Accuracy of Microwave Transistor fT and fMAX Extractions

We present a complete methodology to evaluate the accuracy of microwave transistor figures-of-merit fT (current gain cut-off frequency) and fMAX (maximum oscillation frequency). These figures-of-merit are usually extracted from calibrated S-parameter measurements affected by residual calibration and measurement uncertainties. Thus, the uncertainties associated to fT and fMAX can be evaluated only after an accurate computation of the S-parameters uncertainties, including the contribution from de-embedding. This was done with the aid of two recently released software tools. We also present an analysis on how different interpolation/extrapolation methodologies affect uncertainty. Finally, an overview of the possible causes of errors and suggestions on how to avoid them are given. With the continued rise of reported fT /fMAX values, this study has become necessary in order to add confidence intervals to these figures-of-meri

A W-Band On-Wafer Active Load-Pull System Based on Down-Conversion Techniques

A new W-band active load-pull system is presented. It is the first load-pull system to implement a 94 GHz load by means of an active loop exploiting frequency conversion techniques. The active loop configuration demonstrates a number of advantages that overcome the typical limitations of W-band passive tuners or conventional active open loop techniques in a cost effective way: load reflection coefficients Γ L as high as 0.95 in magnitude can be achieved at 94 GHz, thus providing a nearly full coverage of the Smith Chart. Possible applications of the setup include technology assessment, large-signal device model verification at sub-THz frequencies, and W-band MMIC design and characterization. The availability of direct and accurate load-pull measurements at W-band should prove an asset in the development of sub-THz integrated circuits. First measure- ments performed on high performance InP double heterojunction bipolar transistors (DHBTs) and GaN high electron mobility transistors (HEMTs) are presente

High fractional excretion of glycation adducts is associated with subsequent early decline in renal function in type 1 diabetes

Increased protein glycation, oxidation and nitration is linked to the development of diabetic nephropathy. We reported levels of serum protein glycation, oxidation and nitration and related hydrolysis products, glycation, oxidation and nitration free adducts in patients with type 1 diabetes (T1DM) during onset of microalbuminuria (MA) from the First Joslin Kidney Study, a prospective case–control study of patients with T1DM with and without early decline in GFR. Herein we report urinary excretion of the latter analytes and related fractional excretion values, exploring the link to MA and early decline in GFR. We recruited patients with T1DM and normoalbuminuria (NA) (n = 30) or new onset MA with and without early GFR decline (n = 22 and 33, respectively) for this study. We determined urinary protein glycation, oxidation and nitration free adducts by stable isotopic dilution analysis liquid chromatography-tandem mass spectrometry (LC–MS/MS) and deduced fractional excretion using reported plasma levels and urinary and plasma creatinine estimates. We found urinary excretion of pentosidine was increased ca. twofold in patients with MA, compared to normoalbuminuria (0.0442 vs 0.0103 nmol/mg creatinine, P < 0.0001), and increased ca. threefold in patients with early decline in GFR, compared to patients with stable GFR (0.0561 vs 0.0176 nmol/mg creatinine, P < 0.01). Urinary excretion of all other analytes was unchanged between the study groups. Remarkably, fractional excretions of 6 lysine and arginine-derived glycation free adducts were higher in patients with early decline in GFR, compared to those with stable GFR. Impaired tubular reuptake of glycation free adducts by lysine and arginine transporter proteins in patients with early GFR decline is likely involved. We conclude that higher fractional excretions of glycation adducts are potential biomarkers for early GFR decline in T1DM and MA. Measurement of these analytes could provide the basis for identifying patients at risk of early decline in renal function to target and intensify renoprotective treatment

A fully automatic nerve segmentation and morphometric parameter quantification system for early diagnosis of diabetic neuropathy in corneal images

