A novel method for dipper/non-dipper pattern classification in hypertensive and non-diabetic patients

Before clinical islet transplantation can become an effective and reliable treatment for type 1 diabetic patients, there must be significant improvements in the methods employed for the isolation of islets of Langerhans. We have developed an automated cell extraction system (ACES), which allows computer control of the isolation process. As well, it incorporates a novel method of recombining dissociated pancreatic tissue. Following initial system design and testing to determine the optimal system configuration, a series of 12 consecutive canine islet isolations were performed. Pancreases were perfused with collagenase via the duct and dissociated and recombined using either the standard Ricordi-based protocol (group 1, n = 6) or dissociated and recombined using the ACES system (group 2, n = 6). A total of 90.8 ± 21 x 103 islet equivalents (IE) (mean ± SEM) were recovered in group 1 vs. 99 ± 14 x 103 IE in group 2 (p = NS, student unpaired t-test). Following Ficoll purification the recovery was 56.2 ± 14 x 103 IE for group 1 vs. 54.7 ± 11 x 103 IE for group 2 (p = NS). Viability was equivalent with an 8.6-fold increase in insulin secretion for group 1 and an 8.8-fold increase for group 2 when the islets were exposed to high glucose solution supplemented with IBMX (3-isobutyl-1-methylxanthine) during static incubation. In vivo function was equivalent following transplantation of 2000 IE under the kidney capsule of alloxan-induced diabetic nude mice with five of six and five of seven mice surviving long-term (>50 days posttransplant) (groups 1 and 2, respectively). This data shows that an entirely automated pancreatic islet extraction system can result in effective canine islet recovery without compromising islet yields and viability. The ACES system has several ad van tages over the standard isolation protocol. These include: 1) computer control and monitoring over all phases of the isolation, 2) a single-use sterile disposable tubing set, and 3) a novel method of tissue recombination. Copyright © 1997 Elsevier Science Inc.

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A Kernel Based Neighborhood Discriminant Submanifold Learning for Pattern Classification

Journal of Applied Mathematics ◽

10.1155/2014/950349 ◽

2014 ◽

Vol 2014 ◽

pp. 1-10

Author(s):

Xu Zhao

Keyword(s):

Discriminant Analysis ◽

Pattern Classification ◽

General Model ◽

Original Data ◽

Face Database ◽

Kernel Space ◽

Criterion Function ◽

Locality Preserving ◽

Novel Method ◽

Class Representation

We propose a novel method, called Kernel Neighborhood Discriminant Analysis (KNDA), which can be regarded as a supervised kernel extension of Locality Preserving Projection (LPP). KNDA nonlinearly maps the original data into a kernel space in which two graphs are constructed to depict the within-class submanifold and the between-class submanifold. Then a criterion function which minimizes the quotient between the within-class representation and the between-class representation of the submanifolds is designed to separate each submanifold constructed by each class. The real contribution of this paper is that we bring and extend the submanifold based algorithm to a general model and by some derivation a simple result is given by which we can classify a given object to a predefined class effectively. Experiments on the MNIST Handwritten Digits database, the Binary Alphadigits database, the ORL face database, the Extended Yale Face Database B, and a downloaded documents dataset demonstrate the effectiveness and robustness of the proposed method.

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Glycemic deviation index: a novel method of integrating glycemic numerical value and variability

BMC Endocrine Disorders ◽

10.1186/s12902-021-00691-z ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yizhou Zou ◽

Wanli Wang ◽

Dongmei Zheng ◽

Xu Hou

Keyword(s):

Blood Glucose ◽

Glucose Monitoring ◽

Glycemic Variability ◽

Blood Glucose Monitoring ◽

Diabetic Patients ◽

Glucose Levels ◽

Blood Glucose Levels ◽

Deviation Index ◽

Multiple Characteristics ◽

Novel Method

Abstract Background There are many continuous blood glucose monitoring (CGM) data-based indicators, and most of these focus on a single characteristic of abnormal blood glucose. An ideal index that integrates and evaluates multiple characteristics of blood glucose has not yet been established. Methods In this study, we proposed the glycemic deviation index (GDI) as a novel integrating characteristic, which mainly incorporates the assessment of the glycemic numerical value and variability. To verify its effectiveness, GDI was applied to the simulated 24 h glycemic profiles and the CGM data of type 2 diabetes (T2D) patients (n = 30). Results Evaluation of the GDI of the 24 h simulated glycemic profiles showed that the occurrence of hypoglycemia was numerically the same as hyperglycemia in increasing GDI. Meanwhile, glycemic variability was added as an independent factor. One-way ANOVA results showed that the application of GDI showed statistically significant differences in clinical glycemic parameters, average glycemic parameters, and glycemic variability parameters among the T2D groups with different glycemic levels. Conclusions In conclusion, GDI integrates the characteristics of the numerical value and the variability in blood glucose levels and may be beneficial for the glycemic management of diabetic patients undergoing CGM treatment.

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METHOD OF KEY VECTORS EXTRACTION USING R-CLOUD CLASSIFIERS

New Mathematics and Natural Computation ◽

10.1142/s1793005707000884 ◽

2007 ◽

Vol 03 (03) ◽

pp. 419-426

Author(s):

ANTON BOUGAEV ◽

ALEKSEY URMANOV ◽

LEFTERI TSOUKALAS ◽

KENNY GROSS

Keyword(s):

Pattern Classification ◽

Training Data ◽

New Method ◽

Classification Method ◽

Data Set ◽

Cloud Classification ◽

Data Vector ◽

Engineering Problems ◽

Nonparametric Classification ◽

Novel Method

A novel method for reducing a training data set in the context of nonparametric classification is proposed. The new method is based on the method of R-clouds. The advantages of the R-cloud classification method introduced recently are being investigated. The separating boundary of the R-cloud classifier is represented using Rvachev functions. The method of key vectors extraction uses the value of the R-cloud function to quantify the disturbance of the separating boundary, which is caused by removal of one data vector from the design dataset. The R-cloud method was found instructive and practical in a number of engineering problems related to pattern classification.

