bluuebunny/crossref_metadata_2025 huggingface dataset:
Incidence Measures for Schizophrenia among Commercial Health Insurance and Medicaid Enrollees
Authors: Finnerty Molly T. , Khan Atif , You Kai , Wang Rui , Gu Gyojeong , Layman Deborah , Chen Qingxian , Elhadad Noémie , Joshi Shalmali , Appelbaum Paul S. , Lencz Todd , Markx Sander , Kushner Steven A. , Rzhetsky Andrey
Published: February 2023

Objective

To examine and compare the prevalence, incidence, and specificity and positive predictive value of incidence measures in a national commercial insurance database and a state Medicaid database, for different age groups over the life span.

Methods

This cross-sectional study examined the annual prevalence of schizophrenia in 2019 in two databases: a) MarketScan, a United States national commercial insurance database (N= 16,365,997), and b) New York State Medicaid program (N= 4,414,153). A subset of these individuals with 10 years of continuous insurance prior to 2019 (2009-2018) was used to assess incidence and to create a reference standard for incidence measure testing, including positive predictive value and specificity, by age group. Continuous enrollment was required for all years of study (45-day gap allowance per year, and one or more health care services annually to ensure opportunity to be diagnosed).

Results

The prevalence of schizophrenia in 2019 was 0.13% in MarketScan, and 2.13% in Medicaid. Prevalence was highest in MarketScan among individuals aged 21-25 years. In contrast, prevalence in Medicaid increased over the lifespan, with the peak among those 56-60 years of age. The incidence of new-onset schizophrenia in 2019 was 0.07% in MarketScan and 0.19% in Medicaid and peaked in young adulthood (26-30 years of age) in both databases (0.16% and 0.40%, respectively). Positive predictive value (PPV) for the incidence measures was higher for women than men and increased with longer lookback periods prior to the first schizophrenia diagnosis in 2019. Using a one-year lookback period, the PPV for those ≤35 years of age was 79% in MarketScan and 51% in Medicaid; a ≥95% PPV was achieved with a two-year lookback in MarketScan, and a seven-year lookback period in Medicaid. PPVs were also higher in younger age groups; in Medicaid a two-year lookback period yielded a PPV of 68% for those ≤35 years, but was 94% for those ≤20 years. Specificity was high even for the total population with one year of observation prior to the first schizophrenia diagnosis in 2019, and was higher in Medicaid (92%) than in MarketScan (80%), increasing further with longer lookback periods in both databases.

Conclusions

The prevalence of schizophrenia is over 10-fold higher, and the incidence two-fold higher, in the New York State Medicaid population compared to the MarketScan national commercial insurance database. Within each database, prevalence and incidence varied by sex, age, and duration of insurance. Yet despite these differences, accurate measures of incidence of new-onset schizophrenia could be constructed with high specificity and positive predictive values.
New tuberculosis vaccines in India: Modelling the potential health and economic impacts of adolescent/adult vaccination with M72/AS01Eand BCG-revaccination
Authors: Clark Rebecca A , Weerasuriya Chathika K , Portnoy Allison , Mukandavire Christinah , Quaife Matthew , Bakker Roel , Scarponi Danny , Harris Rebecca C , Rade Kirankumar , Mattoo Sanjay Kumar , Tumu Dheeraj , Menzies Nicolas A , White Richard G
Published: February 2023

Background

India had an estimated 2.9 million tuberculosis cases and 506 thousand deaths in 2021. Novel vaccines effective in adolescents and adults could reduce this burden. M72/AS01Eand BCG-revaccination have recently completed Phase IIb trials and estimates of their population-level impact are needed. We estimated the potential health and economic impact of M72/AS01Eand BCG-revaccination in India and investigated the impact of variation in vaccine characteristics and delivery strategies.

Methods

We developed an age-stratified compartmental tuberculosis transmission model for India calibrated to country-specific epidemiology. We projected baseline epidemiology to 2050 assuming no-new-vaccine introduction, and M72/AS01Eand BCG-revaccination scenarios over 2025–2050 exploring uncertainty in product characteristics (vaccine efficacy, mechanism of effect, infection status required for vaccine efficacy, duration of protection) and implementation (achieved vaccine coverage and ages targeted). We estimated reductions in tuberculosis cases and deaths by each scenario compared to no-new-vaccine introduction, as well as costs and cost-effectiveness from health-system and societal perspectives.

Results

M72/AS01Escenarios were predicted to avert 40% more tuberculosis cases and deaths by 2050 compared to BCG-revaccination scenarios. Cost-effectiveness ratios for M72/AS01Evaccines were around seven times higher than BCG-revaccination, but nearly all scenarios were cost-effective. The estimated average incremental cost was US$190 million for M72/AS01Eand US$23 million for BCG-revaccination per year. Sources of uncertainty included whether M72/AS01Ewas efficacious in uninfected individuals at vaccination, and if BCG-revaccination could prevent disease.

