Mass distributions in a variational model

The time-dependent Hartree-Fock approach may be derived from a variational principle and a Slater Determinant wavefunction Ansatz. It gives a good description of nuclear processes in which one-body collisions dominate and has been applied with success to giant resonances and collisions around the barrier. It is inherently unable to give a good description of two-body observables. A variational principle, due to Balian and Veneroni has been proposed which can be geared to good reproduction of two-body observables. Keeping the Slater Determinant Ansatz, and restricting the two-body observables to be the squares of one-body observables, the procedure can be implemented as a modification of the time-dependent Hartree-Fock procedure. Applications, using the Skyrme effective interaction, are presented for the mass distributions of fragments following de-excitation of the giant dipole resonance in S-32. An illustration of the method's use in collisions is given.Comment: 5 pages, proceedings of XXXII Symposium on Nuclear Physics, Cocoyoc, Mexic

Mass dispersions from giant dipole resonances using the Balian-Veneroni variational approach

The Balian-Veneroni variational approach has been implemented using a 3-dimensional time-dependent Hartree-Fock (TDHF) code with realistic Skyrme interactions and used to investigate the mass dispersions from giant dipole resonances in S-32 and Sn-132 decaying through particle emission. The fluctuations obtained are shown to be quantitatively larger than the standard TDHF results.Comment: 6 Pages, 2 figure

Handheld ISFET Lab-on-Chip detection of TMPRSS2-ERG and AR mRNA for prostate cancer prognostics

Ion-sensitive field-effect transistors (ISFETs) in combination with unmodified complementary metal oxide semiconductors present a point-of-care platform for clinical diagnostics and prognostics. This work illustrates the sensitive and specific detection of two circulating mRNA markers for prostate cancer, the androgen receptor and the TMPRSS2-ERG fusion using a target-specific loop-mediated isothermal amplification method. TMPRSS2-ERG and androgen receptor RNA were detected down to 3x10 1 and 5x10 1 copies respectively in under 30 minutes. Administration of these assays onto the ISFET Lab-on-chip device was successful and the specificity of each marker was corroborated with mRNA extracted from prostate cancer cell lines

Classification of nucleic acid amplification on ISFET arrays using spectrogram-based neural networks.

The COVID-19 pandemic has highlighted a significant research gap in the field of molecular diagnostics. This has brought forth the need for AI-based edge solutions that can provide quick diagnostic results whilst maintaining data privacy, security and high standards of sensitivity and specificity. This paper presents a novel proof-of-concept method to detect nucleic acid amplification using ISFET sensors and deep learning. This enables the detection of DNA and RNA on a low-cost and portable lab-on-chip platform for identifying infectious diseases and cancer biomarkers. We show that by using spectrograms to transform the signal to the time-frequency domain, image processing techniques can be applied to achieve the reliable classification of the detected chemical signals. Transformation to spectrograms is beneficial as it makes the data compatible with 2D convolutional neural networks and helps gain significant performance improvement over neural networks trained on the time domain data. The trained network achieves an accuracy of 84% with a size of 30kB making it suitable for deployment on edge devices. This facilitates a new wave of intelligent lab-on-chip platforms that combine microfluidics, CMOS-based chemical sensing arrays and AI-based edge solutions for more intelligent and rapid molecular diagnostics

Mass Distributions Beyond TDHF

The mass distributions for giant dipole resonances in 32S and 132Sn decaying through particle emission and for deep-inelastic collisions between 16O nuclei have been investigated by implementing the Balian-Veneroni variational technique based upon a three-dimensional time-dependent Hartree-Fock code with realistic Skyrme interactions. The mass distributions obtained have been shown to be significantly larger than the standard TDHF results.Comment: 6 pages, 2 figures, Based on talk by J. M. A. Broomfield at the FUSION08 Conference, Chicago, September 22-26, 2008. Conference proceedings to be published by AI

