bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cortical connectomic mediations on gamma band synchronization in schizophrenia
Authors: Du Xiaoming , Hare Stephanie , Summerfelt Ann , Adhikari Bhim M. , Garcia Laura , Marshall Wyatt , Zan Peng , Kvarta Mark , Goldwaser Eric , Bruce Heather , Gao Si , Sampath Hemalatha , Kochunov Peter , Simon Jonathan Z. , Hong L. Elliot 
Published: January 2023

AbstractAberrant gamma frequency neural oscillations in schizophrenia have been well demonstrated using auditory steady-state responses (ASSR). However, the neural circuits underlying 40 Hz ASSR deficits in schizophrenia remain poorly understood. Sixty-six patients with schizophrenia spectrum disorders and 85 age- and gender-matched healthy controls completed one electroencephalography session measuring 40 Hz ASSR and one imaging session for resting-state functional connectivity (rsFC) assessments. The associations between the normalized power of 40 Hz ASSR and rsFC were assessed via linear regression and mediation models. We found that rsFC among auditory, precentral, postcentral, and prefrontal cortices were positively associated with 40 Hz ASSR in patients and controls separately and in the combined sample. The mediation analysis further confirmed that the deficit of gamma band ASSR in schizophrenia was nearly fully mediated by three of the rsFC circuits between right superior temporal gyrus—left medial prefrontal cortex (MPFC), left MPFC—left postcentral gyrus (PoG), and left precentral gyrus—right PoG. Gamma-band ASSR deficits in schizophrenia may be associated with deficient circuitry level connectivity to support gamma frequency synchronization. Correcting gamma band deficits in schizophrenia may require corrective interventions to normalize these aberrant networks.
A comprehensive investigation into the genetic relationship between music engagement and mental health
Authors: Wesseldijk Laura W. , Lu Yi , Karlsson Robert , Ullén Fredrik , Mosing Miriam A. 
Published: January 2023

AbstractWhile music engagement is often regarded as beneficial for mental health, some studies report higher risk for depression and anxiety among musicians. This study investigates whether shared underlying genetic influences (genetic pleiotropy) or gene-environment interaction could be at play in the music-mental health association using measured genotypes. In 5,648 Swedish twins with information on music and sport engagement, creative achievements, self-reported mental health and psychiatric diagnoses based on nationwide patient registries, we derived polygenic scores for major depression, bipolar disorder, schizophrenia, neuroticism, sensitivity to environmental stress, depressive symptoms and general musicality. In line with phenotypic associations, individuals with higher polygenic scores for major depression and bipolar disorder were more likely to play music, practice more music and reach higher levels of general artistic achievements, while a higher genetic propensity for general musicality was marginally associated with a higher risk for a depression diagnosis. Importantly, polygenic scores for major depression and bipolar remained associated with music engagement when excluding individuals who experienced psychiatric symptoms, just as a genetic propensity for general musicality predicted a depression diagnosis regardless of whether and how much individuals played music. In addition, we found no evidence for gene-environment interaction: the phenotypic association between music engagement and mental health outcomes did not differ for individuals with different genetic vulnerability for mental health problems. Altogether, our findings suggest that mental health problems observed in musically active individuals are partly explained by a pre-existing genetic risk for depression and bipolar disorder and likely reflect horizontal pleiotropy (when one gene influences multiple traits), rather than causal influences of mental health on music engagement, or vice versa (referred to as vertical pleiotropy).
Physical exercise mediates a cortical FMRP–mTOR pathway to improve resilience against chronic stress in adolescent mice
Authors: Yan Lan , Wang Mei , Yang Fengzhen , Wang Yajie , Wang Siqi , So Kwok-Fai , Zhang Li 
Published: January 2023