Conclusions

M72/AS01Eand BCG-revaccination could be impactful and cost-effective in India. However, there is great uncertainty in impact, especially given unknowns surrounding mechanism of effect and infection status required for vaccine efficacy. Greater investment in vaccine development and delivery is needed to resolve these unknowns in vaccine product characteristics.
Toward Digital Phenotypes of Early Childhood Mental Health via Unsupervised and Supervised Machine Learning
Authors: Loftness Bryn C. , Rizzo Donna M. , Halvorson-Phelan Julia , O’Leary Aisling , Prytherch Shania , Bradshaw Carter , Brown Anna Jane , Cheney Nick , McGinnis Ellen W. , McGinnis Ryan S.
Published: February 2023

Childhood mental health disorders such as anxiety, depression, and ADHD are commonly-occurring and often go undetected into adolescence or adulthood. This can lead to detrimental impacts on long-term wellbeing and quality of life. Current parent-report assessments for pre-school aged children are often biased, and thus increase the need for objective mental health screening tools. Leveraging digital tools to identify the behavioral signature of childhood mental disorders may enable increased intervention at the time with the highest chance of long-term impact. We present data from 84 participants (4-8 years old, 50% diagnosed with anxiety, depression, and/or ADHD) collected during a battery of mood induction tasks using the ChAMP System. Unsupervised Kohonen Self-Organizing Maps (SOM) constructed from movement and audio features indicate that age did not tend to explain clusters as consistently as gender within task-specific and cross-task SOMs. Symptom prevalence and diagnostic status also showed some evidence of clustering. Case studies suggest that high impairment (>80th percentile symptom counts) and diagnostic subtypes (ADHD-Combined) may account for most behaviorally distinct children. Based on this same dataset, we also present results from supervised modeling for the binary classification of diagnoses. Our top performing models yield moderate but promising results (ROC AUC .6-.82, TPR .36-.71, Accuracy .62-.86) on par with our previous efforts for isolated behavioral tasks. Enhancing features, tuning model parameters, and incorporating additional wearable sensor data will continue to enable the rapid progression towards the discovery of digital phenotypes of childhood mental health.

Clinical Relevance

This work advances the use of wearables for detecting childhood mental health disorders.
Cellograph: A Semi-supervised Approach to Analyzing Multi-condition Single-cell RNA Sequencing Data Using Graph Neural Networks
Authors: Shahir Jamshaid A. , Stanley Natalie , Purvis Jeremy E.
Published: February 2023

Abstract

With the growing number of single-cell datasets collected under more complex experimental conditions, there is an opportunity to leverage single-cell variability to reveal deeper insights into how cells respond to perturbations. Many existing approaches rely on discretizing the data into clusters for differential gene expression (DGE), effectively ironing out any information unveiled by the single-cell variability across cell-types. In addition, DGE often assumes a statistical distribution that, if erroneous, can lead to false positive differentially expressed genes. Here, we present Cellograph: a semi-supervised framework that uses graph neural networks to quantify the effects of perturbations at single-cell granularity. Cellograph not only measures how prototypical cells are of each condition but also learns a latent space that is amenable to interpretable data visualization and clustering. The learned gene weight matrix from training reveals pertinent genes driving the differences between conditions. We demonstrate the utility of our approach on publicly-available datasets including cancer drug therapy, stem cell reprogramming, and organoid differentiation. Cellograph outperforms existing methods for quantifying the effects of experimental perturbations and offers a novel framework to analyze single-cell data using deep learning.
A cataract-causing Y204X mutation of CRYßB1 promotes C-terminal degradation and higher-order oligomerization
Authors: Jing Xuping , Lu Xiaoyun , Zhu Mingwei , Shi Lingyu , Wei Ping , Zhang Bu-Yu , Xu Yi , Xiang Dao-Man , Tang Ya-Ping , Gong Peng
Published: February 2023

Crystallin (Cry) proteins are a class of main structural proteins of vertebrate eye lens, and their solubility and stability directly determine transparency and refractive power of the lens. Mutation in genes that encode for these Cry proteins is the common cause for congenital cataract. Despite extensive studies, the pathogenic and molecular mechanisms remain unclear. In this study, we identified a novel mutation inCRYΒB1from a congenital cataract family, and demonstrated that this mutation led to an earlier termination of protein translation, resulting in a 49-residue truncation at the CRYβB1 C-terminus. This mutant is susceptible to proteolysis and allows us to determine a 1.2- Å resolution crystal structure of CRYβB1 without the entire C-terminal domain. In this crystal lattice, two N-terminal domain monomers form a dimer that structurally resembles a wild-type (WT) monomer, but with different surface characteristics. Biochemical analyses suggest that this mutant is significantly more liable to aggregate and degrade, when compared to WT CRYβB1. All our results provide an insight into the mechanism regarding how a mutant Cry contributes to the development of congenital cataract possibly through alteration of inter-protein interactions that result in the opacity of eye lens.
Zero-shot learning enables instant denoising and super-resolution in optical fluorescence microscopy
Authors: Qiao Chang , Zeng Yunmin , Meng Quan , Chen Xingye , Chen Haoyu , Jiang Tao , Wei Rongfei , Guo Jiabao , Fu Wenfeng , Lu Huaide , Li Di , Wang Yuwang , Qiao Hui , Wu Jiamin , Li Dong , Dai Qionghai
Published: February 2023

