Longitudinal Studies of Wearables in Patients with Diabetes: Key Issues and Solutions.

Glucose monitoring is key to the management of diabetes mellitus to maintain optimal glucose control whilst avoiding hypoglycemia. Non-invasive continuous glucose monitoring techniques have evolved considerably to replace finger prick testing, but still require sensor insertion. Physiological variables, such as heart rate and pulse pressure, change with blood glucose, especially during hypoglycemia, and could be used to predict hypoglycemia. To validate this approach, clinical studies that contemporaneously acquire physiological and continuous glucose variables are required. In this work, we provide insights from a clinical study undertaken to study the relationship between physiological variables obtained from a number of wearables and glucose levels. The clinical study included three screening tests to assess neuropathy and acquired data using wearable devices from 60 participants for four days. We highlight the challenges and provide recommendations to mitigate issues that may impact the validity of data capture to enable a valid interpretation of the outcomes.

Cardiovascular autonomic neuropathy is associated with increased glycemic variability driven by hyperglycemia rather than hypoglycemia in patients with diabetes.

AIM: Cardiac autonomic neuropathy (CAN) has been suggested to be associated with hypoglycemia and impaired hypoglycemia unawareness. We have assessed the relationship between CAN and extensive measures of glucose variability (GV) in patients with type 1 and type 2 diabetes. METHODS: Participants with diabetes underwent continuous glucose monitoring (CGM) to obtain measures of GV and the extent of hyperglycemia and hypoglycemia and cardiovascular autonomic reflex testing. RESULTS: Of the 40 participants (20 T1DM and 20 T2DM) (aged 40.70 ± 13.73 years, diabetes duration 14.43 ± 7.35 years, HbA1c 8.85 ± 1.70%), 23 (57.5%) had CAN. Despite a lower coefficient of variation (CV) (31.26 ± 11.87 vs. 40.33 ± 11.03, P = 0.018), they had a higher CONGA (8.42 ± 2.58 vs. 6.68 ± 1.88, P = 0.024) with a lower median LBGI (1.60 (range: 0.20-3.50) vs. 4.90 (range: 3.20-7.40), P = 0.010) and percentage median time spent in hypoglycemia (4 (range:4-13) vs. 1 (range:0-5), P = 0.008), compared to those without CAN. The percentage GRADEEuglycemia (3.30 ± 2.78 vs. 5.69 ± 3.09, P = 0.017) and GRADEHypoglycemia (0.3 (range: 0 - 3.80) vs. 1.8 (range: 0.9-6.5), P = 0.036) were significantly lower, while the percentage median GRADEHyperglycemia (95.45 (range:93-98) vs. 91.6 (82.8-95.1), P = 0.013) was significantly higher in participants with CAN compared to those without CAN. CONCLUSION: CAN was associated with increased glycemic variability with less time in euglycemia attributed to a greater time in hyperglycemia but not hypoglycemia.

Continuous glucose monitoring reveals a novel association between duration and severity of hypoglycemia, and small nerve fiber injury in patients with diabetes.

Objective: Continuous glucose monitoring (CGM) has revealed that glycemic variability and low time in range are associated with albuminuria and retinopathy. We have investigated the relationship between glucose metrics derived from CGM and a highly sensitive measure of neuropathy using corneal confocal microscopy in participants with type 1 and type 2 diabetes. Methods: A total of 40 participants with diabetes and 28 healthy controls underwent quantification of corneal nerve fiber density (CNFD), corneal nerve branch density (CNBD), corneal nerve fiber length (CNFL) and inferior whorl length (IWL) and those with diabetes underwent CGM for four consecutive days. Results: CNBD was significantly lower in patients with high glycemic variability (GV) compared to low GV (median (range) (25.0 (19.0-37.5) vs 38.6 (29.2-46.9); P = 0.007); in patients who spent >4% compared to <4% time in level 1 hypoglycemia (54-69 mg/dL) (25.0 (22.9-37.5) vs 37.5 (29.2-46.9); P = 0.045) and in patients who spent >1% compared to <1% time in level 2 hypoglycemia (<54 mg/dL) (25.0 (19.8-41.7) vs 35.4 (28.1-44.8); P = 0.04). Duration in level 1 hypoglycemia correlated with CNBD (r = -0.342, P = 0.031). Duration in level 1 (181-250 mg/dL) and level 2 (>250 mg/dL) hyperglycemia did not correlate with CNFD (P > 0.05), CNBD (P > 0.05), CNFL (P > 0.05) or IWL (P > 0.05). Conclusions: Greater GV and duration in hypoglycemia, rather than hyperglycemia, are associated with nerve fiber loss in diabetes.

Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection.

Diabetes mellitus is characterized by elevated blood glucose levels, however patients with diabetes may also develop hypoglycemia due to treatment. There is an increasing demand for non-invasive blood glucose monitoring and trends detection amongst people with diabetes and healthy individuals, especially athletes. Wearable devices and non-invasive sensors for blood glucose monitoring have witnessed considerable advances. This review is an update on recent contributions utilizing novel sensing technologies over the past five years which include electrocardiogram, electromagnetic, bioimpedance, photoplethysmography, and acceleration measures as well as bodily fluid glucose sensors to monitor glucose and trend detection. We also review methods that use machine learning algorithms to predict blood glucose trends, especially for high risk events such as hypoglycemia. Convolutional and recurrent neural networks, support vector machines, and decision trees are examples of such machine learning algorithms. Finally, we address the key limitations and challenges of these studies and provide recommendations for future work.

Breath Analysis for the In Vivo Detection of Diabetic Ketoacidosis.

Human breath analysis of volatile organic compounds has gained significant attention recently because of its rapid and noninvasive potential to detect various metabolic diseases. The detection of ketones in the breath and blood is key to diagnosing and managing diabetic ketoacidosis (DKA) in patients with type 1 diabetes. It may also be of increasing importance to detect euglycemic ketoacidosis in patients with type 1 or type 2 diabetes or heart failure, treated with sodium-glucose transporter-2 inhibitors (SGLT2-i). The present research evaluates the efficiency of colorimetry for detecting acetone and ethanol in exhaled human breath with the response time, pH effect, temperature effect, concentration effect, and selectivity of dyes. Using the proposed multidye system, we obtained a detection limit of 0.0217 ppm for acetone and 0.029 ppm for ethanol in the detection range of 0.05-50 ppm. A smartphone-assisted unit consisting of a portable colorimetric device was used to detect relative red/green/blue values within 60 s of the interface for practical and real-time application. The developed method could be used for rapid, low-cost detection of ketones in patients with type 1 diabetes and DKA and patients with type 1 or type 2 diabetes or heart failure treated with SGLT2-I and euglycemic ketoacidosis.

Superior Non-Invasive Glucose Sensor Using Bimetallic CuNi Nanospecies Coated Mesoporous Carbon.

The assessment of blood glucose levels is necessary for the diagnosis and management of diabetes. The accurate quantification of serum or plasma glucose relies on enzymatic and nonenzymatic methods utilizing electrochemical biosensors. Current research efforts are focused on enhancing the non-invasive detection of glucose in sweat with accuracy, high sensitivity, and stability. In this work, nanostructured mesoporous carbon coupled with glucose oxidase (GOx) increased the direct electron transfer to the electrode surface. A mixed alloy of CuNi nanoparticle-coated mesoporous carbon (CuNi-MC) was synthesized using a hydrothermal process followed by annealing at 700 °C under the flow of argon gas. The prepared catalyst's crystal structure and morphology were explored using X-ray diffraction and high-resolution transmission electron microscopy. The electrocatalytic activity of the as-prepared catalyst was investigated using cyclic voltammetry (CV) and amperometry. The findings show an excellent response time of 4 s and linear range detection from 0.005 to 0.45 mM with a high electrode sensitivity of 11.7 ± 0.061 mA mM cm-2 in a selective medium.

