bluuebunny/crossref_metadata_2025_split huggingface dataset:
Parkinson’s LRRK2-G2019S risk gene mutation drives sex-specific behavioral and cellular adaptations to chronic variable stress
Authors: Guevara Christopher A. , Alloo Kumayl , Gupta Swati , Thomas Romario , del Valle Pamela , Magee Alexandra R. , Benson Deanna L. , Huntley George W. 
Published: June 2024

AbstractAnxiety is a psychiatric non-motor symptom of Parkinson’s that can appear in the prodromal period, prior to significant loss of brainstem dopamine neurons and motor symptoms. Parkinson’s-related anxiety affects females more than males, despite the greater prevalence of Parkinson’s in males. How stress, anxiety and Parkinson’s are related and the basis for a sex-specific impact of stress in Parkinson’s are not clear. We addressed this using young adult male and female mice carrying a G2019S knockin mutation of leucine-rich repeat kinase 2 (Lrrk2G2019S) andLrrk2WTcontrol mice. In humans,LRRK2G2019Ssignificantly elevates the risk of late-onset Parkinson’s. To assess within-sex differences betweenLrrk2G2019Sand control mice in stress-induced anxiety-like behaviors in young adulthood, we used a within-subject design wherebyLrrk2G2019SandLrrk2WTcontrol mice underwent tests of anxiety-like behaviors before (baseline) and following a 28 day (d) variable stress paradigm. There were no differences in behavioral measures between genotypes in males or females at baseline, indicating that the mutation alone does not produce anxiety-like responses. Following chronic stress, maleLrrk2G2019Smice were affected similarly to male wildtypes except for novelty-suppressed feeding, where stress had no impact onLrrk2G2019Smice while significantly increasing latency to feed inLrrk2WTcontrol mice. FemaleLrrk2G2019Smice were impacted by chronic stress similarly to wildtype females across all behavioral measures. Subsequent post-stress analyses compared cFos immunolabeling-based cellular activity patterns across several stress-relevant brain regions. The density of cFos-activated neurons across brain regions in both male and femaleLrrk2G2019Smice was generally lower compared to stressedLrrk2WTmice, except for the nucleus accumbens of maleLrrk2G2019Smice, where cFos-labeled cell density was significantly higher than all other groups. Together, these data suggest that theLrrk2G2019Smutation differentially impacts anxiety-like behavioral responses to chronic stress in males and females that may reflect sex-specific adaptations observed in circuit activation patterns in stress-related brain regions.
EEG Responses to Upper Limb Pinprick Stimulation in Acute and Early Subacute Motor and Sensorimotor Stroke
Authors: Tedesco Triccas L , Van Hoornweder S , Camilleri TC , Boccuni L , Peeters A , Van Pesch V , Meesen R , Mantini D , Camilleri KP , Verheyden G 
Published: June 2024

AbstractBackgroundElectroencephalography (EEG) during pinprick stimulation has the potential to unveil neural mechanisms underlying sensorimotor impairments post-stroke. This study explored event-related peak pinprick amplitude and oscillatory responses in healthy controls, in people with motor and sensorimotor in acute and early subacute stroke, their relationship and to what extent EEG somatosensory responses can predict sensorimotor impairment.MethodsIn this study, involving 26 individuals, 10 people with a (sub-)acute sensorimotor stroke, 6 people with a (sub)acute motor stroke and 10 age-matched controls, pinpricks were applied to the dorsa of the impaired hand to collect somatosensory evoked potentials. Time(-frequency) analyses of somatosensory evoked potential (SEP) data at electrodes C3 and C4 explored peak pinprick amplitude and oscillatory responses across the three groups. Also, in stroke, (sensori-)motor impairments were assessed at baseline Fugl Meyer Assessment Upper Extremity (FMA-UE) and Erasmus modified Nottingham Sensory Assessment (EmNSA) at baseline and 7 to 14 days later including Fugl Meyer Assessment Upper Extremity (FMA-UE) and Erasmus modified Nottingham Sensory Assessment (EmNSA). Mixed model analyses were used to address objectives.ResultsIt was demonstrated that increased beta desynchronization magnitude correlated with milder motor impairments (R2=0.213), whereas increased beta resynchronization and delta power were associated to milder somatosensory impairment (R2=0.550). At the second session, larger peak-to-peak SEP amplitude and beta band resynchronization at baseline were related to greater improvements in EMNSA and FMA-UE score, respectively, in sensorimotor stroke group.ConclusionsThese findings highlight the potential of EEG combined with somatosensory stimuli to differentiate between sensorimotor and motor impairments in stroke, offering preliminary insights into both diagnostic and prognostic aspects of upper limb recovery.
Control of heat and oxidative stress adaptation by the DJ-1 paralogs inArabidopsis thaliana
Authors: Kataria Priyanka , Pullagurla Naga Jyothi , Laha Debabrata , D’ Silva Patrick 
Published: June 2024

