9 research outputs found
The cancer genome atlas - TCGA molecular classification: A changing paradigm in the management of endometrial cancers
No full textConventionally, endometrial cancers have been risk-stratified as per the clinco-pathological factors. The Cancer Genome Atlas project identified four distinct molecular subtypes within endometrial cancers which further lead to the clinical validation of molecular classification by various research groups. The molecular classification has influenced the risk stratification, thereby impacting adjuvant treatment decisions and prognostication. Molecular classification has paved the precision oncology in gynaecological cancers further strengthening the ongoing advances in targeted therapies and immunotherapy. This review elaborately presents the development of a new molecular classification of endometrial cancers; its evidence-based clinical utility with a brief overview of future perspectives
Clinical presentations, pregnancy complications, and maternal outcomes in pregnant women with COVID‐19 and tuberculosis: A retrospective cohort study
No full text
Growth of single-wall carbon nanotubes by chemical vapor deposition for electrical devices
No full textCarbon emerges in di®erent forms. Diamond and graphite have been well known mate-
rials for centuries. Moreover fullerenes and nanotubes were discovered only a few years ago.
H. W. Kroto et al. depicted the fullerenes in 1985 [1]. A few years later, in 1991, S. Iijima
described carbon nanotubes (CNTs) for the ¯rst time [2] (Figure 1.1).
CNTs have a close relation to graphite, since a single-wall carbon nanotube is like a rolled-up
graphite mono layer. However a nanotube has with its curved shape a higher chemical reacti-
vity than a °at graphite layer. Both the side wall and the caps can be modi¯ed chemically [3].
Carbon nanotubes are regular carbon clusters with attractive mechanical and electronic pro-
perties [4]. Nanotubes have a high mechanical strength due to a very large Young's modu-
lus [5]. They can be used for the storage of hydrogen [5, 6], to store energy in electrochemical
double layer capacitors [7] or to reinforce composite materials [3]. A single nanotube can be
used as a sensor [8{12], a nanorelay [13], a vessel [14] or as a template [3, 15]. It is possible
to produce light bulbs [16] and ¯bers [17] with carbon nanotubes. An array of CNTs can act
as a °at panel display [3, 5] using their feature to act as ¯eld emitting devices [18{21].
CNTs are either metallic (1/3) or semiconducting (2/3). Nowadays it is not possible to select
the desired characteristic of a nanotube in advance. It is only possible to separate metallic
from semiconducting tubes by using an electrical ¯eld [22]. Metallic nanotubes with their
diameter of a few nm represent the ultimate conducting wire whereas the semiconducting
ones can be used as transistors [23{25] even on a transparent and °exible substrate [26]. The
transistors can be optimized by the chemical control of the nanotube-electrode interface [27].
Quantum dots [28, 29] and spin valves [30{32] can be built alike simple logic gates [33] and a
Y-junction recti¯er [34].
Carbon nanotubes have a very interesting property: they are "1-dimensional" molecules [35].
This has to be explained in a few words. In general, quantum con¯nement leads to a spacing
of the allowed eigenenergies. Electrons cannot hop into a higher energy level if the thermal
energy is much smaller than this energy di®erence. In a nanotube an electron is con¯ned in the
directions perpendicular to the tube axis. The nanotube becomes a 1-dimensional conductor.
For several years members of our research group are exploring the electrical properties of
this very special conductor. The behavior of carbon nanotubes is investigated with electrical
transport measurements at low temperatures (down to 50 mK) and in high magnetic ¯elds
(up to 10 T).
The raw material for the ¯rst experiments [36{38] were multi-wall carbon nanotubes ob-
tained from L. Forr¶o (Ecole Polytechnique F¶ed¶erale de Lausanne) which were produced using
laser ablation. The multi-wall carbon nanotubes were used to investigate the suppression of
tunnelling [36, 39], multiple Andreev re°ection [28, 37], electrical spin injection [30{32] and
quantum dots [37, 40{43].
The next step was to grow single-wall carbon nanotubes using chemical vapor deposition
(CVD) [8,44{46]. This procedure has the advantage to be faster than an external collaboration
and in addition the growth of the tubes directly on the device makes the samples ready for
use without an additional treatment.
