205 research outputs found
Importance of source structure on complex organics emission II. Can disks explain lack of methanol emission from some low-mass protostars?
Some protostellar systems show little or no millimetre line emission of
complex organics. This can be interpreted as a low abundance of these
molecules, alternatively they could be present in the system but are not seen
in the gas. The goal is to investigate the latter hypothesis for methanol. We
will attempt to answer the question: Does the presence of a disk and optically
thick dust reduce methanol emission even if methanol is abundant in the ices
and gas? Using the radiative transfer code RADMC-3D, methanol emission lines
from an envelope-only model and an envelope-plus-disk model are calculated and
compared with each other and the observations. Methanol emission from the
envelope-only model is always stronger than from the envelope-plus-disk model
by at least a factor 2 as long as the disk radius is larger than 30 au (for L=8
L). In most cases, this is due to lower temperatures and, hence, the
smaller amount of warm methanol inside the snow surface of the
envelope-plus-disk model. The intensities drop by more than an order of
magnitude for models including high mm opacity dust grains and disk radii of at
least 50 au (for L=8 L) due to continuum over-subtraction. The line
intensities from the envelope-only models overproduce the observations of
protostars with lower methanol emission even with large dust optical depth
effects. The envelope-plus-disk models can explain the bulk of the
observations. However, they can only reproduce the observations of sources with
high luminosities and low methanol emission when dust optical depth effects
especially continuum over-subtraction in the disk becomes effective. Therefore,
both the effects of disk and dust optical depth should be considered to explain
the observations. In conclusion: Absence of methanol emission does not imply
absence of methanol molecules in either gas or ice.Comment: Accepted to A&
Carbon nanoparticles in lateral flow methods to detect genes encoding virulence factors of Shiga toxin-producing Escherichia coli
The use of carbon nanoparticles is shown for the detection and identification of different Shiga toxin-producing Escherichia coli virulence factors (vt1, vt2, eae and ehxA) and a 16S control (specific for E. coli) based on the use of lateral flow strips (nucleic acid lateral flow immunoassay, NALFIA). Prior to the detection with NALFIA, a rapid amplification method with tagged primers was applied. In the evaluation of the optimised NALFIA strips, no cross-reactivity was found for any of the antibodies used. The limit of detection was higher than for quantitative PCR (q-PCR), in most cases between 10 4 and 10 5 colony forming units/mL or 0.1-0.9 ng/¿L DNA. NALFIA strips were applied to 48 isolates from cattle faeces, and results were compared to those achieved by q-PCR. E. coli virulence factors identified by NALFIA were in very good agreement with those observed in q-PCR, showing in most cases sensitivity and specificity values of 1.0 and an almost perfect agreement between both methods (kappa coefficient larger than 0.9). The results demonstrate that the screening method developed is reliable, cost-effective and user-friendly, and that the procedure is fast as the total time required is <1 h, which includes amplification. © 2010 The Author(s).This work was partially supported by the Generalitat Valenciana (BEST/2009/026), the Universidad Politecnica de Valencia (PAID-00-09-2837), and by the Dutch Ministry of Agriculture, Nature and Food Quality (KennisBasis 6 programme). The authors would like to thank Dr. Eva Moller Nielsen at the Danish Veterinary Institute (Copenhagen, Denmark) for providing E. coli control strains and Dr. Lutz Geue (Friedrich-Loeffler-Institut, Wusterhausen, Germany) and Dr. Dorte Dopfer (School of Veterinary Medicine, University of Wisconsin, Madison, WI, USA) for field isolates.Noguera Murray, PS.; Posthuma-Trumpie, G.; Van Tuil, M.; Van Der Wal, F.; De Boer, A.; Moers, A.; Van Amerongen, A. (2011). Carbon nanoparticles in lateral flow methods to detect genes encoding virulence factors of Shiga toxin-producing Escherichia coli. Analytical and Bioanalytical Chemistry. 