Detection of renal dysfunction during and after anaesthesia and surgery - evaluation of the influence of inorganic fluoride, ketorolac and clonidine

Drugs and surgical techniques may have harmful renal effects during the perioperative period. Traditional biomarkers are often insensitive to minor renal changes, but novel biomarkers may more accurately detect disturbances in glomerular and tubular function and integrity. The purpose of this study was first, to evaluate the renal effects of ketorolac and clonidine during inhalation anesthesia with sevoflurane and isoflurane, and secondly, to evaluate the effect of tobacco smoking on the production of inorganic fluoride (F-) following enflurane and sevoflurane anesthesia as well as to determine the effect of F- on renal function and cellular integrity in surgical patients. A total of 143 patients undergoing either conventional (n = 75) or endoscopic (n = 68) inpatient surgery were enrolled in four studies. The ketorolac and clonidine studies were prospective, randomized, placebo controlled and double-blinded, while the cigarette smoking studies were prospective cohort studies with two parallel groups. As a sign of proximal tubular deterioration, a similar transient increase in urine N-acetyl-beta-D-glucosaminidase/creatinine (U-NAG/crea) was noted in both the ketorolac group and in the controls (baseline vs. at two hours of anesthesia, p = 0.015) with a 3.3 minimum alveolar concentration hour sevoflurane anesthesia. Uncorrelated U-NAG increased above the maximum concentration measured from healthy volunteers (6.1 units/l) in 5/15 patients with ketorolac and in none of the controls (p = 0.042). As a sign of proximal tubular deterioration, U-glutathione transferase-alpha/crea (U-GST-alpha/crea) increased in both groups at two hours after anesthesia but a more significant increase was noted in the patients with ketorolac. U-GST-alpha/crea increased above the maximum ratio measured from healthy volunteers in 7/15 patients with ketorolac and in 3/15 controls. Clonidine diminished the activation of the renin-angiotensin aldosterone system during pneumoperitoneum; urine output was better preserved in the patients treated with clonidine (1/15 patients developed oliguria) than in the controls (8/15 developed oliguria (p=0.005)). Most patients with pneumoperitoneum and isoflurane anesthesia developed a transient proximal tubular deterioration, as U-NAG increased above 6.1 units/L in 11/15 patients with clonidine and in 7/15 controls. In the patients receiving clonidine treatment, the median of U-NAG/crea was higher than in the controls at 60 minutes of pneumoperitoneum (p = 0.01), suggesting that clonidine seems to worsen proximal tubular deterioration. Smoking induced the metabolism of enflurane, but the renal function remained intact in both the smokers and the non-smokers with enflurane anesthesia. On the contrary, smoking did not induce sevoflurane metabolism, but glomerular function decreased in 4/25 non-smokers and in 7/25 smokers with sevoflurane anesthesia. All five patients with S-F- ≥ 40 micromol/L, but only 6/45 with S-F- less than 40 micromol/L (p = 0.001), developed a S-tumor associated trypsin inhibitor concentration above 3 nmol/L as a sign of glomerular dysfunction. As a sign of proximal tubulus deterioration, U-beta 2-microglobulin increased in 2/5 patients with S-F- over 40 micromol/L compared to 2/45 patients with the highest S-F- less than 40 micromol/L (p = 0.005). To conclude, sevoflurane anesthesia may cause a transient proximal tubular deterioration which may be worsened by a co-administration of ketorolac. Clonidine premedication prevents the activation of the renin-angiotensin aldosterone system and preserves normal urine output, but may be harmful for proximal tubules during pneumoperitoneum. Smoking induces the metabolism of enflurane but not that of sevoflurane. Serum F- of 40 micromol/L or higher may induce glomerular dysfunction and proximal tubulus deterioration in patients with sevoflurane anesthesia. The novel renal biomarkers warrant further studies in order to establish reference values for surgical patients having inhalation anesthesia.

Detection and progression of chronic allograft nephropathy : A study based on protocol biopsies

