The aim of our study was to evaluate hyperspectral imaging (HSI) as a rapid, non-ionizing technique for the assessment of organ quality and the prediction of delayed graft function (DGF) in kidney ...transplantation after static cold storage (SCS, n = 20), as well as hypothermic machine perfusion (HMP, n = 18). HSI assessment of the kidney parenchyma was performed during organ preservation and at 10 and 30 min after reperfusion using the TIVITA
Tissue System (Diaspective Vision GmbH, Am Salzhaff, Germany), calculating oxygen saturation (StO
), near-infrared perfusion index (NIR), tissue haemoglobin index (THI), and tissue water index (TWI). Recipient and donor characteristics were comparable between organ preservation groups. Cold ischemic time was significantly longer in the HMP group (14.1 h 3.6-23.1 vs. 8.7h 2.2-17.0,
= 0.002). The overall presence of DGF was comparable between groups (HMP group n = 10 (55.6%), SCS group n = 10 (50.0%)). Prediction of DGF was possible in SCS and HMP kidneys; StO
at 10 (50.00 17.75-76.25 vs. 63.17 27.00-77.75%,
= 0.0467) and 30 min (57.63 18.25-78.25 vs. 65.38 21.25-83.33%,
= 0.0323) after reperfusion, as well as NIR at 10 (41.75 1.0-58.00 vs. 48.63 12.25-69.50,
= 0.0137) and 30 min (49.63 8.50-66.75 vs. 55.80 14.75-73.25,
= 0.0261) after reperfusion were significantly lower in DGF kidneys, independent of the organ preservation method. In conclusion, HSI is a reliable method for intraoperative assessment of renal microperfusion, applicable after organ preservation through SCS and HMP, and predicts the development of DGF.
Normothermic machine perfusion (NMP) is nowadays frequently utilized in liver transplantation. Despite commonly accepted viability assessment criteria, such as perfusate lactate and perfusate pH, ...there is a lack of predictive organ evaluation strategies to ensure graft viability. Hyperspectral imaging (HSI)-as an optical imaging modality increasingly applied in the biomedical field-might provide additional useful data regarding allograft viability and performance of liver grafts during NMP. MethodsTwenty-five deceased donor liver allografts were included in the study. During NMP, graft viability was assessed conventionally and by means of HSI. Images of liver parenchyma were acquired at 1, 2, and 4 h of NMP, and subsequently analyzed using a specialized HSI acquisition software to compute oxygen saturation, tissue hemoglobin index, near-infrared perfusion index, and tissue water index. To analyze the association between HSI parameters and perfusate lactate as well as perfusate pH, we performed simple linear regression analysis. ResultsPerfusate lactate at 1, 2, and 4 h NMP was 1.5 0.3-8.1, 0.9 0.3-2.8, and 0.9 0.1-2.2 mmol/L. Perfusate pH at 1, 2, and 4 h NMP was 7.329 7.013-7.510, 7.318 7.081-7.472, and 7.265 6.967-7.462, respectively. Oxygen saturation predicted perfusate lactate at 1 and 2 h NMP (R2 = 0.1577, P = 0.0493; R2 = 0.1831, P = 0.0329; respectively). Tissue hemoglobin index predicted perfusate lactate at 1, 2, and 4 h NMP (R2 = 0.1916, P = 0.0286; R2 = 0.2900, P = 0.0055; R2 = 0.2453, P = 0.0139; respectively). ConclusionsHSI may serve as a noninvasive tool for viability assessment during NMP. Further evaluation and validation of HSI parameters are warranted in larger sample sizes.
We classify Legendrian unknots in overtwisted contact structures on
S
3
. In particular, we show that up to contact isotopy for every pair
(
n
,
±
(
n
-
1
)
)
with
n
> 0 there are exactly two ...oriented non-loose Legendrian unknots in
S
3
with Thurston–Bennequin invariant
n
and rotation number
±
(
n
-
1
)
. (Only one overtwisted contact structure on
S
3
admits a non-loose unknot
K
and the classical invariants have to be tb(
K
) =
n
and
rot
(
K
)
=
±
(
n
-
1
)
for
n
> 1.)
This can be used to prove two results attributed to Y. Chekanov: The first implies that the contact mapping class group of an overtwisted contact structure on
S
3
depends on the contact structure. The second result is that the identity component of the contactomorphism group of an overtwisted contact structure on
S
3
does not always act transitively on the set of boundaries of overtwisted discs.
We classify Legendrian unknots in overtwisted contact structures on S3. In particular, we show that up to contact isotopy for every pair (n,±(n-1)) with n > 0 there are exactly two oriented non-loose ...Legendrian unknots in S3 with Thurston–Bennequin invariant n and rotation number ±(n-1) . (Only one overtwisted contact structure on S3 admits a non-loose unknot K and the classical invariants have to be tb(K) = n and rot(K)=±(n-1) for n > 1.)This can be used to prove two results attributed to Y. Chekanov: The first implies that the contact mapping class group of an overtwisted contact structure on S3 depends on the contact structure. The second result is that the identity component of the contactomorphism group of an overtwisted contact structure on S3 does not always act transitively on the set of boundaries of overtwisted discs.
Here, we present the case of an 81‐year‐old male patient, who was hospitalized for a severe form of COVID‐19. Transthoracic echocardiogram (TTE) performed 1 month after symptom onset was normal. ...Respiratory evolution was favourable, and the patient was discharged at Day 78. At 6 months, despite a good functional recovery, he presented pulmonary sequelae, and the TTE revealed a clear reduction of left ventricular ejection fraction (LVEF) and mild LV dilatation without cardiac symptoms. The cardiac magnetic resonance (CMR) using Lake Louise Criteria (LLC), T1 and T2 mapping showed focal infero‐basal LV wall oedema, elevated T1 and T2 myocardial relaxation times especially in basal inferior and infero‐lateral LV walls, and sub‐epicardial late gadolinium enhancement in those LV walls. The diagnosis of active myocarditis was raised especially based on TTE abnormalities and CMR LLC, T1 and T2 mapping. Currently, we are not aware of published reports of a 6 month post‐COVID‐19 active myocarditis.