Computational super-resolution (SR) methods, including conventional analytical algorithms and deep learning models, have substantially improved optical microscopy. Among them, supervised deep neural networks have demonstrated outstanding SR performance, however, demanding abundant high-quality training data, which are laborious and even impractical to acquire due to the high dynamics of living cells. Here, we develop zero-shot deconvolution networks (ZS-DeconvNet) that instantly enhance the resolution of microscope images by more than 1.5-fold over the diffraction limit with 10-fold lower fluorescence than ordinary SR imaging conditions in an unsupervised manner without the need for either ground truths or additional data acquisition. We demonstrate the versatile applicability of ZS-DeconvNet on multiple imaging modalities, including total internal reflection fluorescence microscopy, three-dimensional (3D) wide-field microscopy, confocal microscopy, lattice light-sheet microscopy, and multimodal structured illumination microscopy (SIM), which enables multi-color, long-term, super-resolution 2D/3D imaging of subcellular bioprocesses from mitotic single cells to multicellular embryos of mouse and C. elegans.
Excessive apoptosis of naïve T cells resulting hyperactivation as a cause of mammalian aging
Authors: Wang Lingxia , Zhang Xixi , Zhang Haiwei , Lu Kaili , Li Ming , Li Xiaoming , Ou Yangjing , Zhao Xiaoming , Wu Xiaoxia , Wu Xuanhui , Liu Jianling , Xing Mingyan , Liu Han , Zhang Yue , Tan Yongchang , Li Fang , Deng Jiangshan , Zhang Xiaojie , Li Jinbao , Zhao Yuwu , Wang Xiuzhe , Luo Yan , Zhou Ben , Zhang Haibing
Published: February 2023

In mammals, the most remarkable T cell variations with aging are the shrinking of naïve T cell pool and enlargement of memory T cell pool, which are partially caused by thymic involution. However, it remains an enigma whether these T-cell-related changes are consequences or causes of mammalian aging. In this study, we find that the T-cell specificRip1KO mice present similar age-related T cell changes and exhibit signs of accelerated aging, including inflammation, multiple age-related diseases and a shorter lifespan. Mechanistically, T cells lacking RIP1 displayed excessive apoptosis, leading to T cell compensatory proliferation, hyperactivation, increased inflammation, and ultimately premature death. Consistent with this, blocking apoptosis by co-deletion ofFaddinRip1deficient T cells significantly recovered the lymphopenia and imbalance between naïve and memory T cell, substantially restored ageing-related phenotypes, and prolonged life span in T-cell specificRip1KO mice. These results suggest that changes in T cells play a causal role in mammalian aging. Therefore, replenishing or blocking apoptosis of naïve T cells could offer new therapeutic approaches for aging and age-related diseases.
Biologically informed NeuralODEs for genome-wide regulatory dynamics
Authors: Hossain Intekhab , Fanfani Viola , Fischer Jonas , Quackenbush John , Burkholz Rebekka
Published: February 2023

Modeling dynamics of gene regulatory networks using ordinary differential equations (ODEs) allow a deeper understanding of disease progression and response to therapy, thus aiding in intervention optimization. Although there exist methods to infer regulatory ODEs, these are generally limited to small networks, rely on dimensional reduction, or impose non-biological parametric restrictions — all impeding scalability and explainability. PHOENIX is a neural ODE framework incorporating prior domain knowledge as soft constraints to infer sparse, biologically interpretable dynamics. Extensive experiments - on simulated and real data - demonstrate PHOENIX’s unique ability to learn key regulatory dynamics while scaling to the whole genome.
Shared inflammatory glial cell signature after brain injury, revealed by spatial, temporal and cell-type-specific profiling of the murine cerebral cortex
Authors: Koupourtidou Christina , Schwarz Veronika , Aliee Hananeh , Frerich Simon , Fischer-Sternjak Judith , Bocchi Riccardo , Simon-Ebert Tatiana , Dichgans Martin , Götz Magdalena , Theis Fabian , Ninkovic Jovica
Published: February 2023

Traumatic brain injury leads to a highly orchestrated immune- and glial cell response partially responsible for long-lasting disability and the development of secondary neurodegenerative diseases. A holistic understanding of the mechanisms controlling the responses of specific cell types and their crosstalk is required to develop an efficient strategy for better regeneration. Here, we combined spatial and single-cell transcriptomics to chart the transcriptomic signature of the injured murine cerebral cortex, and identified specific states of astrocytes, microglia, and oligodendrocyte precursor cells contributing to this signature. Interestingly, these cellular populations share a large fraction of injury-regulated genes, including inflammatory programs downstream of the innate immune-associated pathways Cxcr3 and Tlr1/2. Systemic manipulation of these pathways decreased the reactivity state of glial cells associated with poor regeneration. The functional relevance of the newly discovered shared signature of glial cells highlights the importance of our resource enabling comprehensive analysis of early events after brain injury.
A layer cake model for plant and metazoan chromatin
Authors: Carron Léoplod , Concia Lorenzo , Grob Stefan , Barneche Fredy , Carbone Alessandra , Mozziconacci Julien
Published: February 2023

Early structural studies of chromosome organisation in eukaryotic nuclei led to the identification of euchromatin and heterochromatin, two main archetypes of chromatin visible through microscopy. Subsequently, the diversity of chromatin composition along the linear genome sequence was resolved using high throughput sequencing techniques to map a multitude of chromatin marks and unravel their functional organisation. Recent analyses of human chromosome conformation capture experiments tend to point to the existence of several chromosome sub-compartments that may correspond to epigenomic variations in chromatin composition. Here, we compare genome 3D organisations in representative eukaryotic species to explore the links between chromosomal sub-compartments and chromatin marks, genome replication timing, and genomic repeats in six model organisms, including vertebrates, plants and insects. We report that the 3D organisation of chromatin in organisms with different genome content and size can be described as layers characterised by distinct chromatin marks and activities. We propose a ”layer cake” model for the genome 3D organisation as a more refined view than the prevalent ”two compartments” model of chromatin organisation in multi-cellular organisms.
Detailed spectrographic analysis of rat ultrasonic vocalizations emitted during the acoustic startle response test
Authors: Bartsoen Emilie , Wöhr Markus
Published: February 2023

