Multiple biological processes are driven by oscillatory gene expression at different time scales. Pulsatile dynamics are thought to be widespread, and single-cell live imaging of gene expression has ...lead to a surge of dynamic, possibly oscillatory, data for different gene networks. However, the regulation of gene expression at the level of an individual cell involves reactions between finite numbers of molecules, and this can result in inherent randomness in expression dynamics, which blurs the boundaries between aperiodic fluctuations and noisy oscillators. This underlies a new challenge to the experimentalist because neither intuition nor pre-existing methods work well for identifying oscillatory activity in noisy biological time series. Thus, there is an acute need for an objective statistical method for classifying whether an experimentally derived noisy time series is periodic. Here, we present a new data analysis method that combines mechanistic stochastic modelling with the powerful methods of non-parametric regression with Gaussian processes. Our method can distinguish oscillatory gene expression from random fluctuations of non-oscillatory expression in single-cell time series, despite peak-to-peak variability in period and amplitude of single-cell oscillations. We show that our method outperforms the Lomb-Scargle periodogram in successfully classifying cells as oscillatory or non-oscillatory in data simulated from a simple genetic oscillator model and in experimental data. Analysis of bioluminescent live-cell imaging shows a significantly greater number of oscillatory cells when luciferase is driven by a Hes1 promoter (10/19), which has previously been reported to oscillate, than the constitutive MoMuLV 5' LTR (MMLV) promoter (0/25). The method can be applied to data from any gene network to both quantify the proportion of oscillating cells within a population and to measure the period and quality of oscillations. It is publicly available as a MATLAB package.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Objective
Quantitative data on visual outcomes after trans-sphenoidal surgery is lacking in the literature. This study aims to address this by quantitatively assessing visual field outcomes after ...endoscopic trans-sphenoidal pituitary adenectomy using the capabilities of modern semi-automated kinetic perimetry.
Methods
Visual field area (deg
2
) calculated on perimetry performed before and after surgery was statistically analysed. Functional improvement was assessed against UK driving standards.
Results
Sixty-four patients (128 eyes) were analysed (May 2016–Nov 2019). I4e and I3e isopter area significantly increased after surgery (
p
< 0.0001). Of eyes with pre-operative deficits: 80.7% improved and 7.9% worsened; the median amount of improvement was 60% (IQR 6–246%). Median increase in I4e isopter was 2213deg
2
(IQR 595–4271deg
2
) and in I3e isopter 1034 deg
2
(IQR 180–2001 deg
2
). Thirteen out of fifteen (87%) patients with III4e data regained driving eligibility after surgery. Age and extent of resection (EOR) did not correlate with visual improvement. Better pre-operative visual field area correlated with a better post-operative area (
p
< 0.0001). However, the rate of improvement in the visual field area increased with poorer pre-operative vision (
p
< 0.0001).
Conclusions
A median visual field improvement of 60% may be expected in over 80% of patients. Functionally, a significant proportion of patients can expect to regain driving eligibility. EOR did not impact on visual recovery. When the primary goal of surgery is alleviating visual impairment, optic apparatus decompression without the aim for gross total resection appears a valid strategy. Patients with the worst pre-operative visual field often experience the greatest improvement, and therefore, poor pre-operative vision alone should not preclude surgical intervention.
We have developed a method for assembling genetic pathways for expression in Saccharomyces cerevisiae. Our pathway assembly method, called VEGAS (Versatile genetic assembly system), exploits the ...native capacity of S. cerevisiae to perform homologous recombination and efficiently join sequences with terminal homology. In the VEGAS workflow, terminal homology between adjacent pathway genes and the assembly vector is encoded by 'VEGAS adapter' (VA) sequences, which are orthogonal in sequence with respect to the yeast genome. Prior to pathway assembly by VEGAS in S. cerevisiae, each gene is assigned an appropriate pair of VAs and assembled using a previously described technique called yeast Golden Gate (yGG). Here we describe the application of yGG specifically to building transcription units for VEGAS assembly as well as the VEGAS methodology. We demonstrate the assembly of four-, five- and six-gene pathways by VEGAS to generate S. cerevisiae cells synthesizing β-carotene and violacein. Moreover, we demonstrate the capacity of yGG coupled to VEGAS for combinatorial assembly.