Mafic to intermediate enclaves are evenly distributed throughout the dacitic 1991–1995 lava sequence of Unzen volcano, Japan, representing hundreds of mafic recharge events over the life of the ...volcano. This study documents the morphological, textural, chemical, and petrological characteristics of the enclaves and coexisting silicic host lavas. The eruptive products described in this study appear to be general products of magma mingling, as the same textural types are seen at many other volcanoes. Two types of magmatic enclaves, referred to as Porphyritic and Equigranular, are easily distinguished texturally. Porphyritic enclaves display a wide range in composition from basalt to andesite, are glass-rich, spherical and porphyritic, and contain large, resorbed, plagioclase phenocrysts in a matrix of acicular crystals and glass. Equigranular enclaves are andesitic, non-porphyritic, and consist of tabular, medium-grained microphenocrysts in a matrix glass that is in equilibrium with the host dacite magma. Porphyritic enclaves are produced when intruding basaltic magma engulfs melt and phenocrysts of resident silicic magma at their mutual interface. Equigranular enclaves are a product of a more prolonged mixing and gradual crystallization at a slower cooling rate within the interior of the mafic intrusion.
Different components of the newly defined field of surgical data science have been under research at our groups for more than a decade now. In this paper, we describe our sensor-driven approaches to ...workflow recognition without the need for explicit models, and our current aim is to apply this knowledge to enable context-aware surgical assistance systems, such as a unified surgical display and robotic assistance systems. The methods we evaluated over time include dynamic time warping, hidden Markov models, random forests, and recently deep neural networks, specifically convolutional neural networks.
Identifying potential vulnerable code is important to improve the security of our software systems. However, the manual detection of software vulnerabilities requires expert knowledge and is ...time-consuming, and must be supported by automated techniques.
Such automated vulnerability detection techniques should achieve a high accuracy, point developers directly to the vulnerable code fragments, scale to real-world software, generalize across the boundaries of a specific software project, and require no or only moderate setup or configuration effort.
In this article, we present Vudenc (Vulnerability Detection with Deep Learning on a Natural Codebase), a deep learning-based vulnerability detection tool that automatically learns features of vulnerable code from a large and real-world Python codebase. Vudenc applies a word2vec model to identify semantically similar code tokens and to provide a vector representation. A network of long-short-term memory cells (LSTM) is then used to classify vulnerable code token sequences at a fine-grained level, highlight the specific areas in the source code that are likely to contain vulnerabilities, and provide confidence levels for its predictions.
To evaluate Vudenc, we used 1,009 vulnerability-fixing commits from different GitHub repositories that contain seven different types of vulnerabilities (SQL injection, XSS, Command injection, XSRF, Remote code execution, Path disclosure, Open redirect) for training. In the experimental evaluation, Vudenc achieves a recall of 78%–87%, a precision of 82%–96%, and an F1 score of 80%–90%. Vudenc’s code, the datasets for the vulnerabilities, and the Python corpus for the word2vec model are available for reproduction.
Our experimental results suggest that Vudenc is capable of outperforming most of its competitors in terms of vulnerably detection capabilities on real-world software. Comparable accuracy was only achieved on synthetic benchmarks, within single projects, or on a much coarser level of granularity such as entire source code files.
Mammographic screening and management of breast cancer (BC) in elderly women are controversial and continue to be an important health problem. To investigate, through members of the Senologic ...International Society (SIS), the current global practices in BC in elderly women, highlighting topics of debate and suggesting perspectives.
The questionnaire was sent to the SIS network and included 55 questions on definitions of an elderly woman, BC epidemiology, screening, clinical and pathological characteristics, therapeutic management in elderly women, onco-geriatric assessment and perspectives.
Twenty-eight respondents from 21 countries and six continents, representing a population of 2.86 billion, completed and submitted the survey. Most respondents considered women 70 years and older to be elderly. In most countries, BC was often diagnosed at an advanced stage compared to younger women, and age-related mortality was high. For this reason, participants recommended that personalized screening be continued in elderly women with a long life expectancy.In addition, this survey highlighted that geriatric frailty assessment tools and comprehensive geriatric evaluations needed to be used more and should be developed to avoid undertreatment. Similarly, multidisciplinary meetings dedicated to elderly women with BC should be encouraged to avoid under- and over-treatment and to increase their participation in clinical trials.
Due to increased life expectancy, BC in elderly women will become a more important field in public health. Therefore, screening, personalized treatment, and comprehensive geriatric assessment should be the cornerstones of future practice to avoid the current excess of age-related mortality. This survey described, through members of the SIS, a global picture of current international practices in BC in elderly women.
Replica exchange (RE) is one of the most popular enhanced-sampling simulations technique in use today. Despite widespread successes, RE simulations can sometimes fail to converge in practical amounts ...of time, e.g., when sampling around phase transitions, or when a few hard-to-find configurations dominate the statistical averages. We introduce a generalized RE scheme, density-of-states-informed RE, that addresses some of these challenges. The key feature of our approach is to inform the simulation with readily available, but commonly unused, information on the density of states of the system as the RE simulation proceeds. This enables two improvements, namely, the introduction of resampling moves that actively move the system towards equilibrium and the continual adaptation of the optimal temperature set. As a consequence of these two innovations, we show that the configuration flow in temperature space is optimized and that the overall convergence of RE simulations can be dramatically accelerated.
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