AbstractAerobic exercise effectively relieves anxiety disorders via modulating neurogenesis and neural activity. The molecular mechanism of exercise-mediated anxiolysis, however, remains incomplete. On a chronic restrain stress (CRS) model in adolescent mice, we showed that 14-day treadmill exercise profoundly maintained normal neural activity and axonal myelination in the medial prefrontal cortex (mPFC), in association with the prevention of anxiety-like behaviors. Further interrogation of molecular mechanisms revealed the activation of the mechanistic target of the rapamycin (mTOR) pathway within mPFC under exercise training. At the upstream of mTOR, exercise-mediated brain RNA methylation inhibited the expression of Fragile X mental retardation protein (FMRP) to activate the mTOR pathway. In summary, treadmill exercise modulates an FMRP–mTOR pathway to maintain cortical neural activity and axonal myelination, contributing to improved stress resilience. These results extended our understanding of the molecular substrate of exercise-mediated anxiolytic effect during adolescent period.
Trends in incident diagnoses and drug prescriptions for anxiety and depression during the COVID-19 pandemic: an 18-month follow-up study based on the UK Biobank
Authors: Wang Yue , Ge Fenfen , Wang Junren , Yang Huazhen , Han Xin , Ying Zhiye , Hu Yao , Sun Yajing , Qu Yuanyuan , Aspelund Thor , Hauksdóttir Arna , Zoega Helga , Fang Fang , Valdimarsdóttir Unnur A. , Song Huan 
Published: January 2023

AbstractSerious concerns have been raised about the negative effects of the COVID-19 pandemic on population psychological well-being. However, limited data exist on the long-term effects of the pandemic on incident psychiatric morbidities among individuals with varying exposure to the pandemic. Leveraging prospective data from the community-based UK Biobank cohort, we included 308,400 participants free of diagnosis of anxiety or depression, as well as 213,757 participants free of anxiolytics or antidepressants prescriptions, to explore the trends in incident diagnoses and drug prescriptions for anxiety and depression from 16 March 2020 to 31 August 2021, compared to the pre-pandemic period (i.e., 1 January 2017 to 31 December 2019) and across populations with different exposure statuses (i.e., not tested for COVID-19, tested negative and tested positive). The age- and sex-standardized incidence ratios (SIRs) were calculated by month which indicated an increase in incident diagnoses of anxiety or depression among individuals who were tested for COVID-19 (tested negative: SIR 3.05 [95% confidence interval 2.88–3.22]; tested positive: 2.03 [1.76–2.34]), especially during the first six months of the pandemic (i.e., March-September 2020). Similar increases were also observed for incident prescriptions of anxiolytics or antidepressants (tested negative: 1.56 [1.47–1.67]; tested positive: 1.41 [1.22–1.62]). In contrast, individuals not tested for COVID-19 had consistently lower incidence rates of both diagnoses of anxiety or depression (0.70 [0.67–0.72]) and prescriptions of respective psychotropic medications (0.70 [0.68–0.72]) during the pandemic period. These data suggest a distinct rise in health care needs for anxiety and depression among individuals tested for COVID-19, regardless of the test result, in contrast to a reduction in health care consumption for these disorders among individuals not tested for and, presumably, not directly exposed to the disease.
Epigenetics of traumatic stress: The association of NR3C1 methylation and posttraumatic stress disorder symptom changes in response to narrative exposure therapy
Authors: Wilker Sarah , Vukojevic Vanja , Schneider Anna , Pfeiffer Anett , Inerle Stefan , Pauly Markus , Elbert Thomas , Papassotiropoulos Andreas , de Quervain Dominique , Kolassa Iris-Tatjana 
Published: January 2023

