The introduction of motorized spiral enteroscopy (mSE) into clinical practice holds diagnostic and therapeutic potential for small-bowel investigations. This systematic review and meta-analysis aims ...to evaluate the performance of this modality in diagnosing and treating small-bowel lesions.
A systematic search of MEDLINE, Cochrane, and ClinicalTrials.gov databases were performed through September 2022. The primary outcome was diagnostic success, defined as the identification of a lesion relative to the indication. Secondary outcomes were successful therapeutic manipulation, total enteroscopy rate (examination from the duodenojejunal flexion to the cecum), technical success (passage from the ligament of Treitz or ileocecal valve for anterograde and retrograde approach, respectively), and adverse event rates. We performed meta-analyses using a random-effects model, and the results are reported as percentages with 95% confidence intervals (CIs).
From 2016 to 2022, 9 studies (959 patients; 42% women; mean age >45 years; 474 patients 49.4% investigated for mid-GI bleeding/anemia) were considered eligible and included in analysis. The diagnostic success rate of mSE was 78% (95% CI, 72-84; I2 = 78.3%). Considering secondary outcomes, total enteroscopy was attempted in 460 cases and completed with a rate of 51% (95% CI, 30-72; I2 = 96.2%), whereas therapeutic interventions were successful in 98% of cases (95% CI, 96-100; I2 = 79.8%) where attempted. Technical success rates were 96% (95% CI, 94-97; I2 = 1.5%) for anterograde and 97% (95% CI, 94-100; I2 = 38.6%) for retrograde approaches, respectively. Finally, the incidence of adverse events was 17% (95% CI, 13-21; I2 = 65.1%), albeit most were minor adverse events (16%; 95% CI, 11-20; I2 = 67.2%) versus major adverse events (1%; 95% CI, 0-1; I2 = 0%).
mSE provides high rates of diagnostic and therapeutic success with a low prevalence of severe adverse events.
Background
Vascular complications of severe acute pancreatitis are well known and largely described unlike non-occlusive mesenteric ischemia, which is a rare and potentially fatal complication. ...Non-occlusive mesenteric ischemia is an acute mesenteric ischemia without thrombotic occlusion of blood vessels, poorly described as a complication of acute pancreatitis.
Methods
We retrospectively reviewed a prospectively maintained registry of all pancreatic diseases referred to our center from 2013 to 2018, in order to determine the causes of early death. We identified three patients who died within 48 h after hospital admission from severe acute pancreatitis complicated by irreversible non-occlusive mesenteric ischemia. Their clinical presentation, management, and outcomes were herein reported.
Results
Three consecutive patients with severe acute pancreatitis developed non-occlusive mesenteric ischemia within the first 5 days after onset of symptoms and died 48 h after non-occlusive mesenteric ischemia diagnosis despite optimal intensive care management and surgery, giving a prevalence of 3/609 (0.5%). Symptoms were unspecific with consequently potential delayed diagnosis and management. High doses of norepinephrine required for hemodynamic support (
n
= 3) potentially leading to splanchnic vessels vasoconstriction, transient hypotension (
n
= 3), and previous severe ischemic cardiomyopathy (
n
= 1) could be involved as precipitating factors of non-occlusive mesenteric ischemia.
Conclusion
Non-occlusive mesenteric ischemia can be a fatal complication of acute pancreatitis but is also challenging to diagnose. Priority is to reestablish a splanchno-mesenteric perfusion flow. Surgery should be offered in case of treatment failure or deterioration but is still under debate in early stage, to interrupt the vicious circle of intestinal hypoperfusion and ischemia.
MAIN RECOMMENDATIONS
1
ESGE/EASL recommend that, as the primary diagnostic modality for PSC, magnetic resonance cholangiography (MRC) should be preferred over endoscopic retrograde ...cholangiopancreatography (ERCP).
Moderate quality evidence, strong recommendation.
2
ESGE/EASL suggest that ERCP can be considered if MRC plus liver biopsy is equivocal or contraindicated in patients with persisting clinical suspicion of PSC. The risks of ERCP have to be weighed against the potential benefit with regard to surveillance and treatment recommendations.
Low quality evidence, weak recommendation.
6
ESGE/EASL suggest that, in patients with an established diagnosis of PSC, MRC should be considered before therapeutic ERCP.
Weak recommendation, low quality evidence.
7
ESGE/EASL suggest performing endoscopic treatment with concomitant ductal sampling (brush cytology, endobiliary biopsies) of suspected significant strictures identified at MRC in PSC patients who present with symptoms likely to improve following endoscopic treatment.
Strong recommendation, low quality evidence.
9
ESGE/EASL recommend weighing the anticipated benefits of biliary papillotomy/sphincterotomy against its risks on a case-by-case basis.
Strong recommendation, moderate quality evidence.
Biliary papillotomy/sphincterotomy should be considered especially after difficult cannulation.
Strong recommendation, low quality evidence.
16
ESGE/EASL suggest routine administration of prophylactic antibiotics before ERCP in patients with PSC.
Strong recommendation, low quality evidence.
17
EASL/ESGE recommend that cholangiocarcinoma (CCA) should be suspected in any patient with worsening cholestasis, weight loss, raised serum CA19-9, and/or new or progressive dominant stricture, particularly with an associated enhancing mass lesion.
Strong recommendation, moderate quality evidence.
19
ESGE/EASL recommend ductal sampling (brush cytology, endobiliary biopsies) as part of the initial investigation for the diagnosis and staging of suspected CCA in patients with PSC.
