Neochordal implantation is a common form of surgical mitral valve (MV) repair. However, neochord length is assessed using static left ventricular pressurization, leading surgeons to evaluate leaflet coaptation and valve competency when the left ventricle is dilating instead of contracting physiologically, referred to as diastolic phase inversion (DPI). We hypothesize that the difference in papillary muscle (PM) positioning between DPI and physiologic systole results in miscalculated neochord lengths, which might affect repair performance.

Porcine MVs (n=6) were mounted in an exvivo heart simulator and PMs were affixed to robots that accurately simulate PM motion. Baseline hemodynamic and chordal strain data were collected, after which P2 chordae were severed to simulate posterior leaflet prolapse from chordal rupture and subsequent mitral regurgitation. Neochord implantation was performed in the physiologic and DPI static configurations.

Although both repairs successfully reduced mitral regurgitation, tinal shortening of neochordae might positively affect MV repair performance and durability by reducing load on surrounding native chordae.

Open correction of pectus deformities has evolved since its origin. We performed a Ravitch type repair using a permanent titanium plate fixed with screws and describe the procedure with outcomes after our modifications.

A retrospective review of 61 pectus excavatum and pectus carinatum cases from August 2013 to April 2021 was performed. Data were extracted from medical records and reported. In January 2016, we began administering satisfaction surveys at the 6-month postoperative visit; results are reported.

The mean age of our cohort was 24.5years; 43 (70%) were male. Fifty-four underwent pectus excavatum repair, 6 pectus carinatum repair, and 1 mixed repair. Median Haller index was 3.8. Mean operative duration was 98minutes; mean blood loss was 116.4mL. Median chest tube duration was 5.0days; median hospital stay was 4days. Reexploration for bleeding was 30% in the first 10 patients. Protocol changes including postponing chemical deep vein thrombosis prophylaxis, using intraoperative hemostatic agents, and using shorter implantation screws decreased this to 0% for the remaining cases. The most frequent complication was urinary retention (21.3%). Postoperative surveys were completed for 37 of 50 patients. Seventy-five percent reported health improved, 65% reported exercise capacity improved, 75% reported breathing improved, and 59% reported chest pain improved. Self-esteem improved from 6.6±2.5 (of 10) before surgery to 8.2±2.1 after surgery. Ninety percent were satisfied and 86% would have the operation again.

Ravitch type repair with permanent titanium plate fixation is a safe and effective procedure for correction of pectus excavatum and carinatum. Most patients experience improvement in preoperative symptoms.

Ravitch type repair with permanent titanium plate fixation is a safe and effective procedure for correction of pectus excavatum and carinatum. Most patients experience improvement in preoperative symptoms.

Postoperative heart block is a significant problem in congenital heart surgery because of the unpredictability and variability of conduction tissue location in complex congenital heart defects. A novel technique for intraoperative conduction system mapping during complex congenital heart surgery is described.

Intraoperative conduction system mapping was performed utilizing a high-density multielectrode grid catheter to collect intracardiac electrograms on open, beating hearts during repair of complex congenital heart defects. Electrograms were interpreted by electrophysiologists, and conduction tissue location was communicated in real time to the surgeon. After localizing conduction tissue, the heart was arrested and the repair was completed taking care to avoid injury to the mapped conduction system.

Two patients with complex heterotaxy syndrome underwent intraoperative conduction mapping during biventricular repair. Mapping accurately identified the location of conduction tissue thereby enabling avoidance of conduction system injury during surgery. Notably, conduction was unexpectedly found to be located inferiorly in a patient with L-looped ventricles. Successful biventricular repair was accomplished in both patients without injury to the conduction system.

Intraoperative conduction mapping can effectively localize the conduction system during surgery and enable the surgeon to avoid its injury. This can lower the risk of heart block requiring pacemaker in children undergoing complex congenital heart surgery.

Intraoperative conduction mapping can effectively localize the conduction system during surgery and enable the surgeon to avoid its injury. This can lower the risk of heart block requiring pacemaker in children undergoing complex congenital heart surgery.

To evaluate the effectiveness of the 5-minute test (FMT), developed to record the amount of pericardial bleeding in patients undergoing general cardiac surgery, and determine the relationship between this test and postcardiotomy bleeding.

The medical records of 573 patients who underwent adult cardiac surgery between January 2016 and December 2019 were reviewed retrospectively. Patients were divided into 2 groups the FMT group included patients who underwent general cardiac surgery between January 2018 and December 2019 (n=278), and the control group included patients who underwent general cardiac surgery between January 2016 and December 2017 (n=295). The postcardiotomy reexploration rate due to intrapericardial bleeding or cardiac tamponade within 1week after surgery and the amount of bleeding until 2days after surgery were compared. The FMT procedure involved counting the amount of bleeding by packing 4 to 6 surgical gauze sheets for 5minutes. Sternal closure was performed when the amount of blood measured by the FMT was <100g.

