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Purpose
Image acquisition and subsequent manual analysis of cardiac cine MRI is time-consuming. The purpose of this study was to train and evaluate a 3D artificial neural network for semantic segmentation of radially undersampled cardiac MRI to accelerate both scan time and postprocessing.
Methods
A database of Cartesian short-axis MR images of the heart (148,500 images, 484 examinations) was assembled from an openly accessible database and radial undersampling was simulated. A 3D U-Net architecture was pretrained for segmentation of undersampled spatiotemporal cine MRI. Transfer learning was then performed using samples from a second database, comprising 108 non-Cartesian radial cine series of the midventricular myocardium to optimize the performance for authentic data. The performance was evaluated for different levels of undersampling by the Dice similarity coefficient (DSC) with respect to reference labels, as well as by deriving ventricular volumes and myocardial masses.
Results
Without transfer learning, the pretrained model performed moderately on true radial data [maximum number of projections tested, P = 196; DSC = 0.87 (left ventricle), DSC = 0.76 (myocardium), and DSC =0.64 (right ventricle)]. After transfer learning with authentic data, the predictions achieved human level even for high undersampling rates (P = 33, DSC = 0.95, 0.87, and 0.93) without significant difference compared with segmentations derived from fully sampled data.
Conclusion
A 3D U-Net architecture can be used for semantic segmentation of radially undersampled cine acquisitions, achieving a performance comparable with human experts in fully sampled data. This approach can jointly accelerate time-consuming cine image acquisition and cumbersome manual image analysis.
At the beginning of their foraging careers, Cataglyphis desert ants calibrate their compass systems and learn the visual panorama surrounding the nest entrance. For that, they perform well-structured initial learning walks. During rotational body movements (pirouettes), naïve ants (novices) gaze back to the nest entrance to memorize their way back to the nest. To align their gaze directions, they rely on the geomagnetic field as a compass cue. In contrast, experienced ants (foragers) use celestial compass cues for path integration during food search. If the panorama at the nest entrance is changed, foragers perform re-learning walks prior to heading out on new foraging excursions. Here, we show that initial learning walks and re-learning walks are structurally different. During re-learning walks, foragers circle around the nest entrance before leaving the nest area to search for food. During pirouettes, they do not gaze back to the nest entrance. In addition, foragers do not use the magnetic field as a compass cue to align their gaze directions during re-learning walk pirouettes. Nevertheless, magnetic alterations during re-learning walks under manipulated panoramic conditions induce changes in nest-directed views indicating that foragers are still magnetosensitive in a cue conflict situation.
The negative impact of juvenile undernourishment on adult behavior has been well reported for vertebrates, but relatively little is known about invertebrates. In honeybees, nutrition has long been known to affect task performance and timing of behavioral transitions. Whether and how a dietary restriction during larval development affects the task performance of adult honeybees is largely unknown. We raised honeybees in-vitro, varying the amount of a standardized diet (150 µl, 160 µl, 180 µl in total). Emerging adults were marked and inserted into established colonies. Behavioral performance of nurse bees and foragers was investigated and physiological factors known to be involved in the regulation of social organization were quantified. Surprisingly, adult honeybees raised under different feeding regimes did not differ in any of the behaviors observed. No differences were observed in physiological parameters apart from weight. Honeybees were lighter when undernourished (150 µl), while they were heavier under the overfed treatment (180 µl) compared to the control group raised under a normal diet (160 µl). These data suggest that dietary restrictions during larval development do not affect task performance or physiology in this social insect despite producing clear effects on adult weight. We speculate that possible effects of larval undernourishment might be compensated during the early period of adult life.
Squamous cell carcinomas (SCC) frequently have an exceptionally high mutational burden. As consequence, they rapidly develop resistance to platinum-based chemotherapy and overall survival is limited. Novel therapeutic strategies are therefore urgently required. SCC express ∆Np63, which regulates the Fanconi Anemia (FA) DNA-damage response in cancer cells, thereby contributing to chemotherapy-resistance. Here we report that the deubiquitylase USP28 is recruited to sites of DNA damage in cisplatin-treated cells. ATR phosphorylates USP28 and increases its enzymatic activity. This phosphorylation event is required to positively regulate the DNA damage repair in SCC by stabilizing ∆Np63. Knock-down or inhibition of USP28 by a specific inhibitor weakens the ability of SCC to cope with DNA damage during platin-based chemotherapy. Hence, our study presents a novel mechanism by which ∆Np63 expressing SCC can be targeted to overcome chemotherapy resistance. Limited treatment options and low response rates to chemotherapy are particularly common in patients with squamous cancer. The SCC specific transcription factor ∆Np63 enhances the expression of Fanconi Anemia genes, thereby contributing to recombinational DNA repair and Cisplatin resistance. Targeting the USP28-∆Np63 axis in SCC tones down this DNA damage response pathways, thereby sensitizing SCC cells to cisplatin treatment.