AbstractPlant growth and development are highly regulated processes and are majorly controlled by various environmental factors, whose extreme exposures lead to chronic stress conditions promoting reactive oxygen species (ROS) and carbonyl species (RCS) production. ROS and RCS extensively damage cellular biomolecules and organelles, affecting plant’s viability and development. Emerging reports highlight that the multi-stress responding DJ-1 superfamily proteins are critical in attenuating cytotoxic effects associated with abiotic stress. The current report, validated in yeast and plant models, shows thatAtDJ-1C andAtDJ-1E are robust antioxidants that scavenge ROS and improve survival under oxidative stress. Although they lack conventional glyoxalases and do not attenuate the glycation of proteins,AtDJ-1C andAtDJ-1E preserve the GSH pool and regulate redox homeostasis. Moreover, transcriptome profiling indicates that levels ofAtDJ-1CandAtDJ-1Eare rapidly established to counter heat and oxidative stress conditions. Notably, the knockdown ofAtDJ-1CandAtDJ-1Epromotes detrimental alterations such as reduced chlorophyll retention, impaired root morphogenesis, and induced sensitivity to heat stress due to ROS elevation. Contrastingly, overexpression ofAtDJ-1C andAtDJ-1E improved plant height and rosette formation under physiological conditions. In conclusion, our study unravels the pivotal functions ofArabidopsis thalianaDJ-1C and DJ-1E in governing plant health and survival under heat and oxidative stress conditions.
Whole-genome DNA methylomes of Tree shrew brains reveal conserved and divergent roles of DNA methylation on sex chromosome regulation
Authors: Son Dongmin , Kong Yifan , Tan Yulian , Hu Ting , Shi Lei , Yi Soojin V. 
Published: June 2024

AbstractThe tree shrew (Tupaia belangeri) is a promising emerging model organism in biomedical studies, notably due to their evolutionary proximity to primates. To enhance our understanding of how DNA methylation is implicated in regulation of gene expression and the X chromosome inactivation (XCI) in tree shrew brains, here we present their first genome-wide, single-base-resolution methylomes integrated with transcriptomes from prefrontal cortices. We discovered both divergent and conserved features of tree shrew DNA methylation compared to that of other mammals. DNA methylation levels of promoter and gene body regions are negatively correlated with gene expression, consistent with patterns in other mammalian brains studied. Comparing DNA methylation patterns of the female and male X chromosomes, we observed a clear and significant global reduction (hypomethylation) of DNA methylation across the entire X chromosome in females. Our data suggests that the female X hypomethylation does not directly contribute to the gene silencing of the inactivated X chromosome nor does it significantly drive sex-specific gene expression of tree shrews. However, we identified a putative regulatory region in the 5’ end of the X inactive specific transcript (Xist)gene, a key gene for XCI, whose pattern of differential DNA methylation strongly relate to its differential expression between male and female tree shrews. We show that differential methylation of this region is conserved across different species. Moreover, we provide evidence suggesting that the observed difference between human and tree shrew X-linked promoter methylation is associated with the difference in genomic CpG contents. Our study offers novel information on genomic DNA methylation of tree shrews, as well as insights into the evolution of X chromosome regulation in mammals.
A Hybrid Simulation Model of HIV Program Interventions: From Transmission Behavior to Macroeconomic Impacts
Authors: Crown William , Britton Erin , Razavi Moaven , Luan Yiqun , Veerunaidu Senthil , Kates Jennifer , Gaumer Gary , Jordan Monica , Hurley Clare L. , Nandakumar A.K. 
Published: June 2024