Diabetic Peripheral Neuropathy (DPN) is one of the most common types of diabetes that can affect the cornea. An accurate analysis of the nerve structures can assist the early diagnosis of this disease. This paper proposes a robust, fast and fully automatic nerve segmentation and morphometric parameter quantification system for corneal confocal microscope images. The segmentation part consists of three main steps. First, a preprocessing step is applied to enhance the visibility of the nerves and remove noise using anisotropic diffusion filtering, specifically a Coherence filter followed by Gaussian filtering. Second, morphological operations are applied to remove unwanted objects in the input image such as epithelial cells and small nerve segments. Finally, an edge detection step is applied to detect all the nerves in the input image. In this step, an efficient algorithm for connecting discontinuous nerves is proposed. In the morphometric parameters quantification part, a number of features are extracted, including thickness, tortuosity and length of nerve, which may be used for the early diagnosis of diabetic polyneuropathy and when planning Laser-Assisted in situ Keratomileusis (LASIK) or Photorefractive keratectomy (PRK). The performance of the proposed segmentation system is evaluated against manually traced ground-truth images based on a database consisting of 498 corneal sub-basal nerve images (238 are normal and 260 are abnormal). In addition, the robustness and efficiency of the proposed system in extracting morphometric features with clinical utility was evaluated in 919 images taken from healthy subjects and diabetic patients with and without neuropathy. We demonstrate rapid (13 seconds/image), robust and effective automated corneal nerve quantification. The proposed system will be deployed as a useful clinical tool to support the expertise of ophthalmologists and save the clinician time in a busy clinical setting

Diabetic peripheral neuropathy : advances in diagnosis and strategies for screening and early intervention

Diabetic peripheral neuropathy (DPN) is a common complication of both type 1 and 2 diabetes. It is a leading cause of lower-limb amputation and disabling neuropathic pain. Amputations in patients with diabetes have a devastating effect on quality of life and are associated with an alarmingly low life expectancy (on average only 2 years from the amputation). Amputation also places a substantial financial burden on health-care systems and society in general. With the introduction of national diabetes eye screening programmes, the prevalence of blindness in working-age adults is falling. This is not the case, however, with diabetes related amputations. In this Review, we appraise innovative point-of-care devices that enable the early diagnosis of DPN and assess the evidence for early risk factor-based management strategies to reduce the incidence and slow the progression of DPN. We also propose a framework for screening and early multifactorial interventions as the best prospect for preventing or halting DPN and its devastating sequelae

Evaluation of proxy tests for SFSN: evidence for mixed small and large fiber dysfunction.

BACKGROUND: Though intra-epidermal nerve fiber density (IENFD) is considered the gold standard for diagnosis of small fiber sensory neuropathy (SFSN), we aimed to determine if novel threshold values derived from standard tests of small or large fiber function could serve as diagnostic alternatives. METHODS: Seventy-four consecutive patients with painful polyneuropathy and normal nerve conduction studies (NCS) were defined as SFSN cases or controls by distal IENFD <5.4 and ≥5.4 fibers/mm, respectively. Diagnostic performance of small fiber [cooling (CDT) and heat perception (HP) thresholds, axon reflex-mediated neurogenic vasodilatation] and large fiber function tests [vibration perception thresholds (VPT) and sural nerve conduction parameters] were determined by receiver operating-characteristic (ROC) curve analyses. RESULTS: The 26(35%) SFSN cases had mean IENFD 3.3±1.7 fibers/mm and the 48(65%) controls 9.9±2.9 fibers/mm. Male gender (p = 0.02) and older age (p = 0.02) were associated with SFSN cases compared to controls. VPT were higher and CDT lower in SFSN cases, but the largest magnitude of differences was observed for sural nerve amplitude. It had the greatest area under the ROC curve (0.75) compared to all other tests (p<0.001 for all comparisons) and the optimal threshold value of ≤12 µV defined SFSN cases with 80% sensitivity and 72% specificity. CONCLUSION: In patients presenting with polyneuropathy manifestations and normal NCS, though small fiber function tests were intuitively considered the best alternative measures to predict reduced IENFD, their diagnostic performance was poor. Instead, novel threshold values within the normal range for large fiber tests should be considered as an alternative strategy to select subjects for skin biopsy in diagnostic protocols for SFSN

Reliability and validity of a point-of-care sural nerve conduction device for identification of diabetic neuropathy.

