Trends in drug revenue among major pharmaceutical companies: A 2010-2019 cohort study.

BACKGROUND: Over the past 2 decades there has been a substantial increase in the number of new cancer medicines; this has been accompanied by a dramatic rise in drug costs. It is unknown how these trends impact the revenue of the pharmaceutical sector. METHODS: Retrospective cohort study to characterize temporal trends of revenue generated from cancer medicines as a proportion of total drug revenue among 10 large pharmaceutical companies from 2010 to 2019. Itemized product-sales data publicly available through company websites or annual filings were used to identify annual drug revenue. Revenue data were adjusted for inflation and converted to 2019 US dollars. RESULTS: During the study period, cumulative annual revenue generated from cancer drugs increased by 70%: from $55.8 billion to $95.1 billion, while cumulative revenue from nononcology drugs decreased 18%: from $342.2 billion to $281.5 billion. The proportion of total drug revenue generated from oncology drugs increased substantially over the study period: from 14% in 2010 to 25% in 2019 (τ = 1.0, P < .001). CONCLUSIONS: Among 10 of the world's largest pharmaceutical companies, revenues generated from the sale of cancer drugs have increased by 70% over the past decade, while revenues from other medicines have decreased by 18%. Revenues from cancer drugs now account for one-quarter of the net revenues from these companies. Further work is needed to understand if this increase in sales revenue reflects industry profit, and to what extent increased spending has translated into improvements in patient and population outcomes.

The rat retina has five types of ganglion-cell photoreceptors.

Intrinsically photosensitive retinal ganglion cells (ipRGCs) are inner retinal photoreceptors that mediate non-image-forming visual functions, e.g. pupillary constriction, regulation of pineal melatonin release, and circadian photoentrainment. Five types of ipRGCs were recently discovered in mouse, but whether they exist in other mammals remained unknown. We report that the rat also has five types of ipRGCs, whose morphologies match those of mouse ipRGCs; this is the first demonstration of all five cell types in a non-mouse species. Through immunostaining and λmax measurements, we showed that melanopsin is likely the photopigment of all rat ipRGCs. The various cell types exhibited diverse spontaneous spike rates, with the M1 type spiking the least and M4 spiking the most, just like we had observed for their mouse counterparts. Also similar to mouse, all ipRGCs in rat generated not only sluggish intrinsic photoresponses but also fast, synaptically driven ones. However, we noticed two significant differences between these species. First, whereas we learned previously that all mouse ipRGCs had equally sustained synaptic light responses, rat M1 cells' synaptic photoresponses were far more transient than those of M2-M5. Since M1 cells provide all input to the circadian clock, this rat-versus-mouse discrepancy could explain the difference in photoentrainment threshold between mouse and other species. Second, rat ipRGCs' melanopsin-based spiking photoresponses could be classified into three varieties, but only two were discerned for mouse ipRGCs. This correlation of spiking photoresponses with cell types will help researchers classify ipRGCs in multielectrode-array (MEA) spike recordings.

Postnatal Brain Trajectories and Maternal Intelligence Predict Childhood Outcomes in Complex CHD.

Objective: To determine whether early structural brain trajectories predict early childhood neurodevelopmental deficits in complex CHD patients and to assess relative cumulative risk profiles of clinical, genetic, and demographic risk factors across early development. Study Design: Term neonates with complex CHDs were recruited at Texas Children's Hospital from 2005-2011. Ninety-five participants underwent three structural MRI scans and three neurodevelopmental assessments. Brain region volumes and white matter tract fractional anisotropy and radial diffusivity were used to calculate trajectories: perioperative, postsurgical, and overall. Gross cognitive, language, and visuo-motor outcomes were assessed with the Bayley Scales of Infant and Toddler Development and with the Wechsler Preschool and Primary Scale of Intelligence and Beery-Buktenica Developmental Test of Visual-Motor Integration. Multi-variable models incorporated risk factors. Results: Reduced overall period volumetric trajectories predicted poor language outcomes: brainstem ((ß, 95% CI) 0.0977, 0.0382-0.1571; p = 0.0022) and white matter (0.0023, 0.0001-0.0046; p = 0.0397) at 5 years; brainstem (0.0711, 0.0157-0.1265; p = 0.0134) and deep grey matter (0.0085, 0.0011-0.0160; p = 0.0258) at 3 years. Maternal IQ was the strongest contributor to language variance, increasing from 37% at 1 year, 62% at 3 years, and 81% at 5 years. Genetic abnormality's contribution to variance decreased from 41% at 1 year to 25% at 3 years and was insignificant at 5 years. Conclusion: Reduced postnatal subcortical-cerebral white matter trajectories predicted poor early childhood neurodevelopmental outcomes, despite high contribution of maternal IQ. Maternal IQ was cumulative over time, exceeding the influence of known cardiac and genetic factors in complex CHD, underscoring the importance of heritable and parent-based environmental factors.