AbstractWhile several studies have examined the public health effects of HIV investments, there is a smaller literature that examines the macroeconomic impacts of such investments. The most recent efforts have utilized econometric analyses of country-level panel data, as well as demographic simulations of HIV spending. However, there are no studies that examine the linkages between the behavioral responses to public health investments, demographic changes, and, ultimately, macroeconomic performance. This study demonstrates the feasibility of such a linkage. We develop an agent-based simulation model (ABM) of a Peer Navigator Program to support engagement in HIV therapy in Tanzania. Results from the ABM are weighted to reflect the Tanzania population and fed into the SPECTRUM model. This generates detailed demographic forecasts that are translated into macroeconomic impacts using labor force participation rates from the International Labor Organization, along with an econometric model of gross domestic product (GDP). Although the simulated effects of the Peer Navigator Program in Tanzania are small, the paper demonstrates the feasibility of linking behavioral ABM simulations of program impacts to subsequent demographic effects and, finally, macroeconomic performance.
Principal component analysis revisited: fast multi-trait genetic evaluations with smooth convergence
Authors: Ahlinder Jon , Hall David , Suontama Mari , Sillanpää Mikko J 
Published: June 2024

AbstractA cornerstone in breeding and population genetics is the genetic evaluation procedure, needed to make important decisions on population management. Multivariate mixed model analysis, in which many traits is considered jointly, utilizes genetic and environmental correlations between traits to improve the accuracy. However, the number of parameters in the multi-trait model grows exponentially with the number of traits which reduces its scalability. Here, we suggest using principal component analysis (PCA) to reduce the dimensions of the response variables, and then using the computed principal components (PC) as separate responses in the genetic evaluation analysis. As PCs are orthogonal to each other, multivariate analysis is no longer needed and separate univariate analyses can be performed instead. We compared the approach to traditional multivariate analysis in terms of computational requirement and rank lists according to predicted genetic merit on two forest tree datasets with 22 and 27 measured traits respectively. Obtained rank lists of the top 50 individuals were in good agreement.Interestingly, the required computational time of the approach only took a few seconds without convergence issues, unlike the traditional approach which required considerably more time to run (seven and ten hours respectively). Our approach can easily handle missing data and can be used with all available linear mixed models software as it does not require any specific implementation. The approach can help to mitigate difficulties with multi-trait genetic analysis in both breeding and wild populations.
Transcranial Brain Atlas Based on Photon Measurement Density Function in a Triple-Parameter Standard Channel Space
Authors: Wei Lijiang , Zhao Yang , Liu Farui , Chen Yuanyuan , Xu Yilong , Li Zheng , Zhu Chaozhe 
Published: June 2024

AbstractFunctional near-infrared spectroscopy (fNIRS) is a widely used transcranial brain imaging technique in neuroscience research. Nevertheless, its lack of anatomical information poses challenges for designing appropriate optode montage and localizing fNIRS signals to underlying anatomical regions. The photon measurement density function (PMDF) is often employed to address these issues, as it accurately measures the sensitivity of a fNIRS signal channel to perturbations of absorption coefficients at any brain locations. However, existing PMDF-based localization methods have two limitations: a limited channel space, and PMDF estimation based on single standard head models, which differ anatomically from individual subjects. To overcome these limitations, this study proposes a continuous fNIRS standard channel space and constructs a PMDF-based transcranial brain atlas (PMDF-TBA) by calculating PMDFs based on MRI images of 48 adults. PMDF-TBA contains group-averaged sensitivities of channels to gray matter and brain regions of atlases, such as Brodmann, AAL2, and LPBA40. Through leave-one-out cross-validation, we evaluated the prediction ability of PMDF-TBA for sensitivity of unseen individuals and found that it outperformed PMDFs based on single standard head models. Thus, PMDF-TBA serves as a more generalizable fNIRS spatial localization tool. Therefore, PMDF-TBA can be utilized to optimize optode montage design, improve channel sensitivity to target brain regions, and assist in the source localization of fNIRS data, thereby promoting the application of fNIRS in neuroscience research.
Critical assessment of missense variant effect predictors on disease-relevant variant data
Authors: Rastogi Ruchir , Chung Ryan , Li Sindy , Li Chang , Lee Kyoungyeul , Woo Junwoo , Kim Dong-Wook , Keum Changwon , Babbi Giulia , Martelli Pier Luigi , Savojardo Castrense , Casadio Rita , Chennen Kirsley , Weber Thomas , Poch Olivier , Ancien François , Cia Gabriel , Pucci Fabrizio , Raimondi Daniele , Vranken Wim , Rooman Marianne , Marquet Céline , Olenyi Tobias , Rost Burkhard , Andreoletti Gaia , Kamandula Akash , Peng Yisu , Bakolitsa Constantina , Mort Matthew , Cooper David N. , Bergquist Timothy , Pejaver Vikas , Liu Xiaoming , Radivojac Predrag , Brenner Steven E. , Ioannidis Nilah M. 
Published: June 2024