AbstractEpigenetic processes allow plasticity in gene regulation in response to significant environmental events. Accumulating evidence suggests that effective psychotherapy is accompanied by epigenetic changes, rendering DNA methylation a potential biomarker of therapy success. Due to the central role of glucocorticoid dynamics in stress regulation and the alteration of aversive memories, glucocorticoid receptors are likely involved in the molecular processes that are required to successfully treat Posttraumatic Stress Disorder (PTSD). This study aimed to investigate the relationship between methylation at the glucocorticoid receptor gene (NR3C1) and PTSD treatment success of evidence-based psychotherapy. A sample of N = 153 conflict survivors from Northern Uganda (98 females and 55 males) with PTSD were treated with Narrative Exposure Therapy (NET). Diagnostic interviews and saliva sampling took place at pretreatment and 4 and 10 months after treatment completion. We investigated potential associations between PTSD symptom development and methylation changes at 38 CpG sites spanning NR3C1 over the three times of measurement using the repeated measures correlation. After accounting for multiple comparisons, DNA methylation at CpG site cg25535999 remained negatively associated with PTSD symptoms. These results were followed up by mixed models as well as structural equation modelling. These analyses revealed that treatment responders had a significant cg25535999 methylation increase after treatment with NET. Furthermore, lower methylation at cg25535999 pretreatment predicted a higher symptom improvement. Our results suggest different epigenetic profile dynamics at NR3C1 cg25535999 in therapy responders compared to non-responders and underscore the central role of glucocorticoid signaling in trauma-focused therapy.
Engineered live bacteria suppress Pseudomonas aeruginosa infection in mouse lung and dissolve endotracheal-tube biofilms
Authors: Mazzolini Rocco , Rodríguez-Arce Irene , Fernández-Barat Laia , Piñero-Lambea Carlos , Garrido Victoria , Rebollada-Merino Agustín , Motos Anna , Torres Antoni , Grilló Maria Jesús , Serrano Luis , Lluch-Senar Maria 
Published: January 2023

AbstractEngineered live bacteria could provide a new modality for treating lung infections, a major cause of mortality worldwide. In the present study, we engineered a genome-reduced human lung bacterium, Mycoplasma pneumoniae, to treat ventilator-associated pneumonia, a disease with high hospital mortality when associated with Pseudomonas aeruginosa biofilms. After validating the biosafety of an attenuated M. pneumoniae chassis in mice, we introduced four transgenes into the chromosome by transposition to implement bactericidal and biofilm degradation activities. We show that this engineered strain has high efficacy against an acute P. aeruginosa lung infection in a mouse model. In addition, we demonstrated that the engineered strain could dissolve biofilms formed in endotracheal tubes of patients with ventilator-associated pneumonia and be combined with antibiotics targeting the peptidoglycan layer to increase efficacy against Gram-positive and Gram-negative bacteria. We expect our M. pneumoniae-engineered strain to be able to treat biofilm-associated infections in the respiratory tract.
Genome-wide RNA polymerase stalling shapes the transcriptome during aging
Authors: Gyenis Akos , Chang Jiang , Demmers Joris J. P. G. , Bruens Serena T. , Barnhoorn Sander , Brandt Renata M. C. , Baar Marjolein P. , Raseta Marko , Derks Kasper W. J. , Hoeijmakers Jan H. J. , Pothof Joris 
Published: January 2023

AbstractGene expression profiling has identified numerous processes altered in aging, but how these changes arise is largely unknown. Here we combined nascent RNA sequencing and RNA polymerase II chromatin immunoprecipitation followed by sequencing to elucidate the underlying mechanisms triggering gene expression changes in wild-type aged mice. We found that in 2-year-old liver, 40% of elongating RNA polymerases are stalled, lowering productive transcription and skewing transcriptional output in a gene-length-dependent fashion. We demonstrate that this transcriptional stress is caused by endogenous DNA damage and explains the majority of gene expression changes in aging in most mainly postmitotic organs, specifically affecting aging hallmark pathways such as nutrient sensing, autophagy, proteostasis, energy metabolism, immune function and cellular stress resilience. Age-related transcriptional stress is evolutionary conserved from nematodes to humans. Thus, accumulation of stochastic endogenous DNA damage during aging deteriorates basal transcription, which establishes the age-related transcriptome and causes dysfunction of key aging hallmark pathways, disclosing how DNA damage functionally underlies major aspects of normal aging.
Notch1 mutations drive clonal expansion in normal esophageal epithelium but impair tumor growth
Authors: Abby Emilie , Dentro Stefan C. , Hall Michael W. J. , Fowler Joanna C. , Ong Swee Hoe , Sood Roshan , Herms Albert , Piedrafita Gabriel , Abnizova Irina , Siebel Christian W. , Gerstung Moritz , Hall Benjamin A. , Jones Philip H. 
Published: January 2023