399:831-838. https://doi.org/10.1007/s00216-010-4334-zS831838399Alocilja EC, Radke SM (2003) Biosens Bioelectron 18:841–846Lazcka O, Campo FJD, Muñoz FX (2007) Biosens Bioelectron 22:1205–1217Nataro JP, Kaper JB (1998) Clin Microbiol Rev 11:142–201Meng J, Doyle MP (1998) Bull Inst Pasteur 96:151–163Karmali MA, Gannon V, Sargeant JM (2010) Vet Microbiol 140:360–370de Boer E, Beumer RR (1999) Int J Food Microbiol 50:119–130Ivnitski D, Abdel-Hamid I, Atanasov P, Wilkins E (1999) Biosens Bioelectron 14:599–624Tokarskyy O, Marshall DL (2008) Food Microbiol 25:1–12Chemburu S, Wilkins E, Abdel-Hamid I (2005) Biosens Bioelectron 21:491–499Rule G, Montagna R, Durst R (1996) Clin Chem 42:1206–1209Ngom B, Guo Y, Wang X, Bi D (2010) Anal Bioanal Chem 397:1113–1135Posthuma-Trumpie GA, Korf J, van Amerongen A (2009) Anal Bioanal Chem 393:569–582Carter DJ, Cary RB (2007) Nucleic Acids Res 35:e74Kalogianni DP, Goura S, Aletras AJ, Christopoulos TK, Chanos MG, Christofidou M, Skoutelis A, Ioannou PC, Panagiotopoulos E (2007) Anal Biochem 361:169–175Litos IK, Ioannou PC, Christopoulos TK, Traeger-Synodinos J, Kanavakis E (2009) Biosens Bioelectron 24:3135–3139Blažková M, Koets M, Rauch P, van Amerongen A (2009) Eur Food Res Technol 229:867–874Mens PF, van Amerongen A, Sawa P, Kager PA, Schallig HD (2008) Diagn Microbiol Infect Dis 61:421–427Gordon J, Michel G (2008) Clin Chem 54:1250–1251Aldus CF, van Amerongen A, Ariens RM, Peck MW, Wichers JH, Wyatt GM (2003) J Appl Microbiol 95:380–389Capps KL, McLaughlin EM, Murray AW, Aldus CF, Wyatt GM, Peck MW, van Amerongen A, Ariens RM, Wichers JH, Baylis CL, Wareing DR, Bolton FJ (2004) J AOAC Int 87:68–77van Amerongen A, Koets M (2005) In: van Amerongen A, Barug D, Lauwaars M (eds) Rapid methods for biological and chemical contaminants in food and feed. Wageningen Academic Publishers, Wageningen, pp 105–216Moreira BG, You Y, Behlke MA, Owczarzy R (2005) Biochem Biophys Res Commun 327:473–484Nielsen EM, Andersen MT (2003) J Clin Microbiol 41:2884–2893Huijsdens XW, Linskens RK, Mak M, Meuwissen SGM, Vandenbroucke-Grauls CMJE, Savelkoul PHM (2002) J Clin Microbiol 40:4423–4427Koets M, Sander I, Bogdanovic J, Doekes G, van Amerongen A (2006) J Environ Monit 8:942–946van Amerongen A, Wichers JH, Berendsen LBJM, Timmermans AJM, Keizer GD, van Doorn AWJ, Bantjes A, van Gelder WMJ (1993) J Biotechnol 30:185–195O’Keeffe M, Crabbe P, Salden M, Wichers J, van Peteghem C, Kohen F, Pieraccini G, Moneti G (2003) J Immunol Methods 278:117–126Posthuma-Trumpie GA, Korf J, van Amerongen A (2008) Anal Bioanal Chem 392:1215–1223Chang LL, Shepherd D, Sun J, Ouellette D, Grant KL, Tang XC, Pikal MJ (2005) J Pharm Sci 94:1427–1444Geue L, Segura-Alvarez M, Conraths FJ, Kuczius T, Bockemuhl J, Karch H, Gallien P (2002) Epidemiol Infect 129:173–185Eurachem/CITAC (2003) EURACHEM/CITAC Guide: The expression of uncertainty in qualitative testing. LGC, Teddington, Middlesex, UK, p 22Ellison SLR, Fearn T (2005) Trac-Trends Anal Chem 24:468–476Gilchrist JM (2009) J Clin Microbiol 62:1045–1053Landis JR, Koch GG (1977) Biometrics 33:159–174Mackinnon A (2000) Comput Biol Med 30:127–134Mil’man BL, Konopel’ko LA (2004) J Anal Chem 59:1128–1141AOAC (2006) Final report and executive summaries from the AOAC International Presidential Task Force on best practices in microbiological methodology. AOAC International, Gaithersburg, Maryland, USA, p 20
The usefulness of artificial intelligence for safety assessment of different transport modes