Cuticular hydrocarbons (CHC) are known to serve as discrimination cues and will trigger defence behaviour in a plethora of eusocial insects. However, little is known how about nestmate recognition ability selects for CHC diversification. In this study we investigate differences in CHC composition of four major honey bee species with respect to the differences in their nesting behavior. In contrast to A. mellifera, A. cerana and A. florea, the giant honey bee A. dorsata prefers to build their nests in aggregations with very small spatial distances between nests, which increases the probability of intrusions. Thus, A. dorsata exhibits a particularly challenging nesting behavior which we hypothesize should be accompanied with an improved nestmate recognition system. Comparative analyses of the worker CHC profiles indicate that A. dorsata workers exhibit a unique and more complex CHC profile than the other three honey bee species. This increased complexity is likely based on a developmental process that retains the capability to synthesize methyl-branched hydrocarbons as adults. Furthermore, two sets of behavioral experiments provide evidence that A. dorsata shows an improved nestmate discrimination ability compared to the phylogenetically ancestral A. florea, which is also open-nesting but does not form nest aggregations. The results of our study suggest that ecological traits like nesting in aggregation might be able to drive CHC profile diversification even in closely related insect species.
Background
Localization-based super-resolution microscopy resolves macromolecular structures down to a few nanometers by computationally reconstructing fluorescent emitter coordinates from diffraction-limited spots. The most commonly used algorithms are based on fitting parametric models of the point spread function (PSF) to a measured photon distribution. These algorithms make assumptions about the symmetry of the PSF and thus, do not work well with irregular, non-linear PSFs that occur for example in confocal lifetime imaging, where a laser is scanned across the sample. An alternative method for reconstructing sparse emitter sets from noisy, diffraction-limited images is compressed sensing, but due to its high computational cost it has not yet been widely adopted. Deep neural network fitters have recently emerged as a new competitive method for localization microscopy. They can learn to fit arbitrary PSFs, but require extensive simulated training data and do not generalize well. A method to efficiently fit the irregular PSFs from confocal lifetime localization microscopy combining the advantages of deep learning and compressed sensing would greatly improve the acquisition speed and throughput of this method.
Results
Here we introduce ReCSAI, a compressed sensing neural network to reconstruct localizations for confocal dSTORM, together with a simulation tool to generate training data. We implemented and compared different artificial network architectures, aiming to combine the advantages of compressed sensing and deep learning. We found that a U-Net with a recursive structure inspired by iterative compressed sensing showed the best results on realistic simulated datasets with noise, as well as on real experimentally measured confocal lifetime scanning data. Adding a trainable wavelet denoising layer as prior step further improved the reconstruction quality.
Conclusions
Our deep learning approach can reach a similar reconstruction accuracy for confocal dSTORM as frame binning with traditional fitting without requiring the acquisition of multiple frames. In addition, our work offers generic insights on the reconstruction of sparse measurements from noisy experimental data by combining compressed sensing and deep learning. We provide the trained networks, the code for network training and inference as well as the simulation tool as python code and Jupyter notebooks for easy reproducibility.
Robotic-assisted colon surgery may contain advantages over the laparoscopic approach, but clear evidence is sparse. This study aimed to analyze postoperative inflammation status, short-term outcome and cost-effectiveness of robotic-assisted versus laparoscopic left hemicolectomy. All consecutive patients who received minimal-invasive left hemicolectomy at the Department of Surgery I at the University Hospital of Wuerzburg in 2021 were prospectively included. Importantly, no patient selection for either procedure was carried out. The robotic-assisted versus laparoscopic approaches were compared head to head for postoperative short-term outcomes as well as cost-effectiveness. A total of 61 patients were included, with 26 patients having received a robotic-assisted approach. Baseline characteristics did not differ among the groups. Patients receiving a robotic-assisted approach had a significantly decreased length of hospital stay as well as lower rates of complications in comparison to patients who received laparoscopic surgery (n = 35). In addition, C-reactive protein as a marker of systemic stress response was significantly reduced postoperatively in patients who were operated on in a robotic-assisted manner. Consequently, robotic-assisted surgery could be performed in a cost-effective manner. Thus, robotic-assisted left hemicolectomy represents a safe and cost-effective procedure and might improve patient outcomes in comparison to laparoscopic surgery.