BACKGROUND: Confirmation of diabetic sensorimotor polyneuropathy (DSP) relies on standard nerve conduction studies (NCS) performed in specialized clinics. We explored the utility of a point-of-care device (POCD) for DSP detection by nontechnical personnel and a validation of diagnostic thresholds with those observed in a normative database. RESEARCH DESIGN AND METHODS: 44 subjects with type 1 and type 2 diabetes underwent standard NCS (reference method). Two nontechnical examiners measured sural nerve amplitude potential (SNAP) and conduction velocity (SNCV) using the POCD. Reliability was determined by intraclass correlation coefficients (ICC [2], [1]). Validity was determined by Bland-Altman analysis and receiver operating characteristic curves. RESULTS: The 44 subjects (50% female) with mean age 56 ± 18 years had mean SNAP and SNCV of 8.0 ± 8.6 µV and 41.5 ± 8.2 m/s using standard NCS and 8.0 ± 8.2 µV and 49.9 ± 11.1 m/s using the POCD. Intrarater reproducibility ICC values were 0.97 for SNAP and 0.94 for SNCV while interrater reproducibility values were 0.83 and 0.79, respectively. Mean bias of the POCD was -0.1 ± 3.6 µV for SNAP and +8.4 ± 6.4 m/s for SNCV. A SNAP of ≤6 µV had 88% sensitivity and 94% specificity for identifying age-and height-standardized reference NCS values, while a SNCV of ≤48 m/s had 94% sensitivity and 82% specificity [corrected].. Abnormality in one or more of these thresholds was associated with 95% sensitivity and 71% specificity for identification of DSP according to electrophysiological criteria. CONCLUSIONS: The POCD demonstrated excellent reliability and acceptable accuracy. Threshold values for DSP identification validated those of published POCD normative values. We emphasize the presence of measurement bias--particularly for SNCV--that requires adjustment of threshold values to reflect those of standard NCS

Identification and prediction of diabetic sensorimotor polyneuropathy using individual and simple combinations of nerve conduction study parameters.

OBJECTIVE: Evaluation of diabetic sensorimotor polyneuropathy (DSP) is hindered by the need for complex nerve conduction study (NCS) protocols and lack of predictive biomarkers. We aimed to determine the performance of single and simple combinations of NCS parameters for identification and future prediction of DSP. MATERIALS AND METHODS: 406 participants (61 with type 1 diabetes and 345 with type 2 diabetes) with a broad spectrum of neuropathy, from none to severe, underwent NCS to determine presence or absence of DSP for cross-sectional (concurrent validity) analysis. The 109 participants without baseline DSP were re-evaluated for its future onset (predictive validity). Performance of NCS parameters was compared by area under the receiver operating characteristic curve (AROC). RESULTS: At baseline there were 246 (60%) Prevalent Cases. After 3.9 years mean follow-up, 25 (23%) of the 109 Prevalent Controls that were followed became Incident DSP Cases. Threshold values for peroneal conduction velocity and sural amplitude potential best identified Prevalent Cases (AROC 0.90 and 0.83, sensitivity 80 and 83%, specificity 89 and 72%, respectively). Baseline tibial F-wave latency, peroneal conduction velocity and the sum of three lower limb nerve conduction velocities (sural, peroneal, and tibial) best predicted 4-year incidence (AROC 0.79, 0.79, and 0.85; sensitivity 79, 70, and 81%; specificity 63, 74 and 77%, respectively). DISCUSSION: Individual NCS parameters or their simple combinations are valid measures for identification and future prediction of DSP. Further research into the predictive roles of tibial F-wave latencies, peroneal conduction velocity, and sum of conduction velocities as markers of incipient nerve injury is needed to risk-stratify individuals for clinical and research protocols