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Novel method to determine diagnosis-defining refraction points

10.1101/649442 ◽

2019 ◽

Author(s):

Tsuneto Yamauchi ◽

Mitsuhiro Ohshima ◽

Yoko Yamaguchi ◽

Kazunori Konishi ◽

Kai Kappert ◽

...

Keyword(s):

Laboratory Tests ◽

Diabetic Patients ◽

Reference Ranges ◽

Test Results ◽

Mathematical Methods ◽

Distribution Of Values ◽

Clinical Diagnoses ◽

Novel Method ◽

The Mean ◽

Data Sorting

AbstractDiagnosis of a certain disease generally relies on definitions established by professional medical societies and comprise the patient’s history, physical examination, and test results. These include physical compositions such as body mass index (BMI), and laboratory tests such as serum creatinine and albumin in urine samples. In general, laboratory tests are based on mathematical methods,e.g.defining critical values from the mean ± kσ of a population, where k is a natural number and the standard deviation is σ (“mean ± kσ-method”). In most cases k is defined as 2, leading to reference ranges defining 95% of test results as normal. However, this method mostly depends on a normal distribution of values.Here we applied a novel method (“SoFR-method”) based on data sorting to define refraction points, which carry informative value as diagnostic criteria. Applying the SoFR-method, standard measures such as critical BMI-values are categorized by equal robustness as by the mean ± kσ-method. However, the SoFR-method showed higher validity when analyzing non-normalized values such as creatinine and albumin, as well as hepatocyte growth factor (HGF) and hemoglobin in a novel Perioscreen assay in saliva of diabetic and non-diabetic patients.Taken together, we defined a novel method based on data sorting of test results from patients to effectively define refraction points which might guide more accurately clinical diagnoses and define relevant thresholds.

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Comparison low-density lipoprotein cholesterol levels calcutation using the novel method by Martin vs the Friedewald equation in type 2 diabetic patients

Endocrine Abstracts ◽

10.1530/endoabs.41.ep218 ◽

2016 ◽

Author(s):

Sequeira Duarte ◽

Jorge Azinheira

Keyword(s):

Low Density Lipoprotein ◽

Density Lipoprotein ◽

Diabetic Patients ◽

The Novel ◽

Type 2 Diabetic Patients ◽

Cholesterol Levels ◽

Friedewald Equation ◽

Novel Method ◽

Type 2 Diabetic

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The removal and morphology of intact biofilms from implanted venous access devices

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100141470 ◽

1995 ◽

Vol 53 ◽

pp. 1020-1021

Author(s):

M.A. Gregory ◽

G.P. Hadley

Keyword(s):

Patient Selection ◽

Surgical Oncology ◽

Venous Access ◽

Common Procedure ◽

Indwelling Catheters ◽

Careful Patient ◽

Novel Method ◽

The Subject ◽

Vascular Catheters ◽

Venous Access Devices

The insertion of implanted venous access systems for children undergoing prolonged courses of chemotherapy has become a common procedure in pediatric surgical oncology. While not permanently implanted, the devices are expected to remain functional until cure of the primary disease is assured. Despite careful patient selection and standardised insertion and access techniques, some devices fail. The most commonly encountered problems are colonisation of the device with bacteria and catheter occlusion. Both of these difficulties relate to the development of a biofilm within the port and catheter. The morphology and evolution of biofilms in indwelling vascular catheters is the subject of ongoing investigation. To date, however, such investigations have been confined to the examination of fragments of biofilm scraped or sonicated from sections of catheter. This report describes a novel method for the extraction of intact biofilms from indwelling catheters.15 children with Wilm’s tumour and who had received venous implants were studied. Catheters were removed because of infection (n=6) or electively at the end of chemotherapy.

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Intramuscular Nerve and Neuromuscular Junction Alteration In Extraocular Muscles of Diabetic Mice

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100120102 ◽

1985 ◽

Vol 43 ◽

pp. 682-683

Author(s):

Bruce R. Pachter

Keyword(s):

Diabetes Mellitus ◽

Peripheral Nerves ◽

Sudden Onset ◽

Extraocular Muscles ◽

Diabetic Patients ◽

Oculomotor Palsy ◽

Third Nerve Palsy ◽

Patients With Diabetes ◽

Intramuscular Nerve ◽

Oculomotor Nerves

Diabetes mellitus is one of the commonest causes of neuropathy. Diabetic neuropathy is a heterogeneous group of neuropathic disorders to which patients with diabetes mellitus are susceptible; more than one kind of neuropathy can frequently occur in the same individual. Abnormalities are also known to occur in nearly every anatomic subdivision of the eye in diabetic patients. Oculomotor palsy appears to be common in diabetes mellitus for their occurrence in isolation to suggest diabetes. Nerves to the external ocular muscles are most commonly affected, particularly the oculomotor or third cranial nerve. The third nerve palsy of diabetes is characteristic, being of sudden onset, accompanied by orbital and retro-orbital pain, often associated with complete involvement of the external ocular muscles innervated by the nerve. While the human and experimental animal literature is replete with studies on the peripheral nerves in diabetes mellitus, there is but a paucity of reported studies dealing with the oculomotor nerves and their associated extraocular muscles (EOMs).

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