Audio-Based Drone Detection and Identification Using Deep Learning Techniques with Dataset Enhancement through Generative Adversarial Networks.

Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. In addition to their useful applications, an alarming concern in regard to the physical infrastructure security, safety and privacy has arisen due to the potential of their use in malicious activities. To address this problem, we propose a novel solution that automates the drone detection and identification processes using a drone's acoustic features with different deep learning algorithms. However, the lack of acoustic drone datasets hinders the ability to implement an effective solution. In this paper, we aim to fill this gap by introducing a hybrid drone acoustic dataset composed of recorded drone audio clips and artificially generated drone audio samples using a state-of-the-art deep learning technique known as the Generative Adversarial Network. Furthermore, we examine the effectiveness of using drone audio with different deep learning algorithms, namely, the Convolutional Neural Network, the Recurrent Neural Network and the Convolutional Recurrent Neural Network in drone detection and identification. Moreover, we investigate the impact of our proposed hybrid dataset in drone detection. Our findings prove the advantage of using deep learning techniques for drone detection and identification while confirming our hypothesis on the benefits of using the Generative Adversarial Networks to generate real-like drone audio clips with an aim of enhancing the detection of new and unfamiliar drones.

Progress of Advanced Nanomaterials in the Non-Enzymatic Electrochemical Sensing of Glucose and H2O2.

Non-enzymatic sensing has been in the research limelight, and most sensors based on nanomaterials are designed to detect single analytes. The simultaneous detection of analytes that together exist in biological organisms necessitates the development of effective and efficient non-enzymatic electrodes in sensing. In this regard, the development of sensing elements for detecting glucose and hydrogen peroxide (H2O2) is significant. Non-enzymatic sensing is more economical and has a longer lifetime than enzymatic electrochemical sensing, but it has several drawbacks, such as high working potential, slow electrode kinetics, poisoning from intermediate species and weak sensing parameters. We comprehensively review the recent developments in non-enzymatic glucose and H2O2 (NEGH) sensing by focusing mainly on the sensing performance, electro catalytic mechanism, morphology and design of electrode materials. Various types of nanomaterials with metal/metal oxides and hybrid metallic nanocomposites are discussed. A comparison of glucose and H2O2 sensing parameters using the same electrode materials is outlined to predict the efficient sensing performance of advanced nanomaterials. Recent innovative approaches to improve the NEGH sensitivity, selectivity and stability in real-time applications are critically discussed, which have not been sufficiently addressed in the previous reviews. Finally, the challenges, future trends, and prospects associated with advanced nanomaterials for NEGH sensing are considered. We believe this article will help to understand the selection of advanced materials for dual/multi non-enzymatic sensing issues and will also be beneficial for researchers to make breakthrough progress in the area of non-enzymatic sensing of dual/multi biomolecules.

Further studies on the role of the residue 890 cysteine to tyrosine mutation in the M70 primase ORF of the temperature-sensitive mutant (tsm5) of murine cytomegalovirus.

A mutation (C890Y) introduced into the M70 primase gene of murine cytomegalovirus (MCMV) resulted in reduced viral replication in murine embryo fibroblasts at 40°C and the mutant was severely attenuated in vivo. The attenuated replication of the M70 mutant was also observed in Raw 264.7 macrophages at 37°C, demonstrating that the mutation produced a defective rather than an unstable protein possibly reducing the amount of functional protein under different environmental conditions. Many synonymous mutations were introduced into this ORF by changing codon preferences that should reduce the efficiency of gene translation, but not change protein sequence or structure. Two Bacterial Artificial Chromosome (BAC) constructs were produced with 155 codons (at the distal third of the M70 gene) changed to MCMV less preferred codons and with either cysteine (BAC70(155Cys) ) or tyrosine (BAC70(155Tyr) ) at residue 890. Upon transfection of these BACs into NIH 3T3 cells, only BAC70(155Cys) produced virus and this mutant Mt70(155Cys) replicated similarly to its revertant and the wt MCMV K181 (Perth) variant. A metagenomic analysis of the protein structure of the primase using PredictProtein showed that the change from cysteine (M70Cys) to tyrosine (M70Tyr) has a marked effect on protein structure. However, when the cysteine residue was replaced by serine (M70Ser) or methionine (M70Met), which produced mutant viruses with a wild-type phenotype, the predicted structure was similar to the wild-type structure. J. Med. Virol. 88:1613-1621, 2016. © 2016 Wiley Periodicals, Inc.