Background. Kidney transplantation (KTX) is considered to be the best treatment of terminal uremia. Despite improvements in short-term graft survival, a considerable number of kidney allografts are lost due to the premature death of patients with a functional kidney and to chronic allograft nephropathy (CAN). Aim. To investigate the risk factors involved in the progression of CAN and to analyze diagnostic methods for this entity. Materials and methods. Altogether, 153 implant and 364 protocol biopsies obtained between June 1996 and April 2008 were analyzed. The biopsies were classified according to Banff ’97 and chronic allograft damage index (CADI). Immunohistochemistry for TGF-β1 was performed in 49 biopsies. Kidney function was evaluated by creatinine and/or cystatin C measurement and by various estimates of glomerular filtration rate (GFR). Demographic data of the donors and recipients were recorded after 2 years’ follow-up. Results. Most of the 3-month biopsies (73%) were nearly normal. The mean CADI score in the 6-month biopsies decreased significantly after 2001. Diastolic hypertension correlated with ΔCADI. Serum creatinine concentration at hospital discharge and glomerulosclerosis were risk factors for ΔCADI. High total and LDL cholesterol, low HDL and hypertension correlated with chronic histological changes. The mean age of the donors increased from 41 -52 years. Older donors were more often women who had died from an underlying disease. The prevalence of delayed graft function increased over the years, while acute rejections (AR) decreased significantly over the years. Sub-clinical AR was observed in 4% and it did not affect long-term allograft function or CADI. Recipients´ drug treatment was modified along the Studies, being mycophenolate mophetil, tacrolimus, statins and blockers of the renine-angiotensin-system more frequently prescribed after 2001. Patients with a higher ΔCADI had lower GFR during follow-up. CADI over 2 was best predicted by creatinine, although with modest sensitivity and specificity. Neither cystatin C nor other estimates of GFR were superior to creatinine for CADI prediction. Cyclosporine A toxicity was seldom seen. Low cyclosporin A concentration after 2 h correlated with TGF- β1 expression in interstitial inflammatory cells, and this predicted worse graft function. Conclusions. The progression of CAN has been affected by two major factors: the donors’ characteristics and the recipients’ hypertension. The increased prevalence of DGF might be a consequence of the acceptance of older donors who had died from an underlying disease. Implant biopsies proved to be of prognostic value, and they are essential for comparison with subsequent biopsies. The progression of histological damage was associated with hypertension and dyslipidemia. The augmented expression of TGF-β1 in inflammatory cells is unclear, but it may be related to low immunosuppression. Serum creatinine is the most suitable tool for monitoring kidney allograft function on every-day basis. However, protocol biopsies at 6 and 12 months predicted late kidney allograft dysfunction and affected the clinical management of the patients. Protocol biopsies are thus a suitable surrogate to be used in clinical trials and for monitoring kidney allografts.

Detection of contiguous and distributed damage through contours of equal frequency change

The paper presents the results of a computational modeling for damage identification process for an axial rod representing an end-bearing pile foundation with known damage and a simply supported beam representing a bridge girder. The paper proposes a methodology for damage identification from measured natural frequencies of a contiguously damaged reinforced concrete axial rod and beam, idealized with distributed damage model. Identification of damage is from Equal_Eigen_value_change (Iso_Eigen_value_Change) contours, plotted between pairs of different frequencies. The performance of the method is checked for a wide variation of damage positions and extents. An experiment conducted on a free-free axially loaded reinforced concrete member and a flexural beam is shown as examples to prove the pros and cons of this method. (C) 2009 Elsevier Ltd. All rights reserved.

Kernel-based spatial-color modeling for fast moving object tracking

Visual tracking has been a challenging problem in computer vision over the decades. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. Mean-shift (MS) tracker, which gained more attention recently, is known for tracking objects in a cluttered environment and its low computational complexity. The major problem encountered in histogram-based MS is its inability to track rapidly moving objects. In order to track fast moving objects, we propose a new robust mean-shift tracker that uses both spatial similarity measure and color histogram-based similarity measure. The inability of MS tracker to handle large displacements is circumvented by the spatial similarity-based tracking module, which lacks robustness to object's appearance change. The performance of the proposed tracker is better than the individual trackers for tracking fast-moving objects with better accuracy.

Energy efficient change detection over a MAC using physical layer fusion

We propose a simple and energy efficient distributed change detection scheme for sensor networks based on Page's parametric CUSUM algorithm. The sensor observations are IID over time and across the sensors conditioned on the change variable. Each sensor runs CUSUM and transmits only when the CUSUM is above some threshold. The transmissions from the sensors are fused at the physical layer. The channel is modeled as a multiple access channel (MAC) corrupted with IID noise. The fusion center which is the global decision maker, performs another CUSUM to detect the change. We provide the analysis and simulation results for our scheme and compare the performance with an existing scheme which ensures energy efficiency via optimal power selection.

Decentralized sequential change detection using physical layer fusion

We study the problem of decentralized sequential change detection with conditionally independent observations. The sensors form a star topology with a central node called fusion center as the hub. The sensors transmit a simple function of their observations in an analog fashion over a wireless Gaussian multiple access channel and operate under either a power constraint or an energy constraint. Simulations demonstrate that the proposed techniques have lower detection delays when compared with existing schemes. Moreover we demonstrate that the energy-constrained formulation enables better use of the total available energy than a power-constrained formulation.