Rats emit ultrasonic vocalizations (USV). During aversive situations, rats emit 22-kHz USV, which are considered “alarm calls” and supposed to reflect a negative affective state of the sender. During appetitive situations, rats emit 50-kHz USV, which are believed to reflect a positive affective state. Here, we recorded USV emission in adult male rats during the acoustic startle response test. Our results indicate varied USV emission in both the 22- and 50-kHz USV ranges. Enhanced startle responses were observed in rats with a predominant 22-kHz call profile, supporting the notion that 22-kHz USV emission is associated with a negative affective state.
Dilated Virchow-Robin Spaces are a Marker for Arterial Disease in Multiple Sclerosis
Authors: Ineichen Benjamin V. , Cananau Carmen , Plattén Michael , Ouellette Russell , Moridi Thomas , Frauenknecht Katrin B. M. , Okar Serhat V. , Kulcsar Zsolt , Kockum Ingrid , Piehl Fredrik , Reich Daniel S. , Granberg Tobias
Published: February 2023

Virchow-Robin spaces (VRS) have been associated with neurodegeneration and neuroinflammation. However, it remains uncertain to what degree non-dilated or dilated VRS reflect specific features of neuroinflammatory pathology. Thus, we aimed at investigating the clinical relevance of VRS as imaging biomarker in multiple sclerosis (MS) and to correlate VRS to their histopathologic signature. In a cohort study comprising 205 MS patients (including a validation cohort) and 30 control subjects, we assessed the association of non-dilated and dilated VRS to clinical and magnetic resonance imaging (MRI) out-comes. Brain blocks from 6 MS patients and 3 non-MS controls were histopathologically processed to correlate VRS to their tissue substrate. The count of dilated centrum semiovale VRS was associated with increased T1 and T2 lesion volumes. There was no systematic spatial colocalization of dilated VRS with MS lesions. At tissue level, VRS mostly corresponded to arteries and were not associated with MS pathological hallmarks. Interestingly, dilated VRS in MS were associated with signs of small vessel disease. Contrary to prior beliefs, these observations suggest that VRS in MS do not associate with accumulation of immune cells. But instead, these findings indicate vascular pathology as a driver and/or consequence of neuroinflammatory pathology for this imaging feature.
Cognitive reappraisal and corresponding neural basis mediate the association between childhood maltreatment and depression
Authors: Mao Yu , Li Ling , Hou Xin , Li Yuan , Duan Shukai
Published: February 2023

Background

Childhood maltreatment is considered as a robust predictor of depression. However, the underlying psychological and neurological mechanisms linking childhood maltreatment and depression remain poorly understood. Sufficient evidence demonstrates emotion dysregulation in individuals who have experienced childhood maltreatment, but it is unknown whether these changes represent vulnerability for depression. Here we speculated that decreased cognitive reappraisal and its corresponding neural basis might explain the relationship between childhood maltreatment and follow-up depression.

Methods

First, we investigated whether cognitive reappraisal can explain the relationship between childhood maltreatment and depression, with a cross-sectional (n= 657) behavioral sample. Then we recruit 38 maltreated participants and 27 controls to complete the cognitive reappraisal functional magnetic resonance imaging (fMRI) task. The between-group difference in brain activation and functional connectivity (FC) were tested using independent t-tests. Finally, we investigated the relationship between childhood maltreatment, task-based brain activity and depression.

Results

The behavior results suggested that cognitive reappraisal mediate the association between childhood maltreatment and depression. Specifically, participants with higher level of childhood maltreatment tend to have deficit in cognitive reappraisal, which ultimately predict higher level of depression when facing stressful life event. In addition, the maltreated group exhibited lower activation of orbitofrontal cortex (OFC) and higher FC of between the dorsolateral prefrontal cortex (DLPFC), posterior cingulate cortex (PCC), OFC, and amygdala during cognitive reappraisal, compared with healthy controls. Furthermore, the FC of DLPFC-amygdala mediates the association between childhood maltreatment and depression.