It was veri¯ed that the CVD grown tubes are suitable of for electrical devices [47]. Vibrating
nanotubes [48] and an ambipolar ¯eld-e®ect transistor [23] were studied. Kondo e®ect [49]
and Fano-Resonances [50] were investigated as well.
The latter experiments reveal one common de¯ciency. The grown tubes are often not sepa-
rated but bundled [47] (Figure 6.10). Moreover it is not clear if they are multi- or single-wall
tubes. This means for electronic transport measurements that several tubes are measured si-
multaneously. Thus the tube with the best conductivity dominates the measurement, whereas
the other tubes perturb the measured signal by there presence.
The main focus of this thesis is the development of a growth process of single-wall carbon
nanotubes by using CVD. The aim is to overcome the problem of bundling. The grown
nanotubes have to be free of lattice defects and they need to have good electrode-nanotube
contacts in order to make them suitable for electronic transport measurements. They have
to lay °at, well separated and optimally distributed on SiO2 our standard substrate. On the
one hand the tube density should not be too high since this would increase the probability
of shortcuts between the electrodes due to nanotube-nanotube contacts. On the other hand
it should not be too low since this would make the localization of an appropriate nanotube
much more time consuming (Figure 1.2).
Two ways to achieve this goal were tried. The single-wall nanotubes can be bought, dissolved
in a solvent and spread after cleaning and separation [51{57], as in the thesis [46]. The second
possibility is to grow the tubes directly on the device as presented in this thesis.
Growing carbon nanotubes with CVD is very simple, at least in principle. There are only
a few essential things needed: an oven, a substrate, a catalyst and a carbon feedstock. The
main challenge is to acquire the right knowhow.
The ¯rst step was to build up the CVD system. Afterwards the proper growth conditions
and a simple method to check the demanded properties of the grown tubes had to be found.
Scanning electron microscopy (SEM) is the standard characterization tool used in this thesis.
Transmission electron microscopy (TEM) is a helpful mean in order to show that the tubes
are separated and single-wall, since it allows the investigation of the tubes' internal structure.
Atomic force microscopy (AFM) and Raman spectroscopy are used in addition.
Outline of this thesis
² Chapter 2 gives a short overview with respect to the properties, the growth and the
characterization of carbon nanotubes.
² The oven and the gas system are delineated in Chapter 3. Di®erent carbon feedstocks
were used: ethylene/hydrogen, methane, methane/ethylene and methane/hydrogen.
² The steps towards a suitable catalyst are presented in Chapter 4. Evaporated and
liquid based catalysts were tested. An iron molybdenum alumina catalyst dissolved in
2-propanol provides the best results.
² Chapter 5 gives a comparison of the results obtained utilizing di®erent growth processes,
and describes the formation of amorphous carbon and the oxidation of nanotubes.
² Chapter 6 summarizes experiments on di®erent TEM grids (Au, Cu, Mo, Ni, stainless
steel, Ti, quantifoils) and silicon nitride windows.
² The results from collaborations with other group members are presented in Chapter 7.
