Derivation of the Verlinde Formula from Chern-Simons Theory and the G/G model

We give a derivation of the Verlinde formula for the $G_{k}$ WZW model from Chern-Simons theory, without taking recourse to CFT, by calculating explicitly the partition function $Z_{\Sigma\times S^{1}}$ of $\Sigma\times S^{1}$ with an arbitrary number of labelled punctures. By a suitable gauge choice, $Z_{\Sigma\times S^{1}}$ is reduced to the partition function of an Abelian topological field theory on $\Sigma$ (a deformation of non-Abelian BF and Yang-Mills theory) whose evaluation is straightforward. This relates the Verlinde formula to the Ray-Singer torsion of $\Sigma\times S^{1}$. We derive the $G_{k}/G_{k}$ model from Chern-Simons theory, proving their equivalence, and give an alternative derivation of the Verlinde formula by calculating the $G_{k}/G_{k}$ path integral via a functional version of the Weyl integral formula. From this point of view the Verlinde formula arises from the corresponding Jacobian, the Weyl determinant. Also, a novel derivation of the shift k\ra k+h is given, based on the index of the twisted Dolbeault complex.Comment: 47 pages (in A4 format), LaTex file, (original was truncated by the mailer - apologies, m.b.), IC/93/8

From wellness to medical diagnostic apps: the Parkinson's Disease case

This paper presents the design and development of the CloudUPDRS app and supporting system developed as a Class I medical device to assess the severity of motor symptoms for Parkinson’s Disease. We report on lessons learnt towards meeting fidelity and regulatory requirements; effective procedures employed to structure user context and ensure data quality; a robust service provision architecture; a dependable analytics toolkit; and provisions to meet mobility and social needs of people with Parkinson’s

The cloudUPDRS app: a medical device for the clinical assessment of Parkinson's Disease

Parkinson's Disease is a neurological condition distinguished by characteristic motor symptoms including tremor and slowness of movement. To enable the frequent assessment of PD patients, this paper introduces the cloudUPDRS app, a Class I medical device that is an active transient non-invasive instrument, certified by the Medicines and Healthcare products Regulatory Agency in the UK. The app follows closely Part III of the Unified Parkinson's Disease Rating Scale which is the most commonly used protocol in the clinical study of PD; can be used by patients and their carers at home or in the community unsupervised; and, requires the user to perform a sequence of iterated movements which are recorded by the phone sensors. The cloudUPDRS system addresses two key challenges towards meeting essential consistency and efficiency requirements, namely: (i) How to ensure high-quality data collection especially considering the unsupervised nature of the test, in particular, how to achieve firm user adherence to the prescribed movements; and (ii) How to reduce test duration from approximately 25 minutes typically required by an experienced patient, to below 4 minutes, a threshold identified as critical to obtain significant improvements in clinical compliance. To address the former, we combine a bespoke design of the user experience tailored so as to constrain context, with a deep learning approach based on Recurrent Convolutional Neural Networks, to identify failures to follow the movement protocol. We address the latter by developing a machine learning approach to personalize assessments by selecting those elements of the test that most closely match individual symptom profiles and thus offer the highest inferential power, hence closely estimating the patent's overall score

The CloudUPDRS smartphone software in Parkinson’s study: cross-validation against blinded human raters

Digital assessments of motor severity could improve the sensitivity of clinical trials and personalise treatment in Parkinson’s disease (PD) but have yet to be widely adopted. Their ability to capture individual change across the heterogeneous motor presentations typical of PD remains inadequately tested against current clinical reference standards. We conducted a prospective, dual-site, crossover-randomised study to determine the ability of a 16-item smartphone-based assessment (the index test) to predict subitems from the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale part III (MDS-UPDRS III) as assessed by three blinded clinical raters (the reference-standard). We analysed data from 60 subjects (990 smartphone tests, 2628 blinded video MDS-UPDRS III subitem ratings). Subject-level predictive performance was quantified as the leave-one-subject-out cross-validation (LOSO-CV) accuracy. A pre-specified analysis classified 70.3% (SEM 5.9%) of subjects into a similar category to any of three blinded clinical raters and was better than random (36.7%; SEM 4.3%) classification. Post hoc optimisation of classifier and feature selection improved performance further (78.7%, SEM 5.1%), although individual subtests were variable (range 53.2–97.0%). Smartphone-based measures of motor severity have predictive value at the subject level. Future studies should similarly mitigate against subjective and feature selection biases and assess performance across a range of motor features as part of a broader strategy to avoid overly optimistic performance estimates