Uncontrolled hemorrhage from vessel injuries within the torso remains a significant source of prehospital trauma mortality. Resuscitative endovascular balloon occlusion of the aorta can effectively ...control noncompressible hemorrhage, but this minimally invasive technique relies heavily on imaging not available in the field. Our goal was to develop morphometric roadmaps to enhance the safety and accuracy of fluoroscopy-free endovascular navigation of hemorrhage control devices.
Three-dimensional reconstructions of computed tomographic angiography scans from 122 trauma patients (mean SD age, 47 24 years; range 5-93 years; 64 males; 58 females) were used to measure centerline distances from femoral artery access sites to the major aortic branch artery origins. Morphometric roadmap equations were created using multiple linear regression analysis to predict distances to the origins of the major arteries in the chest, abdomen, and pelvis using torso length, demographics, and risk factors as independent variables. A 40-mm-long occlusion balloon was then virtually deployed targeting Zones 1 and 3 of the aorta using these equations. Balloon placement accuracy was determined by comparing predicted versus actual measured distances to the target zone locations within the aortas from the database.
Torso length and age were the strongest predictors of centerline distances from femoral artery access sites to the major artery origins. Male sex contributed to longer distances, while diabetes and smoking were associated with shorter distances. Hypertension, dyslipidemia, and coronary artery disease had no effect. With the use of morphometric roadmaps, virtual occlusion balloon placement accuracy was 100% for Zone 3 of the aorta, compared with 87% accuracy when using torso length alone.
Morphometric roadmaps demonstrate a potential for improving the safety and accuracy of fluoroscopy-free aortic occlusion balloon delivery. Continued development of minimally invasive hemorrhage control techniques holds promise to improve prehospital mortality for patients with noncompressible exsanguinating torso injuries.
Therapeutic study, level IV; diagnostic study, level III.
Major histocompatibility complex (MHC)–bound peptides that originate from tumor-specific genetic alterations, known as neoantigens, are an important class of anticancer therapeutic targets. ...Accurately predicting peptide presentation by MHC complexes is a key aspect of discovering therapeutically relevant neoantigens. Technological improvements in mass spectrometry–based immunopeptidomics and advanced modeling techniques have vastly improved MHC presentation prediction over the past 2 decades. However, improvement in the accuracy of prediction algorithms is needed for clinical applications like the development of personalized cancer vaccines, the discovery of biomarkers for response to immunotherapies, and the quantification of autoimmune risk in gene therapies. Toward this end, we generated allele-specific immunopeptidomics data using 25 monoallelic cell lines and created Systematic Human Leukocyte Antigen (HLA) Epitope Ranking Pan Algorithm (SHERPA), a pan-allelic MHC-peptide algorithm for predicting MHC-peptide binding and presentation. In contrast to previously published large-scale monoallelic data, we used an HLA-null K562 parental cell line and a stable transfection of HLA allele to better emulate native presentation. Our dataset includes five previously unprofiled alleles that expand MHC diversity in the training data and extend allelic coverage in underprofiled populations. To improve generalizability, SHERPA systematically integrates 128 monoallelic and 384 multiallelic samples with publicly available immunoproteomics data and binding assay data. Using this dataset, we developed two features that empirically estimate the propensities of genes and specific regions within gene bodies to engender immunopeptides to represent antigen processing. Using a composite model constructed with gradient boosting decision trees, multiallelic deconvolution, and 2.15 million peptides encompassing 167 alleles, we achieved a 1.44-fold improvement of positive predictive value compared with existing tools when evaluated on independent monoallelic datasets and a 1.17-fold improvement when evaluating on tumor samples. With a high degree of accuracy, SHERPA has the potential to enable precision neoantigen discovery for future clinical applications.
Display omitted
•Generated 25 stably transfected monoallelic cell lines and applied immunopeptidomics.•Harmonized 512 public immunopeptidomic samples through systematic reprocessing.•Developed pan-allele MHC binding algorithm (SHERPA) utilizing 167 human HLA alleles.•Employed empirically derived antigen-processing features to predict MHC presentation.•SHERPA demonstrates up to 1.44-fold increased precision over competing algorithms.
Accurately identifying neoantigens is critical for many clinical applications. We generated immunopeptidomics data from 25 stably transfected monoallelic cell lines. Then, we systematically reprocessed a large corpus of public data to improve MHC binding pocket diversity and to empirically learn the rules of antigen presentation. In applying these datasets, we trained SHERPA, an MHC binding and presentation prediction algorithm. SHERPA improves performance compared with existing tools by 1.44-fold in held-out monoallelic data and 1.11-fold for known immunogenic epitopes.