Strong recommendation, high quality evidence.
Computational prediction of ligand–target interactions is a crucial part of modern drug discovery as it helps to bypass high costs and labor demands of in vitro and in vivo screening. As the wealth ...of bioactivity data accumulates, it provides opportunities for the development of deep learning (DL) models with increasing predictive powers. Conventionally, such models were either limited to the use of very simplified representations of proteins or ineffective voxelization of their 3D structures. Herein, we present the development of the PSG-BAR (Protein Structure Graph-Binding Affinity Regression) approach that utilizes 3D structural information of the proteins along with 2D graph representations of ligands. The method also introduces attention scores to selectively weight protein regions that are most important for ligand binding. Results: The developed approach demonstrates the state-of-the-art performance on several binding affinity benchmarking datasets. The attention-based pooling of protein graphs enables identification of surface residues as critical residues for protein–ligand binding. Finally, we validate our model predictions against an experimental assay on a viral main protease (Mpro)—the hallmark target of SARS-CoV-2 coronavirus.
The Construction File (CF) specification establishes a standardized interface for molecular biology operations, laying a foundation for automation and enhanced efficiency in experiment design. It is ...implemented across three distinct software projects: PyDNA_CF_Simulator, a Python project featuring a ChatGPT plugin for interactive parsing and simulating experiments; ConstructionFileSimulator, a field-tested Java project that showcases 'Experiment' objects expressed as flat files; and C6-Tools, a JavaScript project integrated with Google Sheets via Apps Script, providing a user-friendly interface for authoring and simulation of CF. The CF specification not only standardizes and modularizes molecular biology operations but also promotes collaboration, automation, and reuse, significantly reducing potential errors. The potential integration of CF with artificial intelligence, particularly GPT-4, suggests innovative automation strategies for synthetic biology. While challenges such as token limits, data storage, and biosecurity remain, proposed solutions promise a way forward in harnessing AI for experiment design. This shift from human-driven design to AI-assisted workflows, steered by high-level objectives, charts a potential future path in synthetic biology, envisioning an environment where complexities are managed more effectively.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Many articles in “in silico” drug design implemented genetic algorithm (GA) for feature selection, model optimization, conformational search, or docking studies. Some of these articles described GA ...applications to quantitative structure-activity relationships (QSAR) modeling in combination with regression and/or classification techniques. We reviewed the implementation of GA in drug design QSAR and specifically its performance in the optimization of robust mathematical models such as Bayesian-regularized artificial neural networks (BRANNs) and support vector machines (SVMs) on different drug design problems. Modeled data sets encompassed ADMET and solubility properties, cancer target inhibitors, acetylcholinesterase inhibitors, HIV-1 protease inhibitors, ion-channel and calcium entry blockers, and antiprotozoan compounds as well as protein classes, functional, and conformational stability data. The GA-optimized predictors were often more accurate and robust than previous published models on the same data sets and explained more than 65% of data variances in validation experiments. In addition, feature selection over large pools of molecular descriptors provided insights into the structural and atomic properties ruling ligand-target interactions.
Computational screening is key to understanding structure-function relationships at the nanoscale but the high computational cost of accurate electronic structure calculations remains a bottleneck ...for the screening of large nanomaterial libraries. In this work we propose a data-driven strategy to predict accuracy differences between different levels of theory. Machine learning (ML) models are trained with structural features of graphene nanoflakes to predict the differences between electronic properties at two levels of approximation. The ML models yield an overall accuracy of 94% and 88%, for energy of the Fermi level and the band gap, respectively. This strategy represents a successful application of established ML methods to the selection of optimum level of theory, enabling more rapid and efficient screening of nanomaterials, and is extensible to other materials and computational methods.
In Search of European Liberalisms Michael Freeden, Javier Fernández-Sebastián, Jörn Leonhard / Michael Freeden, Javier Fernández-Sebastián, Jörn Leonhard
08/2019, Letnik:
6
eBook
Since the Enlightenment, liberalism as a concept has been
foundational for European identity and politics, even as it has
been increasingly interrogated and contested. This comprehensive
study takes ...a fresh look at the diverse understandings and
interpretations of the idea of liberalism in Europe, encompassing
not just the familiar movements, doctrines, and political parties
that fall under the heading of "liberal" but also the intertwined
historical currents of thought behind them. Here we find not an
abstract, universalized liberalism, but a complex and overlapping
configuration of liberalisms tied to diverse linguistic, temporal,
and political contexts.
Spinocerebellar ataxia type 1 (SCA1) is one of several neurological disorders caused by a CAG repeat expansion. In SCA1, this expansion produces an abnormally long polyglutamine tract in the protein ...ataxin-1. Mutant polyglutamine proteins accumulate in neurons, inducing neurodegeneration, but the mechanism underlying this accumulation has been unclear. We have discovered that the 14-3-3 protein, a multifunctional regulatory molecule, mediates the neurotoxicity of ataxin-1 by binding to and stabilizing ataxin-1, thereby slowing its normal degradation. The association of ataxin-1 with 14-3-3 is regulated by Akt phosphorylation, and in a
Drosophila model of SCA1, both 14-3-3 and Akt modulate neurodegeneration. Our finding that phosphatidylinositol 3-kinase/Akt signaling and 14-3-3 cooperate to modulate the neurotoxicity of ataxin-1 provides insight into SCA1 pathogenesis and identifies potential targets for therapeutic intervention.
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