Conclusion

In summary, childhood maltreatment is associated with inefficient cognitive reappraisal ability, manifesting as aberrant modulation of cortical areas on amygdala. These cognitive and neural deficits might explain the relationship between childhood maltreatment and risk of depression in later life. On the other side, cognitive reappraisal might also be a potential resilient factor for the prevention of maltreatment related emotional problems.
Integration of Apocarotenoid Profile and Expression Pattern ofCarotenoid Cleavage Dioxygenasesduring Mycorrhization in Rice
Authors: Votta Cristina , Wang Jian You , Cavallini Nicola , Savorani Francesco , Liew Kit Xi , Lanfranco Luisa , Al-Babili Salim , Fiorilli Valentina
Published: February 2023

Carotenoids are susceptible to degrading processes initiated by oxidative cleavage reactions mediated by Carotenoid Cleavage Dioxygenases that break their backbone, leading to products called apocarotenoids. These carotenoid-derived metabolites include the phytohormones abscisic acid and strigolactones, and different signaling molecules and growth regulators, which are utilized by plants to coordinate many aspects of their life. Several apocarotenoids have been recruited for the communication between plants and arbuscular mycorrhizal (AM) fungi and as regulators of the establishment of AM symbiosis. However, our knowledge on their biosynthetic pathways and the regulation of their pattern during AM symbiosis is still limited. In this study, we generated a qualitative and quantitative profile of apocarotenoids in roots and shoots of rice plants exposed to high/low phosphate concentrations, and upon AM symbiosis in a time course experiment covering different stages of growth and AM development. To get deeper insights in the biology of apocarotenoids during this plant-fungal symbiosis, we complemented the metabolic profiles by determining the expression pattern ofCCDgenes, taking advantage of chemometric tools. This analysis revealed the specific profiles ofCCDgenes and apocarotenoids across different stages of AM symbiosis and phosphate supply conditions, identifying novel markers at both local and systemic levels.

Highlight

Our study presents the profiles ofCCDgene expression and apocarotenoids across different stages of AM symbiosis and Pi supply conditions and reveals novel AM markers at both local and systemic levels.
A gradual migratory divide determines not only the direction of migration but also migration strategy of a social migrant bird
Authors: Piironen Antti , Laaksonen Toni
Published: February 2023

Migratory divides separate populations of migratory animals, facilitating the evolution of intraspecific differences in migration strategies. The optimal migration theory suggests differing migration strategies for birds using different flyways (with different habitats), but the knowledge regarding the impact of the flyway to the individual migration strategies is scarce. We used satellite tracking and neckband resightings to unravel the structure of the migratory divide between two European flyway populations of greylag geeseAnser anser. We modelled satellite tracking data using Gaussian processes to study migration strategies of birds using different flyways. The mean posterior probability for an individual to migrate along the Western Flyway decreased gradually from 0.98 to 0.06 within the Baltic Sea coast, revealing a gradual migratory divide. In addition, migration strategies differed between the flyways. The birds using Western Flyway migrated earlier in autumn, performed longer annual migration and made a clear stopover during migration, whereas the birds using Central Flyway flew directly to their wintering sites. The gradual migratory divide that also divided migration strategies provides exciting insights to ecological and evolutionary factors behind migratory divides. Gaussian processes enabled modelling of detailed migration strategies, encouraging their future usage in movement ecology.
Human immune phenotyping reveals accelerated aging in type 1 diabetes
Authors: Shapiro Melanie R. , Dong Xiaoru , Perry Daniel J. , McNichols James M. , Thirawatananond Puchong , Posgai Amanda L. , Peters Leeana , Motwani Keshav , Musca Richard S. , Muir Andrew , Concannon Patrick , Jacobsen Laura M. , Mathews Clayton E. , Wasserfall Clive H. , Haller Michael J. , Schatz Desmond A. , Atkinson Mark A. , Brusko Maigan A. , Bacher Rhonda L. , Brusko Todd M.
Published: February 2023

The composition of immune cells in peripheral blood is dramatically remodeled throughout the human lifespan, as environmental exposures shape the proportion and phenotype of cellular subsets. These dynamic shifts complicate efforts to identify disease-associated immune signatures in type 1 diabetes (T1D), which is variable in age of onset and rate of β-cell decline. Herein, we conducted standardized flow cytometric immune profiling on peripheral blood from a cross-sectional cohort of T1D participants (n=240), their first-degree relatives (REL,n=310), those at increased risk with two or more islet autoantibodies (RSK,n=24), and autoantibody negative healthy controls (CTR,n=252). We constructed an immune-age predictive model in healthy subjects and developed an interactive data visualization portal (ImmScape;https://ufdiabetes.shinyapps.io/ImmScape/). When applied to the T1D cohort, this model revealed accelerated immune aging (p<0.001) as well as phenotypic signatures of disease after age correction. Of 192 investigated flow cytometry and complete blood count readouts, 46 were significantly associated with age only, 25 with T1D only, and 23 with both age and T1D. Phenotypes associated with T1D after age-correction were predictive of T1D status (AUROC=82.3%). Phenotypes associated with accelerated aging in T1D included increased CXCR3+and PD-1+frequencies in naïve and memory T cell subsets, despite reduced PD-1 expression levels (mean fluorescence intensity) on memory T cells. Additionally, quantitative trait locus analysis linked an increase in HLA-DR expression on monocytes with the T1D-associated HLA-DR4/DQ8 genotype, regardless of clinical group. Our findings demonstrate advanced immune aging in T1D and highlight disease-associated phenotypes for biomarker monitoring and therapeutic interventions.