Accuracy of Non-Contrast CT Brain Interpretation by Emergency Physicians: A cohort study.

OBJECTIVE: To assess the accuracy of emergency physicians (EPs) in the interpretation of non-contrast CT Brain (NCCT Brain) by examining the inter rater reliability between EPs and radiology specialists. METHODOLOGY: A four months prospective cohort study was conducted at emergency department of King Khalid University Hospital (KKUH), Riyadh, Saudi Arabia. We studied the daily performance of our EPs, and compared it to the radiological report issued within the week after. Data were analyzed by calculating sensitivity, specificity, accuracy and agreement (kappa statistic), using radiology report as the reference standard. Results : Out of 241 cases eligible for the study, 210 (87.14%) were concordant, and 31 (12.86%) were discordant. The agreement (kappa) was to be 0.64. Conclusion : We concluded that our EPs are moderately accurate at interpreting NCCT Brain studies. Further education and training programs were necessary for all our EPs to improve the accuracy. Further studies are required to determine the most cost-effective method of minimizing consequential misinterpretations.

An attenuated temperature-sensitive strain of cytomegalovirus (tsm5) establishes immunity without development of CD8(+) T cell memory inflation.

Cytomegalovirus (CMV) is a widely prevalent herpesvirus that is well tolerated by an immune competent host yet establishes a state of chronic infection. The virus is thought to undergo frequent subclinical episodes of reactivation which leads to an unusually large accumulation of CMV-specific CD8(+) T lymphocytes in the peripheral blood, a phenomenon termed "memory inflation." The high magnitude of the CMV T cell response has been implicated in impaired immunity to heterologous pathogens such as EBV, influenza and West Nile virus. Here, using murine CMV (MCMV), we show that memory inflation of virus-specific CD8(+) T cells is avoided if mice are infected with a replication defective virus called temperature-sensitive mutant 5 (tsm5), which carries an attenuating mutation within the DNA primase gene. Mice infected with tsm5 do generate primary T cell responses towards viral proteins but these do not amass to skew the memory repertoire of CD8(+) T cells. Therefore, attenuation of the virus replication machinery may be valuable in future CMV vaccine designs because the virus remains immunogenic but does not contribute to CMV associated T cell immune senescence.

Role of mutations identified in ORFs M27, M36, m139, m141, and m143 in the temperature-sensitive phenotype of murine cytomegalovirus mutant tsm5.

A mutant of murine cytomegalovirus (MCMV), tsm5, which is temperature-sensitive for replication in murine embryo fibroblasts at 40°C, failed to replicate to detectable levels in mice. A total of 18 non-synonymous mutations have been identified in tsm5. In a previous study, a mutation (C890Y) identified in the M70 primase gene, when introduced into the wt M70 primase, resulted in a mutant with reduced viral replication at 40°C in vitro and which was severely attenuated in vivo. Five other previously identified mutations may also contribute to the tsm5 phenotype: (1) an A658S mutation in a protein expressed by the M27 ORF; (2) a V54I mutation in M36; (3) a Y565* mutation in m139; (4) a V195M mutation in m141; and (5) an M232I mutation in m143. In the present study, the above-mentioned mutations were introduced individually (M27, M36, m139, m141, m143) or together (M27/M36) into the MCMV K181 (Perth) variant bacterial artificial chromosome (BAC) using RecE/T homologous recombination. Growth in culture revealed that, apart from the double mutant (M27 and M36) and the m139 mutant, the introduced mutations in the above-mentioned genes did not show a temperature-sensitive phenotype in MEF or Raw 264.7 macrophage cells compared to their revertants or the wt virus. In contrast, replication of the M27/M36 double mutant was drastically reduced in MEFs at 40°C and in macrophages at 37°C. Replication of the m139 mutant was reduced in MEF cells at 40°C but not in macrophages. Thus, at least three further mutations contribute to the tsm5 phenotype.