Recent research in transport safety focuses on the processing of large amounts of available data by means of intelligent systems, in order to decrease the number of accidents for transportation users. Several Machine Learning (ML) and Artificial Intelligence (AI) applications have been developed to address safety problems and improve efficiency of transportation systems. However exchange of knowledge between transport modes has been limited. This paper reviews the ML and AI methods used in different transport modes (road, rail, maritime and aviation) to address safety problems, in order to identify good practices and experiences that can be transferable between transport modes. The methods examined include statistical and econometric methods, algorithmic approaches, classification and clustering methods, artificial neural networks (ANN) as well as optimization and dimension reduction techniques. Our research reveals the increasing interest of transportation researchers and practitioners in AI applications for crash prediction, incident/failure detection, pattern identification, driver/operator or route assistance, as well as optimization problems. The most popular and efficient methods used in all transport modes are ANN, SVM, Hidden Markov Models and Bayesian models. The type of the analytical technique is mainly driven by the purpose of the safety analysis performed. Finally, a wider variety of AI and ML methodologies is observed in road transport mode, which also appears to concentrate a higher, and constantly increasing, number of studies compared to the other modes
Allograft survival based on tacrolimus (Tac) predose concentrations (C<sub>0</sub>) ≤5.9 ng/mL vs. >5.9 ng/mL of c-aABMR patients (cases) and controls combined.
Allograft survival based on tacrolimus (Tac) predose concentrations (C0) ≤5.9 ng/mL vs. >5.9 ng/mL of c-aABMR patients (cases) and controls combined.</p
Evidence on continuous flow peritoneal dialysis: A review
Clinical application of continuous flow peritoneal dialysis (CFPD) has been explored since the 1960s, but despite anticipated clinical benefits, CFPD has failed to gain a foothold in clinical practice, among others due to the typical use of two catheters (or a dual-lumen catheter) and large dialysate volumes required per treatment. Novel systems applying CFPD via the existing single-lumen catheter using rapid dialysate cycling may solve one of these hurdles. Novel on-demand peritoneal dialysate generation systems and sorbent-based peritoneal dialysate regeneration systems may considerably reduce the storage space for peritoneal dialysate and/or the required dialysate volume. This review provides an overview of current evidence on CFPD in vivo. The available (pre)clinical evidence on CFPD is limited to case reports/series with inherently nonuniform study procedures, or studies with a small sample size, short follow-up, and no hard endpoints. Small solute clearance appears to be higher in CFPD compared to conventional PD, in particular at dialysate flows ≥100 mL/min using two single-lumen catheters or a double-lumen catheter. Results of CFPD using rapid cycling via a single-lumen catheter are too preliminary to draw any conclusions. Continuous addition of glucose to dialysate with CFPD appears to be effective in reducing the maximum intraperitoneal glucose concentration while increasing ultrafiltration efficiency (mL/g absorbed glucose). Patient tolerance may be an issue since abdominal discomfort and sterile peritonitis were reported with continuous circulation of the peritoneal dialysate. Thus, well-designed clinical trials of longer duration and larger sample size, in particular applying CFPD via the existing catheter, are urgently required
Intra-patient variability in tacrolimus trough concentrations and renal function decline in pediatric renal transplant recipients