AbstractRegular, systematic, and independent assessment of computational tools used to predict the pathogenicity of missense variants is necessary to evaluate their clinical and research utility and suggest directions for future improvement. Here, as part of the sixth edition of the Critical Assessment of Genome Interpretation (CAGI) challenge, we assess missense variant effect predictors (or variant impact predictors) on an evaluation dataset of rare missense variants from disease-relevant databases. Our assessment evaluates predictors submitted to the CAGI6 Annotate-All-Missense challenge, predictors commonly used by the clinical genetics community, and recently developed deep learning methods for variant effect prediction. To explore a variety of settings that are relevant for different clinical and research applications, we assess performance within different subsets of the evaluation data and within high-specificity and high-sensitivity regimes. We find strong performance of many predictors across multiple settings. Meta-predictors tend to outperform their constituent individual predictors; however, several individual predictors have performance similar to that of commonly used meta-predictors. The relative performance of predictors differs in high-specificity and high-sensitivity regimes, suggesting that different methods may be best suited to different use cases. We also characterize two potential sources of bias. Predictors that incorporate allele frequency as a predictive feature tend to have reduced performance when distinguishing pathogenic variants from very rare benign variants, and predictors supervised on pathogenicity labels from curated variant databases often learn label imbalances within genes. Overall, we find notable advances over the oldest and most cited missense variant effect predictors and continued improvements among the most recently developed tools, and the CAGI Annotate-All-Missense challenge (also termed the Missense Marathon) will continue to assess state-of-the-art methods as the field progresses. Together, our results help illuminate the current clinical and research utility of missense variant effect predictors and identify potential areas for future development.
Serosurveillance of dengue infection and correlation with mosquito pools for dengue virus positivity during the COVID-19 pandemic in Tamil Nadu, India – A state-wide cross-sectional cluster randomized community-based study
Authors: Selvavinayagam Sivaprakasam T. , Sankar Sathish , Yong Yean K. , Anshad Abdul R. , Chandramathi Samudi , Somasundaram Anavarathan , Palani Sampath , Kumarasamy Parthipan , Azhaguvel Roshini , Kumar Ajith B. , Subramaniam Sudharshini , Malathi Manickam , Vijayalakshmi Venkatachalam , Rajeshkumar Manivannan , Kumaresan Anandhazhvar , Pandey Ramendra P. , Muruganandam Nagarajan , Gopalan Natarajan , Kannan Meganathan , Murugesan Amudhan , Balakrishnan Pachamuthu , Byrareddy Siddappa N. , Dash Aditya P. , Larsson Marie , Velu Vijayakumar , Shankar Esaki M. , Raju Sivadoss 
Published: June 2024