Role of mutations identified in ORFs M56 (terminase), M70 (primase) and M98 (endonuclease) in the temperature-sensitive phenotype of murine cytomegalovirus mutant tsm5.

Twenty-six non-synonymous and synonymous mutations have been identified in the temperature-sensitive (ts) mutant (tsm5) of the K181 (Birmingham) variant of murine cytomegalovirus that is deficient in DNA synthesis, processing and packaging at the non-permissive temperature and produces undetectable levels of infectious virus in mice. Non-synonymous mutations identified in the M70 (primase), M56 (terminase) and M98 (nuclease) ORFs were introduced individually and in combination into the K181 (Perth) variant using BAC technology to examine their role in the ts phenotype. The M56 (G439R) and M98 (P324S) mutations had no evident role in the ts phenotype. However, the C890Y M70 mutation alone and in combination with the M56 and/or M98 mutations rendered the virus ts, unable to replicate in mice and highly defective in DNA synthesis. Reversion of the tyrosine mutation to cysteine or introduction of C890M (experimentally) or C890S (naturally) restored the wt phenotype.

Identification of mutations in a temperature-sensitive mutant (tsm5) of murine cytomegalovirus using complementary genome sequencing.

Identification of mutations in mutants derived chemically is a difficult and relatively random process. NimbleGen Comparative Genome Sequencing (CGS) was assessed as an inexpensive, rapid method of identifying mutations in the temperature-sensitive mutant tsm5 of the K181 (Birmingham) variant of murine cytomegalovirus (MCMV). This genome resequencing approach requires an established genome sequence as a reference. Comparison of tsm5 and the K181 (Birmingham) variant with the published K181 (Perth) MCMV genomic sequence revealed a total of 10 synonymous and 15 non-synonymous SNPs in tsm5 and 14 of the latter were confirmed by sequencing. Thus, while CGS cannot be relied upon to identify correctly all mutations it was helpful for identifying a large number of mutations for further investigation that could contribute to the ts phenotype of tsm5.

Patients awareness of their medical conditions in multi-specialty outpatient clinics in Saudi Arabia.

OBJECTIVE: To assess the patients awareness of their medical conditions, identify the factors affecting their awareness, and assess patient's satisfaction with their doctors explanations of medical conditions. METHODS: A cross-sectional study was conducted in October 2005 in the outpatient clinics of King Khalid University Hospital in Riyadh, Kingdom of Saudi Arabia. A self-administered questionnaire was used for data collection. The statistical package for Social Science was used for analysis. RESULTS: Five hundred and one patients were included in the study. The mean age was 45.6 +/- 16.8. Fifty-five percent were female and 29% were highly educated. Most of the patients (64.1%) knew their diagnoses. This was significantly associated with the educational level; chronicity of the disease, and the awareness of other issues related to their illness such as complications and name of their medications (p<0.05). Few patients (20%) knew complications of their diseases. Seventy percent of patients were satisfied with their doctors' explanation of their disease. Knowing the diagnosis (p=0.001) and the disease complications (p=0.014) were associated significantly with patients' satisfaction. CONCLUSION: These figures are less than what they should be. Physicians must be advised of the importance of proper patient education. In addition, the lack of proper education by physicians demonstrated in this study should be compensated for by an increase in non-physician based education tools.