Prytula AA, Bouts AH, Mathot RAA, van Gelder T, Croes LK, Hop W, Cransberg K. Intra-patient variability in tacrolimus trough concentrations and renal function decline in pediatric renal transplant recipients. Abstract: High intra-patient variability in TCL exposure is a risk factor for allograft loss and late acute rejection. We hypothesized that a higher intra-patient variability leads to a faster decline in GFR in pediatric renal transplant patients and that adolescents have a higher intra-patient variability due to poorer adherence. We included 69 children aged 3.518 yr who had undergone renal transplantation between April 1996 and May 2009 in two pediatric nephrology centers in the Netherlands. We analyzed TCL trough concentrations over a period of one yr and calculated TCL trough concentrations variability using VC. We investigated the correlation between the TCL trough concentrations variability and the decline in estimated GFR over four yr. The median intra-patient variability in TCL concentrations was 30.1% (range 8.677.6) and the mean GFR slope -3.8 mL/min/1.73 m2/yr. The VC correlated neither with the GFR slope, nor with the patients age. However, children with late acute rejection had higher VC (p = 0.045). We were unable to provide evidence that a high variability in TCL exposure leads to a faster decline in renal function, although children with late acute rejection have a higher variability in TCL exposure. Adolescents do not have a higher intra-patient variability in TCL trough concentrations than younger childre
Extended pancreas donor program - the EXPAND study rationale and study protocol
BACKGROUND:
Simultaneous pancreas kidney transplantation (SPK), pancreas transplantation alone (PTA) or pancreas transplantation after kidney (PAK) are the only curative treatment options for patients with type 1 (juvenile) diabetes mellitus with or without impaired renal function. Unfortunately, transplant waiting lists for this indication are increasing because the current organ acceptability criteria are restrictive; morbidity and mortality significantly increase with time on the waitlist. Currently, only pancreas organs from donors younger than 50 years of age and with a body mass index (BMI) less than 30 are allocated for transplantation in the Eurotransplant (ET) area. To address this issue we designed a study to increase the available donor pool for these patients.
METHODS/DESIGN:
This study is a prospective, multicenter (20 German centers), single blinded, non-randomized, two armed trial comparing outcome after SPK, PTA or PAK between organs with the currently allowed donor criteria versus selected organs from donors with extended criteria. Extended donor criteria are defined as organs procured from donors with a BMI of 30 to 34 or a donor age between 50 and 60 years. Immunosuppression is generally standardized using induction therapy with Myfortic, tacrolimus and low dose steroids. In principle, all patients on the waitlist for primary SPK, PTA or PAK are eligible for the clinical trial when they consent to possibly receiving an extended donor criteria organ. Patients receiving an organ meeting the current standard criteria for pancreas allocation (control arm) are compared to those receiving extended criteria organ (study arm); patients are blinded for a follow-up period of one year. The combined primary endpoint is survival of the pancreas allograft and pancreas allograft function after three months, as an early relevant outcome parameter for pancreas transplantation.
DISCUSSION:
The EXPAND Study has been initiated to investigate the hypothesis that locally allocated extended criteria organs can be transplanted with similar results compared to the currently allowed standard ET organ allocation. If our study shows a favorable comparison to standard organ allocation criteria, the morbidity and mortality for patients waiting for transplantation could be reduced in the future.