Post-stroke emotionalism; diagnosis, pathophysiology, and treatment

Background: Post-stroke emotionalism affects one in five stroke sufferers 6 months after their stroke, but despite its frequency remains a poorly understood stroke symptom. The literature is limited, especially compared to other frequently observed neurological conditions such as aphasia and visual neglect. Aim and Methods: This narrative review presents a summary of the post-stroke emotionalism literature, to inform clinical practice and future research. We cover discussion of definitions, prevalence, neurobiology, predisposing and precipitating factors, and treatment. Results: Increasing evidence suggests that damage to specific areas functionally linked to emotion expression or regulation processes, disruption to structural pathways and those related to serotonin production and modulation individually or in concert give rise to emotionalism-type presentations. A range of emotionalism measurement tools have been used in research contexts making between study comparisons difficult. Testing for Emotionalism after Recent Stroke–Questionnaire (TEARS-Q) has recently been developed to allow standardized assessment. Treatment options are limited, and there have been few adequately powered treatment trials. Antidepressants may reduce severity, but more trial data are required. There have been no randomized-controlled trials of non-pharmacological interventions. Conclusions: More research is needed to improve recognition and treatment of this common and disabling symptom. We conclude with research priorities and recommendations for the field

Natural history of Duchenne muscular dystrophy in the United Kingdom: a descriptive study using the Clinical Practice Research Datalink

Background: Duchenne muscular dystrophy (DMD) is a rare, muscle-degenerative disease predominantly affecting males. Natural history models capture the full disease pathway under current care and combine with estimates of new interventions’ effects to assess cost-effectiveness by health technology decision-makers. These models require mortality estimates throughout a patient's lifetime, but rare disease datasets typically contain relatively few patients with short follow-ups. Alternative (published) sources of mortality data may therefore be required. Methods: The Clinical Practice Research Datalink (CPRD) was evaluated as a source of mortality and natural history data for future economic evaluations of health technologies for DMD and rare diseases in general in the UK population. This retrospective longitudinal cohort study provides flexible parametric estimates of mortality rates and survival probabilities in the current UK DMD population through primary/secondary records in the CPRD since 1990. It also investigates clinically significant milestones such as corticosteroid use, spinal surgery, and cardiomyopathy in these patients. Results: A total of 1121 male patients were included in the study, observed from 0.7 to 48.9 years. Median life expectancy was 25.64 years (95% confidence interval 24.73, 26.47), consistent with previous global estimates. This has improved to 26.47 (25.16, 27.89) years in patients born after 1990. The median ages at corticosteroid initiation, spinal surgery, ventilation, and cardiomyopathy diagnosis were 6.06 years (5.77, 6.29), 14.79 years (14.29, 15.09), 16.97 years (16.50, 18.31), and 15.26 years (14.22, 16.70), respectively. Conclusions: Estimates of mortality in UK-based DMD patients are age-specific in a uniquely large and nationally representative sample from the CPRD

Detection of YAP1 and AR-V7 mRNA for Prostate Cancer prognosis using an ISFET Lab-On-Chip platform

AbstractProstate cancer (PCa) is the second most common cause of male cancer-related death worldwide. The gold standard of treatment for advanced PCa is androgen deprivation therapy (ADT). However, eventual failure of ADT is common and leads to lethal metastatic castration resistant PCa (mCRPC). As such, the detection of relevant biomarkers in the blood for drug resistance in mCRPC patients could lead to personalized treatment options. mRNA detection is often limited by the low specificity of qPCR assays which are restricted to specialised laboratories. Here, we present a novel reversetranscription loop-mediated isothermal amplification (RT-LAMP) assay and have demonstrated its capability for sensitive detection of AR-V7 and YAP1 RNA (3×101 RNA copies per reaction). This work presents a foundation for the detection of circulating mRNA in PCa on a non-invasive Lab-on-chip (LoC) device for use at point-of-care. This technique was implemented onto a Lab-on-Chip platform integrating an array of chemical sensors (ion-sensitive field-effect transistors - ISFETs) for real-time detection of RNA. Detection of RNA presence was achieved through the translation of chemical signals into electrical readouts. Validation of this technique was conducted with rapid detection (&lt;15 min) of extracted RNA from prostate cancer cell lines 22Rv1s and DU145s.</jats:p