identify key predictors of 30-day-hospitalization.RESULTS: The area under the receiver operating characteristics curve for the RF, XGB and LR models were 0.97, 0.90 and 0.72, respectively. Variable importance plots identified the Drug Burden Index and alcohol consumption as important, immediately potentially modifiable variables in predicting 30-day-hospitalization.CONCLUSIONS: Identifying immediately potentially modifiable risk factors such as the Drug Burden Index and alcohol consumption is of high clinical relevance. If clinicians can influence these variables, they could proactively lower the risk of 30-day-hospitalization. ML holds promise to improve the clinical care of older adults. It is crucial that these models undergo extensive validation through large-scale clinical studies before being utilized in the clinical setting.</p

Synergistic Effect of Ceftazidime-Avibactam with Aztreonam on Carbapenemase-Positive Klebsiella pneumoniae MBL+, NDM+

Mateusz Szyma&nacute;ski,1,2 Ma&lstrok;gorzata M Skiba,2 Ma&lstrok;gorzata Piasecka,2 Alina Olender3 1Human Anatomy Department, Medical University, Lublin, Poland; 2Intensive Care Unit, Stefan Cardinal Wyszy&nacute;ski District Specialist Hospital, Lublin, Poland; 3Chair and Department of Medical Microbiology, Medical University, Lublin, PolandCorrespondence: Ma&lstrok;gorzata M Skiba, Intensive Care Unit, Stefan Cardinal Wyszy&nacute;ski District Specialist Hospital, Al. Kra&sacute;nicka 100, Lublin, 20-718, Poland, Tel +48 81 537 46 60, Email [email protected]: The difficulties in attaining effective antibiotic therapy arising from the multidrug resistance of Gram-negative bacilli compel the exploration of new possibilities for synergistic interactions among existing antibiotics.Research Design and Methods: An analysis was conducted to assess the efficacy of two antibiotic therapy regimens in the treatment of infections caused by Klebsiella pneumoniae strains producing carbapenemases (MBL). Two patient groups were considered: Group A – individuals in whom the treatment of infection involved the application of ceftazidime-avibactam in combination with aztreonam. Group B comprised patients subjected to an alternative antibiotic therapy regimen.Results: In the group subjected to the treatment regimen involving ceftazidime-avibactam and aztreonam, as compared to alternative antibiotic combinations, a statistically lower mortality rate during the course of treatment and a faster clinical response to the administered therapy were evident.Conclusion: The results obtained may be applicable to routine in vitro assays performed and serve as valuable guidance for the potential utilization of the positive effect of antibiotic therapy through the synergy between ceftazidime-avibactam and aztreonam. The selection of antibiotics employed in the therapy of invasive infections caused by K. pneumoniae influences the ultimate treatment outcome.Keywords: synergism, ceftazidime-avibactam, aztreonam, multidrug-resistant K. pneumoniae, metal-beta-lactamase

Noncoding deletions reveal a gene that is critical for intestinal function.

Large-scale genome sequencing is poised to provide a substantial increase in the rate of discovery of disease-associated mutations, but the functional interpretation of such mutations remains challenging. Here we show that deletions of a sequence on human chromosome 16 that we term the intestine-critical region (ICR) cause intractable congenital diarrhoea in infants1,2. Reporter assays in transgenic mice show that the ICR contains a regulatory sequence that activates transcription during the development of the gastrointestinal system. Targeted deletion of the ICR in mice caused symptoms that recapitulated the human condition. Transcriptome analysis revealed that an unannotated open reading frame (Percc1) flanks the regulatory sequence, and the expression of this gene was lost in the developing gut of mice that lacked the ICR. Percc1-knockout mice displayed phenotypes similar to those observed upon ICR deletion in mice and patients, whereas an ICR-driven Percc1 transgene was sufficient to rescue the phenotypes found in mice that lacked the ICR. Together, our results identify a gene that is critical for intestinal function and underscore the need for targeted in vivo studies to interpret the growing number of clinical genetic findings that do not affect known protein-coding genes

Alternative Splicing Promotes Tumour Aggressiveness and Drug Resistance in African American Prostate Cancer.

linical challenges exist in reducing prostate cancer (PCa) disparities. The RNA splicing landscape of PCa across racial populations has not been fully explored as a potential molecular mechanism contributing to race-related tumour aggressiveness. Here, we identify novel genome-wide, race-specific RNA splicing events as critical drivers of PCa aggressiveness and therapeutic resistance in African American (AA) men. AA-enriched splice variants of PIK3CD, FGFR3, TSC2 and RASGRP2 contribute to greater oncogenic potential compared with corresponding European American (EA)-expressing variants. Ectopic overexpression of the newly cloned AA-enriched variant, PIK3CD-S, in EA PCa cell lines enhances AKT/mTOR signalling and increases proliferative and invasive capacity in vitro and confers resistance to selective PI3Kδ inhibitor, CAL-101 (idelalisib), in mouse xenograft models. High PIK3CD-S expression in PCa specimens associates with poor survival. These results highlight the potential of RNA splice variants to serve as novel biomarkers and molecular targets for developmental therapeutics in aggressive PCa