Limbic pathway vulnerability associates with neurologic outcome in children after cardiac arrest.

AIM: To analyze whether brain connectivity sequences including diffusion tensor imaging (DTI) and resting state functional magnetic resonance imaging (rsfMRI) identify vulnerable brain regions and networks associated with neurologic outcome after pediatric cardiac arrest. METHODS: Children aged 2 d-17 y with cardiac arrest were enrolled in one of 2 parent studies at a single center. Clinically indicated brain MRI with DTI and rsfMRI and performed within 2 weeks after arrest were analyzed. Tract-wise fractional anisotropy (FA) and axial, radial, and mean diffusivity assessed DTI, and functional connectivity strength (FCS) assessed rsfMRI between outcome groups. Unfavorable neurologic outcome was defined as Pediatric Cerebral Performance Category score 4-6 or change > 1 between 6 months after arrest vs baseline. RESULTS: Among children with DTI (n = 28), 57% had unfavorable outcome. Mean, radial, axial diffusivity and FA of varying direction of magnitude in the limbic tracts, including the right cingulum parolfactory, left cingulum parahippocampal, corpus callosum forceps major, and corpus callosum forceps minor tracts, were associated with unfavorable neurologic outcome (p < 0.05). Among children with rsfMRI (n = 12), 67% had unfavorable outcome. Decreased FCS in the ventromedial and dorsolateral prefrontal cortex, insula, precentral gyrus, anterior cingulate, and inferior parietal lobule were correlated regionally with unfavorable neurologic outcome (p < 0.05 Family-Wise Error corrected). CONCLUSION: Decreased multimodal connectivity measures of paralimbic tracts were associated with unfavorable neurologic outcome after pediatric cardiac arrest. Longitudinal analysis correlating brain connectivity sequences with long term neuropsychological outcomes to identify the impact of pediatric cardiac arrest in vulnerable brain networks over time appears warranted.

Cerebral Spinal Fluid Volumetrics and Paralimbic Predictors of Executive Dysfunction in Congenital Heart Disease: A Machine Learning Approach Informing Mechanistic Insights.

The relationship between increased cerebral spinal fluid (CSF) ventricular compartments, structural and microstructural dysmaturation, and executive function in patients with congenital heart disease (CHD) is unknown. Here, we leverage a novel machine-learning data-driven technique to delineate interrelationships between CSF ventricular volume, structural and microstructural alterations, clinical risk factors, and sub-domains of executive dysfunction in adolescent CHD patients. We trained random forest regression models to predict measures of executive function (EF) from the NIH Toolbox, the Delis-Kaplan Executive Function System (D-KEFS), and the Behavior Rating Inventory of Executive Function (BRIEF) and across three subdomains of EF - mental flexibility, working memory, and inhibition. We estimated the best parameters for the random forest algorithm via a randomized grid search of parameters using 10-fold cross-validation on the training set only. The best parameters were then used to fit the model on the full training set and validated on the test set. Algorithm performance was measured using root-mean squared-error (RMSE). As predictors, we included patient clinical variables, perioperative clinical measures, microstructural white matter (diffusion tensor imaging- DTI), and structural volumes (volumetric magnetic resonance imaging- MRI). Structural white matter was measured using along-tract diffusivity measures of 13 inter-hemispheric and cortico-association fibers. Structural volumes were measured using FreeSurfer and manual segmentation of key structures. Variable importance was measured by the average Gini-impurity of each feature across all decision trees in which that feature is present in the model, and functional ontology mapping (FOM) was used to measure the degree of overlap in feature importance for each EF subdomain and across subdomains. We found that CSF structural properties (including increased lateral ventricular volume and reduced choroid plexus volumes) in conjunction with proximate cortical projection and paralimbic-related association white matter tracts that straddle the lateral ventricles and distal paralimbic-related subcortical structures (basal ganglia, hippocampus, cerebellum) are predictive of two-specific subdomains of executive dysfunction in CHD patients: cognitive flexibility and inhibition. These findings in conjunction with combined RF models that incorporated clinical risk factors, highlighted important clinical risk factors, including the presence of microbleeds, altered vessel volume, and delayed PDA closure, suggesting that CSF-interstitial fluid clearance, vascular pulsatility, and glymphatic microfluid dynamics may be pathways that are impaired in CHD, providing mechanistic information about the relationship between CSF and executive dysfunction.