Συμβολή στη μελέτη του ειδικού προστατικού αντιγόνου ως δείκτη πρόληψης, έγκαιρης διάγνωσης και παρακολούθησης των παθήσεων του προστάτη

The aim of thiw study is to evaluate the usefulness of prostate specific antigen (PSA) in the early detection of prostatic cancer and to assess the effect of transurethral resection of the prostate (TUR-P) versus open prostatectomy (OP) on the serum PSA concentration, in patients with histologically confirmed benign prostatic hyperplasia (BPH) and determine the time required for the serum PSA level greater than 4.0 ng/ml, underwent both digital rectal examination (DRE) and transrectal ultrasound (TRUS). Ultrasound guided prostate biopsies were performed in the men with abnormal findings on DRE, TRUS or both. Serum PSA value 4.1-10.0 ng/ml and 18 (2.4%) had a PSA value >10.0 ng /ml. A total of 16 carcinomas (41%) was detected in 39 men who had ultrasound guided prostate biopsies. If DRE alone had been used to screen the men whohad cancer, 5 of the 16 (31.2%) would have been missed. We also studied 53 patients with obstuctive benign prostatic hyperplasia scheduled for transurethral resection of the prostate (TUR-P, 35 patients) or open prostatectomy (OP, 18 patients). The serum PSA concentration was measured before and immediately after the procedure on days 1, 3, 5, 7 after the operation, at 3-4 days intervalsfor three weeks or longer and 3 months after prostatectomy. Statistical analysis was made by ANOVA one way with Student's t-test where appropriate with statistical significance at 5% level. The main pre-procedure PSA value of the TUR-P group was a significant PSA rise (102.68 ng/ml), but in the OP group the rise was minimal (14.04ng/ml).Ο σκοπός της παρούσας διατριβής είναι να διαπιστωθεί η αξία του ειδικού προστατικού αντιγόνου (prostate specific antigen, SPA)στην πρώιμη ανίχνευση του καρκίνου του προστάτη, στα πλαίσια μαζικής εξέτασης φαινομενικά υγιών ανδρών και επίσης να μελετηθεί ο ρυθμός μεταβολής των επιπέδων του PSA στον ορό μετά τη διουρηθρική και ανοιχτή προστατεκτομή, σε ασθενείς με ιστολογικά επιβεβαιωμένη καλοήθη υπερπλασία του προστάτη (ΚΥΠ). Σε 745 ασυμπτωτικούς άνδρες με ηλικία πάνω από 50 έτη έγινε προσδιοριδμός του PSA στον ορό. Οι άνδρες με τιμή του PSA >4.0 ng/ml, υποβλήθηκαν σε δακτυλική εξέταση του προστάτη και σε διορθικό υπερηχοτομογράφημα και στη συνέχεια σε κατευθυνόμενη με υπερήχους βιιοψία του προστάτη, αν οι παραπάνω εξετάσεις ήταν ύποπτες για κακοήθεια. Επίσης μελετήθηκαν 53 ασθενείς με ΚΥΠ, από τους οποίους οι 35 (66%) υποβλήθηκαν σε διουρηθρική (ομάδα 2). Το PSA προσδιορίστηκε σε όλους τους ασθενείς πρίν και αμέσως μετά από την χειρουργική επέμβαση. Στη συνέχεια ελήφθησαν διαδοχικές τιμές του PSA την 1η, 3η, 5η, 7η μετεγχειρητική ημέρα, κατόπιν σε διάστημα 3-4 ημερών για χρονικό διάστημα μεγαλύτερο των 3 εβδομάδων και τέλος μετά την προστατεκτομή. Η στατιστική αξιολόγηση των δεδομένων έγινε με ανάλυση μεταβλητότητας (ANOVA) και στη συνέχεια με τη δοκιμασία Student's "t". Επίπεδο στατιστικής σημαντικότητας εθεωρήθηκε το 0.05 (Ρ4.0 ng/ml. Από αυτούς τους άνδρες, οι 38 (5.1 %) είχαν τιμή PSA μεταξύ 4.1ng/ml και 10.0ng/ml ενώ οι 18 (2.4%) είχαν τιμή μεγαλύτερη από 10.0 ng/ml