Detection of SFBC-OFDM signals in frequency- and time-selective MIMO channels

Use of space-frequency block coded (SFBC) OFDM signals is advantageous in high-mobility broadband wireless access, where the channel is highly time- as well as frequency-selective because of which the receiver experiences both inter-symbol interference (ISI) as well as inter-carrier interference (10). ISI occurs due to the violation of the 'quasi-static' fading assumption caused due to frequency- and/or time-selectivity of the channel. In addition, ICI occurs due to time-selectivity of the channel which results in loss of orthogonality among the subcarriers. In this paper, we are concerned with the detection of SFBC-OFDM signals on time- and frequency-selective MIMO channels. Specifically, we propose and evaluate the performance of an interference cancelling receiver for SFBC-OFDM which alleviates the effects of ISI and ICI in highly time- and frequency-selective channels.

Detection of multicode STBC signals in frequency selective fading

Multicode operation in space-time block coded (STBC) multiple input multiple output (MIMO) systems can provide additional degrees of freedom in code domain to achieve high data rates. In such multicode STBC systems, the receiver experiences code domain interference (CDI) in frequency selective fading. In this paper, we propose a linear parallel interference cancellation (LPIC) approach to cancel the CDI in multicode STBC in frequency selective fading. The proposed detector first performs LPIC followed by STBC decoding. We evaluate the bit error performance of the detector and show that it effectively cancels the CDI and achieves improved error performance. Our results further illustrate how the combined effect of interference cancellation, transmit diversity, and RAKE diversity affect the bit error performance of the system.

False Error Study of On-line Soft Error Detection Mechanisms

With technology scaling, vulnerability to soft errors in random logic is increasing. There is a need for on-line error detection and protection for logic gates even at sea level. The error checker is the key element for an on-line detection mechanism. We compare three different checkers for error detection from the point of view of area, power and false error detection rates. We find that the double sampling checker (used in Razor), is the simplest and most area and power efficient, but suffers from very high false detection rates of 1.15 times the actual error rates. We also find that the alternate approaches of triple sampling and integrate and sample method (I&S) can be designed to have zero false detection rates, but at an increased area, power and implementation complexity. The triple sampling method has about 1.74 times the area and twice the power as compared to the Double Sampling method and also needs a complex clock generation scheme. The I&S method needs about 16% more power with 0.58 times the area as double sampling, but comes with more stringent implementation constraints as it requires detection of small voltage swings.

On the Average Case Communication Complexity for Detection in Sensor Networks

The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space viewpoint is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces $\mathcal{S_I}$ and $\mathcal{S_C}$ and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating $\mathcal{S_I}$ and $\mathcal{S_C}$ is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. The average case CC of the relevant greater-than (GT) function is characterized within two bits. In the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm.

Optimal sleep-wake scheduling for quickest intrusion detection using sensor networks

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices, we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: (1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, (2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which (3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time), based on the sensor observations obtained until time slot k. Our results show that an optimum closed loop control on Mk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.

Thiourea based novel chromogenic sensor for selective detection of fluoride and cyanide anions in organic and aqueous media

Novel chromogenic thiourea based sensors 4,4'-bis-[3-(4-nitrophenyl) thiourea] diphenyl ether 1 and 4,4'-bis-[3-(4-nitrophenyl) thiourea] diphenyl methane 2 having nitrophenyl group as signaling unit have been synthesized and characterized by spectroscopic techniques and X-ray crystallography. The both sensors show visual detection, UV-vis and NMR spectral changes in presence of fluoride and cyanide anions in organic solvent as well as in aqueous medium. The absorption spectra indicated the formation of complex between host and guest is in 1:2 stoichiometric ratios. (C) 2010 Elsevier B.V. All rights reserved.

Multiple excitation nano-spot generation and confocal detection for far-field microscopy

An imaging technique is developed for the controlled generation of multiple excitation nano-spots for far-field microscopy. The system point spread function (PSF) is obtained by interfering two counter-propagating extended depth-of-focus PSF (DoF-PSF), resulting in highly localized multiple excitation spots along the optical axis. The technique permits (1) simultaneous excitation of multiple planes in the specimen; (2) control of the number of spots by confocal detection; and (3) overcoming the point-by-point based excitation. Fluorescence detection from the excitation spots can be efficiently achieved by Z-scanning the detector/pinhole assembly. The technique complements most of the bioimaging techniques and may find potential application in high resolution fluorescence microscopy and nanoscale imaging.