AbstractNOTCH1 mutant clones occupy the majority of normal human esophagus by middle age but are comparatively rare in esophageal cancers, suggesting NOTCH1 mutations drive clonal expansion but impede carcinogenesis. Here we test this hypothesis. Sequencing NOTCH1 mutant clones in aging human esophagus reveals frequent biallelic mutations that block NOTCH1 signaling. In mouse esophagus, heterozygous Notch1 mutation confers a competitive advantage over wild-type cells, an effect enhanced by loss of the second allele. Widespread Notch1 loss alters transcription but has minimal effects on the epithelial structure and cell dynamics. In a carcinogenesis model, Notch1 mutations were less prevalent in tumors than normal epithelium. Deletion of Notch1 reduced tumor growth, an effect recapitulated by anti-NOTCH1 antibody treatment. Notch1 null tumors showed reduced proliferation. We conclude that Notch1 mutations in normal epithelium are beneficial as wild-type Notch1 favors tumor expansion. NOTCH1 blockade may have therapeutic potential in preventing esophageal squamous cancer.
Wearable full-body motion tracking of activities of daily living predicts disease trajectory in Duchenne muscular dystrophy
Authors: Ricotti Valeria , Kadirvelu Balasundaram , Selby Victoria , Festenstein Richard , Mercuri Eugenio , Voit Thomas , Faisal A. Aldo 
Published: January 2023

AbstractArtificial intelligence has the potential to revolutionize healthcare, yet clinical trials in neurological diseases continue to rely on subjective, semiquantitative and motivation-dependent endpoints for drug development. To overcome this limitation, we collected a digital readout of whole-body movement behavior of patients with Duchenne muscular dystrophy (DMD) (n = 21) and age-matched controls (n = 17). Movement behavior was assessed while the participant engaged in everyday activities using a 17-sensor bodysuit during three clinical visits over the course of 12 months. We first defined new movement behavioral fingerprints capable of distinguishing DMD from controls. Then, we used machine learning algorithms that combined the behavioral fingerprints to make cross-sectional and longitudinal disease course predictions, which outperformed predictions derived from currently used clinical assessments. Finally, using Bayesian optimization, we constructed a behavioral biomarker, termed the KineDMD ethomic biomarker, which is derived from daily-life behavioral data and whose value progresses with age in an S-shaped sigmoid curve form. The biomarker developed in this study, derived from digital readouts of daily-life movement behavior, can predict disease progression in patients with muscular dystrophy and can potentially track the response to therapy.
HyU: Hybrid Unmixing for longitudinal in vivo imaging of low signal-to-noise fluorescence
Authors: Chiang Hsiao Ju , Koo Daniel E. S. , Kitano Masahiro , Burkitt Sean , Unruh Jay R. , Zavaleta Cristina , Trinh Le A. , Fraser Scott E. , Cutrale Francesco 
Published: January 2023

AbstractThe expansion of fluorescence bioimaging toward more complex systems and geometries requires analytical tools capable of spanning widely varying timescales and length scales, cleanly separating multiple fluorescent labels and distinguishing these labels from background autofluorescence. Here we meet these challenging objectives for multispectral fluorescence microscopy, combining hyperspectral phasors and linear unmixing to create Hybrid Unmixing (HyU). HyU is efficient and robust, capable of quantitative signal separation even at low illumination levels. In dynamic imaging of developing zebrafish embryos and in mouse tissue, HyU was able to cleanly and efficiently unmix multiple fluorescent labels, even in demanding volumetric timelapse imaging settings. HyU permits high dynamic range imaging, allowing simultaneous imaging of bright exogenous labels and dim endogenous labels. This enables coincident studies of tagged components, cellular behaviors and cellular metabolism within the same specimen, providing more accurate insights into the orchestrated complexity of biological systems.
Dataset for Fracture and Impact Toughness of High-Entropy Alloys
Authors: Fan Xuesong , Chen Shiyi , Steingrimsson Baldur , Xiong Qingang , Li Weidong , Liaw Peter K. 
Published: January 2023

