Search

Your search keyword '"Joseph Gleeson"' showing total 10 results
Start Over Author "Joseph Gleeson" Search Limiters Full Text
10 results on '"Joseph Gleeson"'

1. Accuracy of ultrasound, magnetic resonance imaging and intraoperative frozen section in the diagnosis of ovarian tumours: data from a London tertiary centre

Author

Sian Mitchell, Joseph Gleeson, Mansi Tiwari, Frances Bailey, Jonathan Gaughran, Gautam Mehra, Mustafa Zelal Muallem, and Ahmad Sayasneh

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Ovarian cancer has the worst prognosis among all gynaecological cancers. The pre-operative and intraoperative diagnosis of ovarian tumours is imperative to ensure the right operation is performed and to improve patients’ outcomes. Methodology A retrospective review of cases with a confirmed histological diagnosis of ovarian cases was undertaken from January 2017 to December 2021. Comparison was undertaken between this final diagnosis and the pre-operative ultrasound, MRI and frozen section (FS) to assess diagnostic accuracy of each. In the ultrasound cases, the level of the examiner was collected. Statistical analysis was performed using Stata MP v17.0 software (USA, 2023). Results In total, 156 ovarian masses were examined by FS. In the histopathological examination, 123/156 of these tumours were epithelial tumours. Pre-operative US subjective impression was made in 63/156 cases and preoperative MRI subjective impression was made in 129/156 cases. For benign, borderline and malignant tumours, FS demonstrated a sensitivity of 90.8% (95%CI:81.9–96.2), 86.8% (95%CI:71.9–95.6) and 97.6% (95%CI:87.4–99.9) respectively. Ultrasound’s sensitivities were 95.2% (95%CI:76.2–99.9), 20% (95%:4.33–48.1), 57.1% (95%CI:28.9–82.3) and MRI’s sensitivities were 100% (95%CI:80.5–100), 31.5% (95%CI:19.5–45.6) and 63.2% (95%CI:46–78.2) respectively. Conclusions FS remains an accurate tool for diagnosing ovarian malignancy. However, across both imaging modalities and FS, the diagnosis of borderline ovarian tumours remains challenging.

Published
2024
Full Text
View/download PDF

2. Clinician-centric diagnosis of rare genetic diseases: performance of a gene pertinence metric in decision support for clinicians

Author

Michael M. Segal, Renee George, Peter Waltman, Ayman W. El-Hattab, Kiely N. James, Valentina Stanley, and Joseph Gleeson

Subjects
Rare disease diagnosis, Diagnostic decision support system, Artificial intelligence, Genomic analysis, Copy number variation, Medicine
Abstract

Abstract Background In diagnosis of rare genetic diseases we face a decision as to the degree to which the sequencing lab offers one or more diagnoses based on clinical input provided by the clinician, or the clinician reaches a diagnosis based on the complete set of variants provided by the lab. We tested a software approach to assist the clinician in making the diagnosis based on clinical findings and an annotated genomic variant table, using cases already solved using less automated processes. Results For the 81 cases studied (involving 216 individuals), 70 had genetic abnormalities with phenotypes previously described in the literature, and 11 were not described in the literature at the time of analysis (“discovery genes”). These included cases beyond a trio, including ones with different variants in the same gene. In 100% of cases the abnormality was recognized. Of the 70, the abnormality was ranked #1 in 94% of cases, with an average rank 1.1 for all cases. Large CNVs could be analyzed in an integrated analysis, performed in 24 of the cases. The process is rapid enough to allow for periodic reanalysis of unsolved cases. Conclusions A clinician-friendly environment for clinical correlation can be provided to clinicians who are best positioned to have the clinical information needed for this interpretation.

Published
2020
Full Text
View/download PDF

3. Lidocaine Ineffectiveness Suggests New Psychopharmacology Drug Target

Author

Mark, Mintz, Victor, Badner, Lynn K, Feldman, Pnina, Mintz, Mana, Saraghi, Jonathan, Diaz, Irina, Mezhebovsky, Irene, Axelrod, Joseph, Gleeson, Chang, Liu, Cathy, Smith, Helen, Chow, David, Zurakowski, and Michael M, Segal

Subjects
Premenstrual Syndrome, Double-Blind Method, Psychopharmacology, Humans, Lidocaine, Female, Premenstrual Dysphoric Disorder, Personality, Original Research
Abstract

OBJECTIVES: The mechanism of many neuropsychiatric disorders remains unknown, but the ineffectiveness of the sodium channel blocker lidocaine has been suggested to be a biomarker for Attention Deficit Hyperactivity Disorder (ADHD) and a severe form of Premenstrual Syndrome (PMS) that is considered psychiatric. We conducted single-arm double-blind clinical trials to test whether lidocaine ineffectiveness can be used as a biomarker to identify people with these conditions and provide a clue as to the molecular mechanism and potential psychopharmacological intervention. EXPERIMENTAL DESIGN: We developed a noninvasive taste test for lidocaine ineffectiveness, validated by comparing lidocaine injections to pain testing in 12 subjects, and assessed it in individuals with ADHD and PMS. PRINCIPAL OBSERVATIONS: Lidocaine ineffectiveness had a strong association in women with ADHD + PMS in a sample of 53 subjects and controls (p < 0.001). CONCLUSIONS: These results suggest the possibility of the biological understanding of the combination of ADHD and PMS that is characteristic of the psychiatric disorder Premenstrual Dysphoric Disorder (PMDD). These results and comparison to family pedigrees of a neuromuscular channelopathy with overlapping symptoms suggest the possibility that the clinical phenotype in PMDD is produced by sensory overstimulation, and amenable to molecular understanding and treatment.

Published
2023

7. Optimal design of advanced drop-in hydrocarbon biofuel supply chain integrating with existing petroleum refineries under uncertainty

Author

Kailiang Tong, Michael Joseph Gleeson, Gang Rong, and Fengqi You

Subjects
Renewable Energy, Sustainability and the Environment, business.industry, Supply chain, Oil refinery, Forestry, Refinery, Production planning, Petroleum product, Biofuel, Bioenergy, Capital cost, Environmental science, Biochemical engineering, business, Waste Management and Disposal, Agronomy and Crop Science
Abstract

This paper addresses the optimal design of an advanced hydrocarbon biofuel supply chain integrated with existing petroleum refineries. Three major insertion points from the biofuel supply chain to the petroleum refineries are investigated and analyzed, including bio-intermediates co-processed with crude oil, bio-intermediates co-processed with refinery intermediates, and finished biofuels blended with conventional petroleum products. A multiperiod, mixed-integer linear programming model is proposed that accounts for diverse conversion pathway, technology, and insertion point selections, biomass seasonality, geographical diversity, biomass degradation, demand distribution and government incentives. This model simultaneously optimizes the supply chain design, insertion point selection, and production planning. In addition, the conversion rate, operation cost associated with insertion points in petroleum refinery, as well as the biomass availability and product demand are modeled as fuzzy numbers to account for the data uncertainty. A fuzzy possibilistic programming approach is applied to this model, where possibility, necessity and credibility measures are adopted according to the decision makers' preference. This model is illustrated by the county level case study of Illinois. Compared to traditional biofuel supply chains, advanced hydrocarbon biofuel supply chain integrating with existing petroleum refinery infrastructure significantly reduces capital cost and total annualized cost.

Published
2014
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results