These experiments show the good quality of the grown tubes
Child neurodevelopment after multidomain interventions from preconception through early childhood
No full textImportanceMultidomain interventions in pregnancy and early childhood have improved child neurodevelopment, but little is known about the effects of additional preconception interventions.ObjectiveTo evaluate the effect of a multifaceted approach including health; nutrition; water, sanitation, and hygiene (WASH); and psychosocial support interventions delivered during the preconception period and/or during pregnancy and early childhood on child neurodevelopment.Design, Setting, and ParticipantsIn this randomized trial involving low- and middle-income neighborhoods in Delhi, India, 13 500 participants were assigned to preconception interventions or routine care for the primary outcome of preterm births and childhood growth. Participants who became pregnant were randomized to pregnancy and early childhood interventions or routine care. Neurodevelopmental assessments, the trial’s secondary outcome reported herein, were conducted in a subsample of children at age 24 months, including 509 with preconception, pregnancy, and early childhood interventions; 473 with preconception interventions alone; 380 with pregnancy and early childhood interventions alone; and 350 with routine care. This study was conducted from November 1, 2020, through February 25, 2022.InterventionsHealth, nutrition, psychosocial care and support, and WASH interventions delivered during preconception, pregnancy, and early childhood periods.Main Outcomes and MeasuresCognitive, motor, language, and socioemotional performance at age 24 months, assessed using the Bayley Scales of Infant and Toddler Development 3 tool.ResultsThe mean age of participants at enrollment was 23.8 years (SD, 3.0 years). Compared with the controls at age 24 months, children in the preconception intervention groups had higher cognitive scores (mean difference [MD], 1.16; 98.3% CI, 0.18-2.13) but had similar language, motor, and socioemotional scores as controls. Those receiving pregnancy and early childhood interventions had higher cognitive (MD, 1.48; 98.3% CI, 0.49-2.46), language (MD, 2.29; 98.3% CI, 1.07-3.50), motor (MD, 1.53; 98.3% CI, 0.65-2.42), and socioemotional scores (MD, 4.15; 98.3% CI, 2.18-6.13) than did controls. The pregnancy and early childhood group also had lower incidence rate ratios (RRs) of moderate to severe delay in cognitive (incidence RR, 0.62; 98.3% CI, 0.40-0.96), language (incidence RR, 0.73; 98.3% CI, 0.57-0.93), and socioemotional (incidence RR, 0.49; 98.3% CI, 0.24-0.97) development than did those in the control group. Children in the preconception, pregnancy, and early childhood intervention group had higher cognitive (MD, 2.60; 98.3% CI, 1.08-4.12), language (MD, 3.46; 98.3% CI, 1.65-5.27), motor (MD, 2.31; 98.3% CI, 0.93-3.69), and socioemotional (MD, 5.55; 98.3% CI, 2.66-8.43) scores than did those in the control group.Conclusions and RelevanceMultidomain interventions during preconception, pregnancy and early childhood led to modest improvements in child neurodevelopment at 24 months. Such interventions for enhancing children’s development warrant further evaluation
Validation of the OAKS prognostic model for acute kidney injury after gastrointestinal surgery
No full text© The Author(s) 2022. Published by Oxford University Press on behalf of BJS Society Ltd.Background: Postoperative acute kidney injury (AKI) is a common complication of major gastrointestinal surgery with an impact on short- and long-term survival. No validated system for risk stratification exists for this patient group. This study aimed to validate externally a prognostic model for AKI after major gastrointestinal surgery in two multicentre cohort studies. Methods: The Outcomes After Kidney injury in Surgery (OAKS) prognostic model was developed to predict risk of AKI in the 7 days after surgery using six routine datapoints (age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker). Validation was performed within two independent cohorts: a prospective multicentre, international study (‘IMAGINE’) of patients undergoing elective colorectal surgery (2018); and a retrospective regional cohort study (‘Tayside’) in major abdominal surgery (2011–2015). Multivariable logistic regression was used to predict risk of AKI, with multiple imputation used to account for data missing at random. Prognostic accuracy was assessed for patients at high risk (greater than 20 per cent) of postoperative AKI. Results: In the validation cohorts, 12.9 per cent of patients (661 of 5106) in IMAGINE and 14.7 per cent (106 of 719 patients) in Tayside developed 7-day postoperative AKI. Using the OAKS model, 558 patients (9.6 per cent) were classified as high risk. Less than 10 per cent of patients classified as low-risk developed AKI in either cohort (negative predictive value greater than 0.9). Upon external validation, the OAKS model retained an area under the receiver operating characteristic (AUC) curve of range 0.655–0.681 (Tayside 95 per cent c.i. 0.596 to 0.714; IMAGINE 95 per cent c.i. 0.659 to 0.703), sensitivity values range 0.323–0.352 (IMAGINE 95 per cent c.i. 0.281 to 0.368; Tayside 95 per cent c.i. 0.253 to 0.461), and specificity range 0.881–0.890 (Tayside 95 per cent c.i. 0.853 to 0.905; IMAGINE 95 per cent c.i. 0.881 to 0.899). Conclusion: The OAKS prognostic model can identify patients who are not at high risk of postoperative AKI after gastrointestinal surgery with high specificity