Introduction
Neurotransmitter release at presynaptic active zones (AZs) requires concerted protein interactions within a dense 3D nano-hemisphere. Among the complex protein meshwork the (M)unc-13 family member Unc-13 of Drosophila melanogaster is essential for docking of synaptic vesicles and transmitter release.
Methods
We employ minos-mediated integration cassette (MiMIC)-based gene editing using GFSTF (EGFP-FlAsH-StrepII-TEV-3xFlag) to endogenously tag all annotated Drosophila Unc-13 isoforms enabling visualization of endogenous Unc-13 expression within the central and peripheral nervous system.
Results and discussion
Electrophysiological characterization using two-electrode voltage clamp (TEVC) reveals that evoked and spontaneous synaptic transmission remain unaffected in unc-13\(^{GFSTF}\) 3rd instar larvae and acute presynaptic homeostatic potentiation (PHP) can be induced at control levels. Furthermore, multi-color structured-illumination shows precise co-localization of Unc-13\(^{GFSTF}\), Bruchpilot, and GluRIIA-receptor subunits within the synaptic mesoscale. Localization microscopy in combination with HDBSCAN algorithms detect Unc-13\(^{GFSTF}\) subclusters that move toward the AZ center during PHP with unaltered Unc-13\(^{GFSTF}\) protein levels.
Stalk cell polar ion transport provide for bladder‐based salinity tolerance in Chenopodium quinoa
(2022)
Chenopodium quinoa uses epidermal bladder cells (EBCs) to sequester excess salt. Each EBC complex consists of a leaf epidermal cell, a stalk cell, and the bladder.
Under salt stress, sodium (Na\(^{+}\)), chloride (Cl\(^{−}\)), potassium (K\(^{+}\)) and various metabolites are shuttled from the leaf lamina to the bladders. Stalk cells operate as both a selectivity filter and a flux controller.
In line with the nature of a transfer cell, advanced transmission electron tomography, electrophysiology, and fluorescent tracer flux studies revealed the stalk cell’s polar organization and bladder‐directed solute flow.
RNA sequencing and cluster analysis revealed the gene expression profiles of the stalk cells. Among the stalk cell enriched genes, ion channels and carriers as well as sugar transporters were most pronounced. Based on their electrophysiological fingerprint and thermodynamic considerations, a model for stalk cell transcellular transport was derived.
Background
Colorectal cancer incidence increases with patient age. The aim of this study was to assess, at the nationwide level, in-hospital mortality, and failure to rescue in geriatric patients (≥ 80 years old) with colorectal cancer arising from postoperative complications.
Methods
All patients receiving surgery for colorectal cancer in Germany between 2012 and 2018 were identified in a nationwide database. Association between age and in-hospital mortality following surgery and failure to rescue, defined as death after complication, were determined in univariate and multivariate analyses.
Results
Three lakh twenty-eight thousands two hundred and ninety patients with colorectal cancer were included of whom 77,287 were 80 years or older. With increasing age, a significant relative increase in right hemicolectomy was observed. In general, these patients had more comorbid conditions and higher frailty. In-hospital mortality following colorectal cancer surgery was 4.9% but geriatric patients displayed a significantly higher postoperative in-hospital mortality of 10.6%. The overall postoperative complication rate as well as failure to rescue increased with age. In contrast, surgical site infection (SSI) and anastomotic leakage (AL) did not increase in geriatric patients, whereas the associated mortality increased disproportionately (13.3% for SSI and 29.9% mortality for patients with AI, both p < 0.001). Logistic regression analysis adjusting for confounders showed that geriatric patients had almost five-times higher odds for death after surgery than the baseline age group below 60 (OR 4.86; 95%CI [4.45–5.53], p < 0.001).
Conclusion
Geriatric patients have higher mortality after colorectal cancer surgery. This may be partly due to higher frailty and disproportionately higher rates of failure to rescue arising from postoperative complications.