SummaryBackgroundDengue is a vector-borne viral disease impacting millions across the globe. Nevertheless, akin to many other diseases, reports indicated a decline in dengue incidence and seroprevalence during the COVID-19 pandemic (2020-22). This presumably could be attributed to reduced treatment-seeking rates, under-reporting, misdiagnosis, disrupted health services and reduced exposure to vectors due to lockdowns. Scientific evidence on dengue virus (DENV) disease during the COVID-19 pandemic is limited globally.MethodsA cross-sectional, randomized cluster sampling community-based survey was carried out to assess anti-dengue IgM and IgG and SARS-CoV-2 IgG seroprevalence across all 38 districts of Tamil Nadu, India. The prevalence of DENV in the Aedes mosquito pools during 2021 was analyzed and compared with previous and following years of vector surveillance for DENV by real-time PCR.FindingsResults implicate that both DENV-IgM and IgG seroprevalence and mosquito viral positivity were reduced across all the districts. A total of 13464 mosquito pools and 5577 human serum samples from 186 clusters were collected. Of these, 3·76% of mosquito pools were positive for DENV. In the human sera, 4·12% were positive for DENV IgM and 6·4% were positive for DENV IgG. The anti-SARS-CoV-2 antibody titres correlated with dengue seropositivity with a significant association whereas vaccination status significantly correlated with dengue IgM levels.InterpretationContinuous monitoring of DENV seroprevalence, especially with the evolving variants of the SARS-CoV-2 virus and surge in COVID-19 cases will shed light on the transmission and therapeutic attributes of dengue infection.
Evidence for Behavioral Autorepression in Covid-19 Epidemiological Dynamics
Authors: Lewis Daniel D. , Pablo Michael , Chen Xinyue , Simpson Michael L. , Weinberger Leor 
Published: June 2024

AbstractIt has long been hypothesized that behavioral reactions to epidemic severity autoregulate infection dynamics, for example when susceptible individuals self-sequester based on perceived levels of circulating disease. However, evidence for such ‘behavioral autorepression’ has remained elusive, and its presence could significantly affect epidemic forecasting and interventions. Here, we analyzed early COVID-19 dynamics at 708 locations over three epidemiological scales (96 countries, 50 US states, and 562 US counties). Signatures of behavioral autorepression were identified through: (i) a counterintuitive mobility-death correlation, (ii) fluctuation-magnitude analysis, and (iii) dynamics of SARS-CoV-2 infection waves. These data enabled calculation of the average behavioral-autorepression strength (i.e., negative feedback ‘gain’) across different populations. Surprisingly, incorporating behavioral autorepression into conventional models was required to accurately forecast COVID-19 mortality. Models also predicted that the strength of behavioral autorepression has the potential to alter the efficacy of non-pharmaceutical interventions. Overall, these results provide evidence for the long-hypothesized existence of behavioral autorepression, which could improve epidemic forecasting and enable more effective application of non-pharmaceutical interventions during future epidemics.SignificanceChallenges with epidemiological forecasting during the COVID-19 pandemic suggested gaps in underlying model architecture. One long-held hypothesis, typically omitted from conventional models due to lack of empirical evidence, is that human behaviors lead to intrinsic negative autoregulation of epidemics (termed ‘behavioral autorepression’). This omission substantially alters model forecasts. Here, we provide independent lines of evidence for behavioral autorepression during the COVID-19 pandemic, demonstrate that it is sufficient to explain counterintuitive data on ‘shutdowns’, and provides a mechanistic explanation of why early shutdowns were more effective than delayed, high-intensity shutdowns. We empirically measure autorepression strength, and show that incorporating autorepression dramatically improves epidemiological forecasting. The autorepression phenomenon suggests that tailoring interventions to specific populations may be warranted.
Sex differences in donor T cell targeting of host splenocyte subpopulations in acute and chronic murine graft-vs.-host disease: implications for lupus-like autoimmunity
Authors: Soloviova Kateryna , Via Charles S. 
Published: June 2024

AbstractThis study sought to compare in vivo sex differences in either a Th1-dominant CTL response or a Tfh-mediated lupus-like antibody response using the parent-into F1 murine model of acute or chronic GVHD respectively. In acute GVHD we observed no significant sex differences in the hierarchy of donor CD8 CTL elimination of splenocyte subsets. B cells were the most sensitive to elimination in both sexes; however, the male response was significantly stronger. Sex differences in chronic GVHD were more widespread; females exhibited significantly greater numbers of total splenocytes and host CD4 Tfh cells, B cells and CD8 T cells consistent with reports of greater female autoantibody production in this model. The more potent male CTL response in acute GVHD conflicts with reports of greater female CTL responses following infections or vaccines and may reflect the absence of exogenous innate immune stimuli in this model.