Harmonization of Multi-Center Diffusion Tensor Tractography in Neonates with Congenital Heart Disease: Optimizing Post-Processing and Application of ComBat.

Advanced brain imaging of neonatal macrostructure and microstructure, which has prognosticating importance, is more frequently being incorporated into multi-center trials of neonatal neuroprotection. Multicenter neuroimaging studies, designed to overcome small sample sized clinical cohorts, are essential but lead to increased technical variability. Few harmonization techniques have been developed for neonatal brain microstructural (diffusion tensor) analysis. The work presented here aims to remedy two common problems that exist with the current state of the art approaches: 1) variance in scanner and protocol in data collection can limit the researcher's ability to harmonize data acquired under different conditions or using different clinical populations. 2) The general lack of objective guidelines for dealing with anatomically abnormal anatomy and pathology. Often, subjects are excluded due to subjective criteria, or due to pathology that could be informative to the final analysis, leading to the loss of reproducibility and statistical power. This proves to be a barrier in the analysis of large multi-center studies and is a particularly salient problem given the relative scarcity of neonatal imaging data. We provide an objective, data-driven, and semi-automated neonatal processing pipeline designed to harmonize compartmentalized variant data acquired under different parameters. This is done by first implementing a search space reduction step of extracting the along-tract diffusivity values along each tract of interest, rather than performing whole-brain harmonization. This is followed by a data-driven outlier detection step, with the purpose of removing unwanted noise and outliers from the final harmonization. We then use an empirical Bayes harmonization algorithm performed at the along-tract level, with the output being a lower dimensional space but still spatially informative. After applying our pipeline to this large multi-site dataset of neonates and infants with congenital heart disease (n= 398 subjects recruited across 4 centers, with a total of n=763 MRI pre-operative/post-operative time points), we show that infants with single ventricle cardiac physiology demonstrate greater white matter microstructural alterations compared to infants with bi-ventricular heart disease, supporting what has previously been shown in literature. Our method is an open-source pipeline for delineating white matter tracts in subject space but provides the necessary modular components for performing atlas space analysis. As such, we validate and introduce Diffusion Imaging of Neonates by Group Organization (DINGO), a high-level, semi-automated framework that can facilitate harmonization of subject-space tractography generated from diffusion tensor imaging acquired across varying scanners, institutions, and clinical populations. Datasets acquired using varying protocols or cohorts are compartmentalized into subsets, where a cohort-specific template is generated, allowing for the propagation of the tractography mask set with higher spatial specificity. Taken together, this pipeline can reduce multi-scanner technical variability which can confound important biological variability in relation to neonatal brain microstructure.

Severe Familial Exudative Vitreoretinopathy, Congenital Hearing Loss, and Developmental Delay in a Child With Biallelic Variants in FZD4.

Importance: Familial exudative vitreoretinopathy (FEVR) is a nonsyndromic autosomal dominant retinal disorder commonly caused by variants in the FZD4 gene. This study investigates the potential role beyond ocular abnormalities for FZD4 gene variants in patients with FEVR. Objective: To evaluate the role of FZD4 in symptoms beyond those associated with FEVR through a patient with biallelic variants in FZD4. Design, Setting, and Participants: This case series included the DNA testing and phenotyping of 1 patient proband and her parents, combined with signaling assays, to determine the association of patient-derived compound heterozygous variants on FZD4 signaling and biologic function. Main Outcomes and Measures: FZD4 genes were tested using next-generation sequencing and Sanger sequencing. Cell-based assays measured the effect of the variants on FZD4 signaling. Results: The proband presented with absent red reflexes from complete tractional retinal detachments diagnosed at 3 days of age and failed the newborn screening hearing test. Auditory brainstem response at 6 months of age showed bilateral mild to moderate high-frequency sensorineural hearing loss. The patient manifested developmental delays in speech and walking. Intravenous fluorescein angiography (IVFA) of the patient's parents detected stage 1 FEVR. Genetic testing revealed 2 FZD4 variants in the patient, each variant found in 1 parent. Signaling assays confirmed that the presence of both variants was associated with significantly worse signaling activity compared with the heterozygous state. Conclusions and Relevance: Results of this case series suggest that extraocular syndromic FEVR was associated with FZD4 variants. The decrease in FZD4 signaling owing to the biallelic nature of the disease resulted in hearing deficits, developmental delays, and a more severe retinal phenotype.