One Sentence Summary

Peripheral blood characterization reveals accelerated immune-age and age-adjusted proinflammatory immune phenotypes in type 1 diabetes.
Circadian clock genesBmal1andPer2in the nucleus accumbens are negative regulators of alcohol-drinking behavior in mice
Authors: Herrera J. , Button M. , Doherty-Haigh P. , Goldfarb C. , Quteishat N. , Amir S. , Schoettner K.
Published: February 2023

Voluntary alcohol consumption is influenced by a variety of environmental and genetic factors, including circadian clock genes. Even though their sex-specific role in alcohol drinking was identified through selective ablation ofBmal1andPer2from neurons of the mouse striatum, the contribution of specific striatal subregions to the observed drinking behavior remains unclear. Thus, alcohol intake and preference was investigated in male and female mice with a conditional knockout ofBmal1andPer2from cells in the nucleus accumbens (Nac). Mood- and anxiety-related behaviors were assessed prior to alcohol drinking to exclude potential confounding effects of the animal’s behavioral state on alcohol consumption. Alcohol consumption and preference were increased in male and female mice with a conditional knockout ofBmal1, whereas the same effect was only found in males with a deletion ofPer2. Because affective behaviors were only mildly influenced by the conditional gene knockouts, observed alcohol-drinking phenotypes can be directly associated with the Nac-specific clock gene deletion. The results thus suggest an inhibitory role ofBmal1andPer2in the Nac on alcohol consumption in male mice. In females, the inhibitory effect ofBmal1is strictly localized to the Nac, because striatal-wide deletion ofBmal1caused a suppression of alcohol consumption. This sex-dependent stimulatory effect ofBmal1on alcohol drinking is probably mediated through other striatal subregions such as the dorsal striatum.
Idioblasts accumulating anticancer alkaloids inCatharanthus roseusleaves are a unique cell type
Authors: Guedes Joana G. , Ribeiro Rogério , Carqueijeiro Inês , Guimarães Ana Luísa , Bispo Cláudia , Archer John , Azevedo Herlander , Fonseca Nuno A. , Sottomayor Mariana
Published: February 2023

Catharanthus roseusleaves produce a range of monoterpenoid indole alkaloids (MIAs) that include low levels of the anticancer drugs vinblastine and vincristine. The MIA pathway displays a complex architecture spanning different subcellular and cell-type localizations and is under complex regulation. As a result, the development of strategies to increase the levels of the anticancer MIAs has remained elusive. The pathway involves mesophyll specialised idioblasts where the late unsolved biosynthetic steps are thought to occur. Here, protoplasts ofC. roseusleaf idioblasts were isolated by fluorescence-activated cell sorting, and their differential alkaloid and transcriptomic profiles were characterised. This involved the assembly of an improvedC. roseustranscriptome from short- and long-read data, IDIO+. It was observed thatC. roseusmesophyll idioblasts possess a distinctive transcriptomic profile associated with protection against biotic and abiotic stresses, and indicative that this cell type is a carbon sink, in contrast with surrounding mesophyll cells. Moreover, it is shown that idioblasts are a hotspot of alkaloid accumulation, suggesting that their transcriptome may hold the keys to the in-depth understanding of the MIA pathway and the success of strategies leading to higher levels of the anticancer drugs.

Highlight

Catharanthus mesophyll idioblasts are a hotspot of anticancer alkaloid accumulation. The idioblast transcriptome reveals commitment with stress responses and provides a roadmap towards the increase of anticancer alkaloid levels.
Variational Autoencoders for Generating Synthetic Tractography-Based Bundle Templates in a Low-Data Setting
Authors: Feng Yixue , Chandio Bramsh Q. , Thomopoulos Sophia I. , Chattopadhyay Tamoghna , Thompson Paul M.
Published: February 2023

White matter tracts generated from whole brain tractography are often processed using automatic segmentation methods with standard atlases. Atlases are generated from hundreds of subjects, which becomes time-consuming to create and difficult to apply to all populations. In this study, we extended our prior work on using a deep generative model a Convolutional Variational Autoencoder - to map complex and data-intensive streamlines to a low-dimensional latent space given a limited sample size of 50 subjects from the ADNI3 dataset, to generate synthetic population-specific bundle templates using Kernel Density Estimation (KDE) on streamline embeddings. We conducted a quantitative shape analysis by calculating bundle shape metrics, and found that our bundle templates better capture the shape distribution of the bundles than the atlas data used in the original segmentation derived from young healthy adults. We further demonstrated the use of our framework for direct bundle segmentation from whole-brain tractograms.
MeCP2 Represses the Activity of Topoisomerase IIβ in Long Neuronal Genes
Authors: Nettles Sabin A. , Ikeuchi Yoshiho , Agwu Chibueze , Bonni Azad , Gabel Harrison W.
Published: February 2023

A unique signature of neuronal transcriptomes is the high expression of the longest genes in the genome (e.g. >100 kilobases). These genes encode proteins with essential functions in neuronal physiology, and disruption of long gene expression has been implicated in neurological disorders. DNA topoisomerases resolve topological constraints that arise on DNA and facilitate the expression of long genes in neurons. Conversely, methyl-CpG binding protein 2 (MeCP2), which is disrupted in Rett syndrome, can act as a transcriptional repressor to downregulate the expression of long genes. The molecular mechanisms underlying the regulation of long genes by these factors are not fully understood, however, and whether or not they directly influence each other is not known. Here, we identify a functional interaction between MeCP2 and Topoisomerase II-beta (TOP2β) in neurons. We show that MeCP2 and TOP2β physically interactin vivoand map protein sequences sufficient for their physical interactionin vitro. We profile TOP2β activity genome-wide in neurons and detect enrichment at regulatory regions and gene bodies of long neuronal genes, including long genes regulated by MeCP2. Further, we find that knockdown and overexpression of MeCP2 leads to altered TOP2β activity at MeCP2-regulated genes. Our findings uncover a mechanism by which MeCP2 inhibits the activity of TOP2β at long genes in neurons and suggest that this mechanism is disrupted in neurodevelopment disorders caused by mutation of MeCP2.
Local microtubule and F-actin distributions fully determine the spatial geometry ofDrosophilasensory dendritic arbors
Authors: Nanda Sumit , Bhattacharjee Shatabdi , Cox Daniel N. , Ascoli Giorgio A.
Published: February 2023