TRIAL REGISTRATION:
Trial registered at: NCT0138400
In vitro efficacy and safety of a system for sorbent-assisted peritoneal dialysis
In vitro efficacy and safety of a system for sorbent-assisted peritoneal dialysis. Am J Physiol Renal Physiol 319: F162-F170, 2020. First published June 1, 2020; doi:10.1152/ajprenal. 00079.2020.-A system for sorbent-assisted peritoneal dialysis (SAPD) was designed to continuously recirculate dialysate via a tidal mode using a single lumen peritoneal catheter with regeneration of spent dialysate by means of sorbent technology. We hypothesize that SAPD treatment will maintain a high plasma-to-dialysate concentration gradient and increase the mass transfer area coefficient of solutes. Thereby, the SAPD system may enhance clearance while reducing the number of exchanges. Application is envisaged at night as a bedside device (12 kg, nighttime system). A wearable system (2.0 kg, daytime system) may further enhance clearance during the day. Urea, creatinine, and phosphate removal were studied with the daytime and nighttime system (n = 3 per system) by recirculating 2 liters of spent peritoneal dialysate via a tidal mode (mean flow rate: 50 and 100 mL/min, respectively) for 8 h in vitro. Time-averaged plasma clearance over 24 h was modeled assuming one 2 liter exchange/day, an increase in mass transfer area coefficient, and 0.9 liters ultrafiltration/day. Urea, creatinine, and phosphate removal was 33.2 ± 4.1, 5.3 ± 0.5, and 6.2 ± 1.8 mmol, respectively, with the daytime system and 204 ± 28, 10.3 ± 2.4, and 11.4 ± 2.1 mmol, respectively, with the nighttime system. Time-averaged plasma clearances of urea, creatinine and phosphate were 9.6 ± 1.1, 9.6 ± 1.7, and 7.0 ± 0.9 mL/min, respectively, with the nighttime system and 10.8 ± 1.1, 13.4 ± 1.8, and 9.7 ± 1.6 mL/min, respectively, with the daytime and nighttime system. SAPD treatment may improve removal of uremic toxins compared with conventional peritoneal dialysis, provided that peritoneal mass transport will increase
Influence of protein fermentation on gas production profiles
With modern equipment, accurate gas-production profiles can be obtained reflecting the organic-matter fermentation in rumen fluid. Although the gas production caused by fermentation of carbohydrates is well understood and described, ignoring the influence of protein fermentation may lead to misinterpretation of the gas-production data. Gas-production profiles, from grass samples differing in growing days, and hence in protein content, showed an unexpected low gas production for the young samples compared to the old ones. The influence of protein fermentation on gas-production profiles was studied by incubation of mixtures of casein with glucose, Zutkovsky starch and/or potato starch. After prolonged incubation, the fermentation of casein produced only 32% gas compared with carbohydrates and it was calculated that each percentage of protein caused a reduction in gas production of 2.48 ml g-1 organic matter. Relative to potato starch, casein was fermented in an earlier stage of incubation. After correction for the influence of protein fermentation, gas production of the youngest grass sample was the highest and of the oldest sample the lowest. It showed that protein fermentation influenced gas production mainly in the initial hours of incubation, because the major part of protein is part of the soluble fraction. It is concluded that a comparison of gas-production profiles of feed samples differing largely in protein content may lead to a misinterpretation, which necessitates correction for protein fermentation
Influence of protein fermentation on gas production profiles
With modern equipment, accurate gas-production profiles can be obtained reflecting the organic-matter fermentation in rumen fluid. Although the gas production caused by fermentation of carbohydrates is well understood and described, ignoring the influence of protein fermentation may lead to misinterpretation of the gas-production data. Gas-production profiles, from grass samples differing in growing days, and hence in protein content, showed an unexpected low gas production for the young samples compared to the old ones. The influence of protein fermentation on gas-production profiles was studied by incubation of mixtures of casein with glucose, Zutkovsky starch and/or potato starch. After prolonged incubation, the fermentation of casein produced only 32% gas compared with carbohydrates and it was calculated that each percentage of protein caused a reduction in gas production of 2.48 ml g-1 organic matter. Relative to potato starch, casein was fermented in an earlier stage of incubation. After correction for the influence of protein fermentation, gas production of the youngest grass sample was the highest and of the oldest sample the lowest. It showed that protein fermentation influenced gas production mainly in the initial hours of incubation, because the major part of protein is part of the soluble fraction. It is concluded that a comparison of gas-production profiles of feed samples differing largely in protein content may lead to a misinterpretation, which necessitates correction for protein fermentation
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