Absence of Mucosa-Associated Colonic Helicobacters in an Australian Urban Population

Application of nested PCR for Helicobacter species to 416 samples obtained at colonoscopy from 15 patients with Crohn's disease, 12 with ulcerative colitis, and 43 controls revealed H. pylori DNA in only 6 individuals with no disease association. No other Helicobacter species were detected in ileal or colonic samples

The Association of Mycobacterium avium subsp. paratuberculosis with Inflammatory Bowel Disease.

The association of Mycobacterium avium subspecies paratuberculosis (M. paratuberculosis) with Crohn's disease is a controversial issue. M. paratuberculosis is detected by amplifying the IS900 gene, as microbial culture is unreliable from humans. We determined the presence of M. paratuberculosis in patients with Crohn's disease (CD) (n = 22), ulcerative colitis (UC) (n = 20), aphthous ulcers (n = 21) and controls (n = 42) using PCR assays validated on bovine tissue. Culture from human tissue was also performed. M. paratuberculosis prevalence in the CD and UC groups was compared to the prevalence in age and sex matched non-inflammatory bowel disease controls. Patients and controls were determined to be M. paratuberculosis positive if all three PCR assays were positive. A significant association was found between M. paratuberculosis and Crohn's disease (p = 0.02) that was not related to age, gender, place of birth, smoking or alcohol intake. No significant association was detected between M. paratuberculosis and UC or aphthous ulcers; however, one M. paratuberculosis isolate was successfully cultured from a patient with UC. We report the resistance of this isolate to ethambutol, rifampin, clofazamine and streptomycin. Interestingly this isolate could not only survive but could grow slowly at 5°C. We demonstrate a significant association between M. paratuberculosis and CD using multiple pre-validated PCR assays and that M. paratuberculosis can be isolated from patients with UC

Deep learning Parkinson's from smartphone data

The cloudUPDRS app is a Class I medical device, namely an active transient non-invasive instrument, certified by the Medicines and Healthcare products Regulatory Agency in the UK for the clinical assessment of the motor symptoms of Parkinson's Disease. The app follows closely the Unified Parkinson's Disease Rating Scale which is the most commonly used protocol in the clinical study of PD; can be used by patients and their carers at home or in the community; and, requires the user to perform a sequence of iterated movements which are recorded by the phone sensors. This paper discusses how the cloudUPDRS system addresses two key challenges towards meeting essential consistency and efficiency requirements, namely: (i) How to ensure high-quality data collection especially considering the unsupervised nature of the test, in particular, how to achieve firm user adherence to the prescribed movements; and (ii) How to reduce test duration from approximately 25 minutes typically required by an experienced patient, to below 4 minutes, a threshold identified as critical to obtain significant improvements in clinical compliance. To address the former, we combine a bespoke design of the user experience tailored so as to constrain context, with a deep learning approach used to identify failures to follow the movement protocol while at the same time limiting false positives to avoid unnecessary repetition. We address the latter by developing a machine learning approach to personalise assessments by selecting those elements of the UPDRS protocol that most closely match individual symptom profiles and thus offer the highest inferential power hence closely estimating the patent's overall UPRDS score