AbstractFracture dictates the service limits of metallic structures. Damage tolerance of materials may be characterized by fracture toughness rigorously developed from fracture mechanics, or less rigorous yet more easily obtained impact toughness (or impact energy as a variant). Given the promise of high-entropy alloys (HEAs) in structural and damage-tolerance applications, we compiled a dataset of fracture toughness and impact toughness/energy from the literature till the end of the 2022 calendar year. The dataset is subdivided into three categories, i.e., fracture toughness, impact toughness, and impact energy, which contain 153, 14, and 78 distinct data records, respectively. On top of the alloy chemistry and measured fracture quantities, each data record also documents the factors influential to fracture. Examples are material-processing history, phase structures, grain sizes, uniaxial tensile properties, such as yield strength and elongation, and testing conditions. Data records with comparable conditions are graphically visualized by plots. The dataset is hosted in Materials Cloud, an open data repository.
The global historical climate database HCLIM
Authors: Lundstad Elin , Brugnara Yuri , Pappert Duncan , Kopp Jérôme , Samakinwa Eric , Hürzeler André , Andersson Axel , Chimani Barbara , Cornes Richard , Demarée Gaston , Filipiak Janusz , Gates Lydia , Ives Gemma L. , Jones Julie M. , Jourdain Sylvie , Kiss Andrea , Nicholson Sharon E. , Przybylak Rajmund , Jones Philip , Rousseau Daniel , Tinz Birger , Rodrigo Fernando S. , Grab Stefan , Domínguez-Castro Fernando , Slonosky Victoria , Cooper Jason , Brunet Manola , Brönnimann Stefan 
Published: January 2023

AbstractThere is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate dataset for the preindustrial period so far.
Com probe implemented STexS II greatly enhances specificity in SARS-CoV-2 variant detection
Authors: Kim Jae Jong , Park Hyoung-Min , Kyoung A. Young , Lim Si-Kyu , Cha Sun Ho , Lee J. Eugene , Park Byoung Chul 
Published: January 2023

AbstractThe initial introduction of utilizing double helix structural oligonucleotides known as SNP typing with excellent specificity (STexS) in a standard PCR greatly improved the detection of single nucleotide polymorphisms (SNP) by enhancing amplification rates of primer-matching strands and interrupting mismatched strands by constant instability of kinetics regarding alignment attaching and detaching. The model was beneficial overall in detecting SNP variants consisting of large amounts of wildtype strands such as EGFR mutation genotyping for early detection of non-small cell lung cancer. While the STexS PCR is advantageous in detecting SNPs and biomarkers, limitations were yet observed. Despite the ability to detect variants 10 times more effective than a typical amplification-refractory mutation system PCR, it could only perform optimally in DNA concentrations around 101 ~ 105. To further enhance STexS specificity to perform detecting viral-RNA variants such as the infamous SARS-CoV-2, a novel improvement of the regular TaqMan Probe using Com-probes to inhibit high copy wild targets and amplify low copy mutant targets. By introducing the novel STexS II, omicron variants of SARS-CoV-2 were able to be successfully detected in high concentrations of normal genes.
Meshless optical mode solving using scalable deep deconvolutional neural network
Authors: Alagappan G. , Png C. E. 
Published: January 2023

AbstractOptical mode solving is of paramount importance in photonic design and discovery. In this paper we propose a deep deconvolutional neural network architecture for a meshless, and resolution scalable optical mode calculations. The solution is arbitrary in wavelengths and applicable for a wide range of photonic materials and dimensions. The deconvolutional model consists of two stages: the first stage projects the photonic geometrical parameters to a vector in a higher dimensional space, and the second stage deconvolves the vector into a mode image with the help of scaling blocks. Scaling block can be added or subtracted as per desired resolution in the final mode image, and it can be effectively trained using a transfer learning approach. Being a deep learning model, it is light, portable, and capable of rapidly disseminating edge computing ready solutions. Without the loss of generality, we illustrate the method for an optical channel waveguide, and readily generalizable for wide range photonic components including photonic crystals, optical cavities and metasurfaces.