Dendritic morphology underlies the source and processing of neuronal signal inputs. Morphology can be broadly described by two types of geometric characteristics. The first is dendrogram topology, defined by the length and frequency of the arbor branches; the second is spatial embedding, mainly determined by branch angles and tortuosity. We have previously demonstrated that microtubules and actin filaments are associated with arbor elongation and branching, fully constraining dendrogram topology. Here we relate the local distribution of these two primary cytoskeletal components with dendritic spatial embedding. We first reconstruct and analyze 167 sensory neurons from theDrosophilalarva encompassing multiple cell classes and genotypes. We observe that branches with higher microtubule concentration are overall straighter and tend to deviate less from the direction of their parent branch. F-actin displays a similar effect on the angular deviation from the parent branch direction, but its influence on branch tortuosity varies by class and genotype. We then create a computational model of dendritic morphology purely constrained by the cytoskeletal composition imaged from real neurons. The model quantitatively captures both spatial embedding and dendrogram topology across all tested neuron groups. These results suggest a common developmental mechanism regulating diverse morphologies, where the local cytoskeletal distribution can fully specify the overall emergent geometry of dendritic arbors.
Shortcutting from self-motion signals: quantifying trajectories and active sensing in an open maze
Authors: Xu Jiayun , Girardi-Schappo Mauricio , Beique Jean-Claude , Longtin Andre , Maler Leonard
Published: February 2023

Animals navigate by learning the spatial layout of their environment. We investigated spatial learning of mice in an open maze where food was hidden in one of a hundred holes. Mice leaving from a stable entrance learned to efficiently navigate to the food without the need for landmarks. We develop a quantitative framework to reveal how the mice estimate the food location based on analyses of trajectories and active hole checks. After learning, the computed "target estimation vector" (TEV) closely approximated the mice's trajectory and its hole check distribution. We propose that the TEV can be precisely connected to the properties of hippocampal place cells. Finally, we provide the first demonstration that, after learning the location of two food sites, the mice took a shortcut between the sites, demonstrating that they had generated a cognitive map.
A robust model for cell type-specific interindividual variation in single-cell RNA sequencing data
Authors: Chen Minhui , Dahl Andy
Published: February 2023

The development of single-cell RNA sequencing (scRNA-seq) offers opportunities to characterize cellular heterogeneity at unprecedented resolution. Although scRNA-seq has been widely used to identify and characterize gene expression variation across cell types and cell states based on their average gene expression profiles, most studies ignore variation across individual donors. Modelling this inter-individual variation could improve statistical power to detect cell type-specific biology and inform the genes and cell types that underlying complex traits. We therefore develop a new model to detect and quantify cell type-specific variation across individuals called CTMM (Cell Type-specific linear Mixed Model). CTMM operates on cell type-specific pseudobulk expression and is fit with efficient methods that scale to hundreds of samples. We use extensive simulations to show that CTMM is powerful and unbiased in realistic settings. We also derive calibrated tests for cell type-specific interindividual variation, which is challenging given the modest sample sizes in scRNA-seq data. We apply CTMM to scRNA-seq data from human induced pluripotent stem cells to characterize the transcriptomic variation across donors as cells differentiate into endoderm. We find that almost 100% of transcriptome-wide variability between donors is differentiation stage-specific. CTMM also identifies individual genes with statistically significant stage-specific variability across samples, including 61 genes that do not have significant stage-specific mean expression. Finally, we extend CTMM to partition interindividual covariance between stages, which recapitulates the overall differentiation trajectory. Overall, CTMM is a powerful tool to characterize a novel dimension of cell type-specific biology in scRNA-seq.
Stimulus representations in visual cortex shaped by spatial attention and microsaccades
Authors: Srinivasan Karthik , Lowet Eric , Gomes Bruno , Desimone Robert
Published: February 2023

SUMMARY/ABSTRACT

Microsaccades (MSs) are commonly associated with spatially directed attention, but how they affect visual processing is still not clear. We studied MSs in a task in which the animal was randomly cued to attend to a target stimulus and ignore distractors, and it was rewarded for detecting a color change in the target. We found that the enhancement of firing rates normally found with attention to a cued stimulus was delayed until the first MS directed towards that stimulus. Once that MS occurred, attention to the target was engaged and there were persistent effects of attention on firing rates for the remainder of the trial. These effects were found in the superficial and deep layers of V4 as well as the lateral pulvinar and IT cortex. Although the tuning curves of V4 cells do not change depending on the locus of spatial attention, we found pronounced effects of MS direction on stimulus representations that persisted for the length of the trial in V4. In intervals following a MS towards the target in the RF, stimulus decoding from population activity was substantially better than in intervals following a MS away from the target. Likewise, turning curves of cells were substantially sharper following a MS towards the target in the RF. This sharpening appeared to result from both a “refreshing” of the initial transient sensory response to stimulus onset, and a magnification of the effects of attention in this condition. MSs to the target also enhanced the neuronal response to the behaviorally relevant target color change and led to faster reaction times. These results thus reveal a major link between spatial attention, object processing and its coordination with eye movements.
Leptomeningeal collaterals regulate reperfusion in ischemic stroke
Authors: Binder Nadine Felizitas , Amki Mohamad El , Glück Chaim , Middleham William , Reuss Anna Maria , Bertolo Adrien , Thurner Patrick , Deffieux Thomas , Handelsmann Hannah-Lea , Baumgartner Philipp , Orset Cyrille , Bethge Philipp , Kulcsar Zsolt , Aguzzi Adriano , Tanter Mickael , Vivien Denis , Wyss Matthias T. , Luft Andreas , Weller Michael , Weber Bruno , Wegener Susanne
Published: February 2023