ObjectivesPostoperative mortality is a widely used quality indicator, but it may be unreliable when procedure numbers and/or mortality rates are low, due to insufficient statistical power. The ...objective was to investigate the statistical validity of postoperative 30-day mortality as a quality metric for neurosurgical practice across healthcare providers.DesignRetrospective cohort study.SettingHospital Episode Statistics data from all neurosurgical units in England.ParticipantsPatients who underwent neurosurgical procedures between April 2013 and March 2018. Procedures were grouped using the National Neurosurgical Audit Programme classification.Outcomes measuredNational 30-day postoperative mortality rates were calculated for elective and non-elective neurosurgical procedural groups. The study estimated the proportion of neurosurgeons and NHS trusts in England that performed sufficient procedures in 3-year and 5-year periods to detect unusual performance (defined as double the national rate of mortality). The actual difference in mortality rates that could be reliably detected based on procedure volumes of neurosurgeons and units over a 5-year period was modelled.ResultsThe 30-day mortality rates for all elective and non-elective procedures were 0.4% and 6.1%, respectively. Only one neurosurgeon in England achieved the minimum sample size (n=2402) of elective cases in 5 years needed to detect if their mortality rate was double the national average. All neurosurgical units achieved the minimum sample sizes for both elective (n=2402) and non-elective (n=149) procedures. In several neurosurgical subspecialties, approximately 80% of units (or more) achieved the minimum sample sizes needed to detect if their mortality rate was double the national rate, including elective neuro-oncology (baseline mortality rate=2.3%), non-elective neuro-oncology (rate=5.7%), neurovascular (rate=6.7%) and trauma (rate=11%).ConclusionPostoperative mortality lacks statistical power as a measure of individual neurosurgeon performance. Neurosurgical units in England performed sufficient procedure numbers overall and in several subspecialty areas to support the use of mortality as a quality indicator.
Recent studies suggest that cells make stochastic choices with respect to differentiation or division. However, the molecular mechanism underlying such stochasticity is unknown. We previously ...proposed that the timing of vertebrate neuronal differentiation is regulated by molecular oscillations of a transcriptional repressor, HES1, tuned by a post-transcriptional repressor, miR-9. Here, we computationally model the effects of intrinsic noise on the
/miR-9 oscillator as a consequence of low molecular numbers of interacting species, determined experimentally. We report that increased stochasticity spreads the timing of differentiation in a population, such that initially equivalent cells differentiate over a period of time. Surprisingly, inherent stochasticity also increases the robustness of the progenitor state and lessens the impact of unequal, random distribution of molecules at cell division on the temporal spread of differentiation at the population level. This advantageous use of biological noise contrasts with the view that noise needs to be counteracted.
The biomechanics of large- and medium-sized arteries influence the pathophysiology of arterial disease and the response to therapeutic interventions. However, a comprehensive comparative analysis of ...human arterial biaxial mechanical properties has not yet been reported. Planar biaxial extension was used to establish the passive mechanical properties of human thoracic (TA,
n
=
8
) and abdominal (AA,
n
=
7
) aorta, common carotid (CCA,
n
=
21
), subclavian (SA,
n
=
12
), renal (RA,
n
=
13
) and common iliac (CIA,
n
=
16
) arteries from 11 deceased subjects (
54
±
21
years old). Histological evaluation determined the structure of each specimen. Experimental data were used to determine constitutive parameters for a structurally motivated nonlinear anisotropic constitutive model. All arteries demonstrated appreciable anisotropy and large nonlinear deformations. Most CCA, SA, TA, AA and CIA specimens were stiffer longitudinally, while most RAs were stiffer circumferentially. A switch in anisotropy was occasionally demonstrated for all arteries. The CCA was the most compliant, least anisotropic and least frequently diseased of all arteries, while the CIA and AA were the stiffest and the most diseased. The severity of atherosclerosis correlated with age, but was not affected by laterality. Elastin fibers in the aorta, SA and CCA were uniformly and mostly circumferentially distributed throughout the media, while in the RA and CIA, elastin was primarily axially aligned and concentrated in the external elastic lamina. Constitutive modeling provided good fits to the experimental data for most arteries. Biomechanical and architectural features of major arteries differ depending on location and functional environment. A better understanding of localized arterial mechanical properties may support the development of site-specific treatment modalities for arterial disease.