Clinical factors associated with microstructural connectome related brain dysmaturation in term neonates with congenital heart disease.

Objective: Term congenital heart disease (CHD) neonates display abnormalities of brain structure and maturation, which are possibly related to underlying patient factors, abnormal physiology and perioperative insults. Our primary goal was to delineate associations between clinical factors and postnatal brain microstructure in term CHD neonates using diffusion tensor imaging (DTI) magnetic resonance (MR) acquisition combined with complementary data-driven connectome and seed-based tractography quantitative analyses. Our secondary goal was to delineate associations between mild dysplastic structural brain abnormalities and connectome and seed-base tractography quantitative analyses. These mild dysplastic structural abnormalities have been derived from prior human infant CHD MR studies and neonatal mouse models of CHD that were collectively used to calculate to calculate a brain dysplasia score (BDS) that included assessment of subcortical structures including the olfactory bulb, the cerebellum and the hippocampus. Methods: Neonates undergoing cardiac surgery for CHD were prospectively recruited from two large centers. Both pre- and postoperative MR brain scans were obtained. DTI in 42 directions was segmented into 90 regions using a neonatal brain template and three weighted methods. Clinical data collection included 18 patient-specific and 9 preoperative variables associated with preoperative scan and 6 intraoperative (e.g., cardiopulmonary bypass and deep hypothermic circulatory arrest times) and 12 postoperative variables associated with postoperative scan. We compared patient specific and preoperative clinical factors to network topology and tractography alterations on a preoperative neonatal brain MRI, and intra and postoperative clinical factors to network topology alterations on postoperative neonatal brain MRI. A composite BDS was created to score abnormal findings involving the cerebellar hemispheres and vermis, supratentorial extra-axial fluid, olfactory bulbs and sulci, hippocampus, choroid plexus, corpus callosum, and brainstem. The neuroimaging outcomes of this study included (1) connectome metrics: cost (number of connections) and global/nodal efficiency (network integration); (2) seed based tractography methods of fractional anisotropy (FA), radial diffusivity, and axial diffusivity. Statistics consisted of multiple regression with false discovery rate correction (FDR) comparing the clinical risk factors and BDS (including subcortical components) as predictors/exposures and the global connectome metrics, nodal efficiency, and seed based- tractography (FA, radial diffusivity, and axial diffusivity) as neuroimaging outcome measures. Results: A total of 133 term neonates with complex CHD were prospectively enrolled and 110 had analyzable DTI. Multiple patient-specific factors including d-transposition of the great arteries (d-TGA) physiology and severity of impairment of fetal cerebral substrate delivery (i.e., how much the CHD lesion alters typical fetal circulation such that the highest oxygen and nutrient rich blood from the placenta are not directed toward the fetal brain) were predictive of preoperative reduced cost (p < 0.0073) and reduced global/nodal efficiency (p < 0.03). Cardiopulmonary bypass time predicted postoperative reduced cost (p < 0.04) and multiple postoperative factors [extracorporeal membrane oxygenation (ECMO), seizures and cardiopulmonary resuscitation (CPR)] were predictive of postoperative reduced cost and reduced global/nodal efficiency (p < 0.05). Anthropometric measurements (weight, length, and head size) predicted tractography outcomes. Total BDS was not predictive of brain network topology. However, key subcortical components of the BDS score did predict key global and nodal network topology: abnormalities of the cerebellum predicted reduced cost (p < 0.0417) and of the hippocampus predicted reduced global efficiency (p < 0.0126). All three subcortical structures predicted unique alterations of nodal efficiency (p < 0.05), including hippocampal abnormalities predicting widespread reduced nodal efficiency in all lobes of the brain, cerebellar abnormalities predicting increased prefrontal nodal efficiency, and olfactory bulb abnormalities predicting posterior parietal-occipital nodal efficiency. Conclusion: Patient-specific (d-TGA anatomy, preoperative impairment of fetal cerebral substrate delivery) and postoperative (e.g., seizures, need for ECMO, or CPR) clinical factors were most predictive of diffuse postnatal microstructural dysmaturation in term CHD neonates. Anthropometric measurements (weight, length, and head size) predicted tractography outcomes. In contrast, subcortical components (cerebellum, hippocampus, olfactory) of a structurally based BDS (derived from CHD mouse mutants), predicted more localized and regional postnatal microstructural differences. Collectively, these findings suggest that brain DTI connectome and seed-based tractography are complementary techniques which may facilitate deciphering the mechanistic relative contribution of clinical and genetic risk factors related to poor neurodevelopmental outcomes in CHD.