Recanalization is the mainstay of ischemic stroke treatment. However, even with timely clot removal, many stroke patients recover poorly. Leptomeningeal collaterals (LMCs) are pial anastomotic vessels with yet unknown functions. Utilizing a thrombin-based mouse model of stroke and the gold standard fibrinolytic treatment rt-PA, we here show that LMCs play a critical role in preserving vascular function in ischemic territories. We applied laser speckle contrast imaging, ultrafast ultrasound, and two-photon microscopy, to show that after thrombolysis, LMCs allow for gradual reperfusion resulting in small infarcts. On the contrary, in mice with poor LMCs, distal segments of recanalized arteries collapse and deleterious hyperemia causes hemorrhage and mortality. Accordingly, in stroke patients with poor collaterals undergoing thrombectomy, rapid reperfusion resulted in hemorrhagic transformation and unfavorable recovery. Thus, we identify LMCs as key components regulating reperfusion after stroke. Future therapeutic interventions should aim to enhance collateral function, allowing for gradual reperfusion of ischemic tissues after stroke.
Cyclic peptide structure prediction and design using AlphaFold
Authors: Rettie Stephen A. , Campbell Katelyn V. , Bera Asim K. , Kang Alex , Kozlov Simon , De La Cruz Joshmyn , Adebomi Victor , Zhou Guangfeng , DiMaio Frank , Ovchinnikov Sergey , Bhardwaj Gaurav
Published: February 2023

Deep learning networks offer considerable opportunities for accurate structure prediction and design of biomolecules. While cyclic peptides have gained significant traction as a therapeutic modality, developing deep learning methods for designing such peptides has been slow, mostly due to the small number of available structures for molecules in this size range. Here, we report approaches to modify the AlphaFold network for accurate structure prediction and design of cyclic peptides. Our results show this approach can accurately predict the structures of native cyclic peptides from a single sequence, with 36 out of 49 cases predicted with high confidence (pLDDT > 0.85) matching the native structure with root mean squared deviation (RMSD) less than 1.5 Å. Further extending our approach, we describe computational methods for designing sequences of peptide backbones generated by other backbone sampling methods and forde novodesign of new macrocyclic peptides. We extensively sampled the structural diversity of cyclic peptides between 7–13 amino acids, and identified around 10,000 unique design candidates predicted to fold into the designed structures with high confidence. X-ray crystal structures for seven sequences with diverse sizes and structures designed by our approach match very closely with the design models (root mean squared deviation < 1.0 Å), highlighting the atomic level accuracy in our approach. The computational methods and scaffolds developed here provide the basis for custom-designing peptides for targeted therapeutic applications.
Screening in serum-derived medium reveals differential response to compounds targeting metabolism
Authors: Abbott Keene L. , Ali Ahmed , Casalena Dominick , Do Brian T. , Ferreira Raphael , Cheah Jaime H. , Soule Christian K. , Deik Amy , Kunchok Tenzin , Schmidt Daniel R. , Renner Steffen , Honeder Sophie E. , Wu Michelle , Chan Sze Ham , Tseyang Tenzin , Greaves Daniel , Hsu Peggy P. , Ng Christopher W. , Zhang Chelsea J. , Farsidjani Ali , Gramatikov Iva Monique T. , Matheson Nicholas J. , Lewis Caroline A. , Clish Clary B. , Rees Matthew G. , Roth Jennifer A. , Griner Lesley Mathews , Muir Alexander , Auld Douglas S. , Heiden Matthew G. Vander
Published: February 2023

A challenge for screening new candidate drugs to treat cancer is that efficacy in cell culture models is not always predictive of efficacy in patients. One limitation of standard cell culture is a reliance on non-physiological nutrient levels to propagate cells. Which nutrients are available can influence how cancer cells use metabolism to proliferate and impact sensitivity to some drugs, but a general assessment of how physiological nutrients affect cancer cell response to small molecule therapies is lacking. To enable screening of compounds to determine how the nutrient environment impacts drug efficacy, we developed a serum-derived culture medium that supports the proliferation of diverse cancer cell lines and is amenable to high-throughput screening. We used this system to screen several small molecule libraries and found that compounds targeting metabolic enzymes were enriched as having differential efficacy in standard compared to serum-derived medium. We exploited the differences in nutrient levels between each medium to understand why medium conditions affected the response of cells to some compounds, illustrating how this approach can be used to screen potential therapeutics and understand how their efficacy is modified by available nutrients.