Compared with the control group, the FMT group had a significantly lower incidence of postcardiotomy reexploration (1.5% vs 5.7%;

=.007) and a reduced amount of bleeding after cardiac surgery (median, 1165mL [interquartile range (IQR), 756.2-1743.8mL] versus 1440mL [IQR, 825.0-2130.0mL];

=.005). There was a significant positive correlation between the FMT gauze sheet weight and postcardiotomy bleeding (

=0.322;

<.001).

The FMT is an objective and effective tool for estimating postoperative bleeding during cardiac surgery that can prevent postcardiotomy reexploration and reduce the amount of postcardiotomy bleeding.

The FMT is an objective and effective tool for estimating postoperative bleeding during cardiac surgery that can prevent postcardiotomy reexploration and reduce the amount of postcardiotomy bleeding.The determination of charged particle trajectories in collisions at the CERN Large Hadron Collider (LHC) is an important but challenging problem, especially in the high interaction density conditions expected during the future high-luminosity phase of the LHC (HL-LHC). Graph neural networks (GNNs) are a type of geometric deep learning algorithm that has successfully been applied to this task by embedding tracker data as a graph-nodes represent hits, while edges represent possible track segments-and classifying the edges as true or fake track segments. However, their study in hardware- or software-based trigger applications has been limited due to their large computational cost. In this paper, we introduce an automated translation workflow, integrated into a broader tool called hls4ml, for converting GNNs into firmware for field-programmable gate arrays (FPGAs). We use this translation tool to implement GNNs for charged particle tracking, trained using the TrackML challenge dataset, on FPGAs with designs targeting different graph sizes, task complexites, and latency/throughput requirements. This work could enable the inclusion of charged particle tracking GNNs at the trigger level for HL-LHC experiments.Many scientific systems are studied using computer codes that simulate the phenomena of interest. Computer simulation enables scientists to study a broad range of possible conditions, generating large quantities of data at a faster rate than the laboratory. Computer models are widespread in neuroscience, where they are used to mimic brain function at different levels. These models offer a variety of new possibilities for the neuroscientist, but also numerous challenges, such as where to sample the input space for the simulator, how to make sense of the data that is generated, and how to estimate unknown parameters in the model. Statistical emulation can be a valuable complement to simulator-based research. Emulators are able to mimic the simulator, often with a much smaller computational burden and they are especially valuable for parameter estimation, which may require many simulator evaluations. This work compares different statistical models that address these challenges, and applies them to simulations of neocortical L2/3 large basket cells, created and run with the NEURON simulator in the context of the European Human Brain Project. The novelty of our approach is the use of fast empirical emulators, which have the ability to accelerate the optimization process for the simulator and to identify which inputs (in this case, different membrane ion channels) are most influential in affecting simulated features. These contributions are complementary, as knowledge of the important features can further improve the optimization process. Subsequent research, conducted after the process is completed, will gain efficiency by focusing on these inputs.Monitoring, predicting, and controlling the air quality in urban areas is one of the effective solutions for tackling the climate change problem. Leveraging the availability of big data in different domains like pollutant concentration, urban traffic, aerial imagery of terrains and vegetation, and weather conditions can aid in understanding the interactions between these factors and building a reliable air quality prediction model. This research proposes a novel cost-effective and efficient air quality modeling framework including all these factors employing state-of-the-art artificial intelligence techniques. The framework also includes a novel deep learning-based vegetation detection system using aerial images. The pilot study conducted in the UK city of Cambridge using the proposed framework investigates various predictive models ranging from statistical to machine learning and deep recurrent neural network models. This framework opens up possibilities of broadening air quality modeling and prediction to other domains like vegetation or green space planning or green traffic routing for sustainable urban cities. The research is mainly focused on extracting strong pieces of evidence which could be useful in proposing better policies around climate change.The need for accurate yield estimates for viticulture is becoming more important due to increasing competition in the wine market worldwide. One of the most promising methods to estimate the harvest is berry counting, as it can be approached non-destructively, and its process can be automated. In this article, we present a method that addresses the challenge of occluded berries with leaves to obtain a more accurate estimate of the number of berries that will enable a better estimate of the harvest. We use generative adversarial networks, a deep learning-based approach that generates a highly probable scenario behind the leaves exploiting learned patterns from images with non-occluded berries. Our experiments show that the estimate of the number of berries after applying our method is closer to the manually counted reference. In contrast to applying a factor to the berry count, our approach better adapts to local conditions by directly involving the appearance of the visible berries. Furthermore, we show that our approach can identify which areas in the image should be changed by adding new berries without explicitly requiring information about hidden areas.