All spiking, sustained ON displaced amacrine cells receive gap-junction input from melanopsin ganglion cells.

Retinal neurons exhibit sustained versus transient light responses, which are thought to encode low- and high-frequency stimuli, respectively. This dichotomy has been recognized since the earliest intracellular recordings from the 1960s, but the underlying mechanisms are not yet fully understood. We report that in the ganglion cell layer of rat retinas, all spiking amacrine interneurons with sustained ON photoresponses receive gap-junction input from intrinsically photosensitive retinal ganglion cells (ipRGCs), recently discovered photoreceptors that specialize in prolonged irradiance detection. This input presumably allows ipRGCs to regulate the secretion of neuromodulators from these interneurons. We have identified three morphological varieties of such ipRGC-driven displaced amacrine cells: (1) monostratified cells with dendrites terminating exclusively in sublamina S5 of the inner plexiform layer, (2) bistratified cells with dendrites in both S1 and S5, and (3) polyaxonal cells with dendrites and axons stratifying in S5. Most of these amacrine cells are wide field, although some are medium field. The three classes respond to light differently, suggesting that they probably perform diverse functions. These results demonstrate that ipRGCs are a major source of tonic visual information within the retina and exert widespread intraretinal influence. They also add to recent evidence that ganglion cells signal not only to the brain.

A cell-to-cell macromolecular transport assay in Planta utilizing biolistic bombardment.

Here, we present a simple and rapid protocol to detect and assess the extent of cell-to-cell macromolecular transport in planta. In this protocol, a fluorescently tagged-protein of interest is transiently expressed in plant tissue following biolistic delivery of its encoding DNA construct. The intra- and intercellular distribution of the tagged protein is then analyzed by confocal microscopy. We describe this technology in detail, providing step-by-step protocols to assay and evaluate the extent of symplastic protein transport in three plant species, Arabidopsis thaliana, Nicotiana benthamiana and N. tabacum (tobacco).

Nuclear and plastid genetic engineering of plants: comparison of opportunities and challenges.

Plant genetic engineering is one of the key technologies for crop improvement as well as an emerging approach for producing recombinant proteins in plants. Both plant nuclear and plastid genomes can be genetically modified, yet fundamental functional differences between the eukaryotic genome of the plant cell nucleus and the prokaryotic-like genome of the plastid will have an impact on key characteristics of the resulting transgenic organism. So, which genome, nuclear or plastid, to transform for the desired transgenic phenotype? In this review we compare the advantages and drawbacks of engineering plant nuclear and plastid genomes to generate transgenic plants with the traits of interest, and evaluate the pros and cons of their use for different biotechnology and basic research applications, ranging from generation of commercial crops with valuable new phenotypes to 'bioreactor' plants for large-scale production of recombinant proteins to research model plants expressing various reporter proteins.

Autoluminescent plants.

Prospects of obtaining plants glowing in the dark have captivated the imagination of scientists and layman alike. While light emission has been developed into a useful marker of gene expression, bioluminescence in plants remained dependent on externally supplied substrate. Evolutionary conservation of the prokaryotic gene expression machinery enabled expression of the six genes of the lux operon in chloroplasts yielding plants that are capable of autonomous light emission. This work demonstrates that complex metabolic pathways of prokaryotes can be reconstructed and function in plant chloroplasts and that transplastomic